Using eDNA, sediment subfossils, and zooplankton nets to detect invasive spiny water flea (Bythotrephes longimanus)
In light of the ongoing spread and adverse impacts of invasive species, there is an urgent need to develop more effective monitoring and management strategies. Such efforts are constrained by our limited capacity to efficiently detect invasive species. Here, we present the case of Bythotrephes longimanus (spiny water flea) invasion into Wisconsin lakes. Detecting Bythotrephes has proven to be challenging due to its capacity to persist at low densities and its highly seasonal population dynamics. We use Bythotrephes to explore detection using three monitoring methods: zooplankton net tows, environmental DNA (eDNA), and sampling of Bythotrephes tail spine subfossils in sediments. Detection probabilities were highly seasonal for both the net tow and eDNA sampling methods—though detections occurred one to two weeks earlier in net tows—and seasonal targeting substantially improved detection by both methods. Conversely, Bythotrephes spine subfossils were found in all 10 lakes with confirmed Bythotrephes populations and in all five samples taken from each lake, except for a single lake where four of the five samples had subfossils. This method was insensitive to seasonally varying population densities as sediments integrate over variation in population densities. In this case, detection and abundance estimation were well covered by sediments and zooplankton nets, respectively, and eDNA provided little additional benefit to surveillance. Our work highlights the importance of choosing methods that address both species life history and monitoring objectives when designing surveillance programs.
KeywordsInvasive species Detection Bythotrephes Lake sediment eDNA
We would like to thank Carol Warden for field and lab work conducted in Stormy Lake, Gile Flowage, and Lake Gogebic, the North Temperate Lakes Long Term Ecological Research program (NTL-LTER) field crew, including Pam Montz for field and lab work conducted in Trout Lake, and Ted Bier and Kirsten Rhude for field and lab work conducted in Lakes Mendota and Monona. We also thank Kassandra Ford, Marco Scarasso, Michaela Kromrey, Bridget Murphy, Sommer Kuhn, and Michael Josephson for their work in the lab and field. We thank Scott Van Egeren and Maureen Ferry for suggestions and advice in designing and applying this study. Finally, we thank multiple colleagues for comments and friendly review including Emily Stanley, Steve Carpenter, Tony Ives, and Randy Jackson. This work was funded by the Wisconsin Department of Natural Resources, the NSF NTL LTER Program (Grants DEB-0217533 and DEB-1440297), and the office of the UW-Madison Vice Chancellor for Research and Graduate Education.
JRW, MJS, TPS, PJK, and MJVZ designed research; JRW, MJS, and TPS performed research; JRW, MJS, TPS, PJK, and MJVZ analyzed data; JRW, MJS, TPS, PJK, and MJVZ wrote the paper.
- Beranek A (2012) An assessment of the long-term phenology and impact of Bythotrephes longimanus in Island Lake Reservoir, Minnesota, using sediment records. University of Minnesota, Master’s ThesisGoogle Scholar
- Magurran AE, McGill BJ (2011) Biological diversity: frontiers in measurement and assessment. Oxford University Press Inc., New YorkGoogle Scholar
- R Core Team (2016) R: A language and environment for statistical computing. R Foundation for Statistical ComputingGoogle Scholar
- US-EPA (2016) United States Environmental Protection Agency: Zooplankton sampling methodsGoogle Scholar