Detrital production in Nova Scotian kelp beds: patterns and processes
Bibliographic record
Abstract
Connectivity via the transport of detrital material from areas of high to low productivity may be an important determinant of secondary productivity and biodiversity in receiving communities. On the Atlantic coast of Nova Scotia, detritus exported from subtidal kelp beds contributes to food webs in communities inhabiting deeper waters offshore. To estimate the amount of energy available via this pathway, we measured rates of detrital production via erosion of kelp blades in kelp beds at 5 sites varying in wave exposure. Specifically, we measured productivity and erosion of the 2 dominant species of kelp, Laminaria digitata and Saccharina longicruris, over 16 mo. We also examined the effect of environmental and biological factors on erosion rates, including temperature, wave exposure, grazing by snails and cover by the invasive bryozoan Membranipora membranacea. We observed clear seasonal and spatial patterns in productivity, with the highest production in spring. Erosion rate was highly variable across sites and seasons, and was strongly related to the cover of M. membranacea and the intensity of snail grazing at the distal end of kelp blades. Both factors cause tissue degradation, abrasions and perforations that weaken blades. Erosion rate was also positively related to water temperature and site exposure. Annual detrital production from the erosion of kelp blades increased linearly with kelp bed biomass, and ranged from 0.5 to 1.71 kg dry weight m -2 (150-513 g C m -2 ) across sites. These rates equal or exceed annual phytoplankton production off the Atlantic coast of Nova Scotia and estimates of detrital production in seagrass beds in North America.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".