Nocturnal moth communities and potential pollinators of berry agroecosystems in British Columbia
Bibliographic record
Abstract
Agricultural crops are facing a global pollination crisis due to the anthropogenic threats of climate change, habitat loss, and agricultural intensification, threatening the stability of agroecosystems. The bulk of current research to protect and improve pollination services focuses on only a subset of pollinators (i.e. day-active and commercially available), yet night-dwelling insects, specifically moths (Lepidoptera), can also be important pollinators. New research is revealing that nocturnal moths can act as nighttime pollinators, yet their role in providing pollination services for crops and surrounding agricultural landscapes is likely understated. To examine moth biodiversity and identify potential pollinators in berry agroecosystems, I sampled nocturnal moths during flowering periods in fields of cultivated blueberry (N = 3) and strawberry crops (N = 5), in the Lower Mainland of British Columbia, during the spring and summer of 2023. I identified all surveyed moths to family at minimum, and to genus and/or species, when possible, with priority given to large-bodied macromoths which are more likely to be pollinators and have more resources for identification. I compared diversity metrics across sites and months to examine community shifts across space and time and found that moth assemblages primarily shifted at the species level. To determine the role of moths in providing pollination services to berry agroecosystems, I counted and identified pollen carried on each moth as an indication to the flowering plant species they had visited. I used pollen load as a proxy to establish their ability to transport pollen. I confirmed that previously reported pollinating species such as those in the family Sphingidae were present and carried pollen in berry agroecosytems in BC. I also report pollen on species of moths that had not previously been identified as pollen-carrying. Furthermore, I identified blueberry pollen on several species that had not previously been documented as carrying blueberry pollen, establishing several additional species of moths which may pollinate blueberry. Including nocturnal insects in pollination studies can reveal important, novel interactions in ecosystems. The findings in this study provide further support to the importance of moths as pollinators and emphasize the need to include nocturnal insects in future studies.
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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 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".