Supplementary Material s40

Supplementary Material s40

<p>Supplementary material</p><p>Ecological traits affect the response of tropical forest bird species to land-use intensity</p><p>Newbold, T., Scharlemann, J.P.W., Butchart, S.H.M., Şekercioğlu, Ç.H., Alkemade, R., Booth, H. & Purves, D.W.</p><p>Appendix S1. Peer-reviewed publications from which data were collated for the meta- analysis of the response of tropical and sub-tropical bird species’ population densities to land- use intensity</p><p>1 Estrada, A., Coates-Estrada, R. & Meritt, D. A. 1997 Anthropogenic landscape changes and avian diversity at Los Tuxtlas, Mexico. Biodiversity and Conservation 6, 19-43. 2 Farwig, N., Sajita, N. & Böhning-Gaese, K. 2008 Conservation value of forest plantations for bird communities in western Kenya. Forest Ecology and Management 255, 3885-3892. 3 Harvey, C. A. & González Villalobos, J. A. 2007 Agroforestry systems conserve species-rich but modified assemblages of tropical birds and bats. Biodiversity and Conservation 16, 2257-2292. 4 Hutto, R. L. 1989 The effect of habitat alteration on migratory land birds in a West Mexican tropical deciduous forest: a conservation perspective. Conservation Biology 3, 138-148. 5 Johns, A. D. 1991 Responses of Amazonian rain forest birds to habitat modification. Journal of Tropical Ecology 7, 417-437. 6 Lambert, F. R. 1992 The consequences of logging for Bornean lowland forest birds. Philosophical Transactions of the Royal Society of London Series B, Biological Sciences 335, 443-457. 7 Lindenmayer, D. B., Cunningham, R. B., Donnelly, C. F., Nix, H. & Lindenmayer, B. D. 2002 Effects of forest fragmentation on bird assemblages in a novel landscape context. Ecological Monographs 72, 1-18. 8 Marsden, S. J. 1998 Changes in bird abundance following selective logging on Seram, Indonesia. Conservation Biology 12, 605-611. 9 Marsden, S. J., Whiffin, M. & Galetti, M. 2001 Bird diversity and abundance in forest fragments and Eucalyptus plantations around an Atlantic forest reserve, Brazil. Biodiversity and Conservation 10, 737-751. 10 Marsden, S. J., Symes, C. T. & Mack, A. L. 2006 The response of a New Guinean avifauna to conversion of forest to small-scale agriculture. Ibis 148, 629-640. 11 Mason, D. 1996 Responses of Venezuelan understory birds to selective logging, enrichment strips, and vine cutting. Biotropica 28, 296-309. 12 O’Dea, N. & Whittaker, R. J. 2007 How resilient are Andean montane forest bird communities to habitat degradation? Biodiversity and Conservation 16, 1131-1159. (doi:10.1007/s10531-006-9095-9) 13 Owiunji, I. & Plumptre, A. J. 1998 Bird communities in logged and unlogged compartments in Budongo Forest, Uganda. Forest Ecology and Management 108, 115- 126. 14 Parry, L., Barlow, J. & Peres, C. A. 2009 Hunting for sustainability in tropical secondary forests. Conservation Biology 23, 1270-1280. 15 Peh, K. S.-H., de Jong, J., Sodhi, N. S., Lim, S. L.-H. & Yap, C. A.-M. 2005 Lowland rainforest avifauna and human disturbance: persistence of primary forest birds in selectively logged forests and mixed-rural habitats of southern Peninsular Malaysia. Biological Conservation 123, 489-505. 16 Peh, K. S.-H., Sodhi, N. S., de Jong, J., Sekercioglu, C. H., Yap, C. A.-M. & Lim, S. L.-H. 2006 Conservation value of degraded habitats for forest birds in southern Peninsular Malaysia. Diversity and Distributions 12, 572-581. 17 Raman, T. R. S. 2006 Effects of habitat structure and adjacent habitats on birds in tropical rainforest fragments and shaded plantations in the Western Ghats, India. Biodiversity and Conservation 15, 1577-1607. 18 Renner, S. C., Waltert, M. & Mühlenberg, M. 2006 Comparison of bird communities in primary vs. young secondary tropical montane cloud forest in Guatemala. Biodiversity and Conservation 15, 1545-1575. 19 Sodhi, N. S., Koh, L. P., Prawiradilaga, D. M., Darjono, Tinulele, I., Putra, D. D. & Tan, T. H. T. 2005 Land use and conservation value for forest birds in Central Sulawesi (Indonesia). Biological Conservation 122, 547-558. 