Landscape‐scale population connectivity in two parasitoid species associated with the spruce budworm: Testing the birdfeeder effect using genetic data
Bibliographic record
Abstract
Abstract Periodic and spatially synchronous outbreaks of insect pests have dramatic consequences for boreal and sub‐boreal forests. Within these multitrophic systems, parasitoids can be stabilizing agents by dispersing toward patches containing higher host density (the so‐called birdfeeder effect). However, we know little about the dispersal abilities of parasitoids in continuous forested landscapes, limiting our understanding of the spatiotemporal dynamics of host–parasitoid systems, and constraining our ability to predict forest resilience in the context of global changes. In this study, we investigate the spatial genetic structure and spatial variation in genetic diversity of two important species of spruce budworm larval parasitoids during outbreaks: Apanteles fumiferanae Viereck (Braconidae) and Glypta fumiferanae (Viereck) (Ichneumonidae). Using parasitoids sampled in 2014 from 26 and 29 locations across a study area of 350,000 km2, we identified 1,012 and 992 neutral SNP loci for A. fumiferanae (N = 279 individuals) and G. fumiferanae (N = 382), respectively. Using DAPC, PCA, AMOVA, and IBD analyses, we found evidence for panmixia and high genetic connectivity for both species, matching the previously described genetic structure of the spruce budworm within the same context, suggesting similar effective dispersal during outbreaks and high parasitoid population densities between outbreaks. We also found a significant negative relationship between genetic diversity and latitude for A. fumiferanae but not for G. fumiferanae, suggesting that northern range limits may vary by species within the spruce budworm parasitoid community. These spatial dynamics should be considered when predicting future insect outbreak severities in boreal landscapes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".