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  • Cynthia Rosenzweig On the Road for AgMIP

    Cynthia Rosenzweig On the Road for AgMIP

    Photo: Cynthia Rosenzweig (second from right) participates in agricultural panel for Michael Pollan and Raj Patel’s class on Edible Education

    By Molly B Schneider

    Over the last year, AgMIP Principal Investigator, Cynthia Rosenzweig has been traversing the country to spread the word about AgMIP’s research projects. Last month, Rosenzweig traveled to Harvard University, Stanford University and the University of California, Berkeley to meet with students and fellow agricultural and climate change scientists.

    At Harvard and Stanford, Rosenzweig held seminars with key departments in order to promote the work of AgMIP. Primarily, she presented several of AgMIP’s scientific endeavors including the recent work on a global gridded crop model initiative, wheat pilot study and regional integrated assessments of Sub-Saharan Africa and South East Asia. Secondly, she shared the goals and activities of AgMIP in order to encourage collaborations in the key areas of the effects of CO2 and climate change on food quality, research on agricultural stakeholders, and the exploration of synergies between statistical and dynamic modeling approaches.

    At UC Berkeley, Rosenzweig was a guest at food journalists Michael Pollan and Raj Patel’s class on Edible Education. She spoke on the topic of how climate change is affecting agriculture and conversely, how agriculture is affecting climate change as well as possible mitigation and adaptation solutions. Rosenzweig was on the panel with Alice Waters, owner of Chez Panisse and founder of the Edible Schoolyard Program, Anna Lappe, author of Diet for a Hot Planet and Courtney White, sustainable livestock activist.

    At all of the visits, Rosenzweig was able to engage with both existing and new AgMIP collaborators. Interacting with students from a variety of different academic disciplines both stimulated interest and reinforced the need to have high-quality models and methods for agricultural intercomparison.

    Rosenzweig said, “It was really great to get out on the road with AgMIP and share with colleagues around the country the science of AgMIP and its development as a new global program.”

  • Open Access to Agricultural Economics AgMIP Special Issue

    We are happy to announce that the Special AgMIP Issue of Agricultural Economics is now available as open access, free of charge. Click here to access the complete Special Issue on the Agricultural Economics website.

  • AgMIP-USDA Workshop Explores Agricultural Data Harmonization

    By Carolyn Cox

    AgMIP Approach to Data and Model Harmonization

    AgMIP and USDA held a workshop on January 10, 2014 on “Harmonizing Agricultural Data and Models.” The workshop was organized by Jim Jones, Jerry Hatfield, Cynthia Rosenzweig, and Carolyn Cox (Coordinator of the Florida Climate Institute, which hosted the event). The purpose was to explore concepts for harmonizing agricultural databases and models being developed and used by various USDA research projects and AgMIP. Harmonization would lead to web-based data access for evaluating and improving agricultural models and using them for analyses of climate change impacts, adaptation strategies, and potential food security issues. The USDA-ARS and NIFA-funded projects are increasingly being mandated to ensure their data are open for broad use, with the recognition that data are highly valuable for use beyond the immediate goals of specific projects and represent a substantial public investment. However, even though similar data may be collected across projects, the fact that different databases and formats are used by different projects and labs makes the discovery and access to valuable datasets impractical.

    There is increasing use of crop, livestock, and forestry models in research on climate change, food security, and other major issues. Crop models, for example, use similar input data on soils, weather, and management; however, those crop models have been developed by different research groups and use different data formats and units. AgMIP has already made major progress toward harmonizing data inputs and outputs across different crop models because of its emphasis on using multiple models. This work was done by the AgMIP IT Team, led by Cheryl Porter (University of Florida) and Sander Janssen (Wageningen University), with direct contributions by crop modeling groups worldwide (see www.agmip.org/it-team). This AgMIP crop model harmonization approach, which does not require code to be changed, has been implemented for six different crop model families and work is continuing for adding additional models. According to the AgMIP IT Team, a similar approach could be developed to allow web users to access databases on crops, livestock, or other domains without requiring the databases to use the same data structures or the same database software.

