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Record W4404991189 · doi:10.5593/sgem2024/3.1/s14.42

ASSESSMENT OF THE QUALITY AND PRODUCTIVITY OF LODGEPOLE PINE GROWN IN THE WESTERN PART OF LATVIA

2024· article· en· W4404991189 on OpenAlexaboutno aff
Linards Sisenis, Irina Pilvere, Baiba Jansone, Dace Brizga, Edgars Dubrovskis

Bibliographic record

VenueInternational Multidisciplinary Scientific GeoConference SGEM ... · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicForest ecology and management
Canadian institutionsnot available
Fundersnot available
KeywordsProductivityPinus contortaAgroforestryGeographyForestryForest managementEnvironmental science

Abstract

fetched live from OpenAlex

The research aims to examine the pace of growth of lodgepole pine, the amount of damage caused by biungulates and the quality of trunks for lodgepole pine provenances growing in the western part of Latvia in the areas around Ugale and Kuldiga, identifying the most damage-resistant and promising provenances for cultivation in Latvia. In Latvia, foresters and plant breeders have been working for years to increase the quality and productivity of local tree species, while assessing various forest stand management patterns and trying to reduce the rotation period of stands. Nowadays, because of climate change, i.e. with the climate becoming warmer, it is clear that in the future in Latvia not only a management strategy for the dominant tree species have to be changed but also the possibilities of introducing new tree species suitable for the conditions in Latvia need to be considered to reduce the forest rotation period. At the same time, introducing new tree species requires considering that the tree species must have economic potential, i.e. the wood has prospects for being processed and consumed (e.g. construction) in the local region, as carbon is sequestrated during the growth of the trees and stays in Latvia. Lodgepole pine is one of the tree species that could have prospects for cultivation on an industrial scale in plantations, which was introduced in Latvia at the beginning of the last century. Based on the experience of Swedish foresters in growing lodgepole pine on an industrial scale in the 1980s, experimental lodgepole pine plantations were established in Latvia by using both domestic seeds and those from the natural range in Canada and the United States, as well as from Sweden. The research analysed the following tree inventory data collected from the experimental plantations of lodgepole pines at the ages of 27 and 43 years in the western part of Latvia: the height and diameter of the trees and compared the data for Scots pine grown in identical conditions. In addition, the proportions of trees damaged by deer etc. as well as the proportions of trees with multiple tops and branch-to-stem attachments because these defects significantly reduce the chances of producing quality roundwood assortments in the future were analysed for both species. The data were processed using parametric methods. In an experimental plantation in the area near Ugale, 43-year-old lodgepole pines demonstrated a performance similar to that of Scots pines, with average heights of 18.2 and 18.4 meters and diameters of 19.1 and 19.0 cm, respectively, i.e. the differences were insignificant. In the plantation near Kuldiga, the differences were found significant, as the average height difference between the species was 1.3 m, while the diameter difference was 1.3 cm. It was concluded that lodgepole pines had lower trunk quality and were more damaged by deer. It was also found that the least productive lodgepole pine provenances were more damaged by deer.

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 score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.034
GPT teacher head0.331
Teacher spread0.297 · 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
Published2024
Admission routes1
Has abstractyes

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