20 Soh, M. C. K., Sodhi, N. S. & Lim, S. L.-H. 2006 High sensitivity of montane bird communities to habitat disturbance in Peninsular Malaysia. Biological Conservation 129, 149-166. 21 Thiollay, J.-M. 1992 Influence of selective logging on bird species diversity in a Guianan rain forest. Conservation Biology 6, 77-63. 22 Thiollay, J.-M. 1997 Disturbance, selective logging and bird diversity: a Neotropical forest study. Biodiversity and Conservation 6, 1155-1173. 23 Waltert, M., Mardiastuti, A. & Mühlenberg, M. 2004 Effects of land use on bird species richness in Sulawesi, Indonesia. Conservation Biology 18, 1339-1346.</p><p>Table S1. Allocation of the habitat descriptions from the original publications to three classes of land-use intensity used in the models of bird species responses. . Habitat descriptions in publication Land-use intensity class used in model Continuous eucalypt forest Undisturbed Control forest Forest fragments Large natural gaps Montane forest Natural forest Near-primary forest Pine forest Primary closed forest Primary forest Primary montane forest Remnant eucalypt patches (Australia) Remnant eucalypt strips (Australia) Reserves Undisturbed forest Unlogged forest 10-20-yr secondary forest Light 10-yr-old secondary forest 15-year logged forest Fragmented secondary forest Logged Logged (1-2 years) Logged (1950) Logged (8-12 years) Logged forest Old gardens Old secondary forest Old-logged forest Recently-logged forest Secondary forest Short second growth Tall second growth Young secondary forest Agricultural land Intensive Agroforestry systems Allspice plantation Annual culture Banana agroforestry Banana plantation Cacao agroforestry Cacao plantation Cardomom plantation Citrus plantation Coffee plantation Continuous radiata pine plantation Corn plantation Cultivated Eucalyptus plantations (Brazil) Exotic monocultures Forestry Indigenous monocultures Jalapeno Mixed indigenous forest plantations Mixed rural habitat New gardens Oil-palm plantation Open habitat Pasture Plantain monoculture Rubber plantation Tea plantation</p><p>Appendix S2. Methods and results for the test of phylogenetic signal in model residuals.</p><p>To test for a phylogenetic signal in the response of tropical bird species to land-use intensity, we computed Pagel’s lambda statistic for the residuals of the best model, i.e. the model with the lowest AIC value. All methods were carried out using the R packages ‘geiger’ and ‘ape’ [1,2]. As a species-level phylogeny does not currently exist for birds, we used a family-level phylogeny [3] instead, supplemented with an estimate of the phylogenetic relationships of genera and species based on their taxonomic divisions. However, because this phylogeny is over 20 years old, for comparison we repeated the analyses using the most recent BirdLife International taxonomic checklist [4], estimating the phylogeny based only on taxonomic divisions. Branch lengths, including those in the family-level phylogeny, were calculated with the ‘compute.brlen’ function in the R package ‘ape’ [2] using the method proposed by Grafen [5]. Residuals were computed from the best model for each of the five types of observed data, i.e. occurrence in undisturbed, lightly used and intensively used habitat, and abundance in lightly- and intensively-used habitat (see the main text of the paper for details of these data types). For each of these sets of residuals, estimates of Pagel’s lambda statistic were made for the real phylogenetic tree, and for comparison with a collapsed tree where all species were assumed to be equally related, using the ‘fitContinuous’ function of the ‘geiger’ package [1]. To test for a significant phylogenetic signal in each of the five sets of residuals, we took the difference in the log likelihoods of the models with the full tree and the collapsed tree, multiplied by two, and calculated the P-value under a chi-square distribution. The phylogenetic signal was small and non-significant for the residuals of abundance in lightly- and intensively-used habitat (λ = 