Strong coupling between natural Planctomycetes and changes in the quality of dissolved organic matter in freshwater samples
Bibliographic record
Abstract
Dilution-regrowth experiments coupled to fluorescence in situ hybridization were conducted with samples from two humic reservoirs in order to examine how inorganic nutrients (N, P) affect free-living bacterioplankton phylogenetic groups and subsequently the quality of dissolved organic matter (DOM). The experiments were complemented by analyses of the empirical relationships between the targeted bacteria, nutrients, DOM and grazers. The ratio of absorbance of waters (A) at 250 and 365 nm (A(250 nm):A(365 nm)), which has been found to increase with the proportion of small molecules in the DOM pool in other humic waters, was used as an index of DOM quality. When nutrient stimulated bacteria, both the responses of bacterial groups (in the absence of grazers) and the ratio A(250 nm):A(365 nm) were generally different between treatments (+N, +P, +NP), suggesting that in nutrient-poor systems, differences in the type of inorganic nutrient supply will ultimately cause differences in DOM quality. The ratio A(250 nm),:A(365 nm) peaked in the +N treatments where members of the Planctomycetes (PLA) were the most stimulated group, and across treatments, PLA best explained (positive relationship) variations in this ratio. Consistent with this, the in situ data showed that the removal of the negative effects of flagellates on PLA yielded the highest R(2) in attempts to use bacterial groups to explain variations in A(250 nm):A(365 nm). These findings provide lines of evidence, not previously demonstrated in natural waters, that Planctomycetes may be an important factor changing the DOM quality, particularly in nutrient-poor systems when supplied with inorganic N.
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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 | 0.000 |
| Science and technology studies | 0.000 | 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".