Defaunation and habitat disturbance interact synergistically to alter seedling recruitment
Bibliographic record
Abstract
Vertebrate granivores destroy plant seeds, but whether animal-induced seed mortality alters plant recruitment varies with habitat context, seed traits, and among granivore species. An incomplete understanding of seed predation makes it difficult to predict how widespread extirpations of vertebrate granivores in tropical forests might affect tree communities, especially in the face of habitat disturbance. Many tropical forests are simultaneously affected by animal loss as well as habitat disturbance, but the consequences of each for forest regeneration are often studied separately or additively, and usually on a single plant demographic stage. The combined impacts of these threats could affect plant recruitment in ways that are not apparent when studied in isolation. We used wire cages to exclude large (elephants), medium, (sambar deer, bearded pigs, muntjac deer), and small (porcupines, chevrotains) ground-dwelling mammalian granivores and herbivores in logged and unlogged forests in Malaysian Borneo. We assessed the interaction between habitat disturbance (selective logging) and experimental defaunation on seed survival, germination, and seedling establishment in five dominant dipterocarp tree species spanning a 21-fold gradient in seed size. Granivore-induced seed mortality was consistently higher in logged forest. Germination of unpredated seeds was reduced in logged forest and in the absence of small to large-bodied mammals. Experimental defaunation increased germination and reduced seed removal but had little effect on seed survival. Seedling recruitment however, was more likely where logging and animal loss occurred together. The interacting effects of logging and hunting could therefore, actually increase seedling establishment, suggesting that the loss of mammals in disturbed forest could have important consequences for forest regeneration and composition.
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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 | 0.001 | 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 | 0.001 |
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".