Restoring local climate refugia to enhance the capacity for dispersal-limited species to track climate change

Abstract

Climate refugia are areas where species can persist through climate change with little to no movement. Among the factors associated with climate refugia are high spatial heterogeneity, such that there is only a short distance between current and future optimal climates, as well as biotic or abiotic environmental factors which buffer against variability in time. However, climate refugia may be declining due to anthropogenic homogenization of environments and degradation of environmental buffers. To quantify the potential for restoration of refugia-like environmental conditions to increase population persistence under climate change, we simulated a population's capacity to track increasing temperatures over time given different levels of spatial and temporal variability in temperature. To determine how species traits affected the efficacy of restoring heterogeneity, we explored an array of values for species' dispersal ability, thermal tolerance, and fecundity. We found that species were more likely to persist in environments with higher local heterogeneity and lower environmental stochasticity. When simulating a management action that increased the local heterogeneity of a previously homogenized environment, species were more likely to persist through climate change, and population sizes were generally higher, but there was little effect with mild temperature change. The benefits of heterogeneity restoration were greatest for species with limited dispersal ability. In contrast, species with longer dispersal but lower fecundity were more likely to benefit from a reduction in environmental stochasticity than an increase in spatial heterogeneity. Our results suggest that restoring environments to refugia-like conditions could promote species' persistence under climate change in addition to conservation strategies such as assisted migration, corridors, and increased protection.

Restoring spatiotemporal variability to enhance the capacity for dispersal‐limited species to track climate change

“…Data are based on a theoretical model; we provide sample code that we used to generate our data, the data that we generated for this study, and novel code to generate the results and figures in Backus (2023) in Figshare at https://doi.org/10.6084/m9.figshare.c.6995565.v1.…”