The effects of N:P ratio and nitrogen form on four major freshwater bacterial taxa in biofilms
Bibliographic record
Abstract
Bacteria in freshwater systems play an important role in nutrient cycling through both assimilatory and dissimilatory processes. Biotic and abiotic components of the environment affect these transformations as does the stoichiometry of the nutrients. We examined responses of four major taxa of bacteria in biofilms subjected to various N:P molar ratios using either nitrate or ammonium as a nitrogen source. Fluorescent in situ hybridization was used to enumerate the Domain bacteria as well as the alpha-, beta-, and gamma-proteobacteria, and the Cytophaga-Flavobacteria cluster. Generally, bacterial responses to the treatments were limited. However, the Cytophaga-Flavobacteria and beta-proteobacteria both responded more to the ammonium additions than nitrate, whereas, the alpha-proteobacteria responded more to nitrate additions. The beta-proteobacteria also exhibited peak relative abundance at the highest N:P ratio. Nutrient concentrations were significantly different after the incubation period, and there were distinct changes in the stoichiometry of the microcosms with ammonium. We demonstrated that bacteria may play an important role in nutrient uptake, and transformation, and can have a dramatic effect on the nutrient stoichiometry of the surrounding water. However, although some taxa exhibited differences in response to ammonium and nitrate, the impact of nutrient stoichiometry on the abundance of the taxa examined was limited.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".