Summary
- Interactions between multiple anthropogenic stressors can have unexpected synergistic or antagonistic effects, making it difficult to predict their combined effects using single‐stressor studies. The interaction between invasive consumers and nutrient enrichment is particularly important as both stressors frequently co‐occur, and their respective bottom‐up and top‐down effects have the potential to interact across multiple trophic levels.
- We conducted a mesocosm experiment that crossed an increasing nutrient addition gradient against an increasing zebra mussel invasion gradient. Native zooplankton communities were added to the mesocosms, and after 3 months, we examined how the single‐stressor effects on available resources and the zooplankton community were altered by their multiple‐stressor interaction.
- Added nutrients had no effect on small phytoplankton, but increased the abundance and dominance of copepods and reduced the density of large phytoplankton, probably due to increased top‐down predation pressure. Zebra mussels reduced large phytoplankton concentration by about 80%, rotifer abundance by about 75%, and shifted communities towards dominance by cladocerans and adult/juvenile copepods.
- When combined, the top‐down control exerted by the mussels interacted antagonistically to prevent any bottom‐up influence of nutrient enrichment on the zooplankton community. These results provide insight into the potential outcomes of nutrient and invasive consumer stressor interactions, and illustrate the need for researchers to consider environmental change in a multiple‐stressor context.
Methodology
To examine the interactive effects of zebra mussel invasion and nutrient loading we conducted a mesocosm experiment at Queen’s University Biological Station, Canada (QUBS 44.5653N,-76.3240W) from 09-May-2012 to 23-Aug-2012. This experiment used a regression design in which the nutrient enrichment and mussel treatments were applied as crossed gradients. Regression experiments can allow for finer ecological gradients without sacrificing statistical power or having to dramatically increase replication since fewer parameters are required to estimate intercept and slope compared to estimating the mean for all treatment categories in ANOVA designs, and power in regression comes not from the number of treatments or replicates, but from the number of factors and experimental units (Cottingham et al. 2005). Our nutrient addition gradient consisted of ten phosphorus addition levels, increasing from +0 to 85μg/L above ambient. This phosphorus range was selected to reflect observed phosphorus concentrations throughout the Great Lakes and southern Ontario (Nürnberg 1991, Nürnberg 1996). Our mussel treatment gradient consisted of four densities of 0.0, 0.25, 0.5, and 1.0 mussel(s)/L. These levels were chosen to approximate low, medium, and high zebra mussel densities based on our own estimated volumetric calculations using lake survey data from southern Ontario, Quebec, and the northeastern United States (Mellina et al. 1995, Naelpa et al. 1995, Ricciardi et al. 1996, Bailey et al. 1999, Burlakova et al. 2000, Spada et al. 2002, Hunter and Simons 2004, Evans et al. 2011), and previously used experimental volumetric densities (Mellina et al. 1995). The 10 nutrient enrichment and 4 mussel density treatment levels were then crossed against each over a total of 40 mesocosms, such that each mesocosm represented a unique nutrient and mussel density treatment.