Quantifying sustainable intensification of agriculture: The contribution of metrics and modelling
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
(2021) Ecological Indicators, volume 129, pp. 1 - 16
(Article)
Abstract
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
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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.
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Keywords: Ex-ante scenario assessment, Indicators, Metrics, Modelling of agricultural systems, Sustainable development goals, Sustainable intensification, General Decision Sciences, Ecology, Evolution, Behavior and Systematics, Ecology
ISSN: 1470-160X
Publisher: Elsevier
Note: Funding Information: This work was conducted in the context of the SUSTAg project, funded in the frame of the ERA-NET FACCE SURPLUS, which has received funding from the European Union's Horizon 2020 research and innovation programme [grant number 652615]. The work was supported by the Netherlands Organization for Scientific Research [grant number ALW.FACCE.4], the German Federal Ministry of Education and Research [grant numbers FKZ 031B0170B, FKZ 031B0170A], the Ministry of Agriculture and Forestry of Finland, the Spanish National Institute for Agricultural and Food Research and Technology [grant numbers ERA73-SUSTAG-UPM, ERA73-SUSTAG-IFAPA], Agencia Estatal de Investigaci?n [grant numbers MACSUR02-APCIN2016-0005-00-00], the Comunidad de Madrid (Spain) and Structural Funds 2014-2020 (European Regional Development Fund, European Social Fund) [grant number S2018/BAA-4330]. We would like to express our gratitude to the participants of the scientific workshop on SI metrics held in Berlin on 22nd May 2017. In particular, we acknowledge the valuable contributions of the following presenters and moderators of the scientific workshop on SI metrics: A. Beblek, J. Heinke, K. Helming, A. Meyer-Aurich, K. Schmidt, F. Sinabell and Gerrie van de Ven. We thank Ton Markus from the Cartography Department of the Faculty of Geosciences of Utrecht University for support in producing the figures and Meinou de Vries from Studio Infograph for the interactive visualization of the SIMeF presented in Supplementary data 2 of Appendix A. We thank the anonymous reviewers of the manuscript for their constructive comments. Funding Information: This work was conducted in the context of the SUSTAg project, funded in the frame of the ERA-NET FACCE SURPLUS, which has received funding from the European Union’s Horizon 2020 research and innovation programme [grant number 652615]. The work was supported by the Netherlands Organization for Scientific Research [grant number ALW.FACCE.4], the German Federal Ministry of Education and Research [grant numbers FKZ 031B0170B, FKZ 031B0170A], the Ministry of Agriculture and Forestry of Finland, the Spanish National Institute for Agricultural and Food Research and Technology [grant numbers ERA73-SUSTAG-UPM, ERA73-SUSTAG-IFAPA], Agencia Estatal de Investigación [grant numbers MACSUR02-APCIN2016-0005-00-00], the Comunidad de Madrid (Spain) and Structural Funds 2014-2020 (European Regional Development Fund, European Social Fund) [grant number S2018/BAA-4330]. We would like to express our gratitude to the participants of the scientific workshop on SI metrics held in Berlin on 22 nd May 2017. In particular, we acknowledge the valuable contributions of the following presenters and moderators of the scientific workshop on SI metrics: A. Beblek, J. Heinke, K. Helming, A. Meyer-Aurich, K. Schmidt, F. Sinabell and Gerrie van de Ven. We thank Ton Markus from the Cartography Department of the Faculty of Geosciences of Utrecht University for support in producing the figures and Meinou de Vries from Studio Infograph for the interactive visualization of the SIMeF presented in Supplementary data 2 of Appendix A. We thank the anonymous reviewers of the manuscript for their constructive comments. Publisher Copyright: © 2021 The Authors
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