Extinction debt of protected areas in developing landscapes
Bibliographic record
Abstract
To conserve biological diversity, protected-area networks must be based not only on current species distributions but also on the landscape's long-term capacity to support populations. We used spatially explicit population models requiring detailed habitat and demographic data to evaluate the ability of existing park systems in the Rocky Mountain region (U.S.A. and Canada) to sustain populations of mammalian carnivores. Predicted patterns of extirpation agreed with those from logistic-regression models based only on park size and connectedness (or isolation) for the grizzly bear (Ursus arctos) in developed landscapes (northern US. Rocky Mountains) and semideveloped landscapes (southern Canadian Rocky Mountains). The area-isolation model performed poorly where the landscape matrix contained large amounts of suitable habitat (northern Canadian Rocky Mountains). Park area and connectedness were poor predictors of gray wolf (Canis lupus) occurrence because of this species' broader-scale range dynamics and greater ability to inhabit the landscape matrix. A doubling of park area corresponded to a 47% and 57% increase in projected grizzly bear population persistence in developed and semideveloped landscapes, respectively. A doubling of a park's connectedness index corresponded to a 81% and 350% increase in population persistence in developed and semideveloped landscapes, respectively, suggesting that conservation planning to enhance connectivity may be most effective in the earliest stages of landscape degradation. The park area and connectivity required for population persistence increased as the landscape matrix became more hostile, implying that the relatively small combined area of parks in the boreal forest and other undeveloped regions may fall below the threshold for species persistence if parks become habitat islands. Loss of carnivores from boreal landscapes could further reduce the viability of temperate populations occupying refugia at the southern range margin. Spatially realistic population models may be more informative than simplerpatch-matrix models in predicting the effects of landscape change on population viability across a continuum of landscape degradation.
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 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 | 0.004 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".