Resilience building of rural livelihoods in PES programmes: A case study in China's Loess Hills

Impact of livelihood capital and rural site conditions on livelihood resilience of farm households: evidence from contiguous poverty-stricken areas in China

Farm households around the world are increasingly exposed to both external and internal shocks and stressors. Enhancing the resilience of farm households to frequent disturbances holds paramount importance in fostering the sustainability of their livelihoods and the revitalization of rural areas. Based on 1500 household samples from 14 contiguous poverty-stricken areas (CPSA) in China, this study explores the causal pathways between livelihood capitals of farm households and rural site conditions of rural communities, as well as quantifying their impacts on farm households' livelihood resilience using structural equation models. In particular, the livelihood resilience of farm households is measured based on the "Exposure-Sensitivity-Adaptability" framework. The results show that livelihood resilience is positively represented by exposure and adaptability, but is negatively correlated with sensitivity. Specifically, households with lower mean health and higher dependency ratio are more sensitive to risks, while exposure to agroforestry pests and diseases will lead farm households to diversify their livelihood activities and increase crop and livestock variety to enhance their adaptability. The livelihood capital of farm households has a significant positive effect on livelihood resilience (β = 0.874, p < 0.001). Rural site conditions have both significant direct and indirect impacts on livelihood resilience, with the direct impact (β =  - 0.207, p < 0.05) being negative and a bit larger than the positive indirect impact (β = 0.163, p < 0.05), as mediated by livelihood capital. The government should, therefore, invest more in health insurance, education and training, financial support, and infrastructure, and implement village planning to enhance both the quality of household livelihood capitals and rural site conditions in CPSA.

Spatio-Temporal Variation and Decomposition Analysis of Livelihood Resilience of Rural Residents in China

The key to sustainable rural development and coordinated regional development is to properly measure the livelihood resilience of rural residents (LRRR), and investigate its regional differences, distribution characteristics, and evolutionary patterns. This study combined the entropy method, the Dagum Gini coefficient and decomposition, kernel density estimation, and convergence analysis to measure the LRRR in 30 provinces of China from 2006 to 2020, and to analyze its regional differences and sources, dynamic distribution, and characteristics of convergence. The LRRR in China overall declined 2006-2020, with an east-to-west spatial gradient toward lower livelihood resilience. Intra-regional differences in LRRR narrowed in the Eastern and Central Regions, while those in the Western Region widened. Inter-regional differences were the main source of differences in LRRR. The LRRRs in most provinces in China were gradually reaching the same level over time (i.e., σ convergence and β convergence). This research provides a factual reference for policies related to reducing inter-provincial differences in the LRRR in China.

Assessment and Promotion Strategy of Rural Resilience in Yangtze River Delta Region, China

The Yangtze River Delta region is the most economically active and open region in China. It is also the region with the most prominent contradictions between urban and rural development. Therefore, it is necessary to strengthen the resilience of the rural areas in this region so that they can develop further with resources and opportunities after sustaining shocks. This study used a weighted TOPSIS method to measure the rural resilience of 153 research units from 2000 to 2019 and then applied the ESDA method to measure the spatial agglomeration or heterogeneity characteristics. The results show that: (1) The rural resilience of this region is higher in the east and lower in the west; (2) rural resilience has obvious spatial agglomeration characteristics, which have undergone a process of shifting from strong to weak before becoming strong again; and (3) the hotspots of rural resilience gradually shifted from Jiangsu to Zhejiang, while the coldspots gradually shifted from Zhejiang to Anhui. Finally, the K-means clustering algorithm was applied to divide all research units into five types: natural capital-dominated areas, productive capital-dominated areas, human capital-dominated areas, social-financial capital-dominated areas and general development areas. Then, the strategies for resilience promotion were proposed accordingly.

Survey data on livelihood assets, activities and outcomes of smallholder farm households in China's Loess Plateau

Smallholders' decisions on land use and their activities and strategies of livelihoods are the critical source of uncertainty in natural resource use and an essential determinant of sustainability challenges. This data article provides a selection of quantitative data from a questionnaire survey on livelihood assets, activities and outcomes of smallholder farm households in Yan'he Township, which lies in the middle part of China's Loess Plateau, one of the representative Grain for Green Project areas [1]. Data include land-use decisions and agronomic practices, fertilisation, use of pesticides, machine and irrigation, farm and non-farm activities, financial performance, and the levels of household income, wellness, and total consumption of food, energy, and education and health care. The survey also covered geographical, demographic and socioeconomic background information on the respondents and their perceptions, incentives, propensities and subjective wellbeing. The survey has supported a couple of research articles that build indicators and indexes for economic, environmental and socio-cultural sustainability dimensions and the resilience building of coupled social-ecological systems. The data presented in this article were analysed using descriptive and inferential statistics and provided at the Mendeley Repository. The data will assist studies on the interrelationships of smallholder livelihoods, ecosystem conservation, interventionist policy and market support, and community capacity building in sustainability science.

Multilevel analysis of factors affecting participants' land reconversion willingness after the Grain for Green Program

Understanding the postprogram land use plans of participants is necessary for the sustainability of the conservation achievements from payments for ecosystem services (PES) programs. Previous studies have analyzed many individual factors affecting participants' reconversion plans after PES programs. However, whether the regional ecosystem services changes caused by PES programs affect reconversion willingness remains elusive. Here, we used the multilevel linear model to determine the effects of regional ecosystem services changes and individual characteristics on participants' land reconversion willingness after the Grain for Green Program (GFGP) in the Yanhe watershed of the Loess Plateau. We found that household income, ecological awareness, and employment changes negatively affected reconversion willingness, while nonfarm employment positively affected it at the individual level. At the regional level, the grain production and water yield changes could influence the reconversion willingness of respondents with different individual characteristics. With improved understanding of the factors affecting reconversion willingness, several suggestions to improve the sustainability of the GFGP were proposed. Our study provides a template for analyzing the multilevel factors that affect the sustainability of other PES programs.

