When insects help to resolve plant phylogeny: evidence for a paraphyletic genus <i>Acacia</i> from the systematics and host‐plant range of their seed‐predators
Bibliographic record
Abstract
In this study we use an indirect method to address the issue of the systematics of the large and economically important genus Acacia (Leguminosae, Mimosoideae, Acacieae). We propose the use of host‐preference data in closely related insect species as a potentially useful tool to investigate host systematic issues, especially when other approaches yield inconsistent results. We have examined the evolution of host‐plant use of a highly specialized group of seed‐feeders who predate Acacia — the seed‐beetles (Coleoptera, Chrysomelidae, Bruchinae). First, the evolution of host‐plant preferences in a large clade of Bruchidius species was investigated using molecular phylogenetics and character optimization methods. Second, the scope of our study was enlarged by critically reviewing the host‐plant records of all bruchine genera associated with Acacia . Both morphological and molecular data were used to define relevant insect clades, for which comparisons of host‐plant range were performed. Interestingly, the analyses of host‐plant preferences from 163 seed‐beetle species recovered similar patterns of host‐plant associations in the distinct clades which develop within Acacia seeds. Our results clearly support the hypothesis of Acacia being a paraphyletic genus and provide useful insights with reference to the systematics of the whole subfamily as well. This study should also be of interest to those involved in the numerous biological control programs which either already use or aim to use seed‐beetles as auxiliary species to limit the propagation of several invasive legume tree species.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".