Spatial_temporal_dynamics_revised manuscript

1 Spatial-temporal dynamics of grain yield and the potential driving factors at the county level in China Jiawei Pana, Yiyun Chena,b,c *, Yan Zhanga, Min Chena, Bo Luand, Shailaja Fennellc,d, Feng Wanga, Dan Menga, Yaolin Liua, Limin Jiaoa, Jing Wanga a School of Resource and Environmental Sciences, Wuhan University, Wuhan, Hubei Province 430079, China b State Key Laboratory of Soil and Sustainable Agriculture, Chinese Academy of Sciences, Nanjing, 210008, China c Centre of Development Studies, University of Cambridge, Cambridge, CB3 9DT, UK d Department of Land Economy, University of Cambridge, Cambridge, CB3 9EP, UK 10Abstract ： Understanding the spatial-temporal dynamics of grain production and the influencing 11factors at the county level in China may promote the knowledge of land-use management and local 12policymaking, which are conducive to food security and the sustainable development of society This 13study aims to evaluate China’s grain yield (GY) from 2000 to 2014 and investigate the potential 14driving factors (PDFs) that affect the spatial-temporal dynamics of GY, including land, labor force, 15capital, and macro-background Specifically, the locational Gini coefficient and exploratory spatial 16data analysis (ESDA) were used to characterize the spatial patterns of GY and its correlations with 17PDFs Spatial regression models (SRMs) were employed to investigate the spatial dependence of GY 18on each PDF in 2000, 2005, 2010 and 2014 Results reveal that China’s grain production has been on 19the rise with high-yield regions distributed mainly within the northeastern agricultural regions 20Moreover, the proportion of counties in the northeastern agricultural regions with high grain yield 21has increased, while the number of low-yielding counties has increased in other agricultural regions 22This finding highlights the increasing trend of spatial polarization in grain production The 23significant bivariate Moran’s I (p and p