The impacts of climate variability on the niche concept and distributions of species

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Inter-annual climate variability affects the long-term growth rate and thus the viability of populations. Despite the importance of climate variability, niche models and species distribution models (SDMs) typically do not account for it. This causes systematic biases in the projected distributions of species and can mislead conservation measures. Here, we use ideas from stochastic demography to quantify the effects of inter-annual climate variability on population performance and distributions of species, developing a new SDM framework which we call XSDM. The new framework expands the traditional deterministic notion of the fundamental niche, re-conceptualizing the niche to account for stochasticity. XSDM can be applied widely, requiring only occurrence data, e.g. from GBIF, and it shows superior performance to commonly-used SDMs in simulation studies. Using XSDM, we assessed the impacts of inter-annual climate variability on 10 North-American species chosen as illustrative examples. We found that climate variability reduces the potential distribution of the species on average by 26% and up to 57%. SDMs and niche concepts that do not incorporate variability cannot account for this reduction and can thus be strongly biased. Because climate change is altering not only average conditions, but also the frequency and intensity of extreme events, which are aspects of variability, it is paramount to better understand how climate variability influences the distributions of species in order to help mitigate future biodiversity losses due to climate change. Our new XSDM approach provides a new foundation for such a research program by helping re-orient niche theory to include stochastic effects.

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Significance statement

Inter-annual climate variability influences populations’ long-term viability and, therefore, species’ distributional ranges. However, existing niche concepts and species distribution models (SDMs) typically do not account for such variability and therefore cannot accurately predict species’ distributions. Here, we developed the new SDM framework “XSDM” that accounts for climate variability when assessing the ecological niche of a species and predicting its distribution. We tested XSDM using simulations, where it performs better than traditional SDMs. By applying XSDM to 10 example species, we found that climate variability impacts their distribution, reducing potential range by up to half. As global change alters climate variability, e.g., through increased frequency and intensity of extreme events, our new paradigm provides better tools for countering future biodiversity losses.