Premise: In plants, populations and species vary widely along the continuum from outcrossing to selfing. Life-history traits and ecological circumstances influence among-species variation in selfing rates but their general role in explaining intraspecific variation is unknown. Using a database of plant species, we test whether life-history traits, geographic range position, or abundance predict selfing rate variation among populations. 

Methods: We identified species where selfing rates were estimated in at least three populations at known locations. Two key life-history traits (generation time and growth form) were used to predict within-species selfing rate variation. Populations sampled within a species’ native range were assessed for proximity to the nearest edge and abundance. Finally, we conducted linear and segmented regressions to determine functional relationships between selfing rate and geographic range position within species.

Key results: While woody species exhibit lower variation in selfing rates compared to herbs, this is explained by the lower average selfing rate of woody species. Relationships between selfing and peripherality or abundance significantly varied among species in their direction and magnitude. However, there was no general pattern of increased selfing towards range edges. A power analysis shows that tests of this hypothesis require studying many (i.e. 40+) populations.

Conclusions: Intraspecific variation in plant mating systems is often substantial yet remains difficult to explain. Beyond sampling more populations, future tests of biogeographic hypotheses will benefit from phylogeographic information concerning specific range edges, the study of traits influencing mating system (e.g. herkogamy), and measures of abundance at local scales (e.g. population density).

This dataset contains several files that contain information on species and their geographic locations. These data are taken and used by an R script, which then generates the results that we report in our paper.

A user will need to know how to run an R script and how to alter the filename paths so that the R script uploads each necessary file at the appropriate time.