Size fractionated biogeochemical constituents across adjacent coastal systems informs approaches for integrating small catchment studies into regional models
Bibliographic record
Abstract
Abstract Observed and predicted hydrological changes in C‐rich boreal ecosystems have the ability to change the transport trajectory of biogeochemical constituents from the land to ecologically, economically, and culturally important coastal systems. Yet, most of our current understanding of biogeochemical fluxes and cycling across salinity gradients stem from observations of large and urbanized riverine systems, which overlooks the numerically abundant smaller systems. In this study, we conducted a baseline assessment of the biogeochemical constituents across salinity gradients among two adjacent small systems in the boreal zone. Dissolved iron (DFe) and its ratio with dissolved organic carbon (DFe : DOC) were the most sensitive indicators for small catchment heterogeneity. These parameters were the best indicators of change among coastal systems across regional and seasonal scales. Our results also confirm consistencies in common optical measures (SUVA254 and S[275–295/350–400]) and DOC to nitrogen ratios that may adequately provide representation of biogeochemical composition on a regional scale. Simultaneous variation in biogeochemical parameters across particulate and dissolved pools during the summer‐to‐fall transition period indicate this as an important timeframe for targeted investigation of the linkages between biogeochemical parameters and coastal ecosystem functioning. By providing some key spatial and temporal constraints on biogeochemical fluxes among boreal river‐estuaries, our findings indicate that DFe and DFe : DOC ratios should be used to design research aimed at capturing regional and coastal ecosystem scale biogeochemical fluxes to inform Earth System Models.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".