Session 2.3 Biophysical Impacts of Climate Change
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Session 2.3: Oral Presentation
Title: What would happen to wheat production in cotton-wheat cropping zone of Punjab under mid century scenario?
Authors: Ashfaq Ahmad1, T. Khaliq2, S. A. Wajid2, M. Ishfaq2, S. Tahir2, S. Ahmad3,
M. Ashfaq4 and G. Hoogenboom5 1 U.S.-Pakistan Centers for Advanced Studies in Agriculture and Food Security (USPCAS-AFS) University of Agriculture, Faisalabad, Pakistan, 2Agro-climatology Lab., Department of Agronomy, University of Agriculture, Faisalabad, Pakistan, 3 Department of Agronomy, Bahauddin Zakariya University, Pakistan, 4 Institute of Agricultural and Resource Economics, University of Agriculture Faisalabad, Pakistan, 5 University of Florida, USA
Abstract: Wheat is the staple food and contributes nearly 70% of the calorie needs of an average Pakistani. The cotton-wheat belt in the south comprises of 1.36 million ha and grows 45% of the wheat produced in the province. Cotton crops particularly cause serious delays in sowing of wheat. Cotton’s growth cycle and favorable price structure may push wheat planting into late December or early January. Down scaling results under RCP8.5 and CCSM4 model (with cool/dry characteristics) suggest a 2.5 °C rise in the maximum and minimum temperatures with 9% decrease in the precipitation amount in the 2040-2069 projected period over the region. The projected increase in temperature and the corresponding decrease in the precipitation regime give clues regarding devastation in the agricultural yield in the 2040-2069 projection period over the region. Well calibrated and validated models DSSAT and APSIM were used to simulate wheat yield at farmers field and found that both models simulated wheat yield well with <10% error. Both the model were run with base line 1980-2010 and then with future generated data with 5 GCMs.
Results showed that there will be reduction in wheat yield under future scenarios of RCP8.5 and 4.5. This reduction level is different in different district. However, this reduction about 1% in the current yield
Key words: APSIM, CERES-Wheat, GCMs, Climate change, RCP 8.5, RCP 4.5
Session 2.3: Oral Presentation
Title: Climate change impacts on crop yield in Koutiala, Mali
Authors: Myriam Adam1, A.M. Nenkam2, M. Diancoumba2, F. Akinseye2, P.S. Traore2,
S.B. Traore3, S. G. K. Adiku4, and D. S. MacCarthy4 1 CIRAD-INERA-ICRISAT, 01 BP 171, Bobo- Dioulasso 01, Burkina Faso, 2 International Crops Research Institute for the Semi- Arid Tropics, Mali, 3 Centre Régional AGRHYMET, Niger, 4 University of Ghana,
College of Basic and Applied Sciences, School of Agriculture, Ghana
Abstract: An integrated modelling framework is used to simulate crop productivity for current and future climate scenarios. Two crop models, Decision Support Systems for Agro-Technological Transfer (DSSAT) and the Agricultural Productions Systems sIMulator (APSIM), were calibrated and evaluated for the study site in Koutiala, Mali, simulating yields of maize, millet, and peanut for 123 households.
