Testing the predictability of morphological evolution in contrasting thermal environments
Gaining the ability to predict population responses to climate change is a pressing concern. Using a 'natural experiment', we show that testing for divergent evolution in wild populations from contrasting thermal environments provides a powerful approach, and likely an enhanced predictive...
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| Format: | Dataset |
| Language: | unknown |
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2022
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| Online Access: | https://zenodo.org/record/7440241 https://doi.org/10.5061/dryad.bnzs7h4fb |
| Summary: | Gaining the ability to predict population responses to climate change is a pressing concern. Using a 'natural experiment', we show that testing for divergent evolution in wild populations from contrasting thermal environments provides a powerful approach, and likely an enhanced predictive power for responses to climate change. Specifically, we used a unique study system in Iceland, where freshwater populations of threespine sticklebacks (Gasterosteus aculeatus) are found in waters warmed by geothermal activity, adjacent to populations in ambient-temperature water. We focused on morphological traits across six pairs from warm and cold habitats. We found that fish from warm habitats tended to have a deeper mid-body, a sub-terminally orientated jaw, steeper craniofacial profile, and deeper caudal region relative to fish from cold habitats. Our common garden experiment showed that most of these differences were heritable. Population age did not appear to influence the magnitude or type of thermal divergence, but similar types of divergence between thermal habitats were more prevalent across allopatric than sympatric population pairs. These findings suggest that morphological divergence in response to thermal habitat, despite being relatively complex and multivariate, are predictable to a degree. Our data also suggests that the potential for migration of individuals between different thermal habitats may enhance non-parallel evolution and reduce our ability to predict responses to climate change. We recommend the use of the geomorph package in R for the analysis of 2 morphometric data. Funding provided by: Natural Environment Research CouncilCrossref Funder Registry ID: http://dx.doi.org/10.13039/501100000270Award Number: NE/N016734/1 The data is comprised of 2d landmark data from the morphology of stickleback (Gasterosteus aculeatus). These were collected from digital photos taken of individuals derived from wild/field sites, as well as F1 individuals reared under common conditions in the lab. Data comprised of ... |
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