Incorporating local adaptation into forecasts of species’ distribution and abundance under climate change

Abstract

Populations of many species are genetically adapted to local historical climate conditions. Yet most forecasts of species’ distributions under climate change have ignored local adaptation (LA), which may paint a false picture of how species will respond across their geographic ranges. We review recent studies that have incorporated intraspecific variation, a potential proxy for LA, into distribution forecasts, assess their strengths and weaknesses, and make recommendations for how to improve forecasts in the face of LA. The three methods used so far (species distribution models, response functions, and mechanistic models) reflect a trade‐off between data availability and the ability to rigorously demonstrate LA to climate. We identify key considerations for incorporating LA into distribution forecasts that are currently missing from many published studies, including testing the spatial scale and pattern of LA, the confounding effects of LA to nonclimatic or biotic drivers, and the need to incorporate empirically based dispersal or gene flow processes. We suggest approaches to better evaluate these aspects of LA and their effects on species‐level forecasts. In particular, we highlight demographic and dynamic evolutionary models as promising approaches to better integrate LA into forecasts, and emphasize the importance of independent model validation. Finally, we urge closer examination of how LA will alter the responses of central vs. marginal populations to allow stronger generalizations about changes in distribution and abundance in the face of LA.

A novel tool to assess the effect of intraspecific spatial niche variation on species distribution shifts under climate change

“…Although our predictions at the margins of the distribution of widespread species are consistent with these suggestions, the integration of dispersal constraints also showed an opposite pattern if the different populations of the species are locally adapted but not able to disperse (Valladares et al, 2014). It will contribute to increasing our ability to predict future shifts in species distributions and their resilience under climate change (Peterson et al, 2019;Smith et al, 2019). We provide a tool to filter species for which further information should be collected to document processes underlying potential local adaptation, adaptive plasticity and dispersal abilities.…”

“…Such model comparison can be done as a first-step approach for a large number of species (Hällfors et al, 2016) and serve as a basis for identifying cases where standard modelling approaches are unlikely to capture the diversity of climate conditions experienced by the species across their range. Our approach will not be able to capture these mechanisms, but it could be useful to detect and prioritize species for which experimental evidence on such key processes would be required and where advanced modelling methods based on these processes should be applied to better understand and predict how local adaptation, adaptive plasticity and dispersal abilities would interact with changing climate conditions to affect distribution shifts (Diniz-Filho et al, 2019;Peterson et al, 2019). Our approach will not be able to capture these mechanisms, but it could be useful to detect and prioritize species for which experimental evidence on such key processes would be required and where advanced modelling methods based on these processes should be applied to better understand and predict how local adaptation, adaptive plasticity and dispersal abilities would interact with changing climate conditions to affect distribution shifts (Diniz-Filho et al, 2019;Peterson et al, 2019).…”

“…The reliability of these statistical models has been questioned due to their limited ability to integrate key ecological and evolutionary processes affecting changes in species distributions (Franklin, 2013;Schweiger et al, 2012;Thuiller et al, 2013). However, it has been shown that there can be important geographical intraspecific variation in the sensitivity and response to changing climate conditions (Mills et al, 2017;Nice et al, 2019;Peterson, Doak, & Morris, 2019). However, it has been shown that there can be important geographical intraspecific variation in the sensitivity and response to changing climate conditions (Mills et al, 2017;Nice et al, 2019;Peterson, Doak, & Morris, 2019).…”

“…However, it has been shown that there can be important geographical intraspecific variation in the sensitivity and response to changing climate conditions (Mills et al, 2017;Nice et al, 2019;Peterson, Doak, & Morris, 2019). Standard niche-based models may, therefore, incorrectly assess the full range of suitable climate conditions for the species and may produce inaccurate or even wrong predictions of distribution shifts (Hällfors et al, 2016;Nice et al, 2019;Peterson et al, 2019;Smith, Godsoe, Rodríguez-Sánchez, Wang, & Warren, 2019;Valladares et al, 2014). Díaz-Almeyda et al, 2017;Malyshev et al, 2016) and arises from local adaptation or adaptive plasticity along the gradient of climate conditions (Macdonald, Llewelyn, & Phillips, 2018;Moran et al, 2016;Vargas et al, 2017).…”

Environmental variability shapes evolution, plasticity and biogeographic responses to climate change

“…Plasticity in thermal tolerance tends to reduce the magnitude of range shifts (Diamond, 2018), suggesting that plasticity in addition to evolution influences range shifts. Further, studies are increasingly demonstrating that intraspecific evolution and plasticity influence range shifts (Catullo, Ferrier, & Hoffmann, 2015;Cotto et al, 2017;Des Roches et al, 2018;Garzón, Alía, Robson, & Zavala, 2011;Peterson, Doak, & Morris, 2019).…”