Session
MO.1.D || Land Use and Biodiversity in Life Cycle Management
Authors
Mumm, Nico; Eberle, Ulrike
Abstract
Purpose. Agriculture today uses about 38 % of the global land area. Land use and land use change to meet food demand are major drivers of biodiversity loss. The Earth’s ecoregions have different ecological values and ecoregions and country boundaries do not usually coincide. The aim of this study is to develop a detailed dataset of crop specific ecoregion factors for countries (csEFs). Methods. To close this gap, spatial crop production data are combined with ecoregion shapefiles using a geographic information system (QGIS). The 10 x 10 km² spatial grid cells of MapSPAM provide plausible estimates for crop production data of 42 crops globally. Factors for the mapped ecoregions were taken from the classification of Lindner et al. (2019). For each crop and country, weighted ecoregion factors are calculated, using yield and harvested area as weighting factors. The ecoregion shapefiles are based on the classification of The Nature Conservancy. Results & Discussion. The developed dataset shows that csEFs within a country can vary significantly. In China the highest factor (arabica coffee with 0.408) is twice as high as the lowest (cotton with 0.204). Also, the example of soy production in the USA shows the importance of csEFs: The EF in the USA vary widely (0.096-0.24), but the csEF for soybeans is rather low (0.116). This is because the impact of an agricultural product on terrestrial biodiversity depends on the place of production. However, databases and also statistical data are usually available for countries, so that the csEFs developed here, help to refine the impact assessment. Conclusion. By using the factors presented here, it is possible to make a more accurate assessment of the impact on biodiversity than just using a rough estimate based only on the area covered. This is useful in LCA studies, where the exact origin of crops is not known: for example, when evaluating the total food consumption of a country.