Latitude, temperature, and habitat complexity predict predation pressure in eelgrass beds across the Northern Hemisphere
Bibliographic record
Abstract
Latitudinal gradients in species interactions are widely cited as potential causes or consequences of global patterns of biodiversity. However, mechanistic studies documenting changes in interactions across broad geographic ranges are limited. We surveyed predation intensity on common prey (live amphipods and gastropods) in communities of eelgrass (Zostera marina) at 48 sites across its Northern Hemisphere range, encompassing over 37° of latitude and four continental coastlines. Predation on amphipods declined with latitude on all coasts but declined more strongly along western ocean margins where temperature gradients are steeper. Whereas in situ water temperature at the time of the experiments was uncorrelated with predation, mean annual temperature strongly positively predicted predation, suggesting a more complex mechanism than simply increased metabolic activity at the time of predation. This large-scale biogeographic pattern was modified by local habitat characteristics; predation declined with higher shoot density both among and within sites. Predation rates on gastropods, by contrast, were uniformly low and varied little among sites. The high replication and geographic extent of our study not only provides additional evidence to support biogeographic variation in predation intensity, but also insight into the mechanisms that relate temperature and biogeographic gradients in species interactions.
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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 | 0.000 |
| 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".