Long‐term seed survival and dispersal dynamics in a rodent‐dispersed tree: testing the predator satiation hypothesis and the predator dispersal hypothesis
Bibliographic record
Abstract
Summary Mast seeding in animal‐dispersed plants has previously been accounted for by two main hypotheses: the predator satiation hypothesis (that it increases seed survival and establishment before dispersal) and the predator dispersal hypothesis (that it increases seed dispersal or dispersal distance). However, neither hypothesis has been rigorously tested with simultaneous data on seed production, seed predation and seed dispersal by vertebrate seed predators. We studied oil tea C amellia oleifera ( T heaceae) seed production for eight years (2002–2009) in a subtropical forest in south‐west C hina, and investigated how annual seed and rodent abundance determined per capita seed availability for rodent seed predators and seed dispersers and how seed and rodent abundance were related to seed dispersal and seed survival via scatter‐hoarding. We predicted the patterns of seed dispersal and survival to test the two hypotheses about mast seeding. Edward's long‐tailed rat L eopoldamys edwardsi acted as the principal seed disperser of oil tea seeds because of scatter‐hoarding, while other sympatric rodent species acted only as seed predators. We first provided a reasonable method to estimate per capita seed availability based on annual seed abundance and annual metabolic rodent abundance (corrected for metabolic‐scaling body mass of each rodent species). We found that annual seed abundance, annual metabolic rodent abundance and per capita seed availability all had some significant effects on different estimators of seed fates (including dispersal distances) across each stage from seedfall to seedling establishment. Both annual seed abundance and per capita seed availability were positively correlated with pre‐dispersal seed survival, but negatively correlated with scatter‐hoarding (and recaching), seed survival after dispersal and dispersal distances. However, annual metabolic rodent abundance had a positive effect on scatter‐hoarding, but had a negative effect on the time to cache recovery. Synthesis . Since greater seed production was associated with improvement in pre‐dispersal survival of oil tea seeds but a reduction in dispersal (including secondary dispersal and dispersal distance), our long‐term study indicates that, compared with the predator dispersal hypothesis, the predator satiation hypothesis provides a better mechanism predicting seed dispersal and seed survival in animal‐dispersed plants by integrating seed abundance and animal abundance.
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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 | 0.001 |
| 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 | 0.001 |
| 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".