Application of ABM to NRM

2.5.5.1. Social-ecological systems research

The application of agent-based modelling to social-ecological systems is founded in the ability of ABM to facilitate investigation and better understanding of the consequences of decisions in complex systems (Smajgl et al., 2011). Early work by Costanza et al. (1993) noted that both ecological and economic systems exhibit characteristics of complexity and their interconnection requires synthesised and integrated study. Modelling offers a way to comprehend and explore the holism of human-environment systems, particularly through the coupling of environmental models to the social systems that are embedded in them (Hare and Deadman, 2004). Schlüter and Pahl-Wostl (2007)claim that ABMs are particularly well-suited to the analysis of complex human-environment interactions in the context of management (Janssen, 2002; Barreteau et al., 2003;

Gotts et al., 2003; Bousquet and Le Page, 2004; Jannsen and Ostrom, 2006) as ABMs explicitly take consideration of changes in the behaviour and actions of individual entities in response to perceptions of change in the natural or social environment. ABM also allows the study of interactions between different scales of decision-maker and the emergence of collective responses to the changing environment and environmental policies (Hare and Deadman, 2004). The application of ABM to ecosystem or NRM has grown out of the study of ecological (e.g.Drogoul, 1993) and social systems using ABM (e.g. Doran and Gilbert, 1994), which have since been able to be combined into one modelling system, so as to explore the interactions, where ABM can facilitate the combination of multiple hierarchies, scales and interactions.

Early work on the application of multi-agent systems through agent-based modelling to social-ecological management systems was begun by Lansing and Kremer (1993) whose study of Balinese techniques of water sharing and irrigation amongst farmers investigated complex coordination and collective problem-solving through the exploration of simple local rules used for individual community’s decision-making. Other early studies included Bousquet et al. (1993) who use simulation modelling as a discussion tool to investigate space sharing rules and the evolution of an ecological equilibrium in fisheries management; Janssen and Carpenter (1999) who created a model of the management of lake eutrophication used to explore the interactions between the lake and social systems, to better understand resilience of lakes. Bousquet and Le Page (2004) and Hare and Deadman (2004) give good overviews of the evolution of the use of ABM in environmental management research, concluding with a demonstration of the benefits of using ABM to combine interdisciplinary studies of society and environmental systems, but with a need to focus on targeted ABM design to ensure it meets the modelling requirements of the problem its designed to tackle.

72 The important aspect of ABMs in natural-resource management research is their ability to experiment with hypotheses about the way that systems could, might, should and have worked, focusing on the mechanisms and intricacies of behaviour and environmental response feedbacks in order to build understanding. More recent applications of ABMs to social-ecological systems research have focused on governance and the way that it is operationalised through behavioural rules and interactions amongst stakeholders. Studies have picked up on aspects such as learning, social networks and structural interactions in an attempt to better understand the complexities.

For example Agrawal et al. (2013) use ABM in a study of common-pool resource governance, looking at the way that formal governance such as written rules, organisational forms and hierarchical decision-making interact with informal social networks and social norms around the extraction of firewood. They draw on ideas such as Tompkins and Adger (2004) whose work looking at the effect of the consolidation of networks on ecosystem resilience, in order to experiment with thinking about the information networks that surround natural resource use in resource dependent communities and countries. Their study particularly focuses on contexts where governments may be decentralising resource management and trying to create new institutions amongst the already established norms and rules of social networks. Agrawal et al.

(2013) were able to make conclusions about the effectiveness of organisations through the use of an ABM that allowed the authors to test the effects of specific variables and their interactions in a precise and systematic manner.

Watkins et al. (2013) also focus on the mechanisms, interactions and structures within governance approaches. They examine the structural and behaviour factors that might influence decision-making when restoring an ecosystem, using the example of the Chicago Wilderness.

Characteristics such as “the number of actors and groups involved in decision making; the frequency and type of interactions among actors; the initial setup of positions and respect; outside information; and entrenchment and cost of dissent” (Watkins et al., 2013:34) are used to experiment in an ABM with the way groups converge towards a collective position through particular decision-strategies. The role of the ABM is to help suggest the conditions in which specific decision-strategies are activated and to suggest new directions for additional empirical research, particularly about the role of leaders in facilitating the consideration of multiple perspectives and to explore the potential effects on biodiversity outcomes. The role of the ABM process as a support for building further understanding rather than as confirmation of any one truth is emphasised. Studies such as Martin and Schlüter (2015) have more recently emphasised the need to consider combining ABM with other forms of understanding such as system dynamics to allow ABM to be even more effective in building understandings by better recognising the diversity of modelling paradigms, spatial and temporal scales and data availabilities that are often combined in a modelling process. The hybridisation is argued to be able to unpack

social-73 ecological system complexity to better analyse interactions between ecological dynamics and micro-level human actions through ABMs.

