measures of short and long term viability of an agricultural region researchers: xianfeng su, geoff...
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Measures of Short and Long Term Viability of an Agricultural Region
Researchers: Xianfeng Su, Geoff Carlin
Project leaders: Senthold Asseng, Freeman Cook, Peter Campbell, Michael Poole
Main collaborators: Steven Schilizzi, Henry Brockman, Blair Nancarrow, Mescal Stephens, Atakelty Hailu, Angela Wardell-Johnson, Shams Bhuiyan, Scott Heckbert, Mick Harcher, Tom McShane, Art Langston
University of Western Australia
Project Aims & Background
Biophysical, Economic and Social
Components Analysis
Model Design
Model Framework
Simulation
OUTLINE
Simulating Farmers and Land-Use Change
Improve the long-term viability of
agricultural regions ?
Natural Resource Condition and Trend
Stable & resilient local communities
Long-term viability characterised by outcomes from:
Yield/profit, economic
sustainability region
Objectives, Scenarios and Case Study Areas Objectives• To understand the complex interactions
between human and landscape change processes
• To study emergent behaviours in human-landscape systems
• To improve the long-term viability of an agricultural region
Scenarios• Climate change• Environmental risk
perception/management • New technology• Policies• Market• Social values
Katanning Region in Blackwood Catchment
Burdekin Delta
Biophysical, Economic and Social Changes
Trajectory- Individual farmers information - Shires record- Regional data
Drivers found- Farmer interviews- Consultants- Literature reviews- Historical land-use change analysis
30 km
risk
Natural/planted vegetation
Digital Elevation Map
Historical Land-use Changes
Resource: CMIS CSIRO
Salinity & Waterlogging riskNatural/planted vegetation cover
30 km
Change in crop/pasture ratio, Katanning/Kent shire & Auction Price of Greasy Wool
Data: Hailu, UWA
0
100
200
300
400
500
600
700
800
1 2 3 4 5 6 7 8 9 10 11 12 13 14
Years
Wool price (cent/kg)
90 92 94 96 98 00 02
Years
0
10
20
30
40
50
60
70
80
90 92 94 96 98 0 2
Year
% o
f tot
al a
rea
crop
pasture
% of total area
90 92 94 96 98 00 02
Years
Other changes:
Population & age pattern Katanning town
Year1983 1991 1996 2001
Population
2000
2100
2200
2300
2400
MaleFemale
Year1983 1991 1996 2001
% of Population
0
10
20
30
40
50
8 - 32 Yrs33 - 57 Yrs58 - 72 Yrs
Data: ABS
Population decreased, old age trends
cropped area increased & pasture area
decreased
Land value increased
Costs of farm operating increased
Market price changed
New technology: canola has become a major
income for some farmers
Land degraded
Summary 1990 - 2004
Model
design Integrating biophysical, economic and social models
Cropping model
Social Network Model
Economical Model
Policies
LandscapeSoil (erosion, degradation)
Surface and ground water
Land cover (crops/crop trees/pasture/natural vegetation, infrastructure, town)
Livestock
Hydrology model
Output
Land cover and livestock dynamics
% degraded land
Nutrient cycling
SocietyFarmer: attributes and behaviours.
Household: structure, status, management strategies
Community: relations & structure, functions
Demography dynamics
EconomicsInternational and National market
Bank: interest
Household: productions, investment and consumption
Output
Household cash flow
Loan
Atmosphere
Output
Agent’s Courses of Actions;
Demographics pattern;
Communities structure and changes
Information diffusion
Concept Behind the Decision Making Process
Capacities & Constrains of biophysical, economic and social
components
Model design
Abstraction of Main Objects
Financial Model
Farmer Attitude & intended Behaviours
Attitude Model
Policies (past, current, future)
Market
Land cover
Production Consumption
Climate
Investment
Off-farm income
Biophysical Model
Goes to
Impact
Produce &influence
Impact
Impact
Interact
Adopted
Impact
Decide
Change
Decide
Change/ impact
Used in
: External input
Contains
New Tech.
Decide
Attitude Model
Biophysical Capacities & Constraints Financial Capacities & Constraints Social Capacities & Constraints
Decision Making Process
Model design
Agent Beliefs + Situation-action rules behaviour
(reactive agents) (Doran 1999)
Agent Beliefs + Goals + “Rational” Planning behaviour
(deliberative agents) (Doran 1999)
Person needs and value Ability/capability
Opportunity Uncertainty Behaviour
Decision making drivers - land use
Market
Economic scale and margin
Rotation
Time
Profit
Habits
Do the same as last year
-- from Farmer Interviews
Model design
Money
Time
Successful plan
Family
Skilled casual workers
Farm size
Risk management
-- from Farmer Interviews
Constraints for running a farm:
Model design
Evaluate Lifestyle Factors COA
Farmer – farm diary driven COA
Adopt new farming technology or new crop COA
Evaluateenvironmental perceptions COA
Non-farmer low resolution collection of COA’s
Employment COA
Evaluate RegionalAmentities/Services
COA
Major employer viability COA
Abbatoirs
Tree Nursery
Sheep Saleyards
Lumped Retail
Lumped Farm Wholesale
Government & other organization regional services viability COAHealth Services
Education Services
Local Government Services
Sports Clubs
Other Recreation & Service Clubs, etc.
Top Level COA VIEW
Simulation For Farmer Action
A set of ActionsA
C
Behaviour-oriented
Financeflow
Trigger Action
Information
organization
Individual/household
consequence
Gov. Market
community
D
JanFeb DecMar.
Action A Action B
Start End
Year
Information
Information transfer ->Make a decision-> take a action ->Behaviour Change
Model design
An Example of COA in Programming
Farmer Parameter:
Atmosphere Time, Soil Crop Seed available Bank Balance
Machine List of machines Resource Manager
Resource Pool: FarmerRole
Aspects: Sow
COA
Site preparation
Start sow
Atmosphere (Rainfall) Resource Manager Resource Pool: atmosphere
Participant: farmer Duration: 1week Timeout: before sowing time
Participant: person, machine,rainfall, Duration: effectArea/(ha/d) Timeout: not late than the common sow time for different species
Resource Manager Resource Pool: Machine MachineRole
Model design
A simple Time Template used in the program
Time Template Entity (&aspects) Process Feb Mar Apr May Jun July Aug Sep Oct Nov Dec Jan
Atmosphere rainfall(change) Landscape soil (no change) crop (growth) canola wheat barley lupin pasture (growth) Farmer (coa) check Agenda sow last Week * first 2 harvest last2 bf Xmas 2weeks* sell crops banking on loan pay loan household calculate bankBalance 1day pay monthly bill one day per month a day or few days in a week, depending on the task 1 week, from 25th for canola, if rainfall >20mm 2 weeks 3 weeks whole month
Framework – DIAS/FACET/JEOVIEWER
Domain model -- DIAS framework
Connect:
- Hydrology Model
- Economic Model
- Social network model
Social network & COAs -- FACET
Output -- JEOVIEWER
Simulation