Global Food Security 38 (2023) 100710 Contents lists available at ScienceDirect Global Food Security journal homepage: www.elsevier.com/locate/gfs Scientific agenda for climate risk and impact assessment of West African cropping systems M. Diancoumba a,c,*, D. MacCarthy b, H. Webber c,d, F. Akinseye e,f, B. Faye g, F. Noulèkoun h, A. Whitbread i, M. Corbeels j,k, l, N. Worou m a International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Bamako, Mali b Soil and Irrigation Research Centre, Kpong, College of Basic and Applied Sciences, University of Ghana, Ghana c Institute of Landscape Systems Analysis, Leibniz Centre for Agricultural Landscape Research (ZALF), Eberswalder Straße 84, 15374, Müncheberg, Germany d Brandenburg University of Technology, Faculty of Environment and Natural Sciences, Cottbus, Germany e International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Kano, Nigeria f Centre d’Étude Régional pour l’Amélioration de l’Adaptation à la Sécheresse (CERAAS), Thiès Escale, Senegal g Université du Sine Saloum El Hadj Ibrahima Niass (USSEIN), Kaolack, Senegal h Environmental Science and Ecological Engineering, College of Life Science and Biotechnology, Korea University, Seoul, Republic of Korea i Sustainable Livestock System Program, International Livestock Research Institute (ILRI), Dar es Salaam, Tanzania j AIDA, Univ Montpellier, CIRAD, Montpellier, France k CIRAD, UPR AIDA, F-34398, Montpellier, France l International Institute of Tropical Agriculture (IITA), PO Box 30772, Nairobi, 00100, Kenya m Sustainable Livestock System Program, International Livestock Research Institute (ILRI), Dakar, Senegal Process-based cropping systems models are a key tool to assess the African Science Service Centre on Climate Change and Adapted Land impact of climate variability and change, as well as the effect of crop Use (WASCAL) and the Consortium of International Agricultural management options on crop yields, soil fertility and cropping systems Research Centers (CGIAR). Studies from these and other initiatives and resilience (Boote et al., 2013; Jones et al., 2003; Rosenzweig et al., projects in the region (Faye et al., 2018; Traore et al., 2017) have pro- 2014). When correctly parameterized, they provide valuable insights vided evidence of climate change impact and crop-level adaptations that into the contributions of the various factors determining crop responses have been considered by the Intergovernmental Panel on Climate to weather and climate change. Simply put, when capturing the relevant Change. plant and soil processes and calibrated to local crops and crop man- Yet, several challenges preclude cropping systems models from agement, they are an affordable alternative and complement to tradi- providing robust evidence to support more climate resilient cropping tional field experimentation (Whitbread et al., 2010). This is particularly and farming systems. In particular, models differ in their description and true for weather extremes which can occur in countless combinations representation of the complex and dynamic processes of crop growth, and times in the growing season. Coupled with climate model pro- soil nutrient availability, and soil water balances, as well as in the jections, outputs from cropping systems models can inform adaptations appropriate level of parametrization for specific agro-ecological condi- to climate risk and change. Finally, when combined with whole-farm tions (Akinseye et al., 2017). This remains problematic for West African economic models, cropping systems models can allow participatory cropping systems, as a robust calibration and testing of models that were scenario analysis of farm management strategies and help to inform developed for other parts of the world is often not possible due to limited policy interventions around affordable and feasible measures to enable data availability. This can generate unacceptably large uncertainties in and incentivize farmers’ investments under highly variable and risky model outputs (Saltelli et al., 2019). At the same time, there has been weather conditions (Ricome et al., 2017). limited testing of cropping systems models for the management prac- Cropping systems models are increasingly used by the West African tices(MacCarthy et al., 2017; Tittonell et al., 2008), crops (Tui et al., scientific community (Amouzou et al., 2019; Rezaei et al., 2014; Guan 2021), soils and weather conditions which predominate in the region et al., 2017; Sultan et al., 2013; Traore et al., 2017) supported by efforts (Sultan et al., 2013). Given the urgency of finding solutions for sus- in the past decade such as the Agricultural Model Intercomparison and tainable agricultural development in the face of increasing climate risks, Improvement Project (AgMIP), the training programs of the West a robust scientific basis needs to be built to support the desired * Corresponding author. International Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Bamako, Mali. E-mail addresses: