IMPACTS OF NEST CONSTRUCTION BY NATIVE PIGS (SUS SCROFA) ON LOWLAND MALAYSIAN RAIN FOREST SAPLINGS
Bibliographic record
Abstract
Isolation of remnant forest patches, coupled with anthropogenic changes in the surrounding landscape, often leads to changes in the population density of forest-dwelling mammals. At Pasoh Forest Reserve in Peninsular Malaysia, densities of native wild pigs (Sus scrofa) are 10–100 times greater than historical levels due to the local extinction of feline predators and the presence of abundant food sources in areas adjacent to the forest. Female pigs build reproductive nests out of understory vegetation; at Pasoh these nests are constructed primarily of woody saplings several meters tall that pigs snap or uproot, causing substantial local damage. We documented the prevalence of nest building by pigs at Pasoh within a 25-ha area from 1995 to 1998 and investigated the impacts of this mammalian behavior on the understory plant community. In total, 643 pig nests were enumerated, providing an estimate that 6.0 nests·ha−1·yr−1 were constructed in the survey area. Pigs avoided constructing nests adjacent to trails but otherwise built nests throughout the 25-ha survey area. A single pig nest contained, on average, 267 ± 86 (mean ± 1 sd) woody saplings, of which 45% had been uprooted and 55% had the main stem snapped. The understory area affected by the construction of a single pig nest averaged 244 ± 112 m2, with 53% of all free-standing woody plants ≥70 cm tall and <2.0 cm dbh in this area being uprooted or snapped. As a result of nest building, pigs caused an estimated 29% of the observed tree mortality of saplings 1–2 cm dbh, and 43% of sapling mortality and damage combined. Pigs affected plant families differently, with individuals from the economically and ecologically paramount Dipterocarpaceae being about two times more likely to be used in nest construction than other taxa. Our results indicate that pig nest-building activities are a major source of sapling mortality, and that their effects probably will result in substantial shifts in tree community composition in this forest.
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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) | 0.002 | 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".