Complex Dynamical Systems Social-Ecological Systems

Dynamic system is a system whose behaviour changes over time. In a complex system, it is not easy to predict and describe the behaviour of that system from observing it (Sterman, 2000). Typically, a dynamic system is characterised by complexity as it integrally connects diverse knowledge of dynamically interdependent entities, also called components or parts, with one another (Sterman, 2000; Stylios & Groumpos, 2004). These dynamic components interact and are interrelated via many causal connections and negative and positive feedback effects to produce the dynamical behaviour of the systems. A positive feedback positively changes one component instigating a chain of effects that change other components of the system, while a negative feedback inhibits its behaviour and invokes corresponding changes in the downstream components (Marten, 2001). Due to these feedbacks, the current state of the system is influenced by the previous states of the system, and thus the behaviour of the system changes with time in a correlated manner. Furthermore, feedbacks loops make the system behave in a nonlinear manner in reaching its final state, whether stable or unstable.

A system that consists of interrelated components and displays features of nonlinear behaviour is considered an overlapping and coherent system, and it cannot be reduced into parts. Such systems require us to express, analyse and understand their behaviour as a whole system rather than a sum of the behaviours of its parts (Clayton & Radcliffe, 1996;

48 Juarrero, 2010; Stylios & Groumpos, 2004). This would produce complex systems that are not easy to demarcate (Juarrero, 2010), subject to possibilities of nonlinearity (Krasny et al., 2010) and result in imperfection of decision making (Carvalho & Tome, 2000). However, this points to the emergence of a great demand for a significant approach to deal with these intertwined systems as wholes rather than dealing with their reductive parts. Socio- ecological systems considered in this thesis are at the convergence of social systems and ecological systems. Therefore, holistic approaches to socio-ecological systems require understanding both these systems and their interplay.

A social system is 'an orderly and systematic arrangement of social interactions' (Neeraja, 2005). It consists of parts that interact with each other in different aspects of life to form a coherent whole (Parsons, 1975). The parts of the social system are coherent individuals (people) and everything related to them is interacted by a network of interactive, meaningful and interdependent relationships that shape their behaviours (Marten, 2001; Neeraja, 2005) (see Figure 2.8). The number of individuals in the social system can be any number more than two, for example from a small family to the entire population in the world (Marten, 2001). A dynamic social system is a complex system that may have complex interrelated components. A complex dynamical social system has negative and positive feedbacks that allow the system to change with social changes over time; however, despite these changes it typically does not lose its social equilibrium (Neeraja, 2005). That means, the social system is considered an adaptive system that has the flexibility to change in a way that maintains its existence and stability (Marten, 2001).

49 An ecological system or, in short, an ecosystem is a biological community in a particular area that describes the group of interactions among living organisms (humans, animals and plants) and between living organisms and their environment (water, climate and energy) (Campbell, 2008; Krebs, 2009; Marten, 2001; Schulze et al., 2005) (see Figure 2.9). An ecosystem can be of any size in terms of area, for example from a small land to the whole area of the world (Marten, 2001). An ecosystem thus comprises many parts (living and non- living) that are interacted via many strong to weak interdependent relationships (Hartvigsen et al., 1998). It also has negative and positive feedback effects. An ecosystem has the ability to change with changes over time without losing its existence and stability. For these reasons, it is, like a social system, considered a complex adaptive dynamical system (Marten, 2001).

Figure 2.9 A simple example of an ecosystem

If social systems and ecological systems are linked and integrated, they form social- ecological systems or socio-ecological systems. Socio-ecological systems model the interactions between human actions and components of the ecological systems, see Figure 2.10. The interaction dynamics here is interesting. On one hand, humans affect ecosystems through their actions to meet their societal needs. On the other hand, ecosystems satisfy humans’ need to connect with nature and life and affect changes in them (Marten, 2001). Socio-ecological systems are considered persuasive examples of complex dynamical systems that have many intertwined components or parts. All socio-ecological systems have nonlinear behaviour; they include many negative and positive feedback effects that produce complex changes in their behaviours that may still keep them in valid states unless extremes of behaviour or limits of the system are not reached.

