Local adaptation to biotic interactions: a meta-analysis across latitudes
Cite this dataset
Hargreaves, Anna et al. (2021). Local adaptation to biotic interactions: a meta-analysis across latitudes [Dataset]. Dryad. https://doi.org/10.5061/dryad.0vt4b8gv1
Adaptation to local conditions can increase species’ geographic distributions and rates of diversification, but which components of the environment commonly drive local adaptation—particularly the importance of biotic interactions—is unclear. Biotic interactions should drive local adaptation when they impose consistent divergent selection; if this is common we expect transplant experiments to detect more frequent and stronger local adaptation when biotic interactions are left intact. We tested this hypothesis using a meta-analysis of transplant experiments from >125 studies (mostly on plants). Overall, local adaptation was common and biotic interactions affected fitness. Nevertheless, local adaptation was neither more common nor stronger when biotic interactions were left intact, either between experimental treatments within studies (control vs. biotic interactions experimentally manipulated) or between studies that used natural vs. biotically-altered transplant environments. However, the effect of ameliorating negative interactions varied with latitude, suggesting that interactions may promote local adaptation more often in tropical vs. temperate ecosystems, though few tropical studies were available to test this. Our results suggest that biotic interactions often fail to drive local adaptation even though they strongly affect fitness, perhaps because temperate biotic environments are unpredictable at the spatiotemporal scales required for local adaptation.
Data were extracted from primary literature as per description in published article. A large part of the data were originally collected for an article currently in preparation by Bontrager et al.
Locations have been converted into decimal degrees.
Composite fitness measures have been calculated.
All other calculations are done in the associated R script.
Descriptions of each variable/column are given in the associated R script.
The authors have additional studies in progress using the literature search results – other researchers are welcome to use the database but we would appreciate being notified if so (email@example.com, firstname.lastname@example.org, email@example.com)
For R code for the full phylogenetic analyses email firstname.lastname@example.org.
Natural Sciences and Engineering Research Council, Award: Discovery Grant
Fonds de Recherche du Québec – Nature et Technologies, Award: Nouveau chercheur