First data on water mite (Acari, Hydrachnidia) assemblages of Point Rosa Marsh, Harrison Township, Michigan, USA,and their use as environmental bioindicators of aquatic health
Bibliographic record
Abstract
Water mites are aquatic arachnids that have been used in Europe and Central America as bioindicators of ecological health in various freshwater ecosystems (including bogs). Water mites can be found in high densities in the Laurentian Great Lakes and adjacent habitats. Although they are abundant, water mites are generally not used in the assessment of aquatic habitats in the Great Lakes and are usually assigned to the "other" category in macroinvertebrate assessments. This is despite evidence of their utility as aquatic bioindicators. In the present study we consider water mites as bioindicators of the environmental health of Point Rosa marsh, a threatened marsh found on the US side of transboundary Lake St. Clair. The abundance of water mites in Point Rosa Marsh increased from 2017 to 2019 as lake water levels increased. Although increasing water levels in Lake St. Clair can be considered a negative event due to loss of irreplaceable coastal habitat by erosion with potential economic impacts, this present study indicates that water mite populations in Point Rosa Marsh increased during the same period (2017 to 2019). As a result of our study we: update the biodiversity of water mites from Lake St. Clair with new records compared to the last report from the lake over 45 years ago, first report on water mite assemblages at Point Rosa marsh at the Lake St. Clair Metropark on Lake St. Clair and the first demonstration of water mites used as bioindicators in the habitats of the Laurentian Great Lakes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.007 | 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 teacher head, 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".