Importance of forest structure versus floristics to composition of avian assemblages in tropical deciduous forests of Central Highlands, India

Forest Ecology and Management 257 (2009) 2287–2295

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Importance of forest structure versus floristics to composition of avian assemblages in tropical deciduous forests of Central Highlands, India Rajah Jayapal a,*, Qamar Qureshi a, Ravi Chellam b a b

Wildlife Institute of India, Post Box 18, Dehradun 248001, India Wildlife Conservation Society India Programme, 1669, 31st Cross, 16th Main, Banashankari 2nd Stage, Bangalore 560070, India

A R T I C L E I N F O

A B S T R A C T

Article history: Received 3 November 2008 Received in revised form 4 March 2009 Accepted 5 March 2009

We investigated how much forest structure and floristics independently contributed to the composition of avian assemblages at multiple scales and for individual foraging guilds in tropical deciduous forests of Central Highlands, India. We derived dissimilarity matrices between all pairs of the 36 sampling sites with respect to forest structure, floristics, and bird species composition and ran Mantel’s randomization tests to detect significant associations among the matrices after partialling out the effect of geographic distance between sites. Bird species composition was found to be significantly related to forest structure across habitats, and floristics within the moist-deciduous forests. This finding is consistent with earlier observations that birds respond, in their species composition, to vegetation structure across habitats and to vegetation composition within a habitat. As predicted, the composition of insectivorous birds was influenced by forest structure, but the phytophagous guild did not show any relation to vegetation composition in contrast to patterns observed elsewhere. We explain this anomaly as a result of availability of a wide choice of food plants for phytophagous birds in central Indian tropical forests and weak species–environment relationships on account of their nomadism. Extraction of non-timber forest products remains a key economic activity in central India and our results imply that it can potentially influence the composition of forest bird communities through alteration of forest structure and floristics. ß 2009 Published by Elsevier B.V.

Keywords: Birds Tropical forest Forest structure Floristics Ecological scale Avian guilds Mantel’s test

1. Introduction The structure and composition of avian assemblages and how they are influenced by habitat features have been one of the most pervasive themes of investigation in community ecology (Block and Brennan, 1993). In particular, habitat selection in forest bird communities has evoked much attention from both theoretical and empirical perspectives (Cody, 1985). This interest is also, in part, due to the increasing recognition of impacts on forests, of human activities like extraction of timber and other products, livestock grazing, shifting cultivation, and infrastructure development (Canterbury et al., 2000). These activities often alter vegetation structure (‘physiognomy’) and forest composition (‘floristics’), the two key components of habitat selection in land birds in general. The question of how much vegetation composition and structure independently contribute to bird species composition was earlier addressed by Rotenberry (1985), who found that 55% variation in species composition of grassland birds was due to

* Corresponding author. Present address: Group for Nature Preservation and Education (GNAPE), No. 30, Gandhi Mandapam Road, Kotturpuram, Chennai 600085, India. Tel.: +91 44 42016406. E-mail address: [email protected] (R. Jayapal). 0378-1127/$ – see front matter ß 2009 Published by Elsevier B.V. doi:10.1016/j.foreco.2009.03.010

floristics and 35% could be explained by vegetation structure alone. In a majority of subsequent investigations on forest bird communities, vegetation composition emerged as the most significant factor (e.g., Lopez and Moro, 1997; Fleishman et al., 2003; Lee and Rotenberry, 2005). While some studies established the roles of both floristics and physiognomy as equally important in structuring avian assemblages (e.g., Arnold, 1988; Mac Nally, 1990; Bersier and Meyer, 1994), a few could not find any significant evidence for either of the components (e.g., Koen and Crowe, 1987). Such variations in avian responses have been attributed to several factors, among which the ecological scale of investigation (e.g., Wiens et al., 1987) and the food habits of birds (e.g., Cueto and de Casenave, 2000) have wide empirical support. Wiens and Rotenberry (1981) noted that vegetation structure was the key factor for bird community composition across habitats at coarse regional scale and floristics within homogeneous habitats at a more local scale. This finding was subsequently corroborated by several studies (e.g., Wiens et al., 1987; Bersier and Meyer, 1994) and Rotenberry (1985) found that these patterns remained true even within similar habitats across different spatial scales. The observation that vegetation structure outranks floristics in bird– habitat relationships at large scale, and vice versa is also in conformity with the hierarchical model of habitat selection in animal communities (Lee and Rotenberry, 2005).

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It has also been observed that avian foraging guilds, classified on the basis of food types, respond differently to changes in vegetation structure and floristics; for example, Cueto and de Casenave (2000) noted significant associations between forest structure and insectivore guild and between forest composition and frugivore–insectivore guild. This is probably in accordance with the ecological premise that abundance of primary consumers (like frugivores and granivores) is directly dependent on the distribution of food–plant species in the habitat (Rice et al., 1983). On the other hand, habitat selection in secondary consumers (like insectivores) is influenced by vegetation structure as insect diversity is known to increase with the structural complexity of habitats (Holmes et al., 1979). We investigated the relative roles of forest structure and floristics in determining species composition of breeding birds in tropical deciduous forests of central India. We first examined patterns of their contributions across habitats at the regional level, and then we tested the proposition that response of birds would change with spatial scale by examining within-habitat associations between birds and vegetation. We also explored if species composition of avian foraging guilds differed in response to variations in forest structure and composition. In the end, we discussed the conservation implications of these relationships in the light of recent evidences for the impacts of human activities on structural and compositional integrity of forested habitats. The relevance of our study is further underscored by the fact that the region is noted for its forest-based economy and extraction of non-timber forest products remains a mainstay of livelihood for local tribal communities (Kumar and Jain, 2002; Bhattacharya and Hayat, 2004). 2. Study area and methods 2.1. Study area The study was conducted in Central Highlands in the state of Madhya Pradesh in India between April and July during 2002– 2005. Rodgers and Panwar (1988), in their biogeographic classification of India, recognize Central Highlands as a distinct province within the Deccan Peninsula zone. These highlands comprise two parallel chains of hills, viz., the Satpura and the Vindhya Ranges, which run almost continuously from east to west and are separated by the River Narmada all along its course. The mean elevation of the Vindhyas in the north varies between 450 and 600 m, though a few points rise above 900 m. In contrast, the Satpuras in the south are characterized by several high peaks, the highest being the Dhupgarh (1348 m) near Pachmarhi. The Central Highlands extend over an area of about 200,000 km2 and are primarily covered with tropical dry- and moist-deciduous forests. While teak (Tectona grandis) dominates the forest floristics in the west and central parts of the region, an abundance of sal (Shorea robusta) marks the moist deciduous forests in the eastern ranges. We collected data on birds and vegetation from 36 sampling sites located in five eco-climatic subregions of the Central Highlands, viz., Seoni–Chhindwara Plateau, South Maikal Range, East Maikal Range, Betul Plateau, and Satpura Plateau. The average geographic distance (SD) between sites was 8.42  3.12 km within subregions and 240.56  98.53 km across subregions. The sampling sites were chosen using stratified random sampling in order that they represent a wide array of habitat types along the gradients of topography, floristics, canopy cover, vegetation structure, successional age, and protection status (Table 1). 2.2. Sampling of birds Composition of breeding birds of each site were sampled by ‘standardized area search method’ (adopted from Slater, 1994;

