Forest Health: Blending Genetics and Phenomics to Combat a Non-native Disease in a Changing Climate.

Jeremy Johnson

Speaker Bio:
Dr. Johnson is a forest geneticist with broad research interests geared towards understanding the spatial and temporal patterns of how forests respond to multiple threats associated with global ecological change. He does this by specializing in the use of geographic, landscape ecological, and genetic tools and theory, with the goal of ensuring the long-term health of forests using conservation interventions and management.
Dr. Johnson is an assistant professor in the department of forestry at Michigan State University and an affiliate researcher at the USDA Dorena Genetic Resource Center. Prior to this, he was a postdoc in the School of Forestry at Northern Arizona University and the USDA Dorena Genetics Resource Center, after completing his PhD at Texas A&M University.

Abstract:
White pine blister rust (caused by the non-native fungal pathogen, Cronartium ribicola) and climate change are both impacting the future survival of white pines in North America. Many species of white pine have a suite of strategies (including Major Gene Resistance and Quantitative Disease Resistance), occurring at low population frequencies, for resisting the fungus. Even though resistance occurs in white pines, it can be very difficult to identify trees with a resistance mechanism that could be included in breeding for restoration and reforestation. Here we explore the ability of hyperspectral imaging, combined with a custom motion-control system and machine learning, to identify and track the progression of the disease in order to identify seed sources of potential genetic resistance. Additionally, growing evidence suggests that increased temperatures can interact with resistance genes resulting in less effective defenses against white pine blister rust. We explore the role of climate change on resistance stability in white pine species through a controlled temperature by infection experiment. By combining genetics, phenomics, and empirical approaches we can better plan for the future of our forests and inform management actions.