Abstract

Forest tree breeding must undergo significant revisions to adapt to the evolving challenges posed by climate change. Addressing the shifts in environmental conditions requires a comprehensive multidisciplinary approach that includes theoretical work and practical application. Specifically, there is a need to focus on developing new breeding strategies that are theoretically sound and practically feasible, considering the economic constraints of actual tree breeding programs. We present a novel concept utilizing genetic evaluation of multiple traits in forest stands of successive ages across wide ecological ranges. Incorporating genomics allows for detailed genetic evaluation, making use of high-density SNP markers and sophisticated algorithms like GBLUP for genetic parameter estimates. High-throughput phenotyping is conducted using drone-borne lidar technology to capture tree height and survival data across various forest stands. Assisted migration is considered to strategically position genotypes across predicted environmental climatic gradients, thereby accommodating the dynamic nature of ecological shifts. Mathematical optimization acts as an essential component for logistics, guiding the spatial allocation and timely substitution of genotypes to ensure a continually adaptive breeding program. The concept replaces distinct breeding cycles with continuous evaluation and selection, enhancing the rate of genetic response over time.

Keywords

Climate change; Adaptation; Gene diversity; Tree improvement; Genetic evaluation; In situ selection

Published in

Annals of Forest Science
2023, Volume: 80, number: 1, article number: 36
Publisher: SPRINGER FRANCE

SLU Authors

• Garcia Gil, Rosario

  • Department of Forest Genetics and Plant Physiology, Swedish University of Agricultural Sciences
    

Sustainable Development Goals

Take urgent action to combat climate change and its impacts


UKÄ Subject classification

Forest Science


Publication identifier

DOI: https://doi.org/10.1186/s13595-023-01203-w

Permanent link to this page (URI)

https://res.slu.se/id/publ/126652