The dataset contains the radiocarbon age of soil organic matter fractions collected along grassland-to-forest conversion chronosequences across Scotland. Soil samples were collected in summer 2018. In summer 2019, soil samples were fractionated and the radiocarbon age of bulk soil and soil fraction samples determined by accelerator mass spectrometry. Full details about this dataset can be found at https://doi.org/10.5285/0dd45f6f-0536-4ee3-9932-58bac019d2c6

The dataset contains stem respiration (ppm) of 320 trees with DBH (Diameter at breast height) > 26 cm, measured with the EGM-4 (Environmental Gas Monitor for CO2). Data were collected on October 2019. In relation to the soil respiration dataset, it contains soil respiration (µmol CO2m-2 s-1) of different type of collars placed on the forest floor, and measured with the LI – 8100 A soil respiration system. Data were collected from June 2017 to October 2019. In both activities, leak tests were done before collections. All research was conducted in a field site approximately 80 km north of Manaus, in the state of Amazonas, Brasil. Full details about this dataset can be found at https://doi.org/10.5285/591e3708-7ff1-483b-9156-15c721c00daf

This dataset comprises river centrelines, digitised from OS 1:50,000 mapping. It consists of four components: rivers; canals; surface pipes (man-made channels for transporting water such as aqueducts and leats); and miscellaneous channels (including estuary and lake centre-lines and some underground channels). This dataset is a representation of the river network in Great Britain as a set of line segments, i.e. it does not comprise a geometric network.

This dataset presents plant percentage cover by species, average plant cover and species richness for sites along the foredune area of sites distributed between Cape Canaveral (Florida) and Tybee Island (Georgia), USA. Plant cover by species was sampled on three occasions using 0.5 x 0.5m quadrats distributed along 3 transects at up to 28 sites. Observations were conducted in February 2018, July 2018, and January 2019. The coastline was impacted by Hurricane Irma in October 2017 and the data were collected to look at plant composition in coastal foredunes undergoing recovery from the hurricane. The data were collected as part of NERC grant NE/R016593/1, Resilience of a coastal ecosystem following hurricane Irma. Full details about this dataset can be found at https://doi.org/10.5285/100af68f-78e2-4b9d-86b9-5777a5ef38fa

The dataset contains light penetration through the water column at a Durleigh Reservoir in Somerset, England. HOBO Pendant Temperature/Light 8K Data Loggers (Onset) were positioned at 0.5 m, 1.5 m, and 2.5 m depths on a temperature chain Durleigh. The loggers were deployed between 30 May 2018 and 5 October 2018. Full details about this dataset can be found at https://doi.org/10.5285/fc1cf9a7-d7b0-4948-8328-497d6e071950

This dataset contains water temperature measurements at 2 different locations in Durleigh Reservoir in Somerset, England. Water temperatures were measured using RBR SoloT thermistors (measured in °C) and HOBO TidbiT v2 loggers (measured in °F). The dataset consists of water temperature measurements from 2 locations at Durleigh reservoir between 22 February 2018 and 5 October 2018. Measurements were taken at 10 minute intervals. Full details about this dataset can be found at https://doi.org/10.5285/25d34c83-e939-40fd-aa16-6962efb4c731

These data describe the results of a three year (2011-2013) factorial experiment using plant-soil mesocosms testing the effects of biochar on soil biodiversity and soil carbon fluxes. The experimental design comprised three treatments: (1) biochar (absence or presence at 2% w/w); (2) plant type (barley, perennial ryegrass, or unvegetated); and (3) soil texture (sandy clay, sandy silt loam, clay loam). Ecosystem responses measured were net ecosystem exchange of carbon (NEE) & ecosystem respiration (both g CO2 m-2 h-1) and plant biomass (g aboveground and root). Soil biological responses measured were estimates of microbial community structure (fungal-to-bacterial ratio, total phospho-lipid fatty acid (PFLA) nmol g-1 soil) and densities (g-1 soil) of nematode worms and soil microarthropods (Collembola, Acari). The experiment was done at the Centre for Ecology & Hydrology in Penicuik, near Edinburgh in Scotland (UK). Soils used in the experiment were taken from the top 20 cm of the soil profile, from the James Hutton Institute’s Balruderry Farm near Dundee, Scotland, UK (56° 27’ N, 3° 4’ W). This research was funded by a Natural Environment Research Council Open CASE PhD studentship grant (NE/HO18085/1). Full details about this dataset can be found at https://doi.org/10.5285/130369e1-d9c7-436c-bd0c-1ccde4844576

