Impacts of the Northwest Forest Plan on forest composition and bird populations
Bibliographic record
Abstract
The Northwest Forest Plan (NWFP) initiated one of the most sweeping changes to forest management in the world, affecting 10 million hectares of federal land. The NWFP is a science-based plan incorporating monitoring and adaptive management and provides a unique opportunity to evaluate the influence of policy. We used >25 years of region-wide bird surveys, forest data, and land-ownership maps to test this policy's effect on biodiversity. Clearcutting decreased rapidly, and we expected populations of older-forest-associated birds to stabilize on federal land, but to continue declining on private industrial lands where clearcutting continued. In contrast, we expected declines in early-seral-associated species on federal land because of reduced anthropogenic disturbance since the NWFP. Bayesian hierarchical models revealed that bird species' population trends tracked changes in forest composition. However, against our expectations, declines of birds associated with older forests accelerated. These declines are partly explained by losses of older forests due to fire on federal land and continued clearcutting elsewhere. Indeed, the NWFP anticipated that reversing declines of older forests would take time. Overall, the early-seral ecosystem area was stable, but declined in two ecoregions-the Coast Range and Cascades-along with early-seral bird populations. Although the NWFP halted clearcutting on federal land, this has so far been insufficient to reverse declines in older-forest-associated bird populations. These findings underscore the importance of continuing to prioritize older forests under the NWFP and ensuring that the recently proposed creation of early-seral ecosystems does not impede the conservation and development of older-forest structure.
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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 | 0.001 | 0.000 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".