Peer-Reviewed Publications at Dr. Kaiyu Guan's group (Google Scholar):

Area 3: Carbon, GHG and crop yield quantification                                                                                                                                   

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Featured publications:

●   Liu, L., Zhou, W., Guan, K.*, Peng, B., Xu, S., Tang, J., Zhu, Q., Till, J., Jia, X., Jiang, C., Wang, S., Qin, Z., Kong, H., Grant, R., Mezbahuddin, S., Kumar, V., and Jin, Z.* (2023) "Knowledge-based artificial intelligence significantly improved agroecosystem carbon cycle quantification". Nature Communications. 15(1), 357.

●   Yang, Q., Liu, L., Zhou, J., Ghosh, R.,Peng, B., Guan, K., , Tang, J., Zhou, W., Kumar, V., Jin, Z.* (2023) "A flexible and efficient knowledge-guided machine learning data assimilation (KGML-DA) framework for agroecosystem prediction in the US Midwest". Remote Sensing of Environment. 299, 113880.

●    Potash, E., Guan, K., Margenot, A. J., Lee, D., Boe, A., Douglass, M., Heaton, E., Jang, C., Jin, V., Li, N., Mitchell, R., Namoi, N., Schmer, M., Wang, S., Zumpf, C.(2023) "Multi-site evaluation of stratified and balanced sampling of soil organic carbon stocks in agricultural fields". Geoderma. 438, 116587.

●    Ye, L., Guan, K., Qin, Z., Wang, S., Zhou, W., Peng, B., Grant, R., Tang, J., Hu, T., Jin, Z., Schaefer, D. (2023) "Improved quantification of cover crop biomass and ecosystem services through remote sensing-based model-data fusion". Environmental Research Letters.

●    Guan, K.*, Jin, Z.*, Peng, B.*, Tang, J.*, DeLucia, E.H., West, P., Jiang, C., Wang, S., Kim, T., Zhou, W., Griffis, T., Liu, L., Yang, W.H., Qin, Z., Yang, Q., Margenot, A., Stuchiner, E.R., Kumar, V., Bernacchi, C., Coppess, J., Novick, K.A., Gerber, J., Jahn, M., Khanna, M., Lee, D., Chen, Z., Yang, S. (2023) "A scalable framework for quantifying field-level agricultural carbon outcomes". Earth-Science Reviews.104462.

●    Qin, Z.*, Guan, K.*, Zhou, W., Peng, B., Tang, J., Jin, Z., Grant, R., Hu, T., Villamil, M.B., DeLucia, E., Margenot, A., Umakant, M., Chen, Z., and Coppess, J. (2023) "Assessing long-term impacts of cover crops on soil organic carbon in the central U.S. Midwestern agroecosystems". Global Change Biology

●      Yang, Y., Liu, L., Zhou, W., Guan, K., Tang, J., Kim, T., Grant, R.F., Peng, B., Zhu, P., Li, Z., Griffis, T.J. and Jin, Z*. (2022) "Distinct driving mechanisms of non-growing season N2O emissions call for spatial-specific mitigation strategies in the US Midwest" Agricultural and Forest Meteorology, 324, p.109108.

●      Zhou, W., Kaiyu, G.*, Peng, B., Margenot, A., Lee, D.K., Tang, J., Jin, Z., Grant, R., DeLucia, E., Qin, Z., Wander, M.M., and Sheng, W. (2022). "How does uncertainty of soil organic carbon stock affect the calculation of carbon budgets and soil carbon credits for croplands in the U.S. Midwest?". Geoderma.

●      Li, Z.*, Guan, K.*, Zhou, W., Peng, B., Jin, Z., Tang, J.,  Grant, R.F., Nafziger, E.D., Margenot, A.J., Gentry, L.E., DeLucia, E.H., Yang, W.H., Cai, Y., Qin, Z., Archontoulis, S., Fernández, F.G., Yu, Z., Lee, D.K., and Yang, Y. (2022). "Assessing the impacts of pre-growing-season weather conditions on soil nitrogen dynamics and corn productivity in the US Midwest" Field Crops Research, 284, 108563.

●      Liu, L., Xu, S., Tang, J., Guan, K., Griffis, J.T., Erickson, M.D., Frie, A.L., Jia, X., Kim, T., Miller, L.T., Peng, B., Wu, S., Yang, Y., Zhou, W., Kumar, V., and Jin, Z. (2022) "KGML-ag: a modeling framework of knowledge-guided machine learning to simulate agroecosystems: a case study of estimating N2O emission using data from mesocosm experiments" Geoscientific Model Development 15, no. 7 (2022): 2839-2858.

●      Potash, R.*, Guan, K.*, Margenot, A., Lee, D., Delucia, E., Wang, S., and Jang, C. (2022)  "How to estimate soil organic carbon stocks of agricultural fields? Perspectives using ex ante evaluation". Geodema, 411, 115693.

●      Vardon, D. R., Sherbacow, B. J., Guan, K., Heyne, J. S., and Abdullah, Z., (2022) "Realizing "Net-Zero-Carbon" sustainable aviation fuel". Joule.

●      Zhou, W.*, Guan, K.*, Peng, B.*, Tang, J., Jin, Z., Jiang, C., Grant R., and Mezbahuddin S. (2021)  "Quantifying carbon budget, crop yields and their responses to environmental variability using the ecosys model for U.S. Midwestern agroecosystems". Agricultural and Forest Meteorology, 307, 108521.

●      Peng,B.*, Guan,K.*, et al. (2020) "Towards a multiscale crop modelling framework for climate change adaptation assessment", Nature Plants, 6(4), 338-348.

