Patterns of prokaryotic diversity in freshwaters across the circumpolar region
Bibliographic record
Abstract
Northern freshwater ecosystems face a wide range of environmental changes, including climate change, eutrophication, and browning. In Arctic regions, climate warming is occurring nearly four times faster than the global average, leading to higher water temperatures, shorter ice-cover periods, and extended growing seasons for aquatic biota. These changes are expected to have both direct and indirect impacts on these ecosystems, including the microbial communities that underpin their biodiversity and functioning. Building on prior research by the authors, we tested the hypothesis that microbial communities, particularly prokaryotes (bacteria and archaea), exhibit similarities across circumpolar freshwater systems. To investigate this, we surveyed 46 lakes and 30 streams between 2019 and 2022 in Arctic (>70º N) and sub-Arctic (55–70º N) regions spanning Alaska, Canada, Greenland, Norway (including Svalbard), and Sweden. For each waterbody, we collected environmental DNA (eDNA) for 16S rRNA gene metabarcoding and water samples to analyze physical and chemical parameters (temperature, pH, electrical conductivity, and dissolved O2), major ions, and nutrients (organic C, P, and N).Bacteria predominantly represented the main prokaryotic group in this study, with archaeal contributions limited to a few lakes in Svalbard and the Canadian Northwest Territories. Our results revealed that latitude (i.e., Arctic vs. sub-Arctic locations) strongly determined community composition (p = 0.001; pseudo-F = 2.634), whereas the type of waterbody (i.e., lakes vs. streams) had a weaker influence on beta diversity (p = 0.012; pseudo-F = 1.813). Latitude, along with water temperature and dissolved O2, were the main explanatory variables shaping prokaryotic community composition in our study. The core microbiome differed significantly in abundance between Arctic and sub-Arctic locations (p = 0.005). Arctic freshwaters showed the highest alpha diversity (Shannon and Chao1 indices) and were dominated by the genera Rhodoferax, Arcicella, and Polaromonas, all of which positively correlated with increasing dissolved O2 concentrations. In contrast, sub-Arctic freshwaters were primarily dominated by Limnohabitans, a genus widely distributed in inland freshwater habitats. Regarding waterbody types, lakes were predominantly characterized by Flavobacterium, which positively correlated with increasing nutrient concentrations, and exhibited higher alpha diversity compared to streams. Streams, in turn, were largely dominated by Rhodococcus species, which showed significant positive correlations with water temperature. This study enhances our understanding of prokaryotic diversity across the circumpolar region and aims to further provide valuable insights into the assembly mechanisms of freshwater microbial communities.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".