Bibliographic record
Abstract
This paper discusses the potential of birds as indicators of sustainable forest management. Several reviews have been critical of birds as indicators of environmental change, and we discuss the major criticisms in the context of forest management. We address these criticisms by suggesting alternative approaches for an indicator research program including the use of focussed studies to identify cause-and-effect relationships, habitat modelling to act as a surrogate to extensive monitoring of populations, and spatially-explicit population modelling (1) to conduct exploratory sensitivity analysis to identify the most important parameters; (2) to incorporate the spatial configuration of habitat into consideration of the impacts of management; (3) to anticipate future impacts as an alternative to measuring past impacts; (4) and, as a means of evaluating alternative management scenarios including natural disturbance regimes. Birds are unlikely to be able to act as a precise tool for the measurement of some forest condition, but they could be useful indicators of sustainable forest management as part of an iterative research program. Key words: sustainable forest management, biological indicators, forest birds, habitat modelling, population modelling, natural disturbance regimes
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".