Changes to wildlife habitat on agricultural land in Canada, 1981–2001
Bibliographic record
Abstract
Agricultural land in Canada comprises cultivated land, hayland and grazing land with associated riparian areas, wetlands, woodlands, and natural grasslands. Although these agro-ecosystems support many species of Canada’s native fauna, agricultural land use is dynamic, and changes in agricultural practices can have important implications for biodiversity. We report on Agriculture and Agri-Food Canada’s National Agri-environmental Health Analysis and Reporting Program’s assessment of wildlife habitat on farmland in Canada. Habitat use matrices were developed for 493 species of birds, mammals, reptiles and amphibians associated with farm land habitat in Canada. We derived patterns of land use from Statistics Canada’s Census of Agriculture data and applied them at the soil landscape polygon scale. We developed a proportionally weighted Habitat Capacity index to relate habitat use and land use. A 5% decrease in Habitat Capacity occurred on Canada’s agricultural land from 1981 to 2001, associated with an expansion in cropland and a decline in pasture. A regional pattern of small decline in Habitat Capacity is evident in the Prairie Provinces, where dramatic declines in the use of summerfallow had a positive impact on Habitat Capacity. In eastern Canada, greater decreases in Habitat Capacity occurred, associated with an increase in agricultural intensification. Policies and programs designed to sustain biodiversity should not be developed independently of socioeconomic factors or policies favouring agricultural intensification. We recommend a holistic approach to making policy decisions relevant to environmental and economic sustainability in the Canadian agricultural landscape. Key words: Biodiversity, land use change, agroecosystems, wildlife habitat, indicators
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".