Chinese Academy of Agricultural Sciences (CAAS) Training

By Daniel Mason-D'Croz and Shahnila Dunston, IFPRI—

In collaboration with the Chinese Academy of Agricultural Sciences (CAAS), the International Food Policy Research Institute (IFPRI) presented a 5-day short-course on scenario analysis and economic modeling with IFPRI’s International Model for Policy Analysis of Agricultural Commodities and Trade (IMPACT). The course was hosted by CAAS in Beijing, China from 18-22 September 2017. The course was organized with the objective to introduce IMPACT to 12 participants invited by CAAS, and to help them determine how IMPACT might be used to contribute to their current research on Sino-African technology transfers, as well as potential China-specific country analysis.

Speed-Dating

The course was led by Daniel Mason-D’Croz and Shahnila Dunston of IFPRI’s IMPACT team. They presented materials on a variety of scenario design methodologies, an introduction to how to use IMPACT, as well as the underlying economic theory behind IMPACT. The course was organized to be interactive, and walked participants through practical exercises of how IFPRI uses IMPACT to conduct ex-ante analysis.

Developing Factors of Change

The course provided a valuable opportunity to network with China experts, and to hopefully will serve as the basis of future collaboration and knowledge exchange between CAAS and IFPRI. Keith Wiebe of IFPRI also joined Daniel and Shahnila to meet with CAAS officials regarding possible next steps for collaboration.

MINK: Process-based crop modeling for global food security

By Richard Robertson, IFPRI —

Over the last decade, computer models of crop growth have increasingly been used to understand how climate change may affect the world's capacity to produce food. The International Food Policy Research Institute (IFPRI) has undertaken a major sustained effort to analyze changes in the productivity of major crops across the entire world. The results are integrated into economic modeling efforts ranging from household to country-level economy-wide models to the global agricultural sector partial-equilibrium economic model known as IMPACT. With the models working together, researchers can examine how biophysical changes in crop growth interact with changes in social and economic conditions.

Now, for the first time, IFPRI is releasing a comprehensive volume describing the global-scale crop modeling system behind IMPACT known as “Mink” for short. Download here.

Mink generates yield maps for the entire world that can be compared to identify locations most likely to be affected by climate change.

Crop modeling starts at the field level and scaling this up to the global level is challenging. Climate data must be collated, processed, and formatted. Representative crop varieties and planting calendars have to be chosen. Fertilizer input levels need to be specified. Myriad other assumptions need to be considered and appropriate values and strategies determined. And that is just the preparation phase. All the data then have to be organized, exported, and run through the crop models to obtain simulated yields under different climate scenarios and production environments. This necessitates employing parallel computing to get the job done quickly enough to be useful. And then the reams of output data must be organized, manipulated, analyzed, and finally interpreted to provide context as well as specific information so policymakers can plan appropriately for the future.

Collaborators from across the CGIAR and universities in India gather at ICRISAT to learn how to use Mink in support of their own research.

Naturally, with so much going on, the process can be mysterious for those looking in from the outside and potentially confusing even for those on the inside.

The document addresses how Mink works at several different levels. There is the broad discussion of interest to policymakers and managers concerning how global-scale crop modeling can be used, its strengths and weaknesses, how to think about the issues, and where it sits in the wider context of agricultural and policy research. At a middle level, every step of the process is described for those who wish to understand how it works so they can use the results properly, but not necessarily generate the numbers themselves. Along the way, though, various tips, tricks, and lessons learned are revealed for those who do, in fact, wish to replicate this kind of work on their own. And finally, for collaborators and researchers who wish to use Mink themselves, there is the nitty-gritty, nuts-and-bolts level documentation and tutorial aspects that literally say "Change this number; click here and drag there."

