This dataset includes data collected as part of the Abrupt Changes in Ecosystem Services (ACES) project on the composition, income (including consumption and sale of environmental resources), ownership of assets (e.g. farming equipment, household furnishings and own transport) and wellbeing of respondent households in rural Mozambique. Data are also included from a participatory wealth ranking exercise carried out in each village. Data were collected in a total of 27 villages: 7 villages in Mabalane District in Gaza Province, 10 villages in Gurué District in Zambezia Province and 10 villages in Marrupa District in Niassa Province. Data collection was carried out in 2014 and 2015, using a one-off environmentally-augmented household income and assets survey administered by enumerators in the locally appropriate language. The objective of the ACES project was to explore interactions between woodland change, ecosystem services and wellbeing in rural Mozambican households. The study used a space-for-time substitution approach, with villages in each district chosen to represent different points on gradients of land use intensity with respect to the dominant land use types in each district (charcoal production in Mabalane, commercial agriculture in Gurué and subsistence agriculture in Marrupa). Data were collected primarily by researchers based in the School of Geosciences at the University of Edinburgh and at the University of Eduardo Mondlane in Mozambique. All the data collected using the household survey are included in this dataset barring those data which would compromise the anonymity of respondents, such as the names and household coordinates of those interviewed. Full details about this dataset can be found at https://doi.org/10.5285/6d94d084-6c9d-4f81-8a3f-0b82de827858

Data comprise site information (site identifier, name, location, zone of interest, land use type, altitude, slope, topographic position and age of deforest and fallow) and historical information from local people in the Ankeniheny Zahamena forest corridor, Madagascar. Data were collected as part of a project funded by the Ecosystem Services for Poverty Alleviation (ESPA) programme under work package 4 P4GES project, grant references: NE/K008692/1, NE/K010115/1, and NE/K010220-1. Full details about this dataset can be found at https://doi.org/10.5285/5771191f-8c12-40bf-af62-2624876616de

This dataset is a product of the raw HEA (Household Economy Approach) data that were collected in sixteen communities in the Katakwi district, and the raw IHM (Individual Household Method) data that was collected with 42 households in the community of Anyangabella, and 51 households in the community of Kaikamosing. These data were collected in 2018, and consist of multiple aspects of household and individual income sources and expenditure in the Katakwi District. The data were collected to support the analysis of vulnerability levels to further support livelihood impact modelling, and the development of targeted policies to support resilience at household and community level. The data collection team comprised of local, Ugandan partners. All data were collected in the local language and translated into English. Full details about this dataset can be found at https://doi.org/10.5285/e736e22c-f409-49ee-930d-a415ade89e79

Data comprise causal diagrams which show links between aspects that influence the well-being of rural inhabitants (e.g. good quality of food, good family relationships, education, etc) with ecosystem services (e.g. food from trees, wood sticks for construction, firewood, wood for charcoal production, etc.) and their causes (e.g. change in land use) in rural Mozambique. Information was gathered at 20 workshops held in Maputo, Xai Xai, Lichinga, Quelimane, and at village level in the districts of Mabalane, Marrupa and Gurue in 2014 and 2015. The objective of the workshops was to examine aspects that influence well-being and their causes in the miombo woodland area of rural Mozambique. One of the objectives of the project was to construct Bayesian belief networks (BBNs) to model future land use change scenarios in rural Mozambique using a participatory approach, to evaluate the consequences of deforestation in the well-being of the rural population. The data were collected as part of the Abrupt Changes in Ecosystem Services and Wellbeing in Mozambican Woodlands (ACES) project and were funded by the Ecosystem Services for Poverty Alleviation (ESPA) programme, funded by NERC, the Economic & Social Research Council (ESRC) and the Department for International Development (DfID), the three are government organizations from UK. The project was led by the University of Edinburgh, with the collaboration of the Universidad Mondlane, the IIED, and other organizations. Full details about this dataset can be found at https://doi.org/10.5285/14622c4b-8bd4-4624-8ea6-35da7da211cd

This dataset contains the transcripts of interviews and discussion groups from seven villages in the Mabalane district, Gaza province, Mozambique. The seven villages were selected from a forest degradation gradient running from villages with abundant undisturbed forest areas to those with degraded forests, mainly driven by charcoal production. The villages had similar infrastructure, soils, rainfall, and vegetation types. The dataset contains information on seasonality, how availability and use of products from the forest has changed over time (trend analysis), wealth ranking within the villages and differences between wealth statuses, and profiles/characteristics of each village. Interviews were conducted with groups in each village or the leader of the village, between May and September 2014. Data were collected as part of a project funded under the Ecosystem Services for Poverty Alleviation (ESPA) programme. Full details about this dataset can be found at https://doi.org/10.5285/49a70237-c579-4669-b126-3f23d494aba6

