Role of nitrogen cycling functional genes and their key influencing factors in eutrophic aquatic ecosystems
Bibliographic record
Abstract
The nitrogen cycle, essential for the transformation and circulation of nitrogen, involves key processes such as nitrogen fixation, nitrification, denitrification, and ammonification. Microorganisms are crucial in these processes, influencing water quality through energy conversion and nitrogen cycling. Eutrophication, driven by human activities, increases exogenous nitrogen input, accelerating nitrogen cycling and loss, boosting greenhouse gas emissions, and impacting aquatic ecosystems. Functional genes in the nitrogen cycle, such as amoA (nitrification), nirS, nirK, nosZ (denitrification), and hzs and hzo (anaerobic ammonium oxidation), are indicators of nitrogen transformation in sediments. Environmental factors like temperature, dissolved oxygen (DO), organic matter content, nitrogen levels, pH, and salinity significantly influence these genes' expression and regulation. For example, temperature changes can affect nitrifying and denitrifying bacteria activities, DO levels impact microbial growth and metabolism, and higher organic matter content stimulates the expression of nitrogen cycle genes. Understanding how these environmental factors affect nitrogen cycling genes is crucial for addressing eutrophication in aquatic ecosystems. This review focuses on the adaptability and responses of nitrogen-associated functional microorganisms and genes environmental changes, offering theoretical insights and practical guidance for sustainable ecosystem management.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 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".