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Record W6923857884 · doi:10.14288/1.0104062

Vegetation-environment relationships of sub-boreal spruce zone ecosystems in British Columbia

2011· article· en· W6923857884 on OpenAlexaboutno aff

Bibliographic record

VenuecIRcle (University of British Columbia) · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInvertebrate Taxonomy and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsSoil waterVegetation (pathology)EcosystemSnowPrecipitationHydrology (agriculture)Terrestrial ecosystemRange (aeronautics)

Abstract

fetched live from OpenAlex

An environmental study using the association concept and the 'ecological groups' within the biogeoclimatic zonal framework was conducted in the Sub-Boreal spruce zone in British Colimbia [sic]. Quantitative information on the vegetation and environment of the zone has, hitherto, been lacking. Seventy seven stands have been studied. From the six upland associations, delimited by the methods of Zurich-Montpellier School using Domin-Krajina scale, soils from seventeen different Soil Great Groups have been distinguished and described. The relation between vegetation and soil morphology are obvious at the zonal and association levels but are less distinct at lower levels. Based on fourteen sample plots, four low moor associations on nine Mesisols, four Fibrisols and one Humisol are also described. Microclimatic data, air and soil temperatures, humidity, precipitation and snow cover have been recorded from five stands that differed in canopy density, ground cover, species composition, in soil conditions and topography. Air and soil temperature patterns show a remarkable similarity. Diurnal temperature fluctuations are most pronounced under Pinetum contortae while such fluctuations are much less under Alnetum tenuifoliae and Piceetum glaucae. Chemical analyses of 280 soil samples include a wide range of both macro- and micronutrients as well as some toxic heavy metals. Analyses involved water soluble and replaceable major cations, total nitrogen and available phosphorus, and water soluble, replaceable, EDTA- and HCl-extractable trace metals. The soils under white spruce-devil's club and river alder-ostrich fern are the richest in both macro- and micronutrients, followed by aspen and black spruce. Seemingly soils of the black spruce sites sampled show a high nutrient content but it looks doubtful if all these are readily available because of impeded drainage and low base saturation. From the study of the sites, nutritional requirements of subalpine fir appear to be high and those of lodgepole pine very low. Neither the chemical characteristics of the low moor organic soils nor the water chemistry seem to show any distinct relationship with the vegetation of these sites. Using multiple regression analyses eight statistically significant environmental gradients have been used in the study. The soil texture gradient is based on the weighted averages of the sum of percentage silt and clay content calculated for the rooting depth. The water gradient has been established on the available water capacity expressed as a percentage of the rooting volume of the soil. Five nutrient gradients have been established. The calcium and magnesium gradients are based on the replaceable content expressed as equivalents per square meter of the soil rooting volume. Nitrogen gradient based on total nitrogen analysis are expressed as grams per square meter of the rooting volume. Gradients based on EDTA-extractable manganese and iron are expressed the same way as nitrogen. The light gradient is based on observations from fiftyeight plots, extended over a period of two years, using a chemical light meter. All gradients are quantified and the correlations of associations along these gradients are shown. Of all the gradients considered in the study, plant communities showed better correlations with soil texture, water and replaceable calcium. Using relative species significance rather than presence, distributional patterns of individual species along these gradients have been illustrated. Predictive equations based on regression analyses using both transformed measured values and their logarithms have been given for a number of plant species.

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)0.000
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 score0.049
Threshold uncertainty score0.098

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.019
GPT teacher head0.143
Teacher spread0.124 · 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

Citations0
Published2011
Admission routes1
Has abstractyes

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