The study was designed to achieve the following overall results:
1. Provide lake-wide assessment using a consistent statistical survey design for major components of water quality and food web; analyses to include abundance and biomass estimates, with defined statistical confidence levels. Information will allow an unprecedented integration of results across the whole lake without biases and limitations inherent in currently uncoordinated and non-comprehensive efforts across the Great Lakes.
2. Reveal biological/ecological patterns over depth. Information will be useful to illustrate ecological distinctions as a function of water depth, including in water quality and across the food web community.
3. Provide a basis for statistical modeling to optimize lake-wide sampling for future defined objectives. Information will be used to quantify what sampling effort and spatial allocation will satisfy specific lake-wide monitoring objectives (including changes over space or time) for an array of water quality and biology parameters.
4. Provide insight on the relative stability of the Lake Superior food web, including an ability to explore critical linkages and spatial scales of interaction with the physico-chemical environment. The integrated, lake-wide data offers a sound foundation to track long-term changes and/or assist development of ecological forecasting models for managers to develop ecosystem-based protection and restoration strategies.
Through sampling of 54 sites during summer 2011, we were able to provide statistically-sound whole lake estimates of abundance and biomass of plankton, benthos, Mysis, and major pelagic and benthic fish species. In general, lake-wide confidence intervals were in a satisfactory range for comparative analyses. Confidence intervals varied across components. Water quality measures generally had low spatial variability whereas fish (as a community) and individual taxa (like Diporeia or individual fish species) had the highest levels of variability.
Examples of biological patterns showed some populations with strong bias to inshore (benthos, Diporeia, pelagic fish) and some with strong bias to offshore (Mysis); but there were a variety of different patterns across taxa. There were semi-distinct inshore and offshore communities in terms of species distributions, abundance and biomass. But there were also transitional environments and a depth-based progression of species, with populations overlapping between shallow and deep water communities.
Successful statistical modeling to date has produced results to identify the expected level of “precision” (i.e., statistical confidence intervals) with differing levels of sampling effort than we conducted, i.e., with both less and more numbers of sites). The analyses will be an effective guide to future assessments at the lake-wide scale. Modeling efforts on spatial allocation strategies are still in progress.
