Seasonal variation in trophic structure and community niche dynamics of an Arctic coastal community of marine vertebrates
Bibliographic record
Abstract
Temporal variation in food web structure is widespread among highly seasonal environments, such as the Arctic, and is driven by changes in resource availability. Variation in resource availability can lead to species differences in diet composition, isotopic niche width, and trophic position (TP) across seasons. Here, we used tissue samples that represent two distinct turnover rates for diet (liver = shorter term, muscle = longer term) from 18 fish and three marine mammal species to investigate seasonal (i) variation in TPs within the Southampton Island marine ecosystem of Hudson Bay, (ii) variation in consumer isotopic niche width within this part of the food web, and (iii) variation in community niche dynamics among a fish and marine mammal community using stable carbon (δ 13 C) and nitrogen (δ 15 N) isotope analyses. Many zooplanktivores and piscivores increased in TP in summer (i.e., shorter-term turnover period), whereas benthic feeders dependent on ice-obligate prey decreased in TP. Most isotopic niche widths and community metrics (δ 15 N range, total ellipse area, mean centroid distance) were higher in liver than muscle. Our findings demonstrate seasonal changes in TPs, which suggests that Arctic communities may be differentially affected by longer ice-free periods and earlier onset of primary production due to accelerated climate change.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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".