Towards Predicting Basin-Wide Invertebrate Organic Biomass and Production in Marine Sediments from a Coastal
Bibliographic record
Abstract
Detailed knowledge of environmental conditions is required to understand faunal production in coastal seas with topographic and hydrographic complexity. We test the hypothesis that organic biomass and production of subtidal sediment invertebrates throughout the Strait of Georgia, west coast of Canada, can be predicted by depth, substrate type and organic flux modified to reflect lability and age of material. A basin-wide database of biological, geochemical and flux data was analysed using an empirical production/biomass (P/B) model to test this hypothesis. This analysis is unique in the spatial extent and detail of P/B and concurrent environmental measurements over a temperate coastal region. Modified organic flux was the most important predictor of organic biomass and production. Depth and substrate type were secondary modifiers. Between 69–74 % of variability in biomass and production could be explained by the combined environmental factors. Organisms,1 mm were important contributors to biomass and production primarily in shallow, sandy sediments, where high P/B values were found despite low organic flux. Low biomass, production, and P/B values were found in the deep, northern basin and mainland fjords, which had silty sediments, low organic flux, low biomass of organisms,1 mm, and dominance by large, slow-growing macrofauna. In the highest organic flux and biomass areas near the Fraser River discharge, production did not increase beyond moderate flux levels. Although highly productive, this area had low P/B. Clearly, food input is insufficient to explain the complex patterns in faunal production revealed here. Additional
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".