madina.diancoumba@zalf.de, madina.diancoumba@icrisat.org (M. Diancoumba). https://doi.org/10.1016/j.gfs.2023.100710 Received 13 March 2023; Received in revised form 11 July 2023; Accepted 12 July 2023 Available online 18 July 2023 2211-9124/© 2023 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by- nc-nd/4.0/). M. Diancoumba et al. G l o b a l F o o d S e c u r it y 38 (2023) 100710 transformation of cropping systems in West Africa. This requires a focus expertise and associated models and datasets to reside and grow in the on the following action points: i) capacity building in crop modelling, ii) region. improving crop models for the conditions of West Africa, iii) imple- menting FAIR data principles, iv) enhancing research partnerships in 2. Better models crop modelling, and v) using crop models in co-development approaches (Fig. 1). Cropping systems in West Africa are characterized by complex and heterogeneous agricultural landscape structures, such as intercropping, 1. Capacity building agroforestry systems (e.g. parklands), frequently degraded soils, commonly high weed pressure and diverse soil conditions together with Skilled human resources to develop and apply cropping systems generally low levels of nutrient inputs. All of these characteristics can models are critical. Building the capacity of young West African re- have a significant influence on the soil water and nutrient balances and searchers in crop modelling are therefore a key action in which policy on crop productivity. Currently, most of these characteristics and related makers should invest. In this context, university curricula should processes are not well represented in existing cropping systems models. increasingly include courses like cropping systems and agroecosystems In fact, models should be able to better capture the heterogeneity of analysis, systems modeling in general and crop model development in production factors. Therefore, further experimental research efforts are particular. Besides, creating opportunities for graduates in applied needed to adequately understand the full complexity of these factors and mathematics and physics like from the African Institute for Mathemat- their interactions. Additionally, key staple crops of West Africa, such as ical Sciences (AIMS), to work together with agronomists and scientists pearl millet (Pennisetum glaucum (L.) R. Br.), sorghum (Sorghum from related disciplines such as environmental scientists and socio- bicolor (L.) Moench) and cassava (Manihot esculenta Crantz, Euphor- economists, can support strengthening interdisciplinary expertise, and, biaceae), are still underrepresented in standard model releases (e.g. more specifically, will enable them to utilize their advanced analytical LINTUL-Cassava by Adiele et al. (2022), DSSAT-millet/sorghum by skills for the development and improvement of cropping systems models Sanon et al. (2014), APSIM-sorghum by Akinseye et al. (2017), for West Africa. In fact, bringing together experts from these different STICS-sorghum by Traoré et al. (2022)), and orphan crops like, yam, disciplines will lead to a more comprehensive understanding of the Bambara groundnut (Karunaratne et al., 2010) and fonio, are also not complex processes and their interactions occurring within the West Af- well or at all represented. While efforts to improve currently available rican farming systems. This will allow the development and improve- cropping systems models should intensify, we believe that now is an ment of context-specific crop models. Therefore, research programs like opportune moment to develop a regional modeling framework that WASCAL should further promote model development and improvement effectively captures the diverse cropping systems in the region. This as a key pillar of their training component. Furthermore, targeted endeavor will not only contribute to improved understanding of climate training programs, such as the Crop Models for Risk Assessment (CMRA) impacts on crop production but also aligns with capacity building ob- 2022 Summer School (here), on assessing climate risks in cropping jectives in crop modelling. Importantly, this regional modeling frame- systems should be organized on a regular basis. Such schools create an work should integrate the interactions between soil nutrient deficiency opportunity for the exchange of knowledge, expertise and lessons learnt (i.e., nitrogen (N), phosphorus (P), potassium (K), and micronutrients) between practitioners and could lead to a community of practice at the and climate conditions. About 75% of sub-Saharan African soils are re- regional and global scale. Finally, supporting the capabilities associated ported to show plant nutrient deficiency (IFDC, 2006; Leiser et al., with crop modeling are best achieved through institutionalization (e.g., 2012). For instance, the limited availability of P was reported by permanent crop modelling positions in the relevant departments of local Buerkert et al. (2000) as one of the major constraints to cereal produc- universities and national agricultural research institutes) allowing the tion in West Africa. Therefore, it will be important to better simulate the Fig. 1. Required actions for impact through cropping systems modelling. 