Session 2.3: Oral Presentation
Title: Sensitivity of current spring barley production system to climate change
Authors: Davide Cammarano, M. Rivington, K. Matthews, and D. Wardell-Johnson The James Hutton Institute, Scotland, UK
Abstract: Climate change will have significant impact on cultivated barley areas in Scotland, modifying the capability of land and thus the potential areas over which cropping activities may be conducted. In this study we evaluate the impact of climate change on simulated barley yield using 4 Global Circulation Models (GCMs), 2RCP (45 and 85), and 2 crop simulation models. The models were calibrated using benchmark variety trials and evaluated on field trial data collected at an experimental farm for spring barley. The models were run on the cultivated barley areas using geospatial datasets of climate land-use/crop management, and soils. Crop models calibration and evaluation showed little variability between models, and their ability to replicated experimental data. Overall, climate change will not have a significant negative impact on spring barley because the increase in temperature at such high latitude is within the optimal range for the cultivar. Future yield is forecasted to increase between 5 to 9% under RCP45 and RCP85,
Session 2.3: Oral Presentation
Title: Wheat Yield Potential in Europe Under Climate Change Explored by Adaptation Response Surfaces
Authors: Margarita Ruiz-Ramos1, R. Ferrise*2, A. Rodríguez1, I. J. Lorite3, Other
27 co-authors4 1 Producción Agraria-CEIGRAM, Universidad Politecnica de Madrid,
Spain, 2 University of Florence, Italy, 3 IFAPA, Junta de Andalucía, Córdoba, Spain, 4 MACSUR , FACCE-JPI, CropM activity, coordinated by, Finland
Abstract: Uncertainty about climate change increases the complexity of addressing adaptation and optimizing risk management at regional level. Approaches for managing this uncertainty, simulating and communicating climate impacts and adaptation opportunities are required. Here, we applied an ensemble of 8 crop models to identify suitable adaptation options for rainfed winter wheat at Lleida, NE Spain, and analyze the results by constructing adaptation response surfaces. These are plotted surfaces showing the response of an adaptation option compared to the non-adapted simulation in an impact variable (e.g. yield changes) for a range of systematic changes in temperature and precipitation. The general methodology was adapted from Pirttioja et al. (2015). The
adaptation options explored were changes in sowing dates, cultivar phenology, supplementary irrigation and combinations of these. A “full irrigation” scenario
also served as a reference for identifying yield potentials and associated
water requirements. The results indicated that adaptation strategies
may help to reduce detrimental effects of climate change. Combined adaptations
performed better than single adaptation options. The best results were obtained
when a non-vernalizing cultivar was sown 2 weeks earlier and given 40 mm of
supplementary irrigation at anthesis. However, some rainfed only options also
shown potential for mitigating climate change impacts. Our analysis evaluated if the explored adaptations fulfill the biophysical requirements to become practical adaptative
solutions. This study exemplified how adaptation options and their responses can be analyzed, evaluated and communicated in a context of high regional uncertainty for current and future conditions and for short to long-term perspectives.
Session 2.3: Oral Presentation
Title: Towards Coordinating Assessments of Environmental Sustainability in Agricultural Systems for SDG2
Authors: Sonali McDermid1, D. Kanter1, and C. Rosenzweig2 1 New York University, USA, 2 NASA Goddard Institute for Space Studies, USA
Abstract: Article 2.4 in Sustainable Development Goal (SDG2) states: “By 2030, ensure sustainable food production systems and implement resilient agricultural practices that increase productivity and production, that help maintain ecosystems, that strengthen capacity for adaptation to climate change, extreme weather, drought, flooding and other
disasters, and that progressively improve land and soil quality”. Achieving SDG2 demands a better understanding of those agricultural management practices deemed sustainable in both their biophysical and socio-economic contexts, and continued evaluation of these practices through advanced modeling, empirical measurements, and the development of indicators to monitor progress across varying spatial and temporal scales. Efforts are underway to coordinate research on the impacts of climate variability and change, and socio-economic development on agricultural production and rural livelihoods. Here, we initiate discussion of a complementary effort to comprehensively assess the environmental and socio-economic sustainability of various agricultural development trajectories, management practices, and adaptations in relation to meeting the needs of SDG2, while further informing the full suite of SDGs. This requires the formation of a coordinated assessment methodology that allows us to quantitatively understand the role of agricultural development in fostering sustainability in the context of current and future climate change. We suggest a modeling framework for AgMIP that considers, and develops linkages between, water availability and quality; agricultural carbon and nitrogen cycling, inclusive of GHG emissions; and agricultural biogeophysical feedbacks that impact a range of ecosystem services and biodiversity. We envision these efforts will incorporate findings, adaptations, and interactions with integrated assessments of food and nutrition security.
