Spatial and Temporal Perspectives on the Canadian Lake Microbiome
Bibliographic record
Abstract
Lakes are critical freshwater resources and occupy an important place in Canadian culture and recreation. Underpinning lake ecosystems are a broad diversity of microorganisms, which play central roles in regulating water quality, elemental cycles, and food webs. Lakes are increasingly menaced by a range of human pressures which are changing the composition of microbial communities in ways that are challenging to predict, largely because of the immense environmental heterogeneity among lakes at multiple spatial and temporal scales. This dissertation unites spatial and temporal perspectives on the lake microbiome to elucidate its structure, function, and environmental drivers, including human impact. To begin, two studies investigated the contemporary distributions of bacteria and protists using genome-resolved metagenomics and amplicon analyses in over 300 lakes across Canada based on the standardized sampling conducted by the LakePulse Network. For bacteria and protists, lake trophic state and the terrestrial influences of soils and land use – namely, agriculture and human population density – were drivers of taxonomic diversity and various components of microbiome function. The next two studies leveraged sediment DNA archives and paleogenetic techniques to reconstruct the historical diversity and dynamics contextualizing the contemporary lake microbiome. First, metagenome fragment recruitment was used to probe the taxonomic breadth of microorganisms preserved in preindustrial-age sediment records. Small fractions of sediment metagenomes were associated with the preferential preservation of previously undiscovered viruses and bacterioplankton, including lineages with well-characterized ecotypic diversity of paleoindicator potential. Next, multidecadal monitoring and sediment DNA records were compared from the IISD Experimental Lakes Area to evaluate how each of these time series detects eutrophication and climate change signals in lakes with different trophic state histories. Strong congruence was found between algal community turnover in monitoring and sediment records, validating the paleogenetic approach to reconstructing past ecosystem dynamics. While both time series tracked nutrient drivers in fertilized lakes, the 120-year perspective opened by paleogenetics signaled the effects of warming a decade earlier in the continuously fertilized lake than the oligotrophic systems, pointing to synergisms between eutrophication and climate change. Overall, this dissertation shows that the lake microbiome is responding to rising human impact over the past century at a continental scale, notably to effects across the land-water interface and increasingly to a changing climate.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".