Competition, predation, and migration: individual choice patterns of Serengeti migrants captured by hierarchical models
Why this work is in the frame
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Bibliographic record
Abstract
Large‐herbivore migrations occur across gradients of food quality or food abundance that are generally determined by underlying geographic patterns in rainfall, elevation, or latitude, in turn causing variation in the degree of interspecific competition and the exposure to predators. However, the role of top‐down effects of predation as opposed to the bottom‐up effects of competition for resources in shaping migrations is not well understood. We studied 30 GPS radio‐collared wildebeest and zebra migrating seasonally in the Serengeti‐Mara ecosystem to ask how predation and food availability differentially affect the individual movement patterns of these co‐migrating species. A hierarchical analysis of movement trajectories (directions and distances) in relation to grass biomass, high‐quality food patches, and predation risk show that wildebeest tend to move in response to food quality, with little attention to predation risk. In contrast, individual zebra movements reflect a balance between the risk of predation and the access to high‐quality food of sufficient biomass. Our analysis shows how two migratory species move in response to different attributes of the same landscape. Counterintuitively and in contrast to most other animal movement studies, we find that both species move farther each day when resources are locally abundant than when they are scarce. During the wet season when the quality of grazing is at its peak, both wildebeest and zebra move the greatest distances and do not settle in localized areas to graze for extended periods. We propose that this punctuated movement in high‐quality patches is explained by density dependency, whereby large groups of competing individuals (up to 1.65 million grazers) rapidly deplete the localized grazing opportunities. These findings capture the roles of predation and competition in shaping animal migrations, which are often claimed but rarely measured.
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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 it