Data from: Montane refugia predict population genetic structure in the Large-blotched Ensatina salamander
View DatasetDescription
Understanding the biotic consequences of Pleistocene range shifts and fragmentation remains a fundamental goal in historical biogeography and evolutionary biology. Here, we combine species distribution models (SDM) from the present and two late Quaternary time periods with multilocus genetic data (mitochondrial DNA and microsatellites) to evaluate the effect of climate-induced habitat shifts on population genetic structure in the Large-blotched Ensatina (Ensatina eschscholtzii klauberi), a plethodontid salamander endemic to middle and high-elevation conifer forest in the Transverse and Peninsular Ranges of southern California and northern Baja California. A composite SDM representing the range through time predicts two disjunct refugia, one in southern California encompassing the core of the species range and the other in the Sierra San Pedro Mártir of northern Baja California at the southern limit of the species range. Based on our spatial model, we would expect a pattern of high connectivity among populations within the northern refugium and, conversely, a pattern of isolation due to long-term persistence of the Sierra San Pedro Mártir population. Our genetic results are consistent with these predictions based on the hypothetical refugia in that (i) historical measures of population connectivity among stable areas are correlated with gene flow estimates; and (ii) there is strong geographical structure between separate refugia. These results provide evidence for the role of recent climatic change in shaping patterns of population persistence and connectivity within the Transverse and Peninsular Ranges, an evolutionary hotspot.
Citations (3)
Cited on 17 August 2020
Weight: 1.73
Cited on 06 February 2015
Weight: 1.46
- https://doi.org/10.1111/mec.12196DataCite MDC OpenAlex
Cited on 01 March 2013
Weight: 1.23
Mentions (0)
No mentions found
Metrics Over Time
Publication Details
Subfield
Ocean Engineering
Field
Engineering
Domain
Physical Sciences
Confidence Score
43%
Source
Scholar Data Model