Long-term population dynamics of dreissenid mussels (Dreissena polymorpha and D. rostriformis): a cross-system analysis

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.Deutsche Forschungsgemeinschaft Cary Institute of Ecosystem Studies (DLS) NSF‐LTREB. Grant Number: DEB‐1556246 NSF‐OPUS. Grant Numbers: DEB‐1456532, JE 288/9‐1, JE 288/9‐2, TÁMOP‐4.2.2.A‐11/1/KONV‐2012‐0038, GINOP‐2.3.2‐15‐2016‐00019, LG‐T; USGS G14AC000263, US EPA GL00E01184 Cornell Agricultural Experiment Station. Grant Number: NYC‐0226747 New York State Department of Environmental Conservation. Grant Number: 1517823 Belarusian Republican Foundation for Fundamental Researc