Data comprise scenarios of how land use can be in the future and how will it affect ecosystem services in rural Mozambique. The scenarios were constructed from information gathered at five workshops held in Maputo, Xai Xai, Quelimane and Lichinga in 2014 and 2015. The objective of the workshops was to examine aspects that influence well-being (e.g. ecosystem services) and their causes (e.g. change in land use) in the Miombo woodland area of rural Mozambique and identify actions that could contribute to poverty alleviation and biodiversity conservation. The final objective was to construct scenarios of how the land use can be in Mozambique in the future (2035). The data were collected as part of the Abrupt Changes in Ecosystem Services and Wellbeing in Mozambican Woodlands (ACES) project and were funded by the Ecosystem Services for Poverty Alleviation (ESPA) programme, funded by NERC, the Economic & Social Research Council (ESRC) and the Department for International Development (DfID), the three are government organizations from UK. The project was led by the University of Edinburgh, with the collaboration of the Universidad Mondlane, the IIED, and other organizations. Full details about this dataset can be found at https://doi.org/10.5285/97c65c35-1db5-49d5-8ee0-ae5c7b699634

Data comprise location (zone of interest, village name, site code, longitude, latitude, altitude and slope), local tree species name, tree code and tree diameter class of trees selected for direct measurements in the Ankeniheny Zahamena forest corridor, the remains of the evergreen forest of eastern Madagascar. Data were collected as part of a project funded by the Ecosystem Services for Poverty Alleviation (ESPA) programme under work package 4, P4GES project, grant references: NE/K008692/1, NE/K010115/1, and NE/K010220/1. Full details about this dataset can be found at https://doi.org/10.5285/a242e145-21f6-4c3c-b8e4-adce70e50d85

Data comprise counts of damage to palm fronds in mature oil palm (2013-2015), and mature and replanted oil palm (2016-2017) plots as part of a large-scale ecological experiment programme (the Biodiversity and Ecosystem Function in Tropical Agriculture project, established in 2013). Herbivory was measured 17 times in total (every 3-4 months) between April 2013 and August 2017. Eighteen plots were examined across three estates – plots in Ujung Tanjung and Kandista estates were planted in 1987 to 1992 and are mature or over-mature oil palm, while Libo plots (2016-2017 data only) were replanted in 2014. Plots were organised in triplets; in Ujung Tanjung and Kandista, for each triplet one plot was assigned to each of three vegetation treatments: Reduced vegetation cover, normal vegetation management and enhanced vegetation cover. The data contain damage estimated in three ways: by eye for the whole crown, by eye for the 17th frond, and by image processing for 20 leaflets of the 17th frond. Full details about this dataset can be found at https://doi.org/10.5285/c2fbd22c-1ce9-4435-b4b0-e333addef346

This dataset contains the transcripts of interviews on the current structure of the main charcoal supply chains from seven villages in the Mabalane district of Gaza province to Maputo, Mozambique. The seven villages were at different stages of the charcoal production process within similar soils, rainfall, and vegetation types. Semi-structured interviews and focus group discussions were conducted with key informants (e.g. village leaders, charcoal producers, wholesalers, truck drivers and forest officers), from May to October 2014. Data were collected as part of a project funded under the Ecosystem Services for Poverty Alleviation (ESPA) programme. Full details about this dataset can be found at https://doi.org/10.5285/56bae7ce-4798-41a4-b702-2f847952f7ae

This data resource provides plot-level plant occurrence data for the first seven years (2015-2021) of the National Plant Monitoring Scheme (covering the UK, the Channel Islands, and the Isle of Man). Data consist of individual observations of plants, and other habitat characteristics, at the metre-scale; observations are accompanied by percentage cover information recorded according to the Domin frequency-abundance scale commonly used in plant community ecology. Other information provided includes the plot type (size, shape, according to the NPMS classification), the volunteer-recorded NPMS habitat, the date of sampling, and information regarding the spatial location of the plot. Information contained within the metadata file should allow users to reconstruct the sampling history (including gaps) of any plot that has been sampled within the NPMS scheme between 2015 and 2021. This work was supported by the Natural Environment Research Council award number NE/R016429/1 as part of the UK-SCAPE programme delivering National Capability. Full details about this dataset can be found at https://doi.org/10.5285/e742c94f-82a4-43e7-af14-36b131afe81b