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  • The data contains urination metrics including frequency, volume, chemical composition, estimated urine patch N loading rates and metabolomics profile of individual urine events from sheep (Welsh Mountain ewe) grazing a semi-improved upland pasture and a lowland improved pasture located in North Wales, UK. Urine collection studies were run in the spring, summer and autumn of 2016 for the semi-improved site and in autumn of 2016 on the lowland improved pasture. Sheep were housed in urine collection pens and while in the pens, each individual urine event was collected and stored separately. The study was conducted as a wider part of the NERC funded Uplands-N2O project (Grant No: NE/M015351/1). The frequency, volume and chemical composition of individual urine events has implications for nitrogen losses from the grazed pasture ecosystem, including emissions of the powerful greenhouse gas, nitrous oxide, and nitrate leaching. Full details about this dataset can be found at https://doi.org/10.5285/385ec5ab-0c47-46fc-b5df-008ca024296f

  • The dataset consists of observations of aboveground biomass, canopy area, maximum height, stem diameter and sapwood area of Juniperus monosperma (Oneseed Juniper) trees, measured at a site in central New Mexico in 2018 and 2019. In total, 200 stems for sapwood area were measured, and 18 trees for full biomass determinations. Full details about this dataset can be found at https://doi.org/10.5285/871443a9-6634-4eba-abb5-286a1ab58e9b

  • This dataset contains weather conditions, water quality, water chemistry and crustacean zooplankton counts sampled at Loch Leven throughout the year 2019. Loch Leven is a lowland lake in Scotland, United Kingdom. The data were collected as part of a long-term monitoring programme, which began in 1968 and is still underway. Sampling occurs roughly every 2 weeks with laboratory analysis and data processing being performed at the UK Centre for Ecology & Hydrology Edinburgh site. The sampling and processing has been performed under the UK-SCAPE project. Full details about this dataset can be found at https://doi.org/10.5285/e404f64c-ddbc-4e3e-8dca-9bea3d68959a

  • The meteorological data describes the air and soil temperatures, net radiation balance, down-welling photosynthetically active radiation, wind speed, wind direction and the vapour pressure deficit. Data collection was carried out at Cartmel Sands marsh from the 31st of May 2013 till the 26th of January 2015. The Cartmel Sands site is in Morecambe, North West England, and the meteorological tower was situated in the middle of the marsh. This data was collected as part of Coastal Biodiversity and Ecosystem Service Sustainability (CBESS): NE/J015644/1. The project was funded with support from the Biodiversity and Ecosystem Service Sustainability (BESS) programme. BESS is a six-year programme (2011-2017) funded by the UK Natural Environment Research Council (NERC) and the Biotechnology and Biological Sciences Research Council (BBSRC) as part of the UK's Living with Environmental Change (LWEC) programme. Full details about this dataset can be found at https://doi.org/10.5285/b1e2fb9c-8c34-490a-b6ae-2fdf6b460726

  • This dataset consists of mid-infrared (MIR) spectra measured on 427 archived soil samples from arable and grassland habitats across Great Britain in 2007. Data on diffuse reflectance spectra were obtained from subsamples of finely ground soil, recorded as absorbance values for wavenumber range 4000–400 cm-1. The soil samples were collected as part of the Countryside Survey monitoring programme, a unique study or ‘audit’ of the natural resources of the UK’s countryside. The analyses were conducted as part of study aiming to quantify how soil quality indicators change across a gradient of agricultural land management and to identify conditions that determine the ability of different soils to resist and recover from perturbations. Full details about this dataset can be found at https://doi.org/10.5285/d66ca0a6-403d-4f5a-bef1-8ee177f1e1b3

  • This dataset contains information on the fertility and physical characteristics of kākāpō (Strigops habroptilus) eggs laid on Anchor and Whenua Hou islands, New Zealand during the 2018/19 breeding season. Of the 252 total eggs laid, 129 failed to develop; undeveloped eggs were dissected, fixed in formalin, and then inspected using fluorescence microscopy at the University of Sheffield UK. For all eggs, data are provided on mother and clutch of origin, developmental stage reached, and maternal mating behaviour. For dissected undeveloped eggs, additional data include fertilisation status, numbers of sperm visible on the perivitelline layer, egg size and weight, dry eggshell weight, and yolk and albumen weights. Full details about this dataset can be found at https://doi.org/10.5285/cd0e9bc1-bd57-44ae-9fec-2f6239e8726d

