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• W3192474568 abstract "AbstractPredicting how ecological communities will respond to environmental change is challenging but highly relevant in this era of global change. Ecologists commonly use current spatial relationships between species and environmental conditions to make predictions about the future. This assumes that species will track conditions by shifting their distributions. However, theory and experimental evidence suggest that species interactions prevent communities from predictably tracking temporal changes in environmental conditions on the basis of current spatial relationships between species and environmental gradients. We tested this hypothesis by assessing the dynamics of protist species in replicated two-patch microcosm landscapes that experienced different regimes of spatial and temporal environmental heterogeneity (light vs. dark). Populations were kept in monocultures or polycultures to assess the effect of species interactions. In monocultures, abundances were predictable on the basis of current environmental conditions, regardless of whether the populations had experienced temporal environmental change. But in polycultures, abundances also depended on the history of the environmental conditions experienced. This suggests that because of species interactions, communities should respond differently to spatial versus temporal environmental changes. Thus, species interactions likely reduce the accuracy of predictions about future communities that are based on current spatial relationships between species and the environment." @default.
• W3192474568 created "2021-08-16" @default.
• W3192474568 creator A5017037142 @default.
• W3192474568 creator A5031572969 @default.
• W3192474568 creator A5053885667 @default.
• W3192474568 date "2021-12-01" @default.
• W3192474568 modified "2023-10-18" @default.
• W3192474568 title "Species Interactions Limit the Predictability of Community Responses to Environmental Change" @default.
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• W3192474568 doi "https://doi.org/10.1086/716724" @default.
• W3192474568 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/34762574" @default.
• W3192474568 hasPublicationYear "2021" @default.
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