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Record W2032607117 · doi:10.1139/x07-066

Why does longleaf pine have low susceptibility to southern pine beetle?

2007· article· en· W2032607117 on OpenAlexvenueno aff
Sharon J. Martinson, Richard W. Hofstetter, Matthew P. Ayres

Bibliographic record

VenueCanadian Journal of Forest Research · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsnot available
Fundersnot available
KeywordsBiologyBark beetleSympatric speciationCurculionidaePinus <genus>Bark (sound)BotanyInfestationEcologyPEST analysisMountain pine beetleWoody plant

Abstract

fetched live from OpenAlex

Pine forests throughout the world are subject to disturbance from tree-killing bark beetles, but pine species differ in their susceptibilities. In the southeastern United States, Pinus palustris Mill. suffers far less mortality from the southern pine beetle, Dendroctonus frontalis Zimmermann, than do its sympatric congeners. We tested the commonly invoked hypothesis that P. palustris has relatively low susceptibility because it has higher oleoresin flow than other pines, especially Pinus taeda L. However, seven studies in three states over 6 years refuted the hypothesis that P. palustris and P. taeda differ in their constitutive resin flow or in their capacity to replace resin depleted by either experimental wounding or natural beetle attacks. Additionally, surveys of natural beetle attacks revealed that P. taeda and P. palustris were equally likely to be attacked and killed when they cooccurred in front of growing infestations. Thus, the relative susceptibility of these two species changes with the spatial scale at which they are mixed, and the strong landscape-scale pattern of low mortality in P. palustris is not because individual trees are physiologically less susceptible. Ultimately, the conspicuous differential impact of D. frontalis on P. taeda and P. palustris may be the product of coevolution between tree defenses and beetle behavior.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.898
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0100.001

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 head0.022
GPT teacher head0.287
Teacher spread0.266 · 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; both teacher heads agree on what is shown here.

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

Citations25
Published2007
Admission routes1
Has abstractyes

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