Title: Making climate data useful for decision makers at the local scale: the case of Nkayi district, Zimbabwe
Authors: Olivier Crespo1 , S. S. Nangombe2 , T. Muhwati3 , P. Masikati4 , S.H.K. Tui5 , E.
N. Moyo3 , D. Nyoni6 , and J. Rurinda7 1 University of Cape Town, 2 Meteorological Services Department, 3 Climate Change Management Department, 4 ICRAF, 5 ICRISAT, 6 Department of Agricultural Technical and Extension Services, Mechanisation and Irrigation Development, 7 University of Zimbabwe
Abstract: The climate change research community recognizes that climate data need to be translated into climate information useful and relevant for various users such as farmers and decision makers. They need context specific answers to increase their adaptive capacity and to allow effective planning. The most common challenge is to provide information on how climate variability and change will affect the current and future production of crops and livestock, and the entire agricultural systems.
The Agricultural Model Intercomparison and improvment Project (AgMIP) supports co-exploration of climate data analysis and climate information needs, with climate scientist and regional stakeholders, to produce useful climate products and services. Through dedicated and iterative engagement with local communities and regional stakeholders we propose dedicated analysis of current and future climate projections, delivered in
formats that will help farmers and stakeholders to make better informed
We present the results for Nkayi district in Zimbabwe. The climate is semi-arid, with dry moderately cold winter and variable low rainfalls during the hot summer, thus high risk for predominantly rain-fed agriculture. Future projections for the area show consistently increasing temperatures, but inconsistent rainfall changes. Local stakeholders are well aware of and mostly suffering those climate changes, but lack the relevant information to face them. Regional climate and crop research institutions, with Zimbabwean Meteorological Services, Climate Change Management and Ministry of Agriculture, with Nkayi and local farming community representatives, started co-exploring and proposing new ways to respond to local needs for climate information. This will contribute to the Impact Explorer (IE), web-based tool dedicated to the dissemination of locally relevant climate information.
21. Poster Presentation: Session 2.3
Title: The Impact of Climate Change on Rainfall and Maize Production in Nakon Ratchasima, Thailand.
Authors: Jaruwan Heangmanee1 1 University of Southhampton, UK
Abstract: Climate change is not only of concern with regards to environmental change but also in terms of its potential effects on different economic sectors. Agriculture is one such sector, which is extremely sensitive to the weather and water resources and which is being considerably affected by climate change. This research focuses on the impacts of climate change particularly on rainfall in the maize zones of the upper part of the Mun River Basin (Nakon Ratchasima province, Thailand). The projected climate change is derived using downscaled results from the Statistical Downscaling Model (SDSM) and the most recent Decision Centric (SDSM-DC) method, which is used to determine functional
and plausible future daily weather data and can substitute for missing data records for calibrated predictor-predictand variables respectively. The National Center for Environmental Prediction (NCEP) re-analysis was selected as the regional predictor variables for the period 1961-2000. In the case of the study area, which is located between two global grid cells, it was necessary to extend to the multiple-site method by interpolation. To assess the impact of climate change on agriculture, maize yields under different environmental impacts were analysed and simulated using the Cropping system tool-CERES-Maize model. To examine rainfall and maize yield interactions, a field experiment was developed in which maize was grown under 15 different treatment combinations that comprised rainfed and irrigated cultivations. Rainfed and irrigated treatments were located in natural conditions whilst rainfall simulation was in the greenhouses. The water requirements for the maize were based on the future rainfall modelled using SDSM. Two treatments simulated the effects of vegetative measurements (green manuring and cover cropping treatments) which reflect both anthropogenic
controls on vegetataion and possible vegetative response to climate change.
