Development of ecological indicators for the U.S. Great Lakes coastal region – A summary of applications in Lake Huron
Bibliographic record
Abstract
Our overall goal was to develop indicators that both estimate ecological condition and suggest plausible causes of ecosystem degradation across the U.S. Great Lakes coastal region. Here we summarize data gathered along the U.S. Lake Huron coastline for breeding bird, diatom, fish, invertebrate, and wetland plant communities. We sampled these biotic communities on 88 sites in Lake Huron coastal wetlands, uplands, estuaries/bays, and high-energy shorelines. The sites were selected as part of a larger, stratified random design for the entire U.S. Great Lakes coastal region using gradients of anthropogenic stress that incorporated over 200 stressor variables (e.g. agriculture, land cover, human populations, and point source pollution). The U.S. Lake Huron coastal region exemplified wide variation in human-related stress relative to the entire U.S. Great Lakes coast. In general, levels of stress decreased from south to north partly reflecting the change in climate and physiography, but also due to the greater human influences in the southern region as compared with the north. The primary stressors in the southern region are due to agriculture and human development, while the northern region has substantially less agriculture and less human population. The biotic communities sampled were strongly related to the environmental stress gradients, especially agriculture and urbanization. The following indicators were developed based on responses to stress: 1) an index of biological condition for breeding bird communities corresponding to land use, 2) a diatom-inferred total phosphorus indicator corresponding to water quality, 3) exotic fish (carp [Cyprinus carpio] and goldfish [Carassius auratus]) corresponding to agriculture, and 4) a multi-taxa index for wetland plants corresponding to a cumulative stress index. These communities can all serve as useful indicators of the ecological condition of the Lake Huron coast. The ecological indicators provide a baseline on selected conditions for the U.S. Lake Huron coastal region and a means to detect change over time.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".