●      Peng,B.*, Guan,K.*, Chen,M., Lawrence,D.M., Pokhrel,Y., Suyker,A. et al. (2018) "Improving Maize Growth Processes in the Community Land Model: Implementation and Evaluation", Agricultural and Forest Meteorology, 250-251, 64-89.

●      Sultan,B.*, Guan,K.*, Kouressy,M., Biasutti,M., Piani,C., Hammer,G.L., Mclean,G., and Lobell,D.B. (2014) "Robust features of future climate change impacts on sorghum yields in West Africa", Environmental Research Letters, 9(10).

●      Li,Y.*, Guan,K.* et al. (2019) "Towards building a transparent statistical model for improving crop yield prediction: Modeling rainfed corn in the U.S.", Field Crop Research, 234, 55-66.

●       Qin, Z.*, Guan, K*, Zhou, W., Peng, B., Villamil, B., Jin, Z., Tang, J., Grant, R., Gentry, L., Margenot, A., Bollero, G. and Li, Z., (2021) "Assessing the impacts of cover crops on maize and soybean yield in the U.S. Midwestern agroecosystems". Field Crops Research.

Other Publications:

●      Kimball, B.A. et al. (including Guan, K., Peng, B., Zhou, W.) (2024) "Simulation of soil temperature under maize: An inter-comparison among 33 maize models.". Agricultural and Forest Meteorology. 351, 110003.

●      Lee, Y., Khanna, M., Chen, L., Shi, R., Guest, J., BlancBetes, E., Jiang, C., Guan, K., Hudiburg, T., Delucia, E. (2023) "Quantifying uncertainties in greenhouse gas savings and mitigation costs with cellulosic biofuels". European Review of Agricultural Economics. jbad036.

●      Zhang, J., Guan, K.*, Fu, R.*, Peng, B., Zhao, S., Zhuang, Y. (2023) "Evaluating seasonal climate forecasts from dynamical models over South America". Journal of Hydrometeorology.

●      Zhao, C., Stöckle, C.O., Karimi, T., Nelson, R.L., Evert, F.V.K., Pronk, A.A., Riddle, A.A., Marshall, E., Raymundo, R., Li, Y., Guan, K., Gustafson, D., Hoogenboom, G., and Asseng, S. (2022) "Potential benefits of climate change for potatoes in the United States" Environmental Research Letters.

●      Novick, K.A.*, Metzger, S., Anderegg, W.R., Barnes, M., Cala, D.S., Guan, K., Hemes, K.S., Hollinger, D.Y., Kumar, J., Litvak, M., Lombardozzi, D., Normile, C.P., Oikawa, P., Runkle, B.R., Torn, M. and Wiesner, S. (2022) "Informing Nature-based Climate Solutions for the U.S. with the best-available science". Global Change Biology.

●       Li, R., Lombardozzi, D., Shi, M., Frankenberg, C., Parazoo, N.C., Köhler, P., Yi, K., Guan, K. and Yang, X. (2022). "Representation of leaf‐to‐canopy radiative transfer processes improves simulation of far‐red solar‐induced chlorophyll fluorescence in the Community Land Model version 5". Journal of Advances in Modeling Earth Systems, p.e2021MS002747.

●       Guan,K.*, Caylor,K.K., Good,S.P., Biasutti,M., Medvigy,D., Pan,M., Wood,E.F. and SATO,H. (2014) "Continental-scale impacts of intra-seasonal rainfall variability on simulated ecosystem responses in Africa", Biogeosciences, 11, 6939-6954.

●       Rastogi, B., Miller, J., Trudeau, M., Andrews, A., Hu, L., Mountain, M., Nehrkorn, T., Mund, J., Guan, K., and Alden, C. (2021) "Evaluating consistency between total column CO2 retrievals from OCO-2 and the in-situ network over North America: Implications for carbon flux estimation". Atmospheric Chemistry and Physics.

●       Kim, T., Jin, Z., Smith, T., Yang, Y., Yang, Y., Liu, L., Phillips, K., Guan, K., Hunter, L., and Zhou., W. (2021) "A metamodeling approach to identifying nitrogen loss hotspots and mitigation potential in the US Corn Belt". Environmental Research Letters.

●       Xu, T., Guan, K., Peng, B. and Zhao, L., (2021) "Machine Learning-based Modeling of Spatio-temporally Varying Responses of Rainfed Corn Yield to Climate, Soil and Management in the U.S. Corn Belt", Frontiers in Artificial Intelligence.

●       Benes,B., Guan,K., Lang,M., Long,S., Lynch,J., Marshall-Colon,A., Peng,B., Schnable,J., Sweetlove,L. and Turk,M. (2020) "Multiscale computational models can guide experimentation and targeted measurements for crop improvement", The Plant Journal.

●       Cheng,Y. Huang,M., Chen,M., Guan,K., Bernacchi,C., Peng,B., and Tan,Z. (2020) "Parameterizing Perennial Bioenergy Crops in Version 5 of the Community Land Model Based on Site-Level Observations in the Central Midwestern United States", Journal of Advances for Modeling the Earth System, 12, e2019MS001719.

●       Guan,K., Sultan,B., Biasutti,M., and Lobell,D.B. (2015) "What aspects of future rainfall changes matter for crop yields in West Africa", Geophysical Research Letters, 42(19).

●       Alden,C.B., Miller,J.B., Gatti,L.V., Gloor,M.M., Guan,K., ..., and Diffenbaugh,N.S. (2016) "Regional atmospheric CO2 inversion reveals seasonal and geographic differences in heat and drought impacts in the Amazon", Global Change Biology, 22, 3427-3443.