Can life-history traits predict the response of forb populations to changes in climate variability?: Life-history and climate variability
- Citation data:
Journal of Ecology, ISSN: 0022-0477, Vol: 98, Issue: 1, Page: 209-217
- Publication Year:
- Repository URL:
- https://works.bepress.com/david_koons/49; https://digitalcommons.usu.edu/wild_facpub/200; https://works.bepress.com/peter_adler/24
- Agricultural and Biological Sciences; Environmental Science; climate change; elasticity; life history; matrix models; mixed-glass prairie; short-lived perennial; stochastic demography; Ecology and Evolutionary Biology
1. Climate change will cause changes in average temperature and precipitation as well as increased fluctuations around the mean, yet few studies have considered the impacts of altered climate variability on plant populations. We tested whether life-history traits (expected life span, generation time and seed size) can predict plant responses to increased environmental variability across similar plant species sharing the same habitat. 2. We combined long-term demographic data on 10 prairie forb species with stochastic demography techniques to estimate the effects of potential changes in matrix element means and variances on the long-term stochastic population growth rate. 3. For all 10 species, recruitment had higher contribution and elasticity values than survival, meaning that climate change is more likely to influence population growth through effects on recruitment than on survival for these relatively short-lived forbs. Species with longer generation times had lower elasticities to increases in matrix element variability. 4. Synthesis. Our analysis of a unique, long-term data set suggests that longer-lived plant species will be less vulnerable to the effects of future increases in climate variability. While this relationship was previously reported for diverse taxa from many locations, our results show that it also applies within a guild of short-lived species from a single community. The generality of the pattern demonstrates the potential for using life-history traits to make predictions about which species may be the most vulnerable to climate change. © 2009 British Ecological Society.