This dataset was compiled for analyses in the research project ‘Nature's contribution to poverty alleviation, human wellbeing and the SDGs’ (Nature4SDGs) (NERC Grant NE/S012850/1). The dataset integrates secondary data on rural livelihoods, multi-dimensional human wellbeing, household demographics, resource tenure and social-ecological context across 10,971 households in 232 settlements in ten low- and middle-income countries. It primarily draws upon nine existing household surveys, and their associated site descriptions and qualitative interviews. It also draws upon existing global geospatial datasets to provide further village-level information on the social-ecological context. Using this dataset, the Nature4SDGs project is specifically examining multidimensional wellbeing from the use of uncultivated nature; the role of common pool uncultivated resources in reducing income inequalities; and the consumption of wild protein across different social-ecological contexts.Agreed in 2015 by all the countries of the United Nations, the 17 Sustainable Development Goals (SDGs), and their subsidiary targets and indicators, represent a blueprint for enabling humanity to achieve a more sustainable future, one in which all people are able to flourish in peace and prosperity while still protecting the environment on which we all depend. For the SDGs to succeed, we need to be able to (a) measure the progress of relevant indicators and (b) understand which policies and interventions can effectively lead to progress in different indicators. Governments are now starting to report annually on the set of 230 indicators originally identified. However, there is concern that there may be trade-offs between some of the SDGs, e.g. 1 (no poverty) and 15 (life on land). For example, the 2018 SDG report highlights that, despite progress on many fronts, increasing land degradation - caused by competing pressures for food, energy and shelter - threatens the livelihoods of over 1 billion people. To turn trade-offs into synergies, it is important to understand the relationship between nature and people's wellbeing and how this varies for different types of people in varied places. In many cases, marginalised people, whether the poorest or women, have different relationships with nature that are not well represented by data aggregated at national level. For example, improvements in national-level food security indicators may hide the fact that the poorest are getting hungrier. Therefore, to fulfil the SDG's overarching aim to 'leave no-one behind', we need to understand how nature-wellbeing relationships are experienced by marginalised groups so that appropriate policies can be put in place that support everybody. This project will significantly improve our understanding of the complex interactions between people and the environment required to make progress in achieving the SDGs, focusing particularly on SDGs 1 (no poverty), 2 (zero hunger), 10 (reduced inequalities) and 15 (life on land). Our objectives are to: (i) assess the contribution of nature to multidimensional human wellbeing at local level, focusing specifically on the experience of the poorest; (ii) analyse the policies and contextual factors at various scales which drive the observed relationships between nature and wellbeing; and (iii) determine how well local, socially disaggregated nature-wellbeing relationships are reflected in national-level and modelled data used to report on the SDGs. To do this, we will draw on recent data sets from seven projects in the Ecosystem Services for Poverty Alleviation programme and one closely aligned project. These fine-grained social-ecological data sets combine quantitative household survey data with qualitative contextual data from 11 sites in the Global South with varied levels of intervention and degradation. Combining data from these different sites provides us with the unique opportunity to deliver new insights into the contribution of nature to human wellbeing at local level, and how this is influenced by different biophysical, socio-economic and policy factors. Practically, our cross-site comparison will improve understanding of how key policies (particularly related to conservation and agriculture) affect the nature-wellbeing relationship. Furthermore, by drawing on advances in other projects in which we are engaged, we can review how well the local-level nature-wellbeing relationship is reflected in national-level data, thus providing the basis for improving the choice of sustainable development indicators. Additionally, by engaging with policy-makers in the countries where the original data were collected, and particularly in India - where we will have more in-depth impact activities - this project may contribute to more appropriate environment-related policies and interventions which ensure that no-one is left behind.

Compilation of existing datasets, including creation of new variables.