DOI: 10.1016/j.foreco.2015.05.027
Scopus记录号: 2-s2.0-84938210735
论文题名: Drivers of genotype by environment interaction in radiata pine as indicated by multivariate regression trees
作者: Gapare W.J. ; Ivković M. ; Liepe K.J. ; Hamann A. ; Low C.B.
刊名: Forest Ecology and Management
ISSN: 0378-1127
出版年: 2015
卷: 353 起始页码: 21
结束页码: 29
语种: 英语
英文关键词: Climate variables
; Genotype by environment interaction
; Multivariate regression trees
; Pinus radiata
; Soil variables
Scopus关键词: Regression analysis
; Climate variables
; Genotype-by-environment interaction
; Multivariate regression trees
; Pinus radiata
; Soil variables
; Forestry
; coniferous tree
; environmental factor
; forest management
; genotype-environment interaction
; multivariate analysis
; plantation forestry
; provenance
; soil ecosystem
; New Zealand
; Pinus radiata
; Radiata
英文摘要: Productivity of forest tree plantations can be maximized by matching genetically adapted planting stock to environments where they perform best. We used multivariate regression tree (MRT) analysis with environmental predictors to quantify and characterize the nature of genotype by environment interactions (G. ×. E) of radiata pine diameter at breast height (DBH) grown in New Zealand. The analysis was carried out for 21 provenance trials, and 48 progeny trials of second-generation selections that are widely used in plantation forestry today. To quantify the maximum variance explained by G. ×. E, we used unconstrained clustering of genotypes based on their performance across all sites. Subsequently, the clustering was constrained by climate and soil variables, i.e. the putative causes for G. ×. E. Unconstrained clustering explained 62% and 58% of the observed G. ×. E variance in provenance and progeny trials, respectively. Constrained clustering explained approximately 50% and 25% of the G. ×. E variance in provenance and progeny trials, respectively. Minimum temperature was identified as an important driver of G. ×. E in both provenance and progeny trials. Environments can be grouped into warm humid sites, where most second-generation selected genotypes performed better, and cold sites, where specific genotypes performed best. Based on the progeny trials, only marginal (ca. 3%) gains can be made by targeted deployment to warm humid sites, but more substantial (approx. 20%) genetic gain can be made on cold sites, compared to current deployment strategies. © 2015 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/65367
Appears in Collections: 影响、适应和脆弱性
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作者单位: CSIRO Agriculture Flagship, GPO Box 1600, Canberra, ACT, Australia; University of Alberta, Department of Renewable Resources, 739 General Services Building, Edmonton, AB, Canada; Scion (New Zealand Forest Research Institute Ltd), Private Bag 3020, Rotorua, New Zealand
Recommended Citation:
Gapare W.J.,Ivković M.,Liepe K.J.,et al. Drivers of genotype by environment interaction in radiata pine as indicated by multivariate regression trees[J]. Forest Ecology and Management,2015-01-01,353