Forest Diversity and Management (Topics in Biodiversity and Conservation)

Forest Diversity and Management

TOPICS IN BIODIVERSITY AND CONSERVATION Volume 2

The titles published in this series are listed at the end of this volume.

Forest Diversity and Management

Edited by

David L. Hawksworth and Alan T. Bull

Reprinted from Biodiversity and Conservation, volume 15:4 (2006)

123

A C.I.P. Catalogue record for this book is available from the library of Congress.

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Contents

Forest Diversity and Management Introduction

1

D. CLOSSET-KOPP, A. SCHNITZLER and D. ARAN / Dynamics in natural mixed-beech forest of the Upper Vosges

3–33

OSWALDO TÉLLEZ-VALDÉS, PATRICIA DÁVILA-ARANDA and RAFAEL LIRA-SAADE / The effects of climate change on the long-term conservation of Fagus grandifolia var. mexicana, an important species of the Cloud Forest in Eastern Mexico

35–47

OLIVARIMBOLA ANDRIANOELINA, HERY RAKOTONDRAOELINA, LOLONA RAMAMONJISOA, JEAN MALEY, PASCAL DANTHU and JEAN-MARC BOUVET / Genetic diversity of Dalbergia monticola (Fabaceae) an endangered tree species in the fragmented oriental forest of Madagascar

49–68

HÉLÈNE GONARD, FRANÇOIS ROMANE, IGNACIO SANTA REGINA and SALVATORE LEONARDI / Forest management and plant species diversity in chestnut stands of three Mediterranean areas

69–82

FRIEDRICH PATRICK GRAZ / Spatial diversity of dry savanna woodlands Assessing the spatial diversity of a dry savanna woodland stand in northern Namibia using neighbourhood-based measures

83–97

BÄRBEL BLEHER, DANA USTER and THOMAS BERGSDORF / Assessment of threat status and management effectiveness in Kakamega Forest, Kenya

99–117

MASASHI OHSAWA and TAKUO NAGAIKE / Influence of forest types and effects of forestry activities on species richness and composition of Chrysomelidae in the central mountainous region of Japan

119–131

ANDREAS HEMP / The banana forests of Kilimanjaro: biodiversity and conservation of the Chagga homegardens

133–157

M.G.P. TCHOUTO, M. YEMEFACK, W.F. DE BOER, J.J.F.E. DE WILDE, L.J.G. VAN DER MAESEN and A.M. CLEEF / Biodiversity hotspots and conservation priorities in the Campo-Ma‘an rain forests, Cameroon

159–192

R. KINDT, P. VAN DAMME and A.J. SIMONS / Tree diversity in western Kenya: using profiles to characterise richness and evenness

193–210

GERHARD LANGENBERGER, KONRAD MARTIN and JOACHIM SAUERBORN / Vascular plant species inventory of a Philippine lowland rain forest and its conservation value

211–241

WEIBANG SUN, YUAN ZHOU, CHUNYUAN HAN, CHUNXIA ZENG, XIAODONG SHI, QIBAI XIANG and ALLEN COOMBES / Status and conservation of Trigonobalanus doichangensis (Fagaceae)

243–258

NIALL G. BURNSIDE, DAN J. METCALFE, ROGER F. SMITH and STEVE WAITE / Ghyll woodlands of the Weald: characterisation and conservation

259–278

AI-LIAN ZHAO, XIAO-YONG CHEN, XIN ZHANG and DONG ZHANG / Effects of fragmentation of evergreen broad-leaved forests on genetic diversity of Ardisia crenata var. bicolor (Myrsinaceae)

279–291

M.G.P. TCHOUTO, W.F. DE BOER, J.J.F.E. DE WILDE and L.J.G. VAN DER MAESEN / Diversity patterns in the flora of the Campo-Ma’an rain forest, Cameroon: do tree species tell it all?

293–314

JEAN-REMY MAKANA and SEAN C. THOMAS / Impacts of selective logging and agricultural clearing on forest structure, floristic composition and diversity, and timber tree regeneration in the Ituri Forest, Democratic Republic of Congo

315–337

ALFONSO GARMENDIA, SUSANA CÁRCAMO and OSCAR SCHWENDTNER / Forest management considerations for conservation of Black Woodpecker Dryocopus martius and White-backed Woodpecker Dendrocopos leucotos populations in Quinto Real (Spanish Western Pyrenees)

339–355

STEVEN M. VAMOSI / A reconsideration of the reproductive biology of the Atlantic forest in the Volta Velha Reserve

357–364

ALESSIO MORTELLITI and LUIGI BOITANI / Patterns of rodent species diversity and abundance in a Kenyan relict tropical rainforest

365–380

J. LUIS HERNANDEZ-STEFANONI / The role of landscape patterns of habitat types on plant species diversity of a tropical forest in Mexico

381–397

JANE HERBERT / Distribution, habitat and Red List status of the New Caledonian endemic tree Canacomyrica monticola (Myricaceae)

399–406

GRACE NANGENDO, HANS TER STEEGE and FRANS BONGERS / Composition of woody species in a dynamic forest–woodland–savannah mosaic in Uganda: implications for conservation and management

407–435

JÖRN THEUERKAUF and SOPHIE ROUYS / Do Orthoptera need human land use in Central Europe? The role of habitat patch size and linear corridors in the Bialowiez·a Forest, Poland

437–448

BENIGNO GONZÁLEZ-RIVAS, MULUALEM TIGABU, KARIN GERHARDT, GUILLERMO CASTRO-MARÍN and PER CHRISTER ODÉN / Species Composition, diversity and local uses of tropical dry deciduous and gallery forests in Nicaragua

449–467

B. BALAGURU, S. JOHN BRITTO, S.J., N. NAGAMURUGAN, D. NATARAJAN and S. SOOSAIRAJ / Identifying conservation priority zones for effective management of tropical forests in Eastern Ghats of India

469–483

SWEN C. RENNER, MATTHIAS WALTERT and MICHAEL MÜHLENBERG / Comparison of bird communities in primary vs. young secondary tropical montane cloud forest in Guatemala

485–515

T.R. SHANKAR RAMAN / Effects of habitat structure and adjacent habitats on birds in tropical rainforest fragments and shaded plantations in the Western Ghats, India

517–547

Biodiversity and Conservation (2006) 15:1061–1061 DOI 10.1007/s10531-006-0009-7


Springer 2006

Introduction

Topics in Biodiversity and Conservation: Forest diversity and management Natural forests, with a history of ecological continuity extending back for thousands of years, are unrivalled as the treasure store of terrestrial biodiversity on Earth. Yet to date there is no fully comprehensive inventory of the above- and below-ground biota of any forest available, even in western Europe. However, in conserving natural forests, it is reasonable to assume that the myriads of unnamed bacteria, fungi, insects, mites and nematodes present will be safeguarded along with the trees, provided that the forest structure is maintained. But forests are also a key player in the global carbon cycle, and so in the maintenance of the composition of the atmosphere crucial to Life as we know it. To endanger and clear forests is at the peril of future generations, but as so many peoples depend on forests for food and wood, the issue of how forests can be used sustainably, in a way that protects the full spectrum of organisms they contain, has to be addressed. Sadly, the compensatory planting of new forests, whether for exploitation or conservation, does not fully address the need; the trees, other plants and vertebrates may be secured by such approaches, but the full soil biota, and complete spectrum of organisms associated with a natural forest are unlikely ever to be regained. This compilation of peer-reviewed papers, drawn from researchers around the world, examines many different aspects of forest diversity and management. They consider forests in diverse locations, including Australia, Cameroon, China, France, Kenya, the Philippines, Poland, Uganda, and the UK. The forest types considered vary from banana forests, savannah forests, and tropical rainforest to the much revered ancient oak forest of Bialowieza in Poland. The emphasis is on the trees themselves, including effects of logging, changes in management practices, and climate change. In some cases the consequences of forest disturbance or destruction on other plants, birds, or vertebrates are reported for particular forests. Given the wide range of topics brought together here, this collection should be of particular interest to those involved in teaching forest conservation and management, and requiring a cross-section of current work in the field. DAVID L. HAWKSWORTH The Yellow House, Calle Aguila 12, Colonia La Maliciosa, Mataelpino, Madrid 28492, Spain. E-mail: [email protected]

[1]

Biodiversity and Conservation (2006) 15:1063–1093 DOI 10.1007/s10531-004-1874-6


Springer 2006

-1

Dynamics in natural mixed-beech forest of the Upper Vosges D. CLOSSET-KOPP*, A. SCHNITZLER and D. ARAN LBFE, University of Metz, Campus Bridoux, rue du Ge´ne´ral Delestraint, 57070 Metz-Borny, France; *Author for correspondence (e-mail: [email protected]) Received: 10 February 2004; accepted in Revised form 22 July 2004

Key words: Mixed beech forests, Age-structure, Architecture, Soil, Light regime, Stand history Abstract. Forest dynamics were analysed in the Upper Vosges mountains of north-eastern France in two reserve areas, Frankenthal-Missheimle (FM) and Grand Ventron (GV), located in the Ballons des Vosges Natural Regional Park (Parc Naturel Re´gional des Ballons des Vosges). Two plots of 3000 m2 each were established in mixed beech woodlands located just below sub-alpine beech forests for long-term monitoring. The main aim of the study was to interpret how the different species populations in mixed-beech woodlands in the Vosges grow and interact over the long term, and to determine the disturbance history. The study combined vegetation description, dendrological and structural data, architectural descriptions and drawings and light distribution and soil analysis. Historical information was also taken into consideration. Soils in the two plots showed available phosphate P values > 0.14 g kg
1, indicating good levels of phosphorus supply for plants, except for A1/C horizon (1Va soil) which corresponds to a medium-fertility soil. However, soils were found to be shallow because of the slope, a factor that may limit water availability for adult trees and seedlings. As the canopy (composed of existing trees) consists of shade trees, the growth rates for seedlings and saplings (potential trees) depends on the canopy architecture: when growing in sunlit gaps, saplings reach full daylight (canopy height) in less than 100 years. When developing in shade (suppressed state), saplings may need up to 150 years before reaching full daylight. Alternating periods of rapid and slow growth explain why some trees present a wide range of stem diameters and ages in the area leading up to the canopy (some trees are more than 300-years-old), in contrast with the relatively homogeneous height classes distribution, indicating suppression periods. Trees in the FM and GV plots were found to have different growth rates. Both study plots developed with similar past disturbance events, the two most important being at the beginning of the 18th century. In addition, the forests were regularly affected by smaller disturbances until present. Because of the spatial heterogeneity and large range of ages represented, the forest stands within the two natural reserve areas are presently considered to be the bestpreserved sites in the upper Vosges, but their situation near the timber line prevents them from becoming models for forest management at lower altitudes.

Introduction Unmanaged forests are the last representatives of the pristine landscapes of Europe. Unfortunately, they have practically disappeared from European forest panels, with a total of only 3 millions hectares (i.e. 1.7% of the total forest area; COST Action E4 1999). These forest relics are located primarily in remote, inaccessible areas, in unproductive regions, hunting reserves or along frontier borders (Peterken 1996; COST Action 4 1999; Motta et al. 2002; [3]

1064 Schnitzler 2002). Apart from Russia, where old-growth forests may reach up to 20,000 km2 (Sittler et al. 2000), they are small patches (a mean range of 20– 100 ha) within a larger landscape patchwork of managed forests and various land uses. For example, France, with 15 million hectares of metropolitan forest cover, possesses the third largest woody domain in Europe, but only 0.2% (300 km2) of this total are natural forests (Vallauri and Poncet 2003). Most of these are concentrated in mountain regions (the Vosges, the Jura, the Pyrenees and the Alps). Studies have demonstrated that these vestiges cannot remain completely independent of their managed surroundings, and are unable to preserve their potential biodiversity (Helle and Ja¨rvinen 1986). Pollen diagrams have, however, demonstrated that even small ‘virgin’ forests remain stable in composition over hundred of years (Bradshaw and Holmqvist 1999). The main causes of such stability and resilience are the high complexity in structure and architecture associated with the complexity of biotic interactions, which lead to remarkable resistance to climatological events (White 1978; Franks and McNaughton 1991). All remaining natural forests urgently need protection in order to preserve their cultural and scientific value, to protect their wildlife and genetic diversity and to ensure sites for basic research in ecology. They also provide the necessary reference data for applied research in forest management and environmental monitoring (Leibendguth 1959; Peterken 1996). The present study looked at several aspects of the forest dynamics and biodiversity of mixed-beech woodlands of the ‘Parc Naturel Re´gional des Ballons des Vosges’ (PNRBV) (Upper Vosges, north-eastern France). The PNRBV has two natural reserves within its boundaries: the Grand Ventron (GV), created in 1995 covering over 1647 ha, and the Frankenthal–Missheimle (FM), created in 1989 with over 746 ha. Their respective elevations (GV: 720– 1204 m; FM : 690–1363 m) correspond to the submontane (400–800) and montane belts (800–1100 altitude). Both reserves harbour typical, often endangered, plant communities (Schwoehrer and Despert 1999; Schwoehrer 1999; Untereiner et al. 2002). The impact of human activity has been significant since the French Revolution and includes logging, local fires and the planting of non-indigenous spruce since the 1850s (Garnier 1994, 1998). Ungulate densities are also closely linked to human activity and their populations have increased considerably during the 20th century (ONF 2000; Heuze´ 2002). One of the main objectives of the creation of the PNRBV, within the framework of which the present research was carried out, was to contribute to the conservation and sustainable management of the forests through basic and applied research and the development of innovative methodologies. For this reason, our research focused on long-term, forest-monitoring plots situated in strictly protected woodlands of the FM and GV natural reserves which still include small stands of nearly natural woodlands (Gilg 1997). The aim of the study is: (i) to propose and innovate a sampling protocol for long-term studies,

[4]

1065 (ii) to interpret how different species populations of Vosgian mixed-beech woodlands grow and interact over the long-term in light of their disturbance history, (iii) to propose a diagnostic of forest naturalness.

Materials and methods Study sites The Vosges form a long ridge with a continuous crest line, linked to the west and to the Rhine valley to the east by steep slopes. In the southern Vosges, the crest oscillates from 1000 to 1425 m. The climate is oceanic (1600 to 3000 + mm rainfall; mean annual temperature of 4 C above 1000 m). The hercynian bedrock is mainly composed of granite and metamorphic rock, partially covered with morainic material. They include biotitic granite rock, locally porphyroid, with acid plagioclase (An10-20), K-Feldspar, quartz and some apatite (Mansuy 1992). Soils range from acidic browns to podzols (Souchier 1971; Bonneau et al. 1978). The mixed-beech woods found between 600 and 1000 m are part of the Fagion alliance. The main plant community is the Luzulo–Fagetum (Meusel 37) which includes two sub-associations (group Vaccinium myrtillus; group Festuca altissima, Oberdorfer 1992) typical of Central European mountains and hills north of the Alps (Ellenberg 1988; Oberdorfer 1991, 1992; Bogenrieder 2001). The three plant communities include the same tree species (Fagus sylvatica, Abies alba, Acer pseudoplatanus, Sorbus aucuparia) and shrubs (Rubus tereticaulis, Rubus idaeus, Lonicera nigra). Beech (Fagus sylvatica) occupies a central position in the ecology of the Vosgian forests, outcompeting the other tree species. Silver fir (Abies alba) is regular but suffers from browsing (Heuze´ 2002). Acer pseudoplatanus is competitive in shallow soils found in rocky habitats. Spruce (Picea excelsa)is rare, despite the importance of neighbouring plantations. Ground-level flora is dominated by Vaccinium myrtillus, Luzula luzuloides, Deschampsia flexuosa and Prenanthes purpurea. The GV and FM reserves are 8 km apart (Figure 1). They are close (8– 15 km) to a third natural reserve, the Guebwiller (700–950 m), which also includes some stands of nearly natural woodlands (Renaud et al. 2000).

Permanent plots Two plots measuring 3000 m2 (50 · 60 m, i.e. 30 quadrants of 10 · 10 m) each were selected within the less disturbed mixed-beech woodlands of the two reserves. Stand coordinates were referenced by means of a global positioning [5]

1066

Figure 1. Location of FM and GV natural reserves in the Upper Vosges.

system (GPS) (GV: latitude 4827¢N; longitude 665¢E; the plot is situated near the ‘Grand Ventron’ farm; FM: latitude 4830¢N ; longitude 710¢E: the plot is situated below the ‘Trois-Fours’ farm). Metallic boundary markers were buried (forced in the soil) in the ground in order to pursue the study over the very long term. The FM plot is located between 900 and 950 m while the GV plot is 50 m higher (950–1025 m), very close to the multi-stemmed beech forests that form the timber-line (Carbiener 1966). Both plots face East. Plot GV is characterized by a succession of steep slopes (50–60%), and flatter (5–30%), moister zones while the FM plot exhibits more regular slopes, averaging 65%. Plot FM is adjacent to a large, permanent gap resulting from the accumulation of boulders of glacial origin. The fieldwork started in 2000 and ended in 2003.

Soil data Soil-units were defined according to local topography, regeneration patches and humus type characteristics. For each soil-unit, one representative profile was described (horizons, colour, texture, structure, stoniness, root development). All horizons of the representative profiles were sampled, with special attention to the first few centimetres (A11 horizon) where seed germination takes place. In some cases, A11 horizons were also sampled within one soil-unit, with regard to different slopes, regeneration or humus characteristics. [6]

1067 In 2002, five soil units were defined in the GV plot. In 2003, three soil-units were identified and sampled in the FM plot. All samples were air-dried, passed through a 2 mm sieve and then analysed for chemical characteristics (analysis performed by INRA Laboratory for Soil Analysis, Arras, France): residual moisture content at 105 C, organic carbon and total nitrogen (dry combustion method), ‘available’ phosphorus (extracted by H2SO4 and NaOH; Duchaufour and Bonneau 1959), and exchangeable cations (based on cobalthexamine method, Orsiny and Remy 1976). Calculations were performed for C/N ratio, cation exchange capacity (CEC: sum of exchangeable cations), base saturation (ration of exchangeable ‘basic’ cations – Ca2+, Mg2+, K+ and Na+ – to CEC), and exchangeable Mg/Al and Ca/Al ratios.

Stand characteristics Ground flora The ground flora coverage was identified and the coverage of each species estimated, (Braun–Blanquet cover coefficient were converted in percentage cover). Tree seedling densities (height < 130 cm with d.b.h less than 10 cm) were identified and quantified per 10 · 10 m quadrant (30 per stand). Size variables and architecture Tree height, stem diameter and crown area are variables of a tree’s architecture, and an expression of its growth strategy (Halle´ and Oldeman 1970; Halle´ et al. 1978; Oldeman 1979, 1990; Oosterhius et al. 1982). Tree height yields information about ecological conditions and growth strategies: the harsher the climate, the shorter the trees. Tree height distribution is also related to regeneration processes: theoretically, in continuously regenerating stands, the number of individuals in each height-class is expected to follow an exponential decline in numbers from shorter to taller trees. Curves are modified under shady canopies due to the stagnation in growth for much of the tree’s life cycle. In these cases, stem diameter increases when height progress is nearly at a standstill (Peters 1992). Clear allometric relationships exist between these variables. The hf/H ratio (k) compares the height of the tree trunk (hf) up to the first main fork to the total height (H). The inversion point k, where the architectural tendencies are inverted (the axes become smaller and smaller, terminating at the periphery of the crown), is important in forest stand diagnosis: the higher the inversion point (i.e. the shallower the crown depth), the higher the competition with neighbouring trees. Growth strategy can also be interpreted using tree architecture. Architecture corresponds to the visible, morphological expression of hereditary growth development. For tree species, orthotropic versus plagiotropic axes, the ability to reiterate (i.e. the capacity to partially or totally repeat hereditary architec[7]

1068 ture in the same tree, by stimulation of resting meristems, Oldeman 1979) may explain differences in size variables. Fagus sylvatica grows according to Troll’s model with plagiotropic differentiation in all axes. The flattened and highly organized leaf layers (monolayers), as well as the plagiotropy are necessary for intercepting light over large surfaces. Beech is also very flexible, forming shoots of different lengths in response to environmental conditions (Halle´ and Oldeman 1970; Nicolini 1997; Roloff 1999). Acer pseudoplatanus follows Rauh’s model, characterized by orthotropic axes and faster growth than the beech. However, Acer pseudoplatanus is a monolayer, which increases its ability to intercept sunlight (Halle´ et al. 1978). Abies alba follows Massart’s model, characterized by a specialized plagiotropic organization of the branches that confer them high individual survival in the lower forest storeys (Edelin 1977). Architectural criteria also allow us to define the different phases of tree development. Oldeman (1990) has defined three main phases (‘potential tree’, ‘tree of the present’ and ‘tree of the past’), considered as the principal social states in the forest ecosystem. Potential trees and trees of the present can be seen as two distinct phases in the growth of a tree. In potential trees, the growth in height is relatively more important than growth in stem diameter and crown extension. Potential trees may grow faster under the high light levels found in canopy gaps (‘released-growing trees’) or be suppressed by shading from canopy trees. After successive intervals of suppression and released growth, many potential trees reach a minimum height above which they cannot be suppressed. In this case, they develop their architecture by reiteration and reach the tree of the present phase. The transition between these two growth phases is gradual, depending on the site and the forest architecture. To distinguish the two steps in our study, an empirical threshold was set at the height of 20 m, which corresponds to the minimum needed to no longer be suppressed on the steep slopes of the Vosges (suppression is visible when trees present shallow crowns and reiterations along the trunk, and the h/d.b.h. ratio is greater than 100). Tall tree species that have gone beyond this threshold are considered full-grown. For our purposes, living and dead trees of more than 10 cm d.b.h. and height >1 m 30 were identified in the plot and measured (diameter at breast height, total height, height of the main fork. Each (living or dead) tree was carefully drawn according to its exact proportions and morphology. Crown area was defined using four perpendicular directions, including one facing the slope. Tree architecture was represented visually by vertical (six, 10 · 50 m parallel drawings per stand, oriented towards the slope) and horizontal drawings (one for living and one for dead trees in each plot). Relationship between size variables and age The age distribution of the trees depends on the plot history (past and present natural disturbances, impact of historical practices). Stem diameter growth depends on altitude, light intensity, temperature, water and nutrient supply, neighbouring trees, possible pollution as well as the period in the tree’s life [8]

1069 cycle (‘potential’ versus ‘present’). Thus, tree ring analysis is useful for determining the influence of ecological conditions within the particular context of the Upper Vosges. The ring widths of 156 trees (93 in the GV plot and 63 in FM, including beech, silver fir and Acer pseudoplatanus were noted. Two cores were extracted at breast height from each tree, one up-slope and one down-slope. Tree-ring widths were measured using a computer-assisted device (Becker et al. 1995) and cross-dated against previously existing site chronologies (data from INRA, Champenoux), in order to correct for missing or duplicate rings. Stem diameter growth was calculated by dividing core length by the total number of ring widths. Growth rate comparisons were done at each site for each state and each species using non-parametric Mann–Whitney U-tests (Statistica software).

Canopy geometry and light distribution Since tree growth, architecture and size variables are largely explained by light dynamics (e.g. Chazdon and Pearcy 1986; Denslow et al. 1990; Vester 1997), variations in light distribution at points within the canopy were also studied. Relationships between the tree, the forest and the light level in old-growth forests have been studied by Koop (1989). The methodology deals with the architectural parameters of the canopy (canopy geometry) that are commonly used in the literature (i.e. gap fraction and foliage area index LAI), and the light variables (i.e. direct and diffuse solar radiation transmitted throughout the canopy). The simultaneous treatment of canopy geometry and distribution of incident light (PAR, understood as QPAR, quantum irradiance, expressed in mol m
2 d
1, Varlet-Granchet et al., 1989) was studied using hemispherical canopy photography. For each plot, 25 canopy photographs were taken in each 100 m2 section, 10 m apart from each other, at 50 cm above the ground, in overcast conditions. Because some photographs were of poor quality, the final raw data included only 21 photographs for GV and 24 for FM. The camera was equipped with a fish-eye lens with a view angle of 180, carefully levelled and oriented for true North. The raw data from each photograph consisted of a matrix with 18 intervals of 5 zenith angles and 24 sectors of 15 azimuth angles which contained the gap fraction. All values were corrected for latitude, slope, orientation and topographic mask in the GLA model (Frazer et al. 1999). Calculations were performed at hourly intervals, then integrated daily, during the vegetative season (June–September). The radiation intercepted depended upon values calculated for each canopy element involved, over the whole hemisphere and along the solar tracks. Hemispherical photographs therefore present spatial auto-correlations with each other. Values found in FM and GV will be compared with data obtained using similar methods in the Guebwiller mixed-beech forest. Data concern one plot [9]

1070 of 1 ha chosen in a nearly natural forest stand growing in deep soil (slope from 20 to 30)(Renaud et al., 2000; Pierrel 2001).

Results Soil characteristics In both plots, soils are dark coloured, stony or gravely, with a fluffy to massive structure and are finely textured (coarser with depth). Soils are shallow. FM soils show less variability in type than those in GV. Soils belong mostly to the Rankosol (Ranker) type, except for 2V soil which belong to Alocrisol and 5V soil which presents hydromorphic features (located in bench slope). Humus type ranges from oligo-mull to hemi-moder (Brethes et al. 1992). Chemical analysis (Table 1) shows a humose trend, with relatively high organic carbon content, particularly for the 5V soil due to waterlogged conditions. Less organic matter accumulation is observed in FM soils which may be related to better biodegradability of organic materials. In both stands, rather low C/N ratios, from 14.9 to 17.7 in uppermost horizons (A11), accounted for a rapid evolution of plant material added to soil and good nitrogen nutrition for trees. C/N ratios increasing with depth (1Va, 4V and 1F soils) probably indicate a cryptopodzolisation process, morphologically hidden by the humose character of soils. Available phosphorus obtained using the Duchaufour and Bonneau (1959) method is a good indicator of soil fertility. All samples showed available P2O5 values > 0.14 g kg
1, indicating a good phosphorus supply for plants, except for A1/C horizon (1Va soil) which corresponded to a medium-fertility soil (Bonneau 1995). No notable differences were observed in regeneration spots, or between GV and FM plots. Soils show a medium cation exchange capacity (CEC), mostly related to organic matter content (organic carbon), decreasing with depth and lower in FM soils. Low base saturation was always observed in depth, while it exceeded 35% in uppermost horizons in 4V and 3F soils and reached 60% in 2F soil, due to active nutrient cycling. Among basic exchangeable cations, Ca generally predominates over Mg and K (low Na). Similarly, among acid exchangeable cations, Al largely predominates over H (low Mn), except in 1Va, 1Vd, 4V and 2F soils’ uppermost horizons showing a higher H proportion, probably related to cryptopodzolisation. A plentiful supply of Al on exchange sites is known to disturb Mg and Ca supply. The lowest Mg/Al and Ca/Al ratios were found in all deeper horizons (Bw, A1/C and C) except 2F soil, suggesting a possible Mg and Ca deficiency. On the other hand, all uppermost horizons showed higher ratios, apart from 3V soil (Mg) and 5Va soil (Ca). On the whole, no pronounced differences in soil property features were observed between the two plots. [10]

Table 1. Chemical characteristics of soils in GV and FM plots. Stand

Soil

Horizon

Depth cm

Organic carbon g kg
1

C/N

Available P2O5 g kg
1

Exchangeable cations Ca

2+

Mg

2+

K

+

Na

+

Al

3+

2+

CEC

Base saturation%

Mg/ Al

Ca/ Al

pH H 2O

10.73 7.18 5.70 9.47 11.09 11.63 13.17 8.36 5.39 4.37 12.67 9.52 4.45 18.21 13.77 7.80 13.58 3.74 11.77 5.91 4.50 2.72 9.42 7.46 7.20 5.49

29.0 12.6 3.6 15.9 26.0 20.7 30.7 8.4 6.9 5.9 11.1 9.4 6.3 46.0 21.3 5.6 12.7 8.7 15.4 22.8 6.3 5.2 60.2 23.2 37.9 12.1

0.148 0.064 0.012 0.053 0.088 0.098 0.090 0.026 0.021 0.020 0.027 0.032 0.023 0.216 0.072 0.020 0.041 0.032 0.044 0.056 0.020 0.012 0.495 0.075 0.134 0.035

0.490 0.084 0.008 0.086 0.276 0.237 0.393 0.036 0.024 0.018 0.073 0.032 0.018 1.032 0.222 0.021 0.059 0.038 0.106 0.203 0.022 0.020 2.073 0.225 0.574 0.074

3.6 3.6 4.1 4.3 3.7 3.6 3.9 4.0 4.3 4.5 4.2 4.3 4.5 3.7 3.6 4.0 4.5 4.6 4.3 4.4 4.5 4.7 4.2 4.0 4.2 4.3

+

Mn

H

0.068 0.013 0.006 0.117 0.159 0.036 0.298 0.042 0.027 0.014 0.275 0.092 0.028 0.168 0.028 0.006 0.140 0.011 0.289 0.214 0.033 0.010 0.362 0.036 0.263 0.110

3.56 2.09 0.33 0.55 1.50 3.58 1.60 0.33 0.17 – 0.35 0.30 0.08 3.60 2.66 0.50 0.31 0.16 0.55 0.31 – – 1.39 1.30 0.84 0.31

cmol+kg
1 GV

[11] FM

A11 A12 A1/C A11 A11 A11 A11 A12 Bw C A11 A12 C A11 A12 C A11 A12 A11 A11 A12 A1/C A11 A1/C A11 A12

0–2 2–7 7–30 0–2 0–2 0–2 0–2 2–10 10–25 25–50 0–2 2–12 12–40 0–2 2–10 10–33 0–2 2–20 0–2 0–2 2–15 15–25 0–2 2–10 0–2 2–20

14.84 7.91 5.79 18.48 15.41 16.23 18.03 12.65 6.75 6.61 29.24 17.92 6.15 30.77 19.51 8.06 34.37 5.58 18.30 6.66 4.29 3.25 12.45 8.85 7.87 5.29

17.7 17.0 21.8 15.4 16.4 17.3 17.0 15.1 15.4 15.5 17.2 16.0 14.6 17.7 17.2 21.7 17.6 15.9 14.9 15.9 15.4 17.4 16.6 14.9 16.5 14.8

0.386 0.195 0.125 0.35 0.316 0.289 0.404 0.3 0.184 0.16 0.454 0.365 0.219 0.503 0.404 0.197 0.54 0.254 0.438 0.412 0.208 0.286 0.388 0.317 0.46 0.333

1.95 0.35 0.04 0.63 1.81 1.33 2.84 0.26 0.11 0.07 0.78 0.27 0.07 6.25 1.81 0.14 0.68 0.12 0.97 0.82 0.09 0.05 4.13 0.99 1.93 0.33

0.59 0.27 0.06 0.38 0.57 0.55 0.65 0.19 0.10 0.08 0.28 0.27 0.09 1.31 0.59 0.13 0.47 0.10 0.40 0.23 0.08 0.03 0.99 0.33 0.45 0.15

0.49 0.24 0.07 0.42 0.45 0.44 0.49 0.20 0.11 0.07 0.31 0.31 0.08 0.75 0.46 0.11 0.49 0.08 0.39 0.28 0.09 0.04 0.49 0.34 0.32 0.13

0.08 0.05 0.03 0.07 0.05 0.08 0.05 0.05 0.04 0.03 0.03 0.05 0.03 0.08 0.06 0.04 0.09 0.02 0.05 0.02 0.02 0.02 0.06 0.07 0.03 0.05

Data in g kg
1 of dry matter, except for available P2O5 in g kg
1 of air-dried soil: below detection limits.

3.99 4.17 5.16 7.29 6.54 5.61 7.23 7.28 4.83 4.10 10.65 8.23 4.06 6.06 8.16 6.86 11.41 3.24 9.12 4.05 4.18 2.57 1.99 4.40 3.37 4.41

1071

1Va 1Va 1Va 1Vb 1Vc 1Vd 2V 2V 2V 2V 3V 3V 3V 4V 4V 4V 5Va 5Va 5Vb 1F 1F 1F 2F 2F 3F 3F

1072 Stand characteristics Density and spatial patterns Plot GV is more crowded (322 stems ha
1) than FM (275 stems ha
1), but FM volume values were more important (677.7 m3 ha
1 and 949 m3 ha
1 for GV and FM respectively)(Table 2). The dominant species is beech, which accounts for 66% in GV and 70% in FM. Multi-stemmed beech trees were also more important in GV. Abies alba and Acer pseudoplatanus are relatively minor components of the stands, accounting for 18.6 and 13.3% respectively in GV, and 18.1 and 9.4% in plot FM. Acer pseudoplatanus typically occupies rocky, sunnier sites. Sapling density is higher in FM than in GV. In plot FM, the dominant species is Acer pseudoplatanus (42%), followed by Abies alba (32.6%) and Fagus sylvatica (23.7%). Beech is largely dominant in the GV plot, representing 80% of the total number of saplings. Silver fir development is limited by ungulate predation and its sensitivity to frost and drought. Picea excelsa and Sorbus aucuparia are rare. Woody regeneration is strongly clumped in several ellipsoid patches at gap margins, extending towards the slope (Figure 2a, b). The biggest gaps in both plots are caused by rocky areas where tree regeneration is difficult. These gaps are mainly colonised by herbaceous species: Luzula luzuloides, ferns in GV; Festuca altissima, Oxalis acetosella, Galeopsis tetrahit, small woody species (Rubus tereticaulis, Rubus idaeus, Vaccinium myrtillus). Tree and forest architecture Because of the steep slopes, nearly all the trees present asymmetrical shapes: crowns develop marked supplementary axes (reiterations, Oldeman 1974) on trunks, and secondary axes facing the other end of the valley, while there are no secondary, supplementary axes on the opposite side (Figure 3a, a1, b, b1). Asymmetry is particularly developed in Fagus sylvatica and Acer pseudoplatanus, very flexible species which reiterate their initial architectural model easily. Trees of the present reiterate more often than potential trees because they have sufficient energy for crown expansion. Asymmetrical shapes are explained by insertion points k which are low (0.32–0.42) on one side of the trunks and high on the opposite side. There is strong inter-penetration of crowns laterally between the middle and upper-third of tree height, while foliage is much less dense above and below. Potential trees often present triangular crown shapes (suppressed trees growing below healthy, shading trees of the present). To compensate for the small foliar volume, some potential trees have developed small reiterations along the trunk. Firs exhibit many kinds of traumas, including loss of major branches and double forks resulting from loss of apical buds (frost, wind). In plot GV, 23.4% of beech trees are multi-stemmed, with 2–14 trunks of different dimensions. Most trunks have reached the canopy, with some big trunks reaching more than 30 m high. Within one type of individual, the range in height varied from 0 to 6 m, with stem diameters varying from 3 to 16 cm. In [12]

Table 2. Densities and volumes of tree species in FM and GV. Number saplings 4

Number, Fagus sylvatica

[13]

GV 8983 7184 FM 52300 12395 4 stems ha
1; height < 1m30; d.b.h. < 4 cm Number Number, living trees 1 Fagus sylvatica GV 322 213 FM 275 193 Number Number, dead trees 1 Fagus sylvatica GV 63 16 FM 16 0 1 2 3 4 5

Number, Abies alba

Number, Acer pseudoplatanus

Number, Picea excelsa

Number, Sorbus aucuparia

592 17049

1194 22122

18 680

18 52

Number, Abies alba 43 50 Number, Abies alba 47 16

Number, Picea excelsa 6 26 Total volume dead trees 2, 4 23.3 24.8

Total volume living trees 2 677.7 949

Basal area living trees 3 22.8 53.3

Stems ha
1, d.b.h. > 4 cm. m3 ha
1 based on the calculation formula of volume used in Renaud et al. 2000. V = diameter2 · height · 0.35 for coniferous and V = diameter2 · height · 0.5 for broad-leaved tree. m2 ha
1. Dead trunks of multi-stemmed beech trees excluded.

