Gradients in the time seeds take to germinate could alter global patterns in predation strength
Bibliographic record
Abstract
Abstract Aim Species interactions are predicted to become stronger toward low latitudes and elevations, and these predictions have been supported in large experiments measuring daily predation rates on early life‐stages. However, the overall strength and importance of predation depend on both the daily risk of being attacked and how long prey are exposed, and gradients in exposure time are rarely quantified. Here, we test whether time‐to‐germination, which determines seeds' exposure to post‐dispersal attack, is faster in high‐predation environments: low latitudes, low elevations, and warmer wetter climates. Location Global data synthesis. Taxon Angiosperms. Methods We synthesized data on time‐to‐germination from 1410 plant species spanning 118° latitude. We divided data by study environment (lab, greenhouse, garden, nature), as we predicted different patterns depending on whether seeds experienced only intrinsic versus intrinsic + extrinsic germination cues. We tested how mean days‐to‐germination varied with geography (latitude, elevation) and climate (annual mean and seasonality of temperature and precipitation). We also explored whether patterns could be explained by seed size or phylogeny, which vary latitudinally. Results Seeds germinated faster toward higher latitudes across study environments but slower toward higher elevations when experiencing intrinsic + extrinsic germination cues (in nature). Germination was faster in drier, more seasonal and—when tested in nature—warmer environments. Seed size explained some latitudinal variation in time‐to‐germination, whereas accounting for phylogeny did not improve predictions. Germination was slower in natural versus lab environments. Main Conclusions We found little evidence that seeds have commonly evolved faster germination in high‐predation environments. While time‐to‐germination varied with geography and climate, patterns were inconsistent among predictors, and were weaker than those reported for daily seed predation rates. Detected gradients in time‐to‐germination would partially counter elevational gradients in daily seed predation rates but exacerbate latitudinal gradients in predation rates, such that tropical seeds likely experience much stronger lifetime predation risk than high‐latitude seeds.
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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 | 0.001 |
| 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) | 0.002 | 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".