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Please use this identifier to cite or link to this item: https://elib.bsu.by/handle/123456789/261446
Title: Long-term population dynamics of dreissenid mussels (Dreissena polymorpha and D. rostriformis): a cross-system analysis
Authors: Strayer, D.L.
Adamovich, B.V.
Adrian, R.
Aldridge, D.C.
Balogh, C.
Burlakova, L.E.
Fried-Petersen, H.B.
G.-Toth, L.
Hetherington, A.L.
Jones, T.S.
Karatayev, A.Y.
Madill, J.B.
Makarevich, O.A.
Marsden, J.E.
Martel, A.L.
Minchin, D.
Nalepa, T.F.
Noordhuis, R.
Robinson, T.J.
Rudstam, L.G.
Schwalb, A.N.
Smith, D.R.
Steinman, A.D.
Jeschke, J.M.
Keywords: ЭБ БГУ::ЕСТЕСТВЕННЫЕ И ТОЧНЫЕ НАУКИ::Биология
Issue Date: 2019
Publisher: Wiley-Blackwell
Citation: Ecosphere 2019;10(4).
Abstract: Dreissenid mussels (including the zebra mussel Dreissena polymorpha and the quagga mussel D. rostriformis) are among the world's most notorious invasive species, with large and widespread ecological and economic effects. However, their long-term population dynamics are poorly known, even though these dynamics are critical to determining impacts and effective management. We gathered and analyzed 67 long-term (>10 yr) data sets on dreissenid populations from lakes and rivers across Europe and North America. We addressed five questions: (1) How do Dreissena populations change through time? (2) Specifically, do Dreissena populations decline substantially after an initial outbreak phase? (3) Do different measures of population performance (biomass or density of settled animals, veliger density, recruitment of young) follow the same patterns through time? (4) How do the numbers or biomass of zebra mussels or of both species combined change after the quagga mussel arrives? (5) How does body size change over time? We also considered whether current data on long-term dynamics of Dreissena populations are adequate for science and management. Individual Dreissena populations showed a wide range of temporal dynamics, but we could detect only two general patterns that applied across many populations: (1) Populations of both species increased rapidly in the first 1–2 yr after appearance, and (2) quagga mussels appeared later than zebra mussels and usually quickly caused large declines in zebra mussel populations. We found little evidence that combined Dreissena populations declined over the long term. Different measures of population performance were not congruent; the temporal dynamics of one life stage or population attribute cannot generally be accurately inferred from the dynamics of another. We found no consistent patterns in the long-term dynamics of body size. The long-term dynamics of Dreissena populations probably are driven by the ecological characteristics (e.g., predation, nutrient inputs, water temperature) and their temporal changes at individual sites rather than following a generalized time course that applies across many sites. Existing long-term data sets on dreissenid populations, although clearly valuable, are inadequate to meet research and management needs. Data sets could be improved by standardizing sampling designs and methods, routinely collecting more variables, and increasing support.
URI: https://elib.bsu.by/handle/123456789/261446
Scopus: 10.1002/ecs2.2701
metadata.dc.identifier.scopus: 85065021082
Sponsorship: This study is a contribution of the Invasion Dynamics Network (InDyNet), funded by the Deutsche Forschungsgemeinschaft (DFG; JE 288/8-1) including a Mercator Fellowship to DLS. Additional support came from the G.E. Hutchinson Chair at the Cary Institute of Ecosystem Studies (DLS), NSF-LTREB grants (most recently DEB-1556246), and NSF-OPUS grant DEB-1456532 to DLS; DFG projects JE 288/9-1 and JE 288/9-2 to JMJ; TÁMOP-4.2.2.A-11/1/KONV-2012-0038 and the GINOP-2.3.2-15-2016-00019 to CSB and LG-T; USGS G14AC000263 and US EPA GL00E01184 to LEB and AYK; Cornell Agricultural Experiment Station NYC-0226747 and New York State Department of Environmental Conservation grants to LGR and ALH, and NSF grant 1517823 (ALH); and the Belarusian Republican Foundation for Fundamental Research to BA and OM. We thank Krzysztof Lewandowski for his help with data from Polish lakes; Mike Davis, the Minnesota Department of Natural Resources, and the United States Army Corps of Engineers for the Lake Pepin data; Kristen Holeck and Ed Mills for help with Oneida Lake data; the Onondaga County Department of Water Environment Protection; Ulrike Scharfenberger for her advice on the statistical analyses; Jaclyn McGuire for helping to gather information for the supplementary materials; Maggie Oudsema; and Juergen Geist, other InDyNet members, and Ladd Johnson, Alex Latzka, and Teresa Newton for helpful comments and suggestions. Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
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