This dataset consists of tick sampling and microclimate data from Exmoor, Richmond and New Forest study sites; as well as ARCGIS risk maps that model tick abundance driven by climate surfaces and host abundance. Tick sampling data (91 files, each representing a day of sampling) indicate tick abundance (distinguishing larvae, nymphs, adult males and adult females), vegetation height, soil moisture, temperature and relative humidity. Static risk map files indicate modeled tick abundance: 251 landcover files for the three sites, as well as 36 ArcView map files. The study is part of the NERC Rural Economy and Land Use (RELU) programme. Many people take pleasure from activities in forests and wild lands in the UK and others are being encouraged to participate. Unfortunately, there are risks and one of the most insidious is the possibility (albeit tiny) of acquiring a disease from wild animals; for example, ticks can be vectors of the bacterial infection leading to Lyme Disease. Both diagnosis and treatment can be problematic so prevention of acquiring such disease is highly desirable. Surprisingly little is known about how best to warn countryside users about the potential for disease without scaring them away or spoiling their enjoyment. Answering such questions was the goal of this project, and required the integration of a diverse set of scientific skills, and an understanding of the views of those who manage countryside, those who have contracted zoonotic diseases and those who access the land. This project combined knowledge from three strands of work, namely risk assessment, risk perception and communication, and scenario analysis. The study sites were selected to provide a range of environmental conditions and countryside use. Peri-urban parkland, accessible lowland forest and heath and remote upland forest were chosen as represented by Richmond Park on the fringe of Greater London, the New Forest in Southern England, and Exmoor in South West England. The following additional data from this same research project are available at the UK Data Archive under study number 6892 (see online resources): Lyme disease risk perception data resulting from tick imagery vignette experiments, Lyme disease patient interviews and surveys, residents and countryside staff focus groups, forest manager interviews, and multiple scoring procedures of animal social representation; as well as Lyme and tick risk communication data resulting from interviews with organisations and content analysis of risk warning information leaflets, Further documentation for this study may be found through the RELU Knowledge Portal and the project's ESRC funding award web page (see online resources).

This dataset contains water chemistry and phytoplankton cell counts collected from 3 different depths at 3 different sites in Durleigh Reservoir in Somerset, England, during 2018. Water samples were collected on 22 Feb, 5 Apr, 20 Apr, 30 May, 13 Jun, 27 Jun, 9 Jul, 24 Jul, 20 Aug, 21 Aug, 22 Aug, 23 Aug, 24 Aug, and 5 Oct 2018. The data available to download includes phytoplankton cell counts (cells/ml), turbidity (NTU), pH, Ammonia (mg/l), total oxidised nitrogen (mg/l) nitrite (mg/l), nitrate (mg/l), ammonium (mg/l), orthophosphate (mg/l), silica (mg/l), Potassium (mg/l), Calcium (mg/l), Geosmin (ng/l), 2-MIB (ng/l), total and soluble manganese, iron, copper, magnesium, zinc, and aluminium (all: mg/l). Full details about this dataset can be found at https://doi.org/10.5285/f5f85f15-8f3a-474c-ae58-7cdeab2a53ca

The dataset contains the weight of fine root (<2 mm) at two soil depths (0-10 cm and 10-30 cm) collected in a field site approximately 80 km north of Manaus, in the state of Amazonas, Brasil. Data were obtained by the in growth core method, in campaigns conducted every three months from 2017 to 2019 in all plots. Full details about this dataset can be found at https://doi.org/10.5285/b3a55011-bf46-40f5-8850-86dc8bc4c85d