Investigating marine microbial metabolism and diversity of Arctic ecosystems
Bibliographic record
Abstract
The world’s oceans are essential for sustaining life on Earth and harbour a vast diversity of organisms. Marine microbes play crucial roles in global biogeochemical cycling and are at the base of marine food webs. Due to the technical difficulties associated with sampling northern marine systems, relatively little is known about the microbial community composition and metabolism of these ecosystems. \n \nIn this thesis work, the community composition and metabolism of northern marine ecosystems, including the Saint Lawrence Estuary, North Water and Canada Basin were described using meta-omic techniques. In the Saint Lawrence Estuary, differences in microbial community structure, metabolic lifestyles and carbon and nitrogen processing pathways were observed between the surface and deep waters. In the North Water, two distinct microbial communities with different taxonomic compositions and differing nutrient acquisition and resource allocation strategies were identified on either side of the polar mixed layer, and a third distinct community was described in the bottom waters. Functional and taxonomic analyses of the North Water polar mixed layer communities suggest a microbial community more typically associated with waters that undergo pulses of primary production on the Canadian side, while the community on the Greenland side was more typical of waters associated with a more steady level of primary production. In the Canada Basin, metagenomics was used to construct 360 Arctic Ocean metagenome assembled genomes. The analysis of six Chloroflexi MAGs revealed their potential for terrestrial derived aromatic compound degradation and that this metabolic capacity was acquired, at least in part, by lateral gene transfer from terrestrial organisms. To facilitate the meta-omic analyses performed in this thesis, a novel method to isolate microbial community DNA and proteins from the same environmental sample preserved in RNAlater was also developed. \n \n\tThis thesis not only describes the microbial community composition and metabolism of northern marine systems over a broad geographic range, but also adds to the growing metagenomic and metaproteomic resource-base that can be used to develop and test hypotheses about northern marine microbial systems. Additionally, this work has implications for our understanding of how climate change may affect northern marine 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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".