Primates create seedling growth hotspots through pattern of dung deposition
Bibliographic record
Abstract
Abstract Primates play important roles in tropical forests through seed dispersal and herbivory. They comprise a large part of the biomass of forest communities and tend to have clumped patterns of defecations (i.e. at favoured food trees or sleeping sites). Therefore, they may also play important roles in accelerating ecosystem nutrient cycling. Here we conduct a controlled growth experiment to quantify the effect of the addition of primate dung on the growth of both light‐demanding and shade‐tolerant seedlings over 1 year in Kibale National Park, Uganda. A mixed model analysis revealed that light‐demanding species were affected by the natural dung treatment and plants with small initial size had accelerated growth, whereas there was no effect on plant growth for shade‐tolerant species. The long‐term implications of increased dung deposition on the local tree community are unclear as shade‐tolerant species may only show an effect over the long‐term and light‐demanding species may only be able to take advantage of the increased growth if subsequently exposed to high light conditions, such as a treefall gap.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.000 |
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".