Ecosystem‐wide responses to fire and large mammal herbivores in an African savanna
Bibliographic record
Abstract
Abstract Fire and large mammal herbivores (LMH) are the principal top‐down forces maintaining savanna structure. Nonetheless, experiments designed to investigate interactions between fire and LMH are rare in savannas, and relationships between environmental variation and biodiversity in the context of fire and LMH are poorly understood. This study addresses these gaps by manipulating the presence of LMH and early and late dry season fires in a tropical African savanna. In addition, this work simultaneously explores environmental variables including soil and foliar quality, vegetation cover, and nearby water sources to more holistically describe factors affecting savanna functioning and biodiversity. After 1 year of experimental treatments, changes in vegetation were already apparent. Shrub abundance and richness and grass richness were higher in the absence of LMH, while grass biomass increased three‐fold in burned plots as compared to unburned plots. Foliar nutrients tended to increase in open plots, while phenolics decreased. Amphibian abundance decreased with early burns and was higher with LMH. In contrast, small mammal abundance and richness increased without LMH and with time since fire. Richness and foraging of LMH were highest after late burns. These results demonstrate ecosystem‐wide effects of LMH, illustrating the importance of considering multiple taxa when designing fire management programs. For example, burning negatively affected amphibians and small mammals and changed vegetation at the same time it increased LMH foraging. In the long‐term, this experiment will shed light on interacting effects of fire and LMH on savanna biodiversity and function. Abstract in Portuguese is available with the online material.
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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 | 0.000 | 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 | 0.001 |
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; 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".