1073

1074

Figure 2. (a) Crown projection map (50 · 60 m) in FM (shaded areas represent regeneration). Fa for Fagus sylvatica; Ac for Acer pseudoplatanus; Ab for Abies alba. (b) Crown projection map (50 · 60 m) in VN (shaded areas represent regeneration) Fa for Fagus sylvatica; Ac for Acer pseudoplatanus; Ab for Abies alba.

[14]

1075

Figure 3a. Examples of vertical profile (10 m · 50 m) in FM (tree species and age are represented for potential trees and trees of the present. (Fa: Fagus sylvatica; Ab: Abies alba; Ac: Acer pseudoplatanus).

general, one or two were big and healthy, one to three smaller and the remaining trunks (big or small) dead. The proportion of dead trunks increased as the total number of trunks increased. Size-distribution, social status and age-distribution In both plots, tree height distribution presented a simple, global architecture with foliage concentrated in the canopy:canopy trees (i.e. trees of the present) accounted for 60% of the registered trees in FM and 68.8% in GV. In spite of a regular, evenly spaced distribution of trees of the present, canopy stratification [15]

1076

Figure 3a. (Continued)

was rather complex, with the imbrication of three main layers: 20–25 m, 25– 30 m and some emergents between 35 and 40 m. Plot GV had a nearly equal number of trees between 20–25 and 25–30 m (Figure 3a, a1), while FM included more trees in the upper canopy (Figure 3b, b1). Size-distribution is not related to age-distribution, indicating that shadetolerant species cohorts can survive for long periods in a suppressed state. Correlations are better for older trees in the upper parts of the canopy; i.e. [16]

1077

Figure 3b. Examples of vertical profile (10 m · 50 m) in GV (tree species and age are represented for potential trees and trees of the present. (Fa: Fagus sylvatica; Ab: Abies alba; Ac: Acer pseudoplatanus).

maximum ages are closer to sizes: 40 m high and 111 cm d.b.h. for a 345-yearold silver fir, 29 m high and 41 cm d.b.h. for a 214-year-old beech; 23 m high and 54 cm d.b.h. for a 231-year-old Acer pseudoplatanus (Table 3). Most trees of the present had a rotten heart, particularly the Acer pseudoplatanus. However, their foliage and axes were well-developed, without any sign of bark or leaf loss. Trees can be considered as reaching the stage ‘of the present’ at various ages. In general, potential trees in FM reach the canopy earlier than those in GV: a range of 48–162 years in FM compared to a range of 102 (very rare)–223 years in GV. Thus, under good light conditions, averages of 2.2 mm growth per year [17]

1078

Figure 3b. (Continued)

were recorded for three young 45- to 52-year-old beeches in FM. In this plot, potential trees and trees of the present also had similar growth rates for stem diameter while in GV, trees of the present grew significantly (p < 0.001) faster than potential trees (Table 4). These data indicate that suppression was more marked in GV, which limits correlations between stem diameter growth and age (Figure 4). For beech trees, the Spearman correlation coefficient (Rs) is 0.48 while the correlation is above 0.65 in FM. The silver fir presents similar tendencies (Rs = 0.71 in FM; 0.29 in GV). Average growth rates of suppressed beech trees in GV are only 0.3– 0.6 mm per year and 0.7 mm for silver fir. This explains why some GV saplings may be rather old: 119 years for a 4.5 m high silver fir; 135 years for a 7.5 mhigh beech. One potential beech was still in a suppressed state at 215 year of age. Multi-stemmed beech trees present a broad range of ages (from 20 to 78 years) within one individual. [18]

1079 Table 3. Ranges of stem diameter and age for beech, silver fir and sycamore in FM and GV. FM plot n

GV plot

Range of DBH (cm)

Range of ages (years)

n

Range of DBH (cm)

Range of ages (years)

Potential trees < 10 m Fagus sylvatica Abies alba Acer pseudoplatanus

6 3 2

8–11 11–79 5–7

54–102 30–59 21–68

6 2 1

5–19 6 10

41–135 37–119 55

10–20 m Fagus sylvatica Abies alba Acer pseudoplatanus

4 3 1

13–32 21–30 67

35–52 54–80 77

5 14 1

16–32 14–54 11

119–160 149–226 66

Trees of the present 20–30 m Fagus sylvatica Abies alba Acer pseudoplatanus

13 1 5

32–76 45 30–73

146–193 135 117–162

36 4 14

29–64 48–70 10–57

102–321 107–193 78–231

30–40 m Fagus sylvatica Abies alba Acer pseudoplatanus

18 6 1

45–83 57–111 54

150–281 132–345 154

8 2 14

29–54 62–64 10–57

147–223 101–200 78–231

Correlations between stem diameter and age of Acer pseudoplatanus trees were significant for GV (0.87). For FM, Acer pseudoplatanus trees are too rare to be analysed. Dead trees Dead trees (trees of the past) represented 11.2 and 3.1% of the total volume of trees in GV and FM, respectively (Table 2). Most of them were silver firs. In FM no death was recorded among beech trees. Dead trees generated only very small gaps because they were rarely very large: average stem diameters ranged from 10–80 cm. The three dead silver fir trees analysed in GV (d.b.h of 13, 13.6 and 25 cm) died at 79, 89 and 191 year of age respectively. Two beech trees (d.b.h of 25 and 22 cm) died at 145 and 149 years respectively. These trees were either snapped off at different heights (from 2 to 24 m) or uprooted. Dead trees presented different degrees of rot. Standing dead trees had woodpecker holes and were often infected by Fomes fomentarius. Tree establishment Tree distribution by species (Fagus sylvatica, Abies alba and Acer pseudoplatanus) and age-class (Figure 5) in FM and GV indicates a pattern of establishment and mortality during the last 350 years. There was a peak in establishment between 1800 and 1840 in FM (a total of 46 trees in 40 years). In [19]

1080 Table 4. Stem diameter growth for beech, silver fir and sycamore in FM and GV. Potential versus present in each plot Potential n

Present Growth rate

n

Growth rate

FM Fagus sylvatica Abies alba Acer pseudoplatanus

10 6 3

1.37 1.6 1.3

31 7 6

1.47 1.7 1.26

NS NS NS

GV Fagus sylvatica Abies alba Acer pseudoplatanus

11 16 2

0.64 0.83 0.59

44 6 12

0.95 2.02 0.96

*** *** NS

11 16 2

Growth rate 0.64 0.83 0.59

** ** NS

44 6 12

0.95 2.02 0.96

*** NS NS

Potential versus potential per plot FM n 10 6 3

Growth rate 1.37 1.6 1.3

Present versus present per plot Fagus sylvatica 31 Abies alba 7 Acer pseudoplatanus 6

1.47 1.7 1.26

Fagus sylvatica Abies alba Acer pseudoplatanus

GV n

***p < .001 **p < .01 *p < .05 NS: not significant

GV, the peak occurred 20 years earlier, between 1780 and 1820 (a total of 62 trees). Beech was the colonizing tree in more than 50% of the cases. After 1840, recruitment was continuous but weak (approximately 2–4 trees per 20 yearperiod except in 1920–1940 in FM). Before 1780–1800, trees were very sparse (probably most of them have died since that time): two silver firs born respectively in 1640 and 1680, two beech trees born in 1680 and 1720 and one Acer pseudoplatanus in 1760. Figure 6a, b illustrate age distribution in the two plots. Trees from 100 to 200 years of age were regularly distributed as small groups of similar ages. Trees in the 200- 300-year-old category, which had survived stress, pathogens or windstorms, were scattered as relics among these smaller groups. Trees under 100 years of age were clumped around gaps or at the margins of canopy trees. Canopy geometry and light pattern The two plots presented differences in canopy geometry and light patterns (Figure 7a, b; Table 5). Values from FM indicate a more open habitat than [20]

1081

Figure 4. Age-stem diameter distribution for Fagus sylvatica, Abies alba, Acer pseudoplatanus in FM and GV. Rs: Spearmann correlation coeffiecient, ***: p < 0.001, **: p < 0.01, *: p < 0.05, NS: Not significant

[21]

1082

Figure 5.

Tree establishment in GV and FM.

[22]

1083

Figure 6. (a) Tree age and spatial distribution in FM. (b) Tree age and spatial distribution in GV.

that in GV: canopy openness of 14.6% compared to 11.5% in GV; percentages of total incident light of 14.5% compared to 6.7% in GV. The differences can also be visualized when considering the horizontal variations in the gap [23]

1084

Figure 7a. Variations in canopy geometry and light condition in FM.

fraction and the total incident light (trans total): (i) for gap fraction, the highest value in FM reaches 22% compared to 16.5% in GV; (ii) for the total incident light, the highest value is 14.5% compared to 6.7% in GV.

[24]

1085

Figure 7b. Variations in canopy geometry and light condition in GV.

[25]

1086

Table 5. Mean and range of values of canopy geometry and of the distribution of light in GV and FM. n [26]

GV

21

FM

24

Mean values Range of extreme values Mean values Range of extreme values

CO%

LAI m2 m
2

Trans direct mole m
2 d
1

Trans direct%

Trans diffuse mole m
2 d
1

Trans diffuse%

Trans total mole m
2 d
1

Trans total%

11.5 7–16.5 14.6 9.8–22

2.6 1.9–3.8 2.5 1.8–3

0.65 0.07–1.54 0.29 0.07–0.91

6.1 0.67–14.3 14.7 5.3–43.3

0.77 0.27–1.65 0.89 0.5–1.84

7.3 2.6–15.8 13.5 5.9–28

1.42 0.36–2.77 1.14 0.71–1.8

6.7 1.8–11.8 14.5 7.7–24.3

1087

Figure 8. Distribution of sun flecks in FM and GV.

The sun fleck distribution points to marked differences between FM and GV (Figure 8). In GV, the distribution is much more patchy, with a high number of small 5–10¢ sun flecks (970 compared to only 201 in FM) in relation to the higher tree density and more complex forest architecture. There were some very long sun flecks in GV (reaching 155¢) which were not observed in FM (maximum: 65¢). These long sun flecks, that originated from the horizon, occurred in only one photo site near the border of the plot. Canopy geometry and PAR values vary according to the solar zenith angles. In GV, gap fraction values ranged from 22.5 to 32.5, while in FM the angles where gap fractions were highest ranged from 2.5 to 22.5. The zenithal angles where incident light was highest was, in both cases, between 32.5 and 72.5 degrees, corresponding to the slope and the topographic mask. Discussion Forest dynamics near the timber-line The examples given in plots FM and GV indicate that mixed-beech forests are spatially and temporally heterogeneous. Both plots show wide variations in stem density, size-class distribution and age distribution that are ecological traits of woodlands in a nearly natural state. Despite a higher stem density, the GV site exhibited a lower volume of stem wood than the FM site. The importance of deadwood and discontinuities in the distribution of saplings and seedlings are also ecological features regularly observed in natural, shady woodlands in Europe and North America (Jones 1945; Leme´e 1978; Mayer and Neumann 1981; Peterken 1996; Schnitzler 2002). These stand characteristics, combined with the remarkable resistance of mixed-beech forests in the FM and GV reserves (as compared to trees in the surrounding [27]

1088 managed forest stands) to the historical december 1999 storm (Schwoehrer personal observation) indicate that forest stands in the two reserves have retained a relatively high degree of ‘naturalness’ (for a detailed discussion of the word ‘naturalness’, see Peterken 1996). This finding is of interest for the interpretation of forest dynamics. The mechanism of gap formation and development is linked to the scale of disturbance events and biotic processes (pathogens, predation, mast years). In the two reserves, mixed-beech forests near the timber-line included chronic, small-scale gap creation associated with the death of single, large trees or small groups of trees. The causes of death among relatively young trees were unknown, but no doubt multiple and thought to have resulted from either natural causes (windbreaks, pathogens, stem exclusion, severe drought) or anthropogenic influences (logging, air pollution). Natural and anthropogenic causes can also have a combined effect. Significant impacts were felt from the severe growth declines of silver fir in 1917–1923; 1943–1951 and 1976–1983 due to a combination of reduced rainfall (particularly in 1976) and increased air pollution (Becker 1985, 1989; Ulrich and Williot 1994). The air pollution is worst on the eastern slopes of the Upper Vosges near the timber line, coming from Eastern Europe (Becker 1985). These events explain the large numbers of dead silver firs in the two plots. Fir decline may be due to direct acid deposition on leaves, as well as acidification processes and nutrient deficiencies in soils with low buffering capacity. In GV and FM stands, however, soils derive from biotitic granite rock, the weathering of which is supposed to partially compensate for Ca and Mg losses. In both plots, soils should thus be less sensitive to acidification than in other parts of the Vosges mountains, like those with base-poor sandstone and acid granite catchments. Some small-scale gaps have probably expanded and coalesced in the past, thus explaining the succession of trees close in age. But there is also evidence of large-scale disturbance events during the period from 1780 to 1840 which might be of anthropogenic origin: there is historical evidence of frequent logging in forests just below summit pastures at the beginning of the 19th century (Garnier 1994, 1998) The deep shade cast by the beech and silver fir canopy explains why potential trees and regeneration are largely confined to gap margins. The tendency for regeneration and ground flora to form ellipsoid patches below canopy trees is typical of forest stands growing on very steep slopes into which sun flecks penetrate obliquely through foliage, thus displaying a multitude of sun flecks far from the gap (Pierrel 2001). Steep slopes play a role in the mutual influences seen between the light regime in understoreys and the canopy architecture. The steeper the slope, the shallower the soil and the lower the stem density (also related to altitude), the higher the canopy openness and penetration of incident light. In the Guebwiller mixed-beech forest canopy, openness averages 9.7% and only 2–15.7% of the total incident light is transmitted within the plot (Pierrel 2001). Light values are more important in GV and still more in FM. In the latter, the proximity of a [28]

1089 permanent gap further increases the lateral penetration of incident light. This explains why seedling densities are higher in FM and Acer pseudoplatanus can regenerate more easily there than in GV. Presence of that specie in FM have a retroactively impact and directly influences light arrival in the underlayer. A lot of Acer pseudoplatanus seeds is probably coming from outside, and thus Acer pseudoplatanus is probably invading the woodlands plots. Better light conditions also explain why potential trees and trees of the present have similar growth rates in FM: potential trees reach the canopy in 100 years, and their growth continues thereafter in the canopy at the same rhythm. In GV many potential trees have grown in shade, and growth rates are lower: the duration of the potential state lasts lasts 200 years or more. When potential trees arrive at full light, stem growth increases with the development of axes and foliage. Beech trees of the present however, grow less rapidly in GV than in FM which suggests less favorable growth conditions, probably due to the higher altitude. The present-day, large range of ages and sizes recorded between trees of the present in both plots can be interpreted as differences in growth patterns during tree development: (i.e. alternating suppressed and released-growing periods). Such growth processes have been recorded in all forests composed of shade trees (Leme´e 1978; Koop and Hilgen 1987; Peters 1992; Korpel 1995; Peterken 1996). Acer pseudoplatanus presents a different strategy based on its rather low tolerance for shade. Young Acer pseudoplatanus trees are numerous in open, rocky areas or at margins, where there is no suppression phase. Harsher conditions near the summits (for example, only 3 months of age at 900–1000 m) explain why canopy trees are smaller than in forests at lower altitudes: only 40 m high for 300-year-old silver firs near the crests as compared to 52–55 m for 180-year-old silver firs in the Guebwiller natural reserve (Renaud et al. 2000). In managed stands in the Vosges, some beech trees have been known to reach 42 m in 120 years (a 2–3 mm annual growth rate between ages 20–70 according to Seynave 1999) compared to only 29 m in height for a 214year-old beech in plots of similar density. In the virgin forest of Dobroc (720– 1000 m altitude, granite), Slovakia, there are 45 m beeches that are 230-yearsold (Korpel 1995). Multi-stemmed beech shape is a particularity of forests growing near the timber line. Such architecture only occurs under conditions of stress (Carbiener 1966; Peters 1992; Closset 2000). These trees are not lower in stature than single-stemmed trunks as suggested by Givnish (1984), but they are more slender than single tree trunk of similar age. Actually, competition between genetically identical trees has an impact of the lower volume of stem wood. They form large, very stable individuals in the canopy because a multistemmed growth form ensures better mechanical stability for the tree (ClossetKopp and Schnitzler (2000b), thus improving resistance to windthrow. Multi-stemmed individuals form clusters of genetically similar stems, with the

[29]

1090 potential for separate existence. This explains why stems may have different sizes and growth rates as related to age and social state. At the present stage in the evolution of the two plots, old trees are very rare. The three trees which are more than 300-years-old discovered in the plots are the only ones recorded in the upper Vosges to date, but clearly more studies could be done on this subject. The absence of very old trees differentiates forests of the Upper Vosges from other virgin mixed-beech forests in Europe where there are silver fir trees more than 400-years-old, and many more beech trees above the age of 350 (Mayer and Neumann 1981; Korpel 1995; Cenusa 2001; Schnitzler 2002). Given the present day composition of potential tree, we can predict that beech will dominate the canopy.

Objectives and priorities of woodland nature conservation in the upper Vosges Forest stands in the two reserves represent lesser-managed stands in the Upper Vosges, but human impacts have nonetheless been multiple, and often irreversible. Remnants of more natural forest stands are located near the summits and on steeper slopes, an inaccessibility which limits the data needed for a comprehensive analysis of forest dynamics. The present-day surface of strictly protected forests is also too small and too intermixed with managed forests and open landscapes to serve as reference points for management principles, because they are not representative enough of a completely pristine landscape. Given their rarity in Western Europe, these small areas must however be regarded as of utmost importance as a class of woodlands for nature conservation, research and education. A worthy objective of long-term conservation efforts would be to re-create more substantial examples of missing types of mixed-beech forests in the upper Vosges, and in the meantime, to leave unmanaged the remaining forests located in natural reserves.

Acknowledgment We gratefully acknowledge the Parc Naturel Regional des Ballons des Vosges for financial support through the study project from C. Schwoehrer. We are also much indebted to J.L. Dupouey for his invaluable assistance in dendrology and the logistical support of his laboratory (INRA Champenoux). We also wish to express their gratitude to Y. Despert, L. Domergue, C. Kieffer and P. Behr who have contributed core and data sampling.

References Becker M. 1985. Le de´pe´rissement du sapin dans les Vosges. Quelques facteurs lie´s a` la de´te´rioration des cıˆ mes. Revue Forestie`re Franc¸aise 37: 281–287.

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Biodiversity and Conservation (2006) 15:1095–1107 DOI 10.1007/s10531-004-1868-4


Springer 2006

-1

The effects of climate change on the long-term conservation of Fagus grandifolia var. mexicana, an important species of the Cloud Forest in Eastern Mexico OSWALDO TE´LLEZ-VALDE´S*, PATRICIA DA´VILA-ARANDA and RAFAEL LIRA-SAADE Laboratorio de Recursos Naturales, Unidad de Biologı´a, Tecnologı´a y Prototipos, Facultad de Estudios Superiores Iztacala UNAM., Av. de los Barrios 1, Los Reyes Iztacala, Tlalnepantla, C.P. 54090, Estado de Me´xico, Me´xico; *Author for correspondence (e-mail: [email protected]; phone: +01-55-56-23-11-27; fax: 01-55-56-23-12-25) Received 23 July 2003; accepted in revised form 22 July 2004

Key words: BIOCLIM, Bioclimatic modeling, Climate change, Cloud forest, Fagus, Sierra Madre Oriental Abstract. We examined the effects of climate change on the future conservation and distribution patterns of the cloud forests in eastern Mexico, by using as a species model to Fagus grandifolia Ehr. var. mexicana (Martı´ nez) Little which is mainly located in this vegetation type, at the Sierra Madre Oriental. This species was selected because it is restricted to the cloud forest, where it is a dominant element and has not been considered for protection in any national or international law. It is probably threatened due to the fact that it plays an important social role as a source of food and furnishing. We used a floristic database and a bioclimatic modeling approach including 19 climatic parameters, in order to obtain the current potential distribution pattern of the species. Currently, its potential distribution pattern shows that it is distributed in six different Mexican Priority Regions for Conservation. In addition, we also selected a future climate scenario, on the basis of some climate changes predictions already proposed. The scenario proposed is characterized by +2 C and
20% rainfall in the region. Under this predicted climatic condition, we found a drastic distribution contraction of the species, in which most of the remaining populations will inhabit restricted areas located outside the boundaries of the surrounding reserves. Consequently, our results highlight the importance of considering the effects of possible future climate changes on the selection of conservation areas and the urgency to conserve some remaining patches of existing cloud forests. Accordingly, we believe that our bioclimatic modeling approach represents a useful tool to undertake decisions concerning the definition of protected areas, once the current potential distribution pattern of some selected species is known.

Introduction The cloud forests represent one of the most interesting biological systems in the Neotropical region (Luna et al. 1999). They are usually rare, vulnerable and threatened in the world. Its northern distribution limit is the Sierra Madre Oriental, in the state of Tamaulipas, Mexico (Briones 1991) and its southern one reaches Argentina (Webster 1995). [35]

1096 In Mexico, the cloud forests are characterized by being island-like or archipelagic. In other words, they are arranged in isolated patches that usually bear a rich flora, with many endemic species (Rzedowski 1996; Luna et al. 2001). In the last years, the interest for studying the cloud forests, in particular their species richness and conservation, has been raised (Churchill et al. 1995). The reason for this interest is based on the high rates of deforestation and loss of cloud forests due to the introduction of cultivars, especially coffee (Moguel and Toledo 1999), but also to its irrational use for other agricultural activities, as well as for forestry and cattle farming purposes. It is recognized that these forests are threatened all over the world and that the damage that they have suffered is irreversible, due to their high disturbance vulnerability (Luna et al. 1988; McNeely et al. 1995). Fortunately, many of these forests are restricted to inaccessible sites in the mountains and consequently, they are still present and reasonably well conserved. In contrast, those located in places where human being has access have been drastically transformed to secondary pasture and cultivated lands. A few former studies have attempted the identification of priority areas for the conservation of the Mexican cloud forests, using Parsimony Analysis of Endemicity and other biogeographic approaches (Morrone and Crisci 1995; Morrone and Espinosa 1998). Even though these studies have highlighted the importance and need to protect the cloud forests, they have not considered either the probable effects that the climatic change might cause in their future survival, conservation and distribution patterns, nor the proposal of some general conservation strategies to be undertaken in the coming years. We believe this information is very relevant, in order to focus our efforts and resources to undertake accurate long-term conservation actions that can assure the survival of these unique plant communities. In particular, we decided to use Fagus grandifolia var. mexicana as our study model, due to its restricted distribution to the cloud forests. Although, this taxon has been also treated as F. mexicana (Lo´pez and Cha´zaro 1995), F. grandifolia Ehrh. var. mexicana (Martı´ nez) Little (Little 1965; Alca´ntara and Luna 2001), F. grandifolia Ehrh. (Johnston et al. 1989), or even as the subspecies Fagus subsp. mexicana (Shen 1992) that has not yet been published, we recognize the former as the accepted name. In accordance with the fossil record, Fagus grandifolia was present in eastern Asia during the late Oligocene and in western North America, including Alaska, during late Oligocene and early Miocene. However, its current distribution pattern is restricted to eastern North America (Canada and United States) and small patches of Mexico (Tamaulipas, Hidalgo, Veracruz y Puebla). The latter represent relictual areas of a former extensive cloud forest of Fagus grandifolia (Pe´rez 1994). Fagus grandifolia Ehrh. var. mexicana used to be a dominant and common tree representative of some of the Mexican cloud forests (Williams et al. 2003). Some of these cloud forests are restricted to the Sierra Madre Oriental, from the state of Tamaulipas in northeastern Mexico to the states of San Luis [36]

1097 Potosı´ , Quere´taro, Hidalgo, Puebla and Veracruz in central-eastern Mexico. In addition, we suspect that the species might be also present in the state of Oaxaca (Figure 1), but further fieldwork should be done to prove it. Even though, Fagus grandifolia var. mexicana is restricted to the cloud forests and plays an important social role, as a source of food and for furnishing activities (Malda 1990), it has not been considered as either a rare, threatened or endangered species (Vovides et al. 1997; Oldfield et al. 1998; Williams et al. 2003). However, some authors have already suggested the species rareness (Malda 1990; Lo´pez and Cha´zaro 1995). In particular, Perez (1994, 1999) considers that the species is endangered at the national level. He estimates that the total number of individuals of the species existing at the present is below 20,000. He also points out that the largest and most heterogeneous, genetically speaking, population is located at the state of Hidalgo, where 50% of the total number of individuals estimated for the country is located in this area. In addition, all these authors have highlighted the lack of nation and international laws for protecting and/or conserving the species.

Figure 1. Model of the potential distribution of Fagus grandifolia var. mexicana, on relationship to the known records. On the right corner the potential distribution of the species in the state of Oaxaca is shown. [37]

1098 Some recent data documenting the wild populations status of the species have been generated, especially in the states of Tamaulipas, Hidalgo and Veracruz (Williams et al. 2003). In some sites the species is considered extinct, whereas, in other places there are still some small patches of what used to be a cloud forest of Fagus grandifolia. So far, the species has not been recorded in the cloud forests of Quere´taro, which is a neighbor state of Hidalgo and San Luis Potosı´ and bears similar environmental conditions for hosting the species. Probably the absence of Fagus in Quere´taro is due to physiographic differences as suggested by Cartujano et al. (2002). However, it might be also possible that the species has been misidentified due to its morphological similarity to Carpinus sp., Ostrya sp. or Ulmus sp., as has been suggested by Lo´pez and Cha´zaro (1995). Thus, the purpose of this work is to undertake a comprehensive review of the current situation of the cloud forests in eastern Mexico by using Fagus grandifolia var. mexicana as our species model. Consequently, we attempted to undertake the following actions: (1) to document the current recorded distribution of the species in Mexico; (2) to obtain the potential distribution patterns of the species; (3) to assess the effects that the potential distribution pattern of the species might have, under a climatic change scenario; (4) to evaluate the role that the Protected Natural Areas and the Priority Regions of Mexico will be playing for the long-term conservation of cloud forests; (5) to propose a general strategy for attempting the conservation of the oriental Mexican cloud forests. Accordingly, the approach of this work includes the utilization of bioclimatic models that enable to explain the current situation of the eastern cloud forests of Mexico, on the basis of the potential distribution pattern of a representative species (Fagus grandifolia var. mexicana) that is used as a model. In addition, we present an attempt to assess the future distribution of the cloud forests, using the species data, once a predicted scenario due to climatic change is included (Te´llez and Da´vila 2003).

Methods The plant geographic distribution information that we used in this analysis was obtained from the database of the World Information Network of Biodiversity (REMIB) (http://www.conabio.gob.mx/remib/doctos/remibnodosdb.html). The herbarium data were obtained from the National Herbarium of Mexico (MEXU), from 29 specimens that beard geo-referenced information (i.e. complete latitude, longitude, and elevation). The taxonomical identification of the specimens was undertaken by Drs. Shen Shung-Fu and Kevin Nixon who are important specialists of the Fagaceae. On the other hand, the information concerning the vegetation structure and ecological attributes of the species that is included in the discussion of this work was obtained from relevant literature (Malda 1990; Lo´pez and Cha´zaro 1995; Luna et al. 2000; Williams et al. 2003). [38]

1099 The bioclimatic modeling approach used in this work was that of the program ANUCLIM (Houlder et al. 2000). The program uses mathematically and statistically interpolated climatic surfaces (digital files in raster format) that were estimated using the information obtained from a standard network of meteorological stations. The climatic surfaces or digital files were generated using thin plate smoothing spline methods in the ANUSPLIN package (Hutchinson 1991, 1995a, b, 1997; Hutchinson and Gessler 1994). These surfaces include long-term monthly mean values of precipitation and temperature from more than 6200 stations (4000 stations including temperature data and 6000 including precipitation data from the same set of stations). The estimated mean errors for those surfaces were between 8 and 13% for monthly precipitation values and about 0.4–0.5 C for temperature values. These errors are similar to those found in the standard meteorological instruments (Nix 1986). We produced a bioclimatic profile for Fagus grandifolia var. mexicana, using the program BIOCLIM. The derivation of the bioclimatic profile was based on selected-simple-matching thresholds. The values for each of the 19 bioclimatic parameters (Table 1), were assessed by a systematic scanning throughout a grid of data points. We used the profile to predict potential distribution pattern of the species. Using the homoclime matching principle, we identified those points on the climate grid, where the climatic conditions were present within the limits summarized in the bioclimatic profile of the species (Booth et al. 1987). We matched the bioclimatic profiles against a grid of data points that contained climatic data from the existing network of stations (bioclimatic

Table 1. Bioclimatic profile of Fagus grandifolia var. mexicana (Fagaceae). Parameter

Minimum–maximum (Mean ± SD)

Annual mean temperature (C) Mean diurnal range (C) Isothermality (2/7) (C) Temperature seasonality (C of V) (%) Maximum temperature of warmest period (C) Minimum temperature of coldest period (C) Temperature annual range (5–6) (C) Mean temperature of wettest quarter (C) Mean temperature of driest quarter (C) Mean temperature of warmest quarter (C) Mean temperature of coldest quarter (C) Annual precipitation (C) Precipitation of wettest period (C) Precipitation of driest period (C) Precipitation seasonality (C of V) (%) Precipitation of wettest quarter (C) Precipitation of driest quarter (C) Precipitation of warmest quarter (C) Precipitation of coldest quarter (C)

13.4–22.2 (16.6 ± 2.09) 8.2–15 (11.5 ± 1.88) 0.54–0.62 (0.59 ± 0.02) 0.61–1.1 (0.78 ± 0.17) 22.4–33.5 (26.3 ± 3.04) 5–9.9 (6.8 ± 1.16) 14.5–24.4 (19.5 ± 2.93) 14.3–24.7 (18 ± 2.72) 12.3–19.5 (14.6 ± 1.59) 15.5–25.6 (19.1 ± 2.48) 11–17.6 (13.4 ± 1.4) 824–2458 (1401 ± 367.19) 46–127 (75 ± 17.59) 0–15 (1 ± 3.67) 66–88 (77 ± 7.28) 418–1164 (691 ± 168.35) 52–201 (109 ± 42.39) 243–647 (397 ± 78.18) 52–239 (126 ± 54.41)

[39]

1100 parameters file). We used a regular grid of 30 arc seconds (0.00083 or approximately 1 km2) of spatial resolution. The geocoding errors were detected using the program ArcView 3.2. In addition, for a more detailed detection of anomalies and potential errors on the bioclimatic profiles, we used the program BIOCLIM (Houlder et al. 2000). Whenever possible, we corrected errors by using a 1:50,000 scale topographic maps. Fortunately, a single anomalous record was detected and removed. Finally, although the magnitude of climate change is uncertain and many different future scenarios have been proposed, we generated just one climate scenario, as proposed by Karl (1998) and some other authors, whom have predicted similar future climatic conditions (Canziani and Diaz 1998; Giorgi et al. 1998; Neilson 1998). The program BIOCLIM was used, in order to set up the proposed future climate change scenario (year 2050), which shows a temperature increment of 2 C and a precipitation decrement of 20%, for any given present point, at the latitude and longitude where the range and the localities of the species are located. For inserting the climate change scenario, we produced a grid of indices in ARCINFO ASCIIGRID format through the BIOCLIM program and the Digital Elevation Model (DEM). The predicted distribution patterns of the selected species were plotted to represent the future potential distribution patterns found, after climate change conditions were entered. In this paper we only present the results of an extreme scenario for assessing the role the Priority Regions for Conservation (PRCs) proposed by CONABIO (Arriaga et al. 2000), will play in the future. The area covered by the potential distribution of the species was calculated with ArcView 3.2 (ESRI 2000).

Results The results obtained suggest that the present distribution pattern known for Fagus grandifolia var. mexicana, is indeed correct and complete, due to the fact that in all cases, the collecting sites fitted within the limits of the potential distribution area obtained in the analysis (Figure 1). Thus, the species is restricted to the Sierra Madre Oriental from the state of Tamaulipas to southern Veracruz, as has been stated by Williams et al. (2003). However, on the basis of the potential distribution assessment of the species, we believe that probably its southern limit might extend to the state of Oaxaca. However, field verifications should be done before we can assure it (Figure 1). The results also point out that the species is restricted to unique climatic conditions in the Sierra Madre Oriental, as it is shown in its bioclimatic profile (Table 1). Its climatic uniqueness represents the specific spots or areas along the Oriental Sierra Madre where it can grow. In other words, although we state that Fagus grandifolia var. mexicana grows along the Sierra Madre, the fact is that it only grows in some specific areas that have a unique combination of climatic attributes and do not grow in others that have other climatic features. [40]

1101 On the basis of the species current potential geographic range, it is evident that it would be distributed in six Priority Regions for Conservation (Arriaga et al. 2000): (1) El Cielo Biosphere Reserve in the State of Tamaulipas, (2) Sierra Gorda-Rı´ o Moctezuma in the State of Quere´taro, (3) Cloud Forest of the Sierra Madre Oriental in the States of Hidalgo, Veracruz and Puebla, (4) Cuetzalan in the State of Puebla, (5) Pico de Orizaba-Cofre de Perote in the State of Veracruz and, (6) Oaxacan northern Sierra. The current potential distribution model of Fagus (the climatically suitable environments for the development of this species), covers about 5800 km2. However, once the climate change scenario was introduced, its potential distribution pattern contracts drastically in more than 66%. The remaining sites that will be suitable for the establishment of Fagus populations will be covering about 1700 km2 or in other words, about 1/3 of the original potential distribution range, including parts of the states of Quere´taro, Hidalgo, Puebla, and a very small portion of the state of Veracruz (Figure 2). Due to its drastic distribution pattern contraction, the remaining Fagus patches will probably coincide with only three of the Priority Regions for Conservation (PRCs 2, 3 and 4) in the states of Quere´taro, Hidalgo and Puebla and none will be present in the state of Veracruz (Figure 2).

