Biological traits predict shifts in geographical ranges of freshwater invertebrates during climatic warming and drying
Article first published online: 12 DEC 2011
© 2011 Blackwell Publishing Ltd
Journal of Biogeography
Volume 39, Issue 5, pages 957–969, May 2012
How to Cite
Chessman, B. C. (2012), Biological traits predict shifts in geographical ranges of freshwater invertebrates during climatic warming and drying. Journal of Biogeography, 39: 957–969. doi: 10.1111/j.1365-2699.2011.02647.x
- Issue published online: 17 APR 2012
- Article first published online: 12 DEC 2011
- climate change;
- freshwater invertebrates;
- range shifts;
Aim To test the ability of biological traits to predict climate-related changes in geographical ranges of running-water invertebrates.
Location The Australian state of New South Wales and the Australian Capital Territory.
Methods I analysed data from 8928 biomonitoring samples collected during a 16-year period of generally rising air temperatures and declining precipitation. I used quantile regression to test for expansions and contractions on the climatically cooler, warmer, drier and wetter edges of the ranges of 120 invertebrate taxa, and correlated these shifts with the traits of thermophily (degree of preference for high versus low temperature) and rheophily (preference for flowing versus still water).
Results The most commonly inferred range shifts were cool-edge expansion plus warm-edge contraction (71 taxa) and wet-edge expansion plus dry-edge contraction (71), but contractions from both cool and warm extremes (36) and from both dry and wet extremes (28) were also frequent. High-temperature preference was associated with cool-edge expansion and low-temperature preference with wet-edge expansion and contraction from all other extremes. A preference for flow was associated with wet-edge expansion and dry-edge contraction.
Main conclusions Trait analysis has potential for predicting which species will expand their ranges and which will contract, but needs to be coupled with assessment of how the landscape provides each species with opportunities to track or avoid climate change. Improved quantification of climatically relevant traits and integration of trait analysis with species distribution modelling are likely to be beneficial.