2.5.5.2. Participatory ABM

A significant mode of use of ABMs in social-ecological research has been through participatory modelling. Participatory modelling is a process that involves the participation and contribution of those whose behaviour is represented in the model, and who might later use the model for decision-making and strategic planning (Pahl-Wostl, 2002c). There have been approaches to technical environmental model creation that involve the participation of stakeholder groups, for example the seminal work on flood-risk modelling of, for example, Lane et al. (2011b) and Landstom et al. (2011), where scientists repositioned themselves in relation to modelling practices in order to unravel expertise and create new connections and knowledge about the flood risk environment by working across certified experts and non-certified experts (local people), resulting in the creation of a new computer model. Whilst this process helped to hybridise science and politics, bringing diverse knowledges together means its method is intensive and not often used.

Other forms of participatory modelling have developed for their ease of application, as well as for their facilitation of learning and reflection on goals, beliefs and perspectives amongst participants to create a model that is agreed upon and that synthesises the perspectives of those involved, facilitating discussions rather than providing answers. In relation to social-ecological systems, Companion Modelling (Bousquet et al., 1996; Barreteau et al., 1997; Étienne, 2014) is a specific methodology developed around the representation of social-ecological problem situations involving the participation of those involved in the system in a modelling process and is applied to a variety of resource-management situations (e.g. Trebuil et al., 2002; Pahl-Wostl and Hare, 2004; Dray et al., 2006; Garcıa-Barriosa et al., 2008; Abrami et al., 2012; Cleland et al., 2012; Étienne, 2014).

Many of the underpinning ideas of participatory ABM are influential in conceptualising social-ecological resource management contexts, the role of stakeholders, and the potential role of modelling. Therefore although a participatory element will not be explicitly applied in this research, some of the lessons are important to reflect on. In particular it is acknowledged in this research (as it is in a Companion Modelling approach) that every stakeholder in a system has their own perspective and mental model of a situation (Lynam et al., 2012) and it is important to understand and integrate the variety of perspectives when trying to understand complexity.

Equally, in contexts of decentralisation and changing governance (which is happening in the UK

74 currently within water-resource governance) the process of modelling is seen to be important for experimenting with management behaviours and scenarios to potentially contribute to future practice. Modelling can also contribute to a process of evaluation and learning that inevitably comes with new governance and may help begin to hypothesise the connection between management and governance contexts. The prevalence of water management issues in studies using modelling and participatory modelling also demonstrates the interest and suitability of modelling to water management issues and encourages further exploration of different types of water management issues using the benefits of ABM modelling.

2.5.5.3. Water resource research

Although ABMs of social-ecological systems cover a wide variety of topics, one of the most popular applications, both through participatory and non-participatory modelling is to water resource management. Izquierdo et al. (2003) claims that ABM is particularly appropriate to address integrated water-management issues in particular due to:

 The importance of heterogeneity among agents (Axtell, 2000)

 The importance of adaptation (at appropriator and resource management levels)

 The crucial role of the geography of the physical space concerned

 The significance of social networks (often spatially structured)

 The importance of addressing the relationship between the attributes and behaviour of individuals (the ‘micro’ level) and the global properties of social groups (the ‘macro’ level) (Gilbert and Triotzsch, 2003)

The spatial scale of water-resource management and the nature of interactions across sectors, communities and landscapes means that a mode of analysis and exploration that brings together the heterogeneous elements is advantageous. ABM can fulfil that function in multiple ways and is a growing tool for research around water management.

Table 2.1 lists a number of studies that have used ABM to better understand issues surrounding water management, where a non-participatory process of model creation informed a process of learning and reflection of complexities of each of the systems. There are a variety of themes, locations and scales covered by the studies, demonstrating the ability of ABM to be a useful tool in many areas.

75 The scale and scope of ABM use in water-management studies is broad and does not seem to be restricted to particular times or places, but is always in contexts where there are a variety of stakeholders interacting with each other and with the water and land environments, often with competing or conflicting interests and approaches. It seems that modelling is also used in contexts where there is a need for or external demand for a change in practice, perhaps through governance change or based on environmental or social pressures. The variety of contexts and the flexibility of modelling approaches shows the diversity of the mode of ABM to aid exploration of social-ecological systems, particularly in water management where ABM is arguably well suited to representing the complexity of agents and environmental interactions.

Amongst the studies of water management and ABM there are very few studies using ABM around water management in the UK. There are studies of applications of ABM across other European countries, including Spain, Switzerland and France, including companion modelling approaches. In the UK there are a few studies utilising ABM for analysis of flood-risk management (e.g. Dawson et al., 2011; Jenkins et al., 2016; Dubbelboer et al., 2017) and Izquierdo et al. (2003) used ABM in the FEARLUS-W model applied to a Scottish catchment with reference to the legislative context created by the WFD and the subsequent need to understand behaviours around land management in relation to water management. There are very few studies focused on UK catchments using ABM and none, as far as the scope of this study is aware, on the current governance context of the CaBA. There is an opportunity to experiment with the use of ABM as a heuristic device to explore aspects of water management in a UK context, which this PhD research aims to do in relation to understandings of the system as networked and as complex.

