Asynchronous food‐web pathways could buffer the response of Serengeti predators to El Niño Southern Oscillation
Bibliographic record
Abstract
Understanding how entire ecosystems maintain stability in the face of climatic and human disturbance is one of the most fundamental challenges in ecology. Theory suggests that a crucial factor determining the degree of ecosystem stability is simply the degree of synchrony with which different species in ecological food webs respond to environmental stochasticity. Ecosystems in which all food-web pathways are affected similarly by external disturbance should amplify variability in top carnivore abundance over time due to population interactions, whereas ecosystems in which a large fraction of pathways are nonresponsive or even inversely responsive to external disturbance will have more constant levels of abundance at upper trophic levels. To test the mechanism underlying this hypothesis, we used over half a century of demographic data for multiple species in the Serengeti (Tanzania) ecosystem to measure the degree of synchrony to variation imposed by an external environmental driver, the El Niño Southern Oscillation (ENSO). ENSO effects were mediated largely via changes in dry-season vs. wet-season rainfall and consequent changes in vegetation availability, propagating via bottom-up effects to higher levels of the Serengeti food web to influence herbivores, predators and parasites. Some species in the Serengeti food web responded to the influence of ENSO in opposite ways, whereas other species were insensitive to variation in ENSO. Although far from conclusive, our results suggest that a diffuse mixture of herbivore responses could help buffer top carnivores, such as Serengeti lions, from variability in climate. Future global climate changes that favor some pathways over others, however, could alter the effectiveness of such processes in the future.
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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 | 0.001 | 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) | 0.002 | 0.001 |
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; both teacher heads agree on what is shown here.
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".