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Record W2015963151 · doi:10.1139/x09-071

Influences of climate, fire, and topography on contemporary age structure patterns of Douglas-fir at 205 old forest sites in western Oregon

2009· article· en· W2015963151 on OpenAlexvenueno aff
Nathan J. Poage, Peter J. Weisberg, Peter C. Impara, John C. Tappeiner, Thomas S. Sensenig

Bibliographic record

VenueCanadian Journal of Forest Research · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsnot available
Fundersnot available
KeywordsFire historyDouglas firEcologyGeographyScale (ratio)Period (music)Forest structureFire ecologyPhysical geographyEcosystemForestryClimate changeBiologyCartographyCanopy

Abstract

fetched live from OpenAlex

Knowledge of forest development is basic to understanding the ecology, dynamics, and management of forest ecosystems. We hypothesized that the age structure patterns of Douglas-fir at 205 old forest sites in western Oregon are extremely variable with long and (or) multiple establishment periods common, and that these patterns reflect variation in regional-scale climate, landscape-scale topography, and landscape-scale fire history. We used establishment dates for 5892 individual Douglas-firs from these sites to test these hypotheses. We identified four groups of old forest sites with fundamentally different Douglas-fir age structure patterns. Long and (or) multiple establishment periods were common to all groups. One group described old forests characterized by substantial establishment from the early 1500s to the mid-1600s, with decreasing establishment thereafter. Another group was characterized by peaks of establishment in the middle to late 1600s and in the late 1800s and early 1900s. A third group was characterized by a small peak of establishment in the mid-1500s and a larger peak in the middle to late 1800s. Characteristic of the fourth group was the extended period of Douglas-fir establishment from the late 1600s to the late 1800s. Group membership was explained moderately well by contemporary, regional climatic variables and landscape-scale fire history, but only weakly by landscape-scale topography.

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)0.001
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 score0.052
Threshold uncertainty score0.103

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
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 head0.022
GPT teacher head0.276
Teacher spread0.254 · 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

Citations27
Published2009
Admission routes1
Has abstractyes

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Same venueCanadian Journal of Forest ResearchSame topicFire effects on ecosystemsFrench-language works237,207