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• W2262742477 abstract "Species distribution models (SDMs) have been criticized for involving assumptions that ignore or categorize many ecologically relevant factors such as dispersal ability and biotic interactions. Another potential source of model error is the assumption that species are ecologically uniform in their climatic tolerances across their range. Typically, SDMs treat a species as a single entity, although populations of many species differ due to local adaptation or other genetic differentiation. Not taking local adaptation into account may lead to incorrect range prediction and therefore misplaced conservation efforts. A constraint is that we often do not know the degree to which populations are locally adapted. Lacking experimental evidence, we still can evaluate niche differentiation within a species' range to promote better conservation decisions. We explore possible conservation implications of making type I or type II errors in this context. For each of two species, we construct three separate Max-Ent models, one considering the species as a single population and two of disjunct populations. Principal component analyses and response curves indicate different climate characteristics in the current environments of the populations. Model projections into future climates indicate minimal overlap between areas predicted to be climatically suitable by the whole species vs. population-based models. We present a workflow for addressing uncertainty surrounding local adaptation in SDM application and illustrate the value of conducting population-based models to compare with whole-species models. These comparisons might result in more cautious management actions when alternative range outcomes are considered." @default.
• W2262742477 created "2016-06-24" @default.
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• W2262742477 date "2016-06-01" @default.
• W2262742477 modified "2023-10-01" @default.
• W2262742477 title "Addressing potential local adaptation in species distribution models: implications for conservation under climate change" @default.
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• W2262742477 doi "https://doi.org/10.1890/15-0926" @default.
• W2262742477 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/27509755" @default.
• W2262742477 hasPublicationYear "2016" @default.
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