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Using distance sampling to estimate densities of Zebra Mussels (Dreissena polymorpha) in early-stage invasions
Author(s) -
Jake M. Ferguson,
Michael A. McCartney,
Naomi S. Blinick,
Leslie Schroeder,
John Fieberg
Publication year - 2019
Publication title -
freshwater science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.743
H-Index - 116
eISSN - 2161-9565
pISSN - 2161-9549
DOI - 10.1086/706105
Subject(s) - dreissena , distance sampling , sampling (signal processing) , ecology , environmental science , zebra mussel , population density , population , biomass (ecology) , transect , sampling design , biology , statistics , bivalvia , mathematics , mussel , mollusca , computer science , filter (signal processing) , computer vision , demography , sociology
Estimating the density and distribution of invasive populations is critical for management and control efforts but can be a challenge in nascent infestations when population densities are low. Statistically-valid sampling designs that account for imperfect detection of individuals are needed to estimate densities across time and space. Survey methods that yield reliable estimates allow managers to determine how invader biomass affects ecosystem services and evaluate population trends and effectiveness of control measures. We investigated the use of distance sampling via self-contained underwater breathing apparatus divers to determine densities of invasive Zebra Mussels (Dreissena polymorpha) in 2 recently-invaded lakes in central Minnesota. This framework allows divers to cover the large areas necessary in low-density, recent infestations. We estimated that a diver could detect between 5 and 41% of the mussels present in the surveyed area, depending on the specific diver and on whether the lake bottom was vegetated. Presence of vegetation had a greater influence on detection probability than diver identity. We also found our sampling design did not meet a key assumption of conventional distance sampling: that detection along the transect line is perfect. Therefore, accurate density estimates required a double-observer approach. These results highlight the importance of accounting for detectability when comparing estimates over time or across lakes, particularly when different observers conduct surveys. However, further evaluation is needed to determine if changes in field sampling techniques can meet the assumptions behind conventional distance sampling for freshwater mussels. We also suggest that the efficiency of distance sampling should be compared to alternatives such as quadrat sampling across a range of mussel densities.

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