Dieni and Jones, 2002; Watson, 2004), in which a rectangular block of 850 m  60 m (ca. 5 ha in area) was laid and walked at a steady pace for 1 h along a transect that traversed lengthways through the centre of the block. Each block was walked for two to three consecutive mornings between 06:00 and 07:00 h until there were no significant additions to bird species inventory. Sampling was not carried out during days of inclement weather. We also took care that each transect block was placed well within a homogeneous patch of vegetation (typical of the site) to avoid any edge effects. All the land bird species seen and heard during sampling were recorded barring birds in overhead flight. Bird survey was designed and executed with two key assumptions: (i) birds were non-randomly distributed across habitats, and (ii) all the species that occurred in a given habitat/ block were detected. The choice of breeding land birds was particularly made in consideration of the first assumption, since breeding birds are known to show marked degree of habitat selection (Mills et al., 1991; Lopez and Moro, 1997). The second assumption was achieved through our choice of the sampling method. A notable merit of the area search method is that it allows the observer to wander from the transect to confirm the identity of doubtful species or unknown vocalizations, and observer can also use natural history knowledge to detect secretive and unobtrusive birds (Bibby et al., 2000). 2.3. Measurement of vegetation structure and composition Data on forest structure and composition were collected from standard vegetation plots. In each bird-sampling block, six 10 m  10 m square plots were placed using systematic random design with a minimum of 100 m interval between two successive plots. In total, 214 vegetation plots were laid (two sites had 5 plots each) in which eight structural variables, viz., tree abundance, tree species richness, tree girth at breast height (GBH), tree height, percent canopy cover, shrub abundance, number of standing dead trees (snags), and bamboo abundance were measured. We classified all woody plants with a height of >2 m as trees, and all bushy plants between 0.5 and 2 m height were considered as shrubs. Each tree was identified to the species level and assigned to one of the following height classes: 2–5 m, 5–10 m, 10–15 m, and >15 m; tree height diversity was, then, P derived by using Shannon’s index as: [Pi  ln(Pi)], where Pi is proportion of trees in the ith height class. Unidentified trees that comprised about 3% of the samples were allotted species codes on the basis of distinct morphological and anatomical features. Percent canopy cover was measured directly by means of a spherical densiometer as average of crown-cover readings taken from the centre of the plot in four directions. Data on structural variables were, then, pooled across the plots to compute mean values for each sampling site. 2.4. Data analysis We derived dissimilarity matrices between all pairs of 36 sites with respect to bird species composition (using Bray–Curtis distance), forest structure, and tree species composition (both using City Block measure). The three square matrices were then analysed for any significant associations using Mantel’s tests (McCune and Grace, 2002). The statistical significance of correlations was computed concurrently by performing Monte Carlo simulations with 10,000 randomized runs. Since spatial proximity is known to significantly contribute to the observed similarities in faunal and floral communities, we used partial Mantel tests to control for the effects of geographic distance between sites (after Legendre and Troussellier, 1988). The distances were calculated from GPS readings of location data collected at the centre of each

Table 1 List of sampling sites in Central Highlands, India along with their attributes. The vegetation measurements (Mean  SD) are averaged across vegetation plots of 100 m2 area each. Site codea

Tree species richness

Tree abundance

GBH (cm)

Canopy cover (%)

Tree height diversity

Shrub abundance

Snag abundance

Bamboo abundance

Protection statusb

Teak mixed plantation Dry-deciduous lowland forest Dry-deciduous hill forest Butea scrub jungle Dry-deciduous garari forest (Unprotected) Dry-deciduous teak forest Moist-deciduous bamboo forest Dry-deciduous garari forest (Protected) Non-teak mixed hill forest Open deciduous mixed forest Young mixed regeneration forest Moist-deciduous sal forest Dry-deciduous mixed forest Butea-Lagerstroemia scrub jungle Moist-deciduous sal + bamboo forest Bamboo-clad ravine jungle Open mixed bamboo forest Moist-deciduous sal forest (Protected) Sal + bamboo mixed forest Sal + Lantana open mixed forest Moist-deciduous sal forest (Unprotected) Bamboo-dominant mixed valley forest Open scrub jungle Mixed deciduous hill forest + Bamboo Teak-dominant deciduous hill forest Teak-dominant moist foothill forest Teak + bamboo plantation Open mixed bamboo hill forest Old coffee plantation Moist-deciduous mixed forest (non-teak) Dry-deciduous bamboo forest Teak-Lagerstroemia secondary forest Dry-deciduous mixed forest (non-bamboo) Moist-deciduous secondary forest Dry-deciduous hill forest Lantana scrub jungle