50 Figure 2.10 An interaction between a social system and an ecosystem

In socio-ecological systems, humans interact with the components of the environment in reality; therefore, representing the aspects of reality and modelling and controlling these systems require, in addition to existing knowledge, taking advantage of human knowledge at all levels (Prell et al., 2007). Human thinking and reasoning are dominated by approximation rather than absoluteness in describing the knowledge and may vary in relation to time and space (Leon et al., 2010), and therefore, they produce ambiguous evaluations and uncertain data. Thus, an approach that mimics human thought and has the ability to cope with the ambiguity and uncertainty inherent in human reasoning is required.

Typically, socio-ecological systems include a variety of stakeholders (participants) with different knowledge and diverse worldviews that probably produce uncertainty and/or conflicting understandings and challenges. Integrating relevant stakeholder (lay and expert) knowledge and sharing their knowledge in modelling such systems would overcome these challenges and provide a comprehensive understanding and socially desirable outcomes and solutions (Ozesmi & Ozesmi, 2004; Prell et al., 2007; Walker et al., 2002). This necessitates a strong focus on a participatory approach that can address, model and combine various groups of stakeholders and consequently exploit stakeholder engagement in extracting the knowledge of individuals and/or groups.

Several quantitative approaches such as mathematical models, game theory etc. have proved their effectiveness in modelling many complex systems. However, these approaches have had limited success in handling and capturing knowledge of significance to systems

51 such as socio-ecological systems that embed interconnected parts, feedbacks, nonlinear behaviour, complexity, uncertain data and participatory issues (Kosko, 1992b; Ozesmi & Ozesmi, 2004; Zadeh, 1994). In such systems, hard computing approaches are difficult, costly or even impossible (Carvalho & Tome, 2000; Zadeh, 1994). In contrast, soft computing approaches based on fuzzy logic have the freedom and flexibility to model such systems. FCM is a qualitative and network approach that has the ability to represent and address the aforementioned complex issues.

FCM approach is a causal system that incorporates fuzzy logic, allows feedbacks, exploits human knowledge and experiences , describes the behaviour of different components of the system and connections among them, draws a causal representation of the whole system behaviour in a symbolic manner using a directed graph, and helps in decision making (Kosko, 1986a; Papageorgiou & Stylios, 2008). The research in this thesis proposes to enhance the efficiency and representativeness of the soft computing approach of FCM to model any complex dynamical system that consists of interrelated components that interact with positive and/or negative casual connections. The proposed enhancements of FCM approach are through new fuzzy representation and aggregation methods, a proper semi-quantitative condensation method, and novel methods for determining centrality measures and credibility weights for FCMs and their variables.

A problem such as "Water Scarcity Problem in Jordan" can be considered a strong representative of a social-ecological system. It is one of the most critical problems that concern all people in the country and is associated with the most vital element in life, water. Figure 2.11 represents the components of the social system and ecosystem of this system as modelled by the FCM in Figure 2.2. The Figure illustrates positive (green arrow) and negative (red arrow) connections between the components of the two systems and among the components of each system. Due to these connections, negative and positive feedback effects are produced. These feedbacks in turn make the system display nonlinear behaviour. The interactions from the components of the social system to those of the ecosystem represent human activities and actions such as water projects, management, community participation, etc. On the other side, the interactions from the components of the ecosystem to those of the social system represent responses to human activities and actions such as changes in water situation, resources and demand.

52 Figure 2.11 A socio-ecological system representation of water scarcity situation in Jordan based

on the FCM in Figure 2.2; the figure shows how much the components of the system are interconnected and mutually dependent

Despite these complicated overlapping interactions and ensuing system changes, the system, at the end, may settle on a state of social equilibrium. FCM can perfectly address and model this system and determine its new state every time the system undergoes change. In this research, this complex dynamical system is investigated using the advantages of the enhanced FCM approach based on exploitation of the knowledge from different stakeholder perceptions depicting different levels of experience in describing the system. And beyond this investigation, this research offers an opportunity to provide useful knowledge and suggestions that could improve the current stressful situation of water in Jordan. The following section discusses the methods used by the research for enhancing the FCM approach, as well as how these methods can be used to promote addressing socio- ecological systems leading to more beneficial outcomes than are currently possible.