This updated layer of The Gridded Livestock of the World (GLW)database provided modelled livestock densities of the world, adjusted to match official (FAOSTAT)national estimates for the reference year 2005, at a spatial resolution of 3 minutes of arc (about 565 km at the equator).Recent methodological improvements have significantly enhanced these distributions: more up-to date and detailed sub-national livestock statistics have been collected; a new, higher resolution set of predictor variables is used; and the analyticalprocedure has been revised and extended to include a more systematic assessment of model accuracy and therepresentation of uncertainties associated with the predictions.<br><br>For further details on mapping methods see: Robinson, T.P., Wint, G.R.W., Conchedda, G., Van Boeckel, T.P., Ercoli, V., Palamara, E., Cinardi, G., D’Aietti, L., Hay, S.I., Gilbert, M., 2014. Mapping the Global Distribution of Livestock. PLoS ONE 9, e96084. <a href=\"https://doi.org/10.1371/journal.pone.0096084\"target=_blank>https://doi.org/10.1371/journal.pone.0096084</a><br/><br>These digital layers are made publically available via the Livestock Geo-Wiki (<a href=\"http://www.livestock.geo-wiki.org\"target=_blank>livestock.geo-wiki.org</a><br/>

The dataset provides the annual estimated value of buillt capital that is protected by coral reefs in flood protection annually.<br><br>For more infomration please visit <a href="http://maps.oceanwealth.org/" target="_blank">The Mapping Ocean Wealth Explorer</a>.<br/><br>This data is provided by <a href="www.nature.org" target="_blank">The Nature Conservancy</a><br/>"

This updated layer of The Gridded Livestock of the World (GLW)database provided modelled livestock densities of the world, adjusted to match official (FAOSTAT)national estimates for the reference year 2005, at a spatial resolution of 3 minutes of arc (about 565 km at the equator).Recent methodological improvements have significantly enhanced these distributions: more up-to date and detailed sub-national livestock statistics have been collected; a new, higher resolution set of predictor variables is used; and the analyticalprocedure has been revised and extended to include a more systematic assessment of model accuracy and therepresentation of uncertainties associated with the predictions.<br><br>For further details on mapping methods see: Robinson, T.P., Wint, G.R.W., Conchedda, G., Van Boeckel, T.P., Ercoli, V., Palamara, E., Cinardi, G., D’Aietti, L., Hay, S.I., Gilbert, M., 2014. Mapping the Global Distribution of Livestock. PLoS ONE 9, e96084. <a href=\"https://doi.org/10.1371/journal.pone.0096084\"target=_blank>https://doi.org/10.1371/journal.pone.0096084</a><br/><br>These digital layers are made publically available via the Livestock Geo-Wiki (<a href=\"http://www.livestock.geo-wiki.org\"target=_blank>livestock.geo-wiki.org</a><br/>

Countries distinguish between metropolitan (homeland) and independent and semi-independent portions of sovereign states. If you want to see the dependent overseas regions broken out (like in ISO codes, see France for example), use map units instead. Each country is coded with a world region that roughly follows the United Nations setup. Countries are coded with standard ISO and FIPS codes. French INSEE codes are also included. Includes some thematic data from the United Nations (1), U.S. Central Intelligence Agency, and elsewhere.

With the growing recognition that effective action on climate change will require a combination of emissions reductions and carbon sequestration, protecting, enhancing and restoring natural carbon sinks have become political priorities. Mangrove forests are considered some of the most carbon-dense ecosystems in the world with most of the carbon stored in the soil. In order for mangrove forests to be included in climate mitigation efforts, knowledge of the spatial distribution of mangrove soil carbon stocks are critical. Current global estimates do not capture enough of the finer scale variability that would be required to inform local decisions on siting protection and restoration projects. To close this knowledge gap, we have compiled a large georeferenced database of mangrove soil carbon measurements and developed a novel machine-learning based statistical model of the distribution of carbon density using spatially comprehensive data at a 30 m resolution. This model, which included a prior estimate of soil carbon from the global SoilGrids 250 m model, was able to capture 63% of the vertical and horizontal variability in soil organic carbon density (RMSE of 10.9 kg m−3). Of the local variables, total suspended sediment load and Landsat imagery were the most important variable explaining soil carbon density. Projecting this model across the global mangrove forest distribution for the year 2000 yielded an estimate of 6.4 Pg C for the top meter of soil with an 86–729 Mg C ha−1 range across all pixels. By utilizing remotely-sensed mangrove forest cover change data, loss of soil carbon due to mangrove habitat loss between 2000 and 2015 was 30–122 Tg C with >75% of this loss attributable to Indonesia, Malaysia and Myanmar. The resulting map products from this work are intended to serve nations seeking to include mangrove habitats in payment-for- ecosystem services projects and in designing effective mangrove conservation strategies. Sanderman J, Hengl T, Fiske G, Solvik K, Adame MF, Benson L, et al. A global map of mangrove forest soil carbon at 30 m spatial resolution. Environ Res Lett. 2018;13: 055002. doi:10.1088/1748-9326/aabe1c

