Center for Environmental Systems Research, Kassel

SoNARe

Modelling social and economic influences on the decision making of farmers

in the Odra case study region

Center for Environmental Systems Research,Kassel

Michael Elbers

Social Networks of Agents’ Reclamation of land

2CAVES Meeting, 28 March 2007

Outline

• Motivation• The CAVES Odra case study

– Spatially explicit biophysical model (developed by WUT)

• The „finer grained“ agent-based model– Explicit empirically supported farmer decision rules– Modelling economic and social aspects of decision making– First simulation run(s)

• Outlook


Motivation

• Asymmetric dependency relation requires collective action

• Evidence for different farmer types and their respective sets of decision rules

• Explicitly contrast social and economic influences on decision making

• Make social pressure explicit in order to model the influence of water partnership initiators (WPIs) and model general opinion dynamics


Biophysical model setup

• Land parcels– Located along a channel, uniform size– Upstream-downstream neighbouring relationship between

owners– LRS condition, LU type, sluice gate

• Channels– Uniform slope– No branching, no interconnections

• Number of land parcels per channel– Same for all channels

• Weather conditions– Normal, drought, flooding, set yearly– Different weather sequences


Agent-based model setup

• Agents– Farmer– WPI, not necessarily a farmer itself

• Networks– Dependency “network” reflects spatial neighbourhood

relationship– Farmers are embedded in an acquaintance network– WPI is acquainted with, i.e. linked to, all farmers in a star-

like fashion


Agent-based model setup – economic Aspects

• Farmer agents recall their past economic success– Number of years memorised – Yield threshold

• defines “good years” or “bad years”– Economic sensitivity

• determines how much “good”/”bad” yields affect the perceived economic success

– Economic success• good years memorised increase the perceived

economic success, bad years decrease it

• WPI uses social network to observe farmers’ economic success


Agent-based model setup – Social aspects

• Farmers exert social influence– Use outgoing network edges– Positive influence, endorsement

• acquaintances using the same LRS-strategy are supported

– Negative influence • acquaintances using the opposite LRS-strategy are

pressured into switching the strategy

• Farmers perceive their present level of social support– Use incoming network edges– (sum of) social influences received from neighbours in the

acquaintance network (including WPI)

• WPI may exert additional social influence pro LRS


Agent-based model setup – Network types


Agent Decision Making

• Farmers– IF

social support + economic success sufficiently lowTHEN switch LRS maintenance strategy (maintain/¬maintain)

– IFWP exists and maintain LRSTHENjoin / stay in WPELSEdo not join / leave WP

– (always exert social influence in favour of own strategy; possibly higher influence when member of WP)

• Water Partnership Initiator (WPI)– IF

number of farmers with big losses >= 3THENexert social influence pro LRSELSEdo not exert social influence

• Water Partnership (WP)– IF

number of farmers maintaining LRS >= 3THEN activate WPELSEdeactivate WP


Model Execution Cycle

• May: plant crops• October: harvest crops• December: make decisions for the coming year, i.e.

1. perceive and memorise yield 2. exert social influence3. perceive social influence and economic success4. decide (decisions are buffered => synchronised)5. commit to decisions


Abstract Land Parcel Map

Flow direction of channel

Agents maintaining LRS

Agents neglecting LRS


Scenario A

• Baseline scenario, 1 channel, 10 farmers• 2 normal years followed by 1 year of flooding• Farmers do not rate their economic success• No social influence• Thus: no opinion dynamics


Scenario A

12 24 36 48 60 72 84 96 108


Scenario B

• 1 channel, 10 farmers• 2 normal years followed by 1 year of flooding• Farmers rate their economic success

– yieldThreshold = 9.0

• No social influence


Scenario B


Scenario B

84 96 120 132 144 180 192 360... ......


Scenario C

• 10 channels, each 10 farmers• 2 normal years followed by 1 year of flooding• Farmers rate their economic success

– yieldThreshold = 9.0

• Scale-Free topology for acquaintance network• WPI (linked to all farmers in a star-like fashion)• Farmers and WPI exert social influence


Scenario C


Scenario C

36 48


Scenario C

168 180


Scenario C

288 300


Scenario C

336 480


Outlook

• calibrate the model• include allowances and compensation payments• include sluice gate operation / fish ponds• include additional land use types• distribute farmer types heterogenously• apply different network topologies• perform sensitivity analyses

Center for Environmental Systems Research, Kassel

Documents

Transcript of Center for Environmental Systems Research, Kassel