GEB2020_data.xlsx
Bibliographic record
Abstract
This data set corresponds to the study published in Global Ecology and Biogeography entitled: “Latitudinal variation in plant defense against herbivory in a marine foundation species does not follow a linear pattern: the importance of resource availability” We conducted experiments simulating macroherbivore (e.g., bird, fish) damage in Zostera marina at 10 sites across the Eastern Pacific coast (Canada-Mexico) and Quebec and analyzed several seagrass traits related to resistance and tolerance strategies against herbivory. In addition, we examined the effects of potential seagrass changes in defense strategies by performing a series of feeding experiments with mesoherbivores in a subset of sites. We found that eelgrass resistance defenses did not follow a linear latitudinal pattern but rather followed a bell-shaped curve which correlated with bottom-up control. In sites with higher nutrient availability, plants allocated resources to tolerance strategies and had lower resistance traits. Furthermore, seagrasses did not respond linearly to increased herbivory pressure; while they tolerated moderate levels of herbivory, they underwent a significant reduction in tolerance and resistance under high herbivory levels, which also made them more susceptible to consumers in feeding experiments. Our results highlight the importance that nutrient availability has in shaping latitudinal patterns of plant defense against herbivory and show how these defenses may not respond linearly to increased herbivory pressure in seagrasses.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.008 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.004 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.003 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.364 | 0.219 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".