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
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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; both teacher heads agree on what is shown here.
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".