Publication: A triad of kicknet sampling, eDNA metabarcoding, and predictive modeling to assess richness of mayflies, stoneflies and caddisflies in rivers
A triad of kicknet sampling, eDNA metabarcoding, and predictive modeling to assess richness of mayflies, stoneflies and caddisflies in rivers
Date
Date
Date
Citations
Keck, F., Hürlemann, S., Locher, N., Stamm, C., Deiner, K., & Altermatt, F. (2022). A triad of kicknet sampling, eDNA metabarcoding, and predictive modeling to assess richness of mayflies, stoneflies and caddisflies in rivers. Metabarcoding and Metagenomics, 6, 117–131. https://doi.org/10.3897/mbmg.6.79351
Abstract
Abstract
Abstract
Monitoring biodiversity is essential to understand the impacts of human activities and for effective management of ecosystems. Thereby, biodiversity can be assessed through direct collection of targeted organisms, through indirect evidence of their presence (e.g. signs, environmental DNA, camera trap, etc.), or through extrapolations from species distribution and species richness models. Differences in approaches used in biodiversity assessment, however, may come with individual challenges and hinder cross-study comparability. In the
Metrics
Downloads
Views
Additional indexing
Creators (Authors)
Volume
Volume
Volume
Page range/Item number
Page range/Item number
Page range/Item number
Page end
Page end
Page end
Item Type
Item Type
Item Type
Dewey Decimal Classifikation
Dewey Decimal Classifikation
Dewey Decimal Classifikation
Keywords
Language
Language
Language
Publication date
Publication date
Publication date
Date available
Date available
Date available
ISSN or e-ISSN
ISSN or e-ISSN
ISSN or e-ISSN
OA Status
OA Status
OA Status
Free Access at
Free Access at
Free Access at
Publisher DOI
Metrics
Downloads
Views
Citations
Keck, F., Hürlemann, S., Locher, N., Stamm, C., Deiner, K., & Altermatt, F. (2022). A triad of kicknet sampling, eDNA metabarcoding, and predictive modeling to assess richness of mayflies, stoneflies and caddisflies in rivers. Metabarcoding and Metagenomics, 6, 117–131. https://doi.org/10.3897/mbmg.6.79351