Assessing sources and ages of organic matter supporting river and estuarine bacterial production: A multiple‐isotope (Δ14C, 㬔C, and δ15N) approach
Bibliographic record
Abstract
We used radiocarbon (Δ14C) and stable isotopic (Δ13C, Δ15N) signatures of bacterial nucleic acids to estimate the sources and ages of organic matter (OM) assimilated by bacteria in the Hudson River and York River estuary. Dual‐isotope plots of Δ14C and Δ13C coupled with a three‐source mixing model resolved the major OM sources supporting bacterial biomass production (BBP). However, overlap in the stable isotopic (Δ13C and Δ15N) values of potential source end members (i.e., terrestrial, freshwater phytoplankton, and marsh‐derived) prohibited unequivocal source assignments for certain samples. In freshwater regions of the York, terrigenous material of relatively recent origin (i.e., decadal in age) accounted for the majority of OM assimilated by bacteria (49–83%). Marsh and freshwater planktonic material made up the other major source of OM, with 5–33% and 6–25% assimilated, respectively. In the mesohaline York, BBP was supported primarily by estuarine phytoplankton‐derived OM during spring and summer (53–87%) and by marsh‐derived OM during fall (as much as 83%). Isotopic signatures from higher salinity regions of the York suggested that BBP there was fueled predominantly by either estuarine phytoplankton‐derived OM (July and November) or by material advected in from the Chesapeake Bay proper (October). In contrast to the York, BBP in the Hudson River estuary was subsidized by a greater portion (up to ~25%) of old (~24,000 yr BP) allochthonous OM, which was presumably derived from soils. These findings collectively suggest that bacterial metabolism and degradation in rivers and estuaries may profoundly alter the mean composition and age of OM during transport within these systems and before its export to the coastal ocean.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".