2D to 3D: Exploring variation of niche dimensionality across consumers in a coastal Arctic ecosystem and implications on interpretation
Bibliographic record
Abstract
Each species occupies a distinct ecological niche, defined by a specific set of environmental conditions and resource requirements necessary for its survival and reproduction. However, climate change is altering species distributions, predator-prey relationships and resource partitioning between species with these changes being pronounced in the Arctic. Stable isotope analysis of carbon (δ¹³C) and nitrogen (δ¹⁵N) has been widely used to estimate isotopic niches and quantify niche overlap among species, a two-dimensional approach (2D). However, δ¹³C is not always sufficient to differentiate habitat and resource use among species due to minimal variation between end-members. Incorporating sulfur stable isotopes (δ³⁴S) can enhance resolution in such cases. Using an Arctic coastal food web as a model system, we used a three-dimensional isotopic niche approach (3D: δ¹³C-δ¹⁵N-δ³⁴S) with 717 individuals across 69 species spanning multiple taxonomic groups (invertebrates, fish, seabirds, and marine mammals) that utilize resources from benthic and pelagic habitats. We compared the traditional 2D isotopic niches with a 3D framework using nicheROVER to assess how the addition of a third dimension changes niche size estimates and probability of niche overlap between species. We found that benthic-associated species, such as common eider (Somateria mollissima) and various benthic invertebrates, exhibited greater changes in isotopic niche size with the addition of δ³⁴S than pelagic-associated species. In addition, niche overlap among benthic-associated taxa decreased with the 3D approach, indicating better resolution of habitat use and resource partitioning. This finding likely reflects the greater ecological diversity, foraging specialization and more complex food web structure characteristic of benthic ecosystems. We recommend incorporating δ³⁴S for aquatic studies that involve benthic habitats and emphasize the value of multidimensional approaches in ecological niche analysis.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".