Palatability and profitability of co‐occurring seeds alter indirect interactions among rodent‐dispersed trees
Bibliographic record
Abstract
Beyond direct species interactions, seed dispersal is potentially affected by indirect seed-seed interactions among co-occurring nut-bearing trees which are mediated by scatter-hoarding animals as shared seed dispersers. A relevant question in such systems is to what extent different functional traits related to food palatability and profitability affect the kinds of indirect interactions that occur among co-occurring seeds, and the consequences for seed dispersal. We used field experiments to track seed dispersal with individually tagged seeds in both monospecific and mixed seed communities. We measured indirect effects based on 3 seed-seed species pairs from the family Fagaceae with contrasting seed size, tannin level, and dormancy in a subtropical forest in Southwest China. When all else was equal, the presence of adjacently placed seeds with contrasting seed traits created different indirect effects measured through a variety of dispersal-related indicators. Apparent mutualism was reciprocal due to increasing seed dispersal in mixed seed patches with mixed differences in seed tannins and dormancy. However, differences in either seed size or dormancy in co-occurring adjacently placed seeds caused apparent competition with reduced seed removal or seed dispersal (distance) in at least one species. Our study supports the hypothesis that different functional traits related to food palatability and profitability in co-occurring seeds modify foraging decisions of scatter-hoarding animals, and subsequently cause indirect effects on seed dispersal among rodent-dispersed trees. We conclude that such indirect effects mediated by shared seed dispersers may act as an important determinant of seed dispersal for co-fruiting animal-dispersed trees in many natural forests.
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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".