Temperature niche composition change inside and outside protected areas under climate warming
Bibliographic record
Abstract
Conservation of biodiversity relies heavily on protected areas but their role and effectiveness under a warming climate is still debated. We estimated the climate-driven changes in the temperature niche compositions of bird communities inside and outside protected areas in southern Canada. We hypothesized that communities inside protected areas include a higher proportion of cold-dwelling species than communities outside protected areas. We also hypothesized that communities shift to warm-dwelling species more slowly inside protected areas than outside. To study community changes, we used large-scale and long-term (1997-2019) data from the Breeding Bird Survey of Canada. To describe the temperature niche compositions of bird communities, we calculated the community temperature index (CTI) annually for each community inside and outside protected areas. Generally, warm-dwelling species dominated communities with high CTI values. We modeled temporal changes in CTI as a function of protection status with linear mixed-effect models. We also determined which species contributed most to the temporal changes in CTI with a jackknife approach. As anticipated, CTI was lower inside protected areas than outside. However, contrary to our expectation, CTI increased faster over time inside than outside protected areas and warm-dwelling species contributed most to CTI change inside protected areas. These results highlight the ubiquitous impacts of climate warming. Currently, protected areas can aid cold-dwelling species by providing habitat, but as the climate warms, the communities' temperature compositions inside protected areas quickly begin to resemble those outside protected areas, suggesting that protected areas delay the impacts of climate warming on cold-dwelling species.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".