    Representatives from different USDA projects and labs presented summaries of the data that they are collecting, the approaches that they are using to store data, and their thoughts about making their data openly available. In addition, Simon Liu of the USDA National Agricultural Library (NAL) presented concepts that he has been working on to help harmonize agricultural data (click here to see a list of representatives). Breakout sessions allowed the attendees to address key questions concerning approaches for harmonization, the benefits, and ways forward.

    The following conclusions were presented in the closing plenary session:

    • The various NIFA-funded and ARS projects and AgMIP can gain mutual benefits through cooperation on data and agricultural model activities.
    • The approach developed by AgMIP to harmonize among crop models could be adapted to harmonize data from different USDA and NIFA databases with inputs from NIFA/USDA ARS colleagues and the NAL.
    • Collaboration can also lead to similar development for other systems, such as livestock, such that an approach will evolve that facilitates model intercomparisons and improvement and access to data across platforms and database systems.
    • There are low hanging fruit that can be harvested via collaboration among NIFA projects, ARS projects, the NAL, and AgMIP to demonstrate and evaluate the harmonization of data.
    • Multiple models within AgMIP can be used to assist in analyses of data collected in the NIFA-funded projects.
    • A follow-up workshop should be organized to coordinate the efforts of different USDA projects and labs toward database harmonization.

    Common goals and potential collaborations between AgMIP and the ARS/NIFA projects on evaluation, improvement, and use of agricultural models (crop and livestock) were also identified. The collaboration will ultimately help to answer the overarching policy question: What is the vulnerability of the U.S. food and fiber system to climate extremes and change?

     

  • AgMIP Global Economic Research Published in Agricultural Economics

    AgMIP Global Economic Research Published in Agricultural Economics

    By: Nicholas Hudson 

    As global climate continues to change, the question of the potential economic consequences of this change on the world’s food supply is one that scientists have been endeavoring to answer. Previous research has produced wide variations in results concerning the future of prices, production, and trade. The Agricultural Model and Intercomparison and Improvement Project (AgMIP) in association with the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) is leading a global economic model intercomparison, which harmonized the input datasets for 10 global agro-economic models to better evaluate the model results. Each of the economic models ran simulations with standardized initial conditions for multiple scenarios, as outlined in von Lampe, et al. (2014). Through harmonizing the model inputs, this effort hoped to shed light on the different behaviors and more subtle aspects of heterogeneity between the 10 global economic models with the goal of leading to meaningful analysis and inter comparison.

    This article briefly reviews seven studies recently published in a special issue of Agricultural Economics, and introduced in a paper by Jerry Shively and Gerald Nelson (Weblink). The first article, “Why do global long-term scenarios for agriculture differ? An overview of the AgMIP Global Economic Model Intercomparison” (Weblink), reviews the methodology and analyzes the differences between model results. The second article, “Agriculture and climate change in global scenarios: why don’t the models agree?” (Weblink) reviews the effects of climate change shocks simulated by the global agro-economic model intercomparison. The next three articles, “Impacts of increased bioenergy demand on global food markets: an AgMIP economic model inter comparison” (Press Release Weblink), “Land-use change trajectories up to 2050: insights from a global agro-economic model comparison” (Press Release Weblink), and “The future of food demand: understanding differences in global economic models” (Press Release Weblink), specifically analyze how the models differently treat bioenergy, land-use and food demand respectively. The next article, “Projecting future crop productivity for global economic modeling” (Press Release Weblink), looks closely at the uncertainties that arise from scenarios imposed on the global economic models. The last article, “Comparing supply-side specifications in models of global agriculture and the food system” (Weblink), reviews the structural differences in the ways in which models simulate the agricultural sector, specifically the differences between partial equilibrium (PE) and computable general equilibrium (CGE) models.

