Livestock contributes directly to the livelihoods and food security of almost a billion people and affects the diet and health of many more. With estimated standing populations of 1.43 billion ...cattle, 1.87 billion sheep and goats, 0.98 billion pigs, and 19.60 billion chickens, reliable and accessible information on the distribution and abundance of livestock is needed for a many reasons. These include analyses of the social and economic aspects of the livestock sector; the environmental impacts of livestock such as the production and management of waste, greenhouse gas emissions and livestock-related land-use change; and large-scale public health and epidemiological investigations. The Gridded Livestock of the World (GLW) database, produced in 2007, 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 5×5 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 analytical procedure has been revised and extended to include a more systematic assessment of model accuracy and the representation of uncertainties associated with the predictions. This paper describes the current approach in detail and presents new global distribution maps at 1 km resolution for cattle, pigs and chickens, and a partial distribution map for ducks. These digital layers are made publically available via the Livestock Geo-Wiki (http://www.livestock.geo-wiki.org), as will be the maps of other livestock types as they are produced.
The Paris Agreement calls on parties to undertake ambitious efforts to combat climate change by engaging in appropriate policies and measures as put forward through Nationally Determined ...Contributions (NDCs), to strengthen transparency when reporting their greenhouse gas (GHG) emissions and to increase their mitigation contributions to climate action from 2020. It also calls for regular and transparent monitoring and reporting of the GHG emissions and on the NDCs implementation efforts. Biomass fires significantly affect the GHG atmospheric balance, with fire emissions representing more than 5% of total emissions from agriculture, forestry, and other land use (AFOLU), according to recent estimates produced by the Food and Agriculture Organization (FAO). We update previously published Tier 1 estimates of GHG emissions in FAOSTAT—which had been used in the IPCC AR5 analysis—by using new burned area activity data from the Moderate Resolution Imaging Spectroradiometer (MODIS) known as MCD64A1, Collection 6. The previous FAOSTAT estimates had used as input the Global Fire Emission Database v.4 (GFED4) burned area product, based on older MODIS Collection 5.1 burned area product. In line with differences between the input data used, the new FAOSTAT estimates indicate roughly 30% higher fire emissions globally than previously published. Our analysis also confirms that the FAOSTAT Tier 1 approach produces fire emissions estimates that are comparable to those computed at Tier 3 by GFED, and thus represent a useful complementary tool in support of country GHG reporting.
New estimates of greenhouse gas (GHG) emissions from the food system were developed at the country level, for the period 1990–2018, integrating data from crop and livestock production, on-farm energy ...use, land use and land use change, domestic food transport and food waste disposal. With these new country-level components in place, and by adding global and regional estimates of energy use in food supply chains, we estimate that total GHG emissions from the food system were about 16 CO2eq yr−1 in 2018, or one-third of the global anthropogenic total. Three quarters of these emissions, 13 Gt CO2eq yr−1, were generated either within the farm gate or in pre- and post-production activities, such as manufacturing, transport, processing, and waste disposal. The remainder was generated through land use change at the conversion boundaries of natural ecosystems to agricultural land. Results further indicate that pre- and post-production emissions were proportionally more important in developed than in developing countries, and that during 1990–2018, land use change emissions decreased while pre- and post-production emissions increased. We also report results on a per capita basis, showing world total food systems per capita emissions decreasing during 1990–2018 from 2.9 to 2.2 t CO2eq cap−1, with per capita emissions in developed countries about twice those in developing countries in 2018. Our findings also highlight that conventional IPCC categories, used by countries to report emissions in the National GHG inventory, systematically underestimate the contribution of the food system to total anthropogenic emissions. We provide a comparative mapping of food system categories and activities in order to better quantify food-related emissions in national reporting and identify mitigation opportunities across the entire food system.
Object-based methods for image analysis have the advantage of incorporating spatial context and mutual relationships between objects. Few studies have explored the application of object-based ...approaches to mangrove mapping. This research applied an object-based method to SPOT XS data to map the land cover in the mangrove ecosystem of Low Casamance, Senegal. In parallel, the object-based method was tested to analyse the changes in the mangrove area between 1986 and 2006. The object-based method for mangrove mapping applied a multi-resolution segmentation and implemented class-specific rules that incorporate spectral properties and relationships between image objects at different hierarchical levels. The object-based approach for change analysis conducted the segmentation on the multi-date composite of the 1986 and 2006 images and applied a nearest neighbour classifier.
