M. van Ittersum1 – R. Schils1 – W. van der Werf2 – G. van de Ven1 – A. van der Linden 1,3 – K. Giller1 – M. van Noordwijk 1,4
1 Plant Production Systems, Wageningen University, email: martin.vanittersum@wur.nl
2 Centre for Crop Systems Analysis, Wageningen University
3 Animal Production Systems, Wageningen University
4 World Agroforestry Centre (ICRAF), Bogor, Indonesia Introduction
Yield gap analysis has been a well know notion in crop science since the late 1980s, but it has been become popular only recently. It is generally regarded a helpful starting point for mapping the opportunities for sustainable intensification of agricultural sys-tems. Different methods exist to quantify and map yield gaps of our major food crops grown as sole crops (Van Ittersum et al., 2013). In significant parts of the world (e.g. in Sub-Saharan Africa and China), however, crops are not grown as sole crops, but in intercropping systems. This clearly complicates yield gap assessment. Also, at least 30
% of the cereals is fed to livestock and livestock products constitute a major and in-creasing share of our diets. Many of the world’s agricultural systems are in fact crop-livestock systems. Finally, perennial crops are an important source of our nutrition and a component of agricultural systems that increases in relevance. How can the yield gap notion be applied to such more integrated or complex systems and how does it drive model development? Before addressing this question we briefly summarize a global approach with local relevance for sole crops, setting the scene for other systems.
A global approach with local relevance for yield gap analysis of food crops
In the global yield gap atlas project (GYGA – www.yieldgap.org) a global protocol has been developed using a climate zonation, crop area masks, local weather data and the key soil (in particular soil water holding capacity and rootable soil depth) and cropping system information (sowing dates, cultivars, etc.) for the hot spots of crop production, combined with data on observed actual farmers’ yields (Grassini et al., 2015; Van Bus-sel et al., 2015). Crop models are used to assess potential or water-limited potential yields. The global protocol is always applied with local data and local experts are in-volved in the evaluation of modelling and yield gap analysis results. It has now been applied to 25 countries and another ca. 20 countries are on their way, thus creating a unique database (www.yieldgap.org).
Intercrops
Examples of important intercropping systems are wheat-maize, wheat-soybean and maize-cotton intercrops. Such systems often have a land equivalent ratio >1, which makes them efficient in terms of land use. Yield gap analysis for these systems is com-plex because statistics usually do not discriminate between sole and intercrops (also affecting reported yields of sole crops) and because estimation of potential yields
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quires a different type of (inter)crop growth model. In this Symposium Gou et al., pre-sent an intercrop model accounting for the light interception of rows of (different) crops. This model allows the assessment of potential yields of intercrops with a given row configuration. It remains a challenge, however, to find the optimum row configu-ration of intercrops and thus to define the ‘potential’ yield of a given intercrop.
Livestock production and crop-livestock systems
Building upon the work of Van de Ven et al., (2003), Van der Linden et al., (2015) trans-lated the concepts of potential, limited and actual yields, as well as yield gaps to live-stock production. They are also developing a dynamic simulation model that allows the estimation of potential and feed-limited (both quality and quantity) beef production levels of different breeds in different climates. An additional challenge in livestock production is the upscaling from individual animals to the (management) unit of a herd. While livestock production and yield gaps can be expressed per animal, per unit of animal body mass or per unit of feed intake, it is to be expressed in kg livestock product ha-1 year-1 from the integrated crop-livestock perspective. The combined use of crop and livestock production models allows the analysis of crop-livestock systems.
Perennial crops
Perennial crops have features of scaling (from trees to canopies and replacement;
single season to multi-years) and challenges with experimentation in common. Recent-ly an oil palm model with monthRecent-ly time steps and for potential growing conditions has been developed to assess yield gaps of oil palm plantations (Hoffman et al., 2014). This approach will be further developed and applied to cocoa and other perennial systems.
In conclusion
In the presentation these advances in yield gap analysis methods will be presented and illustrated. Common denominators, such as land equivalent ratios, and challenges, including scaling and the use of (local) data will be discussed.
