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Record W3120093911 · doi:10.3389/ffgc.2020.621752

Effects of Thinning on Dynamics and Drought Resistance of Aspen-White Spruce Mixtures: Results From Two Study Sites in Saskatchewan

2021· article· en· W3120093911 on OpenAlexafffundabout
Philip G. Comeau

Bibliographic record

VenueFrontiers in Forests and Global Change · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicForest ecology and management
Canadian institutionsUniversity of Alberta
FundersNatural Resources Canada
KeywordsThinningBasal areaCrown (dentistry)TaigaEnvironmental scienceSalicaceaeBlack sprucePicea abiesForestryResistance (ecology)AgronomyWoody plantBiologyBotanyGeography

Abstract

fetched live from OpenAlex

Drought stress associated with warm temperatures is causing increased mortality and reduced growth of trees in drier portions of the boreal forests of western Canada with both warming and drought expected to increase over the coming decades. While thinning is often shown to reduce drought stress, there is little information on its effects in stands comprised of mixtures of trembling aspen and white spruce that are common in the forests of this region. This study examined effects of pre-commercial thinning on aspen and spruce growth, response to drought stress, and stand dynamics for two study sites located in Saskatchewan, Canada. In unthinned plots aspen densities declined from initial densities of 40,000 to 200,000 trees ha −1 to 2,639 trees ha −1 at age 26. Twenty-one years after thinning (i.e., at age 26) diameter of aspen and spruce had increased, with largest trees being found at the lowest aspen densities (200 aspen ha −1 for aspen and 0 aspen ha −1 for spruce). Aspen density affected average height but not height of aspen top height trees. Spruce height decreased significantly with increasing aspen density. Crown width and live crown ratio of both aspen and spruce declined with increasing aspen density. Data from cores collected from aspen and spruce indicate significant positive effects of tree size (basal area at beginning of the year), and CMI (Climate Moisture Index) on basal area increment of both aspen and spruce while increasing aspen basal area (m 2 ha −1 ) had negative effects on aspen and spruce growth. Increasing tree size (basal area) and aspen competition (basal area ha −1 ) both had negative effects on drought resistance and resilience for both aspen and spruce. Yield projections provided by the Mixedwood Growth Model (MGM) suggest that the mixture of 1,500 aspen ha −1 and 1,000 spruce ha −1 has the potential to provide a 23% increase in total mean annual increment (MAI) with a single harvest at age 100, compared to unthinned aspen stands, but with a 44% reduction in spruce MAI compared to pure spruce stands. Thinning of aspen to densities below 4,000 trees ha −1 at age 5 resulted in reduced aspen yields but increased spruce yields.

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 score0.271
Threshold uncertainty score0.740

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 studies0.0000.000
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 head0.007
GPT teacher head0.223
Teacher spread0.217 · 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

Citations20
Published2021
Admission routes3
Has abstractyes

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