  • This dataset consists of soil data for 64 field sites on paired farm sites, with 29 variables measured for soil texture and structural condition, aggregate stability, organic matter content, soil shear strength, fuel consumption, work rate, infiltration rate, water quality and hydrological condition (HOST) data. The study is part of the NERC Rural Economy and Land Use (RELU) programme. A move to organic farming can have significant effects on wildlife, soil and water quality, as well as changing the ways in which food is supplied, the economics of farm business and indeed the attitudes of farmers themselves. Two key questions were addressed in the SCALE project: what causes organic farms to be arranged in clusters at local, regional and national scales, rather than be spread more evenly throughout the landscape; and how do the ecological, hydrological, socio-economic and cultural impacts of organic farming vary due to neighbourhood effects at a variety of scales. The research was undertaken in 2006-2007 in two study sites: one in the English Midlands, and one in southern England. Both are sites in which organic farming has a 'strong' local presence, which we defined as 10 per cent or more organically managed land within a 10 km radius. Potential organic farms were identified through membership lists of organic farmers provided by two certification bodies (the Soil Association and the Organic Farmers and Growers). Most who were currently farming (i.e. their listing was not out of date) agreed to participate. Conventional farms were identified through telephone listings. Respondents' farms ranged in size from 40 to 3000 acres, with the majority farming between 100 and 1000 acres. Most were mixed crop-livestock farmers, with dairy most common in the southern site, and beef and/or sheep mixed with arable in the Midlands. In total, 48 farms were studied, of which 21 were organic farmers. No respondent had converted from organic to conventional production, whereas 17 had converted from conventional to organic farming. Twelve of the conventional farmers defined themselves as practicing low input agriculture. Farmer interview data from this study are available at the UK Data Archive under study number 6761 (see online resources). 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 application is an implementation of a Fuzzy changepoint based approach to evaluate how well numerical models capture local scale temporal shifts in environmental time series. A changepoint in a time series represents a change in the statistical properties of the time series (either mean, variance or mean and variance in this case). These can often represent important local events of interest that numerical models should accurately capture. The application detects the locations of changepoints in two time series (typically one representing observations and one representing a model simulation) and estimates uncertainty on the changepoint locations using a bootstrap approach. The changepoint locations and associated confidence intervals are then converted to fuzzy numbers and fuzzy logic is used to evaluate how well the timing of any changepoints agree between the time series. The app returns individual similarity scores for each changepoint with higher scores representing a better performance of the numerical model at capturing local scale temporal changes seen in the observed record. To use this application, the user will upload a csv file containing the two time series to be compared. This work was supported by Engineering and Physical Sciences Research Council (EPSRC) Data Science for the Natural Environment (DSNE) project (EP/R01860X/1) and the Natural Environment Research Council (NERC) as part the UK-SCAPE programme (NE/R016429/1). Full details about this application can be found at https://doi.org/10.5285/49d04d55-90a7-4106-b8fe-2e75aba228e4

  • This application is an implementation of the Ecological Risk due to Flow Alteration (ERFA) method in R language. This method assesses the potential impact of flow change on river ecosystems. Although the code was developed with a geographical focus on southeast Asia (example datasets are provided for the Mekong River Basin), it can be applied for any location where baseline and scenario monthly river flow time series are available. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. Full details about this application can be found at https://doi.org/10.5285/98ec8073-7ebd-44e5-aca4-ebcdefa9d044

  • Data comprise monitoring records of a population of Gryllus campestris, a flightless, univoltine field cricket that lives in and around burrows excavated among the grass in a meadow in Asturias (North Spain). The area has an altitude range from around 60 to 270 metres above sea level. The data present information on various mating-related activities of male crickets, including age, singing activity, dominance in fights, and lifespan. Data were collected from 2006 to 2016. Full details about this dataset can be found at https://doi.org/10.5285/57c7f153-0f5c-40ef-bf73-e800cb8d4013