Data in support of: Scalable Detection of Aquatic Invasive Species Across Landscapes Using eDNA and Community Science
收藏DataCite Commons2025-11-18 更新2026-04-25 收录
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https://hdl.handle.net/11299/276931
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资源简介:
Opportunistic sampling to detect aquatic invasive species (AIS) often biases the number of lakes known to be invaded. Environmental DNA (eDNA) assays provide a powerful alternative by filtering water and amplifying DNA from target organisms. The relatively low cost and effort of eDNA sampling make it a scalable solution for AIS monitoring. Moreover, the low-intensity collection process allows broad participation, including non-scientific volunteers. We developed off-the-shelf eDNA sampling kits that can be mailed to volunteers. Samples collected by volunteers were compared with those collected by research professionals to evaluate detection ability and contamination rates. Volunteer-based sampling proved as effective as professional sampling, achieving comparable detection and low contamination rates. This data product includes eDNA detection results for 4 common invasive species to the state of Minnesota for 10 lakes. Analysis scripts found in the documented GitHub repository visualize data, showing the effectiveness of community partners in eDNA sample collection and avoidance of contamination. Our results demonstrate that these kits can be scaled beyond our initial 100 volunteers, demonstrating that large-scale, volunteer-driven eDNA monitoring is feasible and effective.
提供机构:
Data Repository for the University of Minnesota (DRUM)
创建时间:
2025-11-18



