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University of Michigan Biological Station

The University of Michigan Biological Station (UMBS) was founded in 1909.

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New age approach to identifying plant-soil stressors with minimal ecological impact.

Atmospheric
Organismal
Plant Population
Vegetation
Milkweeds
Hyperspectral Imaging
Thermal Imaging
Metabolomics
soil chemistry
Fungi
Gradient
Project Abstract: 
The connection between above and below ground must be addressed in order to get an encompassing understanding of the soil microbiome and the role it plays. For example, plant metabolomics influences soil microbial communities through root exudates, but plant metabolomics and thus root exudates are a product of plant genetics, biotic, and abiotic stresses. Root exudates act as signals indicating nutrient availability, environmental stress, and immune responses within the plant, and thus change across the growing season and impact soil microbial communities. These exudates play a key role in the promotion and inhibition of microbes. To better understand this interaction, I will apply a novel technology in plant-soil interactions: hyperspectral/thermal imaging. Along with this imaging work I will look at the interchange between plant and the soil microbiome and see if we can detect any indicators of stress brought on by environmental conditions and how the microbiome navigates those. These imaging techniques will also allow for nondestructive plant sampling in the field, thus also lessening ecological impact. This technology will magnify the data I can collect at a fraction of the cost and allow me to better address gaps in our understanding of plant metabolomic influences on soil microbial communities.
Investigators: 
white.4048
Status of Research Project: 
Active
Years Active: 
2024 to 2030
Research sites: 
UMBS Station
Methods: 
Objective 1: How does metabolomic diversity in plants influence soil microbial community composition? To address this objective, I will collect rhizosphere soil from 30 genets and 3 plants per genet from the UMBS population, extract DNA and conduct bacterial (16S) and fungal (ITS) metabarcoding to identify microbial community composition. I will use a MANOVA to determine whether plant metabolome and/or soil characteristics predict microbial community composition and conduct a Genome-Wide Association study (GWAS) to determine if there are plant gene regions associated with the microbial community composition. As a first step to validating the use of hyperspectral imaging to metabolomically identify plants I will image genets and correlate spectra with their known metabolome. I will repeat the MANOVA and other analyses using the hyperspectral data. Objective 2: Does variation in Mean Annual Precipitation (MAP) alter plant metabolomes and soil microbial community composition? I will examine the influence of the climatic gradient on common milkweed chemical and other phenotypic traits as well as soil microbiome community composition. I will use resources such as iNaturalist to identify 3 sites containing multiple common milkweed genets at 3 levels of precipitation along the precipitation gradient. I will measure metabolomic traits (cardenolides and latex production) using standard chemical approaches (e.g., gas chromatography) and hyperspectral imaging, and will measure the following phenotypic and phenological traits: plant height, leaf size, leaf shape, seed pod number, seed pod size, seed size, flower number, and flowering time12. I will collect soil microbial community samples as in Objective 1. I will use MANOVA and other multivariate tools to determine if there is a relationship between MAP, plant secondary metabolomes, and plant traits. Objective 3: Does climate history predict responses to variation in climate? To test Objective 3, I will manipulate milkweed genets from across the MAP gradient, water availability, and soil community composition in a greenhouse. I will use hyperspectral and thermal imaging to assess metabolomes in milkweed genets and in response to water availability.