Publication Details

Category Text Publication
Reference Category Journals
DOI 10.1111/1755-0998.13367
Licence creative commons licence
Title (Primary) Improving the reliability of eDNA data interpretation
Author Burian, A.; Mauvisseau, Q.; Bulling, M.; Domisch, S.; Qian, S.; Sweet, M.
Source Titel Molecular Ecology Resources
Year 2021
Department CLE
Volume 21
Issue 5
Page From 1422
Page To 1433
Language englisch
Topic T5 Future Landscapes
Supplements https://onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1111%2F1755-0998.13367&file=men13367-sup-0001-Supinfo.docx
Keywords barcoding; Bayesian analysis; data fusion; detection probability; eDNA; false positives; metabarcoding; occupancy modelling; sources of error; species distribution modelling
Abstract Global declines in biodiversity highlight the need to effectively monitor density and distribution of threatened species. In recent years, molecular survey methods detecting DNA released by target‐species into their environment (eDNA) have been rapidly on the rise. Despite providing new, cost‐effective tools for conservation, eDNA‐based methods are prone to the occurrence of errors. Best field and laboratory practices can mitigate some, but risks of errors cannot be eliminated and need to be accounted for. Here, we synthesise recent advances in data processing tools that increase the reliability of interpretations drawn from eDNA data. We review advances in occupancy models to consider spatial data‐structures and simultaneously assess rates of false positive and negative results. Further, we introduce process‐based models and the integration of metabarcoding data as complementing approaches to increase reliability of target‐species assessments. These tools will be most effective when capitalising on multi‐source datasets collating eDNA with classical survey and citizen‐science approaches, paving the way for more robust decision‐making processes in conservation planning.
Persistent UFZ Identifier https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=24336
Burian, A., Mauvisseau, Q., Bulling, M., Domisch, S., Qian, S., Sweet, M. (2021):
Improving the reliability of eDNA data interpretation
Mol. Ecol. Resour. 21 (5), 1422 - 1433 10.1111/1755-0998.13367