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Record W2165897442 · doi:10.1139/x01-111

Using witness trees to assess forest change in southeastern Ohio

2001· article· en· W2165897442 on OpenAlexvenueno aff
James M. Dyer

Bibliographic record

VenueCanadian Journal of Forest Research · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicEcology and Vegetation Dynamics Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGeographyForestryVegetation (pathology)MarshEcologyBiologyWetland

Abstract

fetched live from OpenAlex

In 1787, the U.S. Congress authorized the sale of the "Ohio Company Purchase", ca. 5000 km 2 in Appalachian Ohio. The land was surveyed using a township and range system shortly thereafter. Data on >5600 witness trees were transcribed from the survey records, and witness tree locations were plotted on a digital map. This information was used to evaluate presettlement forest composition and structure and to investigate vegetation-site relationships before widespread alteration of the forests had taken place. Presettlement conditions were compared with present conditions using forest inventory and analysis (FIA) data. Two hundred years ago, the forests of southeastern Ohio were dominated by large individuals of Quercus alba L., Carya Nutt. spp., Quercus velutina Lam., and Fagus grandifolia Ehrh. These four taxa accounted for 74% of all witness trees. Although almost 70% of the region is forested today, the second-growth forest has witnessed a decrease in Quercus and Carya and an increase in Acer saccharum Marsh., Acer rubrum L., and many early successional species in smaller size classes. Despite the significant shift in forest composition and structure, species in general seem to be occupying similar positions in the present-day landscape compared with the presettlement forest; topographic variables most strongly control species occurrence in 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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.950
Threshold uncertainty score0.975

Codex and Gemma teacher scores by category

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

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 head0.181
GPT teacher head0.378
Teacher spread0.197 · 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.

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

Citations112
Published2001
Admission routes1
Has abstractyes

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