Effects of small rivers on chemical properties of sediment and diets for primary consumers in estuarine tidal flats
Bibliographic record
Abstract
We compared effects of particulate organic matter (POM) transported from small rivers (POM R ) on chemical properties of sediment and diets of primary consumers in 3 estuarine tidal flats with different watershed characteristics in southwestern British Columbia, Canada.The source rivers (0.1 to 1.9 m 3 s -1 , annual mean) flowed through forested and urbanized areas (FR) or through agricultural areas (AG1 and AG2).The C:N ratio of POM R was significantly higher in FR (8.6 to 10.1) than in AG1 and AG2 (6.7 to 7.0).The chlorophyll a concentration of river water was significantly lower in FR (0.4 µg l -1 ) than in AG1 and AG2 (9.4 to 10.3 µg l -1 ).In the tidal flat of FR, organic matter of sediment (SPOM) had relatively higher C:N ratios (FR, 17.9; AG1, 9.6 and AG2, 8.2), suggesting the accumulation of terrestrial organic matter.Mixing model (IsoSource) calculations based on stable isotope measurements showed that in the tidal flat of FR, POM R was dominant in SPOM (~70%), also suggesting POM R was an important food source for some primary consumers (37 to 48%) as were benthic microalgae (35 to 45%).In AG1 and AG2, POM R did not dominate SPOM, and there was no evidence of significant incorporation of POM R into macrobenthos diets.In the present study, POM R from the watershed with substantial forest areas appeared to be more influential on the chemical properties of sediment and macrobenthos diets in the tidal flat.This could be attributed to the low degradability and long retention of POM R in the tidal flat sediments.
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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 | 0.000 | 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) | 0.000 | 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".