Spatially-explicit estimation of Wright's neighborhood size in continuous populations
Frontiers in Ecology and Evolution
Effective population size (N e ) is an important parameter in conservation genetics because it quantifies a population's capacity to resist loss of genetic diversity due to inbreeding and drift. The classical approach to estimate N e from genetic data involves grouping sampled individuals into discretely defined subpopulations assumed to be panmictic. Importantly, this assumption does not capture the continuous nature of populations genetically isolated by distance. Alternative approaches based
... ve approaches based on Wright's genetic neighborhood concept quantify the local number of breeding individuals (NS) in a continuous population (as opposed to the global N e ). However, they do not reflect the potential for NS to vary spatially nor do they account for the resistance of a heterogeneous landscape to gene flow (isolation by resistance). Here, we describe an application of Wright's neighborhood concept that provides spatially-explicit estimates of local NS from genetic data in continuous populations isolated by distance or resistance. We delineated local neighborhoods surrounding each sampled individual based on sigma (σ), a measure of the local extent of breeding. When σ was known, the linkage disequilibrium method applied to local neighborhoods produced unbiased estimates of NS that were highly variable across the landscape. NS near the periphery or areas surrounded by high resistance was as much as an order of magnitude lower compared to the center, raising the potential for a spatial component to extinction vortex dynamics in continuous populations. When σ is not known, it may be estimated from genetic data, but two methods we evaluated identified analysis extents that produced considerable bias or error in the estimate of NS. When σ is known or accurately estimated, and the assumptions of Wright's neighborhood are met, the method we describe provides spatially explicit information regarding short-term genetic processes that may inform conservation genetic analyses and management.