Accounting for competition in multi-environment tree genetic evaluations: a case study with hybrid pines

Abstract

& Key message A novel multi-environment competition individual-tree mixed model resulted in better fit, and greater individual narrow-and broad-sense heritabilities than the model without competition, notably for traits showing competition. In multi-environment tests, the proposed model would allow tree breeders to select genotypes with the best performance in both additive direct and competition breeding values, increasing forest productivity. & Context Genetic merit of trees is known to be affected and interact with local competition effects as well as changes across environmental conditions. Recent studies showed that competition genetic effects can affect the genetic variance and bias the tree breeding values, and its covariance with direct breeding values has been variable across traits. & Aims The present paper extends a mixed-model methodology to the problem of accounting for competition in a multi-environment set of forest genetic trials and exploring its impact on genetic variances as well as the multi-environment genetic correlation. & Methods The proposed model is illustrated using data from two full-sib trials of Pinus elliottii var. elliottii × Pinus caribaea var. hondurensis F 1 . Dispersion parameters and (co)variance of total breeding values were estimated for diameter at breast height, total tree height, and stem straightness at age 10. & Results For traits showing competition effects (diameter at breast height and total tree height), the proposed multi-environment competition model gave better fit than the simpler model. Accounting for competition increased the direct additive variance, reduced the residual variances, and did not change significantly the across-site additive genetic correlation. However, for diameter at breast height, top 5% best genetic rankings showed differences. & Conclusion When traits are strongly affected by inter-tree competition, the use of the proposed model in multi-environment analyses can efficiently identify the phenomenon with general benefits in the fitting of genetic components and open the door to select on the basis of competitiveness.

Inter-plot competition in hybrid maize multi-environment yield trials in Ethiopia can reduce rate of genetic gain

“…This has wider implications in maize breeding in SSA, where maize-growing environments are very diverse, and GEI is common. This is the first study to compare results for GEI between a standard MET analysis and a competition MET model in field crops, however, a similar trend has been reported in forest trees (Belaber et al 2021). Nevertheless, the estimates of genetic correlations between sites for the neighbour effects were very low to high, indicating the presence of high GEI for the competitive effects of the genotypes.…”

“…Competition in a MET setting has previously been reported for forestry trials (Belaber et al 2021), but to our knowledge, this study is the first to extend the model for inter-plot competition to account for the effect of GEI in a two-dimensional spatial array common in field crop breeding trials. The competition MET (C-MET) model partitions the total genetic effects into direct and neighbour effects and estimates the interaction of these genetic effects across sites through genetic variances and covariances in the LMM.…”

“…A comparison between the spatial LMM and a model including competition for random genetic effects as well as residual plot correlation has shown improvements in selection of genotypes based on individual trial results. The same approach was extended to account for the effect of GEI in forest trees (Belaber et al 2021). This method was based on an individual tree model often used in forestry trials (Cappa et al 2015;Tian et al 2020).…”