The equilibrium theory of island biogeography1 is the basis for estimating extinction rates2 and a pillar of conservation science3,4. The default strategy for conserving biodiversity is the designation of nature reserves, treated as islands in an inhospitable sea of human activity5. Despite the profound influence of islands on conservation theory and practice3,4, their mainland analogues, forest fragments in human-dominated landscapes, consistently defy expected biodiversity patterns based on island biogeography theory6,7,8,9,10,11,12,13. Countryside biogeography is an alternative framework, which recognizes that the fate of the world’s wildlife will be decided largely by the hospitality of agricultural or countryside ecosystems12,14,15,16,17. Here we directly test these biogeographic theories by comparing a Neotropical countryside ecosystem with a nearby island ecosystem, and show that each supports similar bat biodiversity in fundamentally different ways. The island ecosystem conforms to island biogeographic predictions of bat species loss, in which the water matrix is not habitat. In contrast, the countryside ecosystem has high species richness and evenness across forest reserves and smaller forest fragments. Relative to forest reserves and fragments, deforested countryside habitat supports a less species-rich, yet equally even, bat assemblage. Moreover, the bat assemblage associated with deforested habitat is compositionally novel because of predictable changes in abundances by many species using human-made habitat. Finally, we perform a global meta-analysis of bat biogeographic studies, spanning more than 700 species. It generalizes our findings, showing that separate biogeographic theories for countryside and island ecosystems are necessary. A theory of countryside biogeography is essential to conservation strategy in the agricultural ecosystems that comprise roughly half of the global land surface and are likely to increase even further14.
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We thank P. Ehrlich, E. Kalko, F. Oviedo Brenes, R. Zahawi, L. Frishkoff, K. Holl, H. Kim Frank, M. Knope, J. L. Reid, A. Wrona, H. York and dozens of field assistants and Costa Rican landowners, and the communities and staffs of the Organization for Tropical Studies, Las Cruces Biological Station, the Smithsonian Tropical Research Institute and the Center for Conservation Biology at Stanford University. Research was funded by the Winslow Foundation, the Moore Family Foundation, the German Academic Exchange Service, the German Science Foundation, Peter and Helen Bing, Ralph and Louise Haberfeld, and a Restoration Workshop Research Grant through the Las Cruces Biological Station. C.D.M. and D.S.K. were supported by National Science Foundation Graduate Research Fellowships.
The authors declare no competing financial interests.
Extended data figures and tables
Shown are the proportions of captured individuals from 30 species in different countryside habitats. Forest dependence rank ranges from forest avoidance (left side of x axis) to reserve dependent (right side of x axis) and was determined by comparing relative abundance in reserves (green) with that in coffee plantations (yellow).The proportions of individuals captured in smaller forest fragments of various sizes are also shown. Total numbers of individuals per species are listed parenthetically after abbreviated species names. A total of 4,424 individuals are represented.
Extended Data Figure 2 Assemblage Abundance Shift Index based on ordination analyses of bat abundances and how they collectively shift relative to bat abundances in minimally altered habitat.
The plots demonstrate how the Assemblage Abundance Shift Index accounted for changes in species richness to focus on predicting changes in assemblage-level shifts in abundances between habitats. In both ecosystems regression analyses favoured logarithmic relationships between the abundance-based assemblage similarity of the bats captured in a net relative to the reserve or mainland nets and the observed species richness of the bats captured in the net (see Methods). Logarithmic models (solid lines) outperformed linear models in model comparisons (countryside ecosystem ΔAICc = 22.75; island ecosystem ΔAICc = 5.92). For each ecosystem, logarithmic models were used to calculate the residual assemblage shift for each net that was not explained by changes in species richness but by changes in the abundances of species. The residuals are therefore an index of assemblage abundance shifting after accounting for changes in species richness. Regression coefficients and statistics are described in Extended Data Table 3.
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Mendenhall, C., Karp, D., Meyer, C. et al. Predicting biodiversity change and averting collapse in agricultural landscapes. Nature 509, 213–217 (2014). https://doi.org/10.1038/nature13139
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