Patterns of Local Adaptation in Space and Time among Soil Bacteria
Bibliographic record
Abstract
Our understanding of microbial biogeography has been governed by the dictum "Everything is everywhere, but the environment selects." In other words, the distribution of microbes is thought to occur in a regime of extensive dispersal and strong selection, generating local adaptation. However, direct tests of these assumptions are rare. Here, we investigate the extent of local adaptation in space and time of a collection of soil-derived microbial isolates, most belonging to the genus Pseudomonas, across a growing season from a deciduous forest in western Quebec, Canada, using a reciprocal transplant design. Average performance of all clones varied substantially in both space and time, in line with the expectation of strong selection in both dimensions. The behavior of genotype-by-environment variance in fitness and its components, responsiveness and inconsistency, in space and through time suggests that the strength of divergent selection increases as sites become more distant from each other in both dimensions. However, divergent selection was not strong enough to maintain different specialized types across the environments studied, which suggests that Pseudomonas and their close relatives are not locally adapted to the prevailing conditions of growth.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 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".