Seasonal dynamics in a nearshore isotopic niche and spatial subsidies from multi-trophic aquaculture
Bibliographic record
Abstract
A poorly understood food web dynamic concerns possible seasonal variation in spatial subsidies associated with multi-trophic aquaculture and their effects on extractive and naturally occurring organisms. We used the stable isotopes δ13C and δ15N and circular statistics to investigate niche overlap across a year-long period at an experimental multi-trophic aquaculture facility in British Columbia, Canada. A two-source mixing model revealed that particulate organic matter was the most important food source for all sample invertebrates (mean range 40%–98%) compared with farm effluent (mean range 3%–35%). There were significant month-to-month changes in δ13C and δ15N for all species except for the brooding transparent tunicate (Corella inflata). We did not detect any directionality for the entire community, but did identify variable directional shifts for each species, suggesting resource partitioning driven by competition and (or) morphology-based differences in feeding strategies. This was further supported by seasonal variation in inter- and intraspecific isotopic niche widths. Isotopic niche overlap among co-occurring invertebrates appeared to be stronger during winter and summer than autumn months. Our study provides valuable insights on the role of multi-trophic derived effluent on a nearshore marine community composed of both natural and cultured species within the same feeding guild.
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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 | 0.001 |
| 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 | 0.001 |
| 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".