Habitat specificity is not universal proxy for sensitivity to habitat conversion among rodents on the Canadian Prairies
Bibliographic record
Abstract
Abstract Converting habitat for agricultural production threatens biodiversity loss worldwide and has significant implications for human well-being. Debates on how to conserve biodiversity as the demand for agriculture products rises is being informed by studies using habitat specificity as a proxy for sensitivity to land modification, assuming all species respond to habitat loss and fragmentation relative to their affinity towards the habitat type being converted. Here, we test this assumption among rodent assemblages on the Canadian Prairies, hypothesizing negative responses among grassland obligates and neutral or positive responses among habitat generalists to landscape change along a gradient of increasing agricultural intensity. We found complex, sometimes contradictory responses among rodent species, which depended on the magnitude of habitat loss that had occurred and did not always reflect each species’ relative affinity for grassland habitat. Our results suggest future studies should avoid assuming a single habitat type appropriately characterizes resource limitation among all species, and instead carefully consider which dimension of the ecological niche defines specificity for each species. Our results indicate habitat specificity is not always a reliable proxy for sensitivity to land modification, with significant implications for biodiversity conservation when used to inform agriculture and land use policies.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".