Mink has been used to provide insight for numerous reports, peer-reviewed journal articles, and the popular press, some examples being:

National Geographic. Climate Change: 5 Ways It Will Affect You: Crops. http://www.nationalgeographic.com/climate-change/how-to-live-with-it/crops.html

Rosegrant et al. 2017. Quantitative foresight modeling to inform the CGIAR research portfolio. http://ebrary.ifpri.org/cdm/ref/collection/p15738coll2/id/131144

Islam et al. 2016. Structural approaches to modeling the impact of climate change and adaptation technologies on crop yields and food security. Global Food Security 10: 63-70. http://dx.doi.org/10.1016/j.gfs.2016.08.003

Wiebe et al. 2015. Climate change impacts on agriculture in 2050 under a range of plausible socioeconomic and emissions scenarios. Environmental Research Letters 10: 085010. http://dx.doi.org/10.1088/1748-9326/10/8/085010

Müller and Robertson. 2014. Projecting future crop productivity for global economic modeling. Agricultural Economics 45: 37-50. http://dx.doi.org/10.1111/agec.12088

Rosegrant et al. 2014. Food security in a world of natural resource scarcity: The role of agricultural technologies. http://dx.doi.org/10.2499/9780896298477

We hope this volume will be a valuable resource for global modelers running simulations, their collaborators making use of the results, and ultimately for policymakers trying to determine appropriate courses of action in a changing world.

Major and ongoing support for this work has been provided by the Bill & Melinda Gates Foundation and the CGIAR Research Program on Policies, Institutions, and Markets (PIM) through the Global Futures and Strategic Foresight Project.

Global Futures & Strategic Foresight Extended Team Meeting at IRRI, 15-19 May 2017

By Keith Wiebe — 

IRRI recently hosted the Global Futures & Strategic Foresight (GFSF) Extended Team Meeting and Writeshop from May 15-19, 2017. GFSF is a CGIAR initiative to explore long-term trends, challenges, and policy options for food and agriculture through multidisciplinary foresight analysis. GFSF is led by IFPRI in collaboration with AfricaRice, Bioversity, CIAT, CIFOR, CIMMYT, CIP, ICARDA, ICRAF, ICRISAT, IITA, ILRI, IRRI, IWMI, and WorldFish. The meeting was led by Keith Wiebe (IFPRI) and Steve Prager (CIAT), with participants from across the CGIAR.

The week-long meeting and writeshop focused on the preparation of a series of papers for an upcoming special issue of the journal Global Food Security. The papers draw on recent analysis of alternative agricultural research and investment scenarios, and will focus on a range of commodities, regions, and cross-cutting topics. It is hoped that the results will help inform decision making in the CGIAR and its partners. GFSF is funded by the CGIAR Research Program on Policies, Institutions, and Markets (PIM), the Bill & Melinda Gates Foundation, and other donors.

 

2017 Global Food Policy Report

We are pleased to announce that we are now going to be making a regular contribution to IFPRI’s annual flagship publication, the Global Food Policy Report, in the form of a statistical annex presenting up-to-date projections for key indicators of production, consumption, trade, and hunger from the IMPACT system of models.  Click here for more information on the 2017 Global Food Policy Report.

We are also making these annex tables available for download via our dedicated Dataverse portal.

Annex Table 6 is available in extended format.

Annex Table 7 is available in extended format.

Exploring impacts of climate and socioeconomic change in West Africa

By Daniel Mason-D'Croz and Shahnila Islam, IFPRI

Climate change will likely have a negative effect on the agriculture sector in West Africa due to changing precipitation patterns and increasing temperatures. These changes can have negative impacts on food security in the region and, ultimately, the consequences of these changes will depend in part on society’s capacity to adapt to an uncertain future. A new article in the peer-reviewed journal Global Environmental Change, “Linking regional stakeholder scenarios and shared socioeconomic pathways: Quantified West African food and climate futures in a global context”, explores this uncertainty through four regional socioeconomic scenarios developed in a series of regional stakeholder driven workshops.

ccafs

Fig. Cartoon representation of West African Scenarios by André Daniel Tapsoba (Palazzo et al. 2016)

This study suggests that investments in agriculture, particularly in productivity enhancing technologies and practices, could not only improve access to food but also ease pressures on agricultural land expansion throughout the region.

This study is part of the Regional Scenarios Project, a large collaborative effort led by the CGIAR program on Climate Change, Agriculture, and Food Security (CCAFS) that has developed regional scenarios in 6 macro regions around the world and has involved significant collaboration among colleagues in the International Institute of Applied Systems Analysis (IIASA), the International Food Policy Research Institute (IFPRI), and the University of Oxford Environmental Change Institute (ECI).

IFPRI’s participation in this project is also supported by the CGIAR Research Program on Policies, Institutions, and Markets (PIM) and the Bill & Melinda Gates Foundation.