Figure 2. Model of the potential distribution of Fagus grandifolia var. mexicana on relationship to the Priority Regions for Conservation (CONABIO), once the proposed climate change scenario was entered. [41]

1102 Discussion Independently of the taxonomical uncertainty of the studied taxon (whether it is a species, a variety or a subspecies), evidently, it is seriously threatened due to its intensive wood extraction, habitat fragmentation and the expansion of the agricultural land use in areas where it naturally grows. In addition, its restricted presence in the cloud forests increases its risk. Currently, the populations of Fagus grandifolia var. mexicana are distributed within the boundaries of at least five Priority Regions for Conservation (Arriaga et al. 2000), although the one from Oaxaca, remains to be proved. From them, the El Cielo Biosphere Reserve represents the only Protected Natural Area that has been officially declared. Consequently, the future protection of the cloud forest, Fagus grandifolia var. mexicana and other animal and plant species of the area is uncertain. The protection uncertainty of Fagus, has already been pointed out by Williams et al. (2003) and mentioned the extinction of the species populations from Teziutla´n, Puebla. In the case of the populations located at the Biosphere Reserve of El Cielo, in the state of Tamaulipas, the agricultural and cattle farming activities have caused a dramatic reduction of the cloud forest. Now, when the climatic change scenario is added to the current situation, the questions to be answered are the following: (1) Is it feasible to have a long-term conservation strategy to protect the cloud forest of the state of Tamaulipas and Puebla? and (2) Where do we have higher probabilities of conserving wellpreserved cloud forests in Mexico? It is clear that the cloud forest of Tamaulipas is already under strong disturbance pressures and consequently its structure and diversity has been already drastically altered. On the other hand, we believe that these communities are currently less modified in the states of Quere´taro and Hidalgo. Now, if in addition, the climate changes occur as it is proposed, the results obtained show that these states also seem to be the adequate cloud forest reservoirs, as has been partially suggested formerly by Luna et al. (2000). Alcantara and Luna (1997), mentioned that Hidalgo represents the state where the cloud forests in Mexico reach their larger extent. They also pointed out that in the central-eastern part of Hidalgo, this plant community still remains in the form of wealthy patches that cover around 100 km2 or more. In these patches, a total of 114 families, 301 genera and 452 species have been recorded by them. Several species of the region are listed in the Mexican Norm NOM-059-ECOL-2000 (Ano´nimo 2000), as vulnerable or in danger of extinction, such as Cyathea fulva, Deppea hernandezii, Nopalxochia phyllanthoides, Magnolia schiedeana, Rhynchostele rosii, Chamaedorea elegans, Psilotum complanatum, Symplocos coccinea and Ceratozamia mexicana (Vovides et al. 1997; Alcantara and Luna 1997). Consequently, Luna and Alca´ntara (2002) emphasize the need to focus the cloud forest conservation efforts in the state of Hidalgo, where many endemic plant species for Mexico have been recorded, such as Bouvardia martinezii, [42]

1103 Carya palmeri, Ceratozamia mexicana, Cyathea mexicana, Dalbergia palo-escrito, Deppea hernandezii, D. microphylla and Magnolia dealbata, among others. In addition, these authors pointed out that some other taxa of the cloud forests that are disjunct between Mexico and the United States show very restricted distribution ranges in Mexico, as in the case of Illicium floridanum, Nyssa sylvatica and Schizandra glabra. In summary, this mixture of hardly known, rare and threatened species is part of a unique natural system that not only bears taxa from different ancestral biotas, but also has high rates of species richness and endemicity, as well as, a very fragile habitat that unfortunately do not have any kind of protection. In the case of the cloud forests of the states of Quere´taro, it is documented that it bears a very rich flora and plant communities. Cartujano et al. (2002), recorded 130 families, 465 genera and 774 species of vascular plants in the cloud forests of the eastern portion of this State. Among this diverse flora, a number of endemics to Mexico or restricted endemics to the Sierra Madre Oriental are included (Cinnamomum bractefoliaceum, Clethra kenoyeri, C. pringlei, Ilex condensata and Inga huastecana, among others), as well as, some species listed as vulnerable, rare, or threatened (Magnolia dealbata, Tilia mexicana, Carpinus caroliniana and Litsea glaucescens, among others) under the Mexican Norm of Endangered Species NOM-059-ECOL2000. Despite the floristic richness and rareness of the cloud forests, timber extraction, livestock grazing and conversion of forest to farmland, which is risking its long-term conservation, represent the main recent disturbance sources of these forests. Unfortunately, precise assessments of the current destruction rate of these forests have not been done (Pe´rez 1994, 1999). Although, in the particular case of cloud forests there is not any former record documenting their probable shifts due to climate change in Mexico. A similar exercise assessing future distribution patterns of some cacti species was done by Te´llez and Da´vila (2003), in a semiarid region of central Mexico. They showed the drastic contraction of some of the cacti species potential distribution patterns, once the climatic changes conditions were included. In summary, in this work we attempted to highlight the importance of including the best biological knowledge available (geographic distribution, vegetation structure and ecology) and a bioclimatic modeling technique to assess the possible present and future role of any reserve or protected area. We also wish to emphasize the need to include Information concerning current and future environmental conditions and the potential distribution patterns of plants and animals, should be included in the decisions for selecting and establishing any reserve or protected area. Due to the methodology and the available data used, it is important to consider that the results obtained in this study might be slightly biased by some unrecorded errors or even by the lack of enough information. The

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1104 inclusion of only 29 records data for the model generation, might seems not representative of the species distribution pattern. However the records used cover, in general terms, all the environmental conditions that theoretically the species might occupy (the geographic, ecological and altitudinal range of the taxon). In addition, natural systems complexity represents a challenge for undertaking a modeling approach. In particular, the evident limitation of the bioclimatic models is the lack of inclusion of information concerning biotic interactions, evolutionary changes, as well as relevant biological processes such as dispersion (Pearson and Dawson 2003). Consequently, the existence of certain degree of errors is probably unavoidable. Also, the bioclimatic data, due to its own nature, shows two kinds of errors: (1) the omission (= the lack of consideration of the space that is occupied by the niche; (2) commission (= the consideration of a space that is not occupied by the niche). Consequently, each algorithm used to model a species ecological niche, has a combination of commission and omission errors (Peterson and Vieglais 2001). Even though, the existence of these errors is recognized, we believe that the bioclimatic modeling represents a useful tool or starting point for understanding the current and potential distribution patterns of animals and plants. Its usefulness has already been proved for some species at certain scales, in which this approach has generated relevant information (Pearson and Dawson 2003). In the case of this study, the model clearly reflects that the spatial climatic resolution used to correlate it to the species records that were included, enabled a precise and solid bioclimatic profile of Fagus. Finally, we believe that with the present biological information, it is feasible and recommendable to carry out a similar exercise for other plant groups. Endemic species and main elements of plant communities should be especially important to be submitted to a bioclimatic modeling. By this means, we can increase the probability of proposing adequate conservation strategies. In the particular case of this study, the results obtained show that through the bioclimatic approach, we can be able to focus in long-term management, planning, and development of new, flexible, and dynamic forms of wildlife and resource conservation (Nix 1986; Lindenmayer et al. 1991; Te´llez and Da´vila 2003).

Acknowledgements We thank to the anonymous reviewers for their valuable comments and corrections. To PAPCA 2002 program of the FES Iztacala UNAM for the financial support to carry out part of this study.

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1106 Hutchinson M.F. and Gessler P.E. 1994. Splines – more than just a smooth interpolator. Geoderma 62: 45–67. Johnston M.C., Nixon K., Nesom G.L., and Martı´ nez M. 1989. Listado de plantas vasculares conocidas de la Sierra de Guatemala, Go´mez Farı´ as, Tamaulipas, Me´xico. Biotam 1: 21–33. Kappelle M., Van Vuuren M.M.I. and Baas P. 1999. Effects of climate change on biodiversity. A review and identification of key research issues. Biodiv. Conserv. 8: 1383–1397. Karl T.A. 1998. Regional trends and variation of temperature and precipitation. In: Watson R.T., Zinyowera M.C., Moss R.H. and Dokken D.J. (eds), The Regional Impacts of Climate Change: An Assessment of Vulnerability. Special Report of IPCC Working Group II. Cambridge University Press, Cambridge, UK, pp. 411–425. Lindenmayer D.B., Nix H.A., McMahon J.P., Hutchinson M.F. and Tanton M.T. 1991. The conservation of Leadbeater’s possum, Gymnobelideus leadbeateri (McCoy): a case study of the use of bioclimatic modelling. J. Biogeogr. 18: 371–383. Little E.L. Jr. 1965. Mexican beech, a variety of Fagus grandifolia. Castanea 30: 167–170. Lo´pez M.L. and Cha´zaro B.M. 1995. Plantas len˜osas raras del bosque meso´filo de montan˜a. I. Fagus mexicana Martı´ nez (Fagaceae). Boletı´ n de la Sociedad Bota´nica de Me´xico 57: 113–115. Luna V.I., Almeida L., Villers L. and Lorenzo L. 1988. Reconocimiento florı´ stico y consideraciones fitogeogra´ficas del bosque meso´filo de montan˜a de Teocelo, Veracruz. Boletı´ n de la Sociedad Bota´nica de Me´xico 48: 35–63. Luna V.I., Alca´ntara A.O., Espinosa O.D.E. and Morrone J.J. 1999. Historical relationships of the Mexican cloud forests: a preliminary vicariance model applying Parsimony Analysis of Endemicity to vascular plant taxa. J. Biogeogr. 26: 1299–1306. Luna V.I., Alca´ntara A.O., Morrone J.J. and Espinosa O.D.E. 2000. Track analysis and conservation priorities in the cloud forests of Hidalgo, Mexico. Div. Distribut. 6: 137–143. Luna V.I., Morrone J.J., Ayala A.O. and Organista D.E. 2001. Biogeographical affinities among Neotropical cloud forests. Plant Systemat. Evol. 228: 229–239. Malda G.B. 1990. Plantas vasculares raras, amenazadas y en peligro de extincio´n en Tamaulipas. Biotam 2: 55–61. McNeely J.A., Gadgil M., Leveque C., Padoch C. and Reedford K. 1995. Human influences on Biodiversity. In: Heywood V.H. and Warton R.T. (eds), Global Diversity Assessment. Cambridge University Press, Cambridge, UK pp. 711–821. Moguel P. and Toledo M.V.M. 1999. Biodiversity conservation in traditional coffee systems of Mexico. Conserv. Biol. 13(1): 11–21. Morrone J.J. and Crisci J.V. 1995. Historical biogeography: introduction to methods. Annu. Rev. Ecol. Systemat. 26: 373–401. Morrone J.J. and Espinosa M.D. 1998. La relevancia de los atlas biogeogra´ficos para la conservacio´n de la biodiversidad mexicana. Ciencia (Me´xico) 49: 12–16. Nix H.A. 1986. A Biogeographic analysis of Australian elapid snakes. In: Longmore R. (ed.), Atlas of the Elapid snakes of Australia. Flora and Fauna. 7: 4–15. Neilson R.P. 1998. Simulation of regional climate change with global coupled climate models and regional modelling techniques. In: Watson R.T., Zinyowera M.C., Moss R.H. and Dokken D.J. (eds), The Regional Impacts of Climate Change: An Assessment of Vulnerability. Special Report of IPCC Working Group II. Cambridge University Press, Cambridge, UK, pp. 439–456. Oldfield S.F., Lusty C. and MacKinven A. 1998. The World List of Threatened Trees. World Conservation Press. Pearson R.G. and Dawson T.P. 2003. Predicting the impacts of climate change on the distribution of species: are bioclimate envelope models useful? Global Ecol. Biogeogr. 12: 361–371. Pe´rez P.M. 1994. Revisio´n sobre el conocimiento dendrolo´gico, silvı´ cola y un censo de las poblaciones actuales del ge´nero Fagus en Me´xico. Tesis de maestrı´ a (Biologı´ a). Facultad de Ciencias. Universidad Nacional Auto´noma de Me´xico, Me´xico, DF, 146 pp.

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1107 Pe´rez P.M. 1999. Las hayas de Me´xico.Monografı´ a de Fagus grandifolia spp. mexicana. Universidad Auto´noma Chapingo, Chapingo, Me´xico, 51 pp. Peterson A.T. and Vieglais D.A. 2001. Predicting species invasions using ecological niche modeling: new approaches from bioinformatics attack a pressing problem. BioScience 51: 363–371. Rzedowski J. 1996. Ana´lisis preliminar de la flora vascular de los bosques meso´filos de montan˜a de Me´xico. Acta Bota´nica mexicana 35: 25–44. Pe´rez P.M. 1999. Las hayas de Me´xico.Monografı´ a de Fagus grandifolia spp. mexicana. Universidad Auto´noma Chapingo, Chapingo, Me´xico, 51 pp. Shen C.F. 1992. A monography of the genus Fagus Tourn. ex. L. (Fagaceae). Dissertation, City University of New York, New York. Te´llez V.O. and Da´vila A.P. 2003. Protected areas and climate change: a case study of the cacti in the Tehuaca´n-Cuicatla´n biosphere reserve, Me´xico. Conserv. Biol. 17(3): 846–853. Vovides A.P., Luna V. and Medina G. 1997. Relacio´n de algunas plantas y hongos mexicanos raros, amenazados o en peligro de extincio´n y sugerencias para su conservacio´n. Acta Bota´nica Mexicana 39: 1–42. Webster G.L. 1995. The Panorama of Neotropical Cloud Forests. In: Churchill S.P., Balslev H., Forero E. and Luteyn J.L. (eds), Biodiversity and Conservation of Neotropical Montane Forestes. Proceedings of the Neotropical Montane Forest Biodiversity and Conservation Symposium. The New York Botanical Garden, 21–26 June 1993, New York, pp. 53–77. Williams L.G., Rowden A. and Newton A.C. 2003. Distribution and stand characteristics of relict populations of Mexican beech (Fagus grandifolia var mexicana). Biol. Conserv. 109: 27–36.

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Biodiversity and Conservation (2006) 15:1109–1128 DOI 10.1007/s10531-004-2178-6


Springer 2006

Genetic diversity of Dalbergia monticola (Fabaceae) an endangered tree species in the fragmented oriental forest of Madagascar OLIVARIMBOLA ANDRIANOELINA1, HERY RAKOTONDRAOELINA2, LOLONA RAMAMONJISOA1, JEAN MALEY3, PASCAL DANTHU4 and JEAN-MARC BOUVET5,* 1

Silo national des Graines Forestie`res, Ambatobe BP 5091, Antananarivo, Madagascar; 2PCP Foreˆts et Biodiversite´/Fofifa DRFP BP 904, Antananarivo, Madagascar; 3Institut des Sciences de l’Evolution Universite´ de Montpellier II, cc 065, Universite´ Montpellier 2, Place Euge`ne Bataillon, 34095 Montpellier Cedex 05, France; 4PCP Foreˆts et Biodiversite´/Cirad, BP 853, Antananarivo, Madagascar; 5Cirad-Foreˆt, Campus international de Baillarguet TA10/C, BP 5035, 34398 Montpellier Cedex, France; *Author for correspondence (e-mail: [email protected]; phone: +33-467593728; fax: +33-467593733) Received 25 February 2004; accepted in revised form 2 August 2004

Key words: Chloroplast microsatellites, Conservation, Gene flow, Genetic structure, Post-glacial recolonisation, RAPD Abstract. There is an urgent need to maintain and restore a broad genetic base for the management of Dalbergia monticola, a very economically important but endangered tree species in Madagascar. Random amplified polymorphism DNAs (RAPDs) and chloroplast microsatellite markers were used to quantify the genetic variation and to analyse the geographic distribution of diversity. Ten locations covering most of the natural range were sampled. Sixty-three RAPD polymorphic and 15 monomorphic loci were obtained from 122 individuals. Genetic diversity was low and very close among populations and regions. The unrooted neighbour-joining tree exhibited 4 groups, representing 6% (p = 0.000) of the total variation. The greater part of the variance, 81%, was observed within populations. A Mantel test suggested that genetic distances between populations were weakly correlated with geographic distances (R = 0.46, p = 0.12). The three chloroplast microsatellite primers assayed on 100 individuals gave 13 chlorotypes. Most of the populations showed 2 or 3 haplotypes. Haplotype diversity for the total population was equal to HeCp = 0.83 and ranged from 0.00 to 0.80 among the populations. The unrooted neighbour-joining tree exhibited 4 groups corresponding to the four regions representing 80% (p = 0.0000) of the total variation. Genetic diversity varies with regions, the north and south being less variable. Chlorotype distribution, the phylogenetic tree and historical information suggest that putative refugias in the centre-north region originating from the early Holocene could explain the pattern of variation observed today. By combining the results obtained at nuclear and organellar loci, a strategy of conservation based on evolutionarily significant units is proposed.

Introduction The separation from Gondwana, 158–160 million years ago, has led to high endemism in Madagascar recognised as one of the most original in the world (Myers et al. 2000; Briggs 2003). About 80% of the plant species are endemic and the richness of fauna and flora is great. Present patterns of the Malagasy [49]

1110 ecosystem have been determined by numerous factors such as climate change and human practices. Glaciation cycles, and especially the last maximum glaciation, are known to have had a strong impact on Malagasy species distributions (Burney 1996; Gasse and Van Campo 2001). Although known human presence is not very ancient in the island, 2000 years BP, practices such as fire have also markedly influenced the distribution of species, especially since the 15th century (Straka 1996). The highlands would have first undergone the action of fire and today are covered with grass. More recently, over the two last centuries, the oriental forests have decreased dramatically due mainly to ‘‘slash and burn’’ practices. Today, primary vegetation probably still covers about 10% of the original area (Myers et al. 2000), so dense forest has been reduced to a fragmented landscape. In addition, forest exploitation has greatly increased over the last 50 years due to rising demand for wood as energy and saw timber. The combination of fragmentation and overexploitation threatens some economically and ecologically important tree species and a conservation strategy for these forest trees is urgently needed. Much research remains to be done to improve basic biological knowledge but, as a broad genetic base is required to maintain the evolutionary process and to preserve the gene pool, assessment of within-species genetic variation can be a useful tool when starting a conservation strategy (Newton et al. 1999; Cavers et al. 2003). Among methodologies employed to assess variation, those based on molecular markers are widely used with forest tree species (Newton et al. 1999). Random amplified polymorphism DNA (RAPD) is one of the most popular DNA-based approaches (Bekessy et al. 2002). It is the least technically demanding and offers a fast method of providing information from a large number of loci, particularly in species where no study has been undertaken. Moreover, the diversity assessed by RAPD is comparable to that obtained with allozymes or RFLP (Wu et al. 1999; Esselman et al. 2000). There are some limitations, however, owing to their lack of reproducibility, and dominance prevents the distinction between homozygous and heterozygous individuals (Gillies et al. 1997). Chloroplast DNA markers are often used to study genetic diversity and structure, especially in combination with nuclear ones (Viard et al. 2001) and have provided useful information on colonisation and dispersal in plant species. Chloroplasts are maternally inherited in most angiosperms and paternally inherited in gymnosperms, so the level of differentiation is greater than bi-parental inheritance. Chloroplast microsatellite markers (cpSSRs) present high polymorphism and are now frequently used in phylogeographic forest tree analyses (Marshall et al. 2002; Palme´ and Verdramin 2002; Collevatti et al. 2003; Grivet and Petit 2003). Although molecular techniques have been widely used in tree species, no studies have been undertaken for Malagasy tree species. In this study we used both RAPD and cpSSRs to investigate the pattern of variation at the natural range scale of a species of rosewood: Dalbergia monticola Baker. This species is one of the major components of the oriental [50]

1111 forest of Madagascar but, for the reasons mentioned previously, it is threatened in its natural stands. Little research has been undertaken that provides information on ecological patterns and no information is available on genetic variation across the species range. The aims of this study were then (i) to quantify the genetic variation within and between populations using these two molecular markers, (ii) to analyse the geographic distribution of diversity in the natural range, and (iii) to define a conservation strategy based on molecular diversity.

Material and methods Species description – plant material Dalbergia monticola’s natural range extends from the northern part of Madagascar (region of Antalaha 15 latitude south) to the southern part (region of Fort Carnot 22 latitude south) forming a fragmented belt 1000 km long and 100 km wide (see the map in Figure 4). Adult trees frequently reach 20 m in height and 1 m in diameter at chest height. Recognised as a long-lived tree species (over 200 years), the natural populations are situated in two main climaxes: the submontane evergreen seasonal forest and the dense rainforest, of altitude ranging from 350 to 1600 m, mean temperature from 18 to 23 C, and mean annual rainfall from 750 to 2500 mm. Dalbergia monticola reproduces mostly sexually and is mainly insect pollinated, flowering and fruiting from August to November, with some geographical variations. It fruits between July and September. The species is mainly barochorous, but its seeds can also be dispersed by animals such as birds, monkeys, and rodents, although no research has been conducted on this. Ten locations were identified, covering most of the natural range from the north to south of the island (Table 1), to sample the species. Within each location, between 6 and 25 trees were chosen randomly in fragmented forest. Due to the lack of trees in some sampling areas, the minimum distance between two consecutive trees was in some cases only 20 m (see range of distance in Table 1). The trees were generally small, most of them having a total height of 5–20 m and a diameter of 15–30 cm. This observation stresses the lack of adult trees due to the intense exploitation of the species. Five healthy leaves were collected from each tree and dried rapidly in the field using silica gel.

DNA extraction DNA was extracted from dried leaves, following the modified protocol described by (Bousquet et al. 1990). Leaves (100 mg) were ground to a fine powder with a [51]

1112 Table 1. Characteristics of the Dalbergia monticola populations sampled in the natural range. Region Location

N

Latitude Longitude Rainfall (mm)

T Elevation Distancea min–max C (m) (m)

North

12 10 17 11 11 10 7 6 25 20 139

1657¢S 1705¢S 1810¢S 1755¢S 1745¢S 1906¢S 1902¢S 1918¢S 2116¢S 2134¢S

12–28 12–28 12–29 12–29 12–29 10–26 10–26 10–26 17–27 10–26

Tsaramolotra Ampitsongona Centre- Didy north Antsevabe Ambohijahanary Centre Bekorakaka Madiorano Ankeniheny South Ranomafana Tolongoina Total a

4844¢E 4842¢E 4835¢E 4832¢E 4835¢E 4821¢E 4812¢E 4823¢E 4726¢E 4732¢E

750 750 1240 1240 1240 1790–2190 1790–2190 1790–2190 2900 2800

900–1200 900–1200 800–900 800–900 800–900 850–900 800–1100 800–1100 900–1000 800–1200

50–500 50–500 20–50 20–100 50–1500 50–1000 100–1500 100–500 20–200 20–1000

range of distance between two consecutive sampled trees.

mortar and pestle in a 1.5 ml Eppendorf tube under liquid nitrogen. DNA extraction buffer (5 ml) was added (100 mM Tris–HCl (pH 8.0), 20 mM EDTA, 1.4 M NaCl, 1% PEG 6000, 2% MATAB, 0.5% sodium sulphite). The tube was then incubated at 74 C for 20 min. Samples were washed with wet chloroform (CIAA, 24:1) to remove cellular debris and protein. After 15 min of centrifugation at 5000 · g, the liquid phase was transferred to 15 ml tubes. Isopropanol (5 ml) was added and mixed gently to precipitate the DNA. The resulting DNA pellets were resuspended in 400 ll of sterile water overnight at 37 C and stored at
20 C until required.

RAPD methods PCR amplifications were performed in a 20 ll reaction mix with 5 ll of DNA (3 ng/ll), 2 · buffer, 0.2 lM of each primer (OPB7, OPB11, OPN15, OPR15, OPW9, OPW12, OPW13, OPW14, OPX3, OPX6, OPX10), 5 U/ll of DNA Taq polymerase, completed with sterile water. The reaction mixture was overlaid with 40 ll of sterile mineral oil to prevent fluid evaporation. All reactions were performed in Techne Cyclogene. Optimal amplification conditions for RAPDs were 1 cycle of 3 min at 94 C (initial denaturation), followed by 45 cycles of 4 min at 94 C (denaturation), 1 min at 36 C (annealing) and 2 min at 72 C (extension). A final step of 10 min at 72 C ensured full extension of all amplified products. RAPD bands were separated in 1.5% agarose gel, staining in ethidium bromide and visualised by UV transillumination. To reduce errors in comparison of RAPD profiles between different PCR runs, the same 10 individuals were included in all PCR runs. Only RAPD bands that could be unequivocally scored were counted in the analysis. Bands of weight higher than 1700 bp and molecular weight lower than 300 bp were [52]

1113 not used so as to ensure good repeatability of the RAPD process and avoid misscoring.

Chloroplast microsatellite method Three universal microsatellite primers (Ccmp4, Ccmp6 and Ccmp7) described by Weising and Gardner (1999), and 1 tobacco microsatellite (Ntcp9) described by (Bryan et al. 1999) were tested over a subset of the total population. Among the 4 primer pairs tested in a sample of 8 individuals, 3 were polymorphic (Ccmp4, Ccmp6, and Ccmp7). For the primers Ccmp, PCR amplifications were done in a 8 ll reaction mix with 2 ll of DNA, 2 · buffer, 10 lM of each primer (R and F), 5 U/ll of DNA Taq polymerase, completed with sterile water. All reactions were performed in a ‘‘Stratagene’’ Thermocyclor. Optimal amplification conditions were 1 cycle of 4 min at 94 C (initial denaturation), following by 30 cycles of 30 s at 94 C (denaturation), 1 min at 56 C (annealing) and 1 min at 72 C (extension). A final step of 5 min at 72 C ensured full extension of all amplified products. PCR amplifications were done for the 9 primers in a 20 ll reaction mix with 5 ll of DNA, 10 · buffer, 2 lM of each primer (R and F), 5 mM of dNTPs, 50 mM of MgCl2, 99% of glycerol, 5 U/ll DNA Taq polymerase, completed with sterile water. Amplification conditions are similar, except for the annealing temperature which is 55 C. Bands were separated and visualised in acrylamide gel.

Data analysis In the case of RAPD data, amplified DNA marker bands were scored in a binary manner as either present (1) or absent (0) and entered into a binary data matrix. Each PCR product was assumed to represent a single locus because homology is generally high at the intraspecific level. The frequency of each band and the percentage of polymorphic loci (%P) were calculated in each population. Shannon’s diversity index was P used to assess molecular variation. This parameter, defined as IRAPD =
i¼2 i¼1 pi log2 pi, where pi is the frequency of the RAPD phenotype (presence (1) or absence (0) of the band), is frequently used in the absence of assumptions concerning the Hardy–Weinberg equilibrium (Gillies et al. 1997; Martin and Hernandez Bermejo 2000). It was calculated for each locus and averaged over loci to provide the degree of variation within each population, IRAPDpop. Shannon’s index was also estimated for the whole sample considered as a single population, IRAPDtot. The expected genetic heterozygosity P Her was estimated with the fixation index F equal to zero. HeRAPD ¼ 1
ni¼1 p2i (where pi is the frequency of the allele i in a population), [53]

1114 and the other diversity parameters, number of haplotypes (na), effective number of haplotypes (ne ¼ 1 Pn1 2 , where pi is the frequency of the allele i in p i¼1 i

a population), percent of polymorphic RAPD loci (%P) and their standard errors were calculated with Popgene 1.32. (Yeh and Boyle 1997). For cpSSRs, because of the non-recombining nature of the chloroplast genome, cpDNA haplotypes were treated as alleles at a single locus. Chloroplast haplotype variation within populations was calculated with the same parameters as for RAPD (ICp HeCp ne) with Popgene software version 1.32. (Yeh and Boyle 1997). The genetic structure, for RAPD and cpSSRs, was estimated using analysis of molecular variance, AMOVA (Excoffier et al. 1992), with Arlequin software version 2000 (Schneider et al. 2000). The percentage variance within and among populations were estimated to partition the variation, and the associated P value was estimated with permutation techniques. To illustrate the genetic structure obtained with the two markers, a cluster analysis using the neighbour-joining method was conducted with the software package DARwin 4.0 (Perrier et al. 2003). The matrix of genetic distances was calculated using the AMOVA-derived Fst. The levels of differentiation among populations estimated from AMOVA for nuclear markers (FstRAPD) and chloroplast markers (FstCp) could be used to derive the pollen-to-seed migration ratio, using the following formula of (Ennos 1994): r ¼ mp =ms ¼ ½ðð1=FstRAPD Þ
1Þ
2ðð1=Fstcp Þ
1Þ=½ð1=Fstcp Þ
1Þ where mp and ms are pollen and seed migration rates, respectively. In the case of RAPDs the value is biased, and probably overestimated, due to the amplification of the cytoplasmic genome. The association between geographic and genetic distances was estimated as a Spearman’s rank correlation coefficient (q). The null hypothesis of the association was tested with the Mantel test using Fstat software (Goudet 2001). Minimum spanning networks between haplotypes (each network embedding all minimum spanning trees for a given distance matrix) were computed with the MINSPNET (Excoffier and Smouse 1994), provided with Arlequin software version 2000 (Schneider et al. 2000). The distance matrix between haplotypes was calculated using a distance matrix based on the square of the difference in microsatellite size with the formula Dij ¼

L X

ðail
ajl Þ2

l¼1

where aij and ajl give the allele size in base pairs at the lth locus of individuals i and j, respectively. [54]

1115 Results Genetic diversity and structure with RAPD markers The 15 random primers generated a total of 65 RAPD polymorphic and 13 monomorphic loci ranging in size from 152 to 340 bp. This set of loci is expected to give a good sampling of the total genome and a good assessment of the genetic diversity. The number of bands per primer varied from 1 to 7. Table 2 shows that the diversity parameter for the total population was equal to 0.19 (0.15) and varied from 0.09 (0.16) for the population of Ankeniheni in the centre to 0.19 (0.21) for the population of Ambohijanahary in the centre north. Shannon’s diversity index followed the same pattern of variation, with a value for the total population equal to 0.30 (0.21) and a range between 0.15 (0.24) in Ankeniheni to 0.28 (0.27) in Ambohijanahary. The percentage of polymorphic loci varied from P = 30% in Ankeniheni to P = 65% in Didy (Table 2) and the total population value was 83%. Although differences between populations for na, ne, HeRAPDand IRAPD were marked, they were smaller than the standard deviation. No pattern of variation for na, ne, IRAPD, HeRAPD and %P was observed among the set of populations. For example, the relationship between diversity parameters and latitude was low, and the coefficient of correlation between latitude and IRAPD was equal to R = 0.08, (associated p value = 0.80). When the four regions were compared, no specific trend was observed for the diversity parameter (Table 3). The differences between the parameters were lower than the standard error. The differentiation assessed among populations was marked. The analysis of molecular variance showed that 76% (p = 0.000) of the variation was present

Table 2. Population size (N), number of haplotypes (na), effective number of haplotypes (ne), Shannon’s index (IRAPD), percent of polymorphic RAPD loci (%P), RAPD diversity (HeRAPD) for each population. The standard error of each parameter is given between brackets. Country

Population

N

na

ne

HeRAPD

IRAPD

%P

North

Tsaramalotro Ampisotgoina Ambohijanahary Antsevabe Didy Bekorokaka Madiorano Ankeniheny Ranomafana Tologoina

11 10 11 11 17 10 6 6 21 19 122

1.51(0.50) 1.49(0.50) 1.60(0.49) 1.43(0.50) 1.65(0.48) 1.52(0.50) 1.41(0.50) 1.30(0.46) 1.64(0.48) 1.52(0.50) 1.83(0.38)

1.21(0.30) 1.23(0.31) 1.30(0.35) 1.24(0.34) 1.25(0.29) 1.25(0.32) 1.20(0.30) 1.16(0.29) 1.20(0.24) 1.25(0.34) 1.27(0.27)

0.14(0.17) 0.14(0.17) 0.18(0.19) 0.14(0.19) 0.16(0.16) 0.15(0.18) 0.12(0.17) 0.09(0.16) 0.14(0.15) 0.19(0.19) 0.19(0.15)

0.22(0.24) 0.22(0.25) 0.28(0.27) 0.21(0.27) 0.26(0.24) 0.24(0.25) 0.19(0.25) 0.15(0.24) 0.23(0.22) 0.23(0.26) 0.30(0.21)

51 49 60 44 65 53 41 30 64 53 83

Centre-north

Centre

South Total

[55]

1116 Table 3. Population size (N), number of haplotypes (na), effective number of haplotypes (ne), Shannon’s index (IRAPD), percent of polymorphic RAPD loci (%P), RAPD diversity (HeRAPD) for each region. The standard error of each parameter is given in brackets. Region

N

na

ne

IRAPD

HeRAPD

%P

North Centre-north Centre South

21 39 22 40

1.59(0.49) 1.73(0.44) 1.61(0.49) 1.74(0.44)

1.24(0.30) 1.29(0.29) 1.23(0.30) 1.25(0.28)

0.15(0.17) 0.19(0.16) 0.15(0.16) 0.16(0.16)

0.24(0.25) 0.30(0.24) 0.24(0.24) 0.27(0.23)

59 73 61 74

within populations, 18% (p = 0.000) among populations within region, and 6% (p = 0.000) among regions. As a result, the unrooted neighbour-joining tree obtained with RAPD markers (Figure 1) exhibited three main clusters corresponding to the three regions south, centre and the combination of

Figure 1. Unrooted neighbour-joining tree based on RAPD markers. The four regions are: the South (S), the Centre (C), the Centre-north (C-N), and the North (N). The tree was drawn with the Fst matrix given by analysis of molecular variance (Excoffier et al. 1992) with Arlequin software version 2000 (Schneider et al. 2000). [56]

1117 centre-north and north. The link of Antsevabe with the cluster of the south is difficult to explain. This clustering suggested a good relationship between the geographical distance and the genetic distance. This was partly confirmed by the Mantel test showing a coefficient of correlation between genetic and geographic distances moderately high (R = 0.46), but not significantly different from zero (p = 0.12), this relationship is illustrated in Figure 2a.

Genetic diversity and structure with chloroplast microsatellite markers The three chloroplast microsatellite primers assayed on 100 individuals gave 10 different alleles: Ccmp4, 2 alleles, Ccmp6, 4 alleles and Ccmp7, 4 alleles. The combination of the 3 loci and the 10 alleles gave 13 chlorotypes (Table 4). Except for Ampitsongoina, each population exhibited several haplotypes and generally one chlorotype was predominant. In the total population, the C11

Figure 2. Relation between genetic and geographical distances for the RAPD and chsloroplast microsatellite markers. Matrices of genetic distances were calculated using the AMOVA-derived Fst (Arlequin software version 2000 (Schneider et al. 2000)). [57]

1118 Table 4. Allelic characteristics in base pairs for the three loci, allelic combination of each chlorotype and frequencies of the chlorotypes present in each population and in the total population of Dalbergia monticola. Zone

Population

North

Tsaramalotro

N

Chlorotype

Ccmp4

Ccmp6

Ccmp7

Frequency

7

C3 121 120 152 0.14 C5 122 120 152 0.86 Ampitsongoina 6 C5 122 120 152 1.00 Centre-north Ambohijanahary 10 C1 122 119 151 0.20 C2 122 120 151 0.10 C4 122 119 152 0.20 C6 122 121 152 0.10 C9 122 120 153 0.30 C10 122 121 153 0.10 Antsevabe 11 C2 122 120 151 0.64 C4 122 119 152 0.36 Didy 15 C1 122 119 151 0.07 C2 122 120 151 0.66 C4 122 119 152 0.07 C5 122 120 152 0.07 C9 122 120 153 0.13 Centre Bekorokaka 6 C3 121 120 152 0.17 C8 121 120 153 0.67 C12 121 120 154 0.16 Madiorano 6 C8 121 120 153 0.83 C12 121 120 154 0.17 Ankeniheny 2 C2 122 120 151 0.50 C9 122 120 153 0.50 South Ranomafana 23 C7 122 122 152 0.04 C11 122 122 153 0.96 Tolongoina 14 C7 122 122 152 0.21 C11 122 122 153 0.58 C13 122 122 154 0.21 Frequencies in total population: C1(0.03), C2 (0.19), C3 (0.02), C4 (0.07), C5 (0.13), C6 (0.01), C7 (0.04), C8 (0.09), C9 (0.06), C10 (0.01), C11 (0.30) C12 (0.02), C13 (0.03)

haplotypes exhibited the highest frequency (30%), followed by C2 (19%) and C5 (13%) while others were lower than 10%. Haplotype diversity varied markedly among the populations and ranged from HeCp = 0.00 (Ampitsongoina) to HeCp = 0.80 (Ambohijanahary) (Table 5). For the total population it was equal to HeCp = 0.71. The number of alleles (na), effective number of haplotypes (ne) and Shannon’s diversity index (ICp) followed the same pattern. No clear pattern of variation with latitude was observed when considering the within-population diversity. However, when the regional level was taken into account the results showed that the diversity parameters were higher in the centre-north and centre than in the north and south. For example, HeCp = 0.68 and 0.55 in the centre-north and centre, while HeCp = 0.14 and 0.32 in the north and south. [58]

1119 Table 5. Diversity parameters assessed with chloroplast microsatellite markers for each population and the total population of Dalbergia monticola. Population size (N), number of haplotypes (na), effective number of haplotypes (ne), Shannon’s index (ICp), haplotypic diversity (HCp). Region

Population

N

na

ne

HeCp

ICp

North

Tsaramalotro Ampisongoina Ambohijanahary Antsevabe Didy Bekorokaka Madiorano Ankeniheny Ranomafana Tologoina

7 6 10 11 15 6 6 2 23 14 100

2 1 6 2 5 3 2 2 2 3 13

1.32 1 5 1.86 2.10 2 1.38 2 1.09 2.39 6.10

0.25 0.00 0.80 0.46 0.52 0.50 0.28 0.50 0.08 0.58 0.83

0.41 0.00 1.69 0.66 1.08 0.87 0.45 0.69 0.18 0.98 2.10

Centre-north

Centre

South Total

With cpSSR, the unrooted neighbour-joining tree exhibited four clusters corresponding to the four regions more distinctly than with RAPD data (Figure 3). Ankeniheny from the centre, however, was included in the cluster of the centre-north region, but the poor sample size of this population (2 individuals) can explain this unexpected position. This strong differentiation among populations was confirmed by the analysis of molecular variance. The variation among groups represented 80% (p = 0.0000) of total variation, the within-group variation among populations 4% (p = 0.000) and the betweenindividual variation within populations 16% (p = 0.000).

