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Record W6967487314 · doi:10.5061/dryad.1c59zw3wv

Data from: Plasticity drives extreme cold tolerance of emerald ash borer (Agrilus planipennis) during a polar vortex

2022· dataset· en· W6967487314 on OpenAlexaffabout

Bibliographic record

VenueOpen MIND · 2022
Typedataset
Languageen
Field
Topic
Canadian institutionsNatural Resources CanadaCanadian Forest ServiceWestern University
Fundersnot available
KeywordsEmerald ash borerAgrilusPopulationBuprestidaeIntroduced speciesOverwinteringCold tolerance

Abstract

fetched live from OpenAlex

Invasive species must often survive combinations of environmental conditions that differ considerably from their native range; however, for a given species it is unclear whether improved tolerance is the result of phenotypic plasticity or genetic adaptation (or both). Agrilus planipennis (Coleoptera: Buprestidae; the emerald ash borer) is an invasive pest of Fraxinus trees in North America and Europe. Previous studies in southwestern Ontario, Canada, showed that A. planipennis is freeze avoidant, preventing internal ice formation by accumulating molar concentrations of glycerol in its hemolymph and depressing its supercooling point (SCP, the temperature at which it freezes). The cold tolerance of these southwestern Ontario animals was used to predict potential distribution, revealing that some Canadian cities should be too cold to allow populations to persist. However, a small population of A. planipennis has persisted in Winnipeg, Manitoba, Canada, through several severe ‘polar vortex’ events. In 2018/19, we collected A. planipennis larvae and prepupae from Winnipeg, Manitoba and Southern Ontario, and found that individuals from Winnipeg were extremely cold tolerant – with SCPs as low as -52 °C in prepupae (compared to 32 °C in Southern Ontario), and survival of unfrozen individuals exposed to -50 °C for one hour. This cold tolerance was accompanied by higher hemolymph osmolality and glycerol concentration than in the SW Ontario individuals. To distinguish between phenotypic plasticity and local adaptation, in 2020/21 we overwintered Winnipeg-sourced individuals either outdoors in southwestern Ontario or in a simulated Winnipeg winter. Simulated Winnipeg winter individuals had cold tolerance similar to those overwintered in Winnipeg, while southwestern Ontario overwintered individuals had cold tolerance similar to those collected previously in the region. The simulated winter individuals had higher hemolymph glycerol concentrations than southwestern Ontario overwintered animals, at least in part due to greater dehydration. Thus, A. planipennis are cold-tolerant enough to survive some of the harshest winters where their host trees can grow, and most likely attain this cold tolerance via phenotypic plasticity. These findings raise the importance of delineating sensitivity of conclusions to unexpected phenotypic plasticity when predicting potential distributions of new invasives or responses to climate change. The data in this dataset are the SCPs and treatment data for the experimental animals used in these cold tolerance experiments.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Dataset · Consensus signal: none
Teacher disagreement score0.115
Threshold uncertainty score0.229

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0200.004

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.

Opus teacher head0.089
GPT teacher head0.316
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreDataset

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".

Quick stats

Citations0
Published2022
Admission routes2
Has abstractyes

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