Annual nitrification dynamics in a seasonally ice-covered lake
Bibliographic record
Abstract
We investigated the variability in ammonia oxidation (AO) rates and the presence of ammonia-oxidizing archaea and bacteria (AOB and AOA) over an annual cycle in the water column of a small, seasonnally ice covered, temperate shield lake. AO, the first step of nitrification, was measured in situ using 15N-labelled ammonium (NH4+) at 1% and 10% of photosynthetic active radiation during day and at the same depths during night. AO was active across seasons and light levels, ranging from undetectable to 333 nmol L-1 d-1 with peak activity in winter under ice cover. NH4+ concentration was the single most important positive predictor of AO rates. High NH4+ concentrations and reduced chlorophyll a concentrations under ice, which favoured AO, were coherent with high nitrate concentrations and super saturation in nitrous oxide. When targeting the ammonia monooxygenase (amoA) gene in samples from the photic zone, we found AOA to be omnipresent throughout the year while AOB were observed predominantly during winter. Our results demonstrate that AO is an ongoing process in sunlit surface waters of temperate lakes and at all seasons with pronounced nitrification activity observed during winter under ice. The combination of high NH4+ concentrations due to fall overturn, reduced light availability that limited phytoplankton competition, and the presence of AOB together with AOA apparently favoured these elevated rates under ice. We suggest that lake ice could be a control point for nitrification in oligotrophic temperate shield lakes, characterized as a moment and place that exerts disproportionate influence on the biogeochemical behaviour of ecosystems.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 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".