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Record W2109636008 · doi:10.1111/jvs.12142

An early forest inventory indicates high accuracy of forest composition data in pre‐settlement land survey records

2013· article· en· W2109636008 on OpenAlexafffund
Raphaële Terrail, Dominique Arseneault, Marie‐Josée Fortin, Sébastien Dupuis, Yan Boucher

Bibliographic record

VenueJournal of Vegetation Science · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicForest Ecology and Biodiversity Studies
Canadian institutionsCenter for Northern StudiesMinistère des Ressources naturelles et des Forêts (Québec)University of TorontoUniversité du Québec à Rimouski
FundersFonds de recherche du Québec – Nature et technologiesUniversité du Québec à Rimouski
KeywordsDominance (genetics)TaxonGeographyRange (aeronautics)Forest inventoryBasal areaForestryAbies balsameaEcologyBalsamForest managementBiology

Abstract

fetched live from OpenAlex

Abstract Questions Do early land survey records of the ‘line description’ type allow accurate reconstructions of pre‐settlement forest composition? Did surveyors record all tree taxa in forest stands encountered along the surveyed lines? Were taxa ranked according to their relative importance in forest stands? What criteria did surveyors used to rank taxa in stands? Location Northern range limit of northern hardwoods, L ower S t. L awrence region, eastern Q uébec, C anada. Methods Validation of 1695 taxon lists recorded by surveyors in the 19th century through comparison of the number of stems by tree species and stem diameter classes recorded in 2790 old‐growth plots over the same two regions during a 1930 forest inventory. Results Taxon prevalence and dominance (i.e. proportion of observations for which each taxon is dominant) are highly correlated between the pre‐settlement surveys and the 1930 forest inventory data sets. Surveyors ranked taxa in decreasing order of relative importance, using criteria directly equivalent to basal area of stems in modern forest inventory plots. Taxon prevalence is more accurately reconstructed using relative metrics (i.e. ranks of taxon prevalence in a region), whereas taxon dominance is more accurately reconstructed using absolute metrics (percentage of dominant stands across landscapes). The early land surveys allow spatial patterns of forest composition to be reconstructed by computing relative taxon prevalence in cells of 3 km × 3 km. Prevalence of balsam fir ( A bies balsamea ) and white birch ( B etula papyrifera ) are underestimated in survey data, probably reflecting their low economic value in the 19th century. Conclusions Taxon lists of early surveyors can accurately reconstruct pre‐settlement forest composition and spatial patterns using metrics of taxon prevalence and dominance across landscapes. Relative prevalence is a more comprehensive description of forest composition than dominance, but tends to underestimate some taxa. Absolute taxon dominance is a more robust metric than prevalence, but only reports on the abundance of the most dominant taxa.

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)0.002
metaresearch head score (Gemma)0.005
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 score0.134
Threshold uncertainty score0.267

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.052
GPT teacher head0.284
Teacher spread0.232 · 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

Citations31
Published2013
Admission routes2
Has abstractyes

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