Read the press release at IIASA.

The journal article can be accessed here.

Related links:

IIASA Blog post by Amanda Palazzo describing the scenario process in West Africa.

GFSF Blog post by Daniel Mason-D’Croz summarizing outputs from the Regional Scenario Project.

CCAFS Regional Scenario Page.

Improved modeling of rice under environmental stresses

By Tao Li & Samarendu Mohanty, IRRI

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Photo Credit: IRRI

The worldwide usage of and increasing citations for ORYZA2000 has established it as a robust and reliable ecophysiological model for predicting the growth and yield of rice in an irrigated lowland ecosystem. Because of its focus on irrigated lowlands, its computation ability is limited in the representation of the effects of the highly dynamic environments of upland, rainfed, and aerobic ecosystems on rice growth and yield. Additional modules and routines to quantify daily variations in soil temperature, carbon, nitrogen, and environmental stresses were then developed and integrated into ORYZA2000 to capture their effects on primary production, assimilate allocation, root growth, and water and nitrogen uptake.

The newest version has been renamed “ORYZA version 3 (v3)”. Case studies have shown that the root mean square errors (RMSE) between simulated and measured values for total biomass and yields ranged from 11.2% to 16.6% across experiments in non-drought and drought and/or nitrogen-deficient environments. ORYZA (v3) showed a significant reduction of the RMSE by at least 20%, thereby improving the model’s capability to represent values measured under extreme conditions. It has also been significantly improved in representing the dynamics of soil water and crop leaf nitrogen contents. With an enhanced capability to simulate rice growth and development and predict yield in non-stressed, water-stressed and nitrogen-stressed environments, ORYZA (v3) is a reliable successor of ORYZA2000.

Download the paper here

Fish to 2050 in the ASEAN region

By Chin Yee Chan, WorldFish

ASEAN

The fisheries and aquaculture sectors in the countries of the Association of Southeast Asian Nations (ASEAN), provide income, employment opportunities, poverty alleviation, and improved food and nutrition security for the region. Extending the previous work from the Fish to 2030 report with the effort of updating parameters of the IMPACT fish model in consultation with regional experts and stakeholders, this WorldFish/IFPRI working paper highlights the business-as-usual projections of fish supply, net trade, prices, consumption, and nutrition intake from fish to 2050. Fish production in the ASEAN region will likely to grow faster than the regional population growth, benefitting the region both by improved food and nutrition security and economic opportunities.

Both aquaculture and capture fisheries production in the ASEAN will continue to grow. Capture fisheries continue to be the dominant fish supply by 2050, while aquaculture will supply more than half of fish for human consumption in coming decade. Regional net exports will continue to increase. Real prices of wild fish will grow slightly faster than farmed fish. Recognizing the complementary roles between capture fisheries and aquaculture sectors, policies need to focus not only on promoting aquaculture expansion, but also to strengthen regional fisheries governance and management to ensure sustainable growth of both sectors.

Download the paper here.

fish2050

Training workshop for the National Agricultural Investment Plans appraisal and design process for Sub-Saharan Africa: Introduction to Foresight Analysis

By Tim Sulser (IFPRI)

With several members of AGRODEP and governmental/university researchers from Nigeria, Uganda, and the Ivory Coast, in September 2016 I led a successful training workshop focused on using strategic foresight analyses to inform the review and development process of country-level National Agricultural Investment Plans (NAIPs).

capture

We first worked to develop a common understanding of the basic theory behind using scenarios and structural modeling to generate an evidence- and science-based perspective aimed at informing the agricultural/food policy process. Afterwards, we “dove into the deep end” of foresight analysis with a hands-on practical exercise to jointly develop our own scenarios for possible future trajectories of the agricultural economies of Sub-Saharan Africa. These scenarios focused on (1) the impact of violent conflict on the agricultural sector and (2) the potential impact of increased investment in agricultural research and development if more of Sub-Saharan Africa were to achieve the goals set out in the CAADP agreement.

This workshop was just a first step along the path to build national and regional level capacity for using strategic foresight studies to inform agricultural and food policy processes for the participants. We look forward to future interactions!

