This dataset includes polygons representing ecosystem types (ET) and their respective ecosystem services (ES) and disservices (EDS) in the Luanhe River Basin, with attributes recording 14 ecosystem types (ET), 11 provisioning services (PS), ten regulating services (RS), five cultural services (CS), 7 Ecological integrity indicators (EI), and 11 ecosystem disservices (EDS). Full details about this dataset can be found at https://doi.org/10.5285/2252d8a4-0ef3-403f-b2c3-3f7acbcac1d5

This dataset comprises bird abundance data collected using point count methods in Bedford, Luton and Milton Keynes in the summer of 2014. The purpose of the study was to characterise the variation in breeding bird fauna across a range of urban forms. The data were collected as part of the Fragments, Functions and Flows in Urban Ecosystem Services (F3UES) project, as part of the Biodiversity and Ecosystem Service Sustainability (BESS) framework. Full details about this dataset can be found at https://doi.org/10.5285/e7ab3cd1-98fe-4ac4-ad44-e66aad3f2b74

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 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

The data consist of observations of cover of plant species in permanent quadrats in a nitrogen deposition experiment on a peat bog. The experiment was located at Whim Moss in central Scotland, between 2002 and 2016. Recording of cover was by visual assessment in 40 x 40 cm quadrats. The experiment was designed to look at the change in vegetation composition with different rates of deposition of nitrogen in different forms (ammonia, ammonium, and nitrate). 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/10.5285/65ecd65f-e518-4cf5-85bf-7d93e66fdb96

Data comprise scores (from 0 to 5) of examples of cultural ecosystem services provided by cockles from Portugal, Spain, France, Ireland and the UK. All data were collected using an a priori framework to classify evidenced examples of services during a face-to-face workshop held in Vigo in north-west Spain, 10th April 2018, with 28 participants from eleven organisations. The workshop was followed up over the following months by smaller country-specific meetings, mostly held by teleconference call or video call and by email. The data were collected as part of a research and industry collaboration, under the COCKLES project ‘Co-operation for restoring cockle shellfisheries and its ecosystem services in the Atlantic Area’, co-funded through the European Regional Development Fund (ERDF). Full details about this dataset can be found at https://doi.org/10.5285/a924f41c-ae29-427c-8113-aebe6bc2d349

In two saltmarshes, Old Hall in the Blackwater (southeast England) and Warton Bank in the Ribble (northwest England), we took vegetation and soil samples every six to eight weeks from August/September 2024 to January 2025 to characterise seasonal denitrification and vegetation dynamics. The data includes, vegetation species and diversity; seawater and porewater samples (NO3-, NH4+, PO43-); seawater ion concentrations (Cl-, Na2+, K+, Br-, Mg3+ and Ca2+); moisture and organic matter content in the sediment. A key ecosystem service in coastal systems is the remediation of nutrient pollution through sediment burial, vegetative uptake and microbial processing. Denitrification is a facultative anaerobic process where microbial activity transforms nitrate (NO3-), which in high concentrations can be environmentally harmful, into the environmentally benign dinitrogen gas (N2). Denitrification's magnitude is considered particularly important in saltmarsh systems compared to other habitats, although an intermediate product, nitrous oxide (N2O), can also be given off and contribute to climate change. Full details about this dataset can be found at https://doi.org/10.5285/72962722-bd56-4b3e-b397-90ceec6c821e

This dataset contains information on the location of the count, some environmental variables, and the number of insects of each type counted for the Flower-Insect Timed Count survey as part of the UK Pollinator Monitoring Scheme (PoMS). It covers the years 2017 to 2022 (note that 2017 was a pilot year and has less data than subsequent years). The “public” FIT Count asks volunteer citizen scientists to count the number of insects, identified into broad taxon groups, seen landing on the flowers of a particular target plant within a 50 cm × 50 cm quadrat during a period of ten minutes. The “1 km square” FIT Count uses the same methodology but is carried out by PoMS volunteers and staff as part of the PoMS 1 km square survey, which takes place within a randomly allocated set of 1 km squares across the UK, and also gathers data on pan-trapped insects (see separate dataset). In 2017-2020 the 1 km square survey took place in England, Scotland and Wales only; from 2021 the survey has full UK coverage, but with limited data from Northern Ireland in 2021 which was a pilot year for that country. UK PoMS is co-ordinated by UKCEH, with the following delivery partners up to 2022: the Bumblebee Conservation Trust, Butterfly Conservation, British Trust for Ornithology, Hymettus, Natural History Museum, the University of Reading and University of Leeds. PoMS Steering Group members in 2022 were JNCC, DAERA, Defra, NatureScot, Welsh Government, All-Ireland Pollinators Plan, Natural England, Science and Advice for Scottish Agriculture, Buglife and National Biodiversity Network. Full details about this dataset can be found at https://doi.org/10.5285/699f2172-88c1-44b7-a8f5-a22296a9e2cb

The dataset contains information on the species identity and frequency of all insect-flower interactions recorded in ten birch (Betula spp.) woodland fragments surveyed in 2009 (May-August). The data were collected in two transects (50 x 2m; 15m apart and at least 50m from the woodland edge) randomly situated prior to the onset of flowering in the centre of each wood. Five of the woodland sites were disturbed by cattle grazing, while five were undisturbed. Landowners confirmed that livestock had been absent for at least 70-100 years in undisturbed sites. Where livestock were present, cattle grazing was light to moderate (e.g. 2007: mean = 8.4 cattle ha-1) and long term (mean = 33 years). The dataset comprises 13 columns, 2002 rows and is 218 KB. It gives the site name, geographic coordinates, whether it was disturbed by cattle grazing or not, the wind speed and temperature at time of sampling, the date of sampling, and the identity of the insect and plants interacting (binomial name or recognisable taxonomic unit). Full details about this dataset can be found at https://doi.org/10.5285/4c058d1f-6166-4606-88a2-d2feaf036a2f

[This nonGeographicDataset is embargoed until January 4, 2027]. This dataset comprises whole-leaf and headspace metabolomics of barley plants (Hordeum vulgare) that were root-inoculated with three rhizobacterial treatments: Acidovorax radicis N35, Bacillus subtilis B171, or no bacteria (control). Plants were also either infested with Sitobion avenae aphids or left uninfested as controls. Plants were grown under controlled conditions in glasshouse (leaf extracts) or climate chamber (headspace analysis). The purpose of these experiments was to compare metabolomic profiles across rhizobacterial treatments, and when aphids were feeding on plants, as an assessment of wider-community effects on rhizosphere inoculation of barley plants. Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/e65881be-9dca-4111-8a3b-fb84cf78cf15