Landscape genetics and limiting factors

Maintaining connectivity for broad-scale ecological processes like dispersal and gene flow is essential for conserving endangered species in fragmented landscapes. However, determining which habitats should be set aside to promote connectivity has been difficult because existing models cannot incorporate effects of multiple pathways linking populations. Here, we test an ecological connectivity model that overcomes this obstacle by borrowing from electrical circuit theory. The model vastly improves gene flow predictions because it simultaneously integrates all possible pathways connecting populations. When applied to data from threatened mammal and tree species, the model consistently outperformed conventional gene flow models, revealing that barriers were less important in structuring populations than previously thought. Circuit theory now provides the best-justified method to bridge landscape and genetic data, and holds much promise in ecology, evolution, and conservation planning.

Ecologists and conservation biologists have used many measures of landscape structure to predict the population dynamic consequences of habitat loss and fragmentation, but these measures are not well justified by population dynamic theory. Here we introduce a new measure for highly fragmented landscapes, termed the metapopulation capacity, which is rigorously derived from metapopulation theory and can easily be applied to real networks of habitat fragments with known areas and connectivities. Technically, metapopulation capacity is the leading eigenvalue of an appropriate 'landscape' matrix. A species is predicted to persist in a landscape if the metapopulation capacity of that landscape is greater than a threshold value determined by the properties of the species. Therefore, metapopulation capacity can conveniently be used to rank different landscapes in terms of their capacity to support viable metapopulations. We present an empirical example on multiple networks occupied by an endangered species of butterfly. Using this theory, we may also calculate how the metapopulation capacity is changed by removing habitat fragments from or adding new ones into specific spatial locations, or by changing their areas. The metapopulation capacity should find many applications in metapopulation ecology, landscape ecology and conservation biology.