    All of the articles prove the efficacy of conducting a study harmonizing the inputs and demonstrate how the difference between the models is greatly reduced by this process. However, all of the articles also highlight that this is just the first step required by rigorous model intercomparison and improvement efforts and that future coordinated studies will be necessary to reduce uncertainty and improve the forecasting abilities of the models.

    Papers at a glance

    Martin von Lampe, et al. Why do global long-term scenarios for agriculture differ? An overview of the AgMIP Global Economic Model Intercomparison 

     Weblink

    This AgMIP global economic modeling group study relies on the method of harmonizing model inputs between the 10 economic models to more accurately compare the simulated crop yields and the global economic responses to climate change. The first method of comparison involves grouping the results into five categories of agreement and disagreement. Additionally, the study employs an econometric meta-analysis to study the price changes both over the duration of the reference scenario as well as between the reference scenario and the alternative scenarios. The study also tests the hypothesis that computable general equilibrium models (CGE), as compared to partial equilibrium models (PE), have greater flexibility when responding to exogenous shocks and thus forecast smaller price changes.

    While previous studies have demonstrated that global economic models predict price changes in similar directions, the magnitude of the changes widely varied between the models. This study found that harmonizing the model inputs greatly reduced the range of price changes induced by the different scenarios while also leading to greater uniformity in other model outputs. Furthermore, this comparison revealed other commonalities between the model results including similar hotspots of future agricultural growth, greater impact of productivity progress over expanded agricultural land-use, and an increasing role of international trade. Accordingly, this study recommends the formation of national and international policies, development of private investment strategies, the maintenance and expansion of domestic infrastructure, and the liberalization of international agricultural trade to prepare for the effects of climate change.

    Despite the similarities between the model outputs, this comparative analysis identified discrepancies between the model outputs, which led to uncertainty, and merit future analysis. Many of these differences arise from contrasting assumptions about the future behavior of the global population. Specifically, differences emerge from the estimated, long-term future demand as impacted by increases in income and the associated rise in food consumption as well as alterations in consumption patterns. Moreover, assumptions about rates of agricultural land-use change and technical advancement expose additional areas of uncertainty that require further research. Regardless, this study demonstrates the benefits of harmonizing model inputs to reduce model disagreement, identifies important factors that will drive agricultural markets in the future, and outlines several structural modeling components and assumptions that could benefit from further research.

    Gerald C. Nelson et al. Agriculture and climate change in global scenarios: why don’t the models agree? 

    Weblink

    This study conducted by AgMIP’s global economic modeling group compares 10 of the leading global economic models with the objective of identifying the factors that lead to differing model outputs with respect to a number of climate change shocks. To better understand these differences, each of the economic models ran multiple scenarios as well as one baseline, or reference scenario, with a common set of climate, crop, and socioeconomic input variables. The scenarios use climate data from two general circulation models, IPSL-CM5A-LR and HadGEM2-ES, crop data from two crop models, LPJmL and DSSAT, and socioeconomic data provided by the Shared Socioeconomic Pathway 2 (SSP2) created for the Intergovernmental Panel on Climate Change (IPCC) 5th Assessment Report (AR5). The study then divides the influence of climate change on agricultural yields into the three components: consumption, area and yield. The effects of yield shock are compared to the baseline scenario to measure the climate change response and then are used to evaluate the impact of the different scenarios on crop prices.

    This comparison highlights a number of differences between the models while also identifying areas of future analysis. Most notably, the models tend to have similar demand responses to climate change but the study did not closely scrutinize the differences in the supply responses and recommends that this area be analyzed in future studies. Similarly, the effects of climate change on crop prices are closely linked to the responsiveness of the change in the quantity demanded as compared to the change in price, or the price elasticity, a variable exogenously determined by each economic modeling group.

    This comparative study confirms other research suggesting that the models’ price elasticity may be calibrated for near-term forecasting rather than the longer-term responsiveness that would be required for predicting price effects over the next 40 years and demonstrates how model outputs are similar when harmonizing input variables. For the studied climate change shocks, globally yields and consumption tended to fall, while agricultural land- use and prices tended to rise. However, the magnitude of such changes varied widely between the different models indicating that the model structure and implicit parameter choice have a large impact on the model outputs. This study recommends further econometric and validation studies to reduce the model output differences and ultimately reduce the uncertainty that arises from such modeling efforts.

