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108 Seiten, Note: 1,3
List of Figures, Tables and Graphs
1.1 State of Research
1.2 Theoretical Framework and Conceptualization
1.2.1 Governance in Social-Ecological Systems
1.2.2 Vulnerability and Adaptation to External Stressors
1.2.3 Collective Learning Processes in Social-Ecological Systems
1.3 Research Design and Methodology
1.4 Case Study Selection
1.4.1 Why Study Floods in Developing Countries?
1.4.2 Comparative Method and Case-Studies
2 Case Study of Bangladesh
2.1 Parameters of Flood and Disaster Management
2.1.1 Political Transition and the Governance of Flood Management
2.1.2 Complexity of Flood Disasters and Vulnerability
2.2 Learning Processes in the Governance of Flood Management before 1988 until Recently
2.2.1 Development Prior to
2.2.2 Changes after the Floods of
2.2.3 Changes after the Floods of
2.3 Collective Learning Processes in the Governance of Flood and Disaster Management in Bangladesh
3 The Case Study of Pakistan
3.1 Parameters of Flood and Disaster Management
3.1.1 Political Transition and Flood Management
3.1.2 Complexity of Flood Disasters and Vulnerability
3.2 Learning Processes in the Governance of Flood Management after
3.2.1 Development in the Flood and Disaster Management after
3.2.2 The Floods of 2010 and their Aftermath
3.3 Collective Learning Processes in the Governance of Flood and Disaster Management in Pakistan
4.1 Collective Learning in Flood and Disaster Management: A Comparison
4.2 Summary of Findings
4.2.1 First Research Question
4.2.2 Second Research Question
4.3 Limitations and Outlook
The prospects that global climate change will have adverse effects on human societies opened up a discourse about how adaptation should be managed. In order to finance adap- tation measures, the parties of the Kyoto Protocol recently established the Adaptation Fund in 2007. In view of the limited resources that are available for adaptation, scales for the prioritization of countries according to their suspected vulnerability have been developed in the literature. Indicators of vulnerability highlighted within this literature, only reflect the indicators of human development and therefore fail to capture the complex structures of vulnerability. The collective learning approach assumes that vulnerability can be signifi- cantly decreased when governance systems adapt to external changes through collective learning processes. The present thesis connects to this notion and therefore assesses the influence of collective learning processes on the vulnerability of the Bangladeshi and Pa- kistani society towards flood hazards. It does so in order to find a determinant of vulnera- bility that is able to capture its complexity. Following a case study comparison that is based on a systematic research on primary and secondary literature this study reconfirms that vulnerability can substantially be decreased in the presence of collective learning processes.
illustration not visible in this excerpt
Table 1 Definitions in the Concept of Triple-Loop Learning
Table 2 Institutional Changes in Governance Systems
Table 3 Changes in Actor Networks in Governance Systems
Table 4 Changes in Multi-Level Interactions in Governance Systems
Table 5 Changes in Governance Modes in Governance Systems
Table 6 Changing Concepts of Uncertainty
Table 7 Major Keywords Categorized by Stage of Research
Table 8 Mill’s Design of Difference
Table 9 Collective Learning Patterns in Bangladesh and Pakistan
Figure 1 Scheme of an Adaptation Process
Graph 1 Physical Exposure and Relative Vulnerability to Floods in South Asia
Graph 2 HDI of Bangladesh and Pakistan by comparison from 1980-2010
When exceptionally heavy monsoon rains led to rapidly increasing water levels of the Pa- kistani Indus River and its tributaries in late July 2010 not a single town hit by the torrents was adequately prepared or even warned despite the presence of information that was giv- en to government officials (Webster et al. 2011; Vastag 2011). The severe unpreparedness of the affected areas is mainly reflected in the numbers of human losses of nearly two thousand but also the number of affected people with over twenty million being directly affected by the floodwater, including displaced and injured people (CRED 2009).
