An Assessment of Dissolved Organic Carbon Biodegradability and Priming in Blackwater Systems
Bibliographic record
Abstract
Abstract Rivers deliver approximately 260 Tg of dissolved organic carbon (DOC) to the ocean annually, yet there is little evidence of terrigenous DOC (tDOC) in the ocean. While tDOC was historically believed to be stable and resistant to microbial degradation, it has recently been shown that freshwater systems mineralize more tDOC than originally thought. The priming effect is a possible mechanism by which inputs of biolabile DOC enhance the bioavailability of stable DOC components in aquatic systems, resulting in higher rates of microbial remineralization. Here we investigate tDOC biodegradability by conducting bioincubation experiments and utilizing ultrahigh resolution mass spectrometry to characterize the chemical composition of blackwater and leachate dissolved organic matter (DOM) samples. The role of priming in blackwater ecosystems was assessed through the inclusion of bioincubation treatments amended with a variety of simple biolabile OC substrates. Blackwaters lost 6.10 ± 3.85% DOC within 1 month, while leachates lost 38.10 ± 16.74% DOC. There were no significant differences between DOC remineralization in control and primed treatments, indicating that priming is not an important factor in the biodegradation of DOC in blackwater ecosystems. However, the proportion of biodegradable DOC and DOM composition were significantly correlated, mostly driven by the contribution of aliphatic compounds (H/C ≥ 1.5, O/C < 0.9) that were abundant (9.3 ± 5.2%) in leachate DOM. The molecular signature of biodegraded leachate DOM resembled that of stable blackwater DOM, indicating that bioavailable DOM components leached from plant litter are rapidly utilized and stable DOM is exported downstream.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 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 teacher head, 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".