    Hermann Lotze-Campen, et al. Impacts of increased bioenergy demand on global food markets: an AgMIP economic model inter comparison 

    Press Release   Weblink

    To meet the predicted global rise in food and energy consumption by 2050 as well as adhere to the ambitious greenhouse gas (GHG) emission targets needed to constrain global warming to 2°C above pre-industrial levels, the Integrated Assessment and other energy modeling efforts have demonstrated that energy created from agricultural biomass will be a crucial component of the future energy mix. Previous literature has shown that current biofuel generation has directly pressured global agricultural markets while also providing low GHG savings at a relatively high abatement cost. To research this increasingly important energy source, five global economic models were used to study the future effects of a bioenergy production expansion on agricultural land-use and global food prices. This AgMIP global economic modeling group study conducted model intercomparison as well as compared the impacts of an increasing, long-term bioenergy demand to the impacts of climate change on agricultural production.

    To more accurately compare the model outputs, inputs were harmonized by the same methodology previously outlined and multiple scenarios were run by the models. The demand for biofuels was largely determined by current public policy commitments, although this factor was not fully standardized due to structural differences inherent to the models. This difference in biofuel demand implementation, along with differences in productivity changes, varying degrees of production substitution, and levels of international trade, drove the models to respond differently to changes imposed by the scenarios. As a result, the models simulated significantly different responses in the allocation of bioenergy production, the area of land-use change, and the levels of demand and international trade. The models generally agree that the impacts of biofuel production on agricultural production and land-use change are relatively modest insomuch as the land supply is made available for increased biofuel production. This study, however, did not consider the implications of water scarcity and nutrient depletion, constrained agricultural land expansion, or welfare losses imposed by emission restrictions. If these factors would have been included in this assessment, particularly in regards to constrained agricultural land expansion, the models likely would have predicted greater effects of climate change on global food prices. Further research will be required to include these factors and more fully harmonize the models to allow for improved model intercomparison.

    Christoph Schmitz, et al. Land-use change trajectories up to 2050: insights from a global agro-economic model comparison 

    Press Release   Weblink

    The past 50 years witnessed a relatively small expansion of agricultural land (15%) in comparison to the increase in agricultural production over that time frame (200%). However, to meet the increasing global food demand into the future, it is unclear whether productivity will continue to increase rapidly or if there will be an expansion of agricultural land-use. To address this question, this study compared the land-use changes predicted for four socioeconomic and climate change scenarios of 10 global economic models. The incorporation of land-use changes in global economic models is a relatively new component and as a result there are large uncertainties between the models and the predicted changes in land-use. Yet, much of these differences between the models arise from the uncertainty of economic and demographic development as well as structural features within the models. To address these uncertainties, the AgMIP global economic modeling group has harmonized key input variables and assumptions to allow for a more uniform comparison. Importantly, many of the models harmonized their technological change (TC) rate as this factor is an important driver of changes in land-use.

    The harmonizing efforts substantially reduced uncertainties between the model results and a couple of notable similarities were observed between the models. All of the models simulated an increase in land-use while also suggesting that Africa will have the greatest expansion of agricultural land in the future. Many of the similarities that were observed between subsets of the 10 models could be explained by similarities in model structure, which also explained the differences between the subsets. The differences between the models’ predicted land-use changes appear to be influenced largely be differences in the cost of land expansion, the predicted regional productivity responses and the assumptions about future land availability. This first comprehensive global economic model intercomparison study of land-use changes highlighted structural differences between the models and has exposed the need for validation either by hind casting or back casting. Further study will also be needed to more accurately model TC as this is a decisive variable driving land-use change.

