학술논문
Genotype-by-environment interaction in coast redwood outside natural distribution - search for environmental cues
Document Type
Report
Author
Source
BMC Genetics. February 10, 2020, Vol. 21 Issue 1
Subject
Language
English
ISSN
1471-2156
Abstract
Author(s): Jaroslav KlápÅ¡tÄ[sup.1] , Dean Meason[sup.1] , Heidi S. Dungey[sup.1] , Emily J. Telfer[sup.1] , Paul Silcock[sup.2] and Simon Rapley[sup.3] Background Global climate change is expected to alter the net [...]
Background Effective matching of genotypes and environments is required for the species to reach optimal productivity and act effectively for carbon sequestration. A common garden experiment across five different environments was undertaken to assess genotype x environment interaction (GxE) of coast redwood in order to understand the performance of genotypes across environments. Results The quantitative genetic analysis discovered no GxE between investigated environments for diameter at breast height (DBH). However, no genetic component was detected at one environment possibly due to stressful conditions. The implementation of universal response function allowed for the identification of important environmental factors affecting species productivity. Additionally, this approach enabled us to predict the performance of species across the New Zealand environmental conditions. Conclusions In combination with quantitative genetic analysis which identified genetically superior material, the URF model can directly identify the optimal geographical regions to maximize productivity. However, the finding of ideally uncorrelated climatic variables for species with narrow ecological amplitude is rather challenging, which complicates construction of informative URF model. This, along with a small number of tested environments, tended to overfit a prediction model which resulted in extreme predictions in untested environments. Keywords: Climate change, Clonal forestry, Universal response function, Genotype x environment interaction, Sequoia sempervirens
Background Effective matching of genotypes and environments is required for the species to reach optimal productivity and act effectively for carbon sequestration. A common garden experiment across five different environments was undertaken to assess genotype x environment interaction (GxE) of coast redwood in order to understand the performance of genotypes across environments. Results The quantitative genetic analysis discovered no GxE between investigated environments for diameter at breast height (DBH). However, no genetic component was detected at one environment possibly due to stressful conditions. The implementation of universal response function allowed for the identification of important environmental factors affecting species productivity. Additionally, this approach enabled us to predict the performance of species across the New Zealand environmental conditions. Conclusions In combination with quantitative genetic analysis which identified genetically superior material, the URF model can directly identify the optimal geographical regions to maximize productivity. However, the finding of ideally uncorrelated climatic variables for species with narrow ecological amplitude is rather challenging, which complicates construction of informative URF model. This, along with a small number of tested environments, tended to overfit a prediction model which resulted in extreme predictions in untested environments. Keywords: Climate change, Clonal forestry, Universal response function, Genotype x environment interaction, Sequoia sempervirens