Episodic outbreaks of small mammals influence predator community dynamics in an east African savanna ecosystem
Bibliographic record
Abstract
Little is known about the dynamics of small mammals in tropical savanna: a critical gap in our understanding of Africa's best known ecosystems. Historical evidence suggested small mammals peak in abundance (outbreak) in Serengeti National Park (SNP), as in agricultural systems. We asked 1) what are bottom–up drivers of small mammals and 2) do predators have top–down effects? We documented dynamics of small mammals, birds of prey, and mammalian carnivores in SNP and agricultural areas. We used climatic fluctuations and differences between unmodified and agricultural systems as perturbations to examine trophic processes, key to understanding responses to climate change and increasing human pressures. Data were derived from intermittent measures of abundance collected 1968–1999, combined with systematic sampling 2000–2010 to construct a 42‐year time series. Data on abundance of black‐shouldered kites (1968–2010), eight other species of rodent‐eating birds (1997–2010), and 10 carnivore species (1993–2010) were also collated. Outbreaks occurred every 3–5 years in SNP, with low or zero abundance between peaks. There was a positive relationship between rainfall in the wet season and 1) small mammal abundance and 2) the probability of an outbreak, both of which increased with negative Southern Oscillation Index values. Rodent‐eating birds and carnivores peaked 6–12 months after small mammals. In agricultural areas, abundance remained higher than in natural habitats. Abundances of birds of prey and mammalian carnivores were extremely low in these areas and not related to small mammal abundance. Small mammals are an important food resource for higher trophic levels in the Serengeti ecosystem. Changes in climate and land use may alter their future dynamics, with cascading consequences for higher trophic levels, including threatened carnivores. Although outbreaks cause substantial damage to crops in agricultural areas, small mammals also play a vital role in maintaining some of the diversity and complexity found in African savanna ecosystems.
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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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".