2017 ESA Annual Meeting (August 6 -- 11)

COS 144-5 - Estimating the impact of structural plasticity on the adaptability of ecological communities

Thursday, August 10, 2017: 9:20 AM
D139, Oregon Convention Center
Simone Cenci, Civil and Environmental Engineering, MIT, Cambridge, MA, Ana Montero Castano, Estación Biológica de Doñana, Sevilla, Spain and Serguei Saavedra, Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA
Background/Question/Methods

Environmental disturbances constantly change the conditions compatible with species coexistence within large ecological communities. Many of these disturbances happen in very short time scales, requiring an equally fast response from species to persist. As a result, community’s structure and composition are not static. They are characterized by species turnover along with loss and appearance of novel species interactions. Which group of species is more likely to adapt under variable environments? Theory predicts that this group should be the one with the lowest dependency with the rest of the community. Yet one question remain to be answered: what mechanisms could explain this rapid adaptation?

Results/Conclusions

Here, we develop a novel network measure that captures the dependency of any given group of species with its surrounding community. We validate this measure with empirical data, and demonstrate theoretically that a low group-community dependency increases the capacity of a group to adapt to new environments through changes of species interactions. The capacity of species to change interactions in response to environmental changes is typically known as structural plasticity. The measure we have introduced captures the structural differences among all the possible groups in which a network can be partitioned, and the relative connectivity of such groups with the rest of the species. Using seven pairs of control and artificially perturbed plant-pollinator communities, we find that the observed groups of species present in both environments are among the ones with the lowest values of group-community dependency. Finally, we show theoretically that changes of species interactions, within a group of species with low group- community dependency, maximize the range of demographic conditions compatible with species coexistence. Overall, our results point out towards new directions to understand and estimate the collective adaptability of species to rapidly changing environments.