The ecology and evolution of human‐wildlife cooperation
Bibliographic record
Abstract
Abstract Human‐wildlife cooperation is a type of mutualism in which a human and a wild, free‐living animal actively coordinate their behaviour to achieve a common beneficial outcome. While other cooperative human‐animal interactions involving captive coercion or artificial selection (including domestication) have received extensive attention, we lack integrated insights into the ecology and evolution of human‐wildlife cooperative interactions. Here, we review and synthesise the function, mechanism, development, and evolution of human‐wildlife cooperation. Active cases involve people cooperating with greater honeyguide birds and with two dolphin species, while historical cases involve wolves and orcas. In all cases, a food source located by the animal is made available to both species by a tool‐using human, coordinated with cues or signals. The mechanisms mediating the animal behaviours involved are unclear, but they may resemble those underlying intraspecific cooperation and reduced neophobia. The skills required appear to develop at least partially by social learning in both humans and the animal partners. As a result, distinct behavioural variants have emerged in each type of human‐wildlife cooperative interaction in both species, and human‐wildlife cooperation is embedded within local human cultures. We propose multiple potential origins for these unique cooperative interactions, and highlight how shifts to other interaction types threaten their persistence. Finally, we identify key questions for future research. We advocate an approach that integrates ecological, evolutionary and anthropological perspectives to advance our understanding of human‐wildlife cooperation. In doing so, we will gain new insights into the diversity of our ancestral, current and future interactions with the natural world. Read the free Plain Language Summary for this article on the Journal blog.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".