Reframing conservation physiology to be more inclusive, integrative, relevant and forward-looking: reflections and a horizon scan
Bibliographic record
Abstract
Applying physiological tools, knowledge and concepts to understand conservation problems (i.e. conservation physiology) has become commonplace and confers an ability to understand mechanistic processes, develop predictive models and identify cause-and-effect relationships. Conservation physiology is making contributions to conservation solutions; the number of 'success stories' is growing, but there remain unexplored opportunities for which conservation physiology shows immense promise and has the potential to contribute to major advances in protecting and restoring biodiversity. Here, we consider how conservation physiology has evolved with a focus on reframing the discipline to be more inclusive and integrative. Using a 'horizon scan', we further explore ways in which conservation physiology can be more relevant to pressing conservation issues of today (e.g. addressing the Sustainable Development Goals; delivering science to support the UN Decade on Ecosystem Restoration), as well as more forward-looking to inform emerging issues and policies for tomorrow. Our horizon scan provides evidence that, as the discipline of conservation physiology continues to mature, it provides a wealth of opportunities to promote integration, inclusivity and forward-thinking goals that contribute to achieving conservation gains. To advance environmental management and ecosystem restoration, we need to ensure that the underlying science (such as that generated by conservation physiology) is relevant with accompanying messaging that is straightforward and accessible to end users.
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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".