The object-based method clearly discriminated the different land cover classes within the mangrove ecosystem. The overall accuracy of the land cover classification was 86%, the overall
kappa value was 0.83 and the user’s accuracy of the ‘mangroves’ class was higher than 97%. The estimated area of mangroves was 76,550 hectares in 2006. This result is an important update reference for mangrove studies in Senegal and the proposed method may represent a valid instrument for similar exercises in other regions.
The image-to-image, object-based approach to change analysis clearly captured the fragmented and scattered pattern of change that prevails in the study area. The user’s accuracy of the increase and decrease classes of transition produced results better than 85%. The overall accuracy, however, is lower due to the method’s difficulties in detecting the small areas of change. To have conclusive evidence for the suitability of this method for change analysis of mangrove forest, this object-based approach should be tested in mangrove ecosystems where changes have different spatial patterns and modifications are more evident. Between 1986 and 2006, a small increase in the mangrove area was observed in Low Casamance. This was probably due to improved rainfall conditions after the droughts of the 1970s and 1980s. The pattern of change detected with the object-based approach corresponds to natural transitions and suggests that anthropogenic influence was limited.
The rapid transformation of the livestock sector in recent decades brought concerns on its impact on greenhouse gas emissions, disruptions to nitrogen and phosphorous cycles and on land use change, ...particularly deforestation for production of feed crops. Animal and human health are increasingly interlinked through emerging infectious diseases, zoonoses, and antimicrobial resistance. In many developing countries, the rapidity of change has also had social impacts with increased risk of marginalisation of smallholder farmers. However, both the impacts and benefits of livestock farming often differ between extensive (backyard farming mostly for home-consumption) and intensive, commercial production systems (larger herd or flock size, higher investments in inputs, a tendency towards market-orientation). A density of 10,000 chickens per km2 has different environmental, epidemiological and societal implications if these birds are raised by 1,000 individual households or in a single industrial unit. Here, we introduce a novel relationship that links the national proportion of extensively raised animals to the gross domestic product (GDP) per capita (in purchasing power parity). This relationship is modelled and used together with the global distribution of rural population to disaggregate existing 10 km resolution global maps of chicken and pig distributions into extensive and intensive systems. Our results highlight countries and regions where extensive and intensive chicken and pig production systems are most important. We discuss the sources of uncertainties, the modelling assumptions and ways in which this approach could be developed to forecast future trajectories of intensification.
Large scale, high-resolution global data on farm animal distributions are essential for spatially explicit assessments of the epidemiological, environmental and socio-economic impacts of the ...livestock sector. This has been the major motivation behind the development of the Gridded Livestock of the World (GLW) database, which has been extensively used since its first publication in 2007. The database relies on a downscaling methodology whereby census counts of animals in sub-national administrative units are redistributed at the level of grid cells as a function of a series of spatial covariates. The recent upgrade of GLW1 to GLW2 involved automating the processing, improvement of input data, and downscaling at a spatial resolution of 1 km per cell (5 km per cell in the earlier version). The underlying statistical methodology, however, remained unchanged. In this paper, we evaluate new methods to downscale census data with a higher accuracy and increased processing efficiency. Two main factors were evaluated, based on sample census datasets of cattle in Africa and chickens in Asia. First, we implemented and evaluated Random Forest models (RF) instead of stratified regressions. Second, we investigated whether models that predicted the number of animals per rural person (per capita) could provide better downscaled estimates than the previous approach that predicted absolute densities (animals per km2). RF models consistently provided better predictions than the stratified regressions for both continents and species. The benefit of per capita over absolute density models varied according to the species and continent. In addition, different technical options were evaluated to reduce the processing time while maintaining their predictive power. Future GLW runs (GLW 3.0) will apply the new RF methodology with optimized modelling options. The potential benefit of per capita models will need to be further investigated with a better distinction between rural and agricultural populations.
CROPGRIDS is a comprehensive global geo-referenced dataset providing area information for 173 crops for the year 2020, at a resolution of 0.05° (about 5.6 km at the equator). It represents a major ...update of the Monfreda et al. (2008) dataset (hereafter MRF), the most widely used geospatial dataset previously available, covering 175 crops with reference year 2000 at 10 km spatial resolution. CROPGRIDS builds on information originally provided in MRF and expands it using 27 selected published gridded datasets, subnational data of 52 countries obtained from National Statistical Offices, and the 2020 national-level statistics from FAOSTAT, providing more recent harvested and crop (physical) areas for 173 crops at regional, national, and global levels. The CROPGRIDS data advance the current state of knowledge on the spatial distribution of crops, providing useful inputs for modelling studies and sustainability analyses relevant to national and international processes.
