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Abstract: We explore the consequences of including both general and specific controls for spatial autocorrelation in country-level models of species imperilment. A general spatial autocorrelation term constructed as a binary contiguity matrix aggregates an unknown number of possible influences, some of which exert a negative impact on species imperilment in the referent country, others of which exert a positive impact. Adding spatial dependency measures that are based on specific cross-border effects can substantially change not only the size and statistical significance of the general spatial dependency term but also the size, sign, and/or statistical significance of the explanatory variables. [Copyright &y& Elsevier]

Abstract: Modeling the determinants of species'' ecological fragility using country-specific data may be complicated by the fact that factors that influence species imperilment may extend or operate beyond arbitrary political boundaries. Following McPherson and Nieswiadomy [McPherson, M.A. and Nieswiadomy, M.L., 2005. Environmental Kuznets curve: threatened species and spatial effects. Ecol. Econ. 55: 395–407.], we confirm the advisability of controlling for spatial autocorrelation in models focusing on imperilment of birds, mammals, reptiles, amphibians, and vascular plants. We also compare the performance of different definitions of the spatial dependency. Although our a priori expectation was that measures that more accurately reflect the degree of spatial interaction between countries, such as the percentage of shared border, would be superior to a measure of simple adjacency, in fact we find that the simple adjacency measure outperforms the other measures in most cases. [Copyright &y& Elsevier]