Functional structure of the natural enemy community of the fall armyworm, Spodoptera frugiperda in the Americas
Bibliographic record
Abstract
Ecosystem functions such as biological pest control are mediated by the richness and abundance of service providers i.e., biological control agents (BCAs), relative contributions of individual taxa and community structure. This is especially relevant in the native range of agricultural herbivores, where a speciose community of co-evolved BCAs can prevent them from attaining pest status. Here, we use a powerful graphical approach to assess the functional structure of BCA communities of the fall armyworm (FAW) Spodoptera frugiperda (Lepidoptera: Noctuidae) on maize in the Neotropics. Drawing upon a curated database of all-time field and laboratory studies, we graphed patterns in the functional contribution, abundance and niche breadth for a respective 69, 53 and 3 taxa of resident parasitoids, predators and pathogens. Regardless of varying taxon coverage and rigor of the underlying studies, functional structure follows a saturating relationship in which the first three taxa account for 90–98% of aggregate biological control function. Abundance-functionality matrices prove critically incomplete, as more than 80% of invertebrate taxa miss empirically derived efficiency metrics while associated FAW infestation data are scarce. Despite its methodological shortfalls and data gaps, our work pinpoints Chelonus insularis , several taxa of egg parasitoids, Doru spp. and Orius spp. as taxa with outsized (average) functionality and conservation potential. This is also exemplified by the highly variable aggregate function across studies, with dispersion indices of 1.52 and 2.14 for invertebrate BCAs. Our work underlines the critical importance of functional ecology research, networked trials and standardized methodologies in advancing conservation biological control globally.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| 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".