This workshop was supported by IFPRI’s West and Central Africa Office (WCAO) in partnership with the African Union Commission (AUC) and the New Partnership for Africa's Development (NEPAD) Planning and Coordinating Agency. The foresight work upon which this workshop was based was supported by funding from the Bill & Melinda Gates Foundation and the CGIAR Research Programs on Policies, Institutions, and Markets (PIM) and Climate Change, Agriculture, and Food Security (CCAFS) to GFSF.

 

Global Futures and Strategic Foresight participating in the Global Action Plan for Agricultural Diversity (GAPAD)

Global Futures and Strategic Foresight was invited to share their foresight perspective at the Global Action Plan on Agricultural Diversification (GAPAD) SDG2 Roundtable Forum in Nairobi, Kenya at the end of October 2016.  GAPAD (gapad.org) is an initiative by the Association of International Research and Development Centers for Agriculture (www.airca.org) to promote agricultural diversification as a tool to address many of the challenges we face today (and will be facing in the future) in food and agricultural systems at the local to global scale.

Global Futures and Strategic Foresight participating in the Global Action Plan for Agricultural Diversity (GAPAD)

Global Futures and Strategic Foresight participating in the Global Action Plan for Agricultural Diversity (GAPAD)

This Roundtable Forum focused specifically on how agricultural diversification could contribute to the UN Sustainable Development Goal 2 to end hunger, achieve food and nutrition security, and promote sustainable agriculture (SDG2; sustainabledevelopment.un.org/sdg2) and involved a broad representation of different experts, scientists, and stakeholders from the agricultural development community.  The successful workshop (Workshop Report from CABI.org) provided crucial material (Workshop Archive from AIRCA) for the GAPAD leaders to bring with them as they participated in the UNFCCC COP22 in Morocco in November (UNFCCC-COP22) and COP13 of UN Convention on Biological Diversity in Mexico in December (UNCBD-COP13).  This Forum also caught the attention of regional media outlets (KTN News Kenya; www.standardmedia.co.ke; www.pamacc.org).

 

CIMMYT gathers partners to discuss biotic stress and crop model integration

By Kindie Tesfaye (CIMMYT) and Evgeniya Anisimova (PIM)

When crops are damaged by other living organisms such as bacteria, viruses, fungi, insects and other pests, weeds or even cultivated plants competing for space and nutrients, we talk of the biotic stress. Biotic stresses are a major constraint to agricultural productivity in low and middle income countries. They affect poor producers and consumers the most and undermine food security in general.

Examples of some biggest current concerns related to biotic stress are the wheat diseases fusarium head blight (FHB), wheat blast (caused by fungi), and the maize lethal necrosis (MLN) caused by viruses (also read here).

Scientists in the International Maize and Wheat Improvement Center (CIMMYT) know all about biotic stresses to crops. They also know that combatting these stresses is a task beyond the scope of any one organization or discipline. This was evident during the workshop in Addis Ababa, Ethiopia, on June 20-22 that brought together breeders, physiologists, entomologists, pathologists, modelers, and socio-economists from CIMMYT and partner organizations including Auburn University, University of Passo Fundo, and the International Food Policy Research Institute (IFPRI). The workshop titled "How can we take biotic stress into consideration with crop growth modeling in maize and wheat?" was organized by CIMMYT as part of the Global Futures & Strategic Foresight (GFSF) project, a CGIAR initiative led by IFPRI under the CGIAR Research Program on Policies, Institutions, and Markets (PIM).

Participants at the CIMMYT workshop.

Participants at the CIMMYT workshop.

Crop growth (or simulation) models are computer programs processing data on weather, soil, and crop management to predict crop yield, maturity date, efficiency of fertilizers and other elements of crop production. Accuracy of the predictions is based on the existing knowledge of the physics, physiology and ecology of crop responses to the environment[1]. So, the more we know about this responsiveness to the environment, including biotic stress, the more accurate these predictions can be. Existing crop growth models do not adequately simulate biotic stress to calculate possible yield reduction. Colleagues who came to Addis Ababa were eager to expand this knowledge and increase the accuracy of the predictions through integrating biotic stress and crop models.

Dr. Gideon Kruseman, an ex-ante and foresight specialist at CIMMYT, and Dr. Bekele Abeyo, a wheat breeder and CIMMYT’s Ethiopia country representative, opened the workshop by reviewing the use of crop models in maize and wheat production systems. Dr. Kruseman explained the importance of integrating the models for biotic stress with crop models for a holistic assessment of the potential impact of new technologies in several environments. Dr. Abeyo emphasized the need for the partners to work together across disciplines.

