Supplementary material
Ecological traits affect the response of tropical forest bird species to land-use intensity
Newbold, T., Scharlemann, J.P.W., Butchart, S.H.M., Şekercioğlu, Ç.H., Alkemade, R.,
Booth, H. & Purves, D.W.
Appendix S1. Peer-reviewed publications from which data were collated for the metaanalysis of the response of tropical and sub-tropical bird species’ population densities to landuse intensity
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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.
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.
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.
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.
Johns, A. D. 1991 Responses of Amazonian rain forest birds to habitat modification.
Journal of Tropical Ecology 7, 417-437.
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.
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.
Marsden, S. J. 1998 Changes in bird abundance following selective logging on Seram,
Indonesia. Conservation Biology 12, 605-611.
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.
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.
Mason, D. 1996 Responses of Venezuelan understory birds to selective logging,
enrichment strips, and vine cutting. Biotropica 28, 296-309.
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)
Owiunji, I. & Plumptre, A. J. 1998 Bird communities in logged and unlogged
compartments in Budongo Forest, Uganda. Forest Ecology and Management 108, 115126.
Parry, L., Barlow, J. & Peres, C. A. 2009 Hunting for sustainability in tropical
secondary forests. Conservation Biology 23, 1270-1280.
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
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selectively logged forests and mixed-rural habitats of southern Peninsular Malaysia.
Biological Conservation 123, 489-505.
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.
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.
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.
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.
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.
Thiollay, J.-M. 1992 Influence of selective logging on bird species diversity in a
Guianan rain forest. Conservation Biology 6, 77-63.
Thiollay, J.-M. 1997 Disturbance, selective logging and bird diversity: a Neotropical
forest study. Biodiversity and Conservation 6, 1155-1173.
Waltert, M., Mardiastuti, A. & Mühlenberg, M. 2004 Effects of land use on bird
species richness in Sulawesi, Indonesia. Conservation Biology 18, 1339-1346.
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
10-yr-old secondary forest
15-year logged forest
Fragmented secondary forest
Logged
Logged (1-2 years)
Light
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
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
Intensive
Appendix S2. Methods and results for the test of phylogenetic signal in model residuals.
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.
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.
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
No traits
MASS
GL
DIET
MIGR
FORSPEC
GL + MIGR + DIET + FORSPEC
AIC (with study effect)
6314
6218
6254
6250
6145
6190
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)
Habitat generalists
b) 1.6
Forest specialists
AR
PP
0.9
0.7
0.8
0.5
0.3
0.4
Prob. presence
c)
Light
Non-migratory
Intensive
0.9
0.7
0.5
0.3
Undisturbed
Light
Light
Intensive
Light
Intensive
d) 1.6
Migratory
Abundance ratio
Undisturbed
1.2
0.8
0.4
Intensive
e)
f)
Nectar
Plants (other)
Invertebrates
Abundance ratio
Fruit
Prob. presence
1.2
0.9
0.7
0.5
0.3
Undisturbed
Light
Vertebrates
1.6
1.2
0.8
0.4
Intensive
Light
Land-use intensity
Primary
Light
h)
Intensive
0.9
0.7
0.5
1.6
1.2
0.8
0.4
0.3
0
5
10
15
20
0
25
i)
Light
Intensive
0.9
0.7
0.5
10
15
20
j)
Abundance ratio
Primary
5
Generation length (years)
Generation length (years)
Prob. presence
Intensive
Land-use intensity
Abundance ratio
Prob. presence
g)
Varied
1.6
1.2
0.8
0.4
0.3
0
2000
4000
Body mass (g)
6000
0
2000
4000
Body mass (g)
6000
25
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.
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
b)
Forest specialists
1.6
AR
0.7
0.8
0.3
0.4
Undisturbed
c)
Prob. presence
1.2
0.5
Light
Non-migratory
Intensive
d)
Migratory
Abundance ratio
PP
0.9
0.9
0.7
0.5
0.3
Undisturbed
Light
Light
Intensive
Light
Intensive
2
1.6
1.2
0.8
0.4
Intensive
e)
f)
Nectar
Plants (other)
Abundance ratio
Fruit
Prob. presence
2
0.9
0.7
0.5
0.3
Undisturbed
Light
Invertebrates
2
Vertebrates
1.6
1.2
0.8
0.4
Intensive
Light
Land-use intensity
Primary
Light
h) 2
Intensive
0.9
0.7
0.5
1.6
1.2
0.8
0.4
0.3
0
5
10
15
20
0
25
Generation length (years)
i)
Primary
Light
Intensive
0.9
0.7
0.5
5
10
15
20
Generation length (years)
j)
Abundance ratio
Prob. presence
Intensive
Land-use intensity
Abundance ratio
Prob. presence
g)
Varied
2
1.6
1.2
0.8
0.4
0.3
0
2000
4000
Body mass (g)
6000
0
2000
4000
Body mass (g)
6000
25
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