Understanding the Effects of China's Agro-Environmental Policies on Rural Households' Labor and Land Allocation with a Spatially Explicit Agent-Based Model

Understanding household labor and land allocation decisions under agro-environmental policies is challenging due to complex human-environment interactions. Here, we develop a spatially explicit agent-based model based on spatial and socioeconomic data to simulate households' land and labor allocation decisions and investigate the impacts of two forest restoration and conservation programs and one agricultural subsidy program in rural China. Simulation outputs reveal that the forest restoration program accelerates labor out-migration and cropland shrink, while the forest conservation program promotes livelihood diversification via increasing non-farm employment. Meanwhile, the agricultural subsidy program keeps labor for cultivation on land parcels with good quality, but appears less effective for preventing marginal croplands from being abandoned. The policy effects on labor allocation substantially differ between rules based on bounded rational and empirical knowledge of defining household decisions, particularly on sending labor out-migrants and engaging in local off-farm jobs. Land use patterns show that the extent to which households pursue economic benefits through shrinking cultivated land is generally greater under bounded rationality than empirical knowledge. Findings demonstrate nonlinear social-ecological impacts of the agro-environmental policies through time, which can deviate from expectations due to complex interplays between households and land. This study also suggests that the spatial agent-based model can represent adaptive decision-making and interactions of human agents and their interactions in dynamic social and physical environments.

Effects of payments for ecosystem services programs in China on rural household labor allocation and land use: Identifying complex pathways

Payments for Ecosystem Services (PES) is increasingly used in developing countries to secure the sustainable provision of vital ecosystem services. The largest PES programs in the world are embedded in China's new forest policies, which aim to expand forest cover for soil and water conservation and improve livelihoods of rural people. The objective of this study is to identify the complex pathways of impacts of two PES programs - the Conversion of Cropland to Forest Program (CCFP) and the Ecological Welfare Forest Program (EWFP) - on household livelihood decisions, and to quantify the direct and indirect impacts along the identified pathways. We fulfill this objective by developing an integrated conceptual framework and applying a Partial Least Squares-Structural Equation Model (PLS-SEM), based on household survey data from Anhui, China. Labor allocation (for on-farm work, local paid work, local business, and out-migration) and land use decisions (i.e., rent in, maintain, rent out, or abandon cropland) for participating households are key to understand PES program effects on livelihoods. Results show that the PES programs have only small direct effects but significant indirect effects via the mediating factor of capital assets. Moreover, group heterogeneity analysis shows that lower-income households do not benefit any more than the better-off households from the PES, while households with medium wealth increase dependence on agriculture. In addition, household demographics, individual attributes, and geographic settings differ in their impacts on labor allocation and land use decisions. We conclude that CCFP and EWFP programs would be more efficient in conserving the environment while improving the economic welfare of lower-income households if capital assets were taken into account in the design of compensation schemes.

Divergent socioeconomic-ecological outcomes of China's Conversion of Cropland to Forest Program in the subtropical mountainous area and the semi-arid Loess Plateau

China's Conversion of Cropland to Forest Program (CCFP) is one of the world's largest Payments for Ecosystem Services (PES) programs. Its socioeconomic-ecological effects are of great interest to both scholars and policy-makers. However, little is known about how the socioeconomic-ecological outcomes of CCFP differ across geographic regions. This study integrates household survey data, satellite imagery, and statistical models to examine labor migration and forest dynamics under CCFP. The investigation is carried out at two mountainous sites with distinct biophysical and socioeconomic conditions, one in a subtropical mountainous region (Anhui) and the other in the semi-arid Loess Plateau (Shanxi). We found divergent CCFP outcomes on migration behavior, stimulating both local- and distant-migration in the Anhui site while discouraging distant-migration in the Shanxi site, after controlling for factors at the individual, household, community and regional levels. Forest recovery is positively associated with distant-migration in Anhui but with local-migration in Shanxi. Contextual factors interact with demographic-socioeconomic factors to influence household livelihoods in both areas, leading to various socio-ecological pathways from CCFP participation to enhanced forest sustainability. Regional differences should therefore be taken into account in the design of future large-scale PES programs.

Resilience Thinking as a System Approach to Promote China’s Sustainability Transitions

Urban regeneration and rural revitalization are becoming major policy initiatives in China, which requires new approaches for sustainability transitions. This paper reviewed the history of policy reforms and institutional changes and analysed the main challenges to sustainability transitions in China. The urban-rural systems were defined as a complex dynamic social-ecological system based on resilience thinking and transition theory. The notions of adaptation and transformation were applied to compose a framework to coordinate “resilience” with “sustainability”. The findings indicate that China’s urbanization has experienced the conservative development of restructuring socio-economic and political systems (before 1984), the fast industrialization and economic development leaned to cities (1984 to 2002), the rapid urbanization led by land expropriation and investment expansion (2002 to 2012), and the quality development transformation equally in urban and rural areas (since 2012). The sustainability transitions have been challenged by controversial institutional arrangements, concerning population mobility control, unequal social welfare, and incomplete property rights. A series of policy interventions should be designed and implemented accordingly with joint efforts of multiple stakeholders and based on the combined technocratic and bottom-up knowledge derived from proactive and conscious individuals and collectives through context-dependent social networks.