EARLY HEARING DETECTION AND INTERVENTION VIRTUAL CONFERENCE
MARCH 2-5, 2021
(Virtually the same conference, without elevators, airplane tickets, or hotel room keys)
5/20/2019 | 12:00 PM - 12:15 PM | DEVELOPMENT OF A VEGETATION-BASED PREDICTIVE MODEL OF DENITRIFICATION POTENTIAL FOR INLAND WETLANDS OF MICHIGAN | 151 DEF
DEVELOPMENT OF A VEGETATION-BASED PREDICTIVE MODEL OF DENITRIFICATION POTENTIAL FOR INLAND WETLANDS OF MICHIGAN
Wetlands are hotspots for various biogeochemical processes, including denitrification. Denitrification is an important ecosystem process, but it has proven difficult and expensive to measure. As such, more accessible and affordable methods for measuring denitrification potentials in wetlands are necessary. Wetland plants are known to play a significant role in regulating denitrification rates in wetlands through the quantity and quality of the carbon they provide through leaf litter and detritus. By analyzing the relationships between these factors and denitrifying gene abundance, a predictive model capable of estimating denitrification potential in wetlands can be constructed. Soil samples from palustrine marshes of Michigan’s Lower Peninsula were collected and analyzed for the abundance of two denitrification-relevant genes using qPCR to establish a gradient of denitrification potential. We then analyzed the relationships between plant-related variables and this gradient in order to develop a preliminary predictive model of denitrification potential. Further sampling and analysis will aid us in strengthening the model and assessing its predictive capabilities, allowing for it use in monitoring and conservation efforts.
- Bioindicators
- Nitrogen
- Microbial
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Presenters/Authors
Jacob Dybiec
(), Central Michigan University, dybie1jm@cmich.edu;
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Deric Learman
(), Central Michigan University, learman1dr@cmich.edu;
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Donald Uzarski
(), Central Michigan University, uzarsd1g@cmich.edu;
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