The influence of logging on vertebrate responses to mast fruiting
Bibliographic record
Abstract
Periods of extreme food abundance, such as irregular masting events, can dramatically affect animal populations and communities, but the extent to which anthropogenic disturbances alter animal responses to mast events is not clear. In South-East Asia, dipterocarp trees reproduce in mast fruiting events every 2-10 years in some of the largest masting events on the planet. These trees, however, are targeted for selective logging, reducing the intensity of fruit production and potentially affecting multiple trophic levels. Moreover, animal responses to resource pulse events have largely been studied in systems where the major mast consumers have been extirpated. We sought to evaluate the influence of human-induced habitat disturbance on animal responses to masting in a system where key mast consumers remain extant. We used motion-triggered camera traps to quantify terrestrial mammal and bird occurrences in Sabah, Malaysian Borneo, relative to variation in fruit biomass from 69 plant families during a major (2014) and minor (2015) masting event and a non-mast year (2013), in both logged and unlogged forests. Bearded pigs (Sus barbatus) showed the clearest responses to masting and occurrence rates were highest in unlogged forest in the year following the major mast, suggesting that the pulse in fruit availability increased immigration or reproduction. We also detected local-scale spatial tracking of dipterocarp fruits in bearded pigs in unlogged forest, while this was equivocal in other species. In contrast, pigs and other vertebrate taxa in our study showed limited response to spatial or temporal variation in fruit availability in logged forest. Our findings suggest that vertebrates, namely bearded pigs, may respond to masting via movement and increased reproduction, but that these responses may be attenuated by habitat disturbance.
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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".