Small is the new big: assessing the population structure of microorganisms
Bibliographic record
Abstract
Microorganisms are a tremendously large and diverse group spanning multiple kingdoms, yet they have been considerably under-studied by ecologists and evolutionary biologists compared to their larger relatives. Although a few microbial species have become the stars of laboratory experiments, relatively few studies have examined microbial species in their natural habitats. As such, the question of whether microbial diversity parallels that of larger bodied species is contentious (Lachance 2004; Fenchel & Finlay 2004). It has been suggested that large population sizes, high dispersal potential and low extinction rates lead to genetically homogeneous populations of microbial species over large geographical scales—arguments that bring to mind discussions about speciation and population structure in the marine environment. In this issue of Molecular Ecology, Herrera et al. (2011) add to this debate by examining 91 isolates of the flower-living yeast Metschnikowia gruessii from southeastern Spain. Their AFLP results support both spatial structuring of genetic diversity across the region, as well as microsite-dependent diversifying selection within single flowers. This study adds to a growing body of literature suggesting that although microbes have much larger population sizes and many differ in their principal mode of reproduction (primarily clonal rather than sexual), patterns of genetic diversity and phylogenetic structure for some microbial species may be similar to that of larger species. This study highlights the need for vastly more research that specifically examines biogeographic structure in this under-utilized group of organisms.
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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 | 0.004 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".