Phylogenetic relation and geographic distribution of the haplotypes The distribution of the 13 haplotypes across the natural range showed a geographical structure (Figure 4). Some haplotypes were present in contiguous populations and regions but none was scattered among distant populations and regions. The network of haplotypes in Figure 4b shows that haplotype C5 has the highest number of connections and C5 is among the most frequent (13%). Generally, haplotypes that are closely related to each other, differing by a single mutation at a microsatellite repeat, are geographically close. For example, the set of haplotypes C7, C11 and C13 is located in the south, haplotypes C1, C2, C4, C1 and C5 are in the centre-north, haplotypes C8, C9, C12, and C10 are in the centre and haplotypes C3, C5 in the north. This relation of isolation by distance is confirmed by the significant correlation between genetic distance (Fst) and geographic distance (q = 0.57; p = 0.02). Figure 2b shows that this linear relationship increased strongly up to 300 km and then reached a plateau, emphasising that Fst is more or less constant and close to 1 after this distance. [59]

1120

Figure 3. Unrooted neighbour-joining tree based on chloroplast microsatellites markers. The four regions are: the South (S), the Centre (C), the Centre-north (C-N), and the North (N). The tree was drawn with the Fst matrix given by analysis of molecular variance (Excoffier et al. 1992) with the Arlequin software version 2000 (Schneider et al. 2000).

Discussion Genetic diversity of Dalbergia monticola Although the oriental forest is strongly fragmented, the impact of fragmentation due to human agriculture on the dynamics of the genetic diversity within the remaining fragments of Dalbergia monticola is likely to be still limited because it is a very recent phenomenon. It takes several generations before the impact of genetic drift can be observed. However, the natural range of Dalbergia monticola was likely to be wider in the recent past and the second wave of settlement from the 15th century had probably reduced the whole population in Madagascar and consequently the genetic diversity of the species. With polymorphic and monomorphic loci used for calculation, the mean intraspecific genetic diversity of Dalbergia monticola obtained with RAPD markers is smaller than that estimated for other tree species (Bekessy et al. [60]

1121

Figure 4. (a) Geographic distribution of the 13 chlorotypes in the natural range of Dalbergia monticola (the limit of the natural range is represented by the dark line). The size of the circle is proportional to the size of the sample. (b) Minimum spanning network among the 13 haplotypes found in the natural range of Dalbergia monticola. The size of the circle is proportional to the frequency of the haplotype in the total population. The connection length is equal to one for the dark line and two for the dotted line.

2002; Newton et al. 2002; Bouvet et al. 2004). Shannon’s diversity index for these species ranged from 0.42 to 0.65, whereas it is 0.30 (0.21) for D. monticola. Values of expected heterozygosity are similar to those estimated for perennial species growing on smaller islands, but the percentage of polymorphic loci in Dalbergia monticola is higher (Kwon and Morden 2002). Although RAPD markers should be considered with caution as they are not a good predictor of total genetic diversity (Nybom and Bartish 2000), the low values of estimated diversity parameters in this species could be explained by the limited range of the species. An island population contains less genetic diversity than a mainland population (Barett 1998). Although Madagascar is a single large island the isolation from other sources gene could favour the effect of genetic drift. Another factor that can explain the low diversity is a recent and rapid expansion after a bottleneck (Savolainen and Kuittinen 2000). There are few published studies concerning the diversity of cpSSrs in angiosperm tree species. The present study shows, however, that the results varied according to the species and the number of primers used. With 3 primers, 100 individuals distributed in 10 populations, the 13 haplotypes identified in Dalbergia monticola are consistent with previous studies on angiosperms (Palme´ and Verdramin 2002; Grivet and Petit 2003). In addition, the haplotypic heterozygosity HeCp = 0.88 is high compared with estimates for other tree species (Palme´ and Verdramin 2002) and suggest high diversity compared to a number of temperate tree species studied. [61]

1122 Genetic structure and gene flow The distribution of genetic diversity with RAPD markers indicates that most of the variation is present within populations (81%). This can be explained by some biological patterns such as long-lived woody perennials and outcrossed insect pollination species according to Nybom and Bartish (2000). Nested analysis of variance with RAPDs shows that only 6% of the total variation is attributed to among-group variation, 16% to among populations within groups, and 76% among individuals within populations. This is low but significant differentiation among regions and populations is closely related to the correlation (moderately high but not significant) between the geographic and genetic distance. This pattern of isolation by distance is often observed in tree species wind or insect-pollinated when long distances within the natural range are considered (Bekessy et al. 2002), while no significant correlation is seen when short distances are taken into account (Schierenbeck et al. 1997). The distribution of the diversity is very different using chloroplast microsatellites. We note a strong differentiation between regions (80%) and a low percentage of variance within populations (16%). This is a classical result for angiosperm forest trees (Raspe´ et al. 2000) because of the maternal inheritance of the chloroplast DNA, and seeds are dispersed over shorter distances compared with pollen (Echt et al. 1998). In Dalbergia monticola, seed dispersal is mainly barochorous and contributes to this strong structure. The relationship between genetic distance and geographic distance for cpSSr (Figure 2b) confirms this strong structure and shows that above 300 km Fst is close to 1. The different patterns of genetic structure of RAPD and cpSSr can also be viewed through the relative rate of pollen flow to seed flow. With FstCp = 0.84 and FstRAPD = 0.23, the calculation of r showed that gene flow by pollen is 15 times greater than by seeds. The difference is marked but is smaller than for temperate species such as Fagus silvatica (r = 84), Quercus robur (r = 286), Quercus petraea (r = 500) (King and Ferris 1998). This can be explained by the fact that they are wind-pollinated whereas D. monticola is insect-pollinated.

Marker distribution and historical factors One of the most consistent factors that strongly influenced the partition of genetic diversity of tree species over the natural range is the last glaciation period and the subsequent migrations from the refuges (Aide and Riviera 1998; Willis and Whittaker 2000). In Europe (Verdramin et al. 1998), South America (Dutech et al. 2000; Bekessy et al. 2002) and the Sudano-Sahelian region of Africa (Bouvet et al. 2004), the genetic variability of tree species has been analysed in connection with the last glaciation period, 15–20,000 years ago, but no studies, to our knowledge, have attempted to establish this relation in Madagascar. As many tropical regions, the island underwent climate fluctuation during the Pleistocene and Holocene periods, but also the impact of human activities. [62]

1123 Three critical periods in the Quaternary should be mentioned. The first was the Last Glaciation Maximum around 20,000–21,000 years ago which led to an extremely cold and arid climate. According to (Adams and Faure 1997), during this episode the rainforest in Madagascar was limited to the north-eastern part of the country (between latitudes 12 and 16), the high plateaus were covered with ericoid, graminoid and composite-dominated vegetation and the oriental escarpment and coastal plain presented tropical woodland characterised by low, open canopy and usually deciduous trees. Other authors have concluded that tropical montane vegetation belts must have been vertically displaced 900– 1500 m (Burney 1996). Such a cold-driven displacement of vegetation zones would have confined the island’s humid forest zones to the relatively small land area along the east coast, with isolated patches elsewhere (low elevation humid refugia). From the early Holocene (8000 14C years ago) the rainforest occupied a broader zone than today. Early Holocene warming led to a gradual replacement of ericoid vegetation in the mid-elevation with forest in wetter locations of the eastern escarpment and a rise in the level of Lake Alaotra (Burney 1996). Some analyses, based on pollen records in high plateau locations (Lake Itasy, Ankatra, Andasibe) suggested that the rain forest was present up to elevations of 1800–2000 m (Straka 1996). The third period corresponds to human settlements 2000 years ago and the effect of burning which increased the frequency of fire and resulted in disturbance of the too wet or too dry ecosystems which generally support a natural fire regime (Burney 1996). Assuming a limitation of the rainforest in the northern part of the range during LGM, we can hypothesise that this region may be the zone of putative refuges for sub-montane rainforest tree species. The assumption cannot be verified by the results of this study because no sample was collected in the northern part of the range in the latitude 15. However, our study proposes another putative refuge. Generally, the highest diversity regions are considered as putative refuges. The higher diversity in the centre-north region and the decrease in diversity in the southern and northern limits of the natural range (Table 6) suggest that the zone of Didy, Ambohijanahary and Antsevabe could be a putative refuge for this species. Phylogenetic trees based on haplotypes (Figures 4b) and their distribution across the natural range (Figure 4a) also point to a pattern of migration from the centre-north region.

Table 6. Diversity parameters assessed with chloroplast microsatellite markers for the four main regions of the natural range of Dalbergia monticola. Population size (N), number of haplotypes (na), effective number of haplotypes (ne), Shannon’s index (ICp), haplotypic diversity (HCp). Region

N

na

ne

HeCp

ICp

North Centre-north Centre South

13 36 14 37

2 7 5 3

1.17 3.16 2.22 1.48

0.14 0.68 0.55 0.32

0.27 1.44 1.13 0.61

[63]

1124 Haplotype C5 occupies a central position in the phylogenetic trees with the highest number of connections (Figure 4b) and is present in the centre-north region. It is likely to be the ancestor of most of the other chlorotypes which mutate during the northward and southward expansion. A putative refuge in the centre-north region, close to Lake Alaotra, is also supported by the study of Reyes (1993) cited by (Burney 1996) who inferred the Late Quaternary climatic changes in north-eastern and central Madagascar using diatom spectra. In this study, Reyes (1993) indicated that early Holocene warming led to the gradual replacement of ericoid vegetation in the mid-elevation with forest developing in wetter locations along the eastern escarpments and a rise in the level of Lake Alaotra. Human settlement probably started 2000 years ago and the impact on the forest ecosystem of human practices has increased over the last two millennia. The probable effect of burning by humans has been to reduce the natural range of Dalbergia monticola. Without an uncontrolled use of burning, the natural range of Dalbergia monticola would be wider than today. Our study does not allow us to measure this effect. More recently, 50 years ago, the impact of human activity led to a marked increase in fragmentation in the oriental rainforest. Fragmentation is a factor which can seriously disturb the evolutionary process and which has to be taken into consideration in conservation. New investigations are needed to measure its impact on the genetic diversity of Dalbergia monticola.

Consequences for conservation of the species Forest genetic resources in Madagascar constitute an essential component of the biological diversity of forest ecosystems. They supply a wide range of goods and services essential to the life of rural communities and efforts to promote sustainable management are required. Strategies involving genetic studies are still rare and exploration of the genetic diversity of Malagasy trees is expected. Newton et al. (1999) emphasise that intraspecific diversity has become a parameter fundamental to the management of species with the aim of maintaining their evolutionary potential. In this study we used neutral markers to assess diversity. The use of such markers to predict the diversity of adaptive genes or economic traits within populations has to be considered with caution (Lynch et al. 1999). RAPD or cpSSrs are different from genes and may not be a good predictor of gene function diversity or of complex traits. However, molecular markers can give indications of the genetic distance between populations and of their different evolutionary histories (Holsinger 1996), and may indicate a similar genetic structure for morphological traits (Nesbitt et al. 1995). Different genes could have been selected, appeared by mutation or have been eliminated by genetic drift in separated populations which do not exchange genes. Some authors use intraspecific diversity to elaborate conservation strategies (Rajagodal et al. [64]

1125 2000). The concept of evolutionary significant units (ESUs) has received increasing support as providing a rational basis for identifying suitable units for conservation (Moritz 1994; Newton et al. 1999) and has been implemented in forest genetic resources when nuclear and organelle haplotypes are available (Cavers et al. 2003). This approach can be proposed given the methodology and the results of the current study. Chloroplast markers can provide a basis for defining ESUs using the main lineages, their distribution in the natural range and the result showing the differentiation between populations (AMOVA and Mantel test). The set of regions north and centre-north, the centre region and the south region can be identified as ESUs. Significant divergence between these three groups with RAPD markers confirms the identification of the three ESUs. Although pollen gene flow is important, isolation by distance was observed by means of the Mantel test, and a significant genetic differentiation among populations and regions was shown by AMOVA. RAPD markers indicate that most of the variability is present within populations, stressing the importance of gene flow among individuals. This result could help to define a strategy to elaborate ex and in situ conservation stands. To start such a programme, the population should consist of many individual trees selected within a few natural populations within the ESUs to capture a large proportion of variation. Much work is needed to elaborate an optimal strategy. As stressed by Cavers et al. (2003), the best strategy will concord with use of neutral markers and adaptive information (also ecological information), but a first step in the identification of ESUs with molecular markers provides a first practical framework.

Acknowledgements We are very grateful to colleagues from ‘‘Silo National des Graines Forestie`res’’ for assistance in collecting samples, to Alexandre Vaillant and Ce´line Cardi from Cirad-foreˆt for their technical assistance in the laboratory, and to the anonymous reviewers. These results are part of master of science thesis of O. Andrianoelina, which was financially supported by the Millennium Seed Bank (MSB) project, managed by the Seed Conservation Department, RBG Kew. The study was carried out at SNGF, which receives funds from the Malagasy Government, as well as at Cirad-Foreˆt, where laboratory work was done. L. Ramamonjisoa, head of the technique division in SNGF and J.M. Bouvet, head of the Research unit on forest genetic resources, were responsible for supervision.

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Biodiversity and Conservation (2006) 15:1129–1142 DOI 10.1007/s10531-004-3103-8


Springer 2006

-1

Forest management and plant species diversity in chestnut stands of three Mediterranean areas HE´LE`NE GONDARD1,*, FRANC¸OIS ROMANE1, IGNACIO SANTA REGINA2 and SALVATORE LEONARDI3 1

CEFE (UMR 5175), 1919 route de Mende, 34293 Montpellier cedex 5, France; 2Instituto de Recursos Naturales y Agrobiologia de Salamanca, P. box 257 C/Cordel de Merinas 40, E-37071 Salamanca, Spain; 3Dipartimento di Metodologie Fisiche e Chimiche per l’Ingegneria, Facolta` di Ingegneria, Universita` di Catania, viale A. Doria 6, 95125 Catania, Italy; *Author for correspondence (e-mail:[email protected]; phone: +33-4-67613276; fax: +33-4-67412138) Received 6 February 2004; accepted in revised form 31 August 2004

Key words: Castanea sativa, Coppice stand, Diversity index, Functional trait, Grove Abstract. Over many centuries, chestnut fruits had an important role as food, while chestnut wood was used for local purposes. Today sweet chestnut stands are very common around the western Mediterranean Basin, and it is necessary to analyze the dynamic of plant species diversity in different chestnut stand types (groves and coppices) to guide management strategies that will allow the conservation of biodiversity. Our objective was to analyze consequences on plant species diversity of various management strategies in chestnut stands of three Mediterranean areas, Salamanca (Spain), the Ce´vennes (France), and Etna volcano (Italy). We found that plant species diversity is different according to management types; it is higher in groves than in coppice stands. We also demonstrated that Castanea sativa cultivated groves were characterized by small heliophillous therophytes. C. sativa abandoned groves, mixed C. sativa–Quercus pyrenaica coppice stands, Q. pyrenaica coppice stands, and young C. sativa coppice stands were characterized by hemicryptophytes with anemochorous dispersal mode and chamaephytes. Medium and old C. sativa coppice stands (that differ by the shoot age) were characterized by phanerophytes with zoochorous dispersal mode. Human perturbations maintain a quite high level of species diversity. In contrast, the abandonment of chestnut stands leads to homogeneous vegetation with decreasing diversity. One solution could be to maintain a landscape mosaic constituted of diverse chestnut stands modified by human activities (groves, cultivated or abandoned, and coppice stands). This could enhance regional plant diversity.

Nomenclature – Flora Europaea (Tutin et al. 1964–1980)

Introduction Sweet chestnut (Castanea sativa Mill) stands are very common around the western Mediterranean Basin. Over many centuries, chestnut fruits had an important role as food for humans and as feed for domestic animals, while chestnut wood was used for local purposes such as wine barrels, vineyard pegs, tool handles and carpentry (Arnaud and Bouchet 1995). Today, chestnut [69]

1130 stands cover large areas particularly in Portugal, Spain, France, Italy and Greece. Thus, it is necessary to analyze the dynamic of plant species diversity in different chestnut stand types (groves and coppices) to guide management strategies that will allow the conservation of biodiversity and at the same time to optimize productivity and profitability. The characterization of community response to different management types in terms of functional traits appears as a promising tool to achieve this goal (McIntyre et al. 1995; Hadar et al. 1999; Lavorel et al. 1999; Gondard et al. 2003). Indeed, from an ecosystem perspective, species richness (number of species), which is the conventional metric of biodiversity, is not as important as functional trait richness. This approach analyzes the functioning of the ecosystem, and its response to abandonment, by focusing on vegetation description defined by functional traits not necessarily linked with taxonomic attribution (Pillar 1999). Functional traits fall into three biological categories: morphological traits describing aspect, life history traits indicating plant behavior in the environment, and regeneration traits (Lavorel et al. 1997). The use of functional traits for the comprehension and analysis of plant species dynamics in relation with perturbation is clearly demonstrated by many authors (Dı´ az and Cabido 1997; Lavorel and Cramer 1999; McIntyre et al. 1999; McIntyre and Lavorel 2001; Dı´ az et al. 2002; Gondard and Deconchat 2003). Consequently, our objective was to analyze consequences on plant species diversity of various management strategies in chestnut stands of three Mediterranean areas, Salamanca (Spain), the Ce´vennes (France), and Etna volcano (Italy). We hypothesized that, whatever area, species diversity between groves and coppice stands is different essentially according to dendrometric characteristics and management types. Indeed, groves have, in general, large trees with regular pruning, understorey cleaning, etc., and coppices have many shoots without clearing but logging. We assumed that species diversity is highest in groves. We focused on understorey stratum which is sensitive to changes of ecosystem conditions (Pregitzer and Barnes 1982; Strong et al. 1991; Mitchell et al. 1997, 1998) and recognized like a very important component in ecosystem functioning (Host and Pregitzer 1991; Arsenault and Bradfield 1995; Brakenhielm and Lui 1998).

Materials and methods The experiment was carried out in three Mediterranean areas, in the Honfrı´ a forest, located in the southern of Salamanca province in Spain, in the Ce´vennes in southern France, and on Etna volcano in Italy (Table 1). The Honfrı´ a forest is representative of traditional chestnut (Castanea sativa) management over many centuries in Spain, but also a model of possible sustainable management in the future. In this forest, chestnut is considered as a paraclimax species and the deciduous oak (Quercus pyrenaica) as a climax species. Thus, we selected five stands that are representative of this forest: a chestnut cultivated grove, a [70]

1131 chestnut abandoned grove, a chestnut coppice stand, a mixed chestnut-oak stand, and an oak pure stand. In the Ce´vennes, we identified a succession following agricultural abandonment from chestnut cultivated grove to chestnut old coppice stand. Thus, we selected five stages that form the successional gradient: a cultivated grove, an abandoned grove, a young coppice (51 years old). On Etna volcano, the tradition is coppice management and not grove. Thus, we selected five coppice stands (Fornazzo, Trisciala, Balilla, Monte Crisimo, Piano Lepre) that are representative of the study area and differ by their stand characteristics (Table 2). In each stand, we established five 10 · 10 m plots. The plots were contiguous because there was only little area available at the site with relatively homogeneous topographic conditions, and in order to respect 100 m2 plot size minimum. In each plot, we recorded all plant species occurring in the understorey stratum. The plant cover of each species was estimated by the point quadrat method (Gounot 1969), using 100 points, i.e. one point each 10 cm, along a 10 m line traversing each plot. According to previous observations, realized by one of us, 100 m2 plots appeared to be suitable for monitoring this kind of vegetation. Data were collected during June month in 2001 in the Ce´vennes, 2002 in the Honfrı´ a forest, and 2003 in Italy. Moreover, plant species recorded were characterized by functional traits such as plant height and life form that refer to morphology, light tolerance that refers to life history traits, and dispersal mode to regeneration traits (Appendix 1).

Data analyses The criteria to compare stands were species richness (number of taxa per 100 m2) and species diversity (Pielou 1975; Magurran 1988). Among the many diversity indices available, we chose P the Shannon index (H’), which was recommended by Pielou (1975): H0 ¼
i¼1;n ðpi log2 ðpi ÞÞ where pi is the abundance ratio of species (i) in the square, and n is the species number in the square. Forest stands in the three geographical areas are submitted to different silvicultural management and also to contrasting environment and climate conTable 1. Characteristics of the three Mediterranean areas studied.

Altitude (m) Mean annual rainfall (mm yr
1) Mean annual temperature (C) Parent material Soil

Honfrı´ a Forest

Ce´vennes

Etna volcano

Spain

France

Italy

900 1500 11 Schist Cambisol

650 1400 11 Schist Cambisol

1000 1100 12 volcanic ash, lava regosol volcanic

[71]

1132 Table 2. Main characteristics of chestnut stands selected in the Ce´vennes in France, on Etna volcano in Italy and in Honfrı´ a Forest in Spain. Confidence intervals p = 0.05. For each site, mean values in the same column followed by different letters are significantly different. p < 0.05, Mann– Whitney test. Tree age Tree (years) height (m)

Diameter at breast height (cm)

Shoot density Basal area (shoot ha
1) (m 2ha
1)

Site

Stand

Honfrı´ a Forest Spain

C. sativa 90 cultivated grove

11.30 ± 1.3b 18.30 ± 2.1c

295 ± 20a

23 ± 5b

C. sativa 85 abandoned grove C. sativa 70 coppice stand Mixed C. sativa–Q. 60 pyrenaica stand Q. pyrenaica 75 pure stand Ce´vennes Cultivated grove 70 France Abandoned grove 75 Young coppice 16 Medium coppice 39 Old coppice 56 Etna volca Fornazzo coppice 31 Italy Trisciala coppice 28 Balilla coppice 37 Monte Crisimo 26 coppice Piano 27 Lepre coppice

8.90 ± 0.8a 20.40 ± 3.0c

382 ± 30a

19 ± 4a

15.3 ± 1.3c 12.90 ± 1.7b 1892 ± 100b

28 ± 8c

10.7 ± 0.8b

8.90 ± 1.2a 3208 ± 150c

21 ± 5a

12.2 ± 1.0b 11.60 ± 1.5b 2960 ± 125c

27 ± 7c

18.00 ± 1.0a 45.00 ± 7.1a 17.40 11.20 12.40 16.40 17.67

± ± ± ± ±

0.5a 0.8b,c 0.9c 0.5d 0.7a

44.60 ± 11.5a 9.40 ± 1.5b 17.80 ± 7.8c,d 24.00 ± 4.8d 9.20 ± 0.5a

120 ± 45a 440 ± 195a 1040 ± 611b 1080 ± 396b 840 ± 488b 4680 ± 1242a,c

26 ± 18a 45 ± 21a 8 ± 4b 17 ± 14c,d 35 ± 13d 38 ± 8a,b

12.17 ± 0.3a 16.67 ± 2.3a 16.00 ± 0.0a

7.20 ± 0.3b 6020 ± 895a 20.9 ± 1.7c 1140 ± 331b 7.10 ± 1.2d 2900 ± 919c

29 ± 3a 43 ± 8b 24 ± 6c

15.67 ± 3.2a

9.90 ± 0.5a 4180 ± 394d,c 38 ± 1a,b

ditions, so differences are expected between them. However, due to the low number of stands analyzed, we used non-parametric test that allows to work with low size samples. We chose the Mann–Whitney non-parametric test that allows to compare means pairwise (Falissard 1998). In each Mediterranean area, we used Correspondence Analysis (CA) and Canonical Correspondence Analysis (CCA, ter Braak 1987) to quantify the effects of management types with species functional traits. We performed a Correspondence Analysis (CA,Greenacre 1984) of plant species observed on the entire point quadrat set (67 in Honfrı´ a forest in Spain, 41 in the Ce´vennes in France, and 40 on Etna volcano in Italy) and management types (coppice stands and groves in Honfrı´ a forest and in the Ce´vennes, and different coppice stand types on the Etna volcano). We used CCA to determine the fraction of variance of the species among management types explained by the species and functional traits. For each Mediterranean area, we carried out the CCA by confronting the CA table with another table composed by the same species [72]

Species richness

1133 60 55 50 45 40 35

a

30 25 20 15 10 5 0

bc

C. sativa cultivated grove

b

b

C. sativa abandoned grove

C. sativa coppice stand

c

Mixed C. sativaQ. pyrenaica stand

Q. pyrenaica stand

Figure 1. Mean species richness in the understorey of the C. sativa and Q. pyranaica stands of the Honfrı´ a forest in the southern of Salamanca province in Spain. Error bars at ±95% confidence limits. Two different letters between the coppice stands indicated significant statistical difference (Mann–Whitney non-parametric test, p < 0.05).

number and functional traits separated in subclasses. Moreover, hierarchical ascending classification was used to make easier the identification of groups in factorial plans (Roux 1985).

Results Species richness and species diversity (Shannon index) In the Honfrı´ a forest and the Ce´vennes, species richness was highest in cultivated groves, (Figures 1, 2). On Etna volcano, species richness was highest in

Species richness

45

a

40 35 30

b

25 20

c

cd d

15 10 5 0

Cultivated Abandoned Grove Grove

Young Coppice

Medium Coppice

Old Coppice

Figure 2. Mean species richness along a successional gradient from cultivated chestnut grove to old C. sativa coppice stand (Le Cros site in the Ce´vennes). Error bars at ±95% confidence limits. Two different letters between the coppice stands indicated significant statistical difference (Mann– Whitney non-parametric test, p < 0.05). [73]

Species richness

1134 45 40 35 30 25 20 15 10 5 0

a b

bc cd

Monte Crisimo

Trisciala

Fornazzo

d

Balilla

Piano Lepre

Figure 3. Mean species richness in the understorey in the five coppice C. sativa stands on the Etna volcano in Italy. Error bars at ±95% confidence limits. Two different letters between the coppice stands indicated significant statistical difference (Mann–Whitney non-parametric test, p < 0.05).

the Trisciala coppice stand (Figure 3), and not significantly different from the abandoned grove in the Ce´vennes (p > 0.05). Species diversity was also highest in cultivated groves and Trisciala coppice stand.

Plant functional traits and management types Consequences of various management types on plant species in term of functional traits were analyzed with CCA, and hierarchical ascending classification allowed the identification of several groups in each Mediterranean area 1 Axis 2 (inertia 15%) 0,8

Honfría forest - Group 2 C.sativa coppice stands Arpa, Casa, Celo, Prav, Qupy, Tesc

Geophyte 0,6

0,4

> 50 cm Axis 1 (inertia 48%) -1

Honfría forest - Group 3 C. sativa abandoned groves & Mixed C. sativa-Q. pyrenaica coppice stands & Q. pyrenaica coppice stands Anod, Caof, Capa, Daca, Gehi, Gepi, Haha, Jamo, Loco, Meme, Feru, Himu Barochorous

0,2

Heliophillous

Hydrochorous Anemochorous

Zoochorous

Therophyte

0

-0,8

-0,6 -0,4 Phanerophyte

Shade tolerant

-0,2

0 Chamaephyte -0,2

0,2 30-50 cm

0,4

0,6

0,8

1

1,2

1-30 cm

Autochorous

Honfría forest - Group 1 C. sativa cultivated groves Anpr, Boma, Brho, Cegl, Cran, Crvi, Cyec, Gaap, Tran, Trar, Trca, Scan, Vubr

-0,4 Hemicryptophyte -0,6

Figure 4. Ordination in the plane of the two axes of functional traits after a canonical correspondence analysis from a matrix composed by the 67 plant species observed on the line point quadrat of the 25 plots in the Honfrı´ a forest in Spain and a matrix composed by the same plant species and their functional traits. Groups were identified by an hierarchical ascending classification. Plots, and some plant species associated to each group were indicated on the figure. Codes of plant species are indicated in Appendix 1. The total variation explained by CCA is 39%. [74]

1135 The Cévennes - Group 2 C. sativa abandoned groves & young coppice stands Armo, Clvu, Dagl, Erci, Hima, Himu, Pone, Prvu, Trpr, Veof, Visa

0,8 Axis 2 (inertia 28%) Autochorous

Barochorous 0,4

Phanerophyte > 50 cm

0,2

Chamaephyte

Zoochorous Shade tolerant

0 -0,8

-0,6 30-50 cm

-0,4

-0,2

0

Heliophillous 1-30 cm

Hemicryptophyte

The Cévennes - Group 3 C. sativa medium and & old coppice stands Bepe, Csa, Hede, Qupu, Rops

0,6

Therophyte

0,2 Hydrochorous

0,4 Geophyte

0,6

0,8 Axis 2 (inertia 37%)

1

-0,2

The Cévennes - Group 1 C. sativa cultivated groves Ruac, Orpe, Ptaq, Tesc

-0,4 Anemochorous -0,6

Figure 5. Ordination in the plane of the two axes of functional traits after a canonical correspondence analysis from a matrix composed by the 41 plant species observed on the line point quadrat of the 25 plots in the Ce´vennes in France and a matrix composed by the same plant species and their life traits. Groups were identified by an hierarchical ascending classification. Plots, and some plant species associated to each group were indicated on the figure. Codes of plant species are indicated in Appendix 1. The total variation explained by CCA is 46%.

studied. In the Honfrı´ a forest, the C. sativa cultivated groves (group 1) were characterized by small heliophillous therophytes (Figure 4). The C. sativa coppice stands (group 2) were characterized by shade tolerant phanerophytes with zoochorous dispersal mode and geophytes. The C. sativa abandoned groves, mixed C. sativa–Q. pyrenaica coppice stands and Q. pyrenaica coppice stands (group 3) were composed essentially by hemicryptophytes and chamaephytes with anemochorous or barochorous dispersal mode. In the Ce´vennes, the C. sativa cultivated groves (group 1) were characterized by therophytes with anemochorous dispersal mode and geophytes (Figure 5). The C. sativa abandoned groves and the young coppice stands (group 2) were characterized by heliophillous hemicryptophytes and chamaephytes. The C. sativa medium and old coppice stands (group 3) were composed more particularly by phanerophytes with zoochorous dispersal mode. In the case of C. sativa coppice stands on Etna volcano in Italy, Monte Crisimo (group 1) were more particularly characterized by therophytes and chamaephytes (Figure 6), Triciala (group 2) by hemicryptophytes with anemochorous dispersal mode, Piano Lepre (group 3) by geophytes with barochorous dispersal mode, and Balilla and Fornazzo (group 4) by shade tolerant phanerophytes with zoochorous dispersal mode.

Discussion and concluding remarks A main trend emerging from our species richness data was higher species richness in the chestnut cultivated groves than in coppice stands; both in the [75]

1136 1,5

Etna volcano - Group 2 C. sativa coppice stands Trisciala Acli, Brsy, Crle, Himu, Rane, Sivu, Trpu

Axis 2 (inertia 29%)

Etna volcano - Group 1 C. sativa coppice stands 1 Monte Crisimo Arth, Avba, Homu, Lasp, Sete, Stme, Vidi, Vite

Anemochorous

Heliophillous 30-50 cm

Chamaephyte Hemicryptophyte 1-30 cm -0,8

-0,6

Barochorous Geophyte

0,5

-0,4

Etna volcano - Group 3 C. sativa coppice stands Piano Lepre Door, Epmi, Lagr, Lave, Leco, Muco, Ptaq

Therophyte Hydrochorous 0 -0,2 Autochorous

0

0,2

0,4

0,6

0,8 Axis 1 (inertia 43%)

-0,5

Shade tolerant -1

> 50 cm Phanerophyte Zoochorous

Etna volcano - Group 4 C. sativa coppice stands Balilla & Fornazzo Casa, Hehe, Prsp, Quda, Ruid, Ruul

-1,5

Figure 6. Ordination in the plane of the two axes of life traits after a canonical correspondence analysis from a matrix composed by the 40 plant species observed on the line point quadrat of the 25 plots on Etna volcano in Italy and a matrix composed by the same plant species and their life traits. Groups were identified by an hierarchical ascending classification. Plots, and some plant species associated to each group were indicated on the figure. Codes of plant species are indicated in Appendix 1. The total variation explained by CCA is 49%.

Honfrı´ a forest in Spain and in the Ce´vennes in France. However, species richness in the cultivated groves of the Honfrı´ a forest (53 ± 4 species) was significantly higher than in the cultivated groves of the Ce´vennes (38 ± 4 species) (p < 0.01). The strawberry culture in some years under chestnut groves in the Honfrı´ a forest can explain this difference. Indeed, the high biodiversity among plants was always related to perturbations (pruning, grazing, fire, etc.), and often observed in Mediterranean areas (Romane et al. 1992). The species diversity decrease observed along the successional gradient in the Ce´vennes appears to be a general trend in Mediterranean Basin (Tatoni and Roche 1994; Debussche et al. 1996). On Etna volcano, tradition is coppice management and not grove, and species diversity in coppice stands was lowest than in the chestnut cultivated groves of the Honfrı´ a forest and the Ce´vennes. Nevertheless, species diversity in Trisciala coppice stand was not significantly different from chestnut abandoned groves in the Ce´vennes (p>0.05). In Trisciala, stumps have regular and large spacing and thus light, which is recognized as a factor linked positively with species richness (Grime and Jarvis 1975; Gilliam et al. 1995; Yorks and Dabydeen 1999), is available in the understorey and favour growth. Like in the study of Rubio et al. (1999) in Extremadure (Central Spain), or Kitazawa and Ohsawa (2002) in Chiba (Central Japan), the difference according to management type was well observed. The species composition differences among management type showed us that generally small heliophillous therophytes characterized C. sativa cultivated groves. Low intensity disturbance can explain the persistence of annual species in cultivated groves (Lavorel 1999). Hemicryptophytes with anemochorous [76]

1137 dispersal mode and chamaephytes characterized C. sativa abandoned groves, mixed C. sativa–Q. pyrenaica coppice stands, Q. pyrenaica coppice stands, and young C.sativa coppice stands. Phanerophytes with zoochorous dispersal mode characterized more particularly medium and old coppice stands (coppice stands that differ by the shoot age). This pattern coincides with the general trend described in Southern France; annual plants are substituted by perennial grasses and shrubs with canopy closure (Houssard et al. 1980; Escarre´ et al. 1983; Tatoni and Roche 1994). Perturbations were necessary to maintain a quite high level of species diversity. In contrast, the abandonment of chestnut stands, for decades or even centuries, will turn into closed and homogeneous vegetation with decreasing plant diversity. One solution could be to maintain a landscape mosaic consisting of diverse chestnut stands modified by human activities (chestnut groves, abandoned chestnut groves and chestnut coppice stands) (Gondard et al. 2001; Rubio and Escudero 2003). This could enhance regional plant diversity. However, in our study we recorded only common species, thus if rare species have been observed, the estimation of biodiversity would be review, and quality aspect take into account. Moreover, due to some of the unsatisfactory aspects of the experimental design (replication number), our study only indicates, but does not validate, several possible management techniques, of which remain to be tested further.

