Rain-fed streams dilute inorganic nutrients but subsidise organicmatter-associated nutrients in coastal waters of the northeast PacificOcean
Bibliographic record
Abstract
Abstract. In coastal regions, rivers and streams may be important sources of nutrients limiting to primary production in marine waters; however, sampling is still only rarely conducted across the land-to-ocean aquatic continuum, precluding conclusions from being drawn about connectivity between freshwater and marine systems. Here we use a more than four year dataset (2014–2018) of nutrients (nitrogen, phosphorus, silica, iron) and dissolved organic carbon spanning streams draining coastal watersheds and nearshore marine surface waters along the Central Coast of British Columbia Canada, at the heart of the North Pacific coastal temperate rainforest region. Mean freshwater and surface marine N : Si : P ratios were 4 : 18 : 1 (P : Fe = 1 : 58) and 6 : 11 : 1, respectively, showing relative consistency across the land-ocean interface but deviation from the extended Redfield ratio. Inorganic nutrient concentrations (NO3−+NO2−, PO43−, Si(OH)4) in freshwaters were less than in the receiving marine environment, indicating that freshwater nutrient inputs in this region were of little importance to – or even diluted – the pool of readily available inorganic nutrients in nearshore waters. Conversely, freshwaters increased the pool of organic matter-associated nutrients, namely dissolved organic nitrogen and iron. The organic matter-rich landscapes of the region yielded globally significant quantities of dissolved organic nitrogen (304–381 kg km−2 y−1) and iron (463–596 kg km−2 y−1); thus acting as important sources of potentially limiting nutrients to both nearshore and offshore waters. These exports may subsidise heterotrophic microbial communities capable of directly consuming and remineralising these nutrients, potentially compensating for the dilution of inorganic nutrients by freshwater inputs. We highlight the need to better understand nutrient limitation in coastal waters and for concerted research efforts to study the spatial and temporal dynamism at the land-ocean interface along the northeast Pacific coast.
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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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".