Dynamics of Crop Production and Greenhouse Gas Balance in a Changing Environment: Data-Driven Systems Approach for Sustainable Agriculture in the United States
Type of DegreePhD Dissertation
Forestry and Wildlife Science
Restriction TypeAuburn University Users
MetadataShow full item record
Contemporary agriculture faces multiple pressing challenges, particularly feeding a growing world population and mitigating climate change. During the past several decades, climate change has significantly impacted crop growth and production, undermining the resilience of food systems. Concurrently, management activities such as nitrogen fertilization and intensive tillage have in turn contributed to climate change through increased greenhouse gas (GHG) emissions. To address these challenges and promote sustainable agriculture, it is imperative to understand how historical climate change and human management activities have influenced crop production and agricultural GHG emissions, and the extent to which climate-smart agriculture (CSA) practices can help reduce net soil GHG emissions without compromising crop production. This dissertation delves into these aspects, employing a data-driven systems approach to quantify the impacts of multiple environmental forcings (e.g., climate change, atmospheric CO2 concentration, and nitrogen deposition) and agricultural management practices (e.g., nitrogen fertilization, tillage, rotation, and cover cropping) on the magnitude and spatiotemporal variations of crop production, net GHG balance, and net GHG emissions intensity (GHGI, defined as net soil GHGs emissions per unit of crop production) in U.S. croplands under both historical and future climate scenarios. We first developed a new agricultural module within the framework of the Dynamic Land Ecosystem Model (DLEM) v4.0 by better representing dynamic crop growth processes (e.g., crop-specific phenological development, carbon allocation, yield formation, and biological nitrogen fixation) and agricultural management practices (e.g., nitrogen fertilization, irrigation, tillage, rotation, manure application, and cover cropping). Evaluations against site- and regional-scale observations demonstrate that the newly developed agricultural model effectively simulates the magnitude and spatial and temporal variations in both crop production and net GHG emissions. Combining this new agricultural model and multi-source datasets, we used a data-driven systems approach to quantify U.S. crop yield losses caused by compound droughts and heatwaves. We also analyzed the temporal variations in the sensitivity of U.S. corn-soybean systems to these extreme climate events over the past decades. Results indicate that U.S. corn and soybean yields exhibited heightened sensitivity to short-term droughts (spanning 1-3 months) and heatwaves during their critical reproductive stages. The simultaneous occurrence of droughts and heatwaves exacerbates yield loss substantially, resulting in yield losses of 29.6% for corn and 25.4% for soybean, surpassing the effects of individual extreme events. U.S. corn-soybean systems also showed a decreased sensitivity to concurrent droughts and heatwaves over the past six decades. We further quantified the impacts of natural and anthropogenic factors on the magnitude and spatiotemporal variations of the net soil GHG balance in U.S. croplands during 1960-2018. Results show that U.S. agricultural soils sequestered 13.2±1.16 Tg CO2-C yr-1 in SOC (at a depth of 3.5 m) during 1960-2018 and emitted 0.39±0.02 Tg N2O-N yr-1 and 0.21±0.01 Tg CH4-C yr-1, respectively. Based on the GWP100 metric (global warming potential on a 100-year time horizon), the estimated national net GHG emission rate from agricultural soils was 121.9±11.46 Tg CO2-eq yr-1, thus contributing to climate warming. The sequestered SOC offset ~28% of the climate-warming effects resulting from non-CO2 GHG emissions, and this offsetting effect increased over time. Increased nitrogen fertilizer use was the dominant factor contributing to the increase in net GHG emissions during 1960-2018, explaining ~47% of total changes. In contrast, the adoption of agricultural conservation practices (e.g., reduced tillage) and rising atmospheric CO2 attenuated net GHG emissions from U.S. croplands. By integrating climate forcings from the CMIP6 climate model, we also predicted future crop production, net GHG balance, and GHGI in U.S. croplands under three climate scenarios, including SSP126, SSP245, and SSP585. Results show a significant increase in the national net GHG balance for the SSP245 and SSP585 scenarios, with the most pronounced increase occurring under the high-emission trajectory SSP585, averaging 236 Tg CO2-eq year−1 during 2020-2100. In contrast, the net GHG balance under the 126 scenario remains relatively stable throughout the study period. Crop production shows significant interannual variations but does not exhibit significant trends across all three climate scenarios. This imbalance, where the net GHG balance increases disproportionately compared to crop production, results in an elevated GHGI. For the SSP126, SSP245, and SSP585 scenarios, the GHGI is estimated to be 0.26 CO2-eq Tg−1, 0.34 CO2-eq Tg−1, and 0.42 CO2-eq Tg−1, respectively. The significant increase in both net GHG balance and GHGI is mainly attributed to increased temperatures and atmospheric CO2 concentrations. Additionally, we further predicted the long-term impacts of four CSA practices—no tillage, crop rotation, cover cropping, and N fertilizer reduction—on crop production and net GHG balance in U.S. croplands across various future climate scenarios. Our results suggest that these CSA practices significantly reduced the net GHG balance in U.S. croplands, with average reductions of 18.9% for no tillage, 10.3% for N fertilizer reduction, 28.6% for cover cropping, and 17.8% for crop rotation across the three climate scenarios. Furthermore, while no tillage and N fertilizer reduction only marginally impacted crop production, cover cropping and crop rotation decreased crop production by approximately 14.7% and 18.5%, respectively. Consequently, our findings underscore the imperative for comprehensive, scenario-specific CSA strategies to meet the dual goals of climate change mitigation and food security. This dissertation filled the knowledge gap by comprehensively assessing and predicting the impacts of multiple environmental forcings and human management practices on crop production and net GHG balance in U.S. croplands under both historical and future climate scenarios. The derived results offer important implications for effectively implementing CSA practices to address both climate change and food security issues, which also aligns with carbon neutrality goals and supports the achievement of climate-resilient and sustainable agricultural systems.