CHP 1 CHP 2 CHP 3 CHP 4 CHP 5 CHP 6 CHP 7 CHP 8 CHP 9 SMR 1 SMR 2 SMR 3 SMR 4 SMR 5 SMR 6 SMR 7 EMR 1 EMR 2 EMR 3 EMR 4 EMR 5 EMR 6 EMR 7 BTP 1 BTP 2 BTP 3 BTP 4 BTP 5 BTP 6 STP 1 STP 2 STP 3 STP 4 STP 5 STP 6 STP 7

5.8  3.3 7.2  2.0 6.2  1.5 1.2  0.5 5.2  1.5 3.5  1.4 4.3  1.2 3.0  1.8 7.3  2.1 5.8  0.8 10.3  3.4 2.0  0.9 9.0  1.3 0.9  0.7 3.7  1.4 4.4  1.8 3.7  1.4 1.7  0.8 4.0  1.6 1.8  0.8 1.8  0.8 5.3  1.2 3.2  1.0 4.5  3.0 2.8  0.8 2.2  1.0 3.0  1.7 3.8  1.0 6.2  1.7 5.3  1.8 6.0  4.7 2.7  1.4 5.2  1.7 4.3  0.8 4.3  2.0 5.7  1.6

11.0  2.1 12.3  2.9 14.3  2.7 3.2  2.2 25.0  3.4 14.8  1.9 12.0  2.8 15.5  4.2 13.3  2.7 15.7  4.0 29.5  4.8 10.2  3.2 21.5  5.6 0.9  0.7 8.7  1.6 13.0  3.3 7.3  1.6 5.8  1.8 9.7  3.1 4.5  1.6 5.7  1.4 10.8  3.3 5.3  2.4 7.5  3.5 5.8  1.2 9.0  4.3 9.5  2.3 10.2  2.3 9.5  2.7 8.3  3.6 20.8  11.3 11.5  3.4 12.8  5.0 10.0  3.7 9.0  4.2 12.5  2.4

38.8  10.8 47.4  7.7 47.0  12.3 53.5  67.6 29.6  4.8 40.1  7.3 55.6  11.6 44.1  5.8 41.0  7.1 40.3  13.7 21.9  1.4 68.7  9.2 34.7  8.2 44.6  41.7 76.6  13.4 70.4  20.7 86.6  24.7 99.1  9.0 56.9  8.2 92.1  11.1 83.5  6.9 83.1  25.1 62.5  10.5 71.1  38.5 66.7  10.9 60.9  11.1 62.0  35.1 59.3  14.3 61.4  12.5 86.9  25.9 33.1  7.2 42.8  5.3 49.8  11.7 58.9  15.7 42.4  7.6 25.5  4.2

77.74  10.03 90.29  6.30 90.38  5.81 16.07  29.51 86.39  12.14 85.66  5.82 94.45  5.15 89.04  3.43 85.01  7.31 87.35  13.17 72.57  15.99 90.47  7.13 78.25  17.84 11.31  16.70 96.45  1.72 90.64  9.18 82.36  12.85 94.93  3.68 83.23  12.77 79.63  15.41 86.52  8.86 91.77  1.84 18.13  22.48 84.18  10.35 82.67  13.30 80.76  12.81 92.68  7.72 87.30  8.84 97.75  1.67 87.09  12.86 86.18  15.57 75.69  16.61 84.49  11.35 88.34  6.63 76.99  10.56 35.82  15.25

0.66  0.14 1.01  0.19 0.98  0.17 0.13  0.28 0.78  0.11 0.92  0.18 0.80  0.40 0.42  0.21 0.89  0.11 0.85  0.23 0.36  0.07 0.89  0.18 0.82  0.17 0.0 1.09  0.25 0.95  0.23 0.98  0.15 0.74  0.17 0.83  0.23 0.88  0.17 0.91  0.20 0.94  0.15 0.26  0.30 0.46  0.26 0.81  0.18 0.69  0.21 0.91  0.18 0.87  0.19 0.84  0.20 1.04  0.12 0.52  0.13 0.80  0.42 1.06  0.21 0.83  0.25 1.02  0.20 0.44  0.28

3.2  2.9 11.7  9.1 3.5  1.5 5.0  2.0 1.0  1.6 10.7  7.5 9.3  10.6 0 9.5  4.3 13.3  12.5 12.0  4.5 0.5  0.6 5.0  4.1 12.9  7.4 21.7  13.1 8.6  9.0 1.2  1.2 0 4.2  3.3 17.0  7.4 14.2  6.1 8.2  5.6 5.2  5.8 16.5  7.2 7.7  5.2 14.5  8.9 6.7  4.1 7.7  5.7 13.3  4.2 6.8  3.7 5.5  3.6 4.2  2.5 29.2  20.7 11.2  6.6 5.0  3.1 33.0  4.9

0.2  0.5 0.2  0.4 0 0 0 1.7  1.9 0 1.5  1.9 1.3  1.5 0 0 0 1.2  1.2 0 0.2  0.4 0.2  0.5 0.2  0.4 0.3  0.5 0 0.3  0.5 0.2  0.4 0 0 0.3  0.5 0 0 1.2  1.0 0.2  0.4 0 0 1.5  1.4 4.2  3.5 2.7  2.0 0.5  0.8 1.0  0.9 1.0  0.9

0.2  0.5 0 1.2  2.4 0 0 0.2  0.4 5.7  1.4 0 0 0 0 0 1.3  1.4 0 2.0  1.1 8.0  3.0 2.7  1.5 0 4.0  3.1 0.2  0.4 0 4.7  2.7 0.8  1.2 1.5  2.0 0 0 1.7  1.2 3.3  1.6 0 1.3  1.8 6.8  4.8 0 0 0 0.3  0.8 0

RF RF-PA RF Nil RF PA PA PA PA RF RF RF RF Nil PA PA PA PA PA RF RF PA Nil RF RF RF RF RF Nil PA PA PA PA PA PA PA

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Vegetation type

a Site codes refer to different subregions in which the sampling sites are located and their abbreviations are as follows: CHP—Seoni–Chhindwara Plateau, SMR—South Maikal Range, EMR—East Maikal Range, BTP—Betul Plateau, and STP—Satpura Plateau. b Protection status: PA—Protected Area with maximum protection, RF—Reserve Forest with minimum protection, and Nil—Revenue land with no protection.

