MétaCan
Menu
Back to cohort
Record W2087302525 · doi:10.1139/x05-254

The vertical and horizontal distribution of roots in northern hardwood stands of varying age

2006· article· en· W2087302525 on OpenAlexvenueno aff
Ruth D. Yanai, Byung Bae Park, Steven P. Hamburg

Bibliographic record

VenueCanadian Journal of Forest Research · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicForest ecology and management
Canadian institutionsnot available
FundersNational Science Foundation
KeywordsBiomass (ecology)HardwoodSoil horizonBasal areaCanopyClearcuttingCoringSpatial distributionEnvironmental scienceForestrySoil waterBotanyBiologyGeographySoil scienceAgronomy

Abstract

fetched live from OpenAlex

Coring methods cannot reveal the distribution of roots with depth in rocky soil, and fine roots are typically sampled without regard to the location of trees. We used quantitative soil pits to describe rooting patterns with soil depth and distance to trees in northern hardwood stands. We sited three 0.5 m 2 quantitative soil pits in each of three young (19–27 years) and three older (56–69 years) stands developed after clear-cutting. Live roots were divided into diameter classes delimited at 0.5, 1, 2, 5, 10, 20, and 100 mm; dead roots were not distinguished by size. Mean total live-root biomass was 2900 ± 500 g·m –2 in older stands and 1500 ± 400 g·m –2 in young stands. The root mass in the 2–20 mm class was 2.7 times greater in the older stands (p = 0.03); fine-root (<2 mm) biomass was 1.5 times greater (p = 0.12), suggesting that fine-root biomass continues to increase past the age of canopy closure in this forest type. Root biomass density declined with soil depth, with the finest roots (<0.5 mm) declining most steeply; roots were found at low densities well into the C horizon. We analyzed root biomass density as a function of the influence of nearby trees (represented as the sum of basal area divided by the distance from the pit) and found that fine as well as coarse roots reflected this influence. In systems where this is the case, root measurements should be made with attention to patterns of tree distribution.

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 score0.806
Threshold uncertainty score0.983

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 studies0.0000.001
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 head0.015
GPT teacher head0.255
Teacher spread0.241 · 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

Citations99
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Forest ResearchSame topicForest ecology and managementFrench-language works237,207