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Record W2249157947

Effects of early herbaceous and woody vegetation control on eastern white pine.

2005· article· en· W2249157947 on OpenAlexaboutno aff
Doug Pitt, William C. Parker, Andrée E. Morneault, Len Lanteigne, A. Stinson, Frederick W. Bell, Steve Colombo

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicFire effects on ecosystems
Canadian institutionsnot available
Fundersnot available
KeywordsHerbaceous plantGrowing seasonVegetation (pathology)Woody plantCompetition (biology)Environmental scienceShrubAgronomyBiologyForestryEcologyGeography
DOInot available

Abstract

fetched live from OpenAlex

Oral and poster Eastern white pine (Pinus strobus L.) is one of North America’s most valuable softwood species. Historically, it thrived in regions characterized by frequent, low-intensity fires that created favorable regeneration conditions. Declining frequency of such fires, coupled with competition, insect, and disease problems, has seriously impeded white pine regeneration efforts. A greater understanding of the vegetation conditions favoring white pine survival, growth, and stem quality would enable more effective management of early stand conditions in the absence of fire. In 2000, an experiment with 3 installations was initiated to quantify the temporal and spatial effects of woody and herbaceous vegetation on white pine seedlings. A response-surface design is being used to combine and test different durations of herbaceous vegetation suppression (0, 2, and 4 years) with various timings of woody vegetation release (time of planting, after 2 growing season, after 5 growing season, and none). Four different hardwood densities are being studied: 0, 5000, 10000, and 15000 stems per ha. The research sites, situated near North Bay, Ontario, and Doaktown, New Brunswick, address the clearcut and 2 gradients of the shelterwood regeneration systems. After 4 growing seasons, white pine subjected to woody-only competition control had 1.2 to 1.4 times the stem volume of trees left untended, earlier release providing the larger gains. In contrast, pine receiving 2 growing seasons of herbaceous competition control averaged 4.3-fold gains in stem volume over untreated trees. Two seasons of herbaceous control, coupled with woody vegetation control after the 2 growing season or at the time of planting, increased these gains to 6.0and 7.7-fold, respectively. These responses to early vegetation control challenge the current operational strategy of planting, waiting 2 growing seasons, and then broadcast releasing with glyphosate (i.e., providing both woody and herbaceous control after the 2 growing season), which provided 3.0-fold volume gains over untended pine. Moreover, these early growth responses were strongly correlated with observations of seedling physiology and microclimate. In general, low photon flux density and soil moisture content in the top 15 cm of mineral soil were associated with reduced photosynthetic potential of white pine seedlings. Herbaceous vegetation appears to be a greater competitor for soil moisture than woody vegetation during the first two growing seasons after planting, explaining the significant positive gains in white pine growth in response to early herbaceous vegetation control. After the second growing season, woody vegetation, with its rapidly increasing height and leaf area, become greater competitors for both light and soil moisture. Although light levels approached critical levels for white pine growth more rapidly in the shelterwood than in the clearcut, moisture and temperature extremes were moderated in the shelterwood environment. White pine height growth and weevil avoidance were greatest with either an aspen or a mature pine (shelterwood) overstorey, suggesting that early herbaceous vegetation control and maintenance of a moderate overhead canopy may maximize white pine stem growth and quality. 1 Canadian Forest Service, Great Lakes Forestry Centre, 1219 Queen St., E., Sault Ste. Marie, ON. P6A 2E5 Phone: 705-5415610 E-mail: dpitt@NRCan.gc.ca. 2 Ontario Ministry of Natural Resources, Ontario Forest Research Institute, 1235 Queen St. E., Sault Ste. Marie, ON. P6A 5N5. 3 Ontario Ministry of Natural Resources, 3301 Trout Lake Rd., North Bay, ON. P1A 4L7. 4 Canadian Forest Service, Atlantic Forestry Centre, P.O. Box 4000, Fredericton, NB. E3B 5P7 5 Tembec, Canadian Ecology Centre, Box 430, #6905 Hwy 17 W, Mattawa, ON. P0H 1V0.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.002
GPT teacher head0.180
Teacher spread0.178 · 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

Citations1
Published2005
Admission routes1
Has abstractyes

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