Genotype by environment interaction (G×E) refers to the comparative performances of genotypes differing among environments, representing differences in genotype rankings or differences in the level of expression of genetic differences among environments. G×E can reduce heritability and overall genetic gain, unless breeding programmes are structured to address different categories of environments. Understanding the impact of G×E, the role of environments in generating G×E and the problems and opportunities is vital to efficient breeding programme design and deployment of genetic material. We review the current main analytical methods for identifying G×E: factor analytic models, biplot analysis and reaction norm. We also review biological and statistical evidence of G×E for growth, form and wood properties in forest species of global economic importance, including some pines, eucalypts, Douglas-fir, spruces and some poplars. Among these species, high levels of G×E tend to be reported for growth traits, with low levels of G×E for form traits and wood properties. Finally, we discuss possible ways of exploiting G×E to maximise genetic gain in forest tree breeding. Characterising the role of environments in generating interactions is seen as the basic platform, allowing efficient testing of candidate genotypes. We discuss the importance of level-of-expression interaction, relative to rankchange interaction, as being greater than in many past reports, especially for deployment decisions. We examine the impacts of G×E on tree breeding, some environmental factors that cause G×E and the strategies for dealing with G×E in tree breeding, and the future role of genomics.

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Fungal pathogens present a complex challenge for genetic management of forest trees. The need is for disease resistance that withstands mutations and genetic shifts in pathogens. Also desirable are defences against new and dangerous pathogens. An understanding of how hosts and pathogens can continue to coexist should help. Experience from agriculture has allowed modelling of pathosystems, the genetic variations within hosts and pathogens that permit coexistence. While it is impractical to construct a comprehensive model, two phenomena seem generally conducive to stability: a cost of "virulence" in pathogen fitness and a multiplicity of host resistance mechanisms. However, other factors, notably indirect costs of resistance, are very difficult to model. Overall, the diversity of behaviour of models, of the nature of resistance and virulence genes, and of biology of both hosts and pathogens precludes any unique formula for stability. For current crops, genetic diversity offers risk spread for susceptibility to a new and serious pathogen or pathotype. For longer-term breeding, relatively rare resistance may be useful, but pedigreed breeding populations typically entail very finite population sizes. Providing for selecting within improved production populations may therefore be needed. This would give breeders technical challenges, and give forest managers opportunity costs and major logistical challenges.

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