This dataset measures the abundance of ant species at baited traps set across twelve trees in four experimental plots in lowland, tropical rainforest. Baited traps were set at 5 m vertical intervals from the ground to as high as possible in the canopy, the stratum of each trap location was recorded. At each height two pairs of baited traps were set, each pair contained one trap baited with carbohydrate (honey and oats) and the second with protein (tuna). Traps within each pair were separated by approximately 20cm were left open for 24 hours. All ants collected were identified to morphospecies level and the species abundance in each trap was recorded. Full details about this dataset can be found at https://doi.org/10.5285/62bf0251-ca8d-4288-a274-0ff6e39b3a3c

Data comprise macroinvertebrate count data (identified to species level), trait and classification information, as well as information on macroinvertebrate biomass and site-specific observations (e.g. canopy cover, habitat type, etc.) collected from the South Fork McKenzie river, Oregon, USA in Autumn 2019 and 2020, and winter of 2021 following the Holiday Farm wildfire in Autumn 2020. Samples were collected from restored and unrestored river reaches to quantify the difference in the response of benthic macroinvertebrate response to wildfire. The study was conducted by the University of Nottingham, with data collected by partners from the US Forest Service, Portland State University, Washington State University and Colorado State University. The work was funded by the Natural Environment Research Council. Full details about this dataset can be found at https://doi.org/10.5285/50119e9c-b6d9-4b72-98c9-588ca1d7c6fe

This dataset contains calculated terrestrial fluxes of methane using static chambers from Stordalen mire, a subarctic peatland (68°20’ N, 19°03’ E) located near Abisko, Northern Sweden . Measurements were carried out during growing season 2013 in three measurement campaigns: 16-27 June (number of sampling occasions, n, = 4), 11-22 August (n=5) and 16-29 September (n=5 for wetland and 4 for birch forest). A total of 60 static chambers were measured, 14 within the birch forest and 46 within the wetland. In addition to fluxes auxiliary measurements such as air and soil temperature, soil moisture and soil nutrients were taken and the vegetation composition was recorded. The data was collected as part of the MAMM project (Methane and other greenhouse gases in the Arctic: Measurements, process studies and Modelling, http://arp.arctic.ac.uk/projects/) funded by the UK Natural Environment Research Council (grant NE/I029293/1). Full details about this dataset can be found at https://doi.org/10.5285/0dc1cdab-0f4f-4564-a863-a4b43335a5d7

This dataset includes stream and rainfall hydrochemistry of the Plynlimon research catchments in Mid Wales. The data cover the period from March 2016 to March 2019. Sampling was carried out fortnightly from March 2016 to July 2017. From August 2017 to November 2018 stream samples were collected every four weeks and the rain sample every two weeks. From December 2018 onwards all samples were collected every four weeks. Data are presented for major anions and cations, pH, conductivity, alkalinity, in-situ measurements of water temperature and stream flow for the six stream locations, and air temperature and volume for the rainfall sites. Stream samples were taken using a grab technique and filtered in the field. Rain samples were collected using bulk precipitation collectors. Fieldwork was carried out by CEH members of staff trained in the fieldwork techniques required. Chemical analysis was carried out by qualified CEH chemists at laboratories at CEH Lancaster and CEH Bangor. The Plynlimon research catchments lie within the headwaters of the River Severn and the River Wye in the uplands of mid-Wales. Intensive and long-term monitoring within the catchments underpins a wealth of hydrological and hydro-chemical research. Monitoring is funded by the Centre for Ecology & Hydrology, and is ongoing since 1968. Full details about this dataset can be found at https://doi.org/10.5285/54fe47f3-778e-4e0b-8cf5-b2fda2473b7f

The dataset consists of the transcripts of expert inputs considering how the conceptual thinking for both ‘smart’ and ‘natural or biophilic’ cities could combine to inform future urban discourses and critically reviewed a set of emerging characteristics that described the interface between these alternative discourses. These inputs include informed practice-based perspectives on themes identified in the literature and comparative assessments, testing the integrating principles identified in the research against business as usual silo approaches, which helped refine the research outcomes. Expert inputs were used to inform the identification of new ways of integrating urban futures discourses, in particular shaping the Smart City – Natural City interface, using Birmingham, UK as a case study. The files include the underlying data provided by a cohort of multi-disciplinary [anonymised] experts who contributed to the research; • the record of the group or table outputs from the Innovation Workshop of 12th September 2017 • copies of photographs of the collective ‘stickies’ contributions at the workshop • the original transcript record of the semi-structured interview conversations • records of Group telephone or meeting conversations • ‘work in progress’ collations of comments received; generated to share with contributors and with co-authors Full details about this dataset can be found at https://doi.org/10.5285/474e090d-4502-432c-b8de-ce9f33571f8e

