Global food system pressure data

These global raster data describe the environmental footprint of the majority of food production for 2017. Please refer to the accompanying publication (and supporting methods; Halpern et al. 2022. The environmental footprint of global food production. Nature Sustainability) for more information. We map four dominant global pressures of food production: disturbance (km2eq); blue freshwater consumption (m3 water); excess nutrients (tonnes NP); and greenhouse gas emissions (tonnes CO2eq). Categories of food include 26 crop categories (plus fodder, which is only consumed as feed); 6 livestock animals (cattle, buffalo, goats, sheep, pigs, chickens); 7 categories of marine fisheries, including forage fish species used for fishmeal and oil, other small pelagics, medium pelagics, large pelagics, benthic, demersal, and reef-associated; freshwater fisheries, with one group for all sizes and taxa; and 6 categories of marine aquaculture, including salmonids, unfed or algae fed shellfish, shrimp and prawns, tuna, other marine finfish, other crustaceans. We primarily assess pressures from sources occurring within the farm-gate. In most cases, we exclude activities occurring beyond the farm-gate, such as processing and transportation of product, manufacture of equipment, and extraction of fuel because we were generally unable to map the location of these activities. For feed components, we map the pressures to the location where the crops are likely grown, after accounting for trade, or fish are captured (vs. where they are fed to animals). In addition to the raw data files, we also provide rescaled pressure data and a cumulative pressure index that combines the 4 pressures. To calculate the cumulative pressure, we adopted similar methods as other cumulative measures, rescaling each individual pressure (GHG, FW, NP, D) by dividing the values in each pixel (i) by the total global pressure summed across all food systems and pixels (T), such that each pixel describes its proportional contribution to the global total for that pressure. We then summed these rescaled pressure layers to obtain a total cumulative pressure score (CP) for each pixel i, such that CPi = GHGi/GHGT + FWi/FWT + NPi/NPT + Di/DT (raster cell values are multiplied by 1000000 to avoid small numbers and rounding errors). The result is that each rescaled pixel is a unitless value describing its proportional contribution to the total global pressure. The cumulative pressure index allows direct comparisons among foods, regions, and pressures to identify where: individual pressures are high relative to other pressures, multiple pressures overlap, and hotspots of cumulative pressure are located. This information provides a more complete picture of the environmental pressures occurring at any global area and from each food type. We us the Gall-Peters equal area coordinate reference system with a resolution of 36km2. This dataset is identical to an earlier version, https://knb.ecoinformatics.org/view/doi:10.5063/F1V69H1B, with the exception that two new files have been added for completeness. These two files are food_rgns.tif and food_rgns_xy.csv.本全球栅格数据（raster data）描述了2017年全球绝大多数食品生产活动的环境足迹（environmental footprint）。如需了解更多细节，请参阅随附的发表文献及补充方法：Halpern等人2022年发表于《Nature Sustainability》的《全球食品生产的环境足迹》一文。 本数据集刻画了食品生产带来的四大全球主导环境压力：土地扰动（km2eq）、蓝色淡水消耗量（m3 water）、过量养分负荷（tonnes NP）以及温室气体排放量（tonnes CO2eq）。食品类别涵盖26类农作物（外加仅作为饲料的饲草）、6类畜禽（牛、水牛、山羊、绵羊、猪、鸡）、7类海洋渔业（包括用于制作鱼粉和鱼油的饵料鱼种、小型中上层鱼类、中型中上层鱼类、大型中上层鱼类、底栖鱼类、底层鱼类以及礁栖鱼类）、涵盖所有体型与类群的淡水渔业，以及6类海洋水产养殖品类：鲑科鱼类、非投饵或藻类投饵贝类、虾类与对虾、金枪鱼、其他海洋硬骨鱼类以及其他甲壳类动物。 本研究主要评估农场门槛范围内的生产活动带来的环境压力。多数情况下，我们未纳入农场门槛外的活动，如产品加工与运输、设备制造以及燃料开采——这类活动的区位通常难以通过栅格刻画。对于饲料组分，我们会在考虑贸易流通后，将压力映射至农作物实际种植地或鱼类捕捞地（而非饲料投喂动物的场地）。 除原始数据文件外，本数据集还提供经标准化处理的压力数据，以及整合四大压力的累积压力指数（cumulative pressure index）。累积压力的计算采用与其他同类累积度量一致的方法：将每个栅格像元（pixel，i）的单压力数值，除以全球所有食品生产系统与所有栅格像元的总压力值（T），以此将温室气体（GHG）、淡水（FW）、氮磷养分（NP）以及土地扰动（D）这四类单压力标准化为该栅格像元对应压力对全球总压力的比例贡献。随后将这些标准化后的压力图层相加，得到每个栅格像元i的总累积压力得分（CP），计算公式为：CPi = GHGi/GHGT + FWi/FWT + NPi/NPT + Di/DT（栅格像元数值已乘以1000000以避免极小数值与舍入误差）。经标准化后的栅格像元数值均为无单位值，用于描述其对全球总压力的比例贡献。 该累积压力指数可实现不同食品品类、区域与压力类型间的直接对比，用于识别：单压力相对偏高的区域、多重压力叠加区域，以及累积压力热点区域。该数据集可为全球任意区域及各类食品生产带来的环境压力提供更完整的刻画视角。 本数据集采用Gall-Peters等面积坐标参考系统（equal area coordinate reference system），栅格分辨率为36平方千米。 本数据集与早期版本（https://knb.ecoinformatics.org/view/doi:10.5063/F1V69H1B）基本一致，仅为提升完整性新增了两个文件：food_rgns.tif与food_rgns_xy.csv。