Abstract

During 2007, counties across the Midwestern US with relatively high levels of landscape simplification (i.e., widespread replacement of seminatural habitats with cultivated crops) had relatively high crop-pest abundances which, in turn, were associated with relatively high insecticide application. These results suggested a positive relationship between landscape simplification and insecticide use, mediated by landscape effects on crop pests or their natural enemies. A follow-up study, in the same region but using different statistical methods, explored the relationship between landscape simplification and insecticide use between 1987 and 2007, and concluded that the relationship varied substantially in sign and strength across years. Here, we explore this relationship from 1997 through 2012, using a single dataset and two different analytical approaches. We demonstrate that, when using ordinary least squares (OLS) regression, the relationship between landscape simplification and insecticide use is, indeed, quite variable over time. However, the residuals from OLS models show strong spatial autocorrelation, indicating spatial structure in the data not accounted for by explanatory variables, and violating a standard assumption of OLS. When modeled using spatial regression techniques, relationships between landscape simplification and insecticide use were consistently positive between 1997 and 2012, and model fits were dramatically improved. We argue that spatial regression methods are more appropriate for these data, and conclude that there remains compelling correlative support for a link between landscape simplification and insecticide use in the Midwestern US. We discuss the limitations of inference from this and related studies, and suggest improved data collection campaigns for better understanding links between landscape structure, crop-pest pressure, and pest-management practices.

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