Micro- and macro- site variants on genotype by environment interaction in Eucalyptus spp

• Ano de defesa: 2019
• Autor(a) principal: Resende, Rafael Tassinari
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: eng
• Instituição de defesa: Universidade Federal de Viçosa
• Palavras-chave em Português: Eucalipto - Melhoramento genético; Florestas - Manejo; Sistemas de informação geográfica; Genética quantitativa; Genética e Melhoramento Florestal
• Link de acesso: http://www.locus.ufv.br/handle/123456789/24832

This thesis is the combination of three scientific papers addressing the same theme: The genotype by environment interaction (GE) between Eucalyptus spp. clones. The publications are also online in the journal Forest Ecology and Management, and can be accessed through the Digital Object Identifier (DOI) (indicated at the beginning of each chapter). The GE interaction is an extremely important aspect of any breeding program. Without it, little effort would be needed to identify the ideal genotypes for certain planting sites. In addition, a small number of cultivars would be fully recommended for the full range of available environments. This work aimed to bring both theoretical and observational features that causes GA, as well as propose an accurate method of recommending genotypes in continuous environments. Therefore, the first chapter demonstrates that competition between identical clones can be triggered by local environmental variants, and those clones with the highest competitive potential tend to be the most stand productives. This study refers to the understanding that natural forest features are also present in monocultures, indicating that competition, when properly managed, either by modeling or silvicultural formations, may contribute to increased forest productivity. The second chapter quantifies in terms of competition; site quality; and environmental heterogeneity, which of these factors lead to greater genetic differentiation, as well as higher yields. This chapter also addresses, in an original way, the interaction between these components within commercial stands and their relationships with forest productivity. Finally, in the third chapter, an elegant way of making genotypic recommendations with a high level of environmental detail is proposed, combining forest genetic improvement with Geographic Information Systems (GIS). Science is in a transition moment, in which countless modern tools are increasingly available. Silviculture and forest management provide scope for such innovations, both in the study of the complex biological interactions present in a growing forest, and in the optimization of resources aiming to increase the yield and quality of the timber products generated.