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100 urn:ogc:def:uom:EPSG::9001

94 record(s)

 

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From 1 - 10 / 94
  • [This dataset is embargoed until September 1, 2021]. Data are presented showing litterfall ant species and abundance from a plot based fertilisation experiment. The experiment was carried out at the Biological Dynamics of Forest Fragments Project (BDFFP) approximately 100 km north of Manaus. Data were collected in October 2018 and September 2019 by Santos-Neto. Sampling was carried out using a Wrinkler extractor. The data were collected to investigate the possible effects of different fertiliser applications on litterfall ant species and abundance. The work was carried out as part of the Amazon Fertilization Experiment (AFEX), funded by the Natural Environment Research Council (NERC), Award reference NE/L007223/1, by the Brazilian government (Researcher scholarship) and the Biological Dynamics of Forest Fragments Project (BDFFP - logistical support and camps maintenance). Full details about this dataset can be found at https://doi.org/10.5285/60e77fd4-7a24-4545-8d90-08e9dfcbd16a

  • This dataset represents the hydro-meteorological monitoring activities undertaken in Ouagadougou, Burkina Faso, during 2016-2018, as part of the DFID funded AMMA-2050 (African Monsoon Multidisciplinary Analysis) project (amma2050.org). The data comprises time series of rainfall, water level and river flow recorded at locations across Ouagadougou city for the purposes of building an understanding of hydrological function and hydrological model development. In-situ data were collected using tipping bucket raingauges and pressure level sensors, with spot gauging of river flows used to develop rating curves used to derive flow from level measurements in channels. The network was designed and set-up by the UK Centre for Ecology and Hydrology (UKCEH) and maintained by the Burkina Faso Institut International d’Ingenierie de l’Eau et de l’Environment (2iE) and processing was undertaken by UKCEH. Full details about this dataset can be found at https://doi.org/10.5285/30ae0230-e352-4a82-901d-ac1d42449044

  • The data comprise a long-term study of alpine plant community dynamics in the Gunnison National Forest of Colorado. The data comprise annual census data for all plants (including seedlings) in each of 50 2x2m plots, including information on size, reproduction, life stage, and mortality, with all plants identified and geo-located. These data are also made available transformed to provide individual-level estimates of growth, survival, fecundity, and recruitment. The dataset covers several thousand individuals of approximately twenty species, and highlights an apparent pattern of demographic decline. The data also include information on microenvironment / microedaphic variation at 2 m resolution covering the entire research site, including information on temperatures, topography, soil chemistry, soil texture, and other variables. The data also include information on the functional traits of many of the species present at the site, including information on biomass allocation, leaf traits, root traits, seed traits, and floral traits. Full details about this dataset can be found at https://doi.org/10.5285/d850fcd2-b70a-415e-acf4-fc27b38d59c1

  • Data from a field-based investigation into the spatio-temporal variability of abiotic and biotic controls on peatland carbon cycling. Data was collected between February 2011 and April 2013, across an area of blanket bog peatland at Black Law Wind Farm, Lanarkshire, Scotland. Plant-soil properties data includes total carbon content, total nitrogen content and carbon to nitrogen ratio of vegetation, litter and peat, carbon and nitrogen stock for litter and peat, bulk density, soil moisture content, pH and soil microbial community composition of peat (Phospholipid Fatty Acids). Peatland carbon cycling data includes measures of litter decomposition, dissolved organic carbon concentration, methane fluxes, net ecosystem exchange, photosynthesis and ecosystem respiration. Physical parameters measured includes below ground temperature from April 2011 to June 2012 and soil moisture content from May 2011 to April 2013. Full details about this dataset can be found at https://doi.org/10.5285/99416ba1-b670-4a82-8225-9644293fb4de

  • Field-pathological findings of 33 saiga antelope carcasses (adults and new-born) found in two sites (Tengiz and Turgai, Kazakhstan) during a mass die-off event in May 2015. In Kazakhstan May 2015, approximately 200,000 saiga antelopes died within a month-period causing a loss of two-thirds of the global population. The dramatic event occurred during calving season when females and young males stop migrating and form massive aggregations for calving purposes. With 100% morbidity and 100% mortality of affected herds observed, the 2015 die-off left the largest saiga population, Betpak-Dala, with approximately 30,000 survivors based on post mortality census, highlighting the imminent extinction threats to this critically endangered species. The lack of pathological investigations during historical mass mortality events has limited our understanding of disease-related mortalities in saiga antelope. Generally, aetiological agents were isolated from dead saiga, but the disease course and a full necropsy were not performed nor present in the records. However, for the first time, a full pathology report was possible during 2015. Full details about this dataset can be found at https://doi.org/10.5285/30cbfba7-f9a1-47d5-abdb-f2741041e487

