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2020

737 record(s)
 
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From 1 - 10 / 737
  • Gridded land use map of Peninsular Malaysia with a resolution of approximate 25 meters for the year 2018. The map includes nine different classes: 1) non-paddy agriculture, 2) paddy fields, 3) rural residential, 4) urban residential, 5) commercial/institutional, 6) industrial/infrastructure, 7) roads, 8) urban and 9) others. The land use map was created as part of the project “Malaysia - Flood Impact Across Scales”. The project is funded under the Newton-Ungku Omar Fund ‘Understanding of the Impacts of Hydrometeorological Hazards in South East Asia’ call. The grant was jointly awarded by the Natural Environment Research Council and the MYPAIR Scheme under the Ministry of Higher Education of Malaysia. Full details about this dataset can be found at https://doi.org/10.5285/36df244e-11c8-44bc-aa9b-79427123c42c

  • Primary forest cover and forest cover loss in Wallacea for the years 2000-2018 to train a deforestation model and produce maps of projected probability of deforestation until 2053. Full details about this dataset can be found at https://doi.org/10.5285/c7148c20-c6b3-43e1-9f99-b6e38e4dfdaf

  • Data are presented showing seedling height, diameter at ground height (DGH), total number of leaves, number of leaves with herbivory damage and leaf mortality, 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 bimonthlyfrom February 2019 to January 2020, by the dataset first author. Height measurements were made with a tape measure and DRH measurements were made with digital calipers. Leaf numbers, damage and mortality were made from visual observations. The data were collected to investigate the possible effects of different fertiliser applications on seedling height, totalnumber of leaves, number of leaves with herbivory damage and leaf mortality.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 maintanance). Full details about this dataset can be found at https://doi.org/10.5285/2da56eb1-ff01-48de-ba2a-d3afceefc85f

  • Data comprise tree trait data collected during September and October 2016 (the peak dry season), in the Caxiuanã National Forest Reserve, eastern Amazon, Brazil. 17 traits (including plot type, tree species name, diameter at breast height, tree light score, carboxylation capacity, electron transport capacity, leaf respiration in the dark, stomatal conductance, stem CO2 efflux, leaf mass per area, leaf nitrogen and phosphorus content, branch wood density, leaf water potential, xylem pressure, lumen conductance, percentage loss of conductivity, hydraulic Safety Margin and leaf area to sapwood area ratio) of 176 trees (most common genera) were sampled across two experimental plots: a one-hectare through-fall exclusion plot with a plastic panel structure that excludes 50% of the canopy through-fall and has done since 2002 and a corresponding one-hectare control plot without any drought structure. This data comes from the Caxiuanã through-fall exclusion (TFE) experiment located in the terra firma forest, on yellow oxisol soils at 15 m above sea level, with a mean annual rainfall between 2,000–2,500 mm and a pronounced dry season between June and November. Full details about this dataset can be found at https://doi.org/10.5285/441565b3-0a7d-4d3c-a7a8-7d7b487c1462

  • This dataset contains responses to a set of evaluation questions on flood resilience improvement within communities in the Katakwi District, Uganda. This data were created as part of the NIMFRU project (National-Scale Impact Based Forecasting of Flood Risk in Uganda) and consists of 21 semi-structured interviews. These have been completed by community members from the project target communities of Anyangabella, Agule and Kaikamosing which are all found in the Katakwi district. Five of the interviews were completed by local district officers. The data were collected in December 2020. These data were collected to understand how communities resilience had changed as a result of the NIMFRU project. Full details about this dataset can be found at https://doi.org/10.5285/d5043ca4-5451-42f1-ae38-69e084bfad80

  • This data were created as part of the NIMFRU project and consists of 21 flood matrices. These have been completed by community members from the project target communities of Anyangabella, Agule and Kaikamosing which are all found in the Katakwi district. Five of the matrices were completed by local district officers. The data were collected in December 2020. These data were collected to understand how communities resilience had changed as a result of the NIMFRU project. Full details about this dataset can be found at https://doi.org/10.5285/463b2bcc-731a-42af-ba69-1662aa21f1bf

