Application of eDNA metabarcoding to assess spatial distribution and habitat use by freshwater fish in a peri-alpine lake
The application of metabarcoding for fish eDNA analysis has been successfully implemented in a multitude of aquatic environments. While spatial distribution of fish eDNA in lentic systems has gained increasing attention recently, there is a knowledge gap regarding the optimal sampling strategies to...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-05-01
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| Series: | Ecological Indicators |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1470160X25003899 |
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| Summary: | The application of metabarcoding for fish eDNA analysis has been successfully implemented in a multitude of aquatic environments. While spatial distribution of fish eDNA in lentic systems has gained increasing attention recently, there is a knowledge gap regarding the optimal sampling strategies to assess the spatial distribution of fish eDNA in deep, peri-alpine lakes. Water samples (n = 84) were collected from Lake Mondsee (Upper Austria, Austria) using different sampling strategies, targeting fish eDNA distribution patterns with high spatial resolution. Thus, three different eDNA sampling strategies were applied at former traditional sampling sites: (i) point sampling in the littoral, profundal and tributary mouths; (ii) depth-integrated sampling in the pelagic zone; and (iii) horizontally-integrated sampling along shoreline (littoral) transects. Metabarcoding of 12S rDNA was used to identify differences in species composition across the littoral, profundal, pelagic zone, and tributary mouths. Moreover, all samples were analyzed regarding total fish DNA concentration (via qPCR) to determine variability among different lake habitats. Observed spatial eDNA distribution patterns aligned with habitat preferences of most fish species and revealed significant differences in species composition and detection across habitats and depth layers. Furthermore, we found that a relatively small number (n = 13) of horizontally-integrated samples was sufficient for a comprehensive fish biodiversity assessment. This study will help to optimize sampling strategies in lake systems and improve ecological status assessments based on metabarcoding data. |
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| ISSN: | 1470-160X |