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Record W2607702699

Climate Change Effects on the Pest Status and Distribution of the Bean Leaf Beetle (Cerotoma trifurcata)

2013· dissertation· en· W2607702699 on OpenAlexfundaboutno aff
Emily A. Berzitis

Bibliographic record

VenueThe Atrium (University of Guelph) · 2013
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicInsect Pest Control Strategies
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaOntario Ministry of Agriculture, Food and Rural Affairs
KeywordsLeaf beetlePEST analysisClimate changeBiologyAgronomyInsect pestBotanyEcologyLarva
DOInot available

Abstract

fetched live from OpenAlex

The bean leaf beetle, Cerotoma trifurcata (Förster) (Coleoptera: Chrysomelidae), has recently become a major pest of soybean (Glycine max (L.) Merrill) in North America. With the possibility of further economic losses, an understanding of the potential indirect and direct effects of climate change on the severity of this pest is required. The plant-mediated effects of elevated CO2 on bean leaf beetle fecundity were examined. While non-nitrogen-fixing plants generally show decreases in leaf carbon to nitrogen ratio under elevated CO2, which can negatively impact insect herbivores, there was no change in the carbon to nitrogen ratio of soybean leaves, a nitrogen-fixer, in this study. The lack of change in leaf carbon to nitrogen ratio under elevated CO2 may explain the absence of a treatment effect on bean leaf beetle fecundity in one year of the experiment. However, in the second year, there was an increase in bean leaf beetle fecundity under elevated CO2. Using a multi-year field experiment, I examined the potential direct effects of climate change, namely the impacts of warmer winters on bean leaf beetle overwintering survival and spring emergence. Under increased temperatures, bean leaf beetles emerged 10 to 20 days earlier in the spring which could allow for an additional generation during the growing season. Higher temperatures also led to decreased survival. I developed a bioclimatic envelope model for the bean leaf beetle to examine the direct effects of climate change on a broader scale. I combined this model with the soybean climate envelope to predict the future potential distribution of the bean leaf beetle based both on climate and host plant availability. Since soybean generally has narrower tolerances than the bean leaf beetle, incorporation of host plant availability had a substantial impact on predictions of bean leaf beetle distribution. The inclusion of climate projections from multiple general circulation models (GCMs) and scenarios was a source of variability in our predictions, with only two of the three GCMs predicting further expansion of the bean leaf beetle into Canada.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.008

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.015
GPT teacher head0.196
Teacher spread0.181 · 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
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

Citations3
Published2013
Admission routes2
Has abstractyes

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