Acknowledgements We thank the European Union (MANCHEST contracts, DG XII). We also warmly thank Maria Failla, Giuseppe Siracusa, Antonino La Mantia, Mirella Clausi, Sergio Salazar Iglesias, Alvaro Peix Geldart, Jesu´s Herna´ndez, Zuheir Shater, Alain Renaux, Michel Grandjanny, Marie Maistre, Maurice Rapp, and Franc¸ois Jardon for their participation in collecting data in the chestnut stands.

Appendix 1. Functional traits (life form, dispersal mode, plant height and light tolerance) of plant species observed along the point quadrat line and used in the Canonical Correspondence Analysis according to available data: Molinier and Mu¨ller 1938; Pignatti 1982; van der Pijl 1982; Bonnier 1990; De Bolos et al. 1993. Th – therophyte, G – geophyte, H – hemicryptophyte, Ch – chamaephyte, Ph – phanerophyte. Code

Species

Life form

Dispersal mode

Height

Light tolerance

Acli Acmi Alpe Anod Anpr Armo

Achillea ligustica Achillea millefolium Alliaria petiolata Anthoxantum odoratum Anthemis pratensis Arenaria montana

H H H H Th H

Anemochorous Anemochorous Anemochorous Anemochorous Anemochorous Anemochorous

30–50 cm 30–50 cm 30–50 cm 30–50 cm 1–30 cm 1–30 cm

shade tolerant shade tolerant shade tolerant heliophillous heliophillous heliophillous

[77]

1138 Appendix 1. Continued. Code

Species

Life form

Dispersal mode

Height

Light tolerance

Arpa Arth Asal Astr Avba Avsu Bepe Brsy Brma Brho Cadi Caof Capa Casa Cavu Cegl Celo Chju Coma Clvu Coar Coav Coli Cran Crle Crvi Cyec Cysc Daca Dagl Deme Door Epla Epmi Erar Erci Feov Feru Gaap Gamo Gasa Gefl Gehi Gepi Gero Gnlu Haha

Aristolochia pallida Asplenium trichomanes Asphodelus albus Asplenium trichomanes Avena barbata Avena sativa Betula pendula Brachypodium sylvaticum Bromus maximus Bromus hordeaceus Carex distachia Calamintha officinalis Campanula patula Castanea sativa Calluna vulgaris Cerastium glomeratum Cephalanthera longifolia Chondrilla juncea Conopodium majus Clinopodium vulgare Convolvulus arvensis Corylus avellana Corrigiola littoralis Crucianella angustifolia Crepis leontodontoides Crepis virens Cynosurus echinatus Cytisus scoparius Daucus carota Dactylis glomerata Deschampsia media Doronicum orientale Epilobium lanceolatum Epipactis microphylla Erica arborea Erica cinerea Festuca ovina Festuca rubra Galium aparine Galium mollugo Galium saccharatum Genista florida Genista hispanica Genista pilosa Geranium robertianum Gnaphalium lutescens Halimium lasianthumsubsp .alyssoides Hedera helix Hippocrepis comosa

G Th G H Th Th Ph H Th Th H H H Ph Ch Th G H G H H Ph H Th H Th Th Ph H H H G H G Ch Ch H H Th H Th Ch Ch Ch Th H Ch

Barochorous Anemochorous Barochorous Zoochorous Anemochorous Zoochorous Anemochorous Anemochorous Anemochorous Zoochorous Barochorous Zoochorous Anemochorous Zoochorous Anemochorous Anemochorous Anemochorous Anemochorous Barochorous Hydrochorous Barochorous Zoochorous Autochorous Anemochorous Anemochorous Anemochorous Anemochorous Autochorous Anemochorous Anemochorous Zoochorous Anemochorous Anemochorous Anemochorous Barochorous Barochorous Anemochorous Anemochorous Zoochorous Barochorous Zoochorous Autochorous Autochorous Autochorous Autochorous Autochorous Zoochorous

30–50 cm 1–30 cm 30–50 cm 1–30 cm >50 cm >50 cm >50 cm 30–50 cm 30–50 cm 1–30 cm 1–30 cm 30–50 cm 30–50 cm >50 cm 30–50 cm 1–10 cm 1–30 cm >50 cm >50 cm 30–50 cm 30–50 cm >50 cm 1–30 cm 1–30 cm 30–50 cm 30–50 cm 1–30 cm >50 cm 30–50 cm >50 cm 30–50 cm 30–50 cm 30–50 cm 1–30 cm >50 cm 30–50 cm 30–50 cm 30–50 cm 1–30 cm 30–50 cm 1–30 cm 1–30 cm 1–30 cm 1–10 cm 1–30 cm 1–30 cm 30–50 cm

shade tolerant shade tolerant heliophillous shade tolerant heliophillous heliophillous shade tolerant shade tolerant heliophillous heliophillous shade tolerant heliophillous heliophillous shade tolerant shade tolerant heliophillous shade tolerant shade tolerant shade tolerant heliophillous heliophillous shade tolerant shade tolerant heliophillous heliophillous heliophillous heliophillous shade tolerant heliophillous heliophillous shade tolerant shade tolerant shade tolerant shade tolerant shade tolerant shade tolerant heliophillous shade tolerant heliophillous shade tolerant shade tolerant shade tolerant shade tolerant shade tolerant shade tolerant heliophillous shade tolerant

Ph H

Zoochorous Autochorous

>50 cm 1–30 cm

shade tolerant shade tolerant

Hehe Hico

[78]

1139 Appendix 1. Continued. Code

Species

Life form

Dispersal mode

Height

Light tolerance

Hihi Hima Himu Hipi Hium Hola Homo Homu Hyra Ilaq Jamo Laan Lagr Lasp Lave Leco Lihe Litr Loco Loet Luca Lufo Lusi Meme Meun Muco Orco Orpe Pehi Pimu Plla Pobu Pone Posy Prav Prgr Prsp Prvu Ptaq Quda Qupu Qupy Rabu Rane Rops Ruac Ruid Rupe

Hispidella hispanica Hieracium maculatum Hieracium murorum Hieracium pilosella Hieracium umbellatum Holcus lanatus Holcus mollis Hordeum murinum Hypochaeris radicata Ilex aquifolium Jasione montana Lathyrus angulatus Lathyrus grandiflorus Lathyrus sphaericus Lathyrus venetus Leopoldia comosa Linaria heterophylla Linaria triornitophora Lotus corniculatus Lonicera etrusca Luzula campestris Luzula forsteri Luzula sieberi Melittis melissophyllum Melica uniflora Muscari commutatum Ornithopus compressus Ornithopus perpusillus Petrorhagia hispanica Piptaterum multiflorum Plantago lanceolata Poa bulbosa Poa nemoralis Poa trivialis subsp. sylvicola Prunus avium Prunella grandiflora Prunus spinosa Prunella vulgaris Pteridium aquilinum Quercus dalechampii Quercus pubescens Quercus pyrenaica Ranunculus bulbosus Ranunculus neapolitanus Robinia pseudo-acacia Rumex acetosella Rubus idaeus Rubia peregrina var . longifolia

H H H H H H H Th H Ph H Th G Th G G H H H Ph H H H H H G Th Th H H H H H H Ph H Ph H G Ph Ph Ph H H Ph G Ph H

Anemochorous Anemochorous Anemochorous Anemochorous Anemochorous Anemochorous Zoochorous Anemochorous Anemochorous Anemochorous Anemochorous Barochorous Autochorous Autochorous Barochorous Anemochorous Anemochorous Autochorous Autochorous Zoochorous Zoochorous Anemochorous Zoochorous Zoochorous Anemochorous Anemochorous Zoochorous Zoochorous Autochorous Anemochorous Anemochorous Barochorous Anemochorous Anemochorous Zoochorous Barochorous Zoochorous Hydrochorous Anemochorous Zoochorous Zoochorous Zoochorous Barochorous Anemochorous Autochorous Anemochorous Zoochorous zoochorous

1–30 cm 30–50 cm 30–50 cm 1–30 cm 30–50 cm >50 cm 30–50 cm 1–30 cm 30–50 cm >50 cm 1–30 cm 30–50 cm >50 cm 1–30 cm 30–50 cm 1–30 cm 1–30 cm 30–50 cm 1–30 cm 30–50 cm 1–30 cm 1–30 cm 1–30 cm 30–50 cm 30–50 cm 1–30 cm 30–50 cm 1–30 cm 1–30 cm >50 cm 1–30 cm 1–30 cm 30–50 cm 30–50 cm >50 cm 1–30 cm >50 cm 1–30 cm >50 cm >50 cm >50 cm >50 cm 30–50 cm 1–30 cm >50 cm >50 cm >50 cm >50 cm

heliophillous shade tolerant shade tolerant shade tolerant heliophillous heliophillous heliophillous heliophillous heliophillous shade tolerant shade tolerant heliophillous heliophillous heliophillous heliophillous heliophillous heliophillous shade tolerant heliophillous shade tolerant heliophillous shade tolerant shade tolerant shade tolerant shade tolerant heliophillous heliphillous shade tolerant heliophillous heliophillous heliophillous heliophillous shade tolerant heliophillous shade tolerant shade tolerant shade tolerant shade tolerant shade tolerant shade tolerant shade tolerant shade tolerant heliophillous shade tolerant heliophillous heliophillous shade tolerant shade tolerant

[79]

1140 Appendix 1. Continued. Code

Species

Life form

Dispersal mode

Height

Light tolerance

Ruul Scan Sete Siin Sivu

Rubus ulmifolius Scleranthus annuus Sedum tenuifolium Silene inflata Silene vulgaris subsp. angustifolia Solidago virgaurea Stellaria media Teucrium scorodonia Thapsia garganica Torilis arvensis Trifolium angustifolium Trifolium arvense Trifolium campestre Trifolium pratense Trifolium pratense subsp. semi-purpureum Trifolium repens Veronica officinalis Vicia disperma Vicia lutea Vicia pseudocracca Vicia sativa Vicia tenuifolia Vulpia bromoides

Ph Th Ch H H

zoochorous zoochorous anemochorous anemochorous anemochorous

>50 cm 1–30 cm 1–30 cm 30–50 cm 30–50 cm

shade tolerant heliophillous heliophillous shade tolerant shade tolerant

H Th G H Th Th Th Th H H

anemochorous anemochorous barochorous anemochorous zoochorous anemochorous anemochorous anemochorous anemochorous anemochorous

30–50 cm 1–30 cm 30–50 cm >50 cm 30–50 cm 1–30 cm 1–30 cm 1–30 cm 1–30 cm 1–30 cm

shade tolerant shade tolerant shade tolerant heliophillous shade tolerant heliophillous heliophillous heliophillous heliophillous heliophillous

H H Th Th Th H Th Th

anemochorous hydrochorous anemochorous autochorous barochorous autochorous anemochorous zoochorous

1–30 cm 1–30 cm 30–50 cm 30–50 cm 30–50 cm 30–50 cm 30–50 cm 1–30 cm

shade tolerant shade tolerant heliophillous heliophillous heliophillous heliophillous heliophillous heliophillous

Sovi Stme Tesc Thga Toar Tran Trar Trca Trpr Trpu Trre Veof Vidi Vilu Vips Visa Vite Vubr

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Biodiversity and Conservation (2006) 15:1143–1157 DOI 10.1007/s10531-004-3105-6


Springer 2006

-1

Spatial diversity of dry savanna woodlands Assessing the spatial diversity of a dry savanna woodland stand in northern Namibia using neighbourhood-based measures FRIEDRICH PATRICK GRAZ 1 Department of Land Management Conservation, Polytechnic of Namibia, P/Bag 13388, Windhoek, Namibia; (e-mail: [email protected]; phone: +264-061-207-2215; fax: +264-061-2072123)

Received 8 March 2004; accepted in revised form 3 August 2004

Key words: Ecology, Mingling index, Namibia, Spatial diversity, Spatial structure, Uniform angle index, Woodland savanna Abstract. The dry woodland savannas of Namibia are of significant socio-economic importance. The paper tests the suitability of a number of diversity indicators developed for species poor systems in Europe in the woodland context. The indicators that were tested included the species specific mingling index, MSp, the measure of surround and the uniform angle index. The simple application of the methods permit relatively unschooled crews to conduct an enumeration in the field.The results show that the indicators do not only display current diversity status, but also reflect the ecological context of the individual species.

Introduction and background The dry woodland savannas of northern Namibia are of significant socioeconomic importance to many rural communities, providing a variety of timber and non-timber products. The woodland resources that are used range from building material and wood fuel to food, medicine and grazing (NFSP 1996). The quantities of the different products that are extracted are considerable. Ollikainen (1992) estimated for example, that firewood alone amounted to a total of 1.5 million cubic metres of wood during 1992. No quantity or value estimates of non-wood products are available for the Namibian dry woodland savannas, although these may be considerable. The various woodland products differ in their importance to the various communities, and at different times. Although exact quantities were not indicated, Lee (1973) reported, for instance, that the intake of Schinziophyton rautanenii nuts could comprise up to 90% of the total food intake of some San communities. While this percentage will have changed in the meantime, Bu¨schel (1999) indicated that the nuts still represent the staple diet of nomadic and sedentary San groups. The importance of the nuts increases particularly when agricultural crops are insufficient to meet normal requirements. [83]

1144 Other communities in the Kavango region of Namibia depend almost entirely on the production and sale of carvings for the tourism industry, although no studies seem to have been published in this regard. Some carvings are also produced in the Caprivi region, but the local population does not appear to depend as much on this form of income although no estimates are available. The emphasis on different species for the carving industry is also shifting. In the early 1990s the industry in the Okavango region made use of Pterocarpus angolensis almost exclusively. Now, however, species like Guibourtia coleosperma, Baikiaea plurijuga and even S. rautanenii (despite its light weight) are being utilized extensively. This is primarily due to the overexploitation of P. angolensis. Further woodland species, such as Burkea africana or Terminalia sericea serve mainly for poles or as firewood, although they support a caterpillar that also represents an important source of food (Leger 1997).

Spatial diversity and woodland structure The word ‘‘structure’’ generally considers the composition of a population of trees in terms of specific characteristics. These may include tree age, size, species or sex (in the case of dioceous trees). Spatial structure, on the other hand looks at the arrangement of such characteristics in space. Spatial diversity refers to the arrangement of the characteristics in relation to each-other or in relation to a particular point on the ground. The woodland savanna in northern Namibia is supported by coarse Aeolian sands with poor water holding capacity and nutrient status. The trees that occur here need to cope with highly variable precipitation and high evaporation rates. Frequent fires and exploitation further affect the environment. Taken in combination, trees and especially their seedling have to cope with a wide variety of conditions over a very short period of time and have adapted accordingly. A number of the woodland species are frequently, though not exclusively, found in almost monospecific stands. This may be due to regeneration requirements, as in the case of P. angolensis (Graz 1996), the ability to compete, especially for water, as in the case of B. plurijuga (Mitlo¨hner 1997) or superior fire tolerance as in the case of B. africana (Rutherford 1981). The monospecificity of stands of S. rautanenii and T. sericea have not been investigated. T. sericiea, however, is a pioneer that may quickly colonize open areas where it may actually form thickets (Shackleton 2001). Bu¨schel (1999) reported on the other hand that stands dominated by S. rautanenii were comprised of trees of different sizes and species in the Okavango region of Namibia. Similarly, Mitlo¨hner (1997) also described stands of mixed species, comprising of P. angolensis, B. africana and B. plurijuga, while observations near the study site also showed mixed stands (unpublished data). [84]

1145 In addition to being almost monospecific, trees within many stands often seem to be of similar size although not necessarily of similar age. Childes (1984) reported, for instance, that B. plurijuga stands were of variable age despite the equal size of the trees. Plants remain small for a number of years until environmental conditions are suitable for further development. This is probably also the case for B. africana and S. rautanenii, although nothing seems to have been documented. The restriction of growth described by Childes for B. plurijuga is similar to the suffrutex development stage of P. angolensis reported by Vermeulen (1990). During this period seedlings from a number of years may accumulate in this developmental stage and develop together to the sapling stage when environmental conditions permit. In such cases the above ground parts are not of the same age as the roots. It is unclear if the differences in the ages of the roots will be reflected in the survival rate of the above ground parts of the trees. It is also uncertain whether or not whole stands of any of the above species will die off and be replaced by others at a different location, or whether the existing regeneration is sufficient to replace those trees that have died. The data pertaining to the structure of stands in northern Namibia currently available is superficial, despite its significant importance for management. Spatial diversity, or a lack of spatial diversity, has important implications. Consider for instance the effect of exploitation on an even sized, monospecific stand; selection based on a minimum diameter may result in a local clear-felling (Von Breitenbach 1968; Graz 1996). The resulting vegetation structure would be increasingly prone to fire that may cause further vegetation change, as well as subsequent erosion and nutrient loss (see Graz 1996). Causes of mortality are not necessarily only of human origin, however. The different sizes of a number of species have, for example, their own degree of fire tolerance. This means that trees up to a particular size class may be removed from a stand by a sufficiently intense fire. Wilson and Witkowski (2003) found that the bark-thickness of B. africana increases with tree circumference between 0 and 400 mm. The thickness of the bark is the primary protector against the effect of fire on the cambium. Fire tolerance may be overcome if the bark of trees is breached by animals (Yeaton 1988) or growth stresses (Graz 2003). Studies relating to spatial aspects have in the past concentrated on the dispersion of plants using measures such as the nearest neighbour of Clark and Evans (1954) or point to plant distances after Pielou (1977). More recently the uniform angle index (UAI) (Gadow 1999; Staupendahl 2001; Gadow et al. 2003) has been implemented to describe complex forest structures. The aggregation of tree attributes have only been addressed more recently by other measures, such as the ‘‘measure of surround’’ (Hui et al. 1998) or the spatial ‘‘mingling’’ (Gadow 1999). [85]

1146 The mingling measure is used to quantify the degree of interspersion or mingling of tree characteristics, as illustrated in Figure 1. Trees that are surrounded by others of similar characteristic are aggregated in terms of the characteristic, implying a lower degree of mingling of this characteristic. On the other hand, trees surrounded by others of dissimilar characteristic imply a higher degree of mingling. Mingling should not only be considered in terms of categorical data, such as species or sex, or whether a tree is alive or dead, but should be expanded to include any measure with which a tree might be described, including height or diameter. Albert and Gadow (1998) reported on the use of these neighbourhood-based measures to assess the effect of selective thinning on the diversity of a beech stand in Germany. The authors had found the measures to be sensitive to small-scale differences and changes of woodland structure, and were able to provide more intuitively acceptable results than the segregation index of Pielou (1977, p. 227 ff). This study aims to achieve two main objectives. The first objective is to assess the applicability of indicators that were developed and assessed in Europe to the Southern African context where little or no basic stand information is available for non-plantation areas. In addition, the study intends to generate information that will promote the understanding of the ecology of Namibia’s woodland resources. Description of the study area The woodland area that was enumerated covers approximately 70 ha and is situated between 1930¢ E, 1915¢ S and 1945¢ E, 1930¢ S near the Kanovlei Forestry Research Station in the western Tsumkwe district of the Otjozondjupa region, northeastern Namibia. The area is dominated by linear fossil dunes or sandy plains on calcareous deposition, similar to those in the adjoining Kavango region described by Graz (1999). The soils are Kalahari sands, classified as unconsolidated aeolian material by Coetzee (2001), with very poor water holding capacity and nutrient status, and subsequently a very low potential for any agricultural development (Department of Water Affairs 1991).

Figure 1. The mingling of black, grey and white ‘trees’ within two square stands (after Gadow, 1999). [86]

1147 The region is traversed by a system of omuramba (vegetated dry riverbed), with the soils classified as unconsolidated fluvial material (Coetzee 2001). These soils are shallower and have a heavier texture than the dunes (Department of Water Affairs 1971). Precipitation is mostly in the form of thunderstorms amounting to an average rainfall of between 500 and 600 mm per year (Amakali 1992). However, the distribution of precipitation is highly variable and prominently positively skewed. Expected rainfall is therefore significantly lower than the long-term averages. Rain generally falls in the period September to May, with most rain occurring between December and March. Average annual evaporation rates are between 2600 and 2800 mm (Crerar and Church 1988) resulting in an overall moisture deficit. de Pauw and Coetzee (1999) have determined an approximate growing period of between 91 and 120 days, based on the relationship between available moisture, the amount of evapotranspiration and the average air temperature. Although the general vegetation is described as tree savanna and woodland by Giess (1998), there is some significant variation in species and structural composition. The Directorate of Forestry identifies a number of dissimilar patches of forest or savanna (Chakanga 1995). While the sandy planes and dunes are dominated by Burkea africana, various species of Combretum, Pterocarpus angolensis, Schinziophyton rautanenii and Terminalia sericea. Scattered patches of Baikiaea plurijuga also occur. The lower lying omuramba vegetation is comprised primarily of Acacia erioloba, Dichrostachys cinerea and Philenoptera nelsii. Nuts from the S. rautanenii trees within the stand are harvested by local communities to augment their food supply, and by the Directorate of Forestry to obtain material for the National Tree Seed Centre and for ex situ conservation of genetic material. Additionally the stand shows signs of periodic wood harvesting of B. plurijuga stems, as well as for firewood. Dry season fires are frequent (Graz 2003).

Material and methods The interspersion of tree attributes The original measure of mingling and its derivatives are based on the proportion of trees with dissimilar characteristics to those of a selected sample tree. The species mingling index Mi for a given sample tree, i, using n neighbours is, for example, obtained through: ð1Þ

Mi ¼

n 1X mij ; n j¼1

[87]

1148 where


mij ¼

1; if the tree is of another species; 0; if the tree is of the same species:

When four neighbours are used to determine Mi the index may obtain one of five possible values: 0/4 none of the neighbours are of a different species, 1/4 one of the neighbours is of a different species, 2/4 two of the neighbours are of a different species, 3/4 three of the neighbours are of a different species, and 4/4 all of the neighbours are of a different species. The arithmetic mean (MSp) of the Mi values that were obtained for a particular species sp provides a measure of the degree of interspersion of the species in the area. MSp provides a value between 0 and 1. Values close to 0 indicate that trees of the reference species sp occur in groups therefore implying a low degree of mingling and high degree of aggregation. High values of MSp, closer to 1, on the other hand, imply a high degree of mingling, i.e. trees of the reference species do not occur together. As is the case when examining the distribution of data around a mean value, additional information may be extracted from the distribution of Mi values of individual species. When the proportion that a species contributes to a stand is known, as assumed in the studies reported on by Lewandowski and Pommerening (1997) and Hui et al. (1998) a theoretical distribution of Mi values may be calculated based on the hypergeometric probability distribution. The distribution reflects the number of expected Mi values that would be obtained if all trees were interspersed randomly. The hypergeometric distribution is used to determine the probability, P, that a number of trees of a particular species may occur in a given sample of n trees taken from a population of N trees containing k trees of the species of interest. The probability that x trees in the sample will be of the species of interest is then determined after Newmark (1997) as:     k N
k  x n
x   P¼ for x ¼ 0; 1; 2; . . . ; n; N n which expands to: P¼

k xðk
xÞ

ðN
kÞ  ðn
xÞðN
k
ðn
xÞÞ N nðN
nÞ

for x ¼ 0; 1; 2; . . . ; n:

The resulting probability multiplied by the total number of samples that were taken provides the expected number of Mi values for that species. The [88]

1149 observed and expected distributions of Mi values may then be compared with the application of standard statistical methods to test for significance of deviations from the theoretical (random) distribution. Although no detailed data is available for any of the woodland areas in Namibia, and the extent of the woodland areas hampers the collection of such information, the sample size provided a suitable estimate of the species composition of the stand. The simulation study reported on by Graz (2004) has shown that the mingling index is sensitive to the species composition of a stand. In a stand of trees interspersed randomly, for example the aggregation of a species, 1
MSp, approximates the proportion that a species Sp contributes to the stand. This may be more intuitively understood if we consider each sample tree to provide an estimate of the proportion that its species contributes to the stand. Values of 1
MSp which are greater than the proportion contribution therefore indicate an overaggregation of the species, while lower values imply overdispersion within the stand. This relationship provides an important base from which the index may be interpreted. This study investigated the interspersion of a number of tree characteristics. In addition to the mingling of species described above, the interspersion of tree dominance is quantified on the basis of diameter (TSp) and height (HSp) using the ‘‘measure of surround’’ described by Hui et al. (1998), and which is applied in a method analogous to that of the mingling index. More particularly: ð2Þ

Ti ¼

where


tij ¼

1;

n 1X tij ; n j¼1

if the tree; j; is thicker than the sample tree i; 0; otherwise:

The species specific mean interspersion of tree diameter, TSp, is then the arithmetic mean of the values of Ti for that species. Similarly, the interspersion of tree height, Hi, is obtained through: ð3Þ

Hi ¼

where


hij ¼

1;

n 1X hij ; n j¼1

if the tree; j; is higher than the sample tree i; 0; otherwise:

The species specific interspersion of tree height, HSp, is then again determined as the mean of the values of Hi for the species. An equivalent measure was used to quantify the interspersion of dead trees (DSp) by counting the number of dead neighbours for each sample tree. [89]

1150 Uniform angle index The UAI was initially described by Gadow et al. (1998) and later by Staupendahl (2001) to provide a measure of the overall contagion of trees within a forest stand. The index is obtained by identifying the n nearest neighbours of a sample tree. Starting with the closest neighbour and moving in a clockwise direction around the sample tree the angle, aj, between two adjacent neighbours is determined in relation to the sample tree. The number of angles smaller than, or equal to, a given critical angle, a0, are then counted, i.e. ð4Þ

Wi ¼

where


wij ¼

1; 0;

n 1X wij ; n j¼1

if aj  a0 ; otherwise:

The critical angle (in degrees) is determined as: ð5Þ

a0 ¼

360 : Number of neighbours

Four neighbours would therefore be evaluated in terms of a 90 critical angle1. Since all of the indexes used to measure the interspersion of tree characteristics were based on four trees, the same neighbours could be used for the UAI. A practical advantage of choosing a0 = 90 is that two adjoining sides of a record book or clipboard may be used to determine whether or not an angle is greater than or less than the critical angle. Effectively, the index describes the spatial distribution around a particular reference tree. If the species of the reference tree is noted we may obtain the mean value for either for the whole population or for a particular species of interest. The mean value of the index is strongly correlated with the nearest neighbour index of dispersion of Clark and Evans (1954) that has long been used in ecological studies. Together with the number of trees in a stand, the UAI may be used to estimate the distribution of distances between a tree and its neighbours (Gadow et al. 2003). This information is generally not available and comparison of observed index values are compared to the simulation results of Gadow et al. (1998) are used.

1

More recent studies have shown that this statement needs to be modified; a more suitable critical angle is 72 (see Gadow et al. 2003). [90]

1151 Sampling The extent of the stand was recorded in the field using a Garmin Venture GPS. The track-log was stored for subsequent mapping. A regular sample grid of one geographic second was then superimposed on the stand amounting to a sample point approximately every 30 m at that latitude. Sampling points were located using a standard GPS receiver. The accuracy of autonomous GPS readings was considered adequate for the purpose of the study. While a dense canopy reduces the reliability of a GPS reading within a stand (Dominy and Duncan 2001), many of the trees in the area had already shed their leaves and canopy interference was considered negligible after initial comparison of signal strengths in wooded and in open areas. Since the enumeration coincided with the war in Iraq it is uncertain whether GPS readings were affected by selective availability on some days. It was felt, however, that this was acceptable. At each sample point the closest tree with a dbh of 5 cm or more was identified to serve as reference tree. Although trees had, in a few cases, snapped off below breast height, such trees were nevertheless sampled, since they play a role in the interspersion of plants. For each sample tree the four nearest neighbouring trees with a diameter of greater than 5 cm were determined and compared with the reference tree in terms of species, mortality, height and diameter, and the UAI was established. Time was kept short by assigning two persons to each sampling team. While the enumerator collected the measures, a navigator moved to find the next sample point. A total of 1121 sample points were assessed. The data was entered into a spreadsheet and the indexes were calculated for each species using cross tables.

Results and discussion The species specific indexes are summarized in Table 1. The table also shows a surrogate species of ‘Dead’ created to record trees that were still standing but had been burnt beyond a stage where they might be identified. Also, species of the genus Combretum and Comiphora were lumped, as individual species could not readily be identified. The row marked ‘overall’ provides the each index as calculated over the entire data set. The overall shows a contagion (Wi) greater than 0.6, here indicating a tendency towards non-random (clumped) dispersion of trees (after Gadow et al. 1998). The dispersion around trees of the individual species does not seem to diverge very much from the mean value of 0.665, if Philenoptera nelsii and Securidaka longipedunculata are discounted because of their very low overall occurrence. This is in line with general observations in the field. The table shows that most of the species have a tendency to aggregate.

[91]

1152 To compare the proportion of a given species within the stand and the value 1
MSp consider Table 2. The table omits those species with very few observations (less than 5% of the total). The final column in the table reflects the parameter M proposed by Graz (2004) to determine the degree of interspersion. The value of M is larger than 0 and less than or equal to 1. Values close to 0 indicates a very low degree of mingling, and 1 indicates a more random distribution of the species in the stand. Table 2 shows that B. plurijuga has the highest degree of aggregation followed by Terminalia sericea. More T. sericea seedlings survive in open areas, i.e. away from conspecific trees (Smith and Grant 1986) where it has the ability to form thickets (Shakelton 2001). This was evident in the field. T. sericea would colonize gaps in the canopy, thus causing the aggregation. The dispersion of B. plurijuga is also shown in Figure 2. The figure shows that the species occurs in a very limited area. The accompanying graph shows the relative distribution of Mi values (bar) and the theoretical hypergeometric distribution. The graph shows a clear difference between the two, due to the clumping of the species, reflected by the low value of M (Table 2). The cause of the aggregation of B. plurijuga is uncertain, since the trees had few larger neighbours as evidenced by the low value of TSp in Table 1. It is possible that the patch of B. plurijuga is a remnant of a larger stand that has been subject to high degrees of mortality. This possibility stems from reports by Von Breitenbach (1968) who suggested that the almost pure stands in the Caprivi region developed towards mixed stands as a result of fire. The possibility is corroborated by the high degree of mortality (DSp) associated with the species (see Figure 3). The dead trees within the B. plurijuga Table 1. Mean of the various indicators for each of the identified species. Species of sample tree

N

P(Sp)

WSp

DSp

MSp

TSp

HSp

Burkea africana Baikiaea plurijuga Combretum species Comiphora species Ochna pulchra Philenoptera nelsii Pterocarpus angolensis Schinziophyton rautanenii Securidaka longipedunculata Strychnos pungens Terminalia sericea Unidentifiable dead tree Overall

116 194 214 36 26 16 178 75 2 26 96 142 1121

0.103 0.173 0.191 0.032 0.023 0.014 0.159 0.067 0.002 0.023 0.086 0.127 1.0000

0.688 0.665 0.657 0.639 0.635 0.750 0.647 0.653 0.625 0.683 0.641 0.701 0.665

0.226 0.116 0.148 0.201 0.087 0.141 0.163 0.137 0.125 0.163 0.130 0.285 0.169

0.751 0.653 0.697 0.875 0.962 0.820 0.813 0.875 0.962 0.893 0.781

0.323 0.249 0.484 0.382 0.567 0.563 0.198 0.243 0.375 0.462 0.565

0.332 0.256 0.479 0.556 0.673 0.625 0.218 0.300 0.625 0.548 0.602

0.794

0.360

0.399

P(Sp) denotes the proportion that a species contributes to the stand as a whole. The species specific indicators are: WSp = mean UAI, DSp = mean mortality, MSp = mean mingling, TSp = mean diameter dominance, and HSp = mean height dominance. The overall values for each indicator was calculated using the entire data set. [92]

1153 Table 2. Comparing the proportion P(Sp) that a species contributes to the population with (1
MSp). Species of sample tree

N

P(Sp)

MSp

1
MSp

P ðpÞ M ¼ 1
M Sp

Baikiaea plurijuga Burkea africana Combretum species Pterocarpus angolensis Schinziophyton rautanenii Terminalia sericea Unidentifiable dead tree Total

116 194 214 178 75 96 142 1121

0.103 0.173 0.191 0.159 0.067 0.086 0.127

0.653 0.751 0.697 0.813 0.875 0.781

0.347 0.249 0.303 0.188 0.125 0.219 0.285*

0.298 0.696 0.631 0.883 0.627 0.391 0.447

*Note that the value of DSp is used here (the mean proportion of dead neighbours), rather than the mingling index.

patch, shown in figure 3, are generally large trees. This is not evident from the indexes but supports the suggestion by Von Breitenbach cited above. Actual tree mortality may be caused directly by repeated burning of the stem, as well as changes in the osmotic potential of the top-soil that is caused by the accumulation of ash in the upper soil layers (Mitlo¨hner pers. comm.) In contrast to B. plurijuga, P. angolensis is interspersed almost randomly according to Table 2 and in Figure 2. As is evident in the figure, the observed distribution of Mi values (bars) follow the theoretical distribution much more closely than those of B. plurijuga. It must be noted, that P. angolensis occurs comparatively seldom within the B. plurijuga patch. This exclusion from the patch is more pronounced for B. africana. The reason or cause for this is not readily apparent. Outside this patch B. africana is more aggregated resulting in the lower value of M. The random distribution of P. angolensis is probably a reflection of the regeneration requirements of the species. Vermeulen (1990) reports that P. angolensis is especially sensitive to competition in the seedling and establishment phases. The species therefore often regenerates in areas that have been cleared by human or other action. Other species would then establish themselves later. The interspersion of trees of different size is reflected in the columns TSp (diameter specific) and HSp (height specific) in Table 1. Preliminary simulation results have shown that a random interspersion of tree sizes would result in an overall average of TSp = 0.5 and HSp = 0.5. The table shows, therefore, that size classes are not interspersed randomly. P. angolensis, S. rautanenii and B. plurijuga need to be highlighted. The low values of TSp and HSp for these species imply that few neighbouring trees are larger than the reference tree. This is supported by general observations in the field. The species therefore dominate in the area in which they occur. It also reflects the regeneration requirements of P. angolensis noted previously, but highlights the importance of further research into the demography of the other two species. [93]

1154

Figure 2. The dispersion of Baikiaea plurijuga, Pterocarpus angolensis and Burkea africana, within the study area. High values of Mi are shown in large circles and vice versa. The graphs depict the observed relative distribution of Mi values (bars), and the theoretical hypergeometric distribution (lines) of the values that would indicate a completely random interspersion of the species.