    Hugo Valin, et al. The future of food demand: understanding differences in global economic models 

    Press Release   Weblink

    While food production has largely kept pace with the increasing global demand driven by population growth, there are concerns that climate change, nutrient depletion, and water scarcity will threaten the ability for the agricultural sector to satiate the food demand in the long-term. This study compares the demand modeling approaches of 10 global economic models in association with the AgMIP global economic modeling group’s strategy of model intercomparison. By using eight scenarios of socioeconomic development, climate change, and bioenergy expansion to harmonize the model inputs, this study is able to more accurately compare the food demand projections of the global economic models in 2050.

    Ultimately, this comparison demonstrates that food demand is more sensitive to socioeconomic drivers, mainly population growth but to some extent income growth as well, than the effects of climate change or bioenergy expansion. All of the models project higher increases in demand than was projected by the Food and Agricultural Organization (FAO) in the baseline scenario. These differences are impacted by assumptions about economic growth under the scenario’s rate of population growth. However, differences in factors of economic growth do not entirely account for this discrepancy. The results were decomposed into the components driven by economic growth, the income effect, and by the role of prices on demand, the price effect. The models have different price trends and have varying levels of sensitivity to price changes, which can either increase or decrease the effect of economic growth on demand. The sensitivity to climate change and bioenergy generation were also evaluated but found to be far less influential than the socioeconomic drivers.

    Modeling food demand is difficult due to the high degree of uncertainty surrounding the main socioeconomic drivers of population and economic growth. As a result, the model results of food demand vary widely across the models. The models do agree, however, that the increase in demand will be greater than that forecasted by the FAO suggesting that there will be a greater required increase in global agricultural production to meet demand than projected by the FAO. This comparative analysis concludes that there will need to be further research conducted to determine how best to simulate income elasticity and the magnitude of the price effect impact on model projections, both of which will be integral to accurately modeling food demand.

    Christoph Müller and Richard D. Robertson. Projecting future crop productivity for global economic modeling. 

    Press Release   Weblink

    This article analyzed the uncertainties of the scenarios imposed on the 10 global economic models as part of AgMIP global economic modeling group’s strategy of model intercomparison and specifically studied the uncertainties that arise from the spatial patterns of crop productivity. Using the scenarios and methodology outlined in Nelson, et al., the global economic models agree that there will be a loss in agricultural production in most regions by 2050. This analysis demonstrates the limitations of the scenarios as well as the strengths, discussing and validating the methodology used by the intercomparison effort led by AgMIP.

    This study concludes that the uncertainties that arise from the spatial patterns of crop productivity pervade, in part, from the uncertainties that exist in the climate projections as well as from differences in the impact model that is used by a particular modeling group. The shortfalls of the scenarios are thoroughly discussed, including but not limited to the modeling of extreme weather events, the lack of pathogens/weeds that would affect crop growth and development, relatively static management systems, and the small number of crops considered in the simulations. Ultimately, the study concludes that the uncertainties from the climate projections and impact models need to be more fully appreciated by economic assessments of climate change into the future.

    Sherman Robinson, et al. Comparing supply-side specifications in models of global agriculture and the food system. 

    Weblink

    This study compares the two most common forms of global economic models used in the AgMIP global economic modeling group’s strategy of model intercomparison, the partial equilibrium (PE) model and the computable general equilibrium (CGE) model. PE models have been used in the agricultural sector for many years but typically do not cover all of the production markets. However, PE models have a finer resolution and thus are able to more easily simulate biophysical factors including degradation of soil quality, water availability and climate change, In comparison, CGE models, which were developed to analyze macroeconomic and trade policy issues, are typically larger scale and have only recently been used to simulate the effects of climate change.

    This study focuses on the differences between CGE and PE models regarding the specification of agricultural technology and supply behavior for long-term global food systems. The scenarios allowed the models to be more fully harmonized thus reducing the differences, suggesting that both structural model forms produce consistent and empirically significant results. While CGE and PE models handle these aspects of supply differently, this research concluded that these discrepancies do not translate to major differences in the model outputs. The article outlines methods by which CGE and PE models could be run to more effectively compare the underlying supply and demand functions that drive these models, although the study concludes that this effort led by AgMIP to harmonize the global economic models was a definitive step in the right direction.

