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Available DatasetsShowing 10 of 10 results
- UK museum specimen metadata and procrustes distance between left and right forewings, for five bumblebee speciesData comprise the collection label details of museums specimens for five bumblebee species (Bombus hortorum, B. muscorum, B. lapidarius, B. pascuorum and B. sylvarum) from five UK museums (Natural History Museum (London), National Museums Scotland, Oxford University Museum of Natural History, Tullie House Museum and Art Gallery, and World Museum (Liverpool)). The details include species, collector, date collected, location, and caste. The location for each specimen was geotagged using Google Maps’ Geocoding application programming interface. Each specimen had its left and right forewing landmarked, with the wing shapes aligned using a Procrustes alignment, and Procrustes distance between the wings calculated. The data came from a digitisation program as part of a NERC funded Standard Grant awarded to R. Gill (NE/P012574/1) and I. Barnes (NE/P012914/1).1Licence not specifiedabout 2 months ago
- River channel migration and characteristics from 1988 to 2019 at 74 bridges in the PhilippinesThe data set contains the Philippines bridge inventory, river migration geodatabase and source code to assess active river channel change (i.e. planform adjustments) using Landsat 5, 7 and 8 products in Google Earth Engine. The data set contains hydro-morphological and bridge characteristics for 74 bridges (> 200 m deck length) in the Philippines from 1988 to 2019 and is available in .csv and .shp format. For a given region of interest (ROI), the code will extract active river channel masks, calculate similarity coefficients between active river channel masks at decadal intervals and calculate active widths and centreline statistics. The code was used by Boothroyd et al. (in press) to investigate decadal river migration at critical bridge infrastructure in the Philippines.1Licence not specifiedabout 2 months ago
- Sediment yield measurements for fire-affected locations in the United Kingdom (2018-2019), Tenerife (2018-2019) and Australia (2019-2020)This dataset describes sediment yields measured in three different locations and time periods after forest fires in UK, Spain and Australia: - Madre del Agua (Tenerife, Spain): 17/08/18 to 14/11/2019 - Thompson (Victoria, Australia): 13/05/19 to 14/01/2020 - Saddleworth (Manchester, UK): 03/08/18 to 30/10/2019 Data were collected using erosion plots and silt fences at hillslope scale to monitor sediment and ash transport during rain events.1Licence not specifiedabout 2 months ago
- Tsetse trypanosome and endosymbiont data from Hurungwe District, Zimbabwe (2016)The data set includes the results of a laboratory analysis in 2016, investigating the presence of trypanosomes and prevalence of tsetse endosymbionts in tsetse flies. The tsetse flies were sampled in Hurungwe District, Mashonaland West Province, Zimbabwe, from February 2014 to November 2014. Flies were sampled using a combination of Epsilon traps and fly rounds, both established techniques for sampling tsetse. Tsetse were stored prior to laboratory analysis using Polymerase chain reaction (PCR) techniques in 2016. The data include two species of tsetse, Glossina pallidipes and Glossina morsitans morsitans. Trypanosome species investigated include Trypanosoma brucei s.l., T. b. rhodesiense, T. vivax, T. congolense, T. simiae, T.simiae (Tsavo) and T. godfreyi. Endosymbionts included in the study were Sodalis glossinidius and Wolbachia spp. Hurungwe District is the only sleeping sickness focus in Zimbabwe and an increase in cases had been detected in years preceding this study. The objective of the study was to investigate the trypanosome species present in the tsetse population and their association with tsetse endosymbionts. This study was conducted as part of research into the relationship between trypanosomiasis, well-being and ecosystems by the Dynamic Drivers of Disease in Africa Consortium (DDDAC). The research was funded by NERC with support from the Ecosystem Services for Poverty Alleviation Programme (ESPA).1Licence not specifiedabout 2 months ago
- Reservoir inflows and release data, and optimised monthly rule curve ordinates (upper, lower and critical) for Pong and Bhakra reservoirs in Northern IndiaData comprise reservoir inflows and release data (including spills), evaporation loss and optimised monthly rule curve ordinates (upper, lower and critical) for Pong and Bhakra reservoirs in Northern India. Also included in the rule curve data are associated reservoir rationing ratios that can be applied to gross demand when rationing is also indicated. Data contain monthly Inflows, net-evaporation loss and release (all in million cubic metres, i.e. x 10^6 m^3) as simulated by WEAP for the Pong and Bhakra reservoir for the baseline (1989 - 2008); mid-century (2032-2050) and end-century (2082-2100) periods. The future inflows were based on forcing the WEAP model of the basin with climate projections of the GFDL-CM3 CMIP model The data were collected by Heriot-Watt University under the Sustaining Himalayan Water Resources in a Changing Climate (SusHi-Wat) project funded by NERC.1Licence not specifiedabout 2 months ago
- Biophysical measurements from Ethiopia's Awassa region during the drought and subsequent floods of 2015-2016This dataset contains the biophysical measurements (mineral nitrogen, percent carbon, percent nitrogen, percent soil moisture, particle size analysis and aggregate stability) from soil collected from farmers' fields in the Halaba district, Southern Nations, Nationalities and Peoples' Region in Ethiopia, after the drought of 2015-2016. Eighteen farms from four kebeles (Asore, Lay Arisho, Konicha and 1st Choroko) were sampled. Soil cores were taken from fields classed as 'home', 'near' and 'far' from the homestead and were taken from two depths (0-20cm and 20-50cm). Soil cores were taken after the El Niño event of 2015/16, so reflect the resilience of different areas of the farm to drought. This dataset was collected as part of the NERC-funded project Building Resilience in Ethiopia's Awassa region to Drought (BREAD).1Licence not specifiedabout 2 months ago
