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Complexity Theory: The Big Picture in Sustainability Scienc Complexity Theory: The Big Picture in Sustainability Scienc

Complexity Theory: The Big Picture in Sustainability Scienc - PowerPoint Presentation

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Complexity Theory: The Big Picture in Sustainability Scienc - PPT Presentation

Defining sustainable development Sustainability Defining sustainable development in broader terms Sustainability Science Criticisms of current approaches Complexity and complex adaptive systems ID: 163503

systems complexity icsd complex complexity systems complex icsd 2015 conference sustainability science adaptive system theory amp development sustainable human

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Slide1

Complexity Theory: The Big Picture in Sustainability Science

Defining sustainable developmentSustainability : Defining sustainable development in broader termsSustainability Science: Criticisms of current approachesComplexity and complex adaptive systemsRelevance of complexity in a sustainability contextA systematic methodology for applying complexity theory in sustainability Complexity science tools for sustainabilityConclusion

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1

AgendaSlide2

Profile: Dr Fawehinmi

BDS (University of Lagos, Nigeria; 1983)MBA (University of Leicester, UK; 2010)Msc (Merit) Public Policy & Management ; University of London, 2011)Phd Candidate (Public Policy, De Montfort University, Leicester, UK) 2012-till dateICSD Conference 2015Degrees

Executive Education

MIT Sloan Executive Certificate in Leadership & Management; November

2014

Certificate in

Complexity Science;

Santa Fe Institute, New Mexico USA; March 2014Member of The New England Complex Systems Institute, Cambridge, Massachusetts, USA

2Slide3

Sustainability Science: Have we got it inside out?

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3Slide4

What is Sustainable Development?

The concept of Sustainable development according to Martens (2006) is messy ‘ because it is by nature complex, normative, subjective and ambiguous’Sustainable development is development which meets the needs of the present without compromising the ability of future generations to meet their own needs - Brutland Commission (WCED 1987) Robinson (2004) argues that this definition is vague, problematic and incomplete. His perspective privileges the term sustainability over the concept of sustainable development — in the conviction that:The term sustainable development, with its connotations of growth; preferred by governments and the organized private sector, as opposed to the term sustainability favoured by academics and NGO’s suggests an under-appreciation of environmental constraintsICSD Conference 2015

4Slide5

Sustainability: A Wider Definition of Sustainable Development

5Robinson’s (2004) definition of the concept of sustainability is based on ecological/environmental, economic and social imperativesEcological Imperative: To maintain the biophysical carrying capacity of the planet Economic Imperative: To provides an adequate material standard of living of all Social Imperative: To provide systems of governance that propagate the values that people want to live by

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5Slide6

Sustainability Science :The Challenges

Sustainability science ambitiously aspires to address a range of human-nature challenges disaggregated as:ICSD Conference 2015

Energy crises

Population growth

Health care concerns

Food and security issuesResources production and

management

The environment and climate change

Impact on pollution on health

Ecosystem protection

Biodiversity protectionGlobal economic & financial risks

6Slide7

Criticisms of Sustainability Science

(1) Current approaches to sustainability science have been criticised as being too siloed(2) Sustainability scientists have been charged with approaching sustainability from a premise of inadequate understanding of the complex dynamics of human –environment systemsAccording to Carpenter (2009) : ‘The gaps in knowledge that exists today cannot be addressed through uncoordinated studies of individual components by isolated traditional disciplines’To address these deficiencies, calls are growing for a robust conceptual framework for sustainability science based on an understanding of the phenomenon of complex adaptive systems ― with complexity theory as its theoretical backbone. ICSD Conference 2015

7Slide8

What is Complexity?

Complexity according to Fernando, S.V (1990) is better explained than defined.Sage (2004) suggests that a system can be described as complex: ‘ when we cannot understand it through simple cause-and-effect relationships or other standard methods of system analysis. In a complex system, we cannot reduce the interplay of individual elements to the study of each of them in isolation. Often several different models of the complete system, each at a different level of abstraction are needed ’ ICSD Conference 2015

8Slide9

‘’ I think the next century will be the century of complexity‘‘

— Stephen Hawking, 2000

Complexity Science: The Clarion call

Source

: ladypushing80wordpress.com,

mylovelyquotes.com

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9Slide10

Complexity Science: The Trailblazers (1940’s —

50’s)

Cybernetics

- Mathematics

Source

: math.tufts.edu, blogerma.ru, optimizacionlinealsergioblogspots.com

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Norbet

Wiener

W Ross Ashby

Ludwig von

Bertalanffy

Systems Biology & Systems Theory Founder

Cybernetics of the Mind

10Slide11

Challenges of Defining Complexity: A Chinese Box Phenomenon

A generally accepted definition of complexity is elusive because of the phenomenon’s wide scope and variabilityAll proposed definitions suffer from incompletenessPer Bak (1996) has referred to complexity as a Chinese box with surprises in each boxA plethora of definitions of complexity have been proposed focusing on System sizeEntropyAlgorithmic information content (AIC)Logical depth Thermodynamic depthFractal dimensionComputational capacity Statistical complexity Degree of hierarchy

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11Slide12

A Broad Definition of Complexity (I)

Goldin & Mariathasan (2014) have suggested that there are three levels of complexity; each with its own characteristic featuresThe three levels are: Small-tent Complexity ― Often referred to as the Santa Fe complexity. Its features include:

Locally interacting agents

No central/global controller

Cross-cutting hierarchical organization

Continual adaptation

Perpetual novelty

Little tendency to global equilibrium

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12Slide13

A Broad Definition of Complexity (II)

Big-tent Complexity — this is broader in scope. It’s features includes: Small - tent complexity as described above Cybernetics Catastrophe theory Chaos theory Meta- Complexity Includes every other definition (the 45 definitions catalogued by Seth Lloyd) and in theory can cover several distinct definitions Goldin & Mariathasan, The Butterfly Effect: How Globalization creates Systemic Risks and What to do about it (2014) Princeton University Press.

