Article first published online: 18 SEP 2013
© 2013 The Authors. New Phytologist © 2013 New Phytologist Trust
Volume 201, Issue 1, pages 335–343, January 2014
How to Cite
Lau, J. A., Shaw, R. G., Reich, P. B. and Tiffin, P. (2014), Indirect effects drive evolutionary responses to global change. New Phytologist, 201: 335–343. doi: 10.1111/nph.12490
- Issue published online: 26 NOV 2013
- Article first published online: 18 SEP 2013
- Manuscript Accepted: 30 JUL 2013
- Manuscript Received: 29 APR 2013
- NSF. Grant Number: IOB 0620318
- NSF LTER. Grant Number: DEB 0080382
- Biocomplexity. Grant Number: 0322057
- carbon dioxide (CO2);
- direct and indirect effects;
- G matrix;
- genetic variation;
- natural selection
- Anthropogenic environmental changes pose significant threats to plant and animal populations. These changes also may affect the evolution of natural populations either directly or indirectly by altering the outcome of species interactions that are important drivers of evolution. This latter indirect pathway may be especially important for evolutionary responses to elevated atmospheric CO2 concentrations (eCO2), which appear to have minimal direct effects on plant evolution but have large effects on interspecific interactions, such as competition.
- We manipulated competitive and CO2 environments of experimental Arabidopsis thaliana populations to test whether eCO2 alters evolutionary trajectories indirectly by altering selection imposed by competitors.
- We found that interspecific competition increased selection on growth traits, reduced heritabilities, and altered genetic covariances between traits and that the magnitude of these effects depended upon the CO2 environment. Although eCO2 had minimal direct effects on evolutionary processes, eCO2 typically reduced the strength of selection imposed by competitors and, therefore, relaxed selection on plant traits when competitors were present.
- Our results indicate that global changes may affect plant evolution indirectly by altering competitive interactions and underscore the importance of conducting research in natural communities when attempting to predict population responses to global change.