Dispersal of pollen, seeds, or vegetative propagules from intensively bred, exotic, or recombinant DNA modified forest plantations may cause detrimental or beneficial ecological impacts on wild or managed ecosystems. Insertion of genes designed to prevent or substantially reduce dispersal could reduce the risk and extent of undesired impacts. Containment measures may also be required by law or marketplace constraints, regardless of risks or benefits. We discuss: (1) the context for when genetic containment or mitigation systems may be needed;(2) technology approaches and mechanisms; (3) the state of knowledge on genes/genomics of sexual reproduction in forest trees; (4) stability of transgene expression during vegetative growth; (5) simulation studies to define the level of containment needed; and (6) needed research to deliver effective containment technologies. We illustrate progress with several examples from our research on recombinant DNA modified poplars. Our simulations show that even partial sterility can provide very substantial reductions in gene flow into wild trees. We conclude that it is impossible to define the most effective containment approaches, nor their reliability, based on current genomic knowledge and technological tools. Additional genomic and technological studies of a wide variety of options are needed. Studies in field environments are essential to provide data relevant to ecological analysis and regulatory decisions and need to be carried out in phylogenetically diverse representatives of the economically most important taxa of forest trees.

Variation in crop performance is directly affected by the environment in which the plant grows. Analyses and estimation of genotype × environment interactions (G×E) have the potential to provide information about the characteristics of genotypes, identify elite genotypes and suitable environmental conditions, establish breeding objectives, and make recommendations for crop management practices. For the past half century, a variety of statistical models have been used for estimating G×E in plant breeding field experiments to facilitate the allocation of superior genotypes to the target population of environments. The most commonly used models are described in this review starting with linear regression and ANOVA models. We then describe modifications in the form of multiplicative models, models that can accommodate external variables, and mixed effect models. Quantification of differential effects of segments of a genome across environments is shown by exploiting marker × environment (M×E) interactions. We close with a brief overview of some nonparametric concepts that aim to understand genotypic stability.

Cassava (Manihot esculenta Crantz) is an important staple food in sub-Saharan Africa. Breeding experiments were conducted at the International Institute of Tropical Agriculture in cassava to select elite parents. Taking into account the heterogeneity in the field while evaluating these trials can increase the accuracy in estimation of breeding values. We used an exploratory approach using the parametric spatial kernels Power, Spherical, and Gaussian to determine the best kernel for a given scenario. The spatial kernel was fit simultaneously with a genomic kernel in a genomic selection model. Predictability of these models was tested through a 10-fold cross-validation method repeated five times. The best model was chosen as the one with the lowest prediction root mean squared error compared to that of the base model having no spatial kernel. Results from our real and simulated data studies indicated that predictability can be increased by accounting for spatial variation irrespective of the heritability of the trait. In real data scenarios we observed that the accuracy can be increased by a median value of 3.4%. Through simulations, we showed that a 21% increase in accuracy can be achieved. We also found that Range (row) directional spatial kernels, mostly Gaussian, explained the spatial variance in 71% of the scenarios when spatial correlation was significant.

Semidwarfism has been used extensively in row crops and horticulture to promote yield, reduce lodging, and improve harvest index, and it might have similar benefits for trees for short-rotation forestry or energy plantations, reclamation, phytoremediation, or other applications. We studied the effects of the dominant semidwarfism transgenes GA Insensitive (GAI) and Repressor of GAI-Like, which affect gibberellin (GA) action, and the GA catabolic gene, GA 2-oxidase, in nursery beds and in 2-year-old high-density stands of hybrid poplar (Populus tremula 3 Populus alba). Twenty-nine traits were analyzed, including measures of growth, morphology, and physiology. Endogenous GA levels were modified in most transgenic events; GA 20 and GA 8 , in particular, had strong inverse associations with tree height. Nearly all measured traits varied significantly among genotypes, and several traits interacted with planting density, including aboveground biomass, rootshoot ratio, root fraction, branch angle, and crown depth. Semidwarfism promoted biomass allocation to roots over shoots and substantially increased rooting efficiency with most genes tested. The increased root proportion and increased leaf chlorophyll levels were associated with changes in leaf carbon isotope discrimination, indicating altered water use efficiency. Semidwarf trees had dramatically reduced growth when in direct competition with wild-type trees, supporting the hypothesis that semidwarfism genes could be effective tools to mitigate the spread of exotic, hybrid, and transgenic plants in wild and feral populations.