Towards a better mechanistic understanding of edge effects

2016 
Context Predicting and managing edge effects requires an understanding of the mechanisms that drive them. However, analytical methods that dominate edge effects research are not well suited to discriminating mechanisms, because they do not measure ‘indirect’ edge effects: effects that are mediated by covariates in statistical models.
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