Exploring the Ecological Coherence between the Spatial and Temporal Patterns of Bacterioplankton in Boreal Lakes
Bibliographic record
Abstract
One of the major contemporary challenges in microbial ecology has been to discriminate the reactive core from the random, unreactive components of bacterial communities. In previous work we used the spatial abundance distributions of bacterioplankton across boreal lakes of Québec to group taxa into four distinct categories that reflect either hydrology-mediated dispersal along the aquatic network or environmental selection mechanisms within lakes. Here, we test whether this categorization derived from the spatial distribution of taxa is maintained over time, by analyzing the temporal dynamics of the operational taxonomic units (OTUs) within those spatially derived categories along an annual cycle in the oligotrophic lake Croche (Québec, Canada), and assessing the coherence in the patterns of abundance, occurrence, and environmental range of these OTUs over space and time. We report that the temporal dynamics of most taxa within a single lake are largely coherent with those derived from their spatial distribution over large spatial scales, suggesting that these properties must be intrinsic of particular taxa. We also identified a set of rare taxa cataloged as having a random occupancy based on their spatial distribution, but which showed clear seasonality and abundance peaks along the year, yet these comprised a very small fraction of the total rare OTUs. We conclude that the presence of most rare bacterioplankton taxa in boreal lakes is random, since both their temporal and spatial dynamics suggest links to passive downstream transport and persistence in freshwater networks, rather than environmental selection.
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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".