AN EXPERIMENTAL TEST OF LOCAL ADAPTATION IN SOIL BACTERIA
Bibliographic record
Abstract
We extracted bacterial isolates of similar colony morphology from spatially located soil samples within 1 ha of old-growth forest. The same soil samples were used to prepare growth medium. Each isolate was then cultured in each medium and its growth recorded. There was no overall tendency for isolates to grow more successfully in their home site (i.e., the medium derived from the soil sample from which they had been extracted). Most isolates grew very poorly, however, and when the analysis was restricted to the minority of vigorous isolates there was clear evidence of local adaptation: isolates tended to grow better at their home site than did isolates from elsewhere and grew better at their home site than they did at other sites. The variation of growth within the 1-ha plot made up a complex fitness landscape of peaks, ridges, and valleys. Most of the vigorous isolates were found at or near a local fitness (growth) peak, although seldom at a global peak. In consequence, there was a tendency for growth to diminish away from the home site. The home isolate was about 50% more fit than average at its home site; fitness diminished exponentially away from the home site at a rate of 0.0577 per meter. These figures are similar to those previously reported for plants. This selection gradient has matched the bacterial assemblage to the edaphic structure of the environment, although the fit is far from perfect.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".