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Ecol Appl. 2019 Oct;29(7):e01975. doi: 10.1002/eap.1975. Epub 2019 Aug 8.

Why are monarch butterflies declining in the West? Understanding the importance of multiple correlated drivers.

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Department of Biology, Tufts University, 200 College Avenue, Medford, Massachusetts, 02155, USA.
Xerces Society, 628 Northeast Broadway Suite 200, Portland, Oregon, 97232, USA.
School of Biological Sciences, Washington State University, 14204 Northeast Salmon Creek Avenue, Vancouver, Washington, 98686, USA.


Understanding the factors associated with declines of at-risk species is an important first step in setting management and recovery targets. This step can be challenging when multiple aspects of climate and land use are changing simultaneously, and any or all could be contributing to population declines. We analyzed population trends of monarch butterflies in western North America in relation to likely environmental drivers. Unlike the larger eastern monarch population, past analyses of western monarchs have only evaluated the importance of climate (i.e., not land use) factors as drivers of abundance. We used partial least squares regression (PLSR) to evaluate the potential importance of changes in land use and climate variables. Trends in western monarch abundance were more strongly associated with land use variables than climate variables. Conclusions about importance of climate and land use variables were robust to changes in PLSR model structure. However, individual variables were too collinear to unambiguously separate their effects. We compared these conclusions to the more widely used technique of multiple regression, followed by multi-model inference (MRMI). Naïve interpretation of MRMI results could be misleading, if collinearity were not taken into account. MRMI was also highly sensitive to variation in model construction. Our results suggest a two-pronged approach to monarch conservation, specifically, starting efforts now to restore habitat, while also using experiments to more clearly delineate separate effects of climate and land use factors. They also demonstrate the utility of PLSR, a technique that is growing in use but is still relatively under-appreciated in conservation biology.


climate change; endangered species; glyphosate; habitat loss; land use change; multimodel inference; multiple regression; neonicotinoids; partial least squares regression; pesticide; threats analysis

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