Birds such as the African Firefinch (Lagonosticta rubricata) were used to empirically test movement capacity for a framework on community connectivity. Credit: Francesco Veronesi
Connectivity, to a large degree, is dependent on how well individuals can disperse. Dispersal, in turn, is dependent in part on body size. Several studies have shown that dispersal distance is related to body size for reptiles, amphibians, birds, and mammals. This scaling relationship between morphology and behavior – called allometry – has potential for predicting connectivity of not just single species, but entire communities.
A new study uses allometric scaling to develop a framework to understand large-scale community connectivity. A four-step process, using birds in Eswatini, Africa as a model system, provides the outline for translating individual species traits into empirically driven, community models that inform biodiversity conservation strategies.
First, individuals from 39 species of birds were translocated from their natural savannah habitats to agricultural fields to measure how they flew. This movement capacity was then compared to morphological traits. Wing length was found to be the best predictor of flight distance and speed: birds with longer wings flew farther and faster in uninhabitable agricultural environments than those with shorter wings.
A framework for the connectivity of communities. From Hartfelder et al. PNAS 2020;117:36:22274-22280.
Next, these experimental findings were compared with data from long-term observed dispersal distances of 13 species from the South African bird ringing database SAFRING. Movement capacity and dispersal distances were well correlated, emphasizing the effectiveness of using translocation experiments to predict dispersal patterns and model connectivity.
Then, the movement capacity – dispersal distance results were linked with connectivity based on multilayer network theory. This allowed for several different connectivity metrics to be calculated for multiple species in the community and provided a way to visualize connectivity across a landscape.
Finally, the results were leveraged to look at observed biodiversity across protected areas. In this case, community-level networks predicted that larger-bodied bird species would have a relatively high potential for connectivity, while small-bodied bird species would have lower connectivity. The networks were useful in explaining observed bird community structure, and providing a platform to use for further conservation planning.
The result is a trait-based framework that accounts for individual species traits while being applicable to entire communities. It can also link empirical studies to theory, and guide strategies for conserving biodiversity for the future.
