Data from: Potential effects of an invasive bivalve, Nuttallia obscurata, on select sediment attributes within the intertidal region of coastal British Columbia
Bibliographic record
Abstract
On the west coast of British Columbia, Canada, the varnish clam, Nuttallia obscurata, is a rapidly spreading invasive species that can reach high densities (i.e. 800 individuals m− 2). A field survey (Tier I) and an in situ mesocosm density manipulation experiment (Tier II) were applied to determine the potential effects of this invasive bivalve on select sediment attributes within the intertidal zone. In situ experiments involved seeding 1 m2 mesocosms with varnish clams at four densities; 0 (control), 200 (low), 500 (mid) and 800 (high). Sediment samples were taken 7 times over a three week period and analyzed for organic matter, ammonium and grain size (gravel, coarse silt, fine silt and silt) at three different depths, 0–3 cm (surface), 3–6 cm (intermediate) and 6–9 cm (bottom). Field surveys demonstrated that at natural densities bivalve distribution was best explained by sediment grain size. Contrary to expectations, the in situ manipulations indicated that at high densities varnish clams did not significantly increase sediment organic matter concentrations. Their ability to deposit feed and re-ingest biodeposits may have prevented accumulations. High densities of varnish clams did however result in significantly higher concentrations of sediment ammonium and percent silt, but mostly within the lower sections of the sediment core. Reworking of the surficial sediments due to intense storm activity likely obscured any differences in determined sediment attributes among the 4 treatments. Nitrogen is a limiting nutrient with ammonium preferentially used by phytoplankton and microphytobenthos. These primary producers form the basis of all marine food webs thus increases in amounts of ammonium to shallow coastal seas as a result of high densities of an invasive bivalve within intertidal zones could result in an increased risk of eutrophication within these sensitive regions.
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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 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.006 | 0.001 |
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".