1. A greenhouse experiment partially supports inferences of ecogeographic isolation from niche models of Clarkia sister species.
- Author
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Goff, Kaleb A., Martinez Del Rio, Cormac, and Kay, Kathleen M.
- Subjects
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SPECIES distribution , *WATER supply , *SPECIES , *SOIL moisture , *POLLINATORS , *EXTREME environments ,REPRODUCTIVE isolation - Abstract
Premise: Ecogeographic isolation, or geographic isolation caused by ecological divergence, is thought to be of primary importance in speciation, yet is difficult to demonstrate and quantify. To determine whether distributions are limited by divergent adaptation or historical contingency, the gold standard is to reciprocally transplant species between their geographic ranges. Alternatively, ecogeographic isolation is inferred from species distribution models and niche divergence tests using widely available environmental and occurrence data. Methods: We tested for ecogeographic isolation between two sister species of California annual wildflowers, Clarkia concinna and C. breweri, with a hybrid approach. We used niche models to predict water availability as the major axis of ecological divergence and then tested that with a greenhouse experiment. Specifically, we manipulated water availability in field soils for two populations of each species and predicted higher fitness in conditions representing home habitats to those representing the environment of each's sister species. Results: Water availability and soil representing C. concinna generally increased both species' fitness. Thus, water and soil may indeed limit C. concinna from colonizing the range of C. breweri, but not vice versa. We suggest that the competitive environment and pollinator availability, which are not directly captured with either approach, may be key biotic factors correlated with climate that contribute to unexplained ecogeographic isolation for C. breweri. Conclusions: Ours is a valuable approach to assessing ecogeographic isolation, in that it balances feasibility with model validation, and our results have implications for species distribution modeling efforts geared toward predicting climate change responses. [ABSTRACT FROM AUTHOR]
- Published
- 2021
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