Spatial scaling and multi-model inference in landscape genetics: Martes americana in northern Idaho

摘要: Individual-based analyses relating landscape structure to genetic distances across complex landscapes enable rigorous evaluation of multiple alternative hypotheses linking gene flow. We utilize two extensions increase the rigor individual-based causal modeling approach inferring relationships between patterns and flow processes. First, we add a univariate scaling analysis ensure that each variable is represented in functional form represents optimal scale its association with Second, use two-step integrate model selection null hypothesis testing analysis. This series indicated American marten northern Idaho was primarily related elevation, involving isolation by distance, geographical barriers, effects canopy closure, roads, tree size class an empirical habitat were not supported. Gene Northern population therefore driven gradient resistance function minimum at 1500 m.