Seasonal dynamics of methanotrophic bacteria in a boreal oil sands end-pit lake
Bibliographic record
Abstract
Base Mine Lake (BML) is the first full-scale demonstration end pit lake for the oil sands mining industry in Canada. We examined aerobic methanotrophic bacteria over all seasons for five years in this dimictic lake. Methanotrophs comprised up to 58% of all bacterial reads in 16S rRNA gene amplicon sequencing analyses (median 2.8%), and up to 2.7 × 104 cells mL−1 of water (median 0.5 × 103) based on qPCR of pmoA genes. Methanotrophic activity and populations in the lake water were highest during fall turnover, and remained high through the winter ice-covered period into spring turnover. They declined during summer stratification, especially in the epilimnion. Three methanotroph genera (Methylobacter, Methylovulum, and Methyloparacoccus) cycled seasonally, based on both relative and absolute abundance measurements. Methylobacter and Methylovulum populations peaked in winter/spring, when methane oxidation activity was psychrophilic. Methyloparacoccus populations increased in the water column through summer and fall, when methane oxidation was mesophilic, and also predominated in the underlying tailings sediment. Other, less abundant genera grew primarily during summer, possibly due to distinct CH4/O2 microniches created during thermal stratification. These data are consistent with temporal and spatial niche differentiation based on temperature, CH4 and O2. This pit lake displays methane cycling and methanotroph population dynamics similar to natural boreal lakes. Importance statement: The study examined methanotrophic bacteria in an industrial end pit lake, combining molecular DNA methods (both quantitative and descriptive) with biogeochemical measurements. The lake was sampled over 5 years, in all four seasons, as often as weekly, and included sub-ice samples. The resulting multi-season and multi-year dataset is unique in its size and intensity, and allowed us to document clear and consistent seasonal patterns of growth and decline of three methanotroph genera (Methylobacter, Methylovulum, and Methyloparacoccus). Laboratory experiments suggested that one major control of this succession was niche partitioning based on temperature. The study helps to understand microbial dynamics in engineered end-pit lakes, but we propose that the dynamics are typical of boreal stratified lakes, and widely applicable in microbial ecology and limnology. Methane oxidising bacteria are important model organisms in microbial ecology, and have implications for global climate change.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".