Transcript Modeling crop-livestock intensification in Southern Africa AgMIP Sub-Saharan Regional Workshop (September 10-14, 2012) Patricia Masikati++

Modeling crop-livestock
intensification in Southern
Africa
AgMIP Sub-Saharan Regional Workshop
(September 10-14, 2012)
Patricia Masikati++
Full title
Crop livestock intensification in the
face of climate change: Exploring
opportunities to reduce risk and
increase resilience in southern Africa
using an integrated multi-modeling
approach
Southern Africa: Drastic increases in the
demand for agricultural products
Strong urbanization and income growth
Growing food
markets and
changes in
composition (more
meat, dairy, fresh
and processed
food)
5-6 times the
marketed food
between 2010 and
Source: Adopted from Capacity Development Initiative in Modernizing Food Systems—
2050
Michigan State, Makerere, Stellenbosch and Pretoria Universities, 2010)
…vs declining per capita food production
Source: Chilonda et al., 2007
Crop production
40
•Water productivity of maize 2 to 3
kg/ha/mm (Potential 9 to 12 kg/ha/mm
•Mineralizable N ranges 5 to 15 kg ha -1
•%OC = 2 to 2.2
120
30
Maxt & Mint (oC)
•Drought frequences 1 in every 3 years
35
100
25
80
20
60
15
Rainfall (mm)
•Rainfall ranges 450-650 mm per year
140
av rain= 562/yr
40
10
20
5
rain
mint
0
0
Jan
Mar
May
Jul
Sep
Nov
maxt
Livestock production
40
35
Frequency
30
25
Mortality
20
Sold
15
Slaughter
10
Lost/stolen
Predators
5
0
Jan
Feb
Mar Apri May
Jun
Jul
Aug Sept
Oct
Nov
Dec
80
70
number of respondents
60
Feed shortages
50
40
30
20
10
0
6
jan
feb
mar
apr
may
jun
jul
aug
sep
oct
nov
dec
Crop livestock systems and interactions
feed
$
feed
fertilisers
Investment capacity
$
Labor availability?
Access to cash/credit?
feed
draft power
$
nutrients
crop residues
Access to information?
manure
milk
Where to invest?
$
What type of crops?
feed
nutrients
draft power
crop residues
How many animals?
fertilisers
What type of feed?
Returns?
Source:
Adopted from
Rufino (2009)
$
On-farm
Proportions of income sources
Household’s sources of income
100%
80%
60%
40%
20%
0%
Mzimba
Crops
Livestock
Nkayi
Agricultural labour
Changara
Off farm income
Remittances
Goal
Identify pathways to improve food security and
develop adaptive management strategies to
reduce climate induced risks and increase
systems resilience
Objectives
•
•
•
Characterize farming systems in Southern
Africa in terms of bio-physical and socioeconomic characteristics
Develop and evaluate crop-livestock
management and climate change
adaptation strategies that improve agrodiversity and economic returns
Explore the interactions and synergies of
increased diversity and integration
Methodology
Description of current farming systems in terms of
biophysical and socio-economic aspects and constraints
(model input data), Literature review and data collected from
existing projects
Bio-physical: crop and livestock productivity, agriculture
potential, management interventions and productive resources
and use efficiency, location with regards to climate transition
zone
Socio-economic: household characteristics, crop and livestock
production orientation, production resources (prices of inputs
and outputs), access to markets, cropping patterns.
Methodology ctd
Evaluation and application of biophysical (crop livestock and
climate) and economic models (regional and global) Secondary and
primary data from existing projects (e.g ICRISAT CPWF, SLP ) for
model evaluation
Crop Models
Crop models such as APSIM, DSSAT, AquaCrop
Climate models
General circulation models
Livestock models
Livestock modeling tools such as AUSFARM, APSfarm and LIFE-SIM
Economic models
Tradeoff Analysis model for Multi-Dimensional impact assessment
(TOA-MD)
Methodology ctd
Integrated system analysis tool to assess
interactions and synergies
A tool to bring together data obtained from the biophysical and economic models and assist to determine
profitable management practices that can increase onfarm production and resilience across existing farming
typologies.
Target alternative crops
Dual purpose cereal and grain legume crops e.g
maize, sorghum, ground nuts, cowpeas) and forage
grasses and legumes (e.g mucuna, lablab, bana,
rhodes grass), that have the potential to provide
and improve both food and fodder which are the
main constraints to improved food security in
mixed farming systems of SSA
Management practices
Crops
1.
