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Record W2064493680 · doi:10.1139/x10-247

Forest developmental trajectories in mountain pine beetle disturbed forests of Rocky Mountain National Park, Colorado

2011· article· en· W2064493680 on OpenAlexvenueno aff
Matthew Diskin, Monique E. Rocca, Kellen N. Nelson, Carissa F. Aoki, William H. Romme

Bibliographic record

VenueCanadian Journal of Forest Research · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsnot available
FundersWarner College of Natural Resources, Colorado State UniversityU.S. Forest ServiceColorado State University
KeywordsPinus contortaAbies lasiocarpaPicea engelmanniiMountain pine beetleDendroctonusEcologyGeographyForestryCanopyNational parkBark beetleBiologyBark (sound)

Abstract

fetched live from OpenAlex

A mountain pine beetle (Dendroctonus ponderosae Hopkins) epidemic has caused widespread mortality of lodgepole pine (Pinus contorta Dougl. ex Loud. var. latifolia Engelm.) trees across western North America,. We characterized the initial effects of beetle-induced mortality on forest structure and composition in Rocky Mountain National Park, Colorado. In 2008, we surveyed stand structure and tree species composition across lodgepole pine dominated forests in the western portion of the Park. We defined five lodgepole pine forest types to describe variability in pre-epidemic forest conditions. This forested landscape appears to be resilient to the effects of the beetle. Surviving trees, including both canopy trees and saplings, were plentiful in most of the post-epidemic forests, even after accounting for anticipated future mortality. Subalpine fir (Abies lasiocarpa (Hook.) Nutt.), Engelmann spruce (Picea engelmannii Parry ex Engelm.), and aspen (Populus tremuloides Michx.) had modestly higher relative abundances after the epidemic. Lodgepole pine remained the dominant species on approximately 85% of the landscape. The impact of the outbreak on forest structure and composition varied considerably among the five forest types, suggesting that post-epidemic forest developmental trajectories will vary according to pre-outbreak stand characteristics. Active management efforts to regenerate lodgepole pine forests, e.g., tree planting, will likely not be necessary on this landscape.

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)0.003
metaresearch head score (Gemma)0.001
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 score0.785
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
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)0.0010.000

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 head0.038
GPT teacher head0.275
Teacher spread0.237 · 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

Citations92
Published2011
Admission routes1
Has abstractyes

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