Person: Claessens, L.
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Claessens
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L.
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Claessens, L.
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0000-0003-2961-8990 4 results
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- Chapter 10. Combining multiple technologies: Integrated soil fertility management(CAB International, 2022) Bekunda, M.; Chikowo, R.; Claessens, L.; Hoeschle-Zeledon, I.; Kihara, J.; Kizito, F.; Okori, P.; Sognigbé, N.; Thierfelder, C.
Publication - A spatial framework for ex-ante impact assessment of agricultural technologies(Elsevier, 2019) Andrade, J.F.; Rattalino Edreira, J.I.; Farrow, A.; Van Loon, M.P.; Craufurd, P.; Rurinda, J.; Shamie Zingore; Chamberlin, J.; Claessens, L.; Adewopo, J.; Ittersum, M.K. van; Cassman, K.G.; Grassini, P.Traditional agricultural research and extension relies on replicated field experiments, on-farm trials, and demonstration plots to evaluate and adapt agronomic technologies that aim to increase productivity, reduce risk, and protect the environment for a given biophysical and socio-economic context. To date, these efforts lack a generic and robust spatial framework for ex-ante assessment that: (i) provides strategic insight to guide decisions about the number and location of testing sites, (ii) define the target domain for scaling-out a given technology or technology package, and (iii) estimate potential impact from widespread adoption of the technology(ies) being evaluated. In this study, we developed a data-rich spatial framework to guide agricultural research and development (AR&D) prioritization and to perform ex-ante impact assessment. The framework uses “technology extrapolation domains”, which delineate regions with similar climate and soil type combined with other biophysical and socio-economic factors that influence technology adoption. We provide proof of concept for the framework using a maize agronomy project in three sub-Saharan Africa countries (Ethiopia, Nigeria, and Tanzania) as a case study. We used maize area and rural population coverage as indicators to estimate potential project impact in each country. The project conducted 496 nutrient omission trials located at both on-farm and research station sites across these three countries. Reallocation of test sites towards domains with a larger proportion of national maize area could increase coverage of maize area by 79–134% and of rural population by 14–33% in Nigeria and Ethiopia. This study represents a first step in developing a generic, transparent, and scientifically robust framework to estimate ex-ante impact of AR&D programs that aim to increase food production and reduce poverty and hunger.
Publication - A framework for priority-setting in climate smart agriculture research(Elsevier, 2018) Thornton, P.; Whitbread, A.; Baedeker, T.; Cairns, J.E.; Claessens, L.; Baethgen, W.; Bunn, C.; Friedmann, M.; Giller, K.E.; Herrero, M.; Howden, M.; Kilcline, K.; Nangia, V.; Ramirez-Villegas, J.; Shalander Kumar; West, P.C.; Keating, B.Climate-smart agriculture (CSA) is widely promoted as an approach for reorienting agricultural development under the realities of climate change. Prioritising research-for-development activities is crucial, given the need to utilise scarce resources as effectively as possible. However, no framework exists for assessing and comparing different CSA research investments. Several aspects make it challenging to prioritise CSA research, including its multi-dimensional nature (productivity, adaptation and mitigation), the uncertainty surrounding many climate impacts, and the scale and temporal dependencies that may affect the benefits and costs of CSA adoption. Here we propose a framework for prioritising agricultural research investments across scales and review different approaches to setting priorities among agricultural research projects. Many priority-setting case studies address the short- to medium-term and at relatively local scales. We suggest that a mix of actions that span spatial and temporal time scales is needed to be adaptive to a changing climate, address immediate problems and create enabling conditions for enduring change.
Publication - Can sub-Saharan Africa feed itself?(National Academy of Sciences, 2016) Ittersum, M.K. van; Bussel, L.G.J. Van; Wolf, J.; Grassini, P.; Wart, J. van; Guilpart, N.; Claessens, L.; De Groote, H.; Wiebe, K.; Mason-D'croz, D.; Haishun Yang; Boogaard, H.; Van Oort, P.; Van Loon, M.P.; Saito, K.; Adimo, O.; Adjei-Nsiah, S.; Agali, A.; Bala, A.; Chikowo, R.; Kaizzi, K.; Kouressy, M.; Makoi, J.H.; Ouattara, K.; Tesfaye, K.; Cassman, K.G.Although global food demand is expected to increase 60% by 2050 compared with 2005/2007, the rise will be much greater in sub-Saharan Africa (SSA). Indeed, SSA is the region at greatest food security risk because by 2050 its population will increase 2.5-fold and demand for cereals approximately triple, whereas current levels of cereal consumption already depend on substantial imports. At issue is whether SSA can meet this vast increase in cereal demand without greater reliance on cereal imports or major expansion of agricultural area and associated biodiversity loss and greenhouse gas emissions. Recent studies indicate that the global increase in food demand by 2050 can be met through closing the gap between current farm yield and yield potential on existing cropland. Here, however, we estimate it will not be feasible to meet future SSA cereal demand on existing production area by yield gap closure alone. Our agronomically robust yield gap analysis for 10 countries in SSA using location-specific data and a spatial upscaling approach reveals that, in addition to yield gap closure, other more complex and uncertain components of intensification are also needed, i.e., increasing cropping intensity (the number of crops grown per 12 mo on the same field) and sustainable expansion of irrigated production area. If intensification is not successful and massive cropland land expansion is to be avoided, SSA will depend much more on imports of cereals than it does today.
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