Environmental DNA reveals fine‐scale habitat associations for sedentary and resident marine species across a coastal mosaic of soft‐ and hard‐bottom habitats

• Published in: Environmental DNA
• Main Authors: Tim J. G. Wilms, Magnus W. Jacobsen, Brian K. Hansen, Henrik Baktoft, Johan Bollhorn, Camilla H. Scharff‐Olsen, Jeannet L. Bertelsen, Enrique García‐Argudo García, Josianne G. Støttrup, Einar E. Nielsen, Jon C. Svendsen
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2022
• Subjects: Baltic Sea; Bayesian multilevel modeling; BRUVS; eDNA; goldsinny wrasse qPCR assay; method comparison; envir; geo; Gadus morhua
• Online Access: https://doi.org/10.1002/edn3.312; https://doaj.org/article/575bb81a34fa4d29a7060484b5ce808d

Abstract Accurate knowledge on spatiotemporal distributions of marine species and their association with surrounding habitats is crucial to inform adaptive management actions responding to coastal degradation across the globe. Here, we investigate the potential use of environmental DNA (eDNA) to detect species–habitat associations in a patchy coastal area of the Baltic Sea. We directly compare species‐specific qPCR analysis of eDNA with baited remote underwater video systems (BRUVS), two non‐invasive methods widely used to monitor marine habitats. Four focal species (cod Gadus morhua, flounder Platichthys flesus, plaice Pleuronectes platessa, and goldsinny wrasse Ctenolabrus rupestris) were selected based on contrasting habitat associations (reef‐ vs. sand‐associated species), as well as differential levels of mobility and residency, to investigate whether these factors affected the detection of species–habitat associations from eDNA. To this end, a species‐specific qPCR assay for goldsinny wrasse is developed and made available herein. In addition, potential correlations between eDNA signals and abundance counts (MaxN) from videos were assessed. Results from Bayesian multilevel models revealed strong evidence for a sand association for sedentary flounder (98% posterior probability) and a reef association for highly resident wrasse (99% posterior probability) using eDNA, in agreement with BRUVS. However, contrary to BRUVS, eDNA sampling did not detect habitat associations for cod or plaice. We found a positive correlation between eDNA detection and MaxN for wrasse (posterior probability 95%), but not for the remaining species and explanatory power of all relationships was generally limited. Our results indicate that eDNA sampling can detect species–habitat associations on a fine spatial scale, yet this ability likely depends on the mobility and residency of the target organism, with associations for sedentary or resident species most likely to be detected. Combined sampling with conventional non‐invasive methods ...