Workshop discussions were dedicated, among other topics, to CIMMYT’s experiences in applications of crop models (for example, see: Chung et al., 2014; Gbegbelegbe, Chung, Shiferaw, Msangi, & Tesfay, 2014; Tesfaye et al., 2015, 2016), opportunities and challenges of incorporating biotic stress directly into crop growth models, linking crop growth models with biotic stress models through soft coupling[2], phenotyping for biotic stresses[3], and the probabilistic approaches to linking biotic stress into crop growth models. Apart from that, colleagues focused on the scale of biotic stress as a challenge, data gaps, and future action points, emphasizing the importance of collaboration with other initiatives such as AgMIP.

Figure: Example of linkages among biophysical and economic models.

Figure: Example of linkages among biophysical and economic models.

As a way forward, participants agreed that soft coupling biotic stress models with crop models is a feasible approach in the short- and mid-term perspective whereas full integration can remain a long-term strategy. The soft coupling efforts presented by colleagues from Auburn University, USA, and University of Passo Fundo, Brazil, should serve as a springboard to link the major maize and wheat biotic stresses with current crop models such as those comprised in the Decision Support System for Agrotechnology Transfer (DSSAT). Moreover, an approach that considers probability of disease incidence, probability of disease severity, and probability of damage can also offer scope for linking crop growth models and biotic stress either separately or in combination with soft coupled models. The probabilistic approach can be especially useful when linking crop growth models with economic models, for example, to see how the chance of a disease outbreak shapes the choices made by farmers.

As a result of the workshop, partners agreed to start a small pilot project on integrating biotic stress with crop models to prove of concept. Concept notes shall be submitted to the competitive grant by the CGIAR Research Program on Maize. At the next stage partners shall come together to develop a bigger project and approach donors.

“I really enjoyed the workshop because it brought together a very diverse range of scientists that I would never normally get to interact with. Modeling abiotic stresses allowed us to quantify the potential impacts of improved varieties at the regional and national level. I’m excited to be able to do this for biotic stresses” -- Jill Cairns, Maize physiologist at CIMMYT.

 

References

Chung, U., Gbegbelegbe, S., Shiferaw, B., Robertson, R., Yun, J. I., Tesfaye, K., … Sonder, K. (2014). Modeling the effect of a heat wave on maize production in the USA and its implications on food security in the developing world. Weather and Climate Extremes, 5-6, 67–77.

Gbegbelegbe, S., Chung, U., Shiferaw, B., Msangi, S., & Tesfay, K. (2014). Quantifying theimpactofweatherextremesonglobalfoodsecurity: A spatialbio-economic approach. WeatherandClimateExtremes, 4, 97–108. Retrieved from http://crossmark.crossref.org/dialog/?doi=10.1016/j.wace.2014.05.005&domain=pdf

Tesfaye, K., Gbegbelegbe, S., Cairns, J. E., Shiferaw, B., Prasanna, B. M., Sonder, K., … Robertson, R. (2015). Maize systems under climate change in sub-Saharan Africa. International Journal of Climate Change Strategies and Management, 7(3), 247 – 271. http://doi.org/10.1108/IJCCSM-01-2014-0005

Tesfaye, K., Kai Sonder, Jill Cairns, Cosmos Magorokosho, Amsal Tarekegne, Girma T. Kassie, Fite Getaneh, Tahirou Abdoulaye, Tsedeke Abate, and Olaf Erenstein (2016). Targeting Drought-Tolerant Maize Varieties in Southern Africa: A Geospatial Crop Modeling Approach Using Big Data. International Food and Agribusiness Management Review, 9 (A): 75-92.


[1] What Are Crop Simulation Models? United States Department of Agriculture. Agricultural Research Service. http://www.ars.usda.gov/main/docs.htm?docid=2890 accessed on 7/27/16

[2] Soft coupling refers to linking two separate models through an interface that allows information to be exchanged amongst them.

[3] Phenotyping for biotic stress refers to trials conducted specifically to obtain information on how varieties react to pests and diseases, by subjecting the trials to substantial levels of the specified stressors.