Changes in trophic ecology of mobile predators in response to rainforest degradation
Bibliographic record
Abstract
Abstract Accelerating loss and degradation of tropical forests has led to a pressing need to understand the conservation value of remaining forests. Whereas most studies focus on the responses in community composition and taxonomic richness, more sensitive responses to habitat degradation are likely to be apparent through changes in the trophic complexity of generalist predators. Food web theory predicts that both trophic position and niche breadth of predators decrease with habitat degradation, with consequences for biotic interactions and ecosystem functioning. Using a stable isotope approach, we analysed trophic positions and niche breaths of an important guild of top predators: insectivorous bats, in the tropical forests of Sabah, Borneo. We aimed to determine the responses in their trophic ecology across an experimental gradient of forest degradation at different spatial scales. At the landscape scale, trophic niche breadth contracted substantially (78%) in association with a narrow reduction (26%) in forest cover. However, food chains were longer in ecosystems with lower tree canopies, representative of localised habitat simplification. Marked differences in trophic niche breath of and trophic position between echolocation guilds provided further evidence for inter‐guild niche partitioning within bat assemblages. Overall, the functionally important shifts in trophic pathways discriminated among habitats of varying degrees of degradation more reliably than conventional community descriptors, such as diversity metrics. Synthesis and applications. This study reveals that habitat quality thresholds—below which we see substantial changes to trophic complexity—are higher than previously considered. Our analysis suggests that patches of forest with cover above 90% should be prioritised for conservation over more highly degraded ecosystems. As these effects were detected after approximately 30 years post‐logging, they likely reflect relatively long‐term responses to forest degradation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".