wu wenbin — model based assessment of potential risks of food insecurity at a global scale
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Model-based Assessment of Potential Risks of Food Insecurity
at a Global Scale
Wenbin WU(吴文斌)
International Conference on Climate Change and Food Security
Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, China
What is food security?
Food security—all people, at all times, have physical, social, and economic access to sufficient, safe, and nutritious food that meets their dietary needs and food preferences for an active and healthy life (FAO,1996).
“让所有人在任何时候都能在物质上和经济上获得充足的、安全的和有营养的食物,来满足其积极和健康生活的膳食需要及食物喜好”
The food security status of any group can be normally considered as the principle outcome of food systems.
Four components of food security
Food availability: the availability of sufficient food, i.e., to the overall ability of the agricultural system to meet food demand.
Food accessibility: the ability of a unit of individuals to obtain access to acquire appropriate foods for a nutritious diet.
Food utilization: individual or household capacity to consume and benefit from food.
More recently, as climate change issues have caught great attention from the world, food stability is also considered one important component of food security. individuals who are at high risk of temporarily or permanently
losing their access to the resources needed to consume adequate food.
Understanding food security is of great implications
FAO, 2009 IFPRI, 2009
Many countries (in particular developing countries) are fighting against the food crisis in different ways. These are usually based on a better understanding of the
dynamics, risks and forces that shape the factors affecting food security . Assessment of food security status is thus high on the
policy agenda of most countries.
What about the future situation?
There has been considerable progress in assessing food security at different space and time scales.
We have little knowledge about the future food security situation: How it will evolve over time and what are the major
impacts of these future changes?
It is not possible to predict future food security status due to uncertainties in future social, political and economic development.
What about the future situation?
It is possible to explore what might happen given certain assumptions about societal and environmental changes through scenario construction: Improved foresight of food security can help better inform policy
decisions.
Scenario-based studies provide an appropriate tool to
develop plausible visions of future pathways of food security
This research attempts to assess the potential risks of food insecurity under given future scenarios.
Methodology in this study
Those studies, which focus only on crop production,
provide only a partial assessment of food security.
A holistic approach for assessment of food security is used in this study to cover the major components of food security as many as possible.
A multi-factor, multi-model and spatially explicit assessment method is proposed in this study.
A spatially explicit assessment method
3
Traditional method: assessment of food security are normally conducted at a national or regional level.
These analyses of food security have some limitations: Not reflect the considerable variations in the food security
situation within a particular country or region. Coarse results and lower spatial location description.
Time1 Time2
Secure or Security grades?
A a spatially explicit assessment method
3
This study: specific attention is paid to develop a spatially explicit assessment method for food security.
Spatial information technologies (Remote sensing, GIS and Spatial models) are used for method development.
Time1 Time2
Secure or Security grades in
each pixel
A multi-factor and multi-model method
Indicators Factors
Models
Per capita food availability
Food availability and stability
Per capita GDP
Food accessibility and affordability
Social factors
Population status
Economic factors
Gross Domestic Product (GDP)
Biophysical factors
Food production
Crop yields
GIS-based EPIC model
Crop sown areas
Crop choice decision model
Crop price and trade
IFPSIM model
Crop area model—crop choice decision model
The crop choice decision model was used to analyze the changes in crop areas by investigating changes in crop choice decisions among a variety of available alternatives.
Land user
Landscape
Natural ecosystem
Socio-economic system
Crop choice decision
Crop yield model—GIS-based EPIC model
Wheat
Maize
Rice
Soybean
Soils
Planting date
Cropping system
Topography
Irrigation
Global land use
Harvest date
The GIS-based EPIC was used to estimate the potential yields of different crop types under a given biophysical and agricultural management environment.
Crop price model—IFPRIM model
Crop price was assessed by the International Food Policy and Agricultural Simulation (IFPSIM) model.
Food supply
(In collaboration with the University of Tokyo, Japan)
Future scenario setting
Time period for scenario analysis: 2000-2020
Scenario development
Scenario analysis
Global total population
Average growth rate of global urban population
Global total GDP
Growth rate of urban population for countries
Total population for countries
Growth rate of GM crops for major countries
Socio-economic scenarios: describes the key elements, such as demography, economic development, technology, and policy interventions, which together provide the description of a possible future state of the world.
High economic growth rate
IPCC SRES: A1 scenario
Relatively low population growth
Climate change scenarios: Defines the major features of future climate change, which may strongly drive changes in the crop yield and cropping systems in future; Monthly maximum temperature, minimum temperature and precipitation data between 2000 and 2020 were obtained from the high resolution projections of MIROC (developed by the University of Tokyo, Japan).
3600 1800 100
year
MIROC simulated data for 1901-2000
(1.1 degree)
CRU observation data for 1901-2000
(0.5 degree)
3600 1800 100
year 3600
1800 20 year
MIROC simulated data for 2000-2020
(1.1 degree)
Downscaling (0.1 degree)
Grid by grid regression
Downscaling (0.1 degree)
Downscaling (0.1 degree)
Grid by grid bias correction Method for climate data calibration
Steps for assessing potential risks of food insecurity
Step 1: Based on the simulated crop yields and crop areas, the changes in total food production were assessed by comparing the food production in 2020 with that in 2000. Change ratio of total food production (CR_p) was calculated with the following Equation:
Y is the crop yield for crop type i; A is the crop areas for crop type i; n is the total number of crops.