Mapping global cropland and field size Fritz, Steffen; See, Linda; McCallum, Ian ...
Global change biology,
20/May , Letnik:
21, Številka:
5
Journal Article
Recenzirano
Odprti dostop
A new 1 km global IIASA‐IFPRI cropland percentage map for the baseline year 2005 has been developed which integrates a number of individual cropland maps at global to regional to national scales. The ...individual map products include existing global land cover maps such as GlobCover 2005 and MODIS v.5, regional maps such as AFRICOVER and national maps from mapping agencies and other organizations. The different products are ranked at the national level using crowdsourced data from Geo‐Wiki to create a map that reflects the likelihood of cropland. Calibration with national and subnational crop statistics was then undertaken to distribute the cropland within each country and subnational unit. The new IIASA‐IFPRI cropland product has been validated using very high‐resolution satellite imagery via Geo‐Wiki and has an overall accuracy of 82.4%. It has also been compared with the EarthStat cropland product and shows a lower root mean square error on an independent data set collected from Geo‐Wiki. The first ever global field size map was produced at the same resolution as the IIASA‐IFPRI cropland map based on interpolation of field size data collected via a Geo‐Wiki crowdsourcing campaign. A validation exercise of the global field size map revealed satisfactory agreement with control data, particularly given the relatively modest size of the field size data set used to create the map. Both are critical inputs to global agricultural monitoring in the frame of GEOGLAM and will serve the global land modelling and integrated assessment community, in particular for improving land use models that require baseline cropland information. These products are freely available for downloading from the http://cropland.geo-wiki.org website.
National, regional and global CO2 emissions and removals from forests were estimated for the period 1990–2020 using as input the country reports of the Global Forest Resources Assessment 2020. The ...new Food and Agriculture Organization of the United Nations (FAO) estimates, based on a simple carbon stock change approach, update published information on net emissions and removals from forests in relation to (a) net forest conversion and (b) forest land. Results show a significant reduction in global emissions from net forest conversion over the study period, from a mean of 4.3 in 1991–2000 to 2.9 Gt CO2 yr−1 in 2016–2020. At the same time, forest land was a significant carbon sink globally but decreased in strength over the study period, from −3.5 to −2.6 Gt CO2 yr−1. Combining net forest conversion with forest land, our estimates indicated that globally forests were a small net source of CO2 to the atmosphere on average during 1990–2020, with mean net emissions of 0.4 Gt CO2 yr−1. The exception was the brief period 2011–2015, when forest land removals counterbalanced emissions from net forest conversion, resulting in a global net sink of −0.7 Gt CO2 yr−1. Importantly, the new estimates allow for the first time in the literature the characterization of forest emissions and removals for the decade just concluded, 2011–2020, showing that in this period the net contribution of forests to the atmosphere was very small, i.e., a sink of less than −0.2 Gt CO2 yr−1 – an estimate not yet reported in the literature. This near-zero balance was nonetheless the result of large global fluxes of opposite sign, namely net forest conversion emissions of 3.1 Gt CO2 yr−1 counterbalanced by net removals on forest land of −3.3 Gt CO2 yr−1. Finally, we compared our estimates with data independently reported by countries to the United Nations Framework on Climate Change, indicating close agreement between FAO and country emissions and removals estimates. Data from this study are openly available via the Zenodo portal (Tubiello, 2020), with DOI https://doi.org/10.5281/zenodo.3941973, as well as in the FAOSTAT (Food and Agriculture Organization Corporate Statistical Database) emissions database (FAO, 2021a).
Despite the importance of organic soils, including peatlands, in the global carbon cycle, detailed information on regional and global emissions is scarce. This is due to the difficulty to map, ...measure, and assess the complex dynamics of land, soil, and water interactions needed to assess the human-driven degradation of organic soils. We produced a new methodology for the comprehensive assessment of drained organic soils in agriculture and the estimation of the associated greenhouse gas emissions. Results indicated that over 25 million hectares of organic soils were drained worldwide for agriculture use, of which about 60% were in boreal and temperate cool areas, 34% in tropical areas, and 5% in warm temperate areas. Total emissions from the drainage were globally significant, totaling nearly one billion tonnes CO2eq annually. Of this, the CO2 component, about 780 million tonnes, represented more than one-fourth of total net CO2 emissions from agriculture, forestry, and land use. The bulk of these emissions came from a few tropical countries in Southeast Asia, and was linked to land clearing and drainage for crop cultivation. Geospatial data relative to this work were disseminated via the FAO geospatial server GeoNetwork, while the national aggregated statistics were disseminated via the FAOSTAT database.
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