A study of water quality, zooplankton and macrophytes in wetlands of the Canadian Great Lakes basin: Implications for the restoration of Cootes Paradise Marsh
Why this work is in the frame
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Bibliographic record
Abstract
The overall objective of this study was to provide information on the ecology of coastal wetlands of the Great Lakes. Very little is known regarding the ecology of these highly productive and unique ecosystems. In particular, the aim was to assess the restoration of Cootes Paradise Marsh (via carp exclusion) by looking at zooplankton and how they are affected by water quality and habitat structure. Sixty additional marshes in the Great Lakes basin were visited to assess the quality of Cootes Paradise relative to these wetlands and to provide wetland managers throughout the basin with a large database with which to compare the restoration and degradation of other threatened marsh habitats. This study describes how aquatic macrophytes and lower trophic levels are affected by water and sediment quality and how wetland quality is influenced by 2 major anthropogenic stressors: land-use and carp. Ultimately, an index (WZI) was developed using the zooplankton community as indicators to aid in the assessment of wetland quality. Because the database we used to develop the index included wetlands from all four Canadian Great Lakes, including a diverse range of wetland quality, wetland types and geomorphological settings, it should be widely applicable across the Great Lakes basin. Detailed comparisons of water quality, macrophyte and zooplankton communities showed that there were significant improvements in wetland quality observed in shallow and protected areas of Cootes Paradise Marsh following carp exclusion; however, open and exposed sites remained unchanged and the quality of this coastal marsh was low to moderate relative to high quality marshes existing elsewhere in the Great Lakes basin. Carp exclusion alone was not responsible for these observed changes, and therefore, further remedial actions will be required to increase the functional capacity of this degraded coastal wetland.
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 it