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1/21 EFFECTS OF CLIMATE CHANGE ON AGRICULTURE: THE SOY-AMEX EXPERIMENT Marcos Heil Costa Aristides Ribeiro DEA/UFV.

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Presentation on theme: "1/21 EFFECTS OF CLIMATE CHANGE ON AGRICULTURE: THE SOY-AMEX EXPERIMENT Marcos Heil Costa Aristides Ribeiro DEA/UFV."— Presentation transcript:

1 1/21 EFFECTS OF CLIMATE CHANGE ON AGRICULTURE: THE SOY-AMEX EXPERIMENT Marcos Heil Costa Aristides Ribeiro DEA/UFV

2 2/21 The effects of climate change on agriculture are usually studied using the following framework: IPCC scenarios IPCC climate downscale (or not) applications Applications include:  agroclimatic zoning  agricultural pests and diseases  crop productivity analysis

3 3/21 IPCC 2001

4 4/21 Climate effects of Amazon deforestation compared to effects of doubling CO Effects of full deforestationEffects of doubling CO 2 Combined effects Costa and Foley, J. Climate, 2000 Local climate effects of changes in land cover are of the same order of magnitude, or even higher, than the climate effects of rising CO 2

5 5/21 Tropical South America will be one of the main agricultural frontiers in the XXI Century Global distribution of croplands Global distribution of pasturelands

6 6/21 Inconsistencies arise when different land surface models are used accross the application framework IPCC Scenarios Coarse resolution IPCC climate Fine resolution climate Application x Climate model Land surface model 1 Regional model Land surface model 2 Crop productivity model Land surface model 3 Sources of inconsistencies

7 7/21 Inconsistencies are higher when crop land cover is higher Global distribution of croplands Global distribution of pasturelands

8 8/21 Expansion of soybeans in Amazonia

9 9/21 Possible solution for inconsistencies: Use the same land surface model in all three operations: Climate simulation Downscale Crop productivity

10 10/21 Same land surface model framework IPCC Scenarios Coarse resolution IPCC climate Fine resolution climate Application x Climate model Land surface model 1 Regional model Land surface model 1 Crop productivity model Land surface model 1 Climate modelRegional model Land surface model Crop productivity model Or:

11 11/21 Our project at UFV: Climate modelRegional model Land surface model Crop productivity model NCAR CCM3RegCM3 IBIS AGRO-IBIS

12 12/21 Our project at UFV: NCAR CCM3RegCM3 IBIS AGRO-IBIS IBIS is a land surface model that simulates fluxes between the vegetation and the atmosphere. AGRO-IBIS (Kucharik and Ramankutty, Earth Interactions, 2005) is a crop productivity model that uses the same GCM-grade land surface physics package of IBIS. It has been validated for corn and soybean for US conditions.

13 13/21 To work appropriately, the model must be adequately parameterized to relevant crops Our project at UFV: AMEX Experiments

14 14/21 AMEX: Agronomical and Micrometeorological Experiments Designed with the purpose of parameterizing GCM-grade crop productivity models Consists of an agronomical experiment running at the same time as a micrometeorological experiment

15 15/21 AMEX: Agronomical and Micrometeorological Experiments First experiment: SOY-AMEX Soybeans, Paragominas, PA, Brazil Experiment funded, first data collection season started in January 2006 Second experiment: SUG-AMEX Sugar cane, Triângulo mineiro, MG, Brazil Experiment funded, waiting for release of funds. Expect to set up experiment in 2007.

16 16/21 Data collected at AMEX sites Instantaneous, half-hourly or hourly measurements: 1. Precipitation 2. Air specific humidity 3. Air temperature 4. Incoming and reflected solar radiation 5. Incoming atmospheric radiation 6. Horizontal and vertical wind speed 7. Wind direction 8. Atmospheric pressure 9. Latent and sensible heat fluxes, CO 2 flux 10. Soil heat flux

17 17/21 Data collected at AMEX sites Daily measurements: 1. Soil moisture, down to 50 cm depth 2. Soil temperature, down to 50 cm depth 3. Rainfall on raingauge, to fill gaps on the hourly precipitation dataset

18 18/21 Data collected at AMEX sites Weekly measurements: 1. LAI 2. Plant height 3. Above-ground biomass (leaves, branches, grains) 4. %C e %N on above ground litter 5. Soil respiration flux 6. Soil fraction covered by vegetation Monthly measurements: 1. Specific leaf area (m 2 of leaf area per kg of dry biomass or kg C). 2. Physiological measurements - carbon assimilation x light curve - carbon assimilation x temperature curve - stomatal conductance

19 19/21 Data collected at AMEX sites Single measurements: 1. Soil moisture retention curve – stratification by layers 2. C, N and soil bulk density as function of depth to 1 m 3. Biomass of fine roots and %C and %N on the fine roots (single sample at the end of cycle) 4. Agronomical characterization of the crop: Initial fertilization Frequency and level of nitrogen fertization Cultivar used Dates of beginning and ending of each phenological stage

20 20/21 First results: SOY-AMEX Silvia Yanagi, doctorate thesis

21 21/21 Summary and Conclusions We may have better evaluations of future climate and agricultural activities if we use the same land surface model throughout the entire analysis framework of the effects of climate change on agriculture At UFV, we plan to use the CCM3/RegCM3/IBIS/AGRO-IBIS suite of models to improve analyses and predictions of the effects of climate change on agriculture The AMEX set of experiments is designed to correctly parametrize GCM-grade crop productivity models The very first results of the parameterizations obtained by SOY- AMEX indicate important differences from previous results Other groups are welcome to join this effort


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