Table 1 also shows a similarity between the values of TSp and HSp of the individual species. Unpublished data shows a high degree of correlation between the dbh and height of B. africana (r2 = 0.8352), as well as for P. angolensis (r2 = 0.7317) for nearby stands. [94]

1155

Figure 3. The aggregation of dead trees within the stand. The degree of interspersion is reflected by the size of the points, with a high degree of aggregation shown by larger points.

Differences between the two indexes are due to the number of species found in the stand, and the differences in their respective diameter
height relationships. A larger difference occurs for the Comiphora species, however, reflecting the squat form of the trees; a relatively thick-trunked but short tree.

Conclusions In the past the applications of neighbourhood-based spatial measures were supported by detailed knowledge of the stands that were assessed, as noted above. This was not the case in this study, where only the extent of the stand was known. However, despite their simple application the indexes are able to provide information about the stands they describe, being able to reflect much of what is currently known about the individual tree species and their ecological circumstances. The results have also highlighted gaps in our knowledge of the ecology of a few of the important trees, such as Schinziophyton rautanenii, Baikiaea plurijuga, and Burkea africana, as well as the various Combretum species that occur in the area. These include regeneration requirements and species succession, and highlights the need for further investigation. The application of the measures described here has shown that they are easily applied in the field with relatively little training required, although the field crews will have to be able to identify the different tree species. This is particularly useful in view of the trend towards community based natural resource management in Namibia, where community members will have to assess their own resources. Since most of the rural community members are able to identify different plants in their vernaculars, species identification should not be a problem, despite sometimes limited literacy levels. [95]

1156

Acknowledgements I would like to thank my sister Ms. H. Riehmer and Ms. R. Haipinge as well as the late Mr. H. Roth for their assistance with data collection in the field. My sincere thanks also to the Directorate of Forestry, Namibia, for allowing me to use the Kanovlei Forest Station as a base, and the Polytechnic of Namibia who funded the field work. I would particularly like to thank Prof. K. von Gadow, Institute of Forest Management, Univeristy of Goettingen for comments.

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Biodiversity and Conservation (2006) 15:1159–1177 DOI 10.1007/s10531-004-3509-3


Springer 2006

-1

Assessment of threat status and management effectiveness in Kakamega Forest, Kenya BA¨RBEL BLEHER1,2,*, DANA USTER3 and THOMAS BERGSDORF 4 Institut fu¨r Zoologie, Abt. V- O¨kologie, Johannes Gutenberg-Universita¨t Mainz, Becherweg 13, 55099 Mainz, Germany; 2Department of Ornithology, National Museums of Kenya, Nairobi, Kenya; 3 Universita¨t Bielefeld, Fakulta¨t fu¨r Biologie, Abt. O¨kologie, Universita¨tsstrasse 25, 33615 Bielefeld, Germany; 4Zoologisches Forschungsinstitut & Museum Alexander Koenig, Adenauerallee 160, 53113 Bonn, Germany; *Author for correspondence (e-mail: [email protected]; phone: +49-(0)61313926108; fax: +49-(0)6131-3923731) 1

Received 6 May 2004; accepted in revised form 6 September 2004

Key words: Conservation, Disturbance indicator, Forest degradation, Logging, Management Abstract. To counteract an increasing biodiversity decline, parks and protected areas have been established worldwide. However, many parks lack adequate management to address environmental degradation. To improve management strategies simple tools are needed for an assessment of human impact and management effectiveness of protected areas. This study quantifies the current threats in the heavily fragmented and degraded tropical rainforest of Kakamega, western Kenya. We recorded seven disturbance parameters at 22 sites in differently managed and protected areas of Kakamega Forest. Our data indicate a high level of human impact throughout the forest with illegal logging being most widespread. Furthermore, logging levels appear to reflect management history and effectiveness. From 1933 to 1986, Kakamega Forest was under management by the Forest Department and the number of trees logged more than 20 years ago was equally high at all sites. Since 1986, management of Kakamega Forest has been under two different organizations, i.e. Forest Department and Kenya Wildlife Service. The number of trees logged illegally in the last 20 years was significantly lower at sites managed by the Kenya Wildlife Service. Finally, logging was lower within highly protected National and Nature Reserves as compared to high logging within the less protected Forest Reserves. Reflecting management effectiveness as well as protection status in Kakamega Forest, logging might therefore provide a valuable quantitative indicator for human disturbance and thus an important tool for conservation managers. Logging might be a valuable indicator for other protected areas, too, however, other human impact such as e.g. hunting might also prove to be a potential indicator.

Introduction Recent decades have seen a serious biodiversity decline due to habitat loss and alteration especially of tropical forests leading to a profound species-extinction crisis (Heywood 1995; Pimm et al. 1995; Whitmore 1997). Thus, much of tropical biodiversity is unlikely to survive without effective protection (Pimm et al. 1995; Myers et al. 2000). To counteract the anthropogenic impact and conserve biodiversity and ecosystem processes parks and protected areas have been established worldwide. Some studies demonstrate that parks can indeed provide basic safeguard against land-clearing in the context of high land-use pressure (Brunner et al. 2001). However, more often parks appear to lack [99]

1160 adequate management to address a host of threats within their borders (Brunner et al. 2001; Putz et al. 2001; Ervin 2003a, b). Protected areas face increasing levels of environmental degradation with more than 70% of 201 parks surveyed across 16 tropical countries being affected by poaching, encroachment and logging (van Schaik et al. 1997). Consequently, the improvement of management strategies of protected areas is of top priority for conservation practitioners. To improve and optimise management strategies methods to assess the threat status of protected areas and to measure management effectiveness of conservation efforts have become a major environmental concern (Margoluis and Salafsky 1998; Salafsky and Margoluis 1999; Hockings et al. 2000; Salafsky et al. 2002; Ervin 2003c; Hockings 2003). These assessments are an essential component of systematic conservation planning (Margules and Pressey 2000); they can enable conservation managers and policymakers to identify management strengths and weaknesses, reveal severity and distribution of levels of human impact, respond to pervasive management problems, refine their conservation strategies and reallocate budget expenditures (Brunner et al. 2001; Ervin 2003 a, c; Parrish et al. 2003). Therefore, the development of simple tools to monitor and assess whether conservation succeeds for protected areas are of great importance and require indicators that are measurable, scientifically sound, and comparable among protected areas over time, but also practical and cost-effective (Margoluis and Salafsky 1998). Traditionally, biological indicators have been used to assess the level of human impact in protected areas and measure management success. Ideally, they are supposed to serve as indicators for changes in the overall biodiversity of a site (Noss 1990; Sparrow et al. 1994). However, relationships between potential indicator species and total biodiversity as well as critical ecosystem processes are not that well established (Lindenmayer et al. 2000). Few of these methods using biologically based indicators are practical and cost-efficient, especially for use in the developing countries as they require substantial effort and resources beyond day-to-day project activities (Salafsky and Margoluis 1999). Finally, their results are often difficult to interprete for non-specialists and generally require the presence of baseline data against which to compare changes (Salafsky and Margoluis 1999). Another approach to assess human impact in protected areas and to assess management effectiveness is to identify and monitor threats directly as a proxy measurement of conservation success such as e.g. implemented in the Threat Reduction Assessment (TRA) (Salafsky and Margoluis 1999) and the Rapid assessment and Prioritization of Protected Area Management (RAPPAM) program recently established by WWF’s Forest for Life program (Ervin 2003c). This approach of directly identifying threats is sensitive to changes over short time periods and throughout a site, comparisons among projects and sites are possible, data can be collected through simple techniques and the method is practical and cost-effective. Furthermore, the results can be readily interpreted by conservation staff and can provide detailed, adaptive management guidance [100]

1161 to protected area managers. The primary tool for RAPPAM is the rapid assessment questionnaire which covers management planning, input and processes, and the identification of future threats and past pressures (Ervin 2003c). However, quantitative and objective approaches are still urgently required for the assessment of threat status and management effectiveness of protected areas to provide reliable, scientifically sound data. In this paper we present results from a survey quantifying human impact and evaluating management effectiveness in Kakamega Forest, western Kenya. Kakamega Forest is one of the last remaining indigenous forests of Kenya situated in an agricultural area with a high human density of more than 175 individuals per km2 (Tsingalia 1988). Like many other countries Kenya harbours an on-going conflict between forest conservation and land use needs of its increasing population (Tsingalia 1988; Wass 1995). This has put a longterm pressure on Kakamega Forest leading to its severe reduction and fragmentation in the last century. Additionally, it has suffered increasing degradation through both, extensive commercial and local exploitation of timber (Tsingalia 1988; Fashing et al. 2004; Mitchell, 2004). Large-scale commercial logging was reduced in the last decades, mostly through official presidential decree banning all indigenous tree species exploitation in the forest in the early 1980s (Tsingalia 1988; Mitchell, 2004), the transfer of the northern part of the forest under the rigorous authority of the Kenya Wildlife Service (KWS), the establishment of forest stations and ranger patrols, and through tourism and long-term research (e.g. Zimmerman 1972; Cords 1987; Mutangah 1996; Fashing et al. 2004). However, illegal activities including logging, fuelwood collection and extraction of bark for medicinal purposes occur to this day and appear to be heterogeneously throughout the forest with some sites providing more protection than others (Kiama and Kiyiapi 2001; Fashing et al. 2004; Fashing, in press). Our study presents a quantitative assessment of the current threats in the main forest block of Kakamega Forest and its fragments comprising areas of different management regimes and different protection priorities. In order to evaluate effectiveness of conservation measures we asked how differently managed and protected areas differ in their level of human impact. With this assessment we aim to provide a quantitative, simple site-level monitoring tool and a first guidance to management planners and decision makers on problems related to human impact and management in Kakamega Forest.

Kakamega Forest and its forest history Study site We conducted the study at Kakamega Forest (between latitudes 0008¢30.5¢¢ N (41,236 in UTM 36 N) and 0022¢12.5¢¢ N (15,984) and longitudes 3446¢08.0¢¢ E (696,777) and 3457¢26.5¢¢ E (717,761), G. Schaab, personal communication), [101]

1162 western Kenya, at an altitude of 1500–1700 m (Figure 1). Kakamega Forest is a mid-altitudinal tropical rainforest and considered to be the eastern most remnant of the lowland Congo Basin rainforests of Central Africa (Kokwaro

Figure 1. Satellite image (channel 5 of Landsat 7 ETM+, 05 Feb 2001) of Kakamega main forest and its five fragments in western Kenya with official forest boundaries as gazetted in 1933 (dashed line) and official boundaries of National and Nature Reserves (white line). Coordinates in UTM 36 N. [102]

1163 1988). Annual rainfall in Kakamega Forest is approximately 2007 mm (as averaged from FD records at Isecheno Forest Station from 1982 to 2001) and highly seasonal with a rainy season from April to November and a short dry season from December to March. The average monthly maximum temperature ranges from 18 to 29 C while the average monthly minimum ranges from 4 to 21 C (Muriuki and Tsingalia 1990).

Management history Kakamega Forest was first gazetted as Trust Forest under proclamation No. 14 in 1933 and has since been managed by the FD; in 1964 it was declared to be a Central Forest (Blackett 1994). Three small Nature Reserves, Isecheno, Kisere and Yala, were established and gazetted within the Forest Reserve in 1967 (Blackett 1994). In 1986, the northern part of Kakamega Forest called Buyangu together with the adjacent Kisere Forest was gazetted as Kakamega National Reserve and fell under management of the KWS. Today, Kakamega Forest is part Forest Reserve, part Nature Reserve and part National Reserve, and management is under the authority of both, FD and KWS, on behalf of the state.

Fragmentation and disturbance history Kakamega Forest is a highly fragmented and disturbed forest and has been continually exploited for many years due to the high surrounding population pressure (Kokwaro 1988; Wass 1995). The main forest block gazetted in 1933 by the FD to control human activities covered 23,777 ha (Kokwaro 1988, for original forest boundaries see Figure 1). The FD aimed mostly at provision of timber for local communities and commercial demand. Clear-felling of indigenous forest to make way for fast-growing exotic tree and softwood plantations was extensive under colonial forest service. Especially the southern parts of Kakamega were exploited until the late 1980s (Bennun and Njoroge 1999; Mitchell, 2004). Clearance for settlement and tea plantations slowed over the 1980s as forest protection was better enforced, but more areas were cleared south of the Yala river (Brooks et al. 1999). Furthermore, selective logging was intense in the past and the general trend of timber extraction showed a continued rise from 1933 to 1981 (Tsingalia 1988; Mutangah 1996). Consequently, the main agents of forest degradation have been mostly logging and extraction of commercially valuable timber, followed by charcoal burning, cattle grazing, shamba system farming, hunting for bush-meat, tree debarking and removal of dead trees for firewood (Oyugi 1996; Mitchell, 2004). In the early 1980s a presidential decree banned all indigenous tree species exploitation, leading to a halt of commercial logging, however, tree poaching and other illegal activities still exist. [103]

1164 Table 1. List of 22 disturbance survey sites in Kakamega Forest. Site No. Site name

Main forest/ Area Transect Area Management Protection fragmenta (ha)b length (m) surveyed (ha) regimec statusd

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22

f f mf mf mf mf mf mf mf mf mf mf mf mf mf f f f f f f f

Malava Kisere Colobus Buyangu Shikusa Salazar I Salazar II Shamiloli Central II Central I Chemneko Vihiga Sawmill Isecheno II Isecheno I Chepsugor Ikuywa I Ikuywa II Yala Kibiri Ishiru Kaimosi

77 420 8245 8245 8245 8245 8245 8245 8245 8245 8245 8245 8245 8245 8245 1370 1370 1370 1178 1178 1178 65

1200 2600 2400 1600 1000 1000 2000 1000 1000 1000 1000 1000 1000 1000 1600 1000 1000 1600 2000 1000 1000 280

2.4 5.2 4.8 3.2 2.0 2.0 4.0 2.0 2.0 2.0 2.0 2.0 2.0 2.0 3.2 2.0 2.0 3.2 4.0 2.0 2.0 0.6

fd kws kws kws kws kws kws fd fd fd fd fd fd fd fd fd fd fd fd fd fd fd

fr nr nr nr nr nr nr fr fr fr fr fr fr nr nr fr fr fr nr nr fr fr

a

Abbreviationss: f, fragment; mf, main forest block. Area sizes obtained from satellite image 05 Feb 2001 Landsat 7 ETM+. c Abbreviations: fd, Forest Department; kws, Kenya Wildlife Service. d Abbreviations: fr, Forest Reserve; nr, National or Nature Reserve. b

As a consequence of the long fragmentation and disturbance history Kakamega Forest was reduced and broken up in several fragments over the last century and today the main forest block covers only 8245 ha (G. Schaab, personal communication; for fragment sizes see Table 1) comprising a heterogenous mixture of different succession stages including disturbed primary forest, secondary forest, clearings and glades, as well as tea and timber plantations (Bennun and Njoroge 1999). For more detailed information on the fragmentation and disturbance history of Kakamega Forest see Tsingalia (1988) and Mitchell (2004).

Methods Disturbance survey In February and April 2002 and in June and July 2003, disturbance surveys were carried out at 22 forested sites in Kakamega main forest and its peripheral fragments (for a complete list of all sites see Table 1). Twelve of the 22 sites [104]

1165

Figure 2. Location of 22 disturbance survey sites in Kakamega Forest (left) and the number of trees logged per hectare in the last 20 years for both, trees 610 cm in diameter and >10 cm in diameter for each site, respectively (right).

chosen for surveys were close to the 12 sites where Mutangah (1996) carried out his disturbance surveys in 1992/1994 (see Table 1); an additional 10 new sites where chosen where Mutangah (1996) had not carried out any surveys in the past (e.g. in the fragments Kisere, Malava and Kaimosi). This was done in order to obtain a large sample size of representative sites distributed over the whole Kakamega Forest. The sites chosen were not necessarily near points of easy access (Figure 2); in fact, many of the sites are located in the centre of the forest (e.g. No. 5, 9, 10). With many trails running through the whole of Kakamega Forest, it is easily accessible for local exploitation. At each site except for the smallest fragment (Kaimosi), transects were run at least 1000 m in length (Table 1). Transects sometimes followed existing trails, e.g. at Colobus site we chose some of the former overgrown monkey research transects established by Gathua in 1996 (Fashing and Gathua, in press). In all other cases where trails did not exist, we made our way through undergrowth along a line. Surveys included recording any of seven disturbance parameters in a belt [105]

1166 of 10 m on each side of the transect thereby covering a total area of 56.6 ha with a median of 2 ha per site (range 0.6–5.2). All disturbances recorded are thought to present mostly illegal activities. Disturbance parameters recorded were 1. the number of trees logged: For each tree stump the circumference was measured to calculate its diameter. Trees with a diameter of less than 10 cm were assumed to be collected mostly by women and used as firewood, whereas trees with a diameter of more than 10 cm were assumed to be cut mostly by men and used as polewood or timber. For each stump the approximate time since cutting was estimated to be either less than 20 years or more than 20 years for a distinction between recent and past logging, respectively. Age was estimated according to the degree of decomposition and the shape of the remaining tree stump, i.e. stumps with smooth surfaces or freshly cut stumps with clear cutting profiles were estimated to be logged in the last 20 years, whereas stumps with wavy or semi-decayed cut surfaces were estimated to be logged more than 20 years ago (following Mutangah 1996). Tree species were identified when possible; however, for trees having been logged more than 20 years ago, species identification was not always possible due to a higher level of decomposition. 2. the number of trees exhibiting any signs of debarking for medicinal use. 3. the number of charcoal kilns, i.e. areas with charcoal remains such as black half-burned pieces of wood and in some cases still burning charcoal heaps. 4. the number of sawing pits, i.e. pits used for cutting large trees. 5. the number of honey gathering sites, i.e. tree stems with bee-hives from which honey had been extracted. 6. the number of abandoned and current paths used by locals e.g. for firewood collection. 7. the number of cattle tracks used to bring cattle to the glades for grazing.

Data analysis We tested the influence of management regime and protection status on the disturbance parameters 1–7 for all 22 sites. For disturbance parameter 1, we tested the influence separately on the number of logged trees of two different age classes (trees logged in the last 20 years, trees logged more than 20 years ago) and two different size classes (diameter  10 cm, diameter >10 cm). For management regime we distinguished between sites being managed by the KWS (n = 6) and the FD (n = 16) (Table 1). For protection status we distinguished between sites with high protection priority i.e. National or Nature Reserves (n = 10) and sites with low protection priority i.e. Forest Reserves (n = 12) (Table 1). Consequently, 6 National/Nature Reserves are managed by the KWS and 4 National/Nature Reserves and 12 Forest Reserves by the FD. Furthermore, we tested the influence of fragmentation on the number of logged trees for both, the two different age and size classes. We calculated [106]

1167 t-tests (t) for normally distributed data with an adjustment in case variances were unequal and Mann–Whitney U-tests (U) for non-normally distributed data. We correlated the different disturbance parameters calculating nonparametric pairwise Spearman correlations. We compared our data from 12 sites (i.e. site No. 5, 7, 8, 11–13, 15–17, 19– 21) with data from Mutangah (1996) who quantified the same disturbance parameters in 1992/1994 at the same 12 sites. Although the sites were the same, transects were not; thus, data are not dependent data. For comparisons of the two data sets we calculated Pearson and Spearman rank correlations for normally and non-normally distributed data, respectively. Data analysis was carried out using JMP (1995).

Results Evidence for human impact was found at all our 22 sites with a median number of 21.1 disturbance events per hectare (q1 = 9.8, q3 = 44.6, range 1.8–81.5, n = 22). The sites Salazar II (No. 7) situated in the northern Kakamega National Reserve and managed by the KWS as well as Yala (No. 19) situated in the Yala Nature Reserve managed by the FD showed lowest disturbance levels with 2.8 and 4.9 disturbances per hectare, respectively (Table 2). The site Ishiru (No. 21) had highest disturbance levels with 68.5 disturbances per hectare; is situated at the southern forest edge and is managed by the FD.

Management, protection status and logging Of all seven disturbance parameters, logging of trees was the most widespread at all 22 sites (Table 2), thus providing the most useful indicator of forest disturbance in this study. Over a total survey area of 56.6 ha, we found 1023 logged trees from 68 species. The most frequent tree species logged were Funtumia africana (2.1 trees logged per hectare), Prunus africana (1.3), Celtis new species name: Celtis gomphophylla (1.0), Trilepisium madagascariensis (0.9), Diospyros abyssinica (0.8) and Aningeria altissima (0.7). The average diameter of tree stumps was 27.0 cm ± 9.6 (if not otherwise noted mean ± 1 SD). Past and present logging We could not find differences in the number of logged trees for past logging (i.e. more than 20 years ago) between different sites indicating that logging levels in the past might have been similar throughout Kakamega Forest (Figures 3a, b; management regime, U: Z = 0.26, p = 0.79; protection status, t: t = 2.32, df = 1, p = 0.15). In contrast, a significant effect of management regime and protection status was found for present logging (i.e. in the last [107]

1168

Table 2. Summary data of disturbance survey for all 22 sites.

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Site No.

No. trees logged/ha >20 years

No. trees logged/ha 20 years ago, trees logged 10 cm) had low levels at KWS sites, but high levels at FD sites (Figure 2). Both, firewood collection and logging for polewood/timber was significantly higher at FD sites as compared to KWS sites (firewood/ha: KWS median = 0, q1 = 0, q3 = 0.3, range 0–1.2, FD median = 5.5, q1 = 1.6, q3=17.3, range 0–26.0; U: Z =
3.04, p = 0.0024; polewood/ha: KWS 2.9 ± 2.6; FD 16.9 ± 12.7; t: F = 16.54, df = 1, p = 0.0007). Similarly, significant differences in the number of logged trees for both firewood and polewood/timber, were found between sites of high and low protection priority (firewood/ha: high protection median = 0, q1 = 0, q3 = 2.0, range 0–19.0, low protection median = 10.0, q1 = 1.8, q3 = 17.3, range 0–26.0; U: Z =
2.55, p = 0.011; polewood/ha: high protection median = 3.2, q1 = 1.5, q3 = 8.1, range 0–26.5, low protection median=15.4, q1 = 7.4, q3 = 26.3, range 2.5–47.5; U: Z =
2.61, p = 0.0092). Fragmentation and logging No differences were found between the main forest and the fragments for the number of trees logged more than 20 years ago and less than 20 years ago, as well as for the number of trees logged for firewood and for polewood/timber (trees logged >20 years ago: U: Z = 0.44, p = 0.64; trees logged < 20 years ago: U: Z = 0.83, p = 0.4037; firewood/ha: U: Z = 1.57, p = 0.1164; polewood/ha: U: Z = 0.03, p = 0.97). Re-assessment of logging: 1992/1994 and today No differences for the number of logged trees per hectare were found between our data and those of Mutangah’s (1996) survey in 1992/1994. This suggests a similar overall logging level (1992/1994: 40.6 ± 34.4, today: 29.2 ± 25.2; t: t = 0.92, df = 22 p = 0.37). Furthermore, we found a significant positive correlation between both data sets suggesting that transects at the same sites still have same logging levels after 10 years (Pearson: r = 0.72, p = 0.0088).

Management, protection status and other human impact For all other disturbance parameters differences between differently managed and protected sites were only found for the number of charcoal kilns with significantly lower numbers in highly protected sites (high protection: median = 0, q1 = 0, q3 = 0, range 0–1.0, low protection: median = 0.5, q1 = 0, q3 = 1.8, range 0–4.5; U: Z =
2.26, p = 0.024). However, in contrast to the number of logged trees, all other disturbance parameters were mostly rare events and appear to be indicators only for localized threats (Table 2). Burning of charcoal, e.g., seems to be a serious threat at the eastern (No. 11, 12) and western edge (No. 8) of the main forest block, whereas cattle tracks appear to be a problem mostly at Isecheno I (No. 15) and at the eastern edge of the forest (No. 8) (Table 2). In [110]

1171 general, no correlation could be found between the disturbance parameters when calculating non-parametric pairwise Spearman correlations (p > 0.05).

Discussion Status quo of human impact According to our survey human impact is found everywhere in Kakamega Forest with logging being most widespread. This confirms the expressions of alarm over the misuse and overexploitation of Kakamega’s forest resources through illegal human activities (Kowkaro 1988; Emerton 1991; Mutangah et al. 1992; Wass 1995; Oyugi 1996; Fashing et al. 2004). Our data support Mutangah’s (1996) survey from 1992/1994 indicating the highest logging levels occur in the most southerly part of the forest as well as along the western edge. Furthermore, some of the disturbed sites (e.g. No. 11, 21) in Mutangah’s (1996) survey have been degraded heavily in the meantime and the canopy cover reduced substantially (N. Saijita and C. Analo, personal communication). In both, Mutangah’s (1996) and our survey, the lowest logging levels were found in the northern Kakamega National Reserve, central Ikuywa and Yala.

Human impact in differently managed areas Our data do not only show the current status quo of the human impact on Kakamega Forest, but also reflect its management history in the last 20 years. Before 1986, when all of Kakamega Forest was managed by the FD, Colobus, Buyangu and Salazar sites (No. 3, 4, 6, 7) in the northern part were well known for intensive commercial logging through timber companies (Tsingalia 1988; Mitchell, 2004). Correspondingly, the number of trees logged more than 20 years ago appears to be equally high at those sites as compared to others. In 1986, the KWS took over the northern part of Kakamega Forest as a National Reserve and the changes in management appear to have resulted in changes in logging numbers in the last 20 years. Illegal tree poaching was reduced at sites under KWS management probably due to tightened security, whereas FD sites still experience higher tree poaching rates today. Furthermore, FD sites show various other local threats such as e.g. charcoal burning and cattle grazing. Under FD management, sites with high protection priority such as Yala and Isecheno Nature Reserves (No. 14, 15, 19) still show lower overall threat levels as compared to sites with low protection priority. For example, Fashing et al.’s (2004) results of a long-term study of tree populations in Kakamega Forest indicate that their study plots in Isecheno remained relatively undisturbed over the last 20 years. A decrease of pioneer species density by 21% in these sites are taken as evidence that the [111]

1172 forest is maturing towards a climax forest and that at least the conservation measures applied to Isecheno appear to have succeeded Fashing et al. 2004). Nevertheless, prospects for other severly disturbed sites are assumed to be bad, as is the general prognosis for Kakamega Forest if protection efforts are not increased and illegal exploitation by local people remains high, particularly on its periphery (Cords and Tsingalia 1982; Kokwaro 1988; Tsingalia 1988; Fashing et al. 2004). How do the two conservation boards KWS and FD differ in their management aims and strategies? The overall aim of the KWS is ‘to conserve, protect and sustainably manage the wildlife resources’ and its areas are set aside for conservation and tourism only (Wass 1995). People are not allowed to collect any forest products and these policies are strictly enforced through regular patrols by up to five game rangers (E.W. Kiarie, personal communication). The overall aim of the FD is to ‘enhance conservation and protection of indigenous forest, to improve the production of timber and fuelwood and to establish a framework for the long-term development forestry’ (Wass 1995). Some sites are also set aside for conservation, however, some used to be plantations of exotic tree species or mixtures of indigenous species, while others experienced enrichment planting (A. Oman, personal communication). Logging, tree debarking and charcoal burning is prohibited, whereas fuelwood collection was licenced until recently (A. Oman, personal communication). It appears that the FD has been largely restricted in its capacity to implement conservation policies effectively due to the lack of adequate resources in contrast to the better funded KWS, leading to insufficient levels of staffing, patrols, weaponry etc. These differences in resources might have led to different disturbance levels as found in our survey. Besides overall funding and the number of staff, other potential factors associated with management regime and effectiveness might be e.g. accessibility to the forest or proximity of the forest to neighbouring settlements, population density, community relations and compensation programs to locals. In a recent assessment of the impact of anthropogenic threats on 93 protected areas of 22 tropical countries park effectiveness was shown to correlate most strongly with density of guards i.e. the more guards the higher effectiveness (Brunner et al. 2001). Furthermore, effectiveness correlated with the level of deterrence of illegal activities in the parks and with the degree of border demarcation and existence of direct compensation programs for local communities (Brunner et al. 2001). However, it did not correlate with enforcement capacity (i.e. a composite variable of training, equipment and salary), accessibility, budget, number of staff working on economic development or education, or the local involvement of communities in park management (Brunner et al. 2001). To obtain more information on the factors influencing management effectiveness in Kakamega Forest more studies are highly recommended following the RAPPAM guidelines.

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1173 Management recommendations for Kakamega Forest The high human impact on Kakamega Forest especially along the western and eastern edge of the main forest block indicates an imminent danger of further fragmentation. The main forest block might fall into two separate forest blocks, i.e. Kakamega National Reserve in the North and Isecheno Nature Reserve in the South. To prevent this from happening in the near future, we strongly recommend following the management plan of forest zoning as outlined by the Kenya Indigenous Forest Conservation Programme (KIFCON 1994; Wass 1995): establishing a protection zone to provide a core for biodiversity conservation extending from the North to South; setting up a rehabilitation zone with enrichment planting where degradation has reached high levels; and establishing a subsistence use zone flanking the protection zones where local people are allowed to extract forest products. This forest zoning aims both, to maintain as much indigenous forest cover as possible and to permit optimal use of forest resources on a sustainable basis (Wass 1995). We recommend placing the protection zone under strict KWS management as our survey indicates that areas of Kakamega Forest managed by the KWS appear to hold surprisingly low disturbance levels despite high land-use pressure. The degradation and logging levels in the suggested subsistence zones are already alarming, so that we suggest enrichment planting there. Finally, encouragement of on-farm-forestry projects might provide resources in the long-term and thus might relieve the subsistence use zone. This is supported by the fact that a tree nursery run by the local grassroot conservation organization KEEP (Kakamega Environmental Education Program) at Isecheno Forest Station has been successfully nursing seedlings of both, indigenous and exotic tree species, for sale to local farmers. Beyond conservation measures for the main forest block, high protection priority must also be given to the low-disturbance sites central Ikuywa (No. 17), Yala (No. 19) and the 400 ha fragment of Kisere (No. 2). Kisere Nature Reserve is of particurlar conservation significance because it has been relatively undisturbed in the past and still harbours species-rich forest communities that include the rare DeBrazza monkeys (Cercopithecus neglectus) (Muriuki and Tsingalia 1990; Chism and Cords 1997). Although managed by KWS, it appears to have experienced increasing disturbance levels in the last few years (N. Saijita and C. Analo, personal communication). This might be due to the lack of ranger outposts in Kisere (KWS headquarters is at Buyangu), and the fact that the number of rangers (10–20) might not be sufficient to cover both, Buyangu and Kisere. Therefore, an immediate increase of regular ranger patrols to control logging more effectively is highly recommended, as suggested by previous authors (Kokwaro 1988; Mutangah 1996; Chism and Cords 1997).

[113]

1174 Logging as indicator for quantitative threat assessment In our survey only logging appeared to be an effective indicator for human impact on the forest and might offer a valuable tool to conservation managers. First, the recording of the number of logged trees provides a quantitative, objective measure of the human impact on protected areas. Most other assessments of threat status and management effectiveness used qualitative rather than quantitative approaches (see e.g. Salafsky and Margoluis 1999; Brunner et al. 2001; Ervin 2003c). For example, following the RAPPAM methodology and using a questionnaire, the question arises whether the protected area managers themselves answering questions on their own management will supply objective answers. Consequently, our method collecting empirical data on the number of logged trees is more objective. Second, methods using logging as a disturbance indicator assess disturbance directly and not through biological indicators. Often, human impact is inferred from long-term studies on plant species composition or population structure as a biological indicator (e.g. Fashing et al. 2004). However, biological indicators can only assess the present situation resulting from past human impact. In contrast, quantifying disturbances directly can provide empirical data on the present human impact. Furthermore, logging as a disturbance indicator can enable us to differentiate between recent and past disturbance and might consequently help to evaluate past management policies. Third, despite its quantitative approach this method provides a simple, lowbudget method important especially for rapid and repeated assessment of disturbed forests. Repeated assessments are crucial especially in protected areas such as Kakamega Forest where heterogeneity in forest condition occurs over small spatial scales (Fashing et al. 2004). Consequently, surveys using logging as a disturbance indicator can provide the maximum amount of current up-todate and scientifically sound information for management planners in return for the effort and time involved. Finally, although the list of potential threats facing protected areas worldwide is long, logging appears to affect nearly 70% of more than 200 parks throughout the tropics (van Schaik et al. 1997) and emerges as one of the most hotly debated issues in tropical forest conservation (Rice et al. 1997; Bowles et al. 1998; Laurance 2001). Consequences of logging do not only include loss of habitat, but also changes in the microclimatic environment, erosion of soil and modification of fire regimes (Barlow et al. 2002; Cochrane and Laurance 2002) with the impact depending on the type of logging, i.e. whether commercial mechanized logging with heavy equipment or local exploitation of timber through e.g. pit-sawying and firewood collection. Furthermore, secondary effects of logging might be increased access to remote forested areas through the creation of roads and paths leading to further logging, forest colonization and hunting (Wilkie et al. 1992; Rice et al. 1997; Laurance 1998; Robinson et al. 1999). Consequently, logging appears to be a serious constant [114]

1175 threat to tropical forests worldwide making its validity as an useful indicator even more probable. Disturbance or impact assessments in combination with long-term studies on forest structure and composition after logging (e.g. Plumptre 1996; Chapman and Chapman 1997; Struhsaker 1997; Fashing et al. 2004) can provide important information on regeneration dynamics after human impact. Studies from Kakamega Forest indicate that regeneration from the severe human impact of the last century might be possible though not without rigorous conservation measures (Fashing et al. 2004, this study). Finally, repeated disturbance assessments are important to keep track of the human impact in protected areas and can provide feedback to management planners when evaluating past management decisions and setting up new conservation goals.

Acknowledgements The study was funded by the German Federal Ministry of Education and Research within the framework of BIOTA East Africa (01LC0025 / subprojects E03, E10 & E11). We thank the Kenyan Ministry for Education and Research for the permission to carry out research in Kakamega Forest, and the KWS and FD for granting us access to their reserves. We appreciate information on management by E.W. Kiarie (Senior Warden, Kakamega National Reserve) and A. Oman (Assistant District Forest Officer, Kakamega). We highly acknowledge field assistance by C. Analo and N. Saijita. G. Schaab kindly provided maps and data on forest patch sizes. We wish to thank the paperclub at Mainz, N. Mitchell, L. Todt, H.Todt, and two anonymous referees for comments on earlier drafts of the manuscript and K. Boehning-Gaese, H. Dalitz and M. Kraemer for overall support.

