Accounting for the temporal variation of spatial effect improves inference and projection of population dynamics models

摘要: Abstract Population dynamics models incorporating density dependence and habitat heterogeneity are useful tools to explain project the spatiotemporal variation of wildlife abundance. Despite their wide application in ecology conservation biology, inference projection these may be problematic when residual spatial autocorrelation (SAC) is found. We aimed improve population by accounting for SAC. considered three Gompertz that incorporated effect wetland abundance Mallard (Anas platyrhynchos). compared a conventional model did not account SAC (ENV) with two novel SAC, one (a spatially autocorrelated process error) vary over time (STA) other varied (DYN). evaluated using data from 1974 1998 1999 2010. then forecasted 2011 2100 under different levels loss. The DYN eliminated had better fit than ENV STA ( Δ D ¯ = 2498.3 n d 1988.8 , respectively). coverage rate was closest nominal value among models. smaller areas decrease future loss we this study, combined practical evaluation approach, can provide reliable abundance, thus have ecological studies practices aim understand environmental changes. In particular, decision-making based on projections, used minimize risk reducing effort still high value, due its favorable performance.