Understanding behavioural responses to human-induced rapid environmental change: A meta-analysis
Bibliographic record
Abstract
Behavioural responses are often the first reaction of an organism to human induced rapid environmental change (HIREC), yet current empirical evidence provides no consensus about the main environmental features that animals respond to behaviourally or which behaviours are responsive to HIREC. To understand how changes in behaviour can be predicted by different forms of HIREC, we conducted a meta-analysis of the existing empirical literature focusing on behavioural responses to five axes of environmental change (climate change, changes in CO2, direct human impact, changes in nutrients and biotic exchanges) in five behavioural domains (aggression, exploration, activity, boldness and sociability) across a range of taxa but with a focus on fish and bird species. Our meta-analysis revealed a general absence of directional behavioural responses to HIREC. However, the absolute magnitude of the effect sizes was large. This means that animals have strong behavioural responses to HIREC, but the responses are not clearly in any particular direction. Moreover, absolute magnitude of the effect sizes differed between different behaviours and different forms of HIREC: Exploration responded more strongly than activity, and climate change induced the strongest behavioural responses. Model heterogeneities identified that effect sizes varied primarily because of study design, and the specific sample of individuals used in a study; phylogeny also explains significant variation in our bird model. Based on these results, we make four recommendations to further our understanding: 1) a more balanced representation of laboratory and field studies, 2) consideration of context dependency, 3) standardisation of the methods and definitions used to quantify and study behaviours, and 4) consideration of the role for individual differences in behaviour.
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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 | 0.016 | 0.028 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.039 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".