  • Hats off to the 4th Annual AgMIP Global Workshop!

    Hats off to the 4th Annual AgMIP Global Workshop!

    Agenda, Participant List, Poster Abstracts, Workshop Report 

    Presentations, Work Group Reports, Poster PDFs

    As the fine autumn weather continued in late October in New York City, the Agricultural Model Intercomparison and Improvement Project (AgMIP) convened its annual Global Workshop – the fourth such event since the US Department of Agriculture founded AgMIP in 2010. Members of the AgMIP community convened at Columbia University’s Faculty House where Jeffrey Sachs, Director of the Earth Institute, AgMIP Steering Group Co-Chairs Mannava Sivakumar and Martin Parry, and AgMIP Principal Investigators Cynthia Rosenzweig, James Jones, Jerry Hatfield, and John Antle kicked off the 3-day workshop.

    The workshop brought together over 240 participants from 130 institutions representing the diversity of the AgMIP community. In addition to AgMIP core disciplines of climate, crop, and economic modeling and information technology, initiatives exploring water, soil and crop rotation, aggregation and scaling, pests and diseases, livestock and grasslands, uncertainty, ozone, and climate variability and extremes were also represented. The workshop focused on critical improvements for next-generation models, data, and decision support systems for agricultural assessments of climate change impact and adaptation, and for sustainable intensification of agriculture. Participants also advanced strategies for coordinated regional and global assessments of food security.

    Workshop participants in front of Low Library, Columbia University.

    “You have convened at a crucial time.” Jeffrey Sachs said to the workshop participants, “Governments are going to need agricultural strategies and technological roadmaps. What new crop types, varieties, farm systems need to be put in place to resist climate change, create resilience, increase water efficiency, reduce heat stress, and so forth? I don’t think these roadmaps exist right now.”

    A Speed Science session followed the introductions, in which 22 scientists shared key findings, recent accomplishments, and plans for the future. The presentations were divided into seven broad categories: Crop Model Intercomparisons and Improvement, Global Assessments, Regional Integrated Assessments, Cross-Cutting Themes, Key Interactions, New Approaches for Climate-Crop Assessment, and Data and Information Technology.

    The first day was capped by an evening poster session and reception held at Columbia University’s Low Library with support by The Earth Institute. G. Michael Purdy, Executive Vice-President for Research at Columbia, encouraged participants to mix and view the 65 posters displaying diverse topics such as Integrated Regional Assessments in Sub-Saharan Africa, South Asia, East Asia and Latin America, Economics, Climate, Pests and Diseases, Extreme Events, Water, Evapotranspiration, Ozone, Soil and Crop Rotation, Adaptation, Data and IT, and crop specific topics such as wheat, rice, maize, soybean and potato.

    Poster session at Low Library, Columbia University.

    “This is a great opportunity for exchange and learning in true interdisciplinary science to inform a very important problem –food security for a diverse and growing global population,” said G. Michael Purdy. “Columbia University is proud to host the coordinating office of AgMIP, and is very grateful to UKaid for its major support of this endeavor, to which USDA, CCAFS, USAID, and numerous collaborating partners contribute to enable the AgMIP community to deliver robust and policy-relevant research outputs.” PDFs of the posters and abstracts are available here for download.

    In addition to breakouts focusing on model integration and scales, the second day of the workshop included a speed session highlighting complimentary global and regional programs CCAFS, MACSUR, USDA CAPs, Yield Gap Atlas, CIMSANS, FAO, and MODEXTREME.

    Discussion during breakout session.

    At the completion of the third day breakout groups reconvened in plenary to present report backs from their sessions. PDFs of the reports as well as presentations from the workshop are available here.

