Modeling the costs and benefits of seed scatterhoarding to plants
Bibliographic record
Abstract
Many plants interact with scatterhoarding animals as mutualists (seed dispersers) and antagonists (seed predators) simultaneously, but the net effects of scatterhoarding animals are rarely measured. In seed‐dispersal mutualisms, plant benefits (recruitment) received from dispersal agents should outweigh the costs, resulting in a relative fitness gain. Otherwise, plant populations cannot be sustained and would go extinct. Here we present a framework to quantify costs and benefits of scatterhoarding for animal‐dispersed plants and propose three models with the three separate scales (seed, tree and population) to quantify the costs and benefits for plants from scatterhoarding rodents. Since scatterhoarding is an adaptive dispersal strategy for many large‐seeded plants, tree‐ and population‐based models are needed to determine the costs and benefits for the plants. In the models presented here, all relevant parameters can be measured by regular surveys. Our tree‐ and population‐based models can be extended to seed plants that have dispersal agents other than scatter hoarding rodents.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".