Spatial-temporal dynamics of grain yield and the potential driving factors at the county level in China

© 2020 Elsevier Ltd Understanding the spatial-temporal dynamics of grain production and the influencing factors at the county level in China may promote the knowledge of land-use management and local policymaking, which are conducive to food security and the sustainable development of society. This study aims to evaluate China's grain yield (GY) from 2000 to 2014 and investigate the potential driving factors (PDFs) that affect the spatial-temporal dynamics of GY, including land, labor force, capital, and macro-background. Specifically, the locational Gini coefficient and exploratory spatial data analysis (ESDA) were used to characterize the spatial patterns of GY and its correlations with PDFs. Spatial regression models (SRMs) were employed to investigate the spatial dependence of GY on each PDF in 2000, 2005, 2010 and 2014. Results reveal that China's grain production has been on the rise with high-yield regions distributed mainly within the northeastern agricultural regions. Moreover, the proportion of counties in the northeastern agricultural regions with high grain yield has increased, while the number of low-yielding counties has increased in other agricultural regions. This finding highlights the increasing trend of spatial polarization in grain production. The significant bivariate Moran's I (p < 0.05) further revealed a global spatial spillover effect in the spatial correlation of GY and four PDFs. The spatial correlations could be categorized into four types: high GY and high PDFs, high GY and low PDFs, low GY and high PDFs, and low GY and low PDFs. SRMs were capable of quantifying the spatial dependence of GY on various PDFs, thereby revealing that land factors had a substantial effect on the grain production dynamics nationwide. The exploration of the spatial relationships between GY and PDFs provide a reference for formulating scientific and reasonable agricultural policies

Spatiotemporal Patterns of Urban Encroachment on Cropland and Its Impacts on Potential Agricultural Productivity in China

Rapid urbanization and population growth in China have raised great concerns regarding food security caused by the loss of limited cultivated land. In this study, we used remotely sensed data and an agricultural productivity estimation model to characterize the spatiotemporal patterns of the conversion of cropland into urban land and quantify its impacts on agricultural productivity potential during China’s rapid urbanization period, from 1990 to 2010. The results show that urban development has transformed approximately 4.18 Mha, or 2.26%, of the total cropland in China. From 1990 to 2000, approximately 1.50 Mha of cropland was developed, while roughly 1.8 times this amount (2.68 Mha) was converted over the period of 2000 to 2010. Most of the conversion is located in the central and eastern coastal provinces and is mainly concentrated on the periphery of the major urban areas. The transformation has, consequently, caused a 71.45 Tg, or 2.65%, loss of potential light-temperature agricultural productivity (PLTAP); losses were 24.33 Tg in the first decade of the study and 47.11 Tg in the second. At the provincial scale, the largest percentages of PLTAP loss are mainly concentrated in the developed provinces on the eastern coast, such as Shanghai, Beijing, Zhejiang, Tianjin, and Jiangsu. Considering that these areas can accommodate more people and produce higher economic output on unit area of built-up land and, yet, scarce land that can be reclaimed, this study suggests that the dynamic balance of total farmland policy in China should be varied provincially according to the major function of the province. The policy adjustment will help maximize the utilization efficiency of land

