Trends in agricultural impact and recovery of wetlands in prairie Canada
Why this work is in the frame
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Bibliographic record
Abstract
Despite widespread recognition that they provide valuable ecosystem services and contribute significantly to global biodiversity, over half of the world's wetlands have been lost, primarily to agriculture. Wetland loss is evident in prairie Canada, but comprehensive information about causes of ongoing impact for existing wetlands is lacking. Habitat data collected for approximately 10,500 wetlands during annual waterfowl surveys (1985-2005) were analyzed using multistate models to estimate rates of wetland impact and recovery from agricultural activities in the Canadian prairies. An impact was defined as an agricultural activity that visibly altered a wetland margin (natural vegetation surrounding wetland interiors) or basin (interior depression capable of holding water), whereas recovery was deemed to have occurred if agricultural activities had ceased and effects were no longer visibly apparent. We estimated separate impact and recovery rates for wetland basins and wetland margins and considered covariates such as location, time, wetness indices, land use, and wetland permanence. Results indicate that impact rates for wetland margins have declined over time, likely due to a decreasing percentage of unaffected wetlands on the landscape. Recovery rates for margins were always lower than impact rates, suggesting progressive incidence of impacts to wetlands over time. Unlike margins, impact and recovery rates for basins fluctuated with May pond densities, which we used as a wetness index. Shallow ephemeral wetlands located in agricultural fields had the highest impact and lowest recovery rates relative to wetlands with higher water permanence or situated in areas of lower agricultural intensity. High rates and incidence of wetland impact in conjunction with low recovery rates clearly demonstrate the need for stronger wetland protection in prairie Canada.
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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) | 0.001 | 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 it