Protective multi-stressor interactions in the Anthropocene: Key considerations for investigating cross-tolerance in a conservation context
Bibliographic record
Abstract
In the Anthropocene, species are increasingly faced with multiple stressors that are more severe and less predictable than before. While multiple stressors often interact to affect organisms negatively, sometimes these interactions can be beneficial, enhancing resilience through cross-protection. Cross-protection interactions occur when exposure to one stressor, such as elevated temperature, enhances an organism's tolerance to a different stressor, like hypoxia, through shared protective mechanisms or signaling pathways. Understanding the potential for cross-protection to combat rapid and diverse environmental change is crucial for conservation, as it potentially alters the predicted consequences of such change. Here, we outline 10 key considerations for investigating cross-protection in a conservation context. These considerations include the importance of stressor intensity and timing, recognizing species-specific and sex-specific responses, and embracing temporal variability in environmental stressors. Additionally, predictions will depend upon uncovering the underlying mechanisms of cross-protection by integrating emerging approaches like omics and meta-analyses. By better understanding-and in some cases explicitly leveraging-cross-protective interactions, conservation practitioners may be able to develop more effective management plans to enhance species resilience, potentially mitigating the immediate effects of emerging stressors. These insights are vital for guiding future research directions and informing conservation policies and management practices to preserve biodiversity in the Anthropocene.
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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 | 0.001 |
| 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 | 0.001 |
| 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".