Density‐dependent resource selection by a terrestrial herbivore in response to sea‐to‐land nutrient transfer by seals
Bibliographic record
Abstract
Abstract Sea‐to‐land nutrient transfers can connect marine food webs to those on land, creating a dependence on marine webs by opportunistic species. We show how nitrogen, imported by gray seals, Halichoerus grypus , and traced through stable isotope (δ 15 N) measurements in marram grass , Ammophila breviligulata , significantly alters foraging behavior of a free‐roaming megaherbivore (feral horses, Equus ferus caballus ) on Sable Island, Canada. Values of δ 15 N correlated with protein content of marram and strongly related to pupping‐seal densities, and positively influenced selective foraging by horses. The latter was density dependent, consistent with optimal foraging theory. We present the first demonstration of how sea‐to‐land nutrient transfers can affect the behavioral process of resource selection (resource use relative to availability) of terrestrial consumers. We hypothesize that persistence of horses on Sable Island is being facilitated by N subsidies. Our results have relevance to advancing theory on trophic dynamics in island biogeography and metaecosystem ecology.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.002 | 0.002 |
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; both teacher heads 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".