Space-for-time substitutions in climate change ecology and evolution

In an epoch of rapid environmental change, understanding and predicting how biodiversity will respond to a changing climate is one of the most urgent challenges faced in ecology and evolution. Since we seldom have sufficient long-term biological data to use the past to anticipate the future, spatial climate-biotic associations are often used as a proxy for predicting biotic responses to climate change over time. These ‘space-for-time substitutions’ (SFTS) have become near ubiquitous in global change biology, but with different subfields having largely developed in isolation. We review how climate-focussed SFTS are used in four subfields of global change biology, each focussed on a different response type – population phenotypes, population genotypes, species’ distributions, and ecological communities. We identify the similarities and differences between the methods, the limitations and opportunities within each subfield, and highlight the potential for different subfields to gain insight from each other. While SFTS are used for a wide range of applications, two main approaches are applied across subfields: in situ gradient methods (including ecological niche modelling) and transplants (common gardens and reciprocal transplants). All SFTS methods and applications share a number of key limitations and assumptions relating to (i) the causality of identified spatial associations and (ii) the transferability of these relationships over time. Despite their widespread use, key assumptions in SFTS remain largely untested, including the fundamental assumption that climate-biotic relationships observed over space are causal and are equivalent to those occurring over time. We highlight how the robustness of SFTS can be improved by addressing these assumptions and limitations, with a particular emphasis on where approaches could be shared between subfields.