reef-associated bioregions for the Solomon Islands
The bolded ecosystem services in this table are likely to be less resilient to future climate conditions
*please refer to Honiara Ecosystem Based Adaptation assessment and masterplan report for narration and further information*
Prioritized EbA adaptation options
*please refer to Honiara Ecosystem Adaptation Assessment report for narration and further information*
Indication of location for the establishment of the Barana and Queen Elizabeth Park to improve the upper Mataniko and Lungga catchment area’s provision of fresh water supply and other ecosystem services.
*refer to Honiara Ecosystem Based Adaptation Option Assessment report for more detailed information*
This dataset contains economic information for catch and catch vessels in the Asia and Pacific region, including country-level data on Solomon Islands.
GEBCO’s gridded bathymetric data set, the GEBCO_2020 grid, is a global terrain model for ocean and land at 15 arc-second intervals. It is accompanied by a Type Identifier (TID) Grid that gives information on the types of source data that the GEBCO_2020 Grid is based.
If the data sets are used in a presentation or publication then we ask that you acknowledge the source.This should be of the form: GEBCO Compilation Group (2020) GEBCO 2020 Grid (doi:10.5285/a29c5465-b138-234d-e053-6c86abc040b9)
Raster data representing the mean levels of chlorophyll in mg/m3 for the surface water layer. The data are available for global-scale applications at a spatial resolution of 5 arcmin (approximately 9.2 km at the equator).
Marine data layers for present conditions were produced with climate data describing monthly averages for the period 2000–2014, obtained from pre-processed global ocean re-analyses combining satellite and in situ observations at regular two- and three-dimensional spatial grids.
Raster data representing the mean levels of dissolved oxygen in µmol/m3 for the surface water layer. The data are available for global-scale applications at a spatial resolution of 5 arcmin (approximately 9.2 km at the equator).
Marine data layers for present conditions were produced with climate data describing monthly averages for the period 2000–2014, obtained from pre-processed global ocean re-analyses combining satellite and in situ observations at regular two- and three-dimensional spatial grids.
Raster data representing the mean levels of nitrate in µmol/m3 for the surface water layer. The data are available for global-scale applications at a spatial resolution of 5 arcmin (approximately 9.2 km at the equator).
Marine data layers for present conditions were produced with climate data describing monthly averages for the period 2000–2014, obtained from pre-processed global ocean re-analyses combining satellite and in situ observations at regular two- and three-dimensional spatial grids.
Raster data representing the mean levels of phosphate in µmol/m3 for the surface water layer. The data are available for global-scale applications at a spatial resolution of 5 arcmin (approximately 9.2 km at the equator).
Marine data layers for present conditions were produced with climate data describing monthly averages for the period 2000–2014, obtained from pre-processed global ocean re-analyses combining satellite and in situ observations at regular two- and three-dimensional spatial grids.
Raster data representing the mean levels of phytoplankton in µmol/m3 for the surface water layer. The data are available for global-scale applications at a spatial resolution of 5 arcmin (approximately 9.2 km at the equator).
Marine data layers for present conditions were produced with climate data describing monthly averages for the period 2000–2014, obtained from pre-processed global ocean re-analyses combining satellite and in situ observations at regular two- and three-dimensional spatial grids.
Raster data representing the mean levels of salinity in practical salinity scale (PSS) for the surface water layer. The data are available for global-scale applications at a spatial resolution of 5 arcmin (approximately 9.2 km at the equator).
Marine data layers for present conditions were produced with climate data describing monthly averages for the period 2000–2014, obtained from pre-processed global ocean re-analyses combining satellite and in situ observations at regular two- and three-dimensional spatial grids.
Raster data representing the mean levels of silicate in µmol/m3 for the surface water layer. The data are available for global-scale applications at a spatial resolution of 5 arcmin (approximately 9.2 km at the equator).
Marine data layers for present conditions were produced with climate data describing monthly averages for the period 2000–2014, obtained from pre-processed global ocean re-analyses combining satellite and in situ observations at regular two- and three-dimensional spatial grids.
Raster data representing the mean levels of temperature in degrees Celsius (°C) for the surface water layer. The data are available for global-scale applications at a spatial resolution of 5 arcmin (approximately 9.2 km at the equator).
Marine data layers for present conditions were produced with climate data describing monthly averages for the period 2000–2014, obtained from pre-processed global ocean re-analyses combining satellite and in situ observations at regular two- and three-dimensional spatial grids.
The Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11 consists of estimates of human population density (number of persons per square kilometer) based on counts consistent with national censuses and population registers, for the years 2000. A proportional allocation gridding algorithm, utilizing approximately 13.5 million national and sub-national administrative units, was used to assign population counts to 30 arc-second grid cells.
The Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11 consists of estimates of human population density (number of persons per square kilometer) based on counts consistent with national censuses and population registers, for the year 2005. A proportional allocation gridding algorithm, utilizing approximately 13.5 million national and sub-national administrative units, was used to assign population counts to 30 arc-second grid cells.
The Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11 consists of estimates of human population density (number of persons per square kilometer) based on counts consistent with national censuses and population registers, for the year 2010. A proportional allocation gridding algorithm, utilizing approximately 13.5 million national and sub-national administrative units, was used to assign population counts to 30 arc-second grid cells.
The Gridded Population of the World, Version 4 (GPWv4): Population Density, Revision 11 consists of estimates of human population density (number of persons per square kilometer) based on counts consistent with national censuses and population registers, for the year 2015. A proportional allocation gridding algorithm, utilizing approximately 13.5 million national and sub-national administrative units, was used to assign population counts to 30 arc-second grid cells.