∑
∑
=
=4
1i
2000i
2000i
4
1ii
2020i
A*Y
A*YpCR
2020
- -
Steps for assessing potential risks of food insecurity
Step 2: To understand whether the projected changes in total food production will influence the overall food availability, relative changes in per capita food availability (CR_a) for the same period were calculated:
Y is the crop yield for crop type i; A is the crop areas for crop type i; POP is the total population; n is the total number of crops.
20004
1i
2000i
2000i
20204
1i
2020i
2020i
POPA*Y
POPA*YaCR
∑
∑
=
=--
4. Steps for assessing potential risks of food insecurity
Step 3: A separate analysis for the changes in per capita GDP were undertaken because it can strongly impact the purchasing power and determine whether a country or region is able to import more food from outside. First computed the overall increase in per capita GDP between
2000 and 2020.
Then calculated the relative difference between the growth rate of per capita GDP in a grid cell and the average per capita growth rate.
Steps for assessing potential risks of food insecurity
Step 4: The changes in per capita food availability and the changes in per capita GDP were combined to examine the hotspots of potential risks of food insecurity for the study period through identifying the areas: With decreased per capita food availability.
With a slower growth rate of per capita GDP than the
average growth rate.
Rice
Maize
2000
2020
-i
i
YYCR
CR: change ratio; Y: crop yield for crop type i;
Simulation results--changes in crop yields
Wheat
Soybean
Simulation results--changes in crop yields
2000
2020
-i
i
YYCR
CR: change ratio; Y: crop yield for crop type i;
Simulation results--changes in crop areas
2000
2020
Simulation results--changes in crop areas
0
40
80
120
160R
ice
Mai
ze
Whe
at
Soyb
ean
Ric
e
Mai
ze
Whe
at
Soyb
ean
Ric
e
Mai
ze
Whe
at
Soyb
ean
Ric
e
Mai
ze
Whe
at
Soyb
ean
Ric
e
Mai
ze
Whe
at
Soyb
ean
Ric
e
Mai
ze
Whe
at
Soyb
ean
Africa Asia Europe Latin-America North-America Oceania
Sow
n A
rea
(in m
illio
n he
ctar
es)
2000 2020
Sown areas of rice, maize and wheat were predicted to increase in each continent. Soybean areas declined in Africa, Asia and North-America, but slightly increased in other regions.
Changes in total food production
Changes in total food production
∑
∑
=
=4
1
20002000
4
1
20202020
*
*
-
iii
iii
AY
AY
CR
CR: change ratio; Y: crop yield for crop type i; A: crop areas for crop type i.
Climate change will result in a reduction in total food production during 2000–2020 in several regions such as southern China, southern and south-eastern Asia, western and eastern Europe, Northern Great Plains in USA, Brazil and some African countries.
Climate change will lead to an increase in total food production in some regions in northern China, northern India, northern Europe, Central USA, Argentina, Australia and some eastern African countries such as Kenya and Zimbabwe.
Changes in per capita food availability
Change in per capita food availability
20002000
20202020
//
-POPTotalPOPTotal
CR
CR: change ratio; Total: total food production; POP: Total population.
A substantial increase in per capita food availability can be found in Northeast China, eastern and southern Europe, USA and Brazil.
Noticeable increase can also be found in southeastern Asia, Argentina, south-eastern Africa and Australia.
Decreases in per capita food availability are located in Northern and Southern China, most southern and south-eastern Asian countries, western Europe, USA, Brazil, Argentina, and most African countries.
Changes in per capita GDP
Change in per capita GDP with respect to the global average
Areas with the highest growth rate of GDP per capita are located in developing countries such as China, south-eastern Asian countries and Latin-American countries, and some south-eastern and northern African countries such as Botswana, Mozambique, Morocco and Egypt.
The areas located in southern Asian countries and most African countries are likely to experience a dramatic decrease in the capacity to import food on a per capita basis than currently as the growth rates of GDP in these areas are 35-50% lower than the world average.
Improve the food security situation: either an increase in per capita food availability or an increase in the capacity to import food. Remain the hotspots of food insecurity: a decrease in both the
per capita food availability and the capacity of being able to import food.
Potential risks of global food insecurity
Developed countries will still be food-secure: their populations less rely on subsistence agriculture, have
higher financial support and purchasing power, the substantial adaptive capacity and proactive food management systems.
Potential risks of global food insecurity
Protect the quantity and quality of farmlands and invest more to improve land productivity so as to provide enough food supply (Food Availability).
Build efficient agricultural subsidy systems to improve the farming income and strengthen purchase power(Food Affordability).
Reform the food circulation and agricultural commodity trade systems to enlarge food supply by linking to outside international and domestic market (Food Accessibility).
Actively improve the adaptive capability of agriculture in response to climate change to ensure a stable food production(Food Stability).
Recommendations for reducing food insecurity risks
International Conference on Climate Change and Food Security
Thank you very much for your attention!!!
wwb@mail.caas.net.cn
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