Quantifying the Potential of Climate Mitigation and Adaptation in the United States Agricultural System with Model-data Integration
Date of Award
Doctor of Philosophy (PhD)
Earth, Atmospheric, and Planetary Sciences
Committee Member 1
Committee Member 2
Committee Member 3
Agriculture is an important sector of U.S. economy. Faced with increasing global food demand driven by population boom, it is necessary to sustain the increasing food production. However, agricultural system is inherently sensitive to climate change and multiple lines of evidence across different spatial scales implied that the future warming will decrease global food production. In this context, this thesis focused on US cropland to investigate its potential in climate mitigation and adaptation by synthesizing the multiple crop models, long term satellite data, official survey data and field experiment. The fundamental questions addressed by this dissertation are: (1) how will the Climate Mitigation Potential (CMP) be varied when considering both biophysical and biogeochemical effects of biofuel crops expansion with different levels of management practices? (2) how will the effectiveness of adopting longer maturity maize cultivars be changed when implemented under future warmer climate? (3) how does heat stress influence maize grain yield across different maize growth stages? In the first study, we used site-level observations of carbon, water, and energy fluxes of biofuel crops to parameterize and evaluate the Community Land Model and estimate CO2 fluxes, surface energy balance, soil carbon dynamics of corn, Switchgrass and Miscanthus ecosystems across the conterminous United States considering different agricultural management practices and land-use scenarios. We found that, using carbon as currency, the CMP of energy crops over croplands and marginal lands is significantly changed from -1.9, 49.1 and 69.3 gC/m2 per year considering only biogeochemical effects to 20.5, 78.5 and 96.2 gC/m2 per year considering both biophysical and biogeochemical effects for corn, Switchgrass and Miscanthus, respectively. The CMP of biophysical effects is dominated by latent heat fluxes. When fertilization and irrigation is applied, the CMP over croplands and marginal lands reaches 79.6, 98.3 and 118.8 gC/m2 per year, respectively. We further found that the CMP over marginal lands is lower than that over croplands. This study highlights that biophysical effects induced from altering surface energy and water balance should be considered to adequately quantify CMP of bioenergy crops at regional scales. In the second study, we argued that shift towards varieties with prolonged grain filling period (GFP) had a much greater contribution to the recent yield trends than previously thought. By using long term satellite data from 2000 to 2015, we identified an average lengthening of GFP of 0.37 days per year over the region, which probably results from variety renewal. An empirical statistical model demonstrated that longer GFP contributed roughly one-quarter (23%) of the yield increase trend by promoting kernel dry matter accumulation, yet less yield benefit was identified in hotter counties. Both official survey data and crop model simulations estimated a similar contribution of GFP trend to yield. If growing degree days that determines the GFP continues to prolong at the current rate for the next 50 years, yield reduction will be lessened with 25% and 18% longer GFP under Representative Concentration Pathway 2.6 (RCP 2.6) and RCP 6.0, respectively. However, this level of progress is insufficient to compensate yield losses in future climates, because drought and heat stress during the GFP will become more prevalent. Our study highlights devising multiple effective adaptation strategies is necessary to withstand the upcoming challenges in food security. For the last study, we integrated crop models, satellite data, statistical data and field experiment data to investigate how increasing temperature influences maize yield through various processes across the US Midwest. Observational data suggests there is a nonlinear increasing temperature sensitivity of maize yield as temperature goes up, which is predominantly determined by sensitivity of harvest index, while the response of biomass growth rate and growing season length is relatively small. Although model ensemble exhibited a similar pattern of temperature sensitivity, the negative impact of warming on harvest index is underestimated. Further analysis shows that the enhanced temperature sensitivity of harvest index mainly results from a higher sensitivity of yield to temperature stress during grain filling period, which accounts for approximate 61% yield reduction. Future warming might influence yield directly through frequent heat stress or indirectly through water stress. Analysis of observational data suggests that high temperature stress is more influential than water stress, especially with warmer climate, while model ensemble shows an opposite result. This discrepancy implies that the yield benefit of increasing atmospheric CO2 might have been overestimated in crop models while direct temperature stress during grain formation is underestimated, because water conservation effect of increasing CO2 brings more yield benefit under water stress conditions but shows limited benefit under heat stress. Our results suggest that, although maize yield has increased significantly in the US, limited progresses have achieved when confronted with heat stress during grain formation, highlighting more efforts are required for future climate adaptation during maize grain formation.
Zhu, Peng, "Quantifying the Potential of Climate Mitigation and Adaptation in the United States Agricultural System with Model-data Integration" (2018). Open Access Dissertations. 1857.