Spatial and inter-annual variation in the Lake Superior offshore zooplankton community
Bibliographic record
Abstract
Lake Superior’s offshore zooplankton community is commonly considered spatially homogeneous and relatively invariant, and thus often referenced as a baseline oligotrophic zooplankton community for the Great Lakes. However, zooplankton biomass can indeed exhibit substantial variability in Lake Superior on finer spatial and temporal scales, but this is not well documented in the literature. We used long-term monitoring data generated by the Environmental Protection Agency’s Great Lakes Biology Monitoring Program from 1997 to 2018 to investigate offshore zooplankton community structure during summer stratification. Both cluster analysis and non-metric multidimensional scaling ordination were used to examine zooplankton spatial patterns in relation to environmental variables. In addition, we used modeled surface current projections for the weeks prior to sampling events to assess the potential importance of horizontal transport in shaping the offshore zooplankton community. We found that although calanoid copepods consistently dominated the community, the relative contribution of cladocerans to total zooplankton biomass was variable. Cluster analysis often singled out three stations, two north of Isle Royale and one offshore of the Pic River, that typically had both higher chlorophyll-a concentrations and higher cladoceran biomass than most others. Analysis of surface current projections suggested horizontal transport of zooplankton could occur from stations with high cladoceran biomass, possibly driving more widespread shifts in the offshore community than expected. Continued assessment of connections between physical and biological variables is important to anticipate food web responses to future stressors, such as climate-driven changes to temperature and circulation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".