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sampling block. We fixed the significance level of a as P  0.05 in all the tests. The dissimilarity matrices were derived using SPSS Release 8.0.0, while the partial Mantel’s tests were performed with the software zt version 1.0 (Bonnet and Van de Peer, 2002). To investigate the within-habitat patterns of associations between bird species composition and vegetation attributes, the sampling sites were classified on the basis of forest structure and composition into subsets of homogeneous habitats. To avoid subjectivity and bias, we used hierarchical clustering technique using UPGMA linkage and city block distance in SPSS to identify and extract subsets of sites that were comparable structurally and floristically. Then, we again ran the partial Mantel tests with a select set of homogeneous sites to examine the relative response of bird species composition to floristics and vegetation structure within a given habitat, keeping geographical distance between sites as covariate. To ascertain if response of birds to habitat features was mediated by food type, breeding birds were categorized into two foraging guilds on the basis of predominance of animal or plant matter in their food, viz., insectivorous birds and phytophagous birds. The phytophagous guild comprised frugivores, nectarivores, and granivores (after Beskaravayny, 1996). To avoid ambiguity, raptors and birds with mixed food habits were removed from the analysis. Information on food habits of birds was largely drawn from Ali and Ripley (1983) and additionally from personal observations in the field. We computed dissimilarity matrices between all pairs of 36 sampling sites with respect to species composition of these two feeding guilds. These were, then, contrasted with matrices of floristics and vegetation structure using partial Mantel tests.

3. Results 3.1. Birds A total of 101 species of birds were recorded from 36 sampling sites, and this was about 53% of total land bird species that are known to breed in Central Indian Highlands (Ali and Ripley, 1983). The site occupancy patterns revealed that a majority of birds were marked by localized distribution (with 56 species found in less than 10 sites); in particular, species like Malabar pied hornbill (Anthracoceros coronatus), Streak-throated woodpecker (Picus xanthopygaeus), White-rumped needletail (Zoonavena sylvatica), Crested treeswift (Hemiprocne coronata), and Malabar whistling thrush (Myophonus horsfieldii) were encountered at just one site each. On the other hand, generalist birds like Jungle babbler (Turdoides striatus), Red-vented bulbul (Pycnonotus cafer), Blackrumped flameback (Dinopium benghalense), and Rufous treepie (Dendrocitta vagabunda) were found in more than 30 sites sampled. A complete list of birds recorded during sampling along with their site-occupancy is given in Appendix A.

Table 2 Associations among bird species composition, floristics, vegetation structure, and distance between sites, as shown by Mantel’s tests across habitats in Central Highlands, India (Matrix size: 36). Contrasted matrices

Covariate

Mantel’s r

Bird composition Floristics

Distance Vegetation structure

Distance

0.294 0.068

P <0.001 0.221

Bird composition

Floristics Vegetation structure

Distance Distance

0.096 0.438

0.123 <0.001

3.3. Bird composition, floristics and vegetation structure: across-habitat patterns Geographic distance between sites was found to have a weak, yet statistically significant influence over similarities in bird species composition. Partial Mantel tests, after controlling for this distance effect, showed that bird species composition had significant association with vegetation structure, but not with woody plant species composition across habitats at the regional level (Table 2). Intriguingly, floristics and vegetation structure remained uncorrelated. 3.4. Bird composition, floristics and vegetation structure: within-habitat patterns The hierarchical cluster analysis classified all the sampling sites into four distinct groups with respect to forest composition and structure (Fig. 1). These clusters were found to represent four habitats on a gradient of moisture and canopy openness, as follows: moist-deciduous forest (18 sites), dry-deciduous open forest (6 sites), dry-deciduous closed forest (8 sites), and open scrub jungle (4 sites). Among these four habitats, moist-deciduous forest was chosen to test for within-habitat patterns of associations among bird composition, floristics, and physiognomy. This habitat was selected as others were found to be less suitable on account of either sampling inadequacy or being equivocally demarcated; for example, the open scrub jungle was represented by a very small number of sites and there was a lack of clarity in

3.2. Vegetation In total, 59 species of woody plants were recorded from all the vegetation plots. In general, either teak or sal was the predominant species forming climax vegetation with varying proportions of tree species mainly Terminalia alata, Lagerstroemia parviflora, Anogeissus latifolia, Diospyros melanoxylon and bamboo (Dendrocalamus strictus) characterizing further sub-associations. In Seoni–Chhindwara Plateau, allelopathic Cleistanthus collinus often formed near-monospecific stands, especially in low-lying tracts. A summary account of all the woody plant species recorded in five subregions along with their proportional abundance is given in Appendix B.

Fig. 1. Dendrogram showing classification of sampling sites into four habitat types in Central Highlands, India. The legends are as follows: ‘+’ moist-deciduous forest, ‘o’ dry-deciduous closed forest, ‘x’ dry-deciduous open forest, and ‘=’ open scrub jungle. See Table 1 for description of the sites.

