Quantifying soil ecosystem services across different spatial scales to improve agricultural nitrogen management

Xia, Yushu

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https://hdl.handle.net/2142/110705 Copy

Description

Title

Quantifying soil ecosystem services across different spatial scales to improve agricultural nitrogen management

Author(s)

Xia, Yushu

Issue Date

2021-04-22

Director of Research (if dissertation) or Advisor (if thesis)

Wander, Michelle

Doctoral Committee Chair(s)

Mulvaney, Richard

Committee Member(s)

• Yang, Wendy
• Guan, Kaiyu
• Martin, Nicolas

Department of Study

Natural Res & Env Sci

Discipline

Natural Res & Env Sciences

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(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.

Graduation Semester

2021-05

Type of Resource

Thesis

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http://hdl.handle.net/2142/110705

Copyright and License Information

Copyright 2021 Yushu Xia

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