22. Poster Presentation: Session 2.3
Title: Evaluation of Climate Impact, Adaptation, Vulnerability and Resilience in Agricultural Systems using AgMIP Regional Integrated Assessment Methods
Authors: Sabine Homann-Kee Tui1 , K. Descheemaeker 2 , P. Masikate3 , R. Valdivia4 , and J. Antle4
1 International Crops Research Institute for the Semi-arid Tropics (ICRISAT), Zimbabwe, 2 Wageningen University, The Netherlands, 3 World Agroforestry Centre (ICRAF), Zambia, 4 Oregon State University, USA
Abstract: Climate-smart agriculture recognizes that climate impacts and vulnerability of smallholder farming systems must be addressed as part of broader pathways towards
sustainable agriculture. Evaluating potential impacts of adaptation technologies can inform transformation of agricultural systems, supporting food security and resilience under climate change. This paper illustrates how AgMIP simulation-based methods can be used for quantifying impacts of adaptation, useful for climate-smart agriculture. We explore trade-offs and performances for a mixed farming system in Nkayi district, semi-arid Zimbabwe, with high vulnerability to changing climate and limited capacity to adapt. Assuming that Zimbabwe will slowly step-up out of its economic crisis and a high emission
scenario (RCP 8.5), we tested adaptation options that stakeholders and scientists considered relevant, including integrated soil fertility management, drought tolerant crop varieties and livestock feed. Results suggested that even if impacts of climate change would be moderate on crops and livestock, more than half the farming population would be negatively affected and hence exposed to greater vulnerability, especially those without livestock. The tested adaptations offset the effects of climate change for crops and livestock. They benefited most farms and enhanced their resilience, the magnitude of gains would however be small, with greater gains for larger farms with livestock. The
fact that these incremental adaptation options reduced poverty levels for less
than 10% of the population is a strong argument for engaging stakeholders in
the design of more transformative solutions, including policies, institutional
arrangements and social organization, towards solving the complex issues in farming under changing climate.
23. Poster Presentation: Session 2.3
Title: Impacts of climate change: a sensitivity analysis to understand the role of soil fertility and water on maize in the face of climate uncertainty in semi-arid Zimbabwe
Authors: Patricia Masikati1 , O. Crespo2 , E. Moyo3 , D. Msendeke4 , J Rurinda5,6 ,
and K. Descheemaeker7
1 International Centre for Research in Agroforestry (ICRAF), Zambia, 2
Climate System Analysis Group, University of Cape Town, South Africa, 3 Climate Change Management Department-Ministry of Environment, Water and Climate, Zimbabwe, 4
Department of Agricultural Technical and Extension Services, Mechanisation and
Irrigation Development, Zimbabwe, 5 Department of Soil Science and Agricultural Engineering, University of Zimbabwe, Zimbabwe, 6 International Plant Nutrition
Institute (IPNI), Kenya, 7 Wageningen University, the Netherlands
Abstract: Although climate change would affect various development areas in Zimbabwe, the risk to agriculture is most important, mainstay of the country. There is limited knowledge on impacts of projected increases in CO2 and temperature on agriculture, changes in precipitation and combined effects on crop production, hence adding to uncertainties surrounding future smallholder farming systems. Biophysical crop models are commonly used to understand the impact of climate change on agricultural systems, investigate crop responses and development of adaptation strategies. We use the Agricultural Production Systems Simulator (APSIM) to assess sensitivity of maize to various aspects of climate change under different soils and management practices in semi-arid Zimbabwe. Results show that maize response to fertilizer reduced with climate change, but response curves varied across soil types and future climate projections. On current soils, which are low in organic carbon content (<0.5 % in top layer) and water holding capacity (<60 mm), the hot-dry scenario resulted in a maximum yield of 1.3 t/ha at a fertilizer application rate of 50 kg N/ha, down from 1.9 t/ha under the current climate. However, on better soils (OC> 0.70 % and PAWC >85 mm) the maximum yield would be >1.7 t/ha at the same application
rate and climate conditions. The sensitivity analysis revealed a sudden decrease in grain yield with a mean temperature increase of 2°C, while increased CO2 resulted in a steady increase of maize grain. Improving soil fertility and water holding capacity have the potential to reduce impacts of climate change on maize production.