R. Jayapal et al. / Forest Ecology and Management 257 (2009) 2287–2295 Table 3 Within-habitat associations among bird species composition, floristics, vegetation structure, and distance between sites, as shown by Mantel’s tests between sites of moist-deciduous forest habitat in Central Highlands, India (Matrix size: 18). Contrasted matrices

Covariate

Mantel’s r

Bird composition Floristics

Distance Vegetation structure

Distance

0.487 0.052

<0.001 0.313

P

Bird composition

Floristics Vegetation structure

Distance Distance

0.202 0.135

0.042 0.089

Table 4 Associations among species composition of feeding guilds, floristics, and vegetation structure, as shown by partial Mantel’s tests across habitats in Central Highlands, India (Matrix size: 36). Contrasted matrices

Covariate

Mantel’s r

Insectivorous birds

Floristics Vegetation structure

Distance Distance

0.015 0.338

0.425 <0.001

P

Phytophagous birds

Floristics Vegetation structure

Distance Distance

0.082 0.145

0.207 0.071

branching of the dry-deciduous habitats into open and closed forests with longer internodes characterizing the former. The effect of geographic distance on similarities in avian assemblages was observed to be more pronounced when only sites of moist-deciduous forest were compared. Partial Mantel tests, after controlling for this distance effect, showed that bird species composition in these sites was significantly related to floristic composition (Table 3). This was in sharp contrast to the regional pattern where forest structure was observed to be the significant predictor of bird species composition. The independence of floristics and physiognomy, however, remained scale-invariant, as they were found to be unrelated in within-habitat analysis as well. 3.5. Guild composition, floristics and vegetation structure An analysis of food habits of birds yielded 50 species of insectivores and 17 species of phytophagous birds. The insectivorous guild included woodpeckers, cuckoos, swifts, shrikes, drongos, minivets, flycatchers, chats, robins, nuthatches, babblers, and prinias. The phytophagous guild comprised parakeets, barbets, hornbills, pigeons, doves, koel, sparrows, munias, sunbirds, and flowerpeckers (see Appendix A for species composition of the two guilds). Mantel’s tests, after distance-related covariances between sites were partialled out, showed that forest structure regulated the species composition of insectivorous guild to a significant extent, while floristics did not seem to have any influence. On the contrary, there was no evidence for the role of either vegetation structure or forest species composition on the composition of phytophagous guild (Table 4). 4. Discussion 4.1. Response of birds to floristics and physiognomy: role of ecological scale Species composition of breeding birds in tropical deciduous forests of central India was significantly correlated with vegetation structure across habitats. This is seemingly at variance with the findings of some previous studies (e.g., Lopez and Moro, 1997; Fleishman et al., 2003; Lee and Rotenberry, 2005) in which vegetation composition was identified as the key habitat feature in fashioning composition of avian assemblages. The disagreement is

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probably due to differences in the ecological scale of investigations, as evident from the regional scope of the present study, which included a wide selection of habitats in its sampling regime. For example, when the analysis was restricted to homogeneous sites representing moist-forest habitat, forest structure gave way to floristics as the significant correlate of bird species composition. This concurs with Wiens and Rotenberry (1981) who observed that physiognomy is crucial at large scale and floristics at local level in ecological distribution of birds. Though direct empirical support for across- and within-habitat patterns of associations between birds and vegetation are few and far between (e.g., Wiens et al., 1987; Bersier and Meyer, 1994), several studies, including some earlier ones, have found circumstantial evidences that corroborate these scale-dependent relationships (e.g., Robinson and Holmes, 1984; Mac Nally, 1990; Estades, 1997; Drapeau et al., 2000). To understand why vegetation structure should function as a habitat cue for forest birds at the landscape level and floristics at a more local scale (as evidences for the contrary seem to be nonexistent), it is useful to consider the following: first, it would be far easier for forest birds to associate search image of a suitable habitat with its structural features (e.g., Robinson and Holmes, 1984); vegetation composition would then complement the selection of optimal habitats from a suite of structurally similar forest types. Secondly, we might critically examine the rate at which both the features of forested habitats change in space with respect to species turnover in avifaunal assemblages along an environmental gradient (e.g., Mac Nally, 1990). In tropical deciduous forests of central India where there exist not more than two major forest associations (teak and sal), vegetation heterogeneity is mediated largely through structural diversity of forests rather than floristics. In other words, structural changes in forests tend to have overriding imminence much before any major floristic changes take effect in space. Therefore, it is not surprising that birds respond more to forest structure than composition in Central Indian Highlands as species diversity is known to vary as a function of environmental heterogeneity (e.g., Rahbek and Graves, 2001). It has also been shown in Neotropical deciduous forests that vegetation structure is influenced by precipitation while forest species diversity remains unaffected (Lerdau et al., 1991). This contradiction between floristics and physiognomy of tropical forests probably explain the hierarchical nature of their relationships with bird composition. The idea that forest birds select habitats first on the basis of vegetation structure and then on the basis of forest species composition also brings to the fore the importance of scale in ecological processes (Wiens et al., 1987; Hill and Hamer, 2004). In this respect, it mirrors the interaction of multi-scale factors in organization of bird communities (Hutto, 1985; Vander Haegen et al., 2000; Hagan and Meehan, 2001; MacFaden and Capen, 2002; Grand and Cushman, 2003). 4.2. Response of avian foraging guilds to floristics and physiognomy It is a well-established fact that vegetation structure and composition have varying effects on different foraging guilds of birds (Wiens, 1989). For example, structurally complex habitats, by virtue of their niche abundance, may accommodate a high insect diversity, as greater the number of available niches lesser the competition for space (Holmes et al., 1979; Gunnarsson, 1990; O’Connor, 1991). As a corollary, insectivorous birds could be expected to respond positively to structural complexity of habitats. Though it is also probably true that several insects are host-specific at least for part of their life-cycle (e.g., Hemipterans and Lepidopterans), the catholicity of bird–insect associations far outweigh insect–plant interactions (see Robinson and Holmes, 1984) and it is also possible for a single tree to harbour more than one species of herbivorous insects (Novotny et al., 2002; Strauss

