Space can substitute for time in predicting climate-change effects on biodiversity

TLDR

Space‑for‑time substitution is widely used in biodiversity modeling to infer ecological trajectories from spatial patterns, yet the assumption that spatial drivers also drive temporal changes in diversity is rarely tested. The study empirically tests this assumption using Late Quaternary pollen records from eastern North America to model climate‑driven compositional turnover. The authors constructed orthogonal datasets of plant compositional turnover and climatic dissimilarity across time and space from these pollen records and modeled climate‑driven compositional turnover. Space‑for‑time predictions were about 72 % as accurate as time‑for‑time predictions, performed poorly during the Holocene when climate variation was small, but overall support cautious use of the method for modeling community responses to climate change.

Abstract

“Space-for-time” substitution is widely used in biodiversity modeling to infer past or future trajectories of ecological systems from contemporary spatial patterns. However, the foundational assumption—that drivers of spatial gradients of species composition also drive temporal changes in diversity—rarely is tested. Here, we empirically test the space-for-time assumption by constructing orthogonal datasets of compositional turnover of plant taxa and climatic dissimilarity through time and across space from Late Quaternary pollen records in eastern North America, then modeling climate-driven compositional turnover. Predictions relying on space-for-time substitution were ∼72% as accurate as “time-for-time” predictions. However, space-for-time substitution performed poorly during the Holocene when temporal variation in climate was small relative to spatial variation and required subsampling to match the extent of spatial and temporal climatic gradients. Despite this caution, our results generally support the judicious use of space-for-time substitution in modeling community responses to climate change.