- Fortnightly soil respiration and related measurements from Climoor field site in Clocaenog Forest (2015-2016)The data resource comprises of two datasets. The first dataset comprises of fortnightly measurements soil respiration, soil temperature, soil moisture and photosynthetic activity. The second data set comprises of fortnightly measurements of rainfall, throughfall and water table depth. Data were collected from the climate change field site Climoor that is located in Clocaenog forest, Northeast Wales during 2015 and 2016. The experimental field site consists of three untreated control plots, three plots where the plant canopy air is artificially warmed during night time hours and three plots where rainfall is excluded from the plots at least during the plants growing season (March to September,) All measurements of this dataset have been carried out every fortnight if not indicated otherwise. Rainfall in millimetres (mm) was measured at the site using a ground-level rain gauge. Rain throughfall (in mm) was measured in each plot using a funnel-bottle construction to collect rain water in the plant canopy. Water table depth was measured for each plot using a measuring tape. Soil respiration and related soil temperature and soil moisture were measured in three areas of each plot. Soil respiration was measured in pre-installed opaque soil collars (20 centimetre diameter) that were installed in 1999. An infra-red gas analyser (EGM-4) was used. Photosynthetic active radiation was measured above the canopy while the soil respiration measurement was conducted. The measurements were carried out by different groups of CEH Bangor staff. The Climoor field experiment intends to answer questions regarding the effects of warming and drought on ecosystem processes. Plot level soil respiration measurements are important to investigate soil carbon dynamics and changes in soil carbon cycling and storage under the imposed climatic treatments. More detailed information about the field site, measurements and related datasets can be found in the supporting documentation. Soil respiration data for 1999-2015 are available from https://doi.org/10.5285/4ed6f721-b23b-454e-b185-02ba54d551f01Licence not specifiedabout 2 months ago
- Surface temperature, surface oxygen, water clarity, water chemistry and phytoplankton chlorophyll a data from Windermere South Basin, 2014 to 2018This is part of an ongoing long-term monitoring dataset of surface temperature, surface oxygen, water clarity, water chemistry and phytoplankton chlorophyll a from fortnightly sampling at the South Basin of Windermere in Cumbria, England that began in 1945 for some variables. The data have been collected by the UK Centre for Ecology & Hydrology (UKCEH). The data available to download comprise surface temperature (TEMP) in degree Celsius, surface oxygen saturation (OXYG) in % air-saturation, Secchi depth (SECC) in metres, alkalinity (ALKA) in µg per litre as CaCO3 and pH. Ammonium (NH4N), nitrate (NO3N), soluble reactive phosphate (PO4P), total phosphorus (TOTP), dissolved reactive silicon expressed as SiO2 (SIO2) and phytoplankton chlorophyll a (TOCA) are all given in µg per litre. Water samples are based on a sample integrated from 0 to 7m. Measurements are made from a boat at a marked location (buoy) at the deepest part of the lake. All data are from January 2014 until the end of 2018. 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.1Licence not specifiedabout 2 months ago
- High-resolution global topographic index valuesThe topographic index is a hydrological quantity describing the propensity of the soil at landscape points to become saturated with water as a result of topographic position (i.e. not accounting for other factors such as climate that also affect soil moisture but are accounted for separately). Modern land surface models require a characterisation of the land surface hydrological regime and this parameter allows the use of the TOPMODEL hydrological model to achieve this .This Geographic Information System layer is intended for use as topographic ancillary files for the TOPMODEL routing model option within the Joint UK Land Environment Simulator (JULES) land surface model. The topographic index variable here is directly comparable to the compound topographic index available from United States Geological Survey's Hydro1K at 30 sec resolution. PLEASE NOTE: This dataset is a correction to a previous version which was found to contain errors ( https://doi.org/10.5285/ce391488-1b3c-4f82-9289-4beb8b8aa7da ). In the previous version all pixels north of 4.57 degrees south were shifted consistently 9.3 km to the west. This version is correctly aligned at all points.1Licence not specifiedabout 2 months ago
- Land Cover Map 2000 (1km percentage aggregate class, N. Ireland)This dataset consists of a 1km resolution raster version of the Land Cover Map 2000 for Northern Ireland. The raster consists of 10 bands. Within each band, each 1km pixel represents a percentage cover value for one of 10 aggregate classes. The aggregate classes are aggregations of the target (or 'sub') classes, broadly representing Broad Habitats (see below). The dataset is part of a series of data products produced by the Centre for Ecology & Hydrology known as LCM2000. LCM2000 is a parcel-based thematic classification of satellite image data covering the entire United Kingdom. LCM2000 is derived from a computer classification of satellite scenes obtained mainly from Landsat, IRS and SPOT sensors and also incorporates information derived from other ancillary datasets. LCM2000 was classified using a nomenclature corresponding to the Joint Nature Conservation Committee (JNCC) Broad Habitats, which encompasses the entire range of UK habitats. In addition, it recorded further detail where possible. The series of LCM2000 products includes vector and raster formats, with a number of different versions containing varying levels of detail and at different spatial resolutions. Note that the Band numberings in the dataset run from 1-11 rather than 0-10 and therefore each band relates to the one below it in the subclass code list.1Licence not specifiedabout 2 months ago
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