Interspecific differences in feeding selectivity shape isotopic niche structure of three ophiuroids in the Arctic Ocean
Bibliographic record
Abstract
Understanding the mechanisms that support feeding interactions and species co-occurrence in regions subject to rapid environmental changes is becoming increasingly important to predict future trends in population dynamics. However, there is still little information available on the trophic ecology for many benthic species to help us better understand trophic interactions and individual trophic roles. Here, we used stable isotopes (δ13C, δ15N) in conjunction with the Bayesian ellipses approach to explore spatial trends in isotopic niche width and overlap of 3 syntopic arctic brittle stars (Echinodermata: Ophiuroidea; Ophiacantha bidentata, Ophiocten sericeum, and Ophiopleura borealis) in Baffin Bay (BB), the Canadian Arctic Archipelago (CAA), and the North Water Polynya (NOW). These 3 coexisting ophiuroids displayed great interspecific plasticity in foraging behaviors and showed a high degree of inter-individual dietary flexibility. However, differences in surface carbon composition drove the variability of resource utilization at the individual level across stations, which in turn affected trophic interactions, niche overlaps, and isotopic niche breadth of ophiuroids. Greater niche overlap was found in the highly productive region of the NOW, where consumers exhibited similar food selectivity, whereas an increase in niche segregation occurred in regions with greater sea-ice concentration. These results suggest that isotopic niche size reflects individual responses to fluctuations in food availability and possibly past competition, both induced by local oceanographic features. Our study indicates that niche parameters of ophiuroids can respond quickly to ecological and environmental gradients, which suggests an important adaptability of these species facing multiple stressors.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".