Shuyi Yang

Dr. Shuyi Yang


Research Focus & Metrics

Academic Career Length

4Years (2023-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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22 December 2023 in New Forests
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Journal Article
Closed access
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SYShuyi Yang
Shuyi Yang
Brian TobinBrian Tobin
Brian Tobin
SBStephen L. Byrne
Stephen L. Byrne
Pedro Álvarez-ÁlvarezPedro Álvarez-Álvarez
Pedro Álvarez-Álvarez
NFNiall Farrelly
Niall Farrelly
COConor O’rEilly
Conor O’rEilly

16 April 2026 in Forests
Verified
Journal Article
Open access
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SYShuyi Yang
Shuyi Yang
HYHaiqian Yu
Haiqian Yu
NFNiall Farrelly
Niall Farrelly
Brian TobinBrian Tobin
Brian Tobin
Sitka spruce (Picea sitchensis (Bong.) Carr.) is among the most commercially important tree species in European and North American forestry, and genetic improvement programmes are therefore essential for promoting its productivity and sustainability. This research emphasises the significance of the breeding programmes. The primary objective of this study was to provide more reliable information on family selection for the improvement programme of Sitka spruce by accounting for competition and environmental heterogeneity effects. Analyses in the present study were carried out on historical inventory data of height (HT) and diameter at breast height (DBH) from a half-sib progeny trial of Sitka spruce in Ireland. Tree measurement data were collected at ages 6, 12, 15 and 20 years. A mixed linear model incorporating spatial and competition terms was applied to estimate genetic parameters of the Sitka spruce population. The direct genetic effects of each family on its own phenotypes and the competition effect on its neighbour’s phenotype were examined over time. The study demonstrated an analytical approach for assessing both genetic as well as environmental aspects of competition in a Sitka spruce progeny trial. The combined model integrating competition and spatial terms (model CS) improved model fit compared with the basic model, which only included the random effects of genetic and experimental design factors (model B), with an AIC difference of up to 3609 between them. Residual error obtained from model CS was usually smaller than from model B, with the greatest reduction of 85%. Furthermore, model CS generally improved the estimation of heritability for growth traits, by up to 241, when compared with model B. In addition, genetic differences in competitive ability among families were also observed. Families with favourable combinations of direct genetic and competitive breeding values were suggested for selection in subsequent cycles of the breeding programme, i.e., families with relatively high direct genetic breeding value but low and consistent competitive breeding value over time. This work develops a practical framework to inform future family selection for Sitka spruce improvement programmes.