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Record W2081120832 · doi:10.1139/x07-008

Differential impacts of the southern pine beetle, <i>Dendroctonus frontalis</i>, on <i>Pinus palustris</i> and <i>Pinus taeda</i>

2007· article· en· W2081120832 on OpenAlexvenueno aff
Nicholas A. Friedenberg, Brenda M. Whited, Daniel H. Slone, Sharon J. Martinson, Matthew P. Ayres

Bibliographic record

VenueCanadian Journal of Forest Research · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsnot available
FundersSouthern Research StationU.S. Forest ServiceU.S. Department of Agriculture
KeywordsBiologyPinus <genus>DendroctonusEcologyLoblolly pineCurculionidaeWoody plantHost (biology)Bark beetleBotany

Abstract

fetched live from OpenAlex

Patterns of host use by herbivore pests can have serious consequences for natural and managed ecosystems but are often poorly understood. Here, we provide the first quantification of large differential impacts of the southern pine beetle, Dendroctonus frontalis Zimmermann, on loblolly pine, Pinus taeda L., and longleaf pine, Pinus palustris P. Mill., and evaluate putative mechanisms for the disparity. Spatially extensive survey data from recent epidemics indicate that, per square kilometre, stands of loblolly versus longleaf pine in four forests (380–1273 km 2 ) sustained 3–18 times more local infestations and 3–116 times more tree mortality. Differences were not attributable to size or age structure of pine stands. Using pheromone-baited traps, we found no differences in the abundance of dispersing D. frontalis or its predator Thanasimus dubius Fabricius between loblolly and longleaf stands. Trapping triggered numerous attacks on trees, but the pine species did not differ in the probability of attack initiation or in the surface area of bark attacked by growing aggregations. We found no evidence for postaggregation mechanisms of discrimination or differential success on the two hosts, suggesting that early colonizers discriminate between host species before a pheromone plume is present.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.506
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.017
GPT teacher head0.259
Teacher spread0.241 · 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.

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

Citations21
Published2007
Admission routes1
Has abstractyes

Explore more

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