Contact for the resource

University of Oslo

17 record(s)
 
Type of resources
Topics
Keywords
Contact for the resource
Provided by
Years
Formats
Representation types
Update frequencies
Resolution
From 1 - 10 / 17
  • Data are presented showing for individual seedling, herbivory damage at the leaf level; galls, pathogens, trail herbivory presence/absence qualitative data; and leaf mortality. Data were collected in each leaf 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 bimonthly from February 2019 to January 2020, by the dataset first author. Leaf loss in percentage was made using the choice for direct visual estimate. We also followed the recommendations proposed by the authors, sectoring the leaves with a millimetre grid, improving measurement accuracy. The presence of Galls, pathogens and trail herbivory presence/absence qualitative data were also collected in each leaf. 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, 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/10.5285/2b8029ff-ddf5-47b2-9231-5fa0cbb6cd41

  • 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

  • The data include organic carbon and nitrogen abundances, carbon isotopes, nitrogen isotopes, major and trace element abundances, RockEval and mercury abundances from sedimentary strata across the Paleocene-Eocene thermal maximum. The samples include areas with hydrothermal influence linked to the emplacement of the North-Atlantic Igneous Province and others distal to hydrothermal activity to evaluate the effect of hydrothermal circulation on geochemical cycles. The results are linked to Rochelle-Bates et al. (in prep.) "Hydrothermal ammonium from a Large Igneous Province mitigated early Eocene climate change". * Note: U1568A Rockeval : Red filled cells highlight unreliable data with Tmax less than 350°C or greater than 450°C, or oxygen indices greater than 200.

  • This dataset comprises MicroCT 3D scans of skulls from Passer sparrows (Passer domesticus, P. hispaniolensis, P. italiae and F1 hybrids) generated during a crossing experiment at the University of Oslo, Norway in 2014/2015. Skulls were scanned with a microCT scanner at the University of Nottingham in 2023. Full details about this nonGeographicDataset can be found at https://doi.org/10.5285/c75ac806-2968-4bf0-8c72-ed4e0dc2ed7e

  • The Aerosol Direct Radiative Impact Experiment (ADRIEX) was a joint UK Met Office/Natural Environment Research Council (NERC)/UK Royal Society/University of Oslo project aiming at improving our understanding of the radiative effects of anthropogenic aerosol and gases (ozone and methane) in the troposphere. This dataset contains CO ouputs from the TOMCAT model. “Chemical attributes” are found by interpolating chemical distributions (in space and time) from a global chemical transport model to the origin of each trajectory (using its full length). During the ICARTT campaign the TOMCAT global CTM is being run in near-real time (about 19 hours behind present) driven by wind analyses from the ECMWF. The back trajectories are sufficiently long that a TOMCAT chemical analysis exists even at the origin of forecast trajectories. For example, the longest forecast lead time for the Azores domain is 5 days but the back trajectories are 7 days long so that the TOMCAT fields dating from 2 days before the latest meteorological analysis are used to find the attributes. For the US East Coast domain the back trajectories are shorter (3 days long) but the longest lead time is also 3 days so that the chemical attributes can be calculated as soon as TOMCAT has been brought up to date with the latest ECMWF analyses.

  • The Aerosol Direct Radiative Impact Experiment (ADRIEX) was a joint UK Met Office/Natural Environment Research Council (NERC)/UK Royal Society/University of Oslo project aiming at improving our understanding of the radiative effects of anthropogenic aerosol and gases (ozone and methane) in the troposphere. This dataset contains emission tracers from UTRAJ model. “Emissions tracers” are calculated by integrating surface emissions along each trajectory when it is within the boundary layer. The surface emissions are specified using an inventory. During the ITOP campaign the EDGAR inventories for NOx and isoprene emissions are used to indicate trajectories that are likely to have been influenced by anthropogenic or biogenic emissions respectively. The emissions from the surface are assumed to be instantaneously mixed throughout the boundary layer column so that they are equivalent to a volume source within the boundary layer. The boundary layer depth (time and space dependent) is obtained from the same numerical weather prediction model as provides the wind and temperature fields (usually the ECMWF model). Chemistry and dilution by mixing is not modelled along the trajectories, so the values assigned to back trajectories are not intended to represent concentrations on the arrival grid. Both NOx and isoprene have short photochemical lifetimes compared with the length of trajectories used.

  • The Aerosol Direct Radiative Impact Experiment (ADRIEX) was a joint UK Met Office/Natural Environment Research Council (NERC)/UK Royal Society/University of Oslo project aiming at improving our understanding of the radiative effects of anthropogenic aerosol and gases (ozone and methane) in the troposphere. This dataset contains forecast trajectories computed using UTRAJ. The term “particle trajectory” describes the path of a point which is blown by a time dependent wind field (i.e. (u, v, w) as a function of (x, y, z, t)). Trajectories following the analysed wind field are described by their coordinates (e.g. longitude, latitude, pressure) at regularly spaced time intervals. “Domain filling” refers to calculations where the arrival points of back trajectories (or release points for forward trajectories) form a dense, regular grid in a specified volume. The term “reverse” is used to indicate that the particles are followed backwards in time. Back trajectories are assumed to arrive on a 3D grid consisting of a stack of horizontal grids (regular in longitude and latitude) on a range of pressure levels. Forward trajectories are assumed to depart from similar grids. The trajectory length (time before arrival for back trajectories) is denoted by the letter T. Other fields can also be recorded following the trajectories: for example, temperature, specific humidity or potential vorticity. These extra fields are described as “attributes” and will be denoted by the variable C. The change in the value of an attribute over the length of a trajectory is denoted by C(0) − C(T).

  • The Aerosol Direct Radiative Impact Experiment (ADRIEX) was a joint UK Met Office/Natural Environment Research Council (NERC)/UK Royal Society/University of Oslo project aiming at improving our understanding of the radiative effects of anthropogenic aerosol and gases (ozone and methane) in the troposphere. This dataset contains O3 outputs from the TOMCAT model. “Chemical attributes” are found by interpolating chemical distributions (in space and time) from a global chemical transport model to the origin of each trajectory (using its full length). During the ICARTT campaign the TOMCAT global CTM is being run in near-real time (about 19 hours behind present) driven by wind analyses from the ECMWF. The back trajectories are sufficiently long that a TOMCAT chemical analysis exists even at the origin of forecast trajectories. For example, the longest forecast lead time for the Azores domain is 5 days but the back trajectories are 7 days long so that the TOMCAT fields dating from 2 days before the latest meteorological analysis are used to find the attributes. For the US East Coast domain the back trajectories are shorter (3 days long) but the longest lead time is also 3 days so that the chemical attributes can be calculated as soon as TOMCAT has been brought up to date with the latest ECMWF analyses.

  • The Aerosol Direct Radiative Impact Experiment (ADRIEX) was a joint UK Met Office/Natural Environment Research Council (NERC)/UK Royal Society/University of Oslo project aiming at improving our understanding of the radiative effects of anthropogenic aerosol and gases (ozone and methane) in the troposphere. This dataset contains ECMWF Boundary layer model data from a ECMWF Computer.

  • The Aerosol Direct Radiative Impact Experiment (ADRIEX) was a joint UK Met Office/Natural Environment Research Council (NERC)/UK Royal Society/University of Oslo project aiming at improving our understanding of the radiative effects of anthropogenic aerosol and gases (ozone and methane) in the troposphere. This dataset contains ECMWF Low level cloud model from a ECMWF Computer.