The changing agricultural landscape in Canada’s Mixedwood Plains Ecozone (2011–2022) and the implications for biodiversity
Bibliographic record
Abstract
The prairies and savannahs historically found in the Mixedwood Plains Ecozone have been largely converted into farmland, the dominant present-day land cover. Consequently, many species native to these grasslands have shifted to inhabiting suitable agricultural lands. More recently, agricultural intensification has led to the conversion of pastures and hay fields to annual crops, further removing habitat suitable for the persistence of grassland species. We quantified the shift from pasture and forage to annual crops as well as the dynamics among agricultural lands and other land covers in the Mixedwood Plains Ecozone, predicting biodiversity implications by providing a case study on Eastern Meadowlark ( Sturnella magna (Linnaeus, 1758)). The total agricultural land area changed little over the study period, but area of pasture and forage decreased while row crop area increased. The loss of agricultural lands to urbanization was partly offset by the conversion of forests and wetlands; however, the farmland gained was of lesser agricultural quality than the farmland lost. Declines in Eastern Meadowlark abundance correlated significantly with carrying capacity loss, suggesting that habitat availability is a limiting factor for this species. We highlight the importance of land management policies to minimize the impacts of land conversion on biodiversity and agricultural production.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".