Large herbivores facilitate savanna tree establishment via diverse and indirect pathways
Bibliographic record
Abstract
1. Savanna ecosystems are defined largely by tree-grass mixtures, and tree establishment is a key driver of community structure and ecosystem function in these systems. The factors controlling savanna tree establishment are understudied, but likely involve some combination of seed, microsite and predator/fire limitation. In African savannas, suppression and killing of adult trees by large mammals like elephants (Loxodonta africana Blumenbach, 1797) and giraffes (Giraffa camelopardalis Linnaeus, 1758) can maintain tree-grass co-dominance, although the impacts of even these conspicuous herbivores on tree establishment also are poorly understood. 2. We combined seed addition and predator exclusion experiments with a large-scale, long-term field manipulation of large herbivores to investigate the relative importance of seeds, microsites and predators in limiting establishment of a monodominant tree (Acacia drepanolobium Sjostedt) in a Kenyan savanna. 3. Both wild and domestic (i.e. cattle; Bos taurus Linnaeus, 1758) large herbivores facilitated tree establishment by suppressing abundances of rodents, the most important seed and seedling predators. However, this indirect, positive effect of wild herbivores was negated by wild herbivores' suppression of seed production. Cattle did not have this direct, negative impact; rather, they further assisted tree establishment by reducing cover of understorey grasses. Thus, the impacts of both groups of large herbivores on tree establishment were largely routed through other taxa, with a negligible net effect of wild herbivores and a positive net effect of cattle on tree establishment. 4. The distinction between the (positive) net effect of cattle and (neutral) net effect of wild herbivores is due to the inclusion of browsers and mixed feeders within the assemblage of wild herbivores. Browsing by wild herbivores limited seed production, which reduced tree recruitment; grazing by cattle was more pronounced than that by wild herbivores, and thus promoted germination and subsequent establishment of small trees. 5. Our study is the first to link seed fates to tree establishment in savanna ecosystems in experimentally-manipulated herbivore communities. Further, our results highlight how large herbivores can modify a suite of independent factors - seed production, competition with understorey species, and seed and seedling predation - to collectively drive tree establishment.
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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 | 0.000 |
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".