TOPICS IN MODELLING ADAPTATION DYNAMICS OF CHINESE AGRICULTURE TO OBSERVED CLIMATE CHANGE

Chinese farmers have adopted multiple adaptation measures to mitigate the negative impact of, and to capture the opportunities brought by, the observed climate change in the last several decades. Such adaptations will continue in the coming decades given the foreseeing climate change. Scientifically assessing such dynamism of suitable agricultural adaptation requires unprecedented efforts of the research community to simulate and predict the interactions among crop growth dynamics, the environment and crop management, and cropping systems at and across various scales. This calls for efforts aiming to quantify the interactions of agro-ecological processes across different scales. This dissertation intends to make scientific contributions in this direction. The leading goal of this dissertation is to develop a cross-scale modeling framework that is capable of incorporating the field agricultural advances into the design and evaluation of regional cropping system adaptation strategies. It then applies this framework to identify feasible cropping system adaptation strategies under observed warmer climate and quantify their potential benefits to the grain production and water sustainability in the major cropping regions in north China. Three objectives of this study are: (1) Develop a cross-scale model-coupling framework between the site level DSSAT model and the regional level AEZ model to improve the AEZ performance in capturing the northern expansion of japonica rice under a warmer climate in the Northeast China Plain. (2) Construct a new wheat-maize cropping systems adaptation strategy to meet the double challenge of maintaining the regional grain production level and recovering local groundwater table in the semi-arid North China Plain, where the persistent overexploitation of groundwater has caused severe environmental damages. (3) Establish a dynamic adaptation strategy to identify the desired water sustainable cropping systems across different localities and to meet the challenge of recovery local groundwater table and minimize the output losses of wheat and then total grain production in the Hebei Plain, where the irrigation water shortage has threatened wheat production and thus potentially compromising China’s food security. This dissertation will improve our understanding of the interactions and interlinkage across multi-scale agro-ecosystems in mitigating the environmental risks associated with the irrigation-intensive farming and in adapting to climate change. The cropping systems adaptation strategies proposed by this dissertation provide scientific basis for future agricultural adaptation policy design compatible with local agro-climatic, land and soil conditions across China

Land cover change from national to global scales:A spatiotemporal assessment of trajectories, transitions and drivers

Changes in global land cover (LC) have significant consequences for global environmental change, impacting the sustainability of biogeochemical cycles, ecosystem services, biodiversity, and food security. Different forms of LC change have taken place across the world in recent decades due to a combination of natural and anthropogenic drivers, however, the types of change and rates of change have traditionally been hard to quantify. This thesis exploits the properties of the recently released ESA-CCI-LC product – an internally consistent, high-resolution annual time-series of global LC extending from 1992 to 2018. Specifically, this thesis uses a combination of trajectories and transition maps to quantify LC changes over time at national, continental and global scales, in order to develop a deeper understanding of what, where and when significant changes in LC have taken place and relates these to natural and anthropogenic drivers. This thesis presents three analytical chapters that contribute to achieving the objectives and the overarching aim of the thesis. The first analytical chapter initially focuses on the Nile Delta region of Egypt, one of the most densely populated and rapidly urbanising regions globally, to quantify historic rates of urbanisation across the fertile agricultural land, before modelling a series of alternative futures in which these lands are largely protected from future urban expansion. The results show that 74,600 hectares of fertile agricultural land in the Nile Delta (Old Lands) was lost to urban expansion between 1992 and 2015. Furthermore, a scenario that encouraged urban expansion into the desert and adjacent to areas of existing high population density could be achieved, hence preserving large areas of fertile agricultural land within the Nile Delta. The second analytical chapter goes on to examine LC changes across sub-Saharan Africa (SSA), a complex and diverse environment, through the joint lenses of political regions and ecoregions, differentiating between natural and anthropogenic signals of change and relating to likely drivers. The results reveal key LC change processes at a range of spatial scales, and identify hotspots of LC change. The major five key LC change processes were: (i) “gain of dry forests” covered the largest extent and was distributed across the whole of SSA; (ii) “greening of deserts” found adjacent to desert areas (e.g., the Sahel belt); (iii) “loss of tree-dominated savanna” extending mainly across South-eastern Africa; (iv) “loss of shrub-dominated savanna” stretching across West Africa, and “loss of tropical rainforests” unexpectedly covering the smallest extent, mainly in the DRC, West Africa and Madagascar. The final analytical chapter considers LC change at the global scale, providing a comprehensive assessment of LC gains and losses, trajectories and transitions, including a complete assessment of associated uncertainties. This chapter highlights variability between continents and identifies locations of high LC dynamism, recognising global hotspots for sustainability challenges. At the national scale, the chapter identifies the top 10 countries with the largest percentages of forest loss and urban expansion globally. The results show that the majority of these countries have stabilised their forest losses, however, urban expansion was consistently on the rise in all countries. The thesis concludes with recommendations for future research as global LC products become more refined (spatially, temporally and thematically) allowing deeper insights into the causes and consequences of global LC change to be determined