Facultative feeding and consistency of trophic structure in marine soft-bottom macrobenthic communities
Bibliographic record
Abstract
We investigated the roles of facultative versus strict niche feeding in the maintenance of trophic consistency in soft-bottom macrobenthic communities in the Strait of Georgia, British Columbia, Canada.Changes in trophic structure across gradients in depth and percent fine sediments were examined over a broad regional scale by identifying trophic compartment(s) responsible for the resulting trophic changes.The use of proportional organic biomass data allows direct comparison of community trophic structure across diverse hydrographic regime(s), large ranges in overall biomass and productivity, and highly variable community composition.Cluster analyses revealed low overall dissimilarity in trophic structure across all substrate and depth ranges (24 and 28% divergence, respectively), suggesting an overall economy of trophic function.Similarity percentage (SIMPER) analyses revealed that low trophic dissimilarity is driven primarily by the remarkably even distribution of the 2 dominant facultative feeding groups in all habitat types.These facultative groups contained the most ubiquitous and abundant taxa found throughout the Strait, and likely confer strong resilience in these communities to habitat change.In contrast, the small but significant divergences in trophic structure over depth and percent fine sediment gradients was explained by the distributions of strict niche feeders: (1) macro-omnivores and herbivores dependent on non-detrital food sources were important in shallow areas (< 25 m) with coarse sediments (<10% fine sediment), contributing to a unique trophic composition in these areas; and (2) subsurface deposit feeders were the only trophic group to vary significantly in proportional biomass explained by depth and percent fine sediment combined (22%; positive linear response to both factors).
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".