Climatic factors influence the interactions among trophic levels in an ecosystem in multiple ways. However, whereas most studies focus on single factors in isolation, mainly due to interrelation and correlation among drivers complicating interpretation and analyses, there are still only few studies on how multiple ecosystems respond to climate related factors at the same time. Here, we use a hierarchical Bayesian model with a bioenergetic predator-prey framework to study how different climatic factors affect trophic interactions and production in small Arctic lakes.
View Article and Find Full Text PDFBackground: Statistical autoregressive analyses of direct and delayed density dependence are widespread in ecological research. The models suggest that changes in ecological factors affecting density dependence, like predation and landscape heterogeneity are directly portrayed in the first and second order autoregressive parameters, and the models are therefore used to decipher complex biological patterns. However, independent tests of model predictions are complicated by the inherent variability of natural populations, where differences in landscape structure, climate or species composition prevent controlled repeated analyses.
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