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End date: 2024 × DDC: 570 × Type: Article × Publisher: Amsterdam [u.a.] : Elsevier × WGL Institute: PIK ×

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    Global and country-level data of the biodiversity footprints of 175 crops and pasture
    (Amsterdam [u.a.] : Elsevier, 2021) Beyer, Robert; Manica, Andrea
    The destruction of natural habitat for cropland and pasture represents a major threat to global biodiversity. Despite widespread societal concern about biodiversity loss associated with food production, consumer access to quantitative estimates of the impact of crop production on the world's species has been very limited compared to assessments of other environmental variables such as greenhouse gas emissions or water use. Here, we present a consistent dataset of the biodiversity footprints of pasture and 175 crops at the global and national level. The data were generated by combining maps of the global distribution of agricultural areas in the year 2000 with spatially explicit estimates of the biodiversity loss associated with the conversion of natural habitat to farmland. Estimates were derived for three common alternative measures of biodiversity - species richness, threatened species richness, and range rarity - of the world's mammals, birds, and amphibians. Our dataset provides important quantitative information for food consumers and policy makers, allowing them to take evidence-based decisions to reduce the biodiversity footprint of global food production.
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    Quantifying sustainable intensification of agriculture: The contribution of metrics and modelling
    (Amsterdam [u.a.] : Elsevier, 2021) Mouratiadou, Ioanna; Latka, Catharina; van der Hilst, Floor; Müller, Christoph; Berges, Regine; Bodirsky, Benjamin Leon; Ewert, Frank; Faye, Babacar; Heckelei, Thomas; Hoffmann, Munir; Lehtonen, Heikki; Lorite, Ignacio Jesus; Nendel, Claas; Palosuo, Taru; Rodríguez, Alfredo; Rötter, Reimund Paul; Ruiz-Ramos, Margarita; Stella, Tommaso; Webber, Heidi; Wicke, Birka
    Sustainable intensification (SI) of agriculture is a promising strategy for boosting the capacity of the agricultural sector to meet the growing demands for food and non-food products and services in a sustainable manner. Assessing and quantifying the options for SI remains a challenge due to its multiple dimensions and potential associated trade-offs. We contribute to overcoming this challenge by proposing an approach for the ex-ante evaluation of SI options and trade-offs to facilitate decision making in relation to SI. This approach is based on the utilization of a newly developed SI metrics framework (SIMeF) combined with agricultural systems modelling. We present SIMeF and its operationalization approach with modelling and evaluate the approach’s feasibility by assessing to what extent the SIMeF metrics can be quantified by representative agricultural systems models. SIMeF is based on the integration of academic and policy indicator frameworks, expert opinions, as well as the Sustainable Development Goals. Structured along seven SI domains and consisting of 37 themes, 142 sub-themes and 1128 metrics, it offers a holistic, generic, and policy-relevant dashboard for selecting the SI metrics to be quantified for the assessment of SI options in diverse contexts. The use of SIMeF with agricultural systems modelling allows the ex-ante assessment of SI options with respect to their productivity, resource use efficiency, environmental sustainability and, to a large extent, economic sustainability. However, we identify limitations to the use of modelling to represent several SI aspects related to social sustainability, certain ecological functions, the multi-functionality of agriculture, the management of losses and waste, and security and resilience. We suggest advancements in agricultural systems models and greater interdisciplinary and transdisciplinary integration to improve the ability to quantify SI metrics and to assess trade-offs across the various dimensions of SI.