The file contain groundwater level/depth (WL), Groundwater and Surface Water Quality data (EC (micro-siemens per centimetre or µS/cm), Temperature (degrees C) and pH) for 49 points under fortnightly monitoring relevant to Gro for GooD research project in Kwale County, Kenya. Blank - Data not available. Note this is same dataset as NGDC record number 118189 with extended time series. Gro for GooD: Groundwater Risk Management for Growth and Development

This data set includes over 500 individual flux measurements of nitrous oxide (N2O) from a mixed livestock farm, carried out in 2012 and 2013 using a high-precision flux chamber method. Measurements of soil properties are also reported for each individual flux measurement. Soil pH, temperature moisture content, bulk density and ammonia and nitrate concentrations (extracted via the KCl method) are reported in the data. The data represents arable and grazed fields (cattle and sheep) as well as other sources of N2O from agricultural lands such as barns, manure heaps and silage storage. This data was used to assess farms scale emissions of N2O from a variety of sources over four seasons. Full details about this dataset can be found at https://doi.org/10.5285/54edbdcf-086e-40a7-b2cc-c1e4fcbfbbbc

This dataset consists of plant species presence and abundance in different sizes of plots recorded from the first 100 1km squares across Great Britain in 2019, as part of a rolling soil and vegetation monitoring program of 500 1km squares, repeated every 5 years. The UKCEH Countryside Survey is a unique study or 'audit' of the natural resources of the UK's countryside. The sample sites are chosen from a stratified random sample, based on a 15 by 15 km grid of GB. Surveys have been carried out in 1978, 1984, 1990, 1998 and 2007 by the UK Centre for Ecology & Hydrology (UKCEH) and predecessors, with repeated visits to the majority of squares. The countryside is sampled and surveyed using rigorous scientific methods, allowing us to compare new results with those from previous surveys. In this way, we can detect the gradual and subtle changes that occur in the UK's countryside over time. In addition to vegetation data, soil data are also gathered by the current phase of the Countryside Survey. 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/fd6ae272-aeb5-4573-8e8a-7ccfae64f506

[THIS DATASET HAS BEEN WITHDRAWN]. This dataset consists of 4,397 insect species associated with 679 native plant species, 120 archaeophytes, and 223 neophytes from the Database of Insects and their Food Plants (DBIF). The DBIF details approximately 60,000 interactions between phytophagous insect (and mite) species and plants recorded in Great Britain over the last century, based on a wide variety of sources, including entomological journals and field guides. The data here represents a reduced subset of the full DBIF (13,277 interactions), only including interactions resolved to the species level (insect species x associated with host plant species y), records that have been expertly verified as reliable and included in previous large-scale analyses (Ward 1988; Ward & Spalding 1993; Ward et al. 1995; Ward et al. 2003), and records that are certain to have occurred in Great Britain. Any records originating from captive breeding studies are excluded. Finally, only plants with associated phylogenetic data and native status are included. Host plant distribution size is also included, in addition to a quantification of the distinctiveness of the insect communities found on a subset of the non-native plants. 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/cc6b5e83-a1f4-40d6-bbbb-64366b002418

Data derived from NERC grant NE/I024127/1 1) 36Cl data and supporting chemistry. This folder contains the 36Cl concentration data, data on sample locations on fault planes, major and trace element concentrations, and similar data for upper slope samples. 2) Depth versus density data for trenches in colluvium. This folder contains measurements of weights and volumes of colluvial material removed from trenches for some of the 36Cl sites. These data are used to calculate colluvial densities to inform modelling of the 36Cl data. 3) Field Site Documentation. This folder contains field data and field photographs and movies of the sample sites. It also contains a file that summarises interpretations of the data in this folder, to provide numerical values needed to support modeling the 36Cl data to recover fault slip histories. 4) Google Earth Files to locate sample sites. This folder contains kmz files for Google Earth to locate the sample sites. 5) Terrestrial LiDAR data for each 36Cl sample sites. This folder contains Terrestrial LiDAR data (from a LiDAR on a tripod).