    Many of the groups made plans to meet again and collaborate on research and publications. Some groups like Pests and Diseases will be new to AgMIP while others will continue to build on work initiated previously. All will try to incorporate their findings into integrated assessments of food security on both the regional and global scale. It is these assessments, which combine information from crop, climate and economic models that will feed the next generation of decision support tools for policymakers in the coming decades.

    Martin Parry, Co-Chair of the AgMIP Steering Committee remarked of the workshop, “What’s obvious about this project is it’s tapped into a huge latent demand…and that’s why it has picked up speed so quickly.” He continued, “90-95% of the effort this week has been on improving the science. But you have also heard a call for messages, from donors and policymakers, and it can be complimentary. As one drives forward in model intercomparision and improvement, instead of a parallel path, have questions embedded in single pathway. How would the outcome from your model be altered with mitigation and adaptation?”

    This is one of the questions AgMIP scientists will continue to pursue as the energy from this intensive workshop propels the teams forward into the coming year.

    Left: Workshop participants raise their hats in the fine fall weather in New York. Right: Jeffrey Sachs addresses the opening plenary session of the 4th Annual AgMIP Global Workshop.

  • Agricultural Stakeholders Contribute to AgMIP Research

    By: Shari Lifson

    Yubak Dhoj G.C., Director General of the Department of Environment in Nepal addresses researchers in Kathmandu.

    Throughout the world, communities dependent on agricultural systems are vulnerable to food insecurity. Each agricultural system is associated with a unique set of environmental and economic conditions and changes in those conditions could affect the future stability of crops and livestock. AgMIP regional research teams in Sub-Saharan Africa and South Asia are engaging policymakers, agricultural ministers, extension agents, and farmers – those who best understand the regional conditions – in order to better understand together how changing climate and other factors may affect agricultural systems and food security. AgMIP researchers in Latin America and East Asia are in the process of establishing similar studies in their regions.

    Collaboration with stakeholders enables the AgMIP research teams to develop Representative Agricultural Pathways (RAPs) for their study regions. The RAPs are economic and social development narratives that include agricultural technology trends, prices and costs of production trends, and agriculture and conservation policy. They are best developed with multidisciplinary teams of researchers and stakeholders with diverse expert knowledge, interests and experience with agricultural systems. Once developed, RAPs can be incorporated in studies that integrate climate, crop and economic models to assess plausible outcomes.

    Stephen King’uyu, Agriculture Deputy Director (Adaptation & Mitigation), Climate Change Secretariat from Kenya, is a stakeholder who has been advising the AgMIP East Africa Regional Research Team. His responsibilities include adoption of protocols related to climate change adaptation and mitigation and formulation of the national policy. He recently attended an AgMIP workshop in Pretoria, South Africa where he shared his experience and knowledge with AgMIP researchers working in regions of Sub-Saharan Africa.

    Farmland in Kenya.

    “Agriculture faces multiple challenges in Kenya related to climate change,” explained King’uyu, “issues related to increased variability of rainfall, increased temperatures which will increase evapotranspiration rates reducing soil moisture required for crop development, and reduced agricultural productivity. Socio-economic issues include increased or unstable fertilizer prices and other farm inputs.”

    King’uyu continued, “I think there are lots and lots of good things that are likely to come out of this partnership with AgMIP. We know what issues are impacting on the farmers and their operations, and ideally that creates a baseline for further work.”

    Dumisani Mbikwa Nyoni is Provincial Agricultural Extension officer in the Department of Agricultural Technical and Extension Services in Zimbabwe where he works with farmers in the promotion of conservation agriculture to address climate change challenges. At the Pretoria workshop he commented on some of the difficulties agriculture in his country is facing, “In the case of Zimbabwe, close to 80% of the population sustains it livelihood from rain-fed agriculture, and we have been witnessing an increase in the number of mid-season dry spells, a shortening of the season length, and increases in the rate of crop failure and an increase in the number of droughts as well, which results in complete crop failure and livestock losses.”

    Some of the adaptation methods that Nyoni feels would assist farmers are new seed varieties for the shorter season length and drought resilience, and options for farmers to intensify production in smaller areas to produce feed for livestock during dry periods.

