Abstract
The interplay of dispersal, disturbance, and local dynamics in spatial mosaics has profound effects on the stability and viability of populations. There are two main reasons to consider spatial models in population dynamics: (1) improved estimation of the parameters by utilizing spatial replications, and (2) ecologically realistic modeling. In this paper, we suggest models that are generalizations of the univariate population dynamics models (for example, Ricker or Gompertz) to space–time situations. We accommodate both spatially correlated environmental perturbations and dispersal. Moreover, we suggest computationally simple parameter estimation procedures based on estimating functions and provide an approach for obtaining approximate confidence intervals. The methodology is illustrated on the spatial time series of gypsy moths in the lower peninsula of Michigan.
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