0.03 and 1.3 × 10-7; P > 0.05) and for occurrence in undisturbed habitat (λ = 1.0 × 10-7; P > 0.05), and small but significant for the residuals of probability of presence in lightly- and intensively-used habitat (λ = 0.08 and 0.09; P < 0.05). Using the BirdLife International taxonomic checklist instead of the family-level phylogeny, the results were very similar. The phylogenetic signal was non-significant for the residuals of abundance in both habitats and for occurrence in undisturbed and lightly used habitat (λ < 0.035, P > 0.05), but was significant for probability of occurrence in intensively used habitat (λ = 0.077, P = 0.0014). Because the effect of traits was strong and consistent for both probabilities of occurrence and abundances, we conclude that the main result of our study was not affected by phylogenetic non-independence.</p><p>Appendix S4. Methods and results of models fitting study as a factor, in addition to land-use change and functional traits (body mass, generation length, range size, migratory status, habitat affinity, diet and trophic level) of the species.</p><p>Fitting study as a factor added a large number of additional free parameters to the models. The large number of parameters in these models (182 in the model with all traits) was rather more than could be justified given the relatively small abundance dataset (4685 records), and led to very slow convergence of the Markov Chain Monte Carlo sampler. Therefore, we fitted only seven models with study as a factor: the model with no traits, models with each of the traits that had a strong effect in the main set of models, fitted individually, and the model with the lowest AIC from the main set of models. All other methods were the same as for the main models, as described in the main manuscript. As with the main set of models, models fitting body mass, generation length, diet, migratory status and forest habitat affinity all better explained observed responses to land-use intensity than models that ignored the effects of these traits (table S2). Parameter estimates for probabilities of presence were somewhat different in these models, which is not surprising because fitting study as a factor affects the calculation of probabilities of presence, although it is worth noting that the magnitude of the effect of land use was reduced compared to the main set of models (figure S1). However, the most important result of these supplementary models was that the effect of traits on observed responses was the same as for the models that did not fit study as a factor (figure S1). Table S2. AIC values of the models fitting probabilities of presence and ratios of abundance of 1317 tropical and sub-tropical bird species in relation to land-use intensity and functional traits of the species, with study as an additional factor. model AIC (with study effect) No traits 6314 MASS 6218 GL 6254 DIET 6250 MIGR 6145 FORSPEC 6190 GL + MIGR + DIET + FORSPEC 5845 (Traits included in these models were: GL – generation length; MIGR – migratory status; DIET – dietary guild; FORSPEC – whether the species was a forest specialist; MASS – body mass) Figure S1. For 1317 tropical and sub-tropical bird species, modelled estimates of probabilities of presence in each of three land-use intensities (a, c, e, g, i) and, given presence, ratios of abundance in light relative to undisturbed, and in intensive relative to undisturbed land use (b, d, f, h, j). Probabilities of presence and ratios of abundance were modelled as functions of species’ traits. The study that the data were drawn from was fitted as a factor in these models. Black and red crosses on graphs for categorical traits, and transparent lines on graphs for continuous traits, show median parameter estimates from the main set of models. a) b) Habitat generalists Forest specialists 1.6 0.9 1.2 R P</p><p>0.7 A P 0.8 0.5 0.3 0.4 Undisturbed Light Intensive Light Intensive c) d) Non-migratory Migratory o 1.6 i t a e r c 0.9</p><p> n</p><p> e 1.2 e c s n e 0.7 a r d p</p><p>0.8 . 