Using insect natural history collections to study global change impacts: challenges and opportunities
Bibliographic record
Abstract
Over the past two decades, natural history collections (NHCs) have played an increasingly prominent role in global change research, but they have still greater potential, especially for the most diverse group of animals on Earth: insects. Here, we review the role of NHCs in advancing our understanding of the ecological and evolutionary responses of insects to recent global changes. Insect NHCs have helped document changes in insects' geographical distributions, phenology, phenotypic and genotypic traits over time periods up to a century. Recent work demonstrates the enormous potential of NHCs data for examining insect responses at multiple temporal, spatial and phylogenetic scales. Moving forward, insect NHCs offer unique opportunities to examine the morphological, chemical and genomic information in each specimen, thus advancing our understanding of the processes underlying species' ecological and evolutionary responses to rapid, widespread global changes.This article is part of the theme issue 'Biological collections for understanding biodiversity in the anthropocene'.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 teacher head, 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".