Habitat Association in Two Genetic Groups of the Insect-Pathogenic Fungus<i>Metarhizium anisopliae</i>: Uncovering Cryptic Species?
Bibliographic record
Abstract
Strains of insect-pathogenic fungi with high virulence toward certain pest insects have great potential for commercial biological control applications. Identifying such strains has been a central theme in using fungi for biological control. This theme is supported by a persistent paradigm in insect pathology which suggests that the host insect is the predominant influence on the population genetics of insect-pathogenic fungi. In this study, a population genetics analysis of the insect-pathogenic fungus Metarhizium anisopliae from forested and agricultural habitats in Ontario, Canada, showed a nonrandom association of alleles between two distinct, reproductively isolated groups (index of multilocus association = 1.2). Analyses of the mitochondrial DNA showed no differences between the groups. The two groups were associated with different habitat types, and associations with insect hosts were not found. The group from forested areas showed an ability for cold-active growth (i.e., 8 degrees C), while the group from the agricultural area showed an ability for growth at high temperatures (i.e., 37 degrees C) and resilience to UV exposure. These results represent a significant paradigm shift; habitat selection, not host insect selection, drives the population structure of these insect-pathogenic deuteromycetous fungi. With each group we observed recombining population structures as well as clonally reproducing lineages. We discuss whether these groups may represent cryptic species. Worldwide, M. anisopliae may be an assembly of cryptic species, each adapted to certain environmental conditions. The association of fungal genotypes with habitat but not with host insects has implications on the criteria for utility of this, and perhaps other, fungal biocontrol agents.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".