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Title:Quantifying soil ecosystem services across different spatial scales to improve agricultural nitrogen management
Author(s):Xia, Yushu
Director of Research:Wander, Michelle
Doctoral Committee Chair(s):Mulvaney, Richard
Doctoral Committee Member(s):Yang, Wendy; Guan, Kaiyu; Martin, Nicolas
Department / Program:Natural Res & Env Sci
Discipline:Natural Res & Env Sciences
Degree Granting Institution:University of Illinois at Urbana-Champaign
Degree:Ph.D.
Genre:Dissertation
Subject(s):Nitrogen management
N2O emissions
Ecosystem Services
Process-based modeling
Remote Sensing
Soil Health
Corn nitrogen inputs
Management zone
Abstract:Management-associated soil ecosystem services (ESS) have been widely used to evaluate or interpret management goals such as agricultural productivity and environmental sustainability. However, efforts to quantify ESS are often complicated by controlling factors that vary across scales and interact to influence ecosystem processes. This dissertation explores how these factors vary across scales to inform frameworks used for modeling or estimating ESS by considering soil nitrogen (N) loss. First, a data fusion method was used to provide crop-specific N input data needed at U.S. county-level resolution. At the broad spatial scale, process-based modeling was coupled with improved datasets to estimate soil nitrous oxide (N2O) emissions from the U.S. Corn Belt before modeled results were evaluated using a metadata-based summarizing flux from a variety of management scenarios. At the regional scale, biomass N credits derived from cover crops were estimated by combining remote sensing imagery and site-specific covariates to estimate contributions to plant available N. At the field scale, a strategic sampling design was developed to quantify rain event-induced soil N2O fluxes, which were found to vary with field zones delineated with soil and site-based covariates. Finally, a systematic review of biochemical soil health indicators and their relationships to covariates, management and crop yield, soil organic C (SOC) stocks, and greenhouse gas (GHG) emissions was carried out to improve indicator’s utility for management. This dissertation illustrates the importance of using indicators and covariates to understand how inherent site and soil factors interact with management at different scales.
Issue Date:2021-04-22
Type:Thesis
URI:http://hdl.handle.net/2142/110705
Rights Information:Copyright 2021 Yushu Xia
Date Available in IDEALS:2021-09-17
Date Deposited:2021-05


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