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Scale Description and findings

Becu et

 Model is a coupled biophysical and social model (including factors of water balance, irrigation, crop and vegetation dynamics, and water, land, cash, labour as social dynamics)

 Elements include farmers, crops, rivers and villages

 Measure crop choices and distribution of water and cash throughout the catchment

 The model results could be used to help tackle changes brought about by decentralisation and to explore the consequences of alternative management options

 Agents represent water use sectors including agriculture, forestry, mining and industry, rural and urban alongside the Catchment Management Agency who make decisions based on feedbacks with the water environment

 Experiments investigate how 1) agents' selection of different indicators to evaluate their actions, and 2) different social-ecological conditions affect understanding of how and what to learn, willingness to learn, and capacity to learn.

China Urban  Calibrated against residential water use data in Beijing city over 15 years based on municipal statistical, government planning, social and market survey data.

 Three types of agents - regulator, water appliance market and households

 Model can act as a tool to highlight the areas of domestic water use that might benefit from interventions

2. Understanding NRM: Approaches and conceptualisations

Table 2.2 Studies using ABM in water management.

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Spain Urban  Consists of a GIS environment characterised by social and economic features, and family units within the environment.

 Factors affecting consumption such as type of urban area, price, socio-cultural perceptions, technological adoption are included

 The ABM is combined with scenario analysis

 Model results are able to provide managers with new insights into the complex issues that characterise water management and influence patterns of water demand

 Use of the FEARLUS model to develop scenarios of possible futures for the catchment with attention to phosphate pollution

 Land managers choose land use options

 Factors like social approval and economic returns incorporated into land managers decision making

 Factors such as water course morphology and hydrological connectivity are incorporated

 Focus on the spatial dynamics of the resource and how the structure of social networks affect pollution between water culture, water policy and autonomous actor behaviour

 Based in participatory modelling and companion modelling

 Use a pressure, state, impact, response concept

 Model could be used to analyse some of the drivers of social change

 Model constitutes a lens to observe the interaction processes observed by game play

77 2. Understanding NRM: Approaches and conceptualisations

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Urban  Consumer behaviours including ingestion, mobility, reduction of water demands, and word-of-mouth communication are included.

 Management strategies are evaluated, including opening hydrants to flush the contaminant and broadcasts.

 Able to experiment with developing rules to characterise the interactions among, utility operators, the media, public health and perpetrators to identify efficient strategies

basin  Three sub-systems – social, irrigation and aquatic

 Looking at the resilience of the different ways that a water system can be managed in relation to variability and uncertainty in water availability

 Comparing centralised and decentralised regimes

 Analysis of the systems can reveal structural features and rules that are important for understanding resilience and functioning of the system

Akhbari

 Based on conflict over water transfer in California

 The ABM proposed is intended to provide a tool that helps to find effective management scenarios to encourage conflicting parties to cooperate.

 agents are defined as a decision-making agent, the state; and demand agents:

water diversions/farmers (demanding for water), and the environmental sector (demanding for enough water flowing along the river with an acceptable quality).

2. Understanding NRM: Approaches and conceptualisations

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management

scenarios  Social and institutional enhancements such as incentives, penalties, new regulations, etc. were introduced to the ABM model as encouragement factors, yield objectives, investment and information sharing

 Test a number of water allocation rules and scenarios

 Model helped contribute to negotiations without being a tool for negotiations

 ABM very suitable for representing multiple and complex interactions between cognative agents (farmers and water supply agents) which are composed by complex knowledge modules and reactive agents (crops and climate agents).

 Authors would want to imporove the model by adding communication and validating the ideas against more detailed empirical observations

Barthel et state of resources and user demand

 Part of a bigger Danubia model which is run by very high level strategic decision makers.

 Its main aim is planning for worst case scenarios and interventions

 Seen as a set of ‘adjusting screws’ for the larger model because of its application to experimentation with decisions that inform plans and actions

 Aims to help water supply companies to identify critical regions for adaption under changing climatic conditions

 Model includes proactive deliberative agents

 Economic and social dynamics are represented through databases and additional rules

2. Understanding NRM: Approaches and conceptualisations

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higher levels of institutional capacity will lead to reduced levels of water conflict

hydrology to explore the societal effects of adding an additional institution to the existing water resources management institutions

River, Idaho, USA

 The models are run over historical and projected time periods, looking at different scenarios of variation in agent environment

 Model is able to identify critical elements of the design of

institutions, when considering their potential success in mitigating conflict

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2.6. Summary

This chapter has brought together and analysed scholarship from multiple disciplines, carving out an interdisciplinary perspective within which the research is situated. A perspective on collaborative water quality management and governance has been provided by bringing together an understanding of complexity and a systems perspective, through an understanding of networks and network analysis alongside the application of ABM to better understand dynamics. The studies and development of knowledge outlined in this chapter will form the background and basis for an analysis of catchment management processes and associated systems of governance.

The scholarship has highlighted the importance of stakeholders as points of agency in management systems and the focus of network analysis and rule creation for simulation modelling. As such, stakeholders are the main focus of data collection, whereby qualitative translation of experiences and knowledge through interviews is used to explore the themes identified in this chapter as important for the study of water resource management. Chapter 3 outlines the case study in which a system of management will be explored, and Chapter 4 outlines the processes of data collection through interviews, and data analysis through a network perspective and modelling approach, underpinned by the knowledge and ideas summarised in this chapter.

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