Assessing the imprint of geography, host species, land cover and space on the local abundance of a generalist nest parasite, the Brown-headed Cowbird
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The Brown-headed Cowbird is an obligate nest parasite suspected of causing local population declines in several threatened and endangered passerine species. Much attention has been directed towards uncovering the fundamental factors that affect cowbird abundance; however, no study has evaluated these factors in the context of a biogeographic-scale analysis that takes into account spatial autocorrelation. Our primary objective was to compare the relative effects of geography, land cover, host species, and space on the local abundance of cowbirds. We used data from the North American Breeding Bird Survey, the National Land Cover Database, and the latitudinal/longitudinal coordinates of the bird survey routes to examine the effects that host species, land cover composition, and geographical location have on cowbird abundance. Multiple regression models were developed for various combinations of these factors. To control for spatial autocorrelation, we used SAM 4.0 (Spatial Analysis in Macroecology) software to implement simultaneous autoregressive modeling of the error term. We then used a model comparison approach to identify the factors that most affect cowbird abundance. Among all models examined, host species richness was the single strongest predictor and the sole statistically significant predictor. Cowbird abundance increased with host species richness. Furthermore, accounting for the effects of spatial autocorrelation resulted in AICc values that were approximately half the magnitude of models that did not account for space. Our results raise questions regarding the efficacy of cowbird removal programs. If cowbirds have evolved an adaptation to aggregate in areas with high host richness, then cowbird removal programs may not be effective over the long term. In a greater context, our study demonstrates the utility of a spatially-based and geographically-extensive analysis in finding range-wide factors that affect the local abundance of a species.