José Carlos Morante-Filho, Víctor Arroyo-Rodríguez, Edyla R. de Andrade, Bráulio A. Santos,. Eliana Cazetta and Deborah Faria. Appendix S1. The scale of ...
SUPPORTING INFORMATION
Compensatory dynamics maintain bird phylogenetic diversity in fragmented tropical landscapes
José Carlos Morante-Filho, Víctor Arroyo-Rodríguez, Edyla R. de Andrade, Bráulio A. Santos, Eliana Cazetta and Deborah Faria
Appendix S1. The scale of landscape effects on bird phylogenetic metrics.
Because the effect of forest loss on biodiversity is known to depend on the spatial scale at which forest amount is measured (i.e. the so-called “scale of landscape effects”; sensu Jackson & Fahrig 2012; Fahrig 2013) we calculated landscape forest cover within five different-sized buffers (i.e., landscapes), ranging from 200 to 600-m radius. We did not include buffers of 100-m and > 600-m radius because in the former case landscapes showed no variation in forest cover, and in the latter case landscapes overlapped in space, and thus limit spatial independence (Eigenbrod, Hecnar & Fahrig 2011). We then included three additional buffers with the same size between the smallest and the largest buffer, obtaining thus landscapes of 12.56 ha (200-m radius), 28.26 ha (300 m), 50.24 ha (400 m), 78.50 ha (500 m) and 113.04 ha (600 m). We considered the percentage of both old-growth and secondary forests in our estimations of native forest cover. Following Fahrig (2013), we further used linear regression to evaluate the strength of the relationship (R2) between forest cover and five phylogenetic metrics (phylogenetic richness based on Hill number of order q= 0 - 0D(T); Mean phylogenetic distance - MPD; mean nearest taxon phylogenetic distance - MNTD; net related index - NRI; and nearest taxon index - NTI) for the complete bird community, forest species and non-forest species. To identify the spatial scale that best described the response of each phylogenetic metric to forest cover, we used the Akaike Information Criterion corrected to small samples (AICc) and Akaike weights, which ranges from 0 to 1, and express the normalized relative
likelihood of each model, to select the most plausible model (Anderson 2008). The model with the lowest AICc value was considered the most plausible, and those with a difference (Δ) in AICc of less than two units and similar AICc weight values were considered equally probable. Because we assessed 5 variables per community, and we assessed 3 communities, we evaluated 15 different scales of effect (Table S1). The scale that best predicted the effect of forest cover on each response variable and community (i.e., with the smallest AICc) was highly variable, including local landscapes of 200, 300, 400 and 600 m radii. Yet, in all cases we found several scales with similar plausibility (i.e. with a ΔAICc < 2). The 600-m scale was selected as the most parsimonious in 4 out of 15 cases, and was included among the best models (i.e. ΔAICc < 2) in all response variables and communities. As this was also the best scale to predict the effect of forest cover on bird taxonomic diversity in the study region (Morante-Filho, Arroyo-Rodríguez & Faria 2016), we decided to use this landscape size in our analyses.
Table S1. Rank selection of best models explaining patterns of phylogenetic metrics for the complete bird community, forest species and non-forest species in function of the percentage of forest cover measured across different spatial scales (i.e. local landscapes with different concentric radii). To identify the spatial scale that best predicted the response of each phylogenetic metric to forest loss we used information-theoretic criteria (Δi: difference in AICc value between the model with lowest AICc and the ith model; wi: Akaike weights). We also show the coefficient of determination (R2) and the P-value of the linear regression within each spatial scale. Complete community Forest species Non-forest species Phylogenetic metrica
0D(T)
MPD
MNTD
NRI
NTI
Scale 200 m 300 m 400 m 600 m 500 m 300 m 200 m 400 m 600 m 500 m 200 m 300 m 400 m 500 m 600 m 400 m 500 m 300 m 600 m 200 m 200 m 300 m
Δi 0.0 0.5 0.8 0.9 1.0 0.0 0.0 0.1 0.2 0.2 0.0 0.0 0.3 0.4 0.4 0.0 0.2 0.3 0.4 0.5 0.0 0.3
Wi 0.129 0.102 0.086 0.084 0.079 0.21 0.21 0.20 0.19 0.19 0.22 0.22 0.19 0.18 0.18 0.23 0.21 0.19 0.19 0.18 0.25 0.22
R2 0.006 -0.005 -0.018 -0.015 -0.01 -0.01 -0.02 -0.02 -0.02 -0.02 -0.01 -0.01 -0.01 -0.02 -0.02 0.002 0.002 0.006 0.007 0.01 -0.001 -0.007
P 0.27 0.21 0.18 0.18 0.16 0.60 0.64 0.72 0.74 0.76 0.45 0.46 0.58 0.65 0.68 0.30 0.35 0.39 0.40 0.44 0.34 0.41
Scale 600 m 500 m 400 m 300 m 200 m 600 m 500 m 400 m 300 m 200 m 400 m 500 m 600 m 300 m 200 m 400 m 300 m 500 m 600 m 200 m 400 m 500 m
Δi 0.0 2.1 2.6 4.1 7.9 0.0 0.2 0.4 0.8 1.5 0.0 1.1 1.4 2.3 7.5 0.0 0.8 1.6 1.7 2.6 0.0 0.2
Wi 0.561 0.201 0.155 0.071 0.011 0.26 0.23 0.21 0.17 0.12 0.2758 0.1596 0.1367 0.0852 0.0064 0.239 0.234 0.161 0.150 0.098 0.282 0.260
R2 0.415 0.384 0.376 0.351 0.287 0.02 0.01 0.009 0.0002 0.02 0.415 0.240 0.210 0.128 0.009 0.358 0.397 0.372 0.371 0.357 0.136 0.132
P
