Biophysical and socioeconomic determinants of tea expansion: Apportioning their relative importance for sustainable land use policy

Tea expansion, a typical process of regional land use and cover change (LUCC), has raised great concerns on regional sustainability. In this regard, exploring the determinants of tea expansion should provide critical implications for land use policy. It has been widely recognized that LUCC interacts nonlinearly with a set of determinants and their feedbacks should be rather complex. Policy makers are now facing the challenge to identify, apportion, and compare the determinants of regional tea expansion for designing more targeted political intervenes. Our paper utilizes a robust tool, the random forest (RF) regression in particular, to explore the determinants of tea expansion across two periods (1985–2007 and 2007–2016) in Anji County, a typical region of tea production in subtropical China. More specifically, tea is extracted from Landsat imageries and total tea cultivated area acts as the dependent variable. Exploratory variables include 38 potential determinants and these determinants are divided into two categories (biophysical and socioeconomic) at two levels (pixel and village). We obtain some similar findings, though the relative importance of determinants varies with the two periods. In general, biophysical determinants (e.g., topography, soil type, land use in the neighborhood) present greater relative importance than the socioeconomic determinants in both periods. In period 1985–2007, biophysical determinants at pixel level are more essential in governing tea expansion. In period 2007–2016, the relative importance of pixel level biophysical determinants is comparable with that of the village level determinants. Comparisons of the two periods indicate that relative importance of soil type and socioeconomic proximity becomes greater in period 2007–2016, while that of the total employees and non-agricultural population proportion becomes lower. Partial dependency plots are further drawn to visualize the marginal effect of each determinant. We finally propose three options for land use policy towards sustainability. Our study demonstrates that the RF regression is efficient for policy makers to understand the determinants of tea expansion with a nonlinear and complex nature.     

Spatial development policy: changing roles for local and regional authorities in the Netherlands

Implementation of spatial policy involves intervention in the land market. In the Netherlands local government also acts as a land developer. Due to an increase in activities in the land market by private actors and an increase in the geographical scale of economic and social processes, this practice is under threat. This paper analyses the background and evolution of Dutch spatial development policy during the last ten years, from the perspective of governmental directive function for spatial policy. It focuses on the multi-level governance between local and regional governments and between local government and private actors.     

Local biophysical effects of land use and land cover change: towards an assessment tool for policy makers

Land use and land cover change (LULCC) affects the climate through both biogeochemical (BGC) and biophysical (BPH) mechanisms. While BGC effects are assessed at global scale and are at the heart of climate treaties such as the Paris Agreement, BPH effects are totally absent despite their increasingly recognized impact, especially at local scale. This stems from the complexity in characterizing their climate impacts both at local and global scale, which makes it impractical to offer clear advices for the development of climate policies. To overcome this barrier, we built a prototype for an assessment tool to evaluate the local BPH impact of a series of land cover transitions. It relies on a dedicated methodology, based on satellite remote sensing data, that can estimate the local change in near surface air temperature associated with BPH effects of potential LULCC. This tool follows a tiered methodological approach, using transparent methods and mirroring what is currently provided by the IPCC to estimate the BGC effects, i.e. through different levels of increasing methodological complexity, from Tier 1 (i.e. default method and factors) to Tier 2 (i.e. similar to Tier 1 but with higher level of details and complexity) and Tier 3 (i.e. tailored solution to address national circumstances). The prototype tool enables the evaluation of the local impacts of land-related BPH effects, therefore facilitating a scientifically informed and comprehensive assessment of land-based climate policies.     

China's agriculture: drivers of change and implications for China and the rest of world

The overall goal of this article is to identify major changes in China's agriculture/food economy and their implications for both China itself and, more importantly, to the rest of world. China has become one of the fastest‐growing economies in the world since late 1970s. GDP grew at about 10% annually in the past 30 years. China's experience shows the importance of both domestic and external policies in achieving sustainable growth. The results from this study provide significant policy implications to many countries that are currently China's major trade partners or those seeking greater economic and trade relations with China. The main conclusions on the implications of China's rapid economic growth are that China's growth will provide more opportunities than challenges to the rest of the world, on average. Overall, the rest of the world will gain from China's economic expansion though this general conclusion may not hold for some countries.     

