Abstract
Size spectra analysis (SSA) is used to detect changes in food webs by simplifying complex community structures through abundance-versus-biomass considerations. We applied SSA to 10 years (2006–2015) of data on Great Lakes organisms ranging in size from picoplankton to macrozooplankton. Summer pelagic size spectra slopes were near the theoretical value of −1.0, but spring slopes were steeper, reflecting seasonal differences in abundance of small and large individuals. Pelagic size spectra slopes were relatively stable over the time period we examined. Height (the predicted number of organisms at the spectra midpoint) varied among lakes and was slightly higher in summer than spring in more productive basins. Including benthic data led to shallower slopes when combined with pelagic data, suggesting benthic organisms may increase food web efficiency; height was less affected by benthic data. Benthic data are not routinely included in SSA, but our results suggest they affect slopes and therefore SSA-based predictions of fish abundance. The ability of SSA to track changes in trophic energy transfer makes it a valuable ecosystem monitoring tool.
Highlights
Understanding and predicting ecosystem productivity requires knowledge about the current state of the ecosystem and how it influences production of different organisms
To test the robustness of relying on Akaike information criterion (AIC) scores, we ran a best linear unbiased prediction (BLUP) type analysis, wherein we examined the lake × season × year slopes from our model, and ran a second multiple linear regression on them using AIC to look for the most parsimonious model
pelagic size spectra (PSS) slopes were near the expected theoretical value of -1.0 in the summer, but they were steeper in spring (Table 2; Fig. 3 & Fig. 4)
Summary
Understanding and predicting ecosystem productivity requires knowledge about the current state of the ecosystem and how it influences production of different organisms. Aquatic systems are structured such that small organisms are numerically abundant and larger organisms are more rare, resulting in similar total biomass across groups when summed in logarithmically increasing size bins (Sheldon et al 1972; Blanchard et al 2014). This predictable relationship between abundance and size is referred to as a size spectrum (Trebilco et al 2013; Sprules and Barth 2015; Blanchard et al 2017). The abundance size spectrum provides a simple approach to understanding ecosystem productivity and structure, which may be useful for detecting disturbances and changes in ecosystem function that might not otherwise be apparent
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