The Global Coral Protection Index is a basic modeled estimate of relative indexed values of coastal and barrier coral reefs for protecting coastal resources from wind and swell waves. Such reefs can reduce erosion and also inundation of low-lying coastal areas. The value of such mitigation is here determined as a function of the exposed populations and infrastructure that receive some level of protection from coral reefs.<br><br>For more infomration please visit <a href="http://maps.oceanwealth.org/" target="_blank">The Mapping Ocean Wealth Explorer</a>.<br/><br>This data is provided by <a href="www.nature.org" target="_blank">The Nature Conservancy</a><br/>"

Aboveground live woody carbon density change (2003-2014): The data provided here are the result of a time-series analysis of carbon density change between 2003-2014 spanning tropical America, Africa, and Asia (23.45 N lat.-23.45 S lat.). For further information about these results please see the associated journal article (Baccini et al. 2017, Science). Spatial (raster) and tabular data described in the journal article are available for download from the links below. Data can be visualized at www.thecarbonsource.org. The visualization includes the ability to select a given change pixel (loss or gain) and display the trajectory of carbon density during the 2003-2014 study period. Raster Data Information: The carbon density change data are divided into three regions: America, Africa, and Asia. For each region there are two raster (.tif) files representing: 1) carbon density net gain, and 2) carbon density net loss. The value of each pixel (463 x 463 m) represents the total net carbon density change (Mg/ha) over the period 2003-2014. Only pixels exhibiting statistical significance at the 95% level are reported. All raster files are in the original MODIS sinusoidal projection.Baccini, A., W. Walker, L. Carvalho, M. Farina, D. Sulla-Menashe, R.A. Houghton. 2017. Tropical forests are a net carbon source based on aboveground measurements of gain and loss. Science 2017 Vol. 358, Issue 6360, pp. 230-234 DOI:10.1126/science.aam5962. Data available online from www.thecarbonsource.org.

The dataset provides the estimated value of built capital protected by coral reefs in flood protection from a 1 in 25-year storm.<br><br>For more infomration please visit <a href="http://maps.oceanwealth.org/" target="_blank">The Mapping Ocean Wealth Explorer</a>.<br/><br>This data is provided by <a href="www.nature.org" target="_blank">The Nature Conservancy</a><br/>"

The dataset provides the annual estimated number of people protected by coral reefs in flood protection annually.<br><br>For more infomration please visit <a href="http://maps.oceanwealth.org/" target="_blank">The Mapping Ocean Wealth Explorer</a>.<br/><br>This data is provided by <a href="www.nature.org" target="_blank">The Nature Conservancy</a><br/>"

The Human Footprint (HFP) provides a measure of the direct and indirect human pressures on the environment globally in years 1993 and 2009. It is derived from remotely-sensed and bottom-up survey information compiled on eight measured variables. This represents not only the most current information of its type, but also the first temporally-consistent set of Human Footprint maps. Data on human pressures were acquired or developed for: 1) built environments, 2) population density, 3) electric infrastructure, 4) crop lands, 5) pasture lands, 6) roads, 7) railways, and 8) navigable waterways. Pressures were then overlaid to create the standardized Human Footprint maps for all non-Antarctic land areas. The Human Footprint maps find a range of uses as proxies for human disturbance of natural systems and can provide an increased understanding of the human pressures that drive macro-ecological patterns, as well as for tracking environmental change and informing conservation science and application. HFP values range from 0 (no human impact) to 50 (heavily human impacted).<br><br>See: <a href=""https://www.nature.com/articles/ncomms12558"">Venter, O. et al., 2016. Sixteen years of change in the global terrestrial human footprint and implications for biodiversity conservation. Nature Communications, 7, pp.1–11</a>.<br/><br>Data can also be downloaded from <a href=""https://datadryad.org/resource/doi:10.5061/dryad.052q5"">Dryad<a/>.<br/>