24. Poster Presentation: Session 2.3
Title: Climate impacts on crop yields in Central Argentina. Adaptation strategies.
Authors: Alfredo L. Rolla1,2 , M. N. Nuñez1,2,3 , M. I. O. de Zarate1,2 , E. R. Guevara4 , S. G. Meira4 , G. R. Rodriguez4 , and J. J. Ramayon5
1 CIMA (CONICET- UBA), 2 UMI IFAECI (CNRS, CONICET, UBA), 3 DCAO (FCEN, UBA), 4INTA, 5 BRSA Consulting
Abstract: In this work the CASANDRA platform was used to make calculations for impacts and
adaptations to future climate on regional crop yields of maize, wheat and soybean, considering the Pampas region as study area (that covers an area of 60 million hectares). The climate inputs to the platform were generated from the CCSM4 climate model of National Centre for Atmospheric Research (NCAR, USA), because it was regarded as the best model among others for the present time in the region. Projections from the climate model show for the near future (2015 – 2039) and far future (2075 – 2099) increases of the annual mean of maximum and minimum temperature. Mean annual precipitation will also increase in the near future, while will increase more significantly for extreme emissions scenarios in the far future. The projected impact on crop yields according to the crop model for the near future shows a decrease of wheat yield, while for maize and soybean crop projections shows significant increment compared with the baseline for moderate (RCP4.5) and extreme (RCP8.5) emissions. In the far future, the wheat in the RCP 4.5 scenario the yield decrease, while in the scenario RCP 8.5 increase comparing with the baseline. For maize will increase and soybean will increase significantly for both scenarios. Some adaptation strategies for the near and far future were designed for maize and wheat, resulting in increases up to 45%. In soybean was not necessary design any strategy of adaptation.
25. Poster Presentation: Session 2.3
Title: Selection of a Representative GCM Subset for Integrated Assessment Modeling
Authors: Alex C. Ruane1 and S. P. McDermid2
1 NASA Goddard Institute for Space Studies, USA, 2 New York University, USA
Abstract: We present the Representative GCM Subset approach developed within the Agricultural Model Intercomparison and Improvement Project (AgMIP) to select a practical subset of global climate models (GCMs) for regional integrated assessment of climate impacts when resource limitations do not permit the full ensemble of GCMs to be evaluated given the need to also focus on impacts sector and economics models. Subsetting inherently leads to a loss of information but can free up resources to explore important uncertainties in the integrated assessment that would otherwise be prohibitive. The Representative GCM Subset approach identifies five individual GCMs that represent the full ensemble of temperature and precipitation change within the growing season while maintaining information about the probability that basic classes of climate changes (relatively cool/wet, cool/dry, middle, hot/wet, and hot/dry) are projected in the full GCM ensemble. We demonstrate the selection methodology for maize impacts in Ames, Iowa, and discuss limitations and situations when additional information may be required to select representative GCMs. We then classify 29 GCMs over all land areas to identify regions and seasons with characteristic diagonal skewness related to surface moisture as well as extreme skewness connected to snow-albedo feedbacks and GCM uncertainty. Finally, we employ this basic approach to recognize that GCM projections demonstrate
coherence across space, time, and greenhouse gas concentration pathway. The Representative GCM Subset approach provides a quantitative basis for the determination of useful GCM subsets, and may be extended for application to a range of scales and sectoral impacts.
