Assessing modularity in genetic networks to manage spatially structured metapopulations

As habitats and landscapes are becoming increasingly fragmented, it is more important than ever that the conservationists understand how organisms move across the landscape and to assess connectivity. Functional connectivity is necessary to maintain metapopulation dynamics, minimize genetic drift, maintain genetic diversity on the landscape, and ultimately for the preservation of future evolutionary potential. Graph theory and network analyses have proven to be exceptional tools for assessing functional connections among habitat patches. Ecological studies have recently begun incorporating modularity into analyses of networks. Modularity arises in networks when nodes (habitat patches) form clusters or modules wherein patches within a module interact extensively with each other, but rarely interact with patches from different modules. The goals of this study were to assess modularity in a genetic network, determine the critical scales that functional connections occur among populations, assess the contributions of populations to connectivity, and to identify habitat and landscape connectivity variables affecting network modularity. We constructed a network of genetic covariance to determine functional connections among breeding populations of Ambystoma annulatum (Ringed Salamander) at Fort Leonard Wood, Missouri, United States. From this network, we tested for the presence of modularity after accounting for the effects of distance between each breeding population, assessed the relative importance of each breeding population in contributing to within-and among-module movements, and tested the effects of habitat and landscape connectivity on network parameters using linear models. The genetic network consisted of four modules, and modularity was significant after accounting for distance. Individual populations generally contributed to within-or among-module movements, but not both. As within-module strength decreased, among-module connectivity increased. Habitat and connectivity parameters were generally poor predictor network parameters, suggesting that modularity may be a result of biotic or abiotic factors that affect successful recruitment from local populations. Our study highlights the importance of fully understanding the functional connections among populations on the landscape. The scale at which connections occur and the role of each population in contributing to connectivity are invaluable to making effective management and conservation decisions. Ultimately, analyses of network modularity have tremendous potential to inform these decisions.