Incorporating genetic gain into growth and yield projections for Alberta’s white spruce and lodgepole pine tree improvement programs
Notice bibliographique
Résumé
Forest Management in Alberta, Canada, has been facing challenges from a shrinking forest land-base over the past few decades. Tree improvement is recognized as one of the most efficient approaches in addressing this issue. However, there are still some knowledge gaps limiting the application and benefit assessment of tree improvement programs. Given that white spruce (Picea glauca (Moench) Voss) and lodgepole pine (Pinus contorta var. latifolia Dougl.) are the two most important commercial tree species in Alberta, these species are the focus of this thesis. In this thesis, five chapters are included, with three data chapters (Chapters 2-4) focusing on estimating: 1) genetic gain at rotation age and corresponding growth and yield from improved white spruce and lodgepole pine seedlots; 2) climate change effects on improved white spruce and lodgepole pine performances; and 3) early growth of improved white spruce in mixedwood stands in northeastern Alberta. In Chapter 2, taking advantage of the latest height measurements from progeny trials in the province of Alberta, I adjusted and compared two available age-age correlation equations developed previously by Lambeth (1980) and Rweyongeza (2016). The results indicated that the adjusted Lambeth equations, with re-estimated parameters, were the most accurate for both species and should be incorporated into Alberta’s growth and yield models. The phenotypic age-age correlation showed no significant deviation from the genetic age-age correlation for either species. The stand volume generated from the growth and yield projection system (GYPSY) model using the newly adjusted Lambeth equations showed that white spruce had a higher age-age correlation when given the same selection and rotation ages, and therefore, a higher percentage improvement in volume per hectare compared to lodgepole pine regardless of rotation age. In Chapter 3, the most recent height measurements from progeny and provenance trials, and three Representative Concentration Pathways (RCPs) were selected to incorporate climate change into growth and yield predictions for both species. An adjusted Pooled Transfer Function (PTF) was developed, which relates standardized population height with population climate transfer distance and population climate and was merged with GYPSY using the newly adjusted Lambeth equations to predict the effects of climate change on the growth and yield of unimproved and improved stands in Alberta. The simulation results indicated that height growth was strongly influenced by the mean coldest month temperature (MCMT, averaged over the daily mean temperature) for white spruce and mean annual precipitation (MAP) for lodgepole pine. By 2090, climate change-related growth expansions for white spruce stands are expected to be greater in areas with low provenance MCMT than in areas with high provenance MCMT for both improved and unimproved seedlots, regardless of the RCPs. Unimproved and improved lodgepole pine stands, however, are expected to show decreased height growth in most regions in Alberta. For both species under all three RCPs, improved seedlots will be outgrown by unimproved seedlots in locations where climate change favours height growth, while improved seedlots will retain their growth advantage over unimproved seedlots in locations where climate change shows an overall negative effect on height growth. In Chapter 4, data collected from four Forest Management Units (FMUs) in northeastern Alberta were used. The results indicated that, in the mixed white spruce and trembling aspen (Populus tremuloides Michx.) stands, the improved white spruce seedlot, which originated from a tree improvement program with an approved height gain of 1.9% at a 100-year rotation, did not show any advantage in height or diameter at an early stage. A distance-independent competition index based on Lorimer’s index, that included size ratio between competitor aspen and subject spruce, accounted for most of the variation in averaged diameter and height increments from 2016-2018 (age of trees 8-10 years), when a power function was used in the competition analysis (competition index was the explanatory variable, and averaged diameter and height increments were the response variable). The competition effects on height and diameter growth differed significantly. For both unimproved and improved seedlots across ecosites, height growth was less sensitive to the competition effects than diameter growth. These results in this thesis fill some of the current knowledge gaps, through providing accurate age-age correlation equations and an adjusted PTF to estimate growth and yield of improved forest stands under climate change.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».