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Data from: Parallel shifts in trout feeding morphology suggest rapid adaptation to alpine lake environments Combrink, Lucia L.; Rosenthal, William C; Boyle, Lindsey J; Rick, Jessica A; Mandeville, Elizabeth G; Krist, Amy C; Walters, Annika W; Wagner, Catherine E
Description
<b>Abstract</b><br/>
Eco-evolutionary interactions following ecosystem change provide critical insight into the ability of organisms to adapt to shifting resource landscapes. Here we explore evidence for the rapid parallel evolution of trout feeding morphology following eco-evolutionary interactions with zooplankton in alpine lakes stocked at different points in time in the Wind River Range (Wyoming, USA). In this system, trout predation has altered the zooplankton species community and driven a decrease in average zooplankton size. In some lakes that were stocked decades ago, we find shifts in gill raker traits consistent with the hypothesis that trout have rapidly adapted to exploit available smaller-bodied zooplankton more effectively. We explore this morphological response in multiple lake populations across two species of trout (cutthroat trout, Oncorhynchus clarkii, and golden trout Oncorhynchus aguabonita) and examine the impact of resource availability on morphological variation in gill raker number among lakes. Furthermore, we present genetic data to provide evidence that historically stocked cutthroat trout populations likely derive from multiple population sources, and incorporate variation from genomic relatedness in our exploration of environmental predictors of feeding morphology. These findings describe rapid adaptation and eco-evolutionary interactions in trout and document an evolutionary response to novel, contemporary ecosystem change.</p>; <b>Methods</b><br />
Trout were sampled with gill nets from alpine lakes in the Wind River Range (WY, USA) during the summers of 2018 - 2021. Gill raker data (i.e., feeding morphology) was collected by dissecting gill arches and obtaining measurements of morpholgoical features from gill arch photographs. Stomach content data was also collected from trout stomachs for a subset of samples, and raw data was obtained by counting the number of prey items within each identifiable taxonomic group. Environmental variables for each lake were also obtained either in the field or from Google Earth (Google Earth Pro, v7.3.4, accessed 2022) or Google Earth Engine (Gorelick et al. 2017, accessed 2022). Genotyping-by-sequencing data was collected for a subset of samples according to the same protocol outlined in Combrink et al., (2022) and Rosenthal et al., (2022) "Hybridization decreases native cutthroat trout reproductive fitness". Sequences were aligned to a Rainbow trout reference genome using the bwa algorithm and variants were called. A complete description of methods can be found in Combrink et al., (2022) Parallel Shifts in Trout Feeding Morphology Suggest Rapid Adaptation to Alpine Lake Environments"</p>; <b>Usage notes</b><br />
R (R Core Team, 2012) and R Studio (Allaire, 2009). Google Earth (Google Earth Pro, v7.3.4, accessed 2022). Google Earth Engine (Gorelick et al. 2017). </p>
Item Metadata
Title |
Data from: Parallel shifts in trout feeding morphology suggest rapid adaptation to alpine lake environments
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Creator | |
Date Issued |
2023-07-20
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Description |
<b>Abstract</b><br/>
Eco-evolutionary interactions following ecosystem change provide critical insight into the ability of organisms to adapt to shifting resource landscapes. Here we explore evidence for the rapid parallel evolution of trout feeding morphology following eco-evolutionary interactions with zooplankton in alpine lakes stocked at different points in time in the Wind River Range (Wyoming, USA). In this system, trout predation has altered the zooplankton species community and driven a decrease in average zooplankton size. In some lakes that were stocked decades ago, we find shifts in gill raker traits consistent with the hypothesis that trout have rapidly adapted to exploit available smaller-bodied zooplankton more effectively. We explore this morphological response in multiple lake populations across two species of trout (cutthroat trout, Oncorhynchus clarkii, and golden trout Oncorhynchus aguabonita) and examine the impact of resource availability on morphological variation in gill raker number among lakes. Furthermore, we present genetic data to provide evidence that historically stocked cutthroat trout populations likely derive from multiple population sources, and incorporate variation from genomic relatedness in our exploration of environmental predictors of feeding morphology. These findings describe rapid adaptation and eco-evolutionary interactions in trout and document an evolutionary response to novel, contemporary ecosystem change.</p>; <b>Methods</b><br /> Trout were sampled with gill nets from alpine lakes in the Wind River Range (WY, USA) during the summers of 2018 - 2021. Gill raker data (i.e., feeding morphology) was collected by dissecting gill arches and obtaining measurements of morpholgoical features from gill arch photographs. Stomach content data was also collected from trout stomachs for a subset of samples, and raw data was obtained by counting the number of prey items within each identifiable taxonomic group. Environmental variables for each lake were also obtained either in the field or from Google Earth (Google Earth Pro, v7.3.4, accessed 2022) or Google Earth Engine (Gorelick et al. 2017, accessed 2022). Genotyping-by-sequencing data was collected for a subset of samples according to the same protocol outlined in Combrink et al., (2022) and Rosenthal et al., (2022) "Hybridization decreases native cutthroat trout reproductive fitness". Sequences were aligned to a Rainbow trout reference genome using the bwa algorithm and variants were called. A complete description of methods can be found in Combrink et al., (2022) Parallel Shifts in Trout Feeding Morphology Suggest Rapid Adaptation to Alpine Lake Environments"</p>; <b>Usage notes</b><br /> R (R Core Team, 2012) and R Studio (Allaire, 2009). Google Earth (Google Earth Pro, v7.3.4, accessed 2022). Google Earth Engine (Gorelick et al. 2017). </p> |
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Notes |
Dryad version number: 4</p> Version status: submitted</p> Dryad curation status: Published</p> Sharing link: https://datadryad.org/stash/share/-5yyv7X9oLXHV5nHmWABPIRdLaKE_RGatw2szjb_C-s</p> Storage size: 49044730</p> Visibility: public</p> |
Date Available |
2023-07-18
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Provider |
University of British Columbia Library
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License |
CC0 1.0
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DOI |
10.14288/1.0434251
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URI | |
Publisher DOI | |
Grant Funding Agency |
National Institute of General Medical Sciences; National Science Foundation; U.S. Forest Service; Wyoming INBRE*; Wyoming Game and Fish Department*; US Fish and Wildlife Service; University of Wyoming; UWyo Advanced Research Computing Center (2022) Teton Computing Environment, Intel x86_64 cluster. https://doi.org/10.15786/M2FY47*; U.S. Forest Service; American Fisheries Society Eugene-Maughan Scholarship*; American Society of Ichthyologists and Herpetologists Edward C. Raney Fund*
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