Modeling resilience to climate change:

assessing effects of microclimate on

agricultural production and the social system

Jacopo A. Baggio

jbaggio@asu.edu or jb80it@gmail.com

Center for the Study of Institutional Diversity

School of Human Evolution and Social Change

Arizona State University

Resilience: a definition

Social-Ecological System

Resilience is the ability of a SES to absorb disturbance and

re-organize while undergoing change, so as to still retain

essentially the same functions, structures, identity and

feedbacks

Economics

The ability of a local economy to retain function,

employment and prosperity in the face of the perturbation

caused by the shock of the loss of a particular type of local

industry or employer

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Understanding the System

The interplay between

technological, social

(economic included), and

ecological systems is

fundamental for an

adaptive governance that is

able to balance efficiency

in the short term with

resilience in the long term.

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Understanding the System

Uncertainty

Dealing with uncertainty and disturbances in CIS in their

present configurations, i.e., maintaining the function of what

we have.

Adapting existing systems incrementally/or stepwise? to

new types of uncertainty and disturbances

Plan for possibility of transitions/transformations

toward new CIS configurations as existing CIS become

untenable.

Such transformations are a necessity for shifting toward

development pathways that satisfy the performance measures

that define the sustainability decision making framework.

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Understanding the System

physica (aisthêsis for the Stoics), i.e.

the study through observation of

perceivable quantities

(e.g. the five senses)

logica (logos), or reasoning, thus

formulation of theories

(e.g. mathematical/computational

models)

ethica (arètê), or the norms in which

the real system are embedded

(e.g. values and norms)

politica (hormê), or dealing with the

actions that shape and are shaped by

the real system

(e.g. action research)

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Method

Domain Case Study Experiments Modelling

Model of Values

Empirical Observation

Action

Deductive Reasoning

DeductiveReasoning

(Logica)

EmpiricalTesting

(Physica)

Model ofValues(Ethica)

Action(Politica)

Experiments

Case Studies

Models

Governance

“Governance” is a product of a set of interacting infrastructure types, that is

Governance Dynamics is dependent not only on “soft infrastructure” (rules and norms) but also on technological and ecological infrastructures that may constrain options

HERE: How to create adaptive strategies in face of uncertainty in micro-climate?

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IAD Framework

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Robustness Framework

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Robustness Framework

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Connection Example Potential Problems

(1) Between resource and resource

users

Availability of water at time of need Too much or too little water

(2) Between users and public

infrastructure providers

Voting for providers

Contributing resources

Recommending policies

Monitoring performance of providers

Indeterminacy / lack of

participation

Free riding

Rent seeking

Lack of information/free riding

(3) Between public infrastructure

providers and public infrastructure

Building initial structure

Regular maintenance; Monitoring

and enforcing rules

Overcapitalization or

undercapitalization; Shirking

disrupting temporal and spatial

patterns of resource use; Cost /

corruption

(4) Between public infrastructure

and resource

Impact of infrastructure on the

resource level

Ineffective

(5) Between public infrastructure

and resource dynamics

Impact of infrastructure on the

feedback structure of the resource–

harvest dynamics

Ineffective, unintended

consequences

(6) Between resource users and

public infrastructure

Coproduction of infrastructure

itself, maintenance of works,

monitoring and sanctioning

No incentives / free riding

(7) External forces on resource and

infrastructure

Severe weather, earthquake,

landslide, new roads

Destroys resource and infrastructure

(8) External forces on social actors Major changes in political system,

migration, commodity prices, and

regulation

Conflict, uncertainty, migration,

greatly increased demand

Governing Uncertain, Complex Systems: A

robust Control Approach

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Governing Uncertain, Complex Systems: Agent

Based Modeling For Robust Control

Behavioral models Based on

Data

Irrigation Experiment

Importance of Variables of

Interest

Comparing Different Model

Alternatives

Calibrating to Fit the Variables

of Interest

Sensitivity Analysis

Scenario Planning

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Setup

(agents initial values)

Agents Investment

Decision

Resource Availability

based on investment

is calculated

Agent 1

Resource Extraction

Decision

Agent 2

Resource Extraction

Decision

Agent 3

Resource Extraction

Decision

Agent 4

Resource Extraction

Decision

Agent 5

Resource Extraction

Decision

Stop?

if Round = 15

YES

Stop

NO

Model Type

Governing Uncertain, Complex Systems:

ABM For Robust Control

Connectivity

Management

Theoretical

Manager action =

CONTROLLER

Comparing Different

Scenario

Most Robust and

Most Efficient!

Planning!

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Setup of theLandscape

Predators andPrey placement

Density of predatorsand prey on patches is

determined

Prey reproduceand disperse

Predators reproduce,hunt for prey, disperse

and die naturally

Patchescarrying capacity

is updated

Manager acts according to specific

strategies

Stop?if predators or prey are extinct

if time-steps = 4000

Stop

NO

YES

More Specifically: Modeling Resilience – Adaptive

Governance (Or adaptive decision making)

Biophysical Conditions: microclimate variations, temperature, humidity, precipitation, soil

Attributes of the Community: farmers background, tradition and rules in use

Action Situations: type of crop, trade, insurance, pest prevention and control

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Robustness Framework: Visualizing Robust

Control of a Complex Interdependent Syustem

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Specifics

Social Infrastructure -> Goals: agricultural

production and trade of cacao

Decision making: type of cacao to plant,

“insurance scheme”, influencing ecological

connectivity

Ecological System: microclimate variations,

pest outbreaks, ecological connectivity

Technological Infrastructure: Dam building,

potential canals, roads etc.

Deliverables

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Assess trade-offs in allocating scares resources

between policies

Minimize risk and unintended consequences

(i.e. uncertainty) of specific policies

i.e. water resources, agricultural production,

infrastructure maintenance and building,

monitoring

Deliverables

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Type of Controls needed to avoid “social

deterioration”

Start to design robust systems able to adapt

(flexibility?) to low probability and potentially

extreme events

Design adaptation strategies

Prepare for the unexpected???

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