26. Poster Presentation: Session 2.3
Title: Climate change impacts on maize production in western Mozambique
Authors: Jairos Rurinda1,2 , A.L. Gungulo3 , P. Masikati4 , O. Crespo5 , and S. H. K. Tui6
1 International Plant Nutrition Institute (IPNI), Kenya, 2 Department of Soil Science and
Agricultural Engineering, University of Zimbabwe, Zimbabwe, 3 Institute of Agricultural Research of Mozambique (IIAM), 4 International Centre for Research in
Agroforestry (ICRAF), Lusaka Zambia, 5 Climate System Anal, 6 Wageningen University, The Netherlands
Abstract: Climate change and increased climate variability are increasingly recognized as major biophysical sources of vulnerability for maize production and livelihoods in southern Africa. We analyzed the impacts of increasing temperatures and varying rainfall patterns on maize yield in Sussundenga, Mozambique. Multiple climate and crop simulation models were used in the analysis. An ensemble of 5 GCMs representing different climates (cool/wet; cool/dry; dry/wet; and dry/hot) were driven by two representative concentration pathways: RCP 4.5 and RCP 8.5 for the time period, 2040 – 2069. The climate data were inputs for two crop growth models, APSIM and DSSAT, which are widely validated across many areas in southern Africa. Both mean maximum and mean minimum temperatures have increased by between 1.5°C and 3°C and between 1°C and 2°C under RCP 8.5 and RCP4.5, respectively for the period 2040 – 2069 compared with the baseline, 1981 –2010. The direction of change of mean annual total rainfall is not yet clear although rainfall variability is highly likely to increase. Average maize yield simulated with APSIM declined by 12% under RCP 8.5 and by 5% under RCP 4.5, compared with the baseline climate. The average maize yield simulated with DSSAT declined by 32% under RCP 8.5 and by 28% under RCP4.5. Overall the results suggest that the impacts of climate change on the current low input maize production system are relatively low. Improved crop and soil fertility management practices would be more important than climate change by mid 21st
century for increased crop yield and livelihoods in western Mozambique.
27. Poster Presentation: Session 2.3
Title: Assessing the Yield Gap and resource use efficiency of Maize -A case study in Ethiopia
Authors: Amit K. Srivastava, T. Gaiser, and F Ewert.
Institute of Crop Science and Resource Conservation, University of Bonn, Germany
Abstract: In sub-Saharan Africa, the yields of the major cereal crops have stagnated at less than 25% of potentially attainable yields while the per capita food production has continued to decrease over the last several decades. Major reasons for the yield gap are frequent drought stress and lack of nutrients warranting their efficient use.There is high demand due to scarcity of information on yield gaps, nutrient use efficiency in Ethiopia. Hence, in this study, the yield gap and Agronomic nitrogen use efficiency was estimated for maize (Zea mays L) in Jimma, Bako, and Yayu districts in the Oromia region of Ethiopia, which constitute major maize production areas, based on simulation runs with the SIMPLACE modeling framework. The simulations were run at 25 x 25 km grid cells and yield was calculated for each simulation grid for the period of 13 years (1998- 2010) and aggregated from the simulation grid to the district level for comparing them
with the statistics. The yield gap was in the tune of 9700 kg ha-1 and results indicate that 200 kg ha-1 of nitrogen is the optimum application rate across the districts. Yield gaps were mainly due to nutrient limitations (nitrogen and to a smaller extent phosphorous) due to less average nitrogen application rates in this region (i.e., <20 kg N ha-1 Yr-1). Insufficient nutrient application happens because inorganic fertilizers are often too expensive for most of the farmers, whilst organic resources are available in limited quantities.
28. Poster Presentation: Session 2.3
Title: Balancing crop production and groundwater table recovery by cropping system adaptation in the North China Plain
Authors: Honglin Zhong1 , L. Sun1 , G. Fischer2 , Z. Tian3 , and Z. Liang4
1 Department of Geographical Sciences, University of Maryland, USA, 2 International Institute for Applied Systems Analysis, Austria, 3 Shanghai Climate Center, Shanghai Meteorological Services, China, 4 Hangzhou Meteorological Services, China
Abstract: To guarantee the food security, China has put great efforts on increasing crop production, and great success has been achieved in the last decades. But high crop productivity demands a great amount of water for irrigation, especially in the major cropping region – North China Plain (NCP), where the groundwater is over-extracted to meet the soaring needs from the rapid social-economic development and maintain high agriculture production.