    Stakeholders at the Sub-Saharan Mid-Term Workshop Pretoria, South Africa.

    At a recent AgMIP Workshop in Kathmandu, Nepal, Yubak Dhoj G.C., Director General of the Department of Environment in Nepal, met with AgMIP researchers working on agricultural systems in the Indo-Gangetic Basin. Dhoj G.C.’s work at the Department of Environment includes implementation of environmental friendly agriculture, pesticides, affluent and waste disposals.

    “Nepal has been facing many challenges with climate change and the recent phenomenon in the environment,” Dhoj G.C. noted. “Nepal is one of the poorest countries in the world and we have major hits with these changes and we don’t have that much in [the way of] coping strategies and adaptation measures. Our country will benefit from outcomes developed in the region.”

    Through the RAPs process, these and other participating stakeholders contribute essential inputs to policy-informed research investigations using a method AgMIP calls “Integrated Regional Assessment.” The exploration of a range of RAPs provides policy makers more robust considerations of possible shifts in local or regional food security in the years ahead.

    Stephen King’uyu commented on how he would use AgMIP research, “Ideally research will provide evidence for policy formulation; every good policy maker would want to think about evidence-based policy.”

  • Regional Research Teams Collaborate and Plan in Pretoria and Kathmandu

    How will climate change impact food security in developing areas of South Asia and Sub-Saharan Africa? AgMIP’s Regional Research Teams on both continents are continuing their efforts to quantitatively answer this question by developing integrated regional assessments that link climate, crop, and economic models. Two workshops in July in Pretoria, South Africa and Kathmandu, Nepal brought the teams together for working sessions and planning with AgMIP leaders and regional stakeholders.

    During the weeklong workshops the Regional Research Teams and Stakeholders met among themselves and with AgMIP Principal Investigators and crop, climate, economic and IT team leaders. Meetings at the workshops also continued the development of research guidelines and protocols to complete the assessments. (more…)

  • John Antle new AgMIP Co-Principal Investigator

    The Agricultural Model Intercomparison and Improvement Project (AgMIP) is pleased to announce the addition of John Antle as a Co-Principal Investigator along with current Co-PIs Cynthia Rosenzweig, Jim Jones, and Jerry Hatfield. Dr. Antle, professor at Oregon State University, has been leader of the AgMIP Regional Economics Team and an integral contributor to AgMIP since its inception in 2010. In his new role John Antle will be involved in guidance of the project as well as continuing to oversee research in regional economics. His dedication and expertise have been invaluable in AgMIPs continuing progress. (more…)

  • AgMIP Training Workshops Progress Regional Integrated Assessments

    In order to assess future impacts of climate change on regional food security, AgMIP teams of researchers are working in Sub-Saharan Africa and South Asia utilizing protocoled AgMIP methods to execute regional integrated assessments of crop productivity and related outcomes. The approach includes use of multiple crop models and linking them with climate and economic models to create the integrated assessments. To assist researchers in utilizing this approach, two training workshops focusing on multiple crop modeling and one on economic modeling were recently held. (more…)

  • Austin Hackathon

    Austin Hackathon

    The “Austin Hackathon”: helping crop models communicate with each other

    by Erik Alejandro Mencos Contreras

    One of the most important, and most complicated aspects of creating a model is developing a way for it to be compatible with other models, so that results can be compared and relevant conclusions drawn from them.

    Over the past 12 months, AgMIP (the Agricultural Model Intercomparison and Improvement Project) held a series of rapid development workshops, also known as sprints, to provide the opportunity for crop modeling and information technology experts to work together in creating a common language that can be used by a wide array of models. The goal is that all the modeling groups from around the world participating in the project will have access to all AgMIP datasets, making it easier to compare the diverse results, identify the uncertainties, and improve the models’ capabilities. The sprints were developed and organized by Cheryl Porter and Chris Villalobos, both from the University of Florida. (more…)