Have native insect pests associated with a native crop in <scp>Maine</scp> declined over the past three to five decades?
Bibliographic record
Abstract
Abstract Lowbush blueberry is an important berry crop in Maine (USA), Quebec and the Maritime provinces of Canada. The other economically important crops in Maine are potato, dairy and organic mixed vegetable produce. Lowbush blueberry is a complex of 1–4 Vaccinium species, primarily dominated by Vaccinium angustifolium Aiton. All but one of the insect pest species in this crop system are native to the regions where it is managed in North America. Insect decline has been shown to be a recent global phenomenon although it has rarely been studied in agricultural ecosystems. Long‐term datasets of insect species abundances are a powerful tool for insect population trends. To determine if native insect pests have declined over the past several decades in Maine lowbush blueberry, we surveyed three native species. All surveys were conducted in commercial blueberry fields; although, none of the sample sites were sprayed with insecticides. Insect pest sampling comprised two surveys (1961–2014 and 1998–2017) conducted on the larval stage of the blueberry maggot fly ( Rhagoletis mendax Curran), one survey (1981–2016) on the larval stage of the blueberry spanworm ( Itame argillacearia (Packard)), and one survey (1983–2019) on the larval stage of the blueberry flea beetle ( Altica sylvia Malloch). Based upon the analysis of our long‐term population‐level datasets, we found no evidence that insect decline has occurred in this native blueberry insect pest complex intimately associated with the lowbush blueberry, a native crop plant in North America, despite recent documentation of rapid climate change occurring in the lowbush blueberry production areas.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".