The roles of humans and apex predators in sustaining ecosystem structure and function: Contrast, complementarity and coexistence
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract In nearly every ecosystem, human predators (hunters and fishers) exploit animals at extraordinarily high rates, as well as target different age classes and phenotypes, compared to other apex predators. Demographically decoupled from prey populations and technologically advanced, humans now impose widespread and significant ecological and evolutionary change. In this paper, we investigate whether there is evidence that humans provide complementary services and whether ecosystem services of predators can be maintained by humans where wild predators are lost. Our objective is to contribute to two key ecological themes: the compatibility of human harvesting within ecosystems and management approaches in consideration of the intentional or unintentional loss of predators. We reviewed evidence for five key effects of predators: natural selection of prey, disease dynamics, landscape effects, carbon cycling and human well‐being. Without carefully designed management strategies, such changes can impose harm to ecosystems and their constituents, including humankind. Ultimately, we applied this information to consider management paradigms in which humans could better support the role of, and potentially behave more like, apex predators and discuss the challenges to such coexistence. 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.
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) | 0.000 | 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 it