Division of Forest and Forest Resources
B4EST: Adaptive BREEDING for productive, sustainable and resilient FORESTs under climate change
End: sep 2022
Start: jan 2018
The goal of B4EST is to increase forest survival, health, resilience and productivity under climate change and naturaldisturbances, while maintaining genetic diversity and key ecological functions, and fostering a competitive EU biobasedeconomy.
Project participantsTore Skrøppa Dario Isidro Ojeda Alayon Thomas Solvin
|Start - end date||01.01.2018 - 30.09.2022|
|Project manager||Arne Steffenrem|
|Division||Division of Forest and Forest Resources|
|Department||Forest Genetics and Regeneration|
B4EST will provide forest tree breeders, forest managers and owners, and policy makers with:
1) better scientificknowledge on adaptation profiles and sustainable productivity, and added value of raw materials in importantEuropean tree species for forestry,
2) new and flexible adaptive tree breeding strategies,
3) tree genotypes of highlyadaptive and economical value,
4) decision-support tools for the choice and use of Forest Reproductive Material(FRM) while balancing production, resilience and genetic diversity, including case studies developed with industrialpartners,
5) integrative performance models to guide FRM deployment at stand and landscape level,
6) economicanalyses of risks/benefits/costs, and
7) policy recommendations.
B4EST will capitalise on the resources developed by past and current EU projects to produce -together with treebreeders, forest managers and owners, and the industry- operational solutions to better adapt forests to climate changeand reinforce the competitiveness of the EU forest-based sector.
To cover the geographical, economic and societal needs of forestry in the EU, B4EST will work with 8 (six native,two non-native) conifers and broadleaves with advanced breeding programmes (Norway spruce, Scots pine, maritimepine, poplars, Douglas-fir, eucalypts) or that are case studies of pest-threatened forests (ash) or valuable non-woodproducts (stone pine).
Our approach will result in a high degree of data and knowledge integration, involving multiple and new targettraits and their trade-offs; genomic information; temporal and spatial assessments in a wide range of environments;stakeholder demands; and forest owner and manager risk perception and acceptability of new breeding strategies.