2 M. Diancoumba et al. G l o b a l F o o d S e c u r it y 38 (2023) 100710 impact of P stress (and that of other nutrients) on crop growth under innovations at field, farm and governance levels. An approach using changing climate. Besides, accurate simulation of the effect of changes in participatory processes like proposed by (Schmitt et al., 2017) can be temperature and water supply on N mineralization, nitrate leaching and used as an initial attempt; in this approach stakeholders co-develop N uptake by the crops is crucial given rise in the number of extreme scenarios of crop management adaptation strategies to climate change weather events (Falconnier et al., 2020). Finally, as pest and disease and evaluate the results of the modelling from their perspectives. This stresses on crop growth are expected to increase with climate change, will ensure that model outputs are suitable for the intended use. Thus, it the modeling framework should also account for these (Brévault et al., is key that alongside formal cooperation between universities and 2014). research organizations, other key private and public partners engage in using knowledge derived from crop modelling to enhance value addition 3. FAIR cropping system data and offer new products and services. By addressing the above action points, it will be possible to design Availability and accessibility of high-quality experimental data have more sustainable and climate resilient agricultural systems that can been identified as a major factor that limits the usefulness of crop model support the needs of local communities for generations to come. applications in West Africa. Here, high-quality experimental data refer to FAIR (Findable, Accessible, Interoperable, and Reusable) data ob- 6. Conclusion tained on one or more variables from a particular field experiment conducted using standard research protocols. These variables include In our view, the actions we propose are highly interdependent and of weather, crop, soil, and crop management data collected at the required equal importance, as they are closely related and must be considered details and frequencies. As an immediate response to data constraints, conjointly. Investments in this proposed agenda is needed if science, and national agricultural research centers need improved data storage and in particular cropping systems modelling, is to support solutions to management systems for the already existing data. Besides, future sustainable crop production in the face of climate change and risk, and datasets from advanced research infrastructure and experimental ap- strengthen the scientific excellence and capacity in crop modelling of the proaches will better support climate risk assessments, for example soil agricultural research institutions and universities in West Africa. moisture monitoring networks or vegetation and drought-related indices from remote-sensing imagery (Leroux et al., 2019). Standard operating Author contributions procedures (SOPs) are needed for describing the steps of data collection, methods of collection and ways to safely store the collected data. Novel All authors listed in this paper have made a considerable and data collection methods, such as the use of smartphone applications to e. knowledgeable contribution to this work, and approved it for g. monitor crop growth, must be demystified and promoted, ensuring publication. appropriate legal frameworks are in place to protect privacy of citizens. Lastly, there is also the need to encourage allocation of donor funds to Funding include the collection, management, and reuse of primary data as an integral part of research projects. This study resulted from a summer school organized by the Leibniz Centre for Agricultural Landscape Research (ZALF) in collaboration with 4. Research partnerships the International Crops Research Institute for the Semi-Arid Tropics (ICRISAT) that was funded by the Volkswagen Foundation and the Nurturing partnership and networking among crop modelers of the Accelerating the Impact of CGIAR Climate Research for Africa region can provide opportunities for co-learning and exchange of ideas, (AICCRA). thereby accessing a broader range of resources and expertise. These will contribute to the overall development of modeling competencies and skills. A starting point is to raise awareness about the importance of crop Declaration of competing interest models in building resilient farming systems in West Africa. This can be done through workshops that facilitate meaningful interactions among The authors have no conflicts of interest to declare that are relevant participants from across the region who share common research in- to the content of this article. terests. 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