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