title: Space can substitute for time in predicting climate-change effects on biodiversity.
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.
authors.affiliation: Nelson Center for Climatic Research and Department of Geography, University of Wisconsin, Madison, WI 53706, USA. jblois@ucmerced.edu
authors.forename: Jessica L
authors.initials: JL
authors.lastname: Blois
authors.forename: John W
authors.initials: JW
authors.lastname: Williams
authors.forename: Matthew C
authors.initials: MC
authors.lastname: Fitzpatrick
authors.forename: Stephen T
authors.initials: ST
authors.lastname: Jackson
authors.forename: Simon
authors.initials: S
authors.lastname: Ferrier
mesh_terms: D044822:Biodiversity; D057231:Climate Change; D003198:Computer Simulation; D003710:Demography; D004463:Ecology / Q000379:methods; D005580:Fossils; D008954:Models, Biological; D009656:North America; D010944:Plants; D011058:Pollen / Q000737:chemistry; D013045:Species Specificity; D013997:Time Factors
keywords: fossil pollen; generalized dissimilarity modeling; global change; paleoecology