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and Irwin, 2004; Lee and Rotenberry, 2005); so, it is less likely that insectivorous birds discriminate floristics more than structure. On the contrary, distribution of birds that show marked degree of phytophagy (feeding largely on plant produces like nectar, fruits, or seeds) is known to be governed by the distribution of food plants (Rice et al., 1983). These interactions between food habits and habitat selection in birds have been empirically supported by Cueto and de Casenave (2000), who observed that insectivorous birds recognized structural differences while the frugivore–insectivore guild responded to differences in plant species composition. But evidences from central Indian avifauna showed mixed patterns, conforming only in part to these generalities. For example, insectivores did respond significantly to the structural aspects of vegetation, as predicted; but phytophagous guild was influenced by neither forest structure nor forest composition. The apparent indifference of phytophagous birds to floristic composition is probably due again to the availability of a wide choice of food–plant species in tropical deciduous forests in central India obviating conditions for any narrow bird–plant associations to evolve. Further, birds dependent on plant resources often move over considerable distances in search of food, and therefore their relationships with habitat features in the immediate vicinity tend to be weaker and less predictable (Herrera, 1985). Alternatively, these relationships may become more explicit when floristics (a taxonomical attribute) is replaced with ‘functional composition’ of woody plant species yielding nectar, fruit, and seeds as food for birds (corresponding to functional diversity as defined by Martinez, 1996 and Marcot and Vander Heyden, 2001). 4.3. Implications for habitat selection in bird communities An interesting observation of the study is the apparent absence of correlation between floristics and physiognomy in central Indian forests; this is presumably due to the fact that the forest composition in central India is numerically dominated by either teak or sal making floristics statistically less varying than structure. There are several studies that acknowledge both vegetation composition and structure as equally important factors in habitat selection of bird communities (e.g., Arnold, 1988; Mac Nally, 1990; Poulsen, 2002). This is particularly expected in the absence of statistical independence of floristics and vegetation structure. Establishing this orthogonality is a prerequisite for assessing the relative contributions of both features to the variation in bird species composition. It can be achieved either by directly contrasting the two habitat matrices first for presence of any correlation (as done here) or by examining the influence of one habitat feature on bird species composition after controlling for any concomitant effects from the other feature (e.g., Fleishman et al., 2003; Lee and Rotenberry, 2005). Geographic distance between sampling sites is another potential confounding factor in quantifying the relative influences of floristics and physiognomy. It is widely recognized that spatial proximity often tends to overestimate the strength of species–environment relationships (Legendre and Troussellier, 1988; Borcard et al., 1992). Hence, a statistical technique like partialling out the covariates is strongly recommended to compute the true proportion of variation in bird species composition due solely to either floristics or physiognomy. In general, the degree to which physiognomy and floristics independently contribute to variations in avian assemblages is found to be almost always less than 50% (Rotenberry, 1985; Fleishman et al., 2003). In the present study, vegetation structure across habitats explained about 19% of bird species composition and floristics only about 4% within moist-forest habitat (though both the findings were statistically significant). This indicates that there may be other independent factors, apart from vegetation

structure and composition, which govern composition of bird communities. For example, Koen and Crowe (1987) found no evidence for either floristics or physiognomy and suggested historical and edaphic factors as possible mechanisms for organization of bird and invertebrate communities respectively. Though relative contributions of habitat features to bird species composition may appear small in degree in our study, their importance remains pivotal for birds on two accounts. First, habitat modifications (either in structure or in composition) still evoke distress response from local avifaunal populations (see Hill and Hamer, 2004 for a review). Secondly, the remaining unexplained part of bird species composition is likely to be a cumulative function of several small independent factors many of which are probably neither contemporary (e.g., historical events) nor amenable to precise quantification (e.g., competition). 4.4. Conclusions We conclude from these findings that both vegetation composition and structure are important, albeit at different spatial scales, in preserving the integrity of species composition of avian assemblages in Central Indian Highlands. Tropical forests have long been under severe pressure from mankind for a variety of forestry and land resources, and the stress factors often accrue large enough to break the limits of resilience of these fragile ecosystems (Folke et al., 2004). An increasing number of studies further demonstrate how human activities can irrevocably alter forest structure and composition (see Wright, 2005 for a review). Some of these disruptive agencies include extraction of timber (Johns, 1988; Sekercioglu, 2002) and non-timber forest products (Ticktin, 2004), forest fire (Bond and Keeley, 2005), livestock grazing (Gillespie et al., 2000), shifting cultivation (Raman et al., 1998), colonization of invasive plants (Fleishman et al., 2003) and infrastructural development (Geist and Lambin, 2002). In fact, assessing the impacts of changes in structure and composition of forests on faunal communities is central to evolving site-specific conservation action plans (Hill and Hamer, 2004). To develop solutions that seek to meet socio-economic needs from forestry sector at minimum ecological cost, we require reliable data on species–environment relationships at multiple scales. Incidentally, extraction of non-timber forest products (NTFPs) remains a key occupation of local tribal communities in central India; in particular, tendu leaves (Diospyros melanoxylon) for beedirolling, harra seeds (Terminalia chebula) used in dyeing and mahuwa flowers (Madhuca longifolia) for brewing and syrup manufacture are harvested in large quantities (Bhattacharya and Hayat, 2004). Overexploitation of these forest products leads to often irreversible changes in both tree species composition and vegetation structure of community and reserved forests. For example, we observed a large number of stunted trees of tendu in village forests as these trees were periodically pruned at the top to facilitate collection of the commercially valuable leaves. It was also noticed that local people frequently resorted to ground-fires to clear leaf-litter prior to the collection of fallen flower-buds of mahuwa, rendering the forest-floor nearly devoid of any shrub or grass cover. Yet, possible impacts of these unsustainable extraction practices on tropical forest biodiversity have been poorly documented in central India; more specifically, it is not known how canopy and understorey birds respond to these habitat modifications. While the findings of our study have given a theoretical underpinning to these issues with respect to habitat scale and ecological assembly of avifauna, we strongly recommend that future studies in the region investigate impacts of NTFP extraction on forest bird communities with direct empirical observations.

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Appendix A (Continued )

Acknowledgments We thank the Madhya Pradesh State Forest Department for providing necessary permission and logistic facilities to conduct the field work. Contributions of our field crew comprising D. Ramesh, Ravi Shankar, and Ishwar Singh are gratefully appreciated. We also thank the Director and the staff at the Wildlife Institute of India, Dehradun for their administrative support and Bruce Marcot, Jagdish Krishnaswamy, Pratap Singh, Dhananjai Mohan, Trevor Price, and two anonymous referees for their critical inputs to the manuscript at different stages.