Conventional practice
2.
Conservation agriculture
3.
Crop rotations
4.
Microdose
Management practices evaluated
with water harvesting techniques
Contribution to:
Food security
Adaptation
Grain yield vs the household size
Performance of management practice
under current and projected climatic
Income generated
changes (variable and decreased
Stover production (quality and
rainfall, increased temperature and
quantity) vs feed requirements of
carbon dioxide
livestock per household and feed
Production and economic uncertainty
shortage period, stover for
conservation agriculture
Adoptability (e.g., returns in the short
term)
Using improved crop varieties of
different food and fodder crops
Livestock
1.
Conventional practice
2.
Improved feeding systems using
crop residues from the different
crop management practices
3.
Commercial feed system
Beneficial products and services
As above
Study countries and Co-PIs
Country
Co-PI
Institute
Malawi
Elizabeth Bandson
Bunda College of
Agriculture
Mozambique
Sebastiao Famba
Universidad Eduardo
Mondlane
South Africa
Olivier Crespo &
Chris Lennard
Sue Walker
University of Cape
Town
University of the
Free State
Kenya*
Lieven Claessens
ICRISAT, Nairobi
Zimbabwe
Patricia Masikati
Andre van Rooyen
Sabine Homann-Kee
Tui
ICRISAT, Bulawayo
* Kenya excluded, also key staff
Activities by teams
Crop-livestock
•
•
•
•
•
Characterize the current farming systems in terms of
biophysical and socio-economic aspects with assistance of
students from study countries (Malawi, Zimbabwe, South
Africa and Mozambique)
Compile crop-livestock data bases for model evaluation
and application. Develop management practices for
targeting and scaling out
Evaluate and apply bio-physical (crop and livestock)
models at regional level, ex-ante analysis of relevant
management practices for different typologies and their
long term production and climatic risks
Generate crop-livestock production data to be used as
input data for the TAO-MD model
Develop bio-physical and economic modelling training
manuals for students and NARs in collaboration with coPIs
Economic
•
•
•
•
•
Analysis of the current and alternative mixed systems and
to assess climate change and adaptation strategies and
their impacts on livelihoods, using the Tradeoff Analysis
model for Multi-Dimensional impact assessment (TOAMD)
Simulating spatial variability in economic returns that
represents heterogeneity in the farm population
Together with the AgMIP leaders, familiarize the southern
Africa team with the TOA-MD methodology during project
training workshops.
Link the TOA-MD model applications with the appropriate
data and multiple model simulations for crops and climate.
Integrate the socio-economic scenarios being developed
within AgMIP (RAPs) in TOA-MD and initiate interactions
with the global economic modelling team
Climate
•
•
•
•
•
•
•
Collection and analysis of CMIP3 (and CMIP5 when
available) GCMs data
Downscaling (statistical and dynamical where possible) of
these data at the station level
Production of daily minimum, maximum temperature and
rainfall project, as well as estimation of solar radiation
and/or potential evapotranspiration for various SRES
emission scenarios
Development of computing tools that will allow other teams
(in southern Africa as well as in Africa), to reproduce the
solar radiation process
Development of computing tools that will allow other teams
(in southern Africa as well as in Africa) to translate the
climate data format to other models
Participation in workshops
Participating in training workshops and develop a training
manual in collaboration with the other co-PIs
Outputs
1. Biophysical and socio-economic characteristics of
crop-livestock systems, constraints and pathways for
sustainable
• Maps with the main characteristics compiled and
documented
• Detailed description of farming systems
• Complied list of farmer profiles and detailed constraints
and development pathways for different typologies
• Framework for systems simulation and analysis
• Draft training manual on biophysical and economic
models for students and NARs staff
Outputs ctd
2. Management strategies relevant to the identified
typologies for improved food security; illustrate
interactions and synergies
•Detailed report on relevant management strategies for the
different typologies and their longterm production trends
and risks
• Training manual on biophysical and economic models for
students and NARs staff
•Report on interactions and synergies that increase
systems diversity and integration
Capacity Building
With Assistance from co-PIs from diff
Universities Training of MSc students
and NARs
MSc students
Training workshops
Outcomes
Greater understanding of challenges and opportunities in the
current mixed farming systems of southern Africa for better
targeting of interventions to increase systems resilience and
reduce climate induced risk.
Improved understanding of the interactions and synergies of
production system components (sub-systems); which
combinations bring about profitable production systems and
how to use these to facilitate development along sustainable
pathways
Thank you