  • A new monthly long term average (climatology) of Leaf Area Index (LAI) has been developed for use as ancillary data with the Joint UK Land Environment Simulator (JULES) Land Surface Model and the UK Met Office Unified Model. It is derived from an improved version of long time series of LAI from the original Global LAnd Surface Satellite (GLASS) products (http://www.glass.umd.edu/LAI/MODIS/0.05D/). The GLASS data consists of a time series of LAI from Moderate Resolution Imaging Spectroradiometer (MODIS) surface-reflectance data for the period 2000-2014. The MODIS data was provided in a spatial resolution of 1km in a sinusoidal projection and is interpolated into 0.5deg on a geographic latitude/longitude projection in this dataset. The total LAI from MODIS is segregated into five different Plant Functional Types (PFTs) using the fractional coverage of each PFT from the Climate Change Initiative (CCI) Land Cover data. For this reason this new LAI climatology should be used in combination with the CCI PFT data, which is also provided here. Two variables are provided with the dataset containing LAI, each covering the same spatial and time extent. The PFT data provided with this dataset covers a time span of only one year, 2010. - Leaf Area Index (LAI) - LAI is an important parameter in land-surface models, influencing the surface roughness, transpiration rate and the soil water content and temperature. Numerous outputs of vegetation models such as net primary productivity (NPP), evapotranspiration (ET), light absorption by plants (FAPAR), nutrient dynamics etc., are influenced by LAI where it is a key variable in energy and water balance calculations. - Vegetation Canopy Height (H) - H plays an important role in the interface between the atmosphere and land surface and it impacts weather and climate at local to global scales by modulating aerodynamic conductance and vegetation dynamics. Therefore, H is fundamentally needed for the calculation of turbulent exchanges of energy and mass between the atmosphere and the terrestrial ecosystem. One variable is provided with the dataset containing CCI PFTs: - Fractional coverage of 5 PFTS or vegetation classes and 4 land use classes – The 5 PFTs are Broad Leaf, Needle Leaf, C3 Grass, C4 Grass and Shrub. The 4 land use classes are Urban area, Inland Water, Bare Soil and Snow/Ice. Full details about this dataset can be found at https://doi.org/10.5285/6d07d60a-4cb9-44e4-be39-89ea40365236

  • These datasets provide Concentration Based Estimated Deposition (CBED) values of nitrogen, sulphur and base cations deposition for 5x5 kilometre (km) grid squares of the UK averaged over the years 1986 to 2012. The data consist of deposition values for sulphur, oxidised nitrogen and reduced nitrogen, and base cations. Total deposition is the sum of four components calculated separately: wet deposition, dry deposition of gases, dry deposition of particulate matter and cloud droplet deposition. Habitat-specific data are provided for (i) moorland/short vegetation, and (ii) forest. Additionally, the grid square average over multiple land cover types (i.e. arable, grassland, forest, moorland, urban) is also calculated. The habitat-specific data are recommended for use with critical loads for the calculation of critical load exceedances. The work in generating and compiling the dataset has been funded by the UK Centre for Ecology & Hydrology (UKCEH) and various Department for Environment, Food & Rural Affairs (Defra) contracts. Full details about this dataset can be found at https://doi.org/10.5285/8e7644fe-9f17-4fc3-8e4e-8b10a42d5d50

  • This dataset reports results on seedling growth and survival for two hyphal exclusion experiments in a subtropical forest. The data include survival status, height, total biomass and the biomass of component plant parts, percentage root colonisation by mycorrhizas, for tree seedlings of ten common species including five ectomycorrhizal (ECM) and five arbuscular mycorrhizal (AM) species, which were transplanted in the in-growth cores with windows covering different sizes of nylon meshes (35 vs. 0.5 µm). The dataset provides raw data on growth and survival metrics for each seedling, plus identifying codes for the dominant sites where the experiments were conducted, as well as experimental block, mesh treatment, botanical names for the tree species, and mycorrhizal type. The data were entered into Excel spreadsheets and exported as comma separated value files (csv). Study area - the Heishiding Nature Reserve (111°53’E, 23°27’N, 150-927 m a.s.l.) in Guangdong Province of south China. Full details about this dataset can be found at https://doi.org/10.5285/f1d17e61-bb6c-47a9-a648-062c63ea7f16

  • [THIS DATASET HAS BEEN WITHDRAWN]. This dataset contains daily and sub-daily hydrometeorological and soil observations from COSMOS-UK (cosmic-ray soil moisture) monitoring network from October 2013 to the end of 2018. These data are from 50 sites across the UK recording a range of hydrometeorological and soil variables. Each site in the network records the following hydrometeorological and soil data at 30 minute resolution: Radiation (short wave, long wave and net), precipitation, atmospheric pressure, air temperature, wind speed and direction, humidity, soil heat flux, and soil temperature and volumetric water content (VWC), measured by point senors at various depths. Each site hosts a cosmic-ray sensing probe; a novel sensor technology which counts fast neutrons in the surrounding atmosphere. In combination with the recorded hydrometeorological data, neutron counts are used to derive VWC over a field scale (COSMOS VWC), at two temporal resolutions (hourly and daily). The presence of snow leads to erroneously high measurements of COSMOS VWC due to all the extra water in the surrounding area. Included in the daily data are indications of snow days, on which, the COSMOS VWC are adjusted and the snow water equivalent (SWE) is given. The potential evapotranspiration (PE), derived from recorded hydrometeorological and soil are also included at daily resolution. Two levels of quality control are carried out, firstly data is run through a series of automated checks, such as range tests and spike tests, and then all data is manually inspected each week where any other faults are picked up, including sensor faults or connection issues. Quality control flags are provided for all recorded (30 minute) data, indicating the reason for any missing data. Full details about this dataset can be found at https://doi.org/10.5285/37702a54-b7a4-40ff-b62e-d14b161b69ca