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Record W2065332284 · doi:10.5558/tfc79485-3

Presettlement forest in southern Ontario: Ecosystems measured through a cultural prism

2003· article· en· W2065332284 on OpenAlexafffundvenueabout
Roger Suffling, Michael I. Evans, Ajith H. Perera

Bibliographic record

VenueThe Forestry Chronicle · 2003
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicTree-ring climate responses
Canadian institutionsOntario Forest Research InstituteUniversity of Waterloo
FundersNatural Resources CanadaParks Canada
KeywordsTsugaBeechGeographyDeciduousForestryPeninsulaEcologyArchaeologyBiology

Abstract

fetched live from OpenAlex

To better manage southern Ontario's natural forests, the former and present status of old growth must be understood. We hypothesize that old-growth pine (Pinus spp.), although dominant elsewhere, was less common in southern Ontario than popular history suggests: we are obliged to evaluate historical information that has been filtered both by the original compilers and through our own biases. Beginning around 600 AD, the predominant beech (Fagus americana) forest was partially replaced by maple (primarily Acer saccharum), oaks (Quercus spp.) and eastern white pine (P. strobus). This pine increase either followed abandonment of pre-Columbian agriculture or, more plausibly, accompanied climate cooling. Eighteenth and 19 th century European settlers encountered abundant large trees, which they hewed for square pine timber, milled timber, and tanbark. Other stands were cut and burned for agricultural clearance, with a potash by-product. Until recently, Ontario research emphasized the old-growth pine stands of central and northern Ontario to the relative exclusion of other kinds of old forest because very few southern Ontario old-growth stands remained to study. Ontario forest resource inventory data (FRI) show stands of over 150 years totalling only 1475 ha in 1978, concentrated on the Oak Ridges Moraine, the St. Lawrence Valley and the Awenda Peninsula. Red (P. resinosa) and eastern white pine stands constituted only 5.3% of the 1978 forested area, with virtually none of over 150 years, whereas eastern hemlock (Tsuga canadensis) stands constituted 12.8%. The difficulty in finding modern old growth necessitates historical reconstruction using physical, written and graphical resources, including early survey records and trade statistics. In a case study of 1822 survey data from Darling Township (Lanark Co.) and 1960 FRI, vegetation was classified using TWINSPAN and mapped using ARC/INFO Thiessen polygons. In 1822, dominant hemlock occupied half the township but it has since been eliminated as a dominant. Conversely, there were no pine-dominated forests in 1822, but these had increased to 16% of the area by 1960. A second case used similar methods, with 1855 data for St. Edmunds and Lindsay townships (Bruce Co.) and 1981 FRI. Although logging halved the area and reduced the stature of pines in the large pinery, the elimination of dominant hemlock (originally 41% by area) is more significant. Fragmentary square timber trade data suggest that at least half the large pines in Bruce County were in St. Edmunds, so pine must have been spectacularly concentrated in a few areas. The third case, a map constructed from Gourlay's 1817–1819 survey, also demonstrates that pine-dominated areas were in the minority in southern Ontario, concentrated on sandy soils around Lakes Ontario and Erie. However, big hemlocks, beeches, maples and oaks were much more common overall. Management responses to this information should include designation of older southern Ontario forest stands (especially those never cleared since settlement) for maturation into an old-growth state, and the systematic restoration of eastern hemlock and beech stands for conservation purposes in southern Ontario. Key words: old-growth forest, Canada, Ontario, historical ecology, forest history

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 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 score0.687
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.030
GPT teacher head0.240
Teacher spread0.210 · 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

Citations30
Published2003
Admission routes4
Has abstractyes

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