Appendix A. List of bird species recorded from all the 36 sampling sites in Central Highlands, India along with the number of sites in which each species was found and feeding guilds (either insectivorous or phytophagous) to which they were assigned in the study Species

No. of sites, occupied

Feeding guild

Jungle babbler, Turdoides striatus Red-vented bulbul, Pycnonotus cafer Black-rumped flameback, Dinopium benghalense Rufous treepie, Dendrocitta vagabunda Plum-headed parakeet, Psittacula cyanocephala Oriental magpie robin, Copsychus saularis Common woodshrike, Tephrodornis pondicerianus Oriental white-eye, Zosterops palpebrosus Purple sunbird, Nectarinia asiatica Rose-ringed parakeet, Psittacula krameri Spotted dove, Streptopelia chinensis Common iora, Aegithina tiphia Common myna, Acridotheres tristis Jungle owlet, Glaucidium radiatum Chestnut-shouldered petronia, Petronia xanthocollis Indian pitta, Pitta brachyura Large cuckooshrike, Coracina macei Greater racket-tailed drongo, Dicrurus paradisaeus Common tailorbird, Orthotomus sutorius Tickell’s blue flycatcher, Cyornis tickelliae Common hawk cuckoo, Hierococcyx varius Grey-breasted prinia, Prinia hodgsonii Indian cuckoo, Cuculus micropterus Black-hooded oriole, Oriolus xanthornus White-throated kingfisher, Halcyon smyrnensis Brown-headed barbet, Megalaima zeylanica Great tit, Parus major Brahminy starling, Sturnus pagodarum Small minivet, Pericrocotus cinnamomeus Thick-billed flowerpecker, Dicaeum agile Eurasian golden oriole, Oriolus oriolus Indian roller, Coracias benghalensis White-bellied drongo, Dicrurus caerulescens Ashy drongo, Dicrurus leucophaeus Asian koel, Eudynamys scolopacea Coppersmith barbet, Megalaima haemacephala White-browed fantail, Rhipidura aureola Large-billed crow, Corvus macrorhynchos Indian peafowl, Pavo cristatus Greater coucal, Centropus sinensis Orange-headed thrush, Zoothera citrina

35 34 33 32 29 28 28 28 27 27 27 25 24 24 24 24 23 22 22 21 21 21 20 20 19 18 18 18 17 16 16 15 15 15 15 15 15 13 13 12 12

Insectivorous Others Insectivorous Others Phytophagous Insectivorous Insectivorous Others Phytophagous Phytophagous Phytophagous Insectivorous Others Others Phytophagous Insectivorous Others Insectivorous Others Insectivorous Insectivorous Insectivorous Insectivorous Others Insectivorous Phytophagous Insectivorous Others Insectivorous Phytophagous Others Insectivorous Insectivorous Insectivorous Phytophagous Phytophagous Insectivorous Others Others Others Others

Species

No. of sites, occupied

Feeding guild

Shikra, Accipiter badius Black drongo, Dicrurus macrocercus White-naped woodpecker, Chrysocolaptes festivus Brown-capped pygmy woodpecker, Dendrocopos nanus Drongo cuckoo, Surniculus lugubris Yellow-crowned woodpecker, Dendrocopos mahrattensis Red junglefowl, Gallus gallus Black-naped monarch, Hypothymis azurea Indian grey hornbill, Ocyceros birostris Alexandrine parakeet, Psittacula eupatria Grey-bellied cuckoo, Cacomantis passerinus Puff-throated babbler, Pellorneum ruficeps Indian scimitar babbler, Pomatorhinus horsfieldii Indian robin, Saxicoloides fulicata Asian paradise-flycatcher, Terpsiphone paradisi Grey junglefowl, Gallus sonneratii Yellow-footed green pigeon, Treron phoenicoptera Brown-cheeked fulvetta, Alcippe poioicephala Black-headed cuckooshrike, Coracina melanoptera Eurasian cuckoo, Cuculus canorus Tawny-bellied babbler, Dumetia hyperythra Red-whiskered bulbul, Pycnonotus jocosus Chestnut-tailed starling, Sturnus malabaricus White-eyed buzzard, Butastur teesa Golden-fronted leafbird, Chloropsis aurifrons Bar-winged flycatcher-shrike, Hemipus picatus Green bee-eater, Merops orientalis Black-lored tit, Parus xanthogenys White-throated fantail, Rhipidura albicollis Eurasian collared dove, Streptopelia decaocto Eurasian blackbird, Turdus merula House swift, Apus affinis Pale-billed flowerpecker, Dicaeum erythrorynchos Grey francolin, Francolinus pondicerianus Bay-backed shrike, Lanius vittatus Scarlet minivet, Pericrocotus flammeus Chestnut-bellied nuthatch, Sitta castanea Oriental turtle dove, Streptopelia orientalis Laughing dove, Streptopelia senegalensis Barred buttonquail, Turnix suscitator Spotted owlet, Athene brama White-rumped shama, Copsychus malabaricus Spangled drongo, Dicrurus hottentottus Red spurfowl, Galloperdix spadicea Long-tailed shrike, Lanius schach Velvet-fronted nuthatch, Sitta frontalis Yellow-legged buttonquail, Turnix tanki Rufous-tailed lark, Ammomanes phoenicurus Malabar pied hornbill, Anthracoceros coronatus Painted francolin, Francolinus pictus Crested treeswift, Hemiprocne coronata Indian bushlark, Mirafra erythroptera Malabar whistling thrush, Myophonus horsfieldii Jungle bush quail, Perdicula asiatica Oriental honey buzzard, Pernis ptilorhyncus Streak-throated woodpecker, Picus xanthopygaeus Rufous-fronted prinia, Prinia buchanani Crested serpent eagle, Spilornis cheela Common babbler, Turdoides caudatus White-rumped needletail, Zoonavena sylvatica

