Physiology, Behavior, and Conservation
Bibliographic record
Abstract
Many animal populations are in decline as a result of human activity. Conservation practitioners are attempting to prevent further declines and loss of biodiversity as well as to facilitate recovery of endangered species, and they often rely on interdisciplinary approaches to generate conservation solutions. Two recent interfaces in conservation science involve animal behavior (i.e., conservation behavior) and physiology (i.e., conservation physiology). To date, these interfaces have been considered separate entities, but from both pragmatic and biological perspectives, there is merit in better integrating behavior and physiology to address applied conservation problems and to inform resource management. Although there are some institutional, conceptual, methodological, and communication-oriented challenges to integrating behavior and physiology to inform conservation actions, most of these barriers can be overcome. Through outlining several successful examples that integrate these disciplines, we conclude that physiology and behavior can together generate meaningful data to support animal conservation and management actions. Tangentially, applied conservation and management problems can, in turn, also help advance and reinvigorate the fundamental disciplines of animal physiology and behavior by providing advanced natural experiments that challenge traditional frameworks.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.019 | 0.001 |
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".