  • Woodland vegetation data from the UK Environmental Change Network (ECN) terrestrial sites. These data are collected at all of ECN's terrestrial sites using a standard protocol (see Supporting documentation). This survey is conducted when plots surveyed during the coarse-grain survey fall in woodland. Seedlings, diameter at breast height (dbh), height and species dominance are recorded within a surrounding 10m x 10m plot. ECN is the UK's long-term environmental monitoring programme. It is a multi-agency programme sponsored by a consortium of fourteen government departments and agencies. These organisations contribute to the programme through funding either site monitoring and/or network co-ordination activities. These organisations are: Agri-Food and Biosciences Institute, Biotechnology and Biological Sciences Research Council, Cyfoeth Naturiol Cymru - Natural Resources Wales, Defence Science & Technology Laboratory, Department for Environment, Food and Rural Affairs, Environment Agency, Forestry Commission, Llywodraeth Cymru - Welsh Government, Natural England, Natural Environment Research Council, Northern Ireland Environment Agency, Scottish Environment Protection Agency, Scottish Government and Scottish Natural Heritage. Full details about this dataset can be found at https://doi.org/10.5285/94aef007-634e-42db-bc52-9aae86adbd33

  • Rabbit and deer data from the UK Environmental Change Network (ECN) terrestrial sites. These data are collected by transect at ECN's terrestrial sites using a standard protocol. The protocol uses an index method based on dropping counts (of deer, rabbits - and where appropriate sheep and Grouse) to estimate relative abundance. They represent twice-yearly continuous records from 1993 to 2015. ECN is the UK's long-term environmental monitoring programme. It is a multi-agency programme sponsored by a consortium of fourteen government departments and agencies. These organisations contribute to the programme through funding either site monitoring and/or network co-ordination activities. These organisations are: Agri-Food and Biosciences Institute, Biotechnology and Biological Sciences Research Council, Cyfoeth Naturiol Cymru - Natural Resources Wales, Defence Science & Technology Laboratory, Department for Environment, Food and Rural Affairs, Environment Agency, Forestry Commission, Llywodraeth Cymru - Welsh Government, Natural England, Natural Environment Research Council, Northern Ireland Environment Agency, Scottish Environment Protection Agency, Scottish Government and Scottish Natural Heritage. Full details about this dataset can be found at https://doi.org/10.5285/0be0aed3-f205-4f1f-a65d-84f8cfd8d50f

  • The dataset describes the effects of different management techniques on grassland biomass production (dry matter yield), nutritional quality (herbage nitrogen content), pollinator communities (abundance and species richness), predatory beetle communities (abundance, species richness and biomass), and soil health (bulk density, total soil carbon and nitrogen). Data was collected from a site in Berkshire (UK), where a field-scale, randomised block experiment had been implemented to investigate how the establishment of a variety of plant functional groups (grasses, legumes, and other flowering forbs) using different cultivation (minimum tillage and deep ploughing) and management (cutting, grazing and their intensity) techniques, affected the provision of various ecosystem services. Full details about this dataset can be found at https://doi.org/10.5285/984b1001-82f1-4ba0-aa1e-412f85d9d24f

  • Bat species data from the UK Environmental Change Network (ECN) terrestrial sites. The count of individual species is recorded. These data are collected while walking a defined transect using a bat detector at ECN's terrestrial sites using a standard protocol. They represent continuous records (the transects are walked four times each year) from 1993 to 2015. ECN is the UK's long-term environmental monitoring programme. It is a multi-agency programme sponsored by a consortium of fourteen government departments and agencies. These organisations contribute to the programme through funding either site monitoring and/or network co-ordination activities. These organisations are: Agri-Food and Biosciences Institute, Biotechnology and Biological Sciences Research Council, Cyfoeth Naturiol Cymru - Natural Resources Wales, Defence Science & Technology Laboratory, Department for Environment, Food and Rural Affairs, Environment Agency, Forestry Commission, Llywodraeth Cymru - Welsh Government, Natural England, Natural Environment Research Council, Northern Ireland Environment Agency, Scottish Environment Protection Agency, Scottish Government and Scottish Natural Heritage. Full details about this dataset can be found at https://doi.org/10.5285/2588ee91-6cbd-4888-86fc-81858d1bf085

  • These spatial layers contain the predicted occurrence and abundance of three heathland shrubs, Arctostaphylos uva-ursi, Vaccinium myrtillus and Vaccinium vitis-idaea identified as susceptible host species for Phytophthora ramorum and Phytophthora kernoviae in Scotland. The distribution models were developed from quadrat vegetation data kindly provided by Scottish Natural Heritage combined with data on climate and soil conditions as well as deer abundance and were fitted using a Bayesian Generalised Mixed Modelling approach adapted for input data on the DOMIN scale. This research was funded by the Scottish Government under research contract CR/2008/55, 'Study of the epidemiology of Phytophthora ramorum and Phytophthora kernoviae in managed gardens and heathlands in Scotland' and involved collaborators from St Andrews University, Science and Advice for Scottish Agriculture (SASA), Scottish Natural Heritage (SNH), Forestry Commission, the Food and Environment Research Agency (FERA) and the Centre for Ecology & Hydrology (CEH). Full details about this dataset can be found at https://doi.org/10.5285/5749df3d-000c-445e-a37f-dc0763b4d5ec