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Biodiversity and Conservation (2006) 15:1179–1191 DOI 10.1007/s10531-004-4693-x


Springer 2006

-1

Influence of forest types and effects of forestry activities on species richness and composition of Chrysomelidae in the central mountainous region of Japan MASASHI OHSAWA* and TAKUO NAGAIKE Yamanashi Forest Research Institute 2290-1 Saishoji, Masuho-cho, Minamikoma-gun, Yamanashi 400-0502, Japan; *Author for correspondence (e-mail: [email protected]; phone: +81-556-22-8001; fax: +81-556-22-8002) Received 4 May 2004; accepted in revised form 28 October 2004

Key words: Batophila acutangula, Biodiversity, Insect diversity, Larix kaempheri, Leaf beetles, Species composition, Species richness, Sphaeroderma tarsatum Abstract. Species richness and composition of the Chrysomelidae (Coleoptera) were studied in larch (Larix kaempheri [Lamb.] Carrie`re) plantations, secondary forests, and primary forests. In addition, the effects of forest management practices, such as thinning and long rotation, were examined in the larch plantation. The species richness of Chrysomelidae was higher in the larch plantation than in the secondary forest or in the primary forest. Among the larch plantations, the species richness in old-aged plantations was higher than that in middle-aged plantations. The composition of the beetle assemblages in the larch plantation differed from that in the secondary forest or in the primary forest. Exosoma akkoae (Chujo), Batophila acutangula Heikertinger, and Calomicrus nobyi Chujo were caught with a bias toward the larch plantation. Longitarsus succineus (Foudras) and Sphaeroderma tarsatum Baly were caught more in the secondary forest and the primary forest, respectively. More B. acutangula and S. tarsatum were caught in stands where their host plants occurred at higher rates. Species richness of understory plants was an important factor for chrysomlid species richness, and frequency of host occurrence affected the number of individuals of leaf beetles examined. It seems that forest types and forest management practices affect host plants as well as Chrysomelidae, and that these effects on the host plants also influence chrysomelid assemblages.

Introduction The original vegetation of forestal area in the central mountainous region in Japan is considered as mixed forest of broad-leaved trees and coniferous trees dominated by Quercus crispula Blume. Since the 1940s, however, primary forests have rapidly diminished as a result of forestry activities, and now the area is known for its larch plantations. To achieve ecologically sustainable forest management in this region, studies were started to elucidate the status of biodiversity in forests and effects of forest management practices in the area, i.e., a basic information necessary for ecologically susutainable management. The study area is largely occupied by Japanese larch (Larix kaempferi [Lamb.] Carrie`re) plantations and secondary broad-leaved forests, dominated by [119]

1180 Quercus crispula Blume, (41 and 33% of the total area, respectively). Larch plantations were established for timber production; thinning has been conducted twice within a 45-year period in this area, in order to enhance growth of dominant trees. Long rotations have been adopted for some larch plantations to obtain high quality wood. Secondary forests were formerly used to produce firewood, charcoal, etc. Now, however, they are mostly left unattended. Because larch plantations and secondary forests occupy large areas, their role in conserving biodiversity is important. Primary forests, though fragmented today, should also be considered important because of the potential presence of rare indigenous species inhabiting in them. Three forest types (larch plantation, secondary forest, and primary forest) and two management practices frequently used in larch plantations (thinning and long rotations) were chosen for this study. Leaf beetles (Chrysomelidae, Coleoptera) are small in size (less than 1.5 cm in general) and their antennas are usually less than half the length of their bodies. They distribute worldwide and about 500 species have so far been reported in Japan (Kimoto and Takizawa 1994). Though they are related with cerambycid beetles which are saproxylic in their larval stage, leaf beetles feed on leaves, stems or roots in both larval and adult stages and are regarded as phytophagous herbivores. The diversity of Cerambycidae, saproxylic beetles, was investigated in this area, and it was reported that higher species richness of the beetles was observed in secondary forests than in larch plantations or primary forests, and that thinning increased cerambycid diversity in larch plantations (Ohsawa 2004). This time, leaf beetles were chosen for the study of diversity to clarify the effects of different forest types and forestry activities on the phytophagous herbivores. There has been one report published on the subject of the diversity and conservation of Chrysomelidae (Greatorex-Davies and Sparks 1994). In this study, the diversity of leaf beetles and some other insects was investigated in the rides of woodlands, and it has been reported that both species richness and abundance of leaf beetles declined with increasing levels of shade, and that rides must be actively managed to keep light levels high if species richness and abundance are to be maintained. The purpose of this study was to compare the species richness and composition of Chrysomelidae, phytophagous herbivores, in larch plantations, secondary forests, and primary forests, and assess the effects of forest practices, such as thinning and long rotations, on the diversity of this family in order to obtain information for conservation of leaf beetles in forest area.

Methods Study site This study was conducted in forests at altitudes ranging from 1390–1770 m (mean annual precipitation: ca. 1120 mm; mean annual temperature: ca. 9.9 C) [120]

1181 in the central mountainous region of Japan (Figure 1 of Ohsawa 2004). Three forest types in this area, i.e., larch plantations, secondary broad-leaved forest (secondary forest), and primary or near-primary broad-leaved forest (primary forest), were selected for the investigation. A total of 46 stands were chosen: 24 stands of larch plantations, aged 21–79 years; 11 stands of secondary forest, dominated by Q. crispula, with other broad-leaved trees such as Ilex macropoda Miq., Fraxinus sieboldiana Blume var. serrata Nakai, Betula platyphylla Sukatchev var. japonica (Miq.) Hara, Acer spp ., and Prunus spp.; and 11 stands of primary forest dominated by Q. crispula, but mixed with conifers such as Abies homolepis Sieb. et Zucc. and Tsuga diversifolia (Maxim.) Masters, with a high proportion of conifers in two of the stands. Larch plantations consisted of three types: 13 stands of middle-aged (21–45 years old), six stands of recently thinned (middle-aged, 1.5 and 2.5 years after thinning), and five stands of old (58– 79 years old) plantations. Survey of leaf beetles A Malaise trap was set in each of the 46 stands to capture insects, and leaf beetles were separated from among those trapped. To minimize forest edge effects and micro-topographical differences within each stand, efforts were made to set each trap in a typical spot for the stand on a simple slope (or in a flat area if there was no slope) in the interior of the stand. Leaf beetles were captured in three 14-day periods: in middle to late June, in middle to late July, and in early to mid-August. Because of high elevation, June to August is an appropriate period for capturing many beetles including Chrysomelidae, according to the results of an investigation conducted on insects through spring to autumn in this area (Ohsawa unpublished data). Dry specimens were prepared for all species of leaf beetles trapped, and were kept in the Yamanashi Forest Research Institute. Environmental factors Environmental factors examined were altitude, gradient, larch plantation versus natural broad-leaved forest mostly dominated by Q. crispula, i.e., secondary forest and primary forest (larch plantation vs. natural broadleaved forest), openness of the canopy, the numbers of vascular plants (95 400 118 30 14.4 20/0.2 0.8 92 5 3 15 3.5 18 25

1

2

3

2

3

4

5

4

5

4

5

HAD

PR

RSS

USD

MDSD

Notes: SW = Sprouting wood; MDF = Mono-dominant forest; CDF = Co-dominant forest; HTS = Huge-tree structure; RBS = Relatively balance structure; MDS = Mono-dominant structure; No. = numbers; TD = Trigonobalanus doichangensis; Hst = Highest; Shst = Shortest; Avg. = Average; DP = dead plants; TP = top layer;

1 = Vaccinium bracteatum;

2 = Castanopsis echinocarpa;

3 = Castanopsis hytrix;

4 = Castanopsis calathiformis;

5 = Schima wallichii; HAD = heavily disturbed by human activities; PR = Population in recovery; RSS = relatively stable structure; USD = unstable structure in developing; MDSD = mono-dominant structure in developing. [247]

1308 these individuals were mostly replaced by other native plant species, alien plant invaders, such as Eupatorium adenophorum (Ageratina adenophora) and Eupatorium odoratum (Chromolaena odorata), and agricultural crops. Occasionally, some seedlings or young trees appeared around scattered individuals inside the evergreen broadleaf forests. However, other plants such as Castanopsis calathiformis, Castanopsis echinocarpa, Lithocarpus fenestratus, Schima wallichii and Anneslea fragrans had already dominated in the vegetation. The formation of Type IsI is due to heavy cutting and vegetation destruction. The isolated individuals are found in the most endangered habitat and their genetic diversity is easily reduced by further human activities, grazing animals, farming and further biotic invasion. (2) Type SW (Sprouting woods): Type SW is the result of fuel wood cutting by indigenous people. Investigations show that the indigenous ethnic groups of Dai, Wa and Laku are familiar with T. doichangensis and have realized that the tree can sprout easily after top-cutting and thinning and thus they have adopted the methods of ‘alternate cutting or thinning cutting’ for the primitive sustainable use of the tree as fuel wood. As a result of these practices, plants of T. doichangensis in these woods showed some unique characteristics in tree shape, tree height structure and associated floristic composition (Table 1). In this community the tallest T. doichangensis was about 13 m and the average height was around 5 m. Some 60% of T. doichangensis reached the reproductive phase and about 25.6% of the individuals were below 1 m in height. T. doichangensis was the dominant species in woods, and 50 species of accompanying higher plants were present. The most important trees were Vaccinum bracteatum, Castanopsis hystrix, Lithocarpus fenestratus, Craibiodendron stellatum, Anneslea fragrans, Ternstroemia gymnanthera and Schima wallichii. Vernonia parishii, Arthraxon lanceolatus, Carex baccans and Zingiber striolatum were the typical herbaceous plants. Among epiphytes, Phymatodes lucida, Vanda coerulea and Eria pannea were also commonly found on the trunk. As ontogenesis of T. doichangensis was prevented by cutting, most trees could not complete their natural growth and their reproductive capacity was relatively restrained. (3) Type MDF (Mono-dominant forest): Plants of T. doichangensis in type MDF are found as small mono-dominated patches scattered in the secondary evergreen broadleaf forest. The tallest plant of T. doichangensis was about 10 m and the average height was around 5–6 m. Approximately 70% of the trees in the plots were mature with a height of ‡4 m. Around 20% of the plants were 2–3 m in height, while seedlings and young trees represented only 6% of the total population. Accompanying higher plants were represented by some 30 species and most of the woody species were the same as in Type SW, but there were far fewer herbaceous plants and epiphytes. Osyris wightiana, Viburnum cylindricum, Broussonetia papyrifera and Phyllanthus emblica were present in the community. T. doichangensis in Type MDF showed vigorous growth and a strong regenerative ability. (4) Type CDF (Co-dominant forest): Plants of T. doichangensis in Type CDF often formed a mosaic of mono-dominant patches in the primitive evergreen [248]

1309 broadleaf forest. In this type of community, T. doichangensis grows naturally without destructive disturbance from human activities. Based on the tree height-grade Type CDF can be divided into 3 ranks. These are Big Tree Structure (BTS), Relatively balanced structure (RBS) and Mono-dominant structure of mature trees (MDS) (Table 1). In rank BTS over 50% of T. doichangensis were trees with a height of ‡20 m and approximately 90% of the plants were in the reproductive phase. Compared with the other 2 ranks BTS had a lower percentage of young trees and seedlings. In rank RBS only 6% of T. doichangensis were trees with a height of ‡20 m, while some 17% of the total were dead, and almost 60% of the plants were in the flowering and fruiting stage. Rank RBS had almost equal number of flowering and non-flowering individuals of T. doichangensis. Compared with the ranks of BTS and RBS, rank MDS had the highest number of flowering individuals and nearly 90% of them were in the reproductive phase. The percentages of trees over 20 m tall or less than 1 m in the MDS were the lowest, and around 15% of all trees with a height of 3–18 m were dead. Both ranks of RBS and MDS had more individuals per 100 m2, however, both of them also had a certain percentage of plants that had died naturally. It can be inferred that T. doichangensis in the codominant forest is dynamic, and both types of RBS and MDS would develop into BTS with some individuals dying gradually because of strong competition for resources. The interrelationship of MDS M RBS M MDS may be the main characteristic for T. doichangensis in the primitive evergreen broadleaf forest. About 25 species of accompanying higher plant were found in CDF. Of these, Castanopsis calathiformis, Lithocarpus echinotholus and Lithocarpus fenestratus, were the most common in the upper canopy and Castanopsis calathiformis was the most competitive species with T. doichangensis. Other woody plants, such as Olea rosea, Eriobotrya cavaleriei, Cinnamomum bejolghota, Phoebe macrophylla, Helicia nilagirica, Ternstroemia gymnanthera, Pyrenaria diospyricarpa, Pithecellobium clypearia, and Eurya groffii, were also commonly found.

Genetic diversity and population genetic structure One hundred and fifty seven bands from 100 to 2900 bp were generated by the 16 selected primers, with each primer producing 6–13 bands with an average of 9.81 bands. Eighty three of the total bands were polymorphic and accounted for 52.87% (Table 2). These findings show that genetic diversity at the species level was abundant. Table 2 also indicates that the percentages of polymorphic bands in both populations of Lancang and Chiang-Rrai were far lower than those in the 3 other populations of Cangyuan, Menglian and Ximeng. Therefore, the genetic variation within both populations of Lancang and Chiangrai was lower that that in others. Table 3 shows that the effective number of alleles (ne), Shannon’ s index of diversity (I) and Nei’ s gene diversity (h) were 1.2646, 0.2431 and 0.1595, [249]

1310 Table 2. The sequences of random oligonucleotide primers and the number of polymorphic bands. Primers

Sequences

Total bands

Polymorphic bands

OPC05 OPC14 OPC15 OPJ 09 OPM02 OPM06 OPM13 OPM15 OPM16 OPM20 OPN14 OPN20 OPS03 OPV06 OPV10 OPV15

TCGTCTGCCC TGCGTGCTTG GACGGATCAG TGAGCCTCAC ACAACGCCTC CTGGGCAACT GGTGGTCAAG GACCTACCAC GTAACCAGCC AGGTCTTGGG TCGTGCGGGT GGTGCTCCGT CAGAGGTCCC ACGCCCAGGT GGACCTGCTG CAGTGCCGGT

9 10 11 11 6 8 10 12 13 10 12 7 11 10 9 8

4 5 6 6 0 5 4 5 7 4 9 3 6 9 4 6

Table 3. The genetic diversity and genetic structure of T. doichangensis. Population

na

ne

H

I

P/%

Ht

Hs

Gst

Nm

LC CHR CY ML XM Mean

1.1019 1.1911 1.3185 1.2930 1.3312 1.5287

1.0538 1.0804 1.1675 1.1469 1.1696 1.2646

0.0311 0.0513 0.0985 0.0911 0.1024 0.1595

0.0472 0.0812 0.1502 0.1403 0.1568 0.2431

10.19 19.11 31.85 29.30 33.12 52.87

0.1600

0.0749

0.5320

0.4398

Notes: na, observed number of alleles; ne, effective number of alleles Kimura and Crow (1964); h, Nei’s (1973) gene diversity; I, Shannon’s Information index; P, the percentage of polymorphic loci; Ht, gene diversity of species; Hs, gene diversity within populations; Nm, gene flow; Gst, coefficient of gene differentiation.

respectively, and the genetic variation of T. doichangensis is rather low (the effective number of alleles64%). The data may suggest that there are some ‘canopy’ based associations within these ghyll woodlands. For example, Group 1 is shown to be 42% similar to the other ghyll woodlands surveyed yet, there is a moderately high level of canopy similarity within the group itself (56%) (see appendices). More specifically, two classes are identified and, of these, the two Brick Kiln ghyll woodland areas are identical in canopy structure. Furthermore, the analysis picks out two, somewhat individual, ghyll woodlands based upon canopy composition, Kiln Wood (Lower ghyll) (no. 11) and Sandyden Wood (no. 49). These woodlands are shown as only 38% similar to all other ghyll woodlands surveyed and have no comparative ghylls at the group or class level (Figure 3a).

The understorey The data shows that, generally, there is similarity in the composition of the understorey within the ghyll woodland systems (Figure 3b). Values of between 31 and 61% similarity were obtained when comparing the overall data set and the various sub-groupings provided through cluster analysis. The analysis at the group level showed a substantial increase in the similarity values with all groups, apart from group 1, greater than 60% similar. These findings may indicate some potential categories or communities. Analysis at the class level shows strong association within the ghyll woodland systems, with similarity values around 75–100%. The analysis shows that when the understorey vegetation is examined many of the ghyll sites display little difference (e.g. Marline Valley, Batemans and Northlands [266]

1327

Figure 3. Cluster analysis dendrogram of the ghyll woodland canopy (a), under-storey (b), and field (c) survey data. A complete table of percentage similarity values derived from cluster analysis is provided in the appendix.

[267]

1328 Wood). It is, however, interesting to note that the analysis shows that Marline valley does have some zonation within the ghyll – reflected in the fact that two surveys were conducted at the site. Marline valley (away from stream) and Marline Valley (near stream) are identical, as are Marline Valley (by watercourse) and Marline Valley (away from watercourse). When comparing these two groups the analysis only shows a similarity value of 47% between them (Figure 3b). The analysis isolates Waterfall Wood as relatively distinctive. When the GIS database and survey sheets are examined, this separation appears to be an artefact of the understorey composition. Waterfall wood is the only ghyll with the understorey solely dominated by Alnus species. Highams Ghyll and Sandyden Wood also have Alnus species present within the understorey; however, closer inspection shows that Highams also has Crataegus monogyna dominant and Ilex aquifolium occasional within the understorey, whilst Sandyden Ghyll has Sambucus nigra frequent within the understorey and Corylus avellana occasional.

The field layer The analysis of the field layer data using cluster analysis shows that some data sets appear very dissimilar with values ranging from 21 to 39% similarity (derived from 11 site surveys). In contrast, 48 of the remaining sites show high levels of similarity (Figure 3c). When considering the cluster analysis for field data, the dendrogram clearly shows that those sites to the right of the figure are on the whole largely dissimilar whilst those sites to the left of the figure reveal moderately good levels of similarity, >50% (Figure 3c). When grouped, over half of the sites show similarity levels of 62%. Furthermore, within group 1, for example, the associations show 13 sites with 80% similarity and a further 15 sites with 81% similarity (see appendices). Despite these high levels of field layer similarity within the majority of ghyll systems, there are additional ghyll systems which are shown to be relatively distinctive in character and field layer composition. Sandyden Wood and Waterfall Wood are shown to be 50% similar to each other in presence/ absence, but are only 39% similar to all other ghyll woodlands surveyed. Wicks Copse and Tilsmore Wood are also outliers with similarity values of 25 and 21% respectively (Figure 3c). Wren’s Warren is also distinct, separated from other ghylls by the presence of Vaccinium spp. within the field layer (see appendices).

Ghyll woodlands and soils Cadastral analysis via the GIS demonstrates that the ghyll woodlands occupy a range of soil types. At a general level, GIS analysis indicates that 85% of the [268]

1329 ghyll woodlands are associated, to some extent, with brown soils and particularly with argillic brown earths of the Curtisden association (Association 5.72i of Jarvis et al. 1984). This association is widespread throughout the HW, occurring on siltstones and sandstones. In this association, slope relief is typically strong with moderately to steeply sloping valleys [ghylls] separated by gently sloping interfluves. Soils of the Curtisden association are usually moderately deep on gentle or moderate slopes. Characteristically, the soils comprise slowly permeable compact subsoil, which is subject to seasonal water logging. Springs and flushes are often common on the sloping ground of permeable and impermeable strata (Jarvis et al. 1984). Ghyll woodlands are also commonly found on surface-water gley soils (Stagnogley Associations 7.11e, 7.11i and 7.12b of Jarvis et al. 1984), which are linked, again to varying degrees, with 55% of ghyll systems. The Wickhams 1 and 5 Associations are extensive on the Low Weald. The Wickham Associations have slowly permeable subsoils and are often waterlogged for prolonged periods in winter. Often heavily wooded, these soils are naturally acidic and can have good reserves of available water (Jarvis et al. 1984). Other associations are linked with the ghyll systems but their importance is low. Podzolic soils, in particular gley podzolic soils, are associated with 4% of the ghyll systems. Only 1% are associated with ground water gley soils.

Cluster analysis of geological and topographical data Cluster analysis was undertaken for the geological components of the surveys, including surrounding geology, 1st, 2nd, 3rd Geological Beds (in chronological sequence), height at top of ghyll, and height difference within the ghyll valley. The geological and topographical data shows substantial level of similarity within the ghyll woodland systems with 89% of the sites being >68% similar (Figure 4). All reside on the clays and sands of the Hastings Beds. Beyond this level of similarity there are some additional sub-groupings with particularly strong associations yielding similarity values >80% (Figure 4), which reflect the presence of ghylls on Ashdown sands, Tunbridge sands, Wadhurst clays and Fairlight clays. Figure 4a also shows that some sites appear relatively distinctive in comparison to the majority of ghylls surveyed. Site 41 (Guestling Wood) shows low similarity values of 28% to all other ghyll systems examined. Two of the Fairlight Glen surveys (Sites 46 and 27) show good similarity when compared to each other (87%), but are only 41% similar to all other systems. Equally, Courtlands Wood (Site 5) and Little Iwood (Site 10) are similar to one another (90%) but are only 54% similar to all other survey sites. Examination of the GIS database and survey sheets suggests that these differences are related to surrounding geology, strata and average levels of fall along the ghyll. Further cluster analysis was undertaken for the geological components [269]

1330

Figure 4. Cluster analysis dendrogram of the ghyll woodland geological (a) and geological and vegetation survey data combined (b).

and the vegetational data from the ghyll woodland surveys combined (Figure 4b). The dendrogram repeats patterns observed within the previous cluster analysis showing a strong association (>62%) between the majority of ghyll woodland sites surveyed (over 80% of sites). In addition, the dendrogram isolated the same sites as being distinctive including Fairlight Glen, Guestling Wood, Courtlands Wood, Little Iwood and Marline Valley (Figure 4b). This similarity of outcomes may be associated with the dominance of geological data within the analysis of both data matrices and the relatively weak [270]

1331 contribution of the vegetational components to the geology and vegetational matrix.

PCA of geological and vegetational data PCA analysis of the geological and vegetational survey data reinforces the conclusions drawn from the cluster analysis. Analysis shows high levels of association between the majority of ghyll systems based upon the variables (shown by the main grouping on the ordination, Figure 5). This suggests that the majority of ghyll systems have similar geological and vegetational characteristics and little or no separation is present along either axis. It is however, interesting to note that there are two ghylls separated from the main grouping along the first component showing 24% of the variation (eigenvalue = 2.419) (Figure 5). Both Fairlight Glen and Marline Valley (near watercourse) are separated along this axis and examination of the GIS database suggests that this relates to strong differences in their geological

Figure 5. PCA analysis ordination of the ghyll woodland geological and vegetational survey data. [271]

1332 beds, valley form and average degree of fall along the ghyll. Equally, a further three ghylls are separated from the main grouping along the second component showing 20% of the variation (eigenvalue=2.002). Guestling Wood, Courtlands Wood and Little Iwood are separated here and the survey data again points to geological conditions although some differences are evident within their National Vegetational Classifications (Rodwell 1998) (Figure 5).

Discussion Using a GIS-based spatial approach and multi-variate statistical techniques, this inductive study has provided an initial analysis of a sample of ghyll woodlands within the Weald of southeast England which suggests the significance of these important ecosystems within the broader landscape context. Biological Records Centre digital data sets identify 1130 ghyll woodlands in the High and Low Weald LCA. Spatial analysis suggests that, on an area basis, these ghylls comprise 23% of the woodland within East Sussex alone. This, however, is likely to be an over-estimate due to boundary issues, and the previous classification of substantial woodland areas as ghylls beyond the confines of the characteristic valley systems (Burnside et al. 2002). This latter point is of particular relevance to area calculations, as ghyll systems are normally regarded as restricted to small linear valley features. The analysis of the composite GIS survey database and field surveys using multi-variate techniques has shown that the vegetation within the ghyll woodlands is relatively similar in the canopy, understorey and field layers with similarity values of around 50–60%. The similarity reflects the common occurrence of NVC type W10 and W8 woodlands and a dominance of Quercus sp. and Fraxinus sp. respectively in the canopy. Equally, within the understorey and field layer the often widespread incidence of Ilex aquifolium and Corylus avellana, and in other cases of Rubus fruticosus and Pteridium aquilinum, provided good similarity levels. In some cases, however, the vegetation within particular ghylls does appear distinctive with percentage similarity values dropping to 20–30%. In relation to the canopy this reflected cases whereby the vegetation was solely dominated by Salix species. In relation to the understorey layer, the distinctive nature of some ghylls reflected the strong presence of Castanea sativa and the management practice of rotation coppicing. Analysis of the geological data also illustrates that the ghylls are undifferentiated at the general level. Cluster analysis identified that around 90% of sites were 70% similar for geological beds (e.g. Ashdown beds or Tunbridge Wells sands) and topographic characteristics (e.g. depth of ghyll and degree of fall). However, as shown by the vegetational analysis, some of the ghylls do remain relatively distinctive in topography (levels including 30–40% [272]

1333 similarity), which reflects the importance of landscape influence. The PCA shows, from a geological, geomorphological and ecological perspective that valley form, underlying geology and woodland type (sensu NVC) can be used to differentiate some ghyll woodlands (Figure 5). For example, Fairlight Glen and Marline valley are shown to be representative of steep-sided, confined valleys, on harder Wadhurst clays with a dominance of traditional Quercus robur – Pteridium aquilinum – Rubus fruticosus woodland (NVC – W10). Whilst Guestling wood, Little Iwood and Courtlands wood, are representative of more open valleys on unconsolidated and unlithified head-material. The latter ghylls exhibit a strong presence of Fraxinus excelsior – Acer campestre – Mercurialis perennis woodland (NVC – W8), vegetation more characteristic of base-rich soils (Rodwell 1998). In comparative terms, many of the ‘main groupings’ display less distinctive traits and exhibit the more general characteristics, which include Ashdown or Tunbridge geology, a moderate depth of ghyll (circa 20 m) and more than one woodland community along the entire valley profile. Comparison of the ghyll woodland data and nature conservation designation confirms that in many cases the ghyll systems have received little protection. It is apparent that a substantial number of the ghyll woodlands fall within the broad remit of landscape designations, such as AONB, but on a site-by-site basis only about 10% have benefited from a nationally recognised conservation designation. This may result from the small size and linear character of individual ghyll woodlands when placed in the context of the broader wooded landscape. Effectively, ghyll woodlands represent small pockets of exceptionally high diversity, but often occur in broader woodlands that do not warrant designation. The analysis presented here may well indicate an under-representation of these intrinsically small and fragmented sites within existing statutory protection (Kirby 2003). These linear and fragmented sites may also be susceptable to the negative aspects of edge effect and incursion by more robust and competitive species (Harrison and Bruna 1999). Alterations to the understorey and canopy layers as a result of species change could have severely detrimental effects to the structure of the woodland systems (Burke 1998), and may result in a reduction in biodiversity and the loss of more specialised species indicative of the ghyll woodland habitats. The study emphasises the importance of developing appropriate management plans for these sites, and the need to set appropriate nature conservation designation. As stated earlier, many of the ghyll woodlands are AW and have for the most part remained relatively undisturbed (Hodgetts 1997; Rose and Patmore 1997). This is an important consideration in relation to both biodiversity management and biological conservation. In many cases, whilst maintaining rich (and often locally rare) cryptogamic communities, ghyll valleys have no prescribed management plans and are under private ownership. Sustaining and promoting biodiversity at the [273]

1334 landscape scale requires the characterisation and maintenance of pockets of high biodiversity (Ernoult et al. 2003). In the case of some ghyll woodlands, this may only involve non-interventionist management but, nevertheless, designation must be secured. Some ghylls have been given regional status via SNCI designation, but this is a local designation and provides only limited protection.

Conclusion GIS database and multi-variate statistical approaches have been used to investigate ghyll woodland systems of the Sussex Weald. The ghylls have been shown to be a reasonably uniform vegetation type in terms of the canopy and their geological and soil characteristics. Yet, the variation in geology and climate, along with historical factors creates a system which is very species rich at the small scale (Waller and Marlow 1994; Rose and Patmore 1997; Sussex Biodiversity Partnership 2000). Analysis shows that the ghyll woodlands offer substantial opportunity for analysis of woodland characterisation and diversity. Some workers consider that bryophyte species occurrence and frequency may be the key to the systematic differentiation of ghyll woodland communities (Rose 1995; Rose and Patmore 1997), whilst others propose a more balanced approach looking at both ecological and landscape factors together (Burnside et al. 2002). However, this study shows that the geomorphology, understorey and field layer may act as an initial indicator of site conditions and character. The research has also demonstrated that ghylls have relatively weak levels of habitat protection in respect of their known conservation value for lower plants. Addressing this protection is of critical importance given the national, and potentially international, significance of the ghyll woodlands of the Weald. Further GIS investigations linking surveys of mosses and lichens with climatic and aspect data could provide a means to identify noteworthy ghyll woodlands for conservation targeting.

Acknowledgements Special thanks go to Neil Carrett for his assistance and input in the project, and Colin Reader (Habitat Management Services) and John Patmore (University of Brighton) for conducting the surveys. We would also like to thank David Saunders and Laetitia Tual (East Sussex County Council) for their support and provision of additional data for this project. GIS analysis was performed on ArcView 3.x software, Environmental Systems Research Institute and FragStats (ver 2), McGarigal and Marks (1992). [274]

1335 Statistical analysis performed using WinSTAT 3.1, Kalmia Co. Inc., 1995. Terrain data supplied by EDINA Edinburgh University, 2002; soil data supplied by SILSOE, Cranfield University, 2002; forestry and woodland data supplied by Forestry Commission, 2002; English Nature GUI, 2002, and Sussex Biological Records Centre, 2001.

Appendices Table A1. Percentage Similarity of cluster analysis for Canopy data.

[275]

1336 Table A2. Percentage Similarity of cluster analysis for Understory data.

[276]

1337 Table A3. Percentage similarity of cluster analysis for Field data.

References Bailey S.A., Haines-Young R.H. and Watkins C. 2002. Species presence in fragmented landscapes: modelling of species requirements at the national level. Biological Conservation 108: 307–316. Brandon P. 1977. The Sussex Landscape. Hodder and Stoughton, London. Burke D.M. 1998. Edge and fragment size effects on the vegetation of deciduous forests in Ontario, Canada. Natural Areas Journal 18: 45–53. Burnside N.G., Carrett N.J., Metcalfe D. and Waite S. 2002. GIS analysis of Ancient and Ghyll Woodlands within East Sussex. Biogeography & Ecology Research Group, University of Brighton, Brighton. Cleere H. and Crossley D. 1985. The Iron-industry of the Weald. Leicester University Press, Leicester. Countryside Commission. 1994. The High Weald. Countryside Commission, Northhampton. English Nature. 2002. Landscape Character Areas, Data prepared by English Nature GUI. URL http://www.english-nature.org.uk/. Ernoult A., Bureau F. and Poudevigne I. 2003. Patterns of organisation in changing landscapes: implications for the management of biodiversity. Landscape Ecology 18(3): 239–251. ESRI. 1998. ArcView 3.2, Software System. Environmental Systems Research Institute Inc. Everitt B.S., Landau S. and Leese M. 2001. Cluster Analysis, 4th ed. Arnold, London. [277]

1338 Forestry Commission. 2001. National Inventory of Woodland and Trees: England. Forestry Commission, Edinburgh. Fowler J., Cohen L. and Jarvis P. 1999. Practical Statistics for Field Biology. Wiley, Chichester, West Sussex. Gallois R.W. 1965. British Regional Geology, 4th ed. Department of Scientific and Industrial Research, London, UK. Gkaraveli A., Williams J.H. and Good J.E.G. 2001. Fragmented native woodlands in Snowdonia (UK): assessment and amelioration. Forestry 74(2): 89–103. Haines-Young R. and Chopping M. 1996. Quantifying landscape structure: a review of landscape indices and their application to forested landscapes. Progress in Physical Geography 20: 418–445. Harrison S. and Bruna E. 1999. Habitat fragmentation and large-scale conservation: what do we know for sure? Ecography 22: 225–232. Hodgetts N.G. 1997. A National and International Context for the Cryptograms in the Weald with Reference to Current and Future Conservation Initiatives for UK Cryptograms. In: Jackson A. and Flanagan M. (eds), Conservation of Cryptogams in the Weald. Proceedings of the Workshop held at Wakehurst Place 2nd May 1996. Royal Botanic Gardens, Kew pp.1–18. Jarvis M.G., Allen S.J., Fordham S., Hazelden J., Moffat A.J. and Sturdy R.G. 1984. Soils and their Use in South East England. Soil Survey, Harpenden. Kent M. and Coker P. 1992. Vegetation Description and Analysis a Practical Approach. John Wiley and Sons, Chichester. Kirby K.J. 2003. Woodland conservation in privately-owned cultural landscapes: the English experience. Environmental Science and Policy 6(3): 253–259. McGarigal, K. and Marks B.J. 1994. FRAGSTATS Spatial Pattern Analysis Program for Quantifying Landscape Structure, Version 2. Forest Science Department, Oregon State University, Corvallis. Peterken G.F. 1981. Wood anemone in central Lincolnshire: an ancient woodland indicator? Transactions Lincolnshire Natural Union 20: 78–82. Peterken G.F. 1993. Woodland Conservation and Management, 2nd ed. Chapman and Hall, London. Rackham O. 1980. Ancient Woodland. Arnold, London. Ratcliffe D.A. 1968. An ecological account of the Atlantic bryophytes in the British Isles. New Phytologist 67: 365–430. Reid C.M., Kirby K.J. and Cooke R. 1996. A Preliminary Assessment of Woodland Conservation in England by Natural Area. English Nature, Peterborough, UK. Rodwell J.S. 1998. British Plant Communities Volume 1: Woodlands and Scrub. Cambridge University Press, Cambridge. Rose F. 1995. The Habitats and Vegetation of Sussex. The Booth Museum of Natural History, Brighton Borough Council. Rose F. and Patmore J.M. 1997. Gill Woodlands in the Weald. English Nature, Peterborough. SSLRC. 2001. Sussex Soil Associations. Data prepared by National Soil Resources Institute (SSLRC), Digital Data Copyright (c) Cranfield University, 2001 (SSLRC Project Code: JP7017v/ 9). Sussex Biodiversity Partnership. 2000. Woodland Habitat Action Plan. Sussex Biodiversity Partnership, Sussex. Waller M.P. and Marlow A.D. 1994. Flandrian vegetational history of southeastern England – stratigraphy of the Brede Valley and pollen data from Brede Bridge. New Phytologist 126(2): 369–392. Waite S. 2000. Statistical Ecology: A Practical Guide. Prentice Hall, Harlow, UK. Wiens J.A. 1989. The Ecology of Bird Communities, Vol. 2. Cambridge University Press, New York. Woodland Trust. 2000. Woodland Biodiversity: Expanding Our Horizons. Woodland Trust, Grantham, Lincs. Woolridge S.W. and Goldring F. 1962. The Weald, 3rd ed. Collins, London. UK.

