Integrating dispersal, breeding and abundance data with graph theory for the characterization and management of functional connectivity in amphibian pondscapes

Abstract

[Context] Robust assessment of functional connectivity in amphibian population networks is essential to address their global decline. The potential of graph theory to characterize connectivity among amphibian populations has already been confirmed, but the movement data on which modelled graphs rely are often scarce and inaccurate. While probabilistic methods that account for intraspecific variability in dispersal better reflect the biological reality of functional connectivity, they must be informed by systematically recorded individual movement data, which are difficult to obtain for secretive taxa like amphibians.

[Objectives] Our aim is to assess the applied potential of probabilistic graph theory to characterize overall connectivity across amphibian pondscapes using finescale capture-recapture data, and to inform conservation management based on the role of ponds on functional connectivity.

[Methods] We monitored an amphibian community in a pondscape located in a Spanish “dehesa” for 2 years. Photoidentification was used to build capture histories for individuals of six species, from which dispersal kernels and population sizes were estimated to model probabilistic graphs.

[Results] We obtained kernels of variable robustness for six species. Node importance for connectivity varied between species, but with common patterns such as shared road crossing areas and the presence of coincident interconnected pond clusters.

[Conclusions] The combination of photoidentification, capture-recapture data and graph theory allowed us to characterize functional connectivity across the pondscape of study accounting for dispersal variability and identify areas where conservation actions could be most efficient. Our results highlight the need to account for interspecific differences in the study and management of amphibian pondscapes.