Do Collared Peccaries Negatively Impact Understory Insectivorous Rain Forest Birds Indirectly Via Lianas and Vines?
Bibliographic record
Abstract
Abstract Tropical rain forest understory insectivorous birds are declining, even in large forest reserves, yet the mechanisms remain unclear. Abundant large mammals can reshape forest structure, which degrades foraging microhabitat. We used six sites in Nicaragua, Costa Rica, and Panama with varying collared peccary ( Pecari tajacu ) density to test three linked hypotheses: (1) locally declining understory insectivores forage preferentially in liana tangles; (2) vine and liana density, cover, and frequency of dense tangles are lower in the presence of abundant collared peccaries; and consequently (3) abundant collared peccaries are associated with reduced understory insectivorous bird abundance. Three insectivores that declined at La Selva preferentially foraged in liana tangles: Checker‐throated Antwren ( Epinecrophylla fulviventris ), Dot‐winged Antwren ( Microrhopias quixensis ), and Ruddy‐tailed Flycatcher ( Terenotriccus erythrurus ). Vine density, liana cover, liana tangle frequency, and forest cover were lower in the presence of collared peccaries relative to experimental mammal exclosures, with the greatest differences at La Selva Biological Station, Costa Rica. Across sites, five of seven vine and liana measures showed negative, curvilinear relationships with peccary densities. Vine and liana measures peaked at sites with intermediate peccary density, and were low at La Selva. Structural equation models suggest negative indirect effects of the collared peccaries on focal bird densities, mediated by vine and liana density, cover, or tangle frequency. Forest area and rainfall affected both lianas and birds, but collared peccaries also contributed to the reduced abundance of understory insectivores. Indirect effects such as that suggested here may occur even in large, protected forest reserves where large mammal communities are changing.
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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 | 0.001 |
| 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 | 0.001 | 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 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".