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Record W4241541254 · doi:10.1890/09-0896

Response of a boreal forest to canopy gap openings - assessing vertical and horizontal tree growth with multi-temporal lidar data

2010· article· en· W4241541254 on OpenAlexaffabout
Udayalakshmi Vepakomma, Benoît St-Onge, Daniel Kneeshaw

Bibliographic record

VenueEcological Applications · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicRemote Sensing and LiDAR Applications
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsCanopyTaigaDeciduousBorealBlack spruceLidarHardwoodEcologyEnvironmental scienceSilvicultureTree canopyPhysical geographyGeographyAtmospheric sciencesRemote sensingBiologyGeology

Abstract

fetched live from OpenAlex

Fine-scale height-growth response of boreal trees to canopy openings is difficult to measure from the ground, and there are important limitations in using stereo-photogrammetry in defining gaps and determining individual crowns and height. However, precise knowledge on height growth response to different openings is critical for refining partial harvesting techniques. In this study, we question whether conifers and hardwoods respond equally in terms of sapling growth or lateral growth to openings. We also ask to what distance gaps affect tree growth into the forest. We use multi-temporal lidar to characterize tree/sapling height and lateral growth responses over five years to canopy openings and high resolution images to identify conifers and hardwoods. Species-class-wise height-growth patterns of trees/saplings in various neighborhood contexts were determined across a 6-km2 matrix of Canadian boreal mixed deciduous coniferous forests. We then use statistical techniques to probe how these growth responses vary by spatial location with respect to the gap edge. Results confirm that both mechanisms of gap closure contribute to the closing of canopies at a rate of 1.2% per annum. Evidence also shows that both hardwood and conifer gap edge trees have a similar lateral growth (average of 22 cm/yr) and similar rates of height growth irrespective of their location and initial height. Height growth of all saplings, however, was strongly dependent on their position within the gap and the size of the gap. Results suggest that hardwood and softwood saplings in gaps have greatest growth rates at distances of 0.5–2 m and 1.5–4 m from the gap edge and in openings smaller than 800 m2 and 250 m2, respectively. Gap effects on the height growth of trees in the intact forest were evident up to 30 m and 20 m from gap edges for hardwood and softwood overstory trees, respectively. Our results thus suggest that foresters should consider silvicultural techniques that create many small openings in mixed coniferous deciduous boreal forests to maximize the growth response of both residual and regenerating trees.

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)0.000
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 score0.230
Threshold uncertainty score0.453

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0010.001
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 head0.029
GPT teacher head0.287
Teacher spread0.258 · 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

Citations1
Published2010
Admission routes2
Has abstractyes

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