Examining the impact of agricultural drainage ditch management on in-stream bacterial communities involved in nitrogen cycling: insights from the Environmental Change One Health Observatory (ECO2)
Bibliographic record
Abstract
Introduction Agricultural drainage ditches are essential for maintaining flow efficiency and are often managed by brushing (i.e., vegetation clearing along ditch banks) and dredging. These maintenance practices not only impact flow but also the ditches’ capacity to process and assimilate agricultural chemicals. However, the influence of ditch management on microbial activities, essential in processing and transforming these contaminants, remains underexplored. Methods We conducted a four-year surface water sampling campaign in two long-established (over 40 years) agricultural drainage ditches situated in eastern Ontario, Canada. One drainage ditch underwent intensive bank brushing and channel dredging, while the other remained unmanaged. We assessed the impact of these contrasting ditch management practices on the diversity and compositional structure of surface water microbiome communities, with a particular focus on the distribution of genes associated with nitrogen (N) cycling, using shotgun metagenomics sequencing and an assembly-based metagenome approach. Results and discussion From 117 surface water samples, we reconstructed 157 metagenome-assembled genomes (MAGs), predominantly from the Patescibacteria superphylum. Brushing alone, conducted about 10 months prior to dredging, had an insignificant impact on the aquatic microbial community. However, dredging led to a significant reduction in community diversity and abundance of genes affiliated with denitrification, dissimilatory nitrate reduction to ammonia, and complete nitrification through comammox. Ditch management resulted in noticeable shifts in the microbial community, evidenced by the enrichment of taxa in Polaromonas , Emticicia , Flectobacillus , and Patescibacteria in the water of the managed ditch sites. The metagenomes of these taxa harbor genes involved in various nitrogen biotransformation pathways. Interestingly, following dredging, the levels of ammonia and ammonium, nitrite, and total Kjeldahl N in the managed ditch did not increase, but significantly decreased; likely due to ditch substrate removal and potentially increased flow efficiency and dilution. Being one of the few studies conducted to date, this study provided unique insights into the consequences of drainage ditch management on freshwater microbiomes involved in N cycling.
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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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".