Search

The main determinants of agricultural employment are related to households’ access to private assets and the influence of inherited social–economic stratification and power relationships. However, despite the recommendations of rural studies which have shown the importance of multilevel approaches to rural poverty, very few studies have explored quantitatively the effects of common-pool resources and household livelihood capitals on agricultural employment. Understanding the influence of access to both common-pool resources and private assets on rural livelihoods can enrich our understanding of the drivers of rural poverty in agrarian societies, which is central to achieving sustainable development pathways. Based on a participatory assessment conducted in rural communities in India, this paper differentiates two levels of livelihood capitals (household capitals and community capitals) and quantifies them using national census data and remotely sensed satellite sensor data. We characterise the effects of these two levels of livelihood capitals on precarious agricultural employment by using multilevel logistic regression. Our study brings a new perspective on livelihood studies and rural economics by demonstrating that common-pool resources and private assets do not have the same effect on agricultural livelihoods. It identifies that a lack of access to human, financial and social capitals at the household level increases the levels of precarious agricultural employment, such as daily-wage agricultural labour. Households located in communities with greater access to collective natural capital are less likely to be agricultural labourers. The statistical models also show that proximity to rural centres and access to financial infrastructures increase the likelihood of being a landless agricultural labourer. These findings suggest that investment in rural infrastructure might increase livelihood vulnerability, if not accompanied by an improvement in the provisioning of complementary rural services, such as access to rural finance, and by the implementation of agricultural tenancy laws to protect smallholders’ productive assets. Electronic supplementary material The online version of this article (doi:10.1007/s13280-019-01150-9) contains supplementary material, which is available to authorized users.

Climate change is likely to have profound effects on developing countries both through the climate impacts experienced, but also through the policies, programmes and projects adopted to address climate change. Climate change mitigation (actions taken to reduce the extent of climate change), adaptation (actions taken to ameliorate the impacts), and on-going development are all critical to reduce current and future losses associated with climate change, and to harness gains. In the context of limited resources to invest in climate change, policies, programmes, or projects that deliver ‘triple wins’ (i.e. generating climate adaptation, mitigation and development benefits) – also known as climate compatible development – are increasingly discussed by bilateral and multilateral donors. Yet there remains an absence of empirical evidence of the benefits and costs of triple win policies. The purpose of this paper is therefore to assess evidence of ‘triple wins’ on the ground, and the feasibility of triple wins that do not generate negative impacts. We describe the theoretical linkages that exist between adaptation, mitigation and development, as well as the trade-offs and synergies that might exist between them. Using four developing country studies, we make a simple assessment of the extent of climate compatible development policy in practice through the lens of ‘no-regrets’, ‘low regrets’ and ‘with regrets’ decision making. The lack of evidence of either policy or practice of triple wins significantly limits the capacity of donors to identify, monitor or evaluate ‘triple wins at this point in time. We recommend a more strategic assessment of the distributional and financial implications of 'triple wins' policies.

Deltas are dynamic and the relationships between ecosystem services, livelihoods and well-being within them are multi-scalar and often non-linear. Social mechanisms of access and management vary between different bundles of ecosystem services: a social-ecological system approach therefore identifies the trade-offs and interactions which occur across diverse temporal and spatial scales and communities. Although Bangladesh is moving towards a more urbanised future, access to ecosystem services continues to be critical to the well-being of populations in rural areas. However, rights to those services are available to a diminishing few. Current winners and losers from development processes are persistent, and ecosystem services are unlikely to lift the rural poor out of poverty without a complete restructuring of social and economic relations in rural areas.

Social survey and geographical data, stratified by social-ecological systems, are used to analyse multiple measures of poverty, in-depth information on rural livelihoods and coping strategies for populations in the delta region. The resultant dataset provides extensive information on the ways in which households use ecosystem services to generate well-being. Analysis of the data shows that any reliance on provisioning ecosystem services for farming, aquaculture, fisheries or forest products increases the likelihood of households being above the poverty line. However, high levels of ecosystem service use are associated with high levels of well-being only in those with significant land assets and associated social capital. The data also provide a quantitative baseline understanding that is fundamental to the integrated analysis.

A flexible meta-model, the Delta Dynamic Integrated Emulator Model (ΔDIEM), is developed to capture the socio-biophysical system of coastal Bangladesh as simply and efficiently as possible. Operating at the local scale, calculations occur efficiently using a variety of methods, including linear statistical emulators, which capture the behaviour of more complex models, internal process-based models and statistical associations. All components are tightly coupled, tested and validated, and their behaviour is explored with sensitivity tests. Using input data, the integrated model approximates the spatial and temporal change in ecosystem services and a number of livelihood, well-being, poverty and health indicators of archetypal households. Through the use of climate, socio-economic and governance scenarios plausible trajectories and futures of coastal Bangladesh can be explored.

The magnitude and extent of fluvial, tidal and storm surge flooding in coastal Bangladesh are quantified using hydrodynamic numerical models under a series of climate and sea-level rise scenarios to 2100. Fluvial floods occur from July to October and are confined to the northern part of the coastal region. Tidal floods occur in the southern part of the coastal region along the banks of the estuaries and only last a few hours. The flood extents for both types of flood are influenced by sea-level rise and increased upstream river flows. Flooding associated with cyclone landfall and resulting storm surge also increases in extent, with a nearly four times increase by the end of the century in extreme cases, reinforcing the need for a long-term adaptation strategy.

Census and spatial data are used to analyse geographical variations in poverty and identify the key socio-economic and environmental drivers of poverty. Results show a strong clustering of poverty within the study area with multivariate analysis indicating a significant association with environmental predictors. However, whilst increasing intensity of salinity intrusion is significantly associated with poverty, neither large shrimp nor freshwater prawn farms impact on poverty. The strong association identified between salinity intrusion and poverty could be attributed to loss of arable land, reduced agricultural productivity and income, food insecurity, rural unemployment, social unrest, conflicts and forced migration. This analysis provides important inputs to the integrated analysis of coastal Bangladesh and the delta.