Savannas are increasingly threatened by anthropogenic forces that are causing broad-scale directional shifts in woody vegetation that homogenizes their structure. Yet, whether animal communities respond consistently to changes in woody vegetation in savannas, particularly in terms of the effects of spatial scale, remains poorly understood. We addressed this gap by testing for changes in birds, bats and terrestrial small mammals across a gradient of woody cover in the savannas of southeastern Africa for two years at multiple spatial scales. We found that homogenization of vegetation structure corresponded with decreases in animal richness, diversity and functional diversity. Additionally, metrics of animal diversity declined at opposing ends of a canopy cover gradient (<10% and >65%), where we found distinctly different animal assemblages. These patterns were consistently more pronounced on a broader grid scale (30.25 ha) when compared with the plot scale (0.25 ha). The broad-scale reductions in the diversity and functions of animals observed may be indicative of reductions in the resilience, stability and ecosystem function of tropical savannas. Our results suggest that conservation and management aimed at promoting heterogeneity at broad scales may be critical for maintaining diversity and functionality in savannas.
Appendix A. Functional traits, arranged by taxonomic group (bird, small mammal and bat) and category (diet, foraging, morphology, reproduction and nest refugia), used to calculate functional diversity. We add a seasonality category for bird to address their migratory nature. We derived measures derived from Hockey et al., 2005, Monadjem et al., 2010, Wilman et al., 2014 and Monadjem et al., 2015. We used both categorical and quantitative traits and defaulted to categorical traits if information was sparse.
Table S1. Weight and change (Δ) in AICc from generalized-linear mixed models for richness, diversity and functional diversity of birds, small mammals and bats at the plot and grid scale. A priori models included a heterogeneity index and means (m) and variances (v) of grass biomass (grass), canopy cover (canopy) and shrub cover (shrub). Models included quadratic terms for curvilinear effects. The best models and models within 2 AICc, excluding lesser models with one variable added to better model, are bold.
Table S2. Pseudo R2 and Beta (β) estimates with upper and lower 95% CI for variables from best competing generalized linear models of richness, diversity and functional diversity for birds, small mammals and bats and all estimates from composite models (taxon combined). A priori models included a heterogeneity index and means (m) and variances (v) of grass biomass (grass), canopy cover (canopy) and shrub cover (shrub). Models included quadratic terms for curvilinear effects. Composite models included 4 variables (heterogeneity index, mean shrub and canopy plus a quadratic term). Beta estimates with 95% CI that did not include 0 are bold.
Table S3. Weight and change (Δ) in AICc and pseudo R2 composite (birds, small mammals and bats combined) models of richness, diversity (H′) and functional diversity at the grid and plot scale. Models considered metrics of diversity as a function of a heterogeneity index, a quadric influence of canopy cover (canopy curve) and mean shrub cover [shrub(m)]. Models were ranked based on AICc and the highest R2 values are bold.
Table S4. Distance-based redundancy analysis (db-RDA) results for birds, bats, and small mammals and the grid and plot scale. For each combination of taxa and scale we show; overall inertia and the associated adjusted R2, the amount of variation described by each db-rda axis, permutation test results(anova.cca function in the vegan package in R) for the db-rda axes and permutation test results (anova.cca function in the vegan package in R) for the db-rda constraint variables.