Neighborhood socioeconomics,food environment and land use determinants of public health: Isolating the relative importance for essential policy insights

Recent literature has advocated the connection between land use policies with public health promotion. In this regard, examining the land use determinants of public health and isolating the relative importance with other influential factors should provide essential policy insights. However, very limited efforts have been made in this aspect, particularly for the developing countries. Using a case of Wuhan (China), this paper attempts to capture the land use determinants of obesity prevalence among middle-aged adults and to compare the relative importance with neighborhood socioeconomics and food environment. A conceptual framework is first proposed to guide the analysis within a land use policy context. Data are then collected during the China’s National Physical Fitness Survey in 2010 and multivariate linear regression is applied to analyze the district level determinants. Results show that neighborhood socioeconomics, food environment and land use all have significant effects on obesity prevalence among the middle-aged adults. The men obesity is associated with the occupation, education and housing, while women obesity is correlated with income and housing. Women obesity associates with healthy food environment, while men obesity correlates with unhealthy food environment. Open public space is negative to women obesity, and institutional land is negative to men obesity. Greater walkability and street connectivity associate with lower obesity risk for both genders. The variance decomposition demonstrates that food environment is the most important determinant of men obesity, while land use is the most essential determinant of women obesity. For the obesity prevalence among total population, neighborhood socioeconomics are key determinants. Based on our analysis, we finally provide some insights for land use policies that aim at addressing the obesity issue in developing countries.     

Home Bias in Primary Agricultural and Processed Food Trade: Assessing the Effects of National Degree of Uncertainty Aversion

This study investigates the effects of national degrees of uncertainty aversion (unfamiliarity avoidance) on the magnitude of bias towards domestic products rather than imports. The empirical analysis is implemented for primary agricultural and processed food products, using a panel dataset covering trade between and within OECD countries. Primary agricultural products are often blended and associated with reference prices. Conversely, processed food products exhibit higher levels of product differentiation. The empirical results confirm expectations by emphasizing the magnifying effects of uncertainty aversion on home bias in the case of processed food products but not in the case of primary agricultural products. These magnifying effects are primarily associated with processed food products destined for final household consumption. Other results reveal significant variations between different countries (based on geo‐economic and national income categories). Our results also indicate that home bias and uncertainty aversion effects on home bias have not decreased over time. The empirical results remain robust under different estimation methods.     

Developing a holistic approach to the analysis of farmer decision-making: Implications for adaptation policy and practice in developing countries

Smallholder farmers operate within a risky and uncertain context. In addition to climate variability and climate change, social, environmental, institutional, and market-related dynamics affect their agricultural decisions and ability to cope and adapt. In this paper, we develop and apply a set of framing questions to investigate the factors shaping farmer decision-making and how these are situated in pathways of response. Drawing on a literature review of decision-making for risk management, five questions are posed to frame enquiry: what livelihood decisions are undertaken by households, who makes what decisions, when do households make decisions and why do they make them, and how do decision making processes evolve and response pathways arise. This approach conceptualises and explores household decision-making in a holistic manner, moving beyond previous studies that examine smallholder decisions through disciplinary boundaries (e.g. psychology, economics, risk management) or particular theoretical approaches (e.g. bounded rationality, theory of planned behaviour). The framing questions together with key insights from literature are used to design and interpret empirical evidence from Pratapgarh, a tribal-dominated rainfed district in southeast Rajasthan, India. The findings suggest that while resource ownership and access are the main drivers of decision-making, socio-cognitive factors such as perceived adaptive capacity and perceived efficacy to carry out adaptive actions are equally important factors mediating farmer responses. We also find that the holistic approach helps explain how personal motivations and individual perceptions of adaptive capacity interact with socioeconomic, climatic, and agro-ecological dynamics at local and regional scales to mediate risk perception and inform response behaviour. A typology of response pathways demonstrates how different households’ trajectories are determined. Making a case for mixed methods to investigate farmer decision-making holistically, this paper provides an approach that reflects the complex and iterative nature of real farmer decision-making and can be used by researchers, policymakers, and practitioners to better understand and describe decision making and to develop informed policies and interventions.     

Urban sprawl and climate change: A statistical exploration of cause and effect,with policy options for the EU

This study provides a brief evaluation of the relationship between trends in transport emissions and urban land-use by analysing correlation between transport CO₂ emissions data, GDP and population data with land-use change data from the CORINE database for EU Member States between 1990 and 2000.