0.5 n b u o b r A</p><p>P 0.3 0.4 Undisturbed Light Intensive Light Intensive e) f) Fruit Nectar Plants (other) Invertebrates Vertebrates Varied</p><p> o 1.6 i e</p><p>0.9 t c a n r e</p><p> s e 1.2 e</p><p>0.7 c r n p</p><p> a . d b</p><p> n 0.8 o 0.5 u r b P 0.3 A 0.4 Undisturbed Light Intensive Light Intensive Land-use intensity Land-use intensity g) h) Primary Light Intensive 1.6 o i t a e 0.9 r c</p><p> n</p><p> e 1.2 e c s n e 0.7 r a p d</p><p>. n 0.8 b u o</p><p>0.5 b r A P 0.3 0.4 0 5 10 15 20 25 0 5 10 15 20 25 Generation length (years) Generation length (years) i) j) Primary Light Intensive 1.6 o i t e 0.9 a c r</p><p> n</p><p> e 1.2 e c s e 0.7 n r a p d</p><p>. n</p><p> b 0.8 u</p><p> o 0.5 b r A P 0.3 0.4 0 2000 4000 6000 0 2000 4000 6000 Body mass (g) Body mass (g) Appendix S5. Results of models where data from the study in sub-tropical forests in Australia were dropped, because this study is likely to represent a distinct environment to the other studies, which were from tropical forests.</p><p>The study in Australia, representing sub-tropical forest, is likely to represent a distinct environment to the majority of the studies in this meta-analysis, which were from tropical forests. In order to check that the inclusion of the data from the Australian study did not alter the main results, we repeated all models without this data. The parameter estimates from these models were almost identical to the those from the main set of models (figure S2). Figure S2. For 1241 tropical bird species, modelled estimates of probabilities of presence in each of three land-use intensities (a, c, e, g, i) and, given presence, ratios of abundance in light relative to undisturbed, and in intense relative to undisturbed land use (b, d, f, h, j). Probabilities of presence and ratios of abundance were modelled as functions of species’ traits. AIC weights for the traits were: 0.20 for body mass, 0.64 for generation length, and indistinguishable from 1 for migratory status, diet and forest habitat affinity. Black and red crosses on graphs for categorical traits, and transparent lines on graphs for continuous traits, show median parameter estimates from the main set of models. a) Habitat generalists Forest specialists b) 2 0.9 1.6</p><p>R 1.2 P</p><p>0.7 A P 0.5 0.8 0.3 0.4 Undisturbed Light Intensive Light Intensive c) d) 2</p><p>Non-migratory Migratory o i t a e 1.6 r c 0.9</p><p> n e e c s</p><p> n 1.2 e 0.7 a r d p</p><p>. 0.5 n 0.8 b u o b r A</p><p>P 0.3 0.4 Undisturbed Light Intensive Light Intensive e) f) Fruit Nectar Plants (other) Invertebrates Vertebrates Varied 2 o i e</p><p>0.9 t c a</p><p> n 1.6 r e</p><p> s e e</p><p>0.7 c r</p><p> n 1.2 p</p><p> a . d b n</p><p> o 0.5</p><p> u 0.8 r b P 0.3 A 0.4 Undisturbed Light Intensive Light Intensive Land-use intensity Land-use intensity g) h) Primary Light Intensive 2 o i t e 0.9 a 1.6 c r</p><p> n e e s c e 0.7 n 1.2 r a p d</p><p>. n b u</p><p> o 0.5 0.8 b r A P 0.3 0.4 0 5 10 15 20 25 0 5 10 15 20 25 Generation length (years) Generation length (years) i) j) Primary Light Intensive 2 o i t e 0.9 a 1.6 c r</p><p> n e e c s e 0.7 n 1.2 r a p d</p><p>. n b u</p><p> o 0.5 0.8 b r A P 0.3 0.4 0 2000 4000 6000 0 2000 4000 6000 Body mass (g) Body mass (g) References</p><p>1 Harmon, L., Weir, J., Brock, C., Glor, R., Challenger, W. & Hunt, G. 2009 geiger: Analysis of evolutionary diversification. R Package Version 1.3-1. http://cran.r- project.org/web/packages/geiger</p><p>2 Paradis, E. et al. 2012 ape: Analyses of Phylogenetics and Evolution. R Package Version 3.0-5. http://cran.r-project.org/web/packages/ape</p><p>3 Sibley, C. G. & Ahlquist, J. E. 1990 Phylogeny and classification of birds: a study in molecular evolution. New Haven, USA: Yale University Press.</p><p>4 Birdlife International 2011 BirdLife International Taxonomic Checklist Version 4. </p><p>5 Grafen, A. 1989 The phylogenetic regression. Philosophical Transactions of the Royal Society of London Series B: Biological Sciences 326, 119-157. </p>

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