Abstract
Inference concerning the impact of habitat fragmentation on dispersal and gene flow is a key theme in landscape genetics. Recently, the ability of established approaches to identify reliably the differential effects of landscape structure (e.g. land-cover composition, remnant vegetation configuration and extent) on the mobility of organisms has been questioned. More explicit methods of predicting and testing for such effects must move beyond post hoc explanations for single landscapes and species. Here, we document a process for making a priori predictions, using existing spatial and ecological data and expert opinion, of the effects of landscape structure on genetic structure of multiple species across replicated landscape blocks. We compare the results of two common methods for estimating the influence of landscape structure on effective distance: least-cost path analysis and isolation-by-resistance. We present a series of alternative models of genetic connectivity in the study area, represented by different landscape resistance surfaces for calculating effective distance, and identify appropriate null models. The process is applied to ten species of sympatric woodland-dependant birds. For each species, we rank a priori the expectation of fit of genetic response to the models according to the expected response of birds to loss of structural connectivity and landscape-scale tree-cover. These rankings (our hypotheses) are presented for testing with empirical genetic data in a subsequent contribution. We propose that this replicated landscape, multi-species approach offers a robust method for identifying the likely effects of landscape fragmentation on dispersal.
Highlights
Habitat loss and fragmentation lead to small and increasingly isolated populations of wildlife in habitat remnants, decreasing metapopulation viability [1,2,3]
For Circuitscape on a uniform surface (UNIFORM), over all pairs, correlation was strongest with geographic distance (GEOG), but for pairs separated by less than 50 km it was more highly correlated with log-transformed geographic distance (logGEOG)
The cause of this complex curve is an ‘edge effect’ in Circuitscape, where pairwise resistances increase toward the edge of the grid. We demonstrated this ‘edge effect’ for a simplified simulated dataset (Figure 2) and for the more complex pattern of our study area. This effect is disproportionately larger for greater pairwise distances at the same geographic distance from the grid-edge (Figure 2)
Summary
Habitat loss and fragmentation lead to small and increasingly isolated populations of wildlife in habitat remnants, decreasing metapopulation viability [1,2,3]. Small, isolated populations lose fitness through inbreeding depression of individuals and loss of genetic diversity from populations, decreasing adaptability to environmental change; these processes elevate extinction risk [4,5,6]. The time lag over which this occurs depends on many factors and may be many generations [7]. This ‘extinction debt’ is the number of taxa that, following habitat loss, no longer satisfy a threshold criterion for their survival [8]. Many authorities [9,10] have identified the critical role of connectivity (the inverse of fragmentation) at landscape, regional and continental scales in effective conservation management
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