Size Structure of Marine Soft-Bottom Macrobenthic Communities across Natural Habitat Gradients: Implications for Productivity and Ecosystem Function
Bibliographic record
Abstract
Size distributions of biotic assemblages are important modifiers of productivity and function in marine sediments. We investigated the distribution of proportional organic biomass among logarithmic size classes (2(-6)J to 2(16)J) in the soft-bottom macrofaunal communities of the Strait of Georgia, Salish Sea on the west coast of Canada. The study examines how size structure is influenced by 3 fundamental habitat descriptors: depth, sediment percent fines, and organic flux (modified by quality). These habitat variables are uncorrelated in this hydrographically diverse area, thus we examine their effects in combination and separately. Cluster analyses and cumulative biomass size spectra reveal clear and significant responses to each separate habitat variable. When combined, habitat factors result in three distinct assemblages: (1) communities with a high proportion of biomass in small organisms, typical of shallow areas (<10 m) with coarse sediments (<10% fines) and low accumulation of organic material (<3.0 gC/m(2)/yr/δ(15)N); (2) communities with high proportion of biomass in the largest organisms found in the Strait, typical of deep, fine sediments with high modified organic flux (>3 g C/m(2)/yr/δ(15)N) from the Fraser River; and (3) communities with biomass dominated by moderately large organisms, but lacking the smallest and largest size classes, typical of deep, fine sediments experiencing low modified organic flux (<3.0 gC/m(2)/yr/δ(15)N). The remaining assemblages had intermediate habitat types and size structures. Sediment percent fines and flux appear to elicit threshold responses in size structure, whereas depth has the most linear influence on community size structure. The ecological implications of size structure in the Strait of Georgia relative to environmental conditions, secondary production and sediment bioturbation are discussed.
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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 | 0.001 |
| 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".