Natural disasters like the Indus River Floods are very complex phenomena that result from a variety of determinants including human as well as natural impacts (Wisner et al. 2003). Climate change is supposed to have a significant influence on hydrological natural disasters in present and near future (IPCC 2007). Though climate change does not change the ways that natural disasters like floods occur, it acts as a catalyst aggravating existing problems (Ibid. 2007: 361). If climate change is not creating any unknown problems, one might ask, why should one start conducting research in fields that have been subject to detailed research for a long time previously? The answer can partly be found within the first paragraph of this introduction: Even though what can be observed stays the same, changes in the patterns and impact of climate change-related events occur at the present time and are predicted to intensify in the course of time. These changing patterns result in very high levels of uncertainty for policy-makers and societies, which potentially can lead to enormous devastation if they are ignored.
General awareness about the severe impacts of disasters on human development has been raised especially on the international level like within the framework of the Millen- nium Development Goals. Based on the heightened awareness about risks, steps towards risk reduction have been initiated on an international and a national level. Consequently, in the year 2000 the United Nations International Strategy on Disaster Reduction (UNISDR) was established with the mandate to improve coordination of disaster reduction. On a na- tional level disaster risk was incorporated into Poverty Reduction Strategy Papers in order to ensure sustainable development (UNDP 2004). Also in academic circles for many years, research has been conducted on the subject of disaster risk reduction. This lead to an ad- vanced understanding of how various types of natural hazards can interact with societies (Mercer 2010; Wisner et al. 2003). Or rather, how disasters are getting constructed by hu- mans that modify their environment.
Within the past two decades, climate change became a broadly discussed issue within the discourse on disaster reduction of practitioners and academics (cf. UNISDR 2008; Mercer 2007). Besides efforts at mitigation, adaptation to climate change became a very relevant subject of concern. In order to adapt to the prospective and ongoing impacts of climate change at the international level, relevant instruments have been set up recently. The Adaptation Fund set up under the United Nations Framework Convention on Climate Change (UNFCCC) is one example of these instruments, whose major objective is to sup- port programs and projects in member countries “that are particularly vulnerable to the adverse effects of climate change” (UNFCCC 2011). Vulnerability and risk assessments are therefore seen as important factors determining the prioritization of different countries or regions in order to support their adaptation measures (Adger et al. 2004:15)
Recently, studies in the climate change adaptation and disaster risk literature have been conducted in order to make countries comparable with regard to their vulnerability to external hazards (cf. Adger et al. 2004; UNDP 2004; Brooks et al. 2005). A variety of so- cial, political, economic and hazard-specific indicators have been identified in these studies in order to build foundations of a vulnerability or risk index. Adger, Brooks, Bentham and Eriksen conclude in their assessment that the identified indicators of vulnerability “ [ … ] might be of use to international agencies and donors wishing to pri- oritise adaptation assistance to the most vulnerable nations, but it tells us nothing about the structure and causes of vulnerability. ” (Ibid. 2004: 93).
The need to develop and test further determinants of vulnerability, which are able to capture its complexity, was therefore addressed by some authors (e.g. Adger et al. 2004: 101; UNDP 2004: 115-16).
It is therefore the aim of the present thesis to make a contribution in order to address the currently existing gap in the knowledge about determinants of vulnerability. For this purpose, the influence of a more complex determinant on the vulnerability of a society on national level was tested. In order to deepen the insight into a specific field of disaster risk and delimit the scope of this paper, a specific hazard was chosen. Thus, floods were chosen to be the major subject to this investigation because flood hazards are very complex phe- nomena that are largely influenced by the interaction of humans with their environment. Furthermore, floods are a typical hydrological hazard that is expected to be increased by climate change through extreme precipitation and stronger seasonal melt of glaciers (IPCC 2007).
In the course of investigating for a determinant that is eligible to capture broader complexity of vulnerability, a side observation gave the decisive impulse. A quantitative research study conducted by the United Nations Development Programme (UNDP) on the vulnerability of different countries to flood hazards, revealed a rather counter-intuitive re- sult: In four world regions there exists a trend stating that the higher a society’s physical exposure1 to flood hazard is the lower tends to be its relative vulnerability2 (UNDP 2004; Graph 1). A similar trend is getting visible when holding the annual numbers of floods against the relative vulnerability between countries of one region. The hazard frequency