11 11 10

Others Insectivorous Insectivorous

9

Insectivorous

9 8

Insectivorous Insectivorous

8 8 8 8 7 7 7 7 7 6 6 5 5 5 5 5 5 4 4 4 4 4 4 4 4 3 3 3 3 3 3 3 3 3 2 2 2 2 2 2 2 1 1 1 1 1 1 1 1 1 1 1 1 1

Others Insectivorous Phytophagous Phytophagous Insectivorous Insectivorous Insectivorous Insectivorous Insectivorous Others Phytophagous Insectivorous Others Insectivorous Insectivorous Others Others Others Others Insectivorous Insectivorous Insectivorous Insectivorous Phytophagous Others Insectivorous Phytophagous Others Insectivorous Insectivorous Insectivorous Phytophagous Phytophagous Others Others Insectivorous Insectivorous Others Insectivorous Insectivorous Others Others Phytophagous Others Insectivorous Others Others Others Insectivorous Insectivorous Insectivorous Others Insectivorous Insectivorous

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Appendix B. List of woody plant species recorded from vegetation plots across all sampling sites in Central Highlands, India and their abundance proportions (%) in each of the subregions Woody plant species Acacia catechu Acacia leucophloea Aegle marmelos Albizzia lebbek Albizzia procera Anogeissus latifolia Bauhinia malabarica Bauhinia racemosa Bauhinia vahlii Bombax ceiba Boswellia serrata Bridelia squamosa Buchanania lanzan Butea monosperma Butea superba Careya arborea Carissa spinarum Casearia elliptica Cassia fistula Chloroxylon swietenia Cleistanthus collinus Dalbergia latifolia Dalbergia paniculata Dendrocalamus strictus Diospyros melanoxylon Emblica officinalis Ficus microcarpa Ficus racemosa Ficus religiosa Flacourtia indica Gardenia latifolia Grevillea robusta Grewia hirsuta Grewia tiliaefolia Kydia calycina Lagerstroemia parviflora Lannea coromandelica Madhuca indica Mangifera indica Miliusa velutina Millettia auriculata Mitragyna parvifolia Ougeinia ougeinensis Pterocarpus marsupium Schleichera trijuga Schrebera swietenioides Semecarpus anacardium Shorea robusta Soymida febrifuga Syzygium cumini Tectona grandis Terminalia alata Terminalia arjuna Terminalia belerica Terminalia chebula Ventilago maderaspatana Ziziphus mauritiana Ziziphus oenoplia Ziziphus xylopyra Unidentified species

Food value for birds

Fruit Nectar Nectar Nectar Nectar Seed Nectar, Seed Fruit Fruit Nectar Nectar Nectar Fruit Fruit

Seed Fruit Fruit Fruit Fruit Fruit Fruit Nectar Fruit Fruit Fruit Fruit Nectar Fruit

Seed

Fruit

Fruit Fruit Fruit

Seoni–Chhindwara Plateau

South Maikal Range

East Maikal Range

Betul Plateau

Satpura Plateau

2.5 0.1 0.1 0.0 0.0 1.5 0.0 3.2 0.0 0.0 1.1 0.7 0.7 2.8 0.1 0.0 0.0 0.0 0.7 1.1 25.9 0.1 0.4 6.0 6.7 2.8 0.0 0.0 0.1 0.0 0.1 0.0 0.0 2.2 0.1 11.0 1.3 1.0 0.0 2.8 0.0 0.1 0.3 0.0 0.1 0.0 0.8 0.0 0.1 0.0 15.5 2.0 0.1 0.0 0.0 0.4 0.0 0.1 1.1 3.6

0.0 0.0 0.0 0.3 0.0 14.6 0.3 0.2 0.0 0.0 1.4 0.3 4.5 0.5 0.0 0.3 0.2 1.2 1.4 0.3 0.0 1.7 0.3 10.3 7.0 1.4 0.2 0.0 0.0 0.0 0.0 0.0 0.0 0.2 0.2 5.7 1.5 2.6 0.0 0.5 0.0 0.0 0.9 1.0 0.0 0.2 0.2 13.7 0.0 1.4 4.5 15.2 0.0 0.0 0.0 0.0 1.2 0.0 1.4 3.4

0.0 0.0 0.0 0.3 0.0 4.4 0.0 0.0 0.3 0.0 0.3 0.3 5.4 0.7 0.0 0.0 0.0 1.0 0.7 0.0 0.0 0.0 0.0 25.1 4.4 1.0 0.0 0.0 0.0 0.7 0.3 0.0 0.0 0.0 0.7 1.0 0.3 1.0 0.0 0.0 0.0 0.0 0.0 0.3 0.3 0.0 0.7 44.1 0.0 1.0 0.0 1.4 0.0 0.0 0.0 0.0 0.0 0.3 0.3 3.4

0.0 0.0 0.0 2.3 0.0 1.3 0.0 1.3 0.6 0.6 0.0 0.0 0.3 0.0 0.0 0.3 0.0 1.9 1.0 0.0 0.0 0.0 0.0 12.6 0.0 0.6 0.0 1.3 0.0 0.0 0.0 1.0 0.3 0.0 1.0 1.6 0.0 0.0 1.0 0.6 0.3 0.0 9.1 0.0 0.3 0.0 0.0 0.0 0.0 4.9 38.8 1.6 0.0 0.3 0.3 0.0 0.3 0.0 1.0 13.3

2.5 0.0 5.7 0.0 0.4 0.8 0.0 2.2 0.0 0.2 0.0 0.6 0.6 0.8 1.0 1.0 0.0 0.0 1.0 5.3 0.0 0.0 1.2 10.0 9.6 2.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.4 0.0 10.0 0.2 1.8 0.0 1.6 0.6 0.2 1.2 0.0 0.0 0.0 0.0 0.0 0.0 3.1 22.7 7.3 0.0 0.6 0.0 0.2 0.0 0.0 2.4 3.1

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