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Record W2977273281 · doi:10.3390/f10100860

Climate Change Impacts on the Potential Distribution and Range Shift of Dendroctonus ponderosae (Coleoptera: Scolytidae)

2019· article· en· W2977273281 on OpenAlexaff
Yuting Zhou, Xuezhen Ge, Zou Ya, Siwei Guo, Tao Wang, Shixiang Zong

Bibliographic record

VenueForests · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsDendroctonusMountain pine beetleClimate changeLatitudeRange (aeronautics)Global warmingEcologyBark beetleDistribution (mathematics)GeographyEnvironmental sciencePhysical geographyBark (sound)Biology

Abstract

fetched live from OpenAlex

Dendroctonus ponderosae Hopkins (Coleoptera: Scolytidae) is one of the most important bark beetles in North America and causes considerable economic and ecological losses during outbreaks. The distribution of this pest species is likely to be altered by climate change, which may threaten currently unaffected areas. In this study, we used CLIMEX to project the potential global distribution of D. ponderosae according to both historical climate data (1987–2016) and future climate warming estimates (2021–2100) to evaluate the impact of climate change on this species. Regions with suitable climate for D. ponderosae are distributed in all continents except Antarctica under both historical and future climate conditions, and these are predicted to change continuously with climate change. Overall, climate suitability will increase in middle- and high-latitude regions and decrease in low-latitude regions, and regions most sensitive to climate change are located in the mid-latitude zone. Moreover, the shift directions and ranges of climate-suitable regions under future conditions will differ among continents, and the shift distances in the north–south direction are larger than these in the east–west direction for Africa, Asia, Europe, South America, and Oceania, indicating that shift direction is possibly mainly affected by temperature. These projected distributions may provide theoretical guidance for early-warning intervention and risk assessment.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.950

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.009
GPT teacher head0.215
Teacher spread0.206 · 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 teacher head, not a consensus.

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

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

Citations5
Published2019
Admission routes1
Has abstractyes

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