References
Hoffman, M.P., Castaneda Vera, A., Van Wijk, M.T., Giller, K.E., Oberthűr, T., Donough, C., Whitbread, A.M.
(2014). Simulating potential growth and yield of oil palm (Elaeis guineensis) with PALMSIM: Model description, evaluation and application. Agricultural Systems, 131, 1-10.
Van Bussel, L.G.J., Grassini, P., Van Wart, J., Wolf, J., Claessens, L., Yang, H., Boogaard, H., de Groot, H., Saito, K., Cassman, K.G., van Ittersum, M.K. (2015). From field to atlas: Upscaling of location-specific yield gap estimates. Field Crops Research 177, 98-108.
Van de Ven, G.W.J., De Ridder, N., Van Keulen, H., Van Ittersum, M.K. (2003). Concepts in production ecology for analysis and design of animal and plant-animal production systems. Agricultural Systems 76, 507-525.
Van der Linden, A., Oosting, S.J., van de Ven, G.W.J., de Boer, I.J.M., van Ittersum, M.K. (2015). A framework for quantitative analysis of livestock systems using theoretical concepts of production ecology.
Agricultural Systems 139, 100-109.
Van Ittersum, M.K., Cassman, K.G., Grassini, P., Wolf, J., Tittonell, P., Hochman, Z. (2013). Yield gap analysis with local to global relevance—A review. Field Crops Research 143, 4-17.
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Integrated crop water management might sustainably halve the global food gap
J. Jägermeyr1 – D. Gerten1 – S. Schaphoff1 –J. Heinke1,2 – W. Lucht1,4
1 Research Domain Earth System Analysis, Potsdam Institute for Climate Impact Research (PIK), Telegra-phenberg A62, 14473 Potsdam, Germany
2 International Livestock Research Institute (ILRI), P.O. Box 30709, Nairobi, 00100 Kenya
3 Commonwealth Scientific and Industrial Research Organization (CSIRO), St. Lucia, QLD 4067, Australia
4 Geography Department, Humboldt-Universität zu Berlin, Unter den Linden 6, 10099 Berlin, Germany Correspondence: jonas.jaegermeyr@pik-potsdam.de
Introduction
As planetary boundaries are being approached rapidly, humanity has little room for additional expansion and conventional intensification of agriculture, while a growing world population further spreads the food gap. Improved on-farm water management can close water-related yield gaps ecologically and to a considerable degree, but its global significance remains unclear. In this modeling study we investigate systematically to what extent integrated crop water management might contribute to closing the global food gap, constrained by the assumption that pressure on water resources and land does not increase.
Materials and Methods
Using a process-based bio-/agrosphere model, we simulate the yield-increasing potential of elevated irrigation water productivity (including irrigation expansion with thus saved water) and optimized use of in situ precipitation water (alleviated soil evaporation, enhanced infiltration, supplemental irrigation) for current and projected future climate (from 20 climate models, four CO2 concentration pathways, and different CO2 fertilization effects). Respective water management interventions are simulated in a mechanistic way based on a novel degree of process-detail and high spatio-temporal resolution.
Results and Discussion
Results show that irrigation improvements can save substantial amounts of water in many river basins (>30 % of non-productive water consumption, in a "best-practice"
scenario), and if rerouted to neighboring rainfed systems, can boost yields significantly (4-14\ % global increase). Low-tech solutions for small-scale farmers on water-limited croplands show the potential to increase rainfed yields to a similar extent. In combination, the here studied ambitious, yet achievable integrated water management strategies could increase global production by 40 % and close the water-related yield gap by 62 %. Unabated climate change will have adverse effects on crop yields in many regions, but water management as analyzed here can buffer such effects to a significant degree.
79 Conclusions
Simulated yield gains might be sufficient to halve the global food gap by 2050 on a sustainable basis. Overall, this study highlights, development goals that fail focusing on systematic implementation of crop water management, substantially miss opportunities to reduce pressure on planetary boundaries, while advancing a sustainable food system and its climate resilience.
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