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13Slide14

Characteristics of Complex [Adaptive] Systems (I)

In complexity science, the distinction is often made between complex systems that are intelligent and capable of adapting to their environment and non- adaptive systems. In sustainability science, our particular interest is in complex adaptive systems; which exhibit the following characteristics:Adaptability: Agents interact and change their behaviour in reaction to the behaviour of other agents Emergence: System exhibits patterns of continuous unpredictable novelty. A ‘’process whereby the global system results from the actions and interaction of agents ‘’(Sawyer; 2005) Self-organized criticality/Phase transition: The concept describes a self-organizational mechanism of abrupt transitions in large scale systems that may be triggered by small events (earthquakes, stock market crashes avalanches etc). ‘’The Sandpile metaphor’’

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14Slide15

Characteristics of Complex [

Adaptive] Systems (II)Chaos: Complex systems exhibit constantly changing hard to predict behaviour[chaotic dynamics].The defining feature of such a system is ‘’sensitive dependence on initial conditions’’. A classic [metaphoric] example of sensitivity to initial conditions is the ‘’ butterfly effect ‘’ ― the action of a butterfly flapping its wings somewhere on the planet resulting in a hurricane elsewhere. Order,(due to an underlying attractor) is often seen in chaotic systems. This chaotic effect has been mathematically proven Non–linearity: Due to positive and negative feedbacks in combination, Complex systems processes are not linear ―causality is not proportional to effect. Effects may be larger than causes. Power laws: Complex systems sometimes exhibit probability distributions that obey a decreasing mathematical function known as a power law. The probability of events such as earthquakes, floods storms follow power laws. ICSD Conference 2015

15Slide16

Complex Systems: Self Organization, Emergence & Adaptive Behaviour

Source

: en.wikipedia.org

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16Slide17

Emergence in C

omplex Systems

Source: http://www.tcd.ie/futurecities/research/energy/adaptations-complex-systems.php

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17Slide18

Complexity theory & Science: The Opinion Camps

Chambers (1997) has identified three well delineated academic camps of opinion regarding the question of complexity theory being a paradigm shift or not.The Champions : Who are strongly persuaded by the ideas of complexity theory offering deep paradigmatic insightThe Pragmatists: Who think complexity offers interesting and useful parallels and are ready to embrace its potential for social sciences and human organization The Critics: Who see complexity in the light of an insignificant coincidence ICSD Conference 2015

18Slide19

Complexity Science: Relevance to Sustainability

Fedrof , N (2013) in a clear advocacy for a complexity science approach to sustainability posited that: ‘ The earth and its inhabitants are the most complex system we know but we don’t yet have either a theory of complexity or an experimental approach to manage this system — our global system wisely ’ Seidler & Bawa (2004) summoned the association between complex adaptive systems and coupled human systems remarking that:‘ Most of the challenging questions today are posed in contexts that meet the criteria for so called complex adaptive systems. These criteria include extensive interaction of and aggregation of diverse components, adaptation, non-linearities, emergent properties, amplifier effects ’

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19Slide20

Sustainability: Examples of Complex adaptive Coupled Human systems

Emergent phenomena – a hallmark characteristic of complex adaptive systems is observed across a spectrum of coupled human-environmental systems. Such as:EconomiesFinancial MarketsCitiesEcosystemsThe BiosphereWeatherHealth Systems ICSD Conference 2015

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Applying Complexity in Sustainability

Andries et al (2009) have offered a systematic methodology for applying complexity thinking in sustainability based on four themes as the basis of application.Characterise and Understand Complex Human –Environment Systems (HESs)Develop typologies of classes of HESs’ and match classes with properties Understand Local Adaptive responses and Global consequences Decision makers need to predict global effects better and avoid basing decisions/plans on local situations and short time scales Characterise Trade-Off’s in HESs Understand making environment/development trade-offs is critical to producing better sustainability outcomes Disciplines and Methods RequiredIntegration of theoretical and modelling predictions of complex adaptive systems with empirical evidence from actual human environment systems

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21Slide22

Complexity Science Tools for Sustainabilty

ScienceThrough advances in computing and simulations, complexity science provides powerful decision support tools for sustainability.Two promising approaches are :ICSD Conference 2015

Agent-based modelling(ABM)

Network Analyses

Well suited for :

Representing social interactions and autonomous behaviours

Studying the environmental impact at different scales

For studying the emergence of adaptive response to changing environment and environmental policies

Social network analyses can help reveal the characteristics of individual actors and the dynamic modification of their behaviours over time

22Slide23

Explaining Agent Based Modelling

Agent-based Simulation is a New Field Grounded in the Biological, Social, and Other SciencesWhat is an agent?A discrete entity with its own goals and behavioursAutonomous, with a capability to adapt and modify its behavioursAssumptionsSome key aspect of behaviours can be described. Mechanisms by which agents interact can be described.Complex social processes and a system can be built “from the bottom up.”ExamplesPeople, groups, organizationsSocial insects, swarms–Robots, systems of collaborating robots Agents are diverse and

heterogeneous ―Macal, C.M & North,M.J (2006) Argonne National Labs

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