Reconstructing historical fish occurrence and introductions in lakes using sedimentary DNA

The recovery of DNA preserved in the sediment of aquatic systems (sedDNA) has provided short-term and long-term data on biological groups (e.g., bacteria, phytoplankton, zooplankton, and fishes) and has advanced our understanding of how environmental changes have affected aquatic communities. Here, we demonstrate the use of fish sedDNA from lake sediment cores in reconstructing the history of fish occurrences in four lakes within the Oil Sands region in Alberta, Canada. A general fish and eight targeted qPCR-based eDNA assays for freshwater fish species (cisco, lake whitefish, northern pike, chain pickerel, burbot, rainbow trout, lake trout, and walleye) were rigorously designed and validated. Utilizing these assays, we detected sedDNA from several fish species in sediment cores spanning over a century, which aligned with conventional fish surveys and historical records of human-mediated introductions. The use of fish sedDNA provided greater temporal resolution into the historical fish faunal records, bridging the knowledge gap that spanned from 100- to 150-year-old data. The present study also allowed documentation of human-mediated introductions of fish populations to the examined lakes. These findings can be used to refine native freshwater fish ranges and clarify the influence of human-mediated introductions on fish diversity in lakes, providing essential baseline data for conservation management and environmental impact assessments.

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Short Name of Publication Reconstructing historical fish occurrence and introductions in lakes using sedimentary DNA
Deliverable Type Journal Article
Program Catagory Fish
Program Type OSM
Author Mark Louie D. Lopez, Matthew Bonderud, Michael J. Allison, Findlay MacDermid, Erin J. Ussery, Mark E. McMaster, Ave Dersch, Paul Drevnick, Caren C. Helbing
Periodical Title Global Ecology and Conservation
Year of Publication 2024
Publishing Organization
Month of Publication June
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Digital Object Identifier (DOI) https://doi.org/10.1016/j.gecco.2024.e03040
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