Success stories and emerging themes in conservation physiology
Bibliographic record
Abstract
The potential benefits of physiology for conservation are well established and include greater specificity of management techniques, determination of cause-effect relationships, increased sensitivity of health and disturbance monitoring and greater capacity for predicting future change. While descriptions of the specific avenues in which conservation and physiology can be integrated are readily available and important to the continuing expansion of the discipline of 'conservation physiology', to date there has been no assessment of how the field has specifically contributed to conservation success. However, the goal of conservation physiology is to foster conservation solutions and it is therefore important to assess whether physiological approaches contribute to downstream conservation outcomes and management decisions. Here, we present eight areas of conservation concern, ranging from chemical contamination to invasive species to ecotourism, where physiological approaches have led to beneficial changes in human behaviour, management or policy. We also discuss the shared characteristics of these successes, identifying emerging themes in the discipline. Specifically, we conclude that conservation physiology: (i) goes beyond documenting change to provide solutions; (ii) offers a diversity of physiological metrics beyond glucocorticoids (stress hormones); (iii) includes approaches that are transferable among species, locations and times; (iv) simultaneously allows for human use and benefits to wildlife; and (v) is characterized by successes that can be difficult to find in the primary literature. Overall, we submit that the field of conservation physiology has a strong foundation of achievements characterized by a diversity of conservation issues, taxa, physiological traits, ecosystem types and spatial scales. We hope that these concrete successes will encourage the continued evolution and use of physiological tools within conservation-based research and management plans.
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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 | 0.026 | 0.030 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.006 | 0.031 |
| Scholarly communication | 0.016 | 0.025 |
| Open science | 0.003 | 0.010 |
| Research integrity | 0.006 | 0.017 |
| Insufficient payload (model declined to judge) | 0.005 | 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; 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".