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Biodiversity and Conservation (2006) 15:1339–1351 DOI 10.1007/s10531-005-4875-1


Springer 2006

-1

Effects of fragmentation of evergreen broad-leaved forests on genetic diversity of Ardisia crenata var. bicolor (Myrsinaceae) AI-LIAN ZHAO1, XIAO-YONG CHEN1,2,*, XIN ZHANG1 and DONG ZHANG1 1

Department of Environmental Sciences, East China Normal University, Shanghai 200062, P. R. China; 2Shanghai Key Laboratory for Ecological Processes and Restoration in Urban Areas, Zhongshan R. (N.) 3663, Shanghai 200062, P. R. China; *Author for correspondence (e-mails: [email protected], [email protected]; phone: +86-21-62232697; fax: +86-21-62233669) Received 11 May 2004; accepted in revised form 20 March 2005

Key words: Ardisia crenata var. bicolor, Differentiation, Forest fragmentation, Genetic diversity, Population size, RAPD markers Abstract. Due to the long generation times and high densities, dominant tree species usually did not respond consistently with theoretical predictions to the recent fragmentation. Genetic structures of shrubs and herbs, especially those with low densities, may be more sensitive to forest fragmentation. We studied the genetic structure of a self-compatible subshrub, Ardisia crenata var. bicolor (Myrsinaceae) in a recently fragmented landscape. Ten RAPD primers used for analysis generated a total of 76 bands. We found that A. c. var. bicolor had relatively low species-level (P95 = 63.2%; H = 0.106; Shannon diversity index (SI) = 0.246) and within-population diversity (P95 = 5.3
46.1%; H = 0.026
0.175; SI = 0.032
0.253), and significant population differentiation (GST = 0.445). Significantly positive relationships were found between measures of diversity (P95, H and SI) and the log of estimated population size. No significant relationship was observed between Nei’s genetic distance and spatial distance of pairwise populations, indicating no isolationby-distance. Given most species of forests are shrubs and herbs with short generation times, our observation indicated that distinct genetic consequences of recent fragmentation may be expected for quite a number of plant species.

Introduction Due to increased urbanization, intensive agricultural practices and habitat destruction, many plant species occur in highly fragmented habitats (Van Rossum et al. 2004). Usually, consequences of habitat fragmentation consist of reduced population size and increased isolation (Saunders et al. 1991; Van Rossum et al. 2004), leading to genetic erosion and increased genetic differentiation among populations, through random drift, increased levels of inbreeding and reduced gene flow (Young et al. 1996; Chen 2000; Van Rossum et al. 2004). Ultimately these genetic processes may result in fitness declines and extinction (Keller and Waller 2002; Bacles et al. 2004). There have been increasing studies concerning genetic effects in plants of habitat fragmentation, and loss of genetic diversity and increased differen[279]

1340 tiation have been found in some systems (e.g., Raijmann et al. 1994; Hall et al. 1996; Morden and Loeffler 1999; Frankham et al. 2002). However, these responses to increased fragmentation are unlikely to be common, and other factors may influence the genetic consequences of fragmentation. First, most studies were conducted on long-lived species in a recently fragmented landscape and there were not sufficient time for bottleneck and inbreeding to take action (Young et al. 1993; Cardoso et al. 1998). Long-lasting, dormant seed banks also can buffer against genetic effects for decades or centuries (Morris et al. 2002). Second, many plant species studied were dominant species with high density. Thus, populations in fragmented habitats were large enough to maintain relatively high genetic diversity. Thirdly, some species are naturally rare species, and have evolved mechanisms to overcome the disadvantages of small population size. Thus, genetic consequences of recent fragmentation may not be detectable for a long time (England et al. 2002). Shrubs and herbs constitute the main part of species composition of forests. Therefore, genetic effects observed in dominant species of forests might not be general for most forest species. Shrubs and herbs – especially those with low densities – may be more genetically sensitive to forest fragmentation because of their much shorter life span. A shorter life span means they pass many generations even in recently fragmented habitats and, given their low densities, they therefore experience large declines in population size even if the fragmentation is not serious. However, much fewer studies have been conducted on herbs and shrubs than on tree species. For example, populations of herbaceous Swertia perennis in small, isolated habitats had reduced genetic variability and the highest within-population inbreeding coefficients (Lienert et al. 2002). In the herb, Scutellaria montana, populations that were less than 100 individuals tended to have lower proportions of polymorphic loci than that of populations more than 100 individuals (Cruzan 2001). Ardisia (Myrsinaceae) is a tropical and subtropical genus and includes about 200 species. Coral ardisia, A. crenata, native to Japan to north India, is an insect-pollinated and self-compatible evergreen subshrub (Cheon et al. 2000). In China, a variant, A. crenata var. bicolor, was identified according to the purple color of the lower side of its leaves, whereas some researchers thought it as a distinct species, i.e. A. bicolor. A. crenata var. bicolor is a small upright-growth shrub. Although outcrossing rate of A. c. var. bicolor was estimated to be about 1 based on allozyme using Ritland’s (1990) MLT program (Chen et al. 2001), bag-pollination treatments indicated that it is selfcompatible (unpublished data). This species can reproduce vegetatively via rhizome, but spreading to a short distance, usually less than 1 m (personal observations). In the present study, populations of A. c. var. bicolor in a fragmented landscape were selected to determine whether there is a relationship between population size and the level of variation and to evaluate the degree of [280]

1341 population subdivision and differentiation, using RAPD markers. Although RAPDs have some limitations – such as dominant allelic expression and occasionally low reproducibility – they have advantages in investigating genetic variation, such as random sampling in the whole genome, high levels of polymorphism, and fast and easy to perform, and have been widely used in estimating genetic variation of plant populations (Nybom and Bartish 2000; Nybom 2004).

Methods Population sampling The study sites were located in Tiantong Forest Park (TFP) and adjacent areas (Figure 1). TFP was distributed by evergreen broad-leaved forests (EBLFs) dominated by Fagaceae species, such as Castanopsis fargesii, Ca. carlesii, Ca. sclerophylla, Lithocarpus glaber, L. henryi, Cyclobalanopsis nubium, and species of Theaceae (Schima superba) and Lauraceae (Machilus thunbergii) (Song and Wang 1995). Around TFP, there were EBLFs fragments of previous continuous forests or recovered from abandoned or unmanaged plantations. These fragmented EBLFs were usually dominated by Cyclobalanopsis glauca, Cy. gilva, Ca. sclerophylla, L. glaber, Ca. carlesii, M. thunbergi. Surrounding these EBLFs, there were Cunninghamia lanceolata plantations, Phyllostachys pubescens forests, and shrubs dominated by Quercus fabra and bamboos. In TFP and adjacent areas, A. c. var. bicolor usually appears in forests of lower than 300 m above sea-level. Based on detailed surveys, 10 populations of A. c. var. bicolor were sampled (Figure 1). The estimated sizes of each population ranged from 5 to about 1000 individuals (Table 1). Leaves were collected randomly from individuals with a distance of at least 2 m between each other in medium and large populations, avoiding collecting the same clones. In small populations, as many as possible individuals were collected with a distance of at least 2 m between sampled individuals.

DNA extraction and PCR condition We isolated DNA with modified Doyle and Doyle’s (1987) procedure (Fan et al. 2004). A set of random 10-mer primers was purchased from Sagon Inc., Shanghai. After screening more than 100 arbitrary primers, 10 primers that consistently amplified clear banding patterns were chosen for further studies (Table 1). RAPD assays were performed using the conditions described by Fan et al. (2004). Samples were amplified at least two replicates and same pattern was obtained by the primers used in this study. Five ll amplification product was separated on 1.6% agarose gel in 0.5· TBE buffer and visualized by [281]

1342

Figure 1. Locations of sampling sites of Ardisia crenata var. bicolor in Tiantong Forest Park and adjacent areas.

[282]

1343 Table 1. RAPD primers used in the survey of Ardisia bicolor and number of scored bands. Primer

Sequence 5¢-3¢

Number of scored bands

Primer

Sequence 5¢-3¢

Number of scored bands

S59 S1200 S1221 S1238 S1341

CTGGGGACTT GTGAACGCTC CACACCGTGT GTTGCGCAGT GTCCACCTCT

8 9 3 11 4

S1361 S2068 S2084 S2100 S2160

TCGGATCCGT CATACGGGCT CCCAAGCGAA CAAAGGCGTG CACCGACATC

10 8 4 9 10

staining with ethidium bromide and photographed under UV light with BioRAD Gel Doc2000TM.

Data analysis Each PCR product was assumed to represent a single locus and was scored for presence and absence. The resulting data matrix was analyzed using Popgene 1.31 (Yeh et al. 1999). Gene diversities (H) at population and at the species level were calculated based on Lynch and Milligan’s (1994) Taylor expansion estimate using TFPGA (Tools For Population Genetic Analyses) v1.3 (Miller 1997). Nei’s unbiased genetic identity (I) and genetic distance (D) between populations were also analysed using Popgene 1.31. Because the data were larger than the up-limit of AMOVA, coefficient of gene differentiation (GST) was calculated to estimate population differentiation. Shannon diversity index P (Lewontin 1972), SI =
pi log2 pi, was calculated to provide a relative estimate of the degree of variation at population and species levels using Popgene 1.31 (Yeh et al. 1999). The proportion of diversity among populations was estimated as (SIsp
SIpop)/SIsp, whereas SIsp and SIpop were SI at species and population level, respectively. A Mantel type matrix randomization test (Mantel 1967) was performed to evaluate the relationship between the matrix of genetic distances and the matrix of geographic distances using TFPGA (Miller 1997). Relationships between measures of within-population genetic variation and population size were analyzed using Regression methods in Microsoft Excel program.

Results The RAPD profile The 10 primers used for analysis generated a total of 76 bands, among which polymorphic bands were 48 (or 63.2%) and 51 (or 67.1%) based on 95 and [283]

1344 Table 2. Patterns of genetic diversity for Ardisia bicolor populations. Population

Estimated population size

A B C D E F G H I J K L M N O P Mean

1000 1000 100 100 1000 500 5 200 5 100 50 10 100 200 300 30 294

Total

4700

Sample size

P95

P

H

SI

34 33 15 14 37 34 2 21 2 32 22 5 25 23 13 8 20

35.5% 32.9% 29.0% 30.3% 46.1% 32.9% 7.89% 30.3% 5.3% 22.4% 27.6% 15.8% 21.1% 34.2% 39.5% 19.7% 26.9%

40.8% 35.5% 30.3% 32.9% 47.4% 38.2% 7.9% 31.6% 5.3% 27.6% 32.9% 15.8% 23.7% 36.8% 40.8% 19.7% 29.2%

0.144 0.122 0.120 0.128 0.175 0.127 0.039 0.122 0.026 0.073 0.113 0.065 0.077 0.129 0.171 0.072 0.106

0.208 0.178 0.168 0.179 0.253 0.186 0.048 0.174 0.032 0.112 0.163 0.089 0.112 0.186 0.236 0.103 0.152

320

63.2%

67.1%

0.192

0.246

P95 and P are percentages of polymorphic bands based on 95 and 100% criteria, respectively; H denotes mean Nei’s gene diversity based on Nei’s (1972) unbiased estimates; SI, Shannon’s diversity index.

100% criteria, respectively (Table 2). The number of scored bands ranged from 3 for primer S1221 to 11 for primer S1238. 308 of the 320 individuals from the 16 populations were found to have a unique multilocus genotype, and six genotypes have two individuals. The individuals having the same multilocus genotypes belonged to same populations. No population-specific band was observed in the data set.

Genetic diversity Percent polymorphic RAPD loci varied from 5.3 (population I) to 46.1 % (E), based on 95% criterion, with a mean of 26.9% (Table 2). The Nei’s gene diversity ranged from 0.026 to 0.175 with a mean of 0.106 and the pooled species-level value was 0.192. The relative degree of diversity in each population as measured by Shannon’s index varied from 0.032 to 0.253 (Table 2). The mean Shannon diversity for all populations was 0.152 and the pooled species-level value was 0.246. Among the 16 populations, population E exhibited the highest level of genetic variability (P, H and SI) and population O was the next, whereas population I was the lowest (Table 2). Regression analysis indicated significantly positive relationships between measures of within-population genetic variation (P95, H and SI) and the log of population sizes (Figure 2). [284]

1345

Figure 2. Relationships between measures of within-population genetic variation and population size in Ardisia crenata var. bicolor. P95, H and SI were the percentage of polymorphic loci at 95% criterion, expected heterozygosity and Shannon diversity index, respectively.

Genetic differentiation The coefficient of genetic differentiation between populations (GST) was 0.445, indicating a high differentiation among populations. The Shannon’s index analysis partitioned 38.4% of the total variation among populations. Genetic distances (D) between populations varied from 0.018 to 0.149 (Table 3) with a mean of 0.055±0.023. The level of gene flow (Nm) was estimated to be 0.312. Mantel test indicated no significant relationship between genetic distance and spatial distance (r = 0.021, P = 0.422). [285]

1346

Table 3. Nei’s unbiased genetic identity (below diagonal) and genetic distance (above diagonal) between populations of Ardisia crenata var. bicolor.

[286]

Population

A

B

C

D

E

F

G

H

I

J

K

L

M

N

O

P

A B C D E F G H I J K L M N O P

– 0.9635 0.9646 0.9790 0.9569 0.9749 0.8965 0.9580 0.9458 0.9415 0.9661 0.9625 0.9652 0.9625 0.9435 0.9565

0.0372 – 0.9611 0.9627 0.9567 0.9530 0.9145 0.9705 0.9463 0.9477 0.9704 0.9522 0.9709 0.9756 0.9347 0.9412

0.0361 0.0397 – 0.9682 0.9507 0.9558 0.9085 0.9635 0.9532 0.9366 0.9590 0.9393 0.9547 0.9709 0.9309 0.9389

0.0212 0.0380 0.0324 – 0.9583 0.9636 0.9119 0.9613 0.9482 0.9428 0.9610 0.9614 0.9650 0.9675 0.9548 0.9484

0.0441 0.0442 0.0505 0.0426 – 0.9618 0.9144 0.9668 0.9317 0.9442 0.9540 0.9301 0.9494 0.9723 0.9717 0.9553

0.0254 0.0481 0.0452 0.0370 0.0389 – 0.9091 0.9711 0.9307 0.9467 0.9513 0.9395 0.9595 0.9555 0.9361 0.9433

0.1092 0.0893 0.0959 0.0922 0.0895 0.0953 – 0.9147 0.8909 0.9178 0.9145 0.8855 0.9206 0.9411 0.9303 0.8618

0.0429 0.0300 0.0372 0.0395 0.0338 0.0294 0.0892 – 0.9597 0.9460 0.9611 0.9346 0.9623 0.9667 0.9488 0.9665

0.0558 0.0552 0.0479 0.0532 0.0707 0.0718 0.1155 0.0411 – 0.9294 0.9446 0.9258 0.9454 0.9488 0.9274 0.9563

0.0603 0.0538 0.0655 0.0589 0.0574 0.0548 0.0858 0.0555 0.0732 – 0.9818 0.9610 0.9620 0.9609 0.9312 0.8991

0.0345 0.0300 0.0418 0.0398 0.0471 0.0499 0.0894 0.0397 0.0570 0.0184 – 0.9701 0.9714 0.9708 0.9409 0.9242

0.0383 0.0490 0.0626 0.0393 0.0725 0.0624 0.1216 0.0676 0.0771 0.0397 0.0304 – 0.9746 0.9410 0.9115 0.9018

0.0354 0.0296 0.0464 0.0356 0.0519 0.0414 0.0827 0.0385 0.0562 0.0387 0.0290 0.0257 – 0.9595 0.9273 0.9161

0.0382 0.0247 0.0296 0.0331 0.0281 0.0456 0.0608 0.0339 0.0526 0.0398 0.0296 0.0608 0.0413 – 0.9495 0.9451

0.0581 0.0676 0.0716 0.0462 0.0287 0.0660 0.0722 0.0526 0.0754 0.0713 0.0609 0.0926 0.0755 0.0518 – 0.9478

0.0445 0.0606 0.0631 0.0530 0.0457 0.0584 0.1487 0.0341 0.0447 0.1064 0.0789 0.1034 0.0876 0.0565 0.0536 –

1347 Discussion The present study reveals relative low genetic diversity in A. c. var. bicolor compared to other species based on RAPD markers. Percentage of polymorphic bands, Nei’s gene diversity and Shannon index of the pooled data were 67.1%, 0.192 and 0.246, respectively (Table 2). These values were even lower than many endangered species, Metasequoia glyptostroboides (P: 87.9%, H=0.318, SI = 0.476) (Li et al. 2005), Caesalpinia echinata (P = 95.7%) (Cardoso et al. 1998), Leucadendron elimense (P = 98.8%) (Tansley and Brown 2000), Boloria aquilonaris (H = 0.402) (Vandewoestijne and Baguette 2002), but higher than Haplostachys haplostachya (H = 0.166) (Morden and Loeffler 1999), Dryopteris cristata (P = 2.5%) (Landergott et al. 2001). Our results were not in accordance with the predictions based on the association of life history traits and genetic variation. According to the data of RAPDs, there were strong associations between genetic diversity and breeding system or successional status (Nybom and Bartish 2000; Nybom 2004). Outcrossing species had significantly high genetic diversity than selfers. Higher genetic diversity was found in late- than early - successional species. Species of ingested seed dispersal also possessed relatively high genetic diversity (Nybom 2004). Given such considerations, high genetic diversity was expected based on its high outcrossing rate (Chen et al. 2001), mid to late-successional status and bird dispersal manner. Relatively low genetic diversity in the studied A. c. var. bicolor populations might be explained by their geographical positions. The studied populations are located on the eastern margin of its distribution in mainland China (Figure 1). Due to effects of founder events, genetic drift and inbreeding, marginal populations usually possess relative low genetic variation, which had been confirmed in diverse species (Chen et al. 1997; Tyler 2002; Cassel and Tammaru 2003). Restricted geographical range in the present study might be another explanation of the low genetic diversity. Though 10 populations were sampled, their spatial distances were small. The largest distance of pairwise populations is 4.6 km. If populations were sampled in a large range, more genetic variation might be expected. Though some studies failed to observe the distinct genetic consequences of forest fragmentation on plant populations (Ellstrand and Elam 1993; Young et al. 1996), our results indicated that habitat fragmentation had played a vital role in genetic structure of A. c. var. bicolor populations. Fragmentation led to the loss of genetic diversity. In small populations, significantly lower diversity was observed than large and medium ones. Significant relationship was found between estimated population size and within-population genetic variation as measured by P, H and Shannon index. Decreased genetic diversity in small populations was due to various reasons. Firstly, the instantaneous effects of fragmentation (i.e., sampling effects) lead to stochastic loss of rare alleles because only a small portion of the original [287]

1348 gene pool remains after the decrease. Buchert et al. (1997) had compared the genetic diversity in pre-harvest and post-harvest gene pools of two virgin stands of eastern white pine (Pinus strobus). They found total and mean number of alleles was reduced by 25% after tree density reductions of 75%. About 40% of the low frequency alleles and 80% of the rare alleles were lost because of harvesting (Buchert et al. 1997). Secondly, inbreeding and genetic drift further decreased genetic variation in small populations (Young et al. 1996). In the present study, most small populations experienced bottleneck for more than 10 generations, given a generation of 3 years and deforestation of at least 50 years. It is enough for inbreeding and drift to virtually change the genetic composition of small populations of less than 50 individuals. Thirdly, founder effect might also contribute to low genetic diversity in some small populations (Frankham et al. 2002). Population G, for instance, located in dense high shrubs, had only two small individuals, indicating a recent founding event. High genetic differentiation was observed among populations of A. c. var. bicolor. GST indicated that about 44.5% of the genetic variation occurred among populations with short spatial distances. This value is higher than the RAPD-based estimates of other widespread, or animal-dispersal species (Nybom and Bartish 2000). High genetic differentiation among populations was also in accordance with theoretical prediction of fragmentation, indicating the effects of bottleneck and inbreeding. No significant relationship between genetic distance and spatial distance was found in the present study. This is usually interpreted that selection or drift plays a more significant role than gene flow. In this study, no distinct difference in habitats was found among populations, though the dominant species were different. At local scale, populations from different communities usually showed similar genetic composition in studied species, such as, Cyclobalanopsis glauca (Chen and Song 1998). Therefore, selection plays a minor role in the differentiation of A. c. var. bicolor populations, and drift led by fragmentation contributed to the high differentiation. Our findings in A. c. var. bicolor give a gloomy implication for forest species because most species of forests are shrubs and herbs and among them most are moderate- or low-density species. For example, there were about a dozen of species in tree layer of EBLFs; among them, usually less than 3 species dominated the community. However, the number of species in shrub and herb layers was about three to four folds of that in tree layer (Song and Wang 1995). Among them, most are moderate or low density, like A. c. var. bicolor, and are vulnerable to fragmentation. This situation is also common in tropical, temperate or boreal forests. Thus, although some studies showed no distinct effects on long-lived tree species which have survived hundreds of years of fragmentation, our study indicated that distinct genetic consequences of recent fragmentation may be expected for quite a number of plant species. More attention should be paid to these species and conservation efforts are needed. [288]

1349 Acknowledgements We thank Mr Ling-jian Li and Ms Xiao-xia Fan for the assistance in sample collection and preparation. We thank J. P. Sniadecki of Grand Valley State University for English improvement and helpful comments and reviewers for their critical comments and suggestions. This study was supported by Natural Science Foundation of China (39870128, 30170060), The State’s Tenth Fiveyear ‘‘211 Project’’ and Shanghai Priority Academic Discipline. References Bacles C.F.E., Lowe A.J. and Ennos R.A. 2004. Genetic effects of chronic habitat fragmentation on tree species: the case of Sorbus aucuparia in a deforested Scottish landscape. Molecular Ecology 13: 573–584. Buchert G.P., Rajora O.P., Hood J.V. and Dancik B.P. 1997. Effects of harvesting on genetic diversity in old-growth eastern white pine in Ontario, Canada. Conservation Biology 11: 747–758. Cardoso M.A., Provan J., Powell W., Ferreira P.C.G. and de Oliveira D.E. 1998. High genetic differentiation among remnant populations of the endangered Caesalpinia echinata Lam. (Leguminosae-Caesalpinioideae). Molecular Ecology 7: 601–608. Cassel A. and Tammaru T. 2003. Allozyme variability in central, peripheral and isolated populations of the scarce heath (Coenonympha hero: Lepidoptera, Nymphalidae); implications for conservation. Conservation Genetics 4: 83–93. Chen X.Y. 2000. Effects of habitat fragmentation on genetic structure of plant populations and implications for the biodiversity conservation. Acta Ecologica Sinica 20: 884–892. Chen X.Y., Li N. and Shen L. 2001. The mating system of Ardisia crenata var. bicolor (Myrsinaceae), a subtropical understory shrub, in Tiantong National Forest Park, Zhejiang Province. Acta Phytoecologica Sinica 25: 161–165. Chen X.Y. and Song Y.C. 1998. Microgeographic differentiation in a Cyclobalanopsis glauca poplation in western Huangshan, Anhui Province. Journal of Plant Resources Environment 7: 10–14. Chen X.Y., Wang X.H. and Song Y.C. 1997. Genetic diversity and differentiation of Cyclobalanopsis glauca populations in East China. Acta Botanica Sinica 39: 149–155. Cheon C.P., Chung M.Y. and Chung M.G. 2000. Allozyme and clonal diversity in Korean populations of Ardisia japonica and Ardisia crenata (Myrsinaceae). Israel Journal of Plant Science 48: 239–245. Cruzan M. 2001. Population size and fragmentation thresholds for the maintenance of genetic diversity in the herbaceous endemic Scutellaria montana (Lamiaceae). Evolution 55: 1569–1580. Doyle J.J. and Doyle J.L. 1987. A rapid DNA isolation procedure for small quantities of fresh leaf tissue. Phytochemical Bulletin 19: 11–15. Ellstrand N.C. and Elam D.R. 1993. Population genetic consequences of small population size: implications for plant conservation. Annual Review of Ecology and Systematics 24: 217–242. England P.R., Usher A.V., Whelan R.J. and Ayre D.J. 2002. Microsatellite diversity and genetic structure of fragmented populations of the rare, fire-dependent shrub Grevillea macleayana. Molecular Ecology 11: 967–977. Fan X.X., Shen L., Zhang X., Chen X.Y. and Fu C.X. 2004. Assessing genetic diversity of Ginkgo biloba L. (Ginkgoaceae) populations from China by RAPD markers. Biochemical Genetics 42: 269–278. Frankham R., Ballou J.D. and Briscoe D.A. 2002. Introduction to Conservation Genetics. Cambridge University Press, Cambridge.

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Biodiversity and Conservation (2006) 15:1353–1374 DOI 10.1007/s10531-005-5394-9


Springer 2006

-1

Diversity patterns in the flora of the Campo-Ma’an rain forest, Cameroon: do tree species tell it all? M.G.P. TCHOUTO1,*, W.F. DE BOER2, J.J.F.E. DE WILDE3 and L.J.G. VAN DER MAESEN3 1

Limbe Botanic Garden, BP 437 Limbe, Cameroon; 2Resource Ecology Group, Wageningen University, Bornsesteeg 69, 6708 PD Wageningen, The Netherlands; 3Biosystematics Group, Wageningen University, Generaal Foulkesweg 37, 6703 BL Wageningen, The Netherlands; *Author for correspondence (e-mail: [email protected]) Received 9 February 2004; accepted in revised form 31 March 2005

Key words: Biodiversity, Cameroon, Campo-Ma’an, Central Africa, Conservation, Endemic species, Forest refuge, Plant diversity, Tropical rain forest Abstract. This study describes diversity patterns in the flora of the Campo-Ma’an rain forest, in south Cameroon. In this area, the structure and composition of the forests change progressively from the coastal forest on sandy shorelines through the lowland evergreen forest rich in Caesalpinioideae with Calpocalyx heitzii and Sacoglottis gabonensis, to the submontane forest at higher elevations and the mixed evergreen and semi-deciduous forest in the drier Ma’an area. We tested whether there is a correlation between tree species diversity and diversity of other growth forms such as shrubs, herbs, and lianas in order to understand if, in the context of African tropical rain forest, tree species diversity mirrors the diversity of other life forms or strata. Are forests that are rich in tree species also rich in other life forms? To answer this question, we analysed the family and species level floristic richness and diversity of the various growth forms and forest strata within 145 plots recorded in 6 main vegetation types. A comparison of the diversity within forest layers and within growth forms was done using General Linear Models. The results showed that tree species accounted for 46% of the total number of vascular plant species with DBH ‡1 cm, shrubs/small trees 39%, climbers 14% and herbs less than 1%. Only 22% of the diversity of shrubs and lianas could be explained by the diversity of large and medium sized trees, and less than 1% of herb diversity was explained by tree diversity. The shrub layer was by far the most species rich, with both a higher number of species per plot, and a higher Shannon diversity index, than the tree and the herb layer. More than 82% of tree species, 90% of shrubs, 78% of lianas and 70% of herbaceous species were recorded in the shrub layer. Moreover, shrubs contributed for 38% of the 114 strict and narrow endemic plant species recorded in the area, herbs 29%, trees only 20% and climbers 11%. These results indicate that the diversity of trees might not always reflect the overall diversity of the forest in the Campo-Ma’an area, and therefore it may not be a good indicator for the diversity of shrubs and herbaceous species. Furthermore, this suggests that biodiversity surveys based solely on large and medium sized tree species (DBH ‡10 cm) are not an adequate method for the assessment of plant diversity because other growth form such as shrubs, climbers and herbs are under-represented. Therefore, inventory design based on small plots of 0.1 ha, in which all vascular plants with DBH ‡1 cm are recorded, is a more appropriate sampling method for biodiversity assessments than surveys based solely on large and medium sized tree species.

Introduction In a large, heterogeneous and structurally complex forest ecosystem such as the Campo-Ma’an tropical rain forest, selection of the most appropriate methods [293]

1354 for the assessment of plant biodiversity is a difficult matter. So far, many botanical biodiversity studies in tropical rain forest are often limited to tree species (mainly medium and large trees, or for some cases trees with DBH ‡10 cm) which are assumed to reflect the forest floristic composition and physical structure (Letouzey 1968; Reitsma 1988; Hart et al. 1989; Mosango 1990; Koubouana 1993; Wolter 1993; Lejoly 1995a, b; Newbery and Gartlan 1996; White 1996; Sonke´ 1998; Sonke´ and Lejoly 1998; van Valkenburg et al. 1998). Moreover, for most of these studies tree species accounted for more than 50% of the overall species composition. This traditional approach of forest inventory might not be sufficient for biodiversity assessment because other taxa belonging to other life forms such as shrubs, small trees, woody lianas, herbaceous climbers, herbs and epiphytic flora are not or under-represented. Furthermore, it has been shown in Central and West Africa that many plant species of high conservation value such as endemic and rare species are shrub and herbaceous species (Letouzey 1968, 1985; Robbrecht 1996; Sosef 1996; Achoundong 2000; Cable and Cheek 1998). However, during the last two decades shrubs, herbs and climbers are progressively being taking into consideration during biodiversity assessment, forest dynamic and ecological studies (Gentry and Dodson 1987; Poulsen and Balslev 1991; Valencia et al. 1994; Balslev et al. 1998; Condit et al. 2000). But, there is still a gap in knowledge regarding their contributions in the overall vascular plant species diversity in tropical rain forests. Some work has been done in this respect in Iquitos, Colombia and Guyana (Gentry 1988a, b; Duivenvoorden and Lips 1995; ter Steege 2000). This study is the first attempt to study the diversity patterns in the flora of a Central African tropical rain forest, and the contribution of the different plant layers to the total species diversity. We will analyse the diversity of the flora in the Campo-Ma’an rain forest, and test whether there is a correlation between tree species diversity and diversity of other growth forms such as shrubs, herbs and lianas. This will help us to understand if, in the context of African tropical rain forest, tree species diversity tells it all.

Methods Study area The study was conducted in the Campo-Ma’an rain forest in south Cameroon. The site covers about 7700 km2 and is located between latitudes 210¢– 252¢ N and longitudes 950¢–1054¢ E. The Campo-Ma’an area is a Technical Operational Unit (TOU) that comprises a National Park, five forest management units, two agro-industrial plantations, and a multi-uses zone. Following the FAO classification system, soils in the Campo-Ma’an area are generally classified as Ferrasols and Acrisols (Franqueville 1973; Muller 1979; van Gemerden and Hazeu 1999). They are strongly weathered, deep to very [294]

1355 deep and clayey in texture (except at the seashores and in river valleys where they are mainly sandy), acid and low in nutrients with pH (H2O) values generally around 4. The topography ranges from undulating to rolling in the lowland area, to steeply dissect in the more mountainous areas. In the Campo area, altitudes are mostly low, ranging from sea level to about 500 m. In the eastern part, which is quite mountainous, the altitude varies between 400 and 1100 m and the rolling and steep terrain brings about a more variable landscape. The area has a typical equatorial climate with two distinct dry seasons (November–March and July–mid-August) and two wet seasons (April–June and mid-August–October). The average annual rainfall generally decreases with an increasing distance from the coast, ranging from 2950 mm/year in Kribi and 2800 mm in Campo to 1670 mm in Nyabissan in the Ma’an area. The Ma’an region has significantly less rainfall than other areas. The average annual temperature is about 25 C and there is little variation between years. The hydrography of the area shows a dense pattern with many rivers, small river basins, fast-flowing creeks and rivers in rocky beds containing many rapids and small waterfalls. Generally, the area has a low population density of about 10 inhabitants per km2 and is sparsely populated (ca. 61,000 inhabitants) with most people living around Kribi, along the coast, and in agro-industrial and logging camps (ERE De´veloppement 2002; de Kam et al. 2002). Despite the low population density, there are few employment opportunities. The local people are very poor and so far rely solely on the forest resources to meet their basic needs. As a result, local pressure on the Campo-Ma’an rain forest is increasing and there are several activities that are carried out in the area with varying ecological impacts on the forest ecosystem. These activities include agriculture, logging, poaching and hunting.

Field sampling After a study of satellite images, topographic and vegetation maps, a reconnaissance trip was carried out in the study area to identify representative and homogeneous vegetation types to be sampled. Sampling sites were selected on the basis of physical and human factors such altitude, slope, rainfall, soils, the proximity to the sea, and the degree of forest use. Sampling was carried out in small plots of 0.1 ha (50 m · 20 m) at irregular intervals along a line transect from a random starting point, In total 145 plots covering 14.5 ha were established in undisturbed forests or matured secondary forests within 6 main vegetation types ranging from coastal forest, swamp, lowland evergreen forest, to submontane forest at higher elevations (800–1100 m above sea level). Twenty two (22) plots were established in coastal forest, 26 in the lowland forest rich in Caesalpinioideae, 39 in the lowland forest rich in Calpocalyx heitzii and Sacoglottis gabonensis, 39 in mixed evergreen and semi-deciduous forest, 14 in the submontane forest and 5 in swamps proportion to their area [295]

1356 coverage. Most of the plots were located in the National Park and the forest management units, which are less affected by human activities. In each 0.1 ha plot, all trees, shrubs, herbs and lianas with DBH ‡1 cm were measured, recorded and identified as far as possible. For unknown species, a voucher specimen was collected. Herbaceous species and seedlings of trees, shrubs and climbers were sampled in subplots of 5 m · 5 m each that were established in the 0.1 ha plots. These subplots were not used for the analyses, the output was only used to illustrate the contribution of the ground layer and herbaceous species when all vascular plant species are included in the floristic assessment of the forest.

Data analysis The analysis focused on family and species level floristic richness within the various life forms and forest strata recorded in the 145 plots. In this study tree layer comprised all vascular plant species with DBH ‡10 cm, shrub layer (1.5 cm £ DBH < 10 cm) and herbaceous layer (1 cm £ DBH < 1.5 cm). Diversity was measured by recording the number of species and their relative abundance in the different plots and vegetation types. This study focused on the a diversity (species richness), which is defined as the number of species within a chosen area, given equal weight to each species, and the b diversity, which is the difference in species diversity between areas or communities (Magurran 1988; Kent and Coker 1992; Bisby 1995). b diversity was quantified with the Shannon diversity index (H¢) using all individuals above 1 cm DBH and all species per plot. Phytosociological parameters (relative density and relative frequency) and Shannon diversity index were calculated following Whittaker (1975), Kent and Coker (1992) and Magurran (1988). The SPSS package version 10.0 for Windows was used for statistical analyses. The Spearman’s correlation test was used to correlate the species richness and diversity between the various growth forms and forest layers. We compared species diversity within forest layers and within growth forms using a General Linear Model (GLM) followed by a Tukey Multiple Comparison test (p4 with the most diverse, and species rich plots located in the submontane forests, forests rich in Caesalpinioideae, and forests rich in Calpocalyx heitzii and Sacoglottis gabonensis.

Floristic composition and diversity within forest strata The number of stems/ha and the number of vascular plant species per plot were generally higher in the shrub layer compared to the herbaceous layer and the tree layer. The number of stems/ha (Table 2) in the shrub layer varied from 3914 (mixed evergreen and semi-deciduous forest) to 4572 (coastal forest), in the herbaceous layer from 905 (swamps) to 1963 (submontane forest), and in the tree layer from 489 (coastal forest) to 785 stems/ha (submontane forest). The number of species in the shrub layer varied from 231 species (swamps) to 413 (mixed evergreen and semi-deciduous forest), in the herbaceous layer from 99 (swamps) to 229 (Calpocalyx heitzii and Sacoglottis gabonensis forest) and in the tree layer from 100 (swamps) to 183 species (submontane forest). In terms of Shannon diversity (H¢), the shrub layer was the most diverse followed by the tree and herbaceous layers (Table 2). The Shannon diversity varied in the shrub layer from 4.39 (swamps) to 5.13 (forest rich in Caesalpinioideae), in the tree layer from 3.82 (swamps) to 4.83 (forest rich in [297]

1358 Table 2. Summary of the number of species, number of families, number of stem/ha and Shannon diversity (H¢) recorded in the tree, shrub and herbaceous layers for each vegetation types for all vascular plants with DBH ‡ 1 cm. Floristic composition

Forest types Coastal forest

[298]

Tree layer: DBH‡10 cm No. of stems/ha 489 No. of species 147 No. of families 43 Shannon diversity index (H¢) 4.62 Shrub layer: 1.5 cm £ DBH