MétaCan
Menu
Back to cohort
Record W2054398892 · doi:10.1139/x00-184

Analysis of temporal variation and species-site relationships of witness tree data in southeastern Pennsylvania

2001· article· en· W2054398892 on OpenAlexvenueno aff
Bryan A. Black, Marc D. Abrams

Bibliographic record

VenueCanadian Journal of Forest Research · 2001
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBotany, Ecology, and Taxonomy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMarshGeographyWoodlandDendrochronologyForestryEcologyEnvironmental scienceArchaeologyWetlandBiology

Abstract

fetched live from OpenAlex

Witness tree species – site relationships are described with respect to parent material, soil drainage, and soil surface texture in Lancaster County, southeastern Pennsylvania. Quercus velutina Lam. and Carya were positively associated with "limestone" parent materials and well-drained, loamy sites. Quercus velutina was strongly associated with "acid shale and sandstone" parent materials and well-drained, upland soils. Quercus alba L. was most abundant on parent material classes associated with stream valleys and coves while Qurecus prinus L. and Castanea dentata (Marsh.) Borkh. were positively associated with well-drained, rocky sites on "quartzite" parent materials. Procedures were then developed to test for significant changes in witness tree species frequencies over the 100-year period of metes and bounds surveys in Lancaster County. These tests revealed that Quercus coccinea L., Nyssa sylvatica Marsh., and early successional species were surveyed much later than Quercus rubra L., Q. alba, and Carya spp. Agricultural land clearing, cutting for firewood, selective logging, and the charcoal-iron industry all probably contributed these species changes. Overall, abundances of minor species appear to be much more sensitive to these early settlement land uses. Given the extent of metes and bounds surveys, these tests for temporal variations may be applied to witness tree data throughout the eastern United States.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.946
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.176
GPT teacher head0.303
Teacher spread0.128 · 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

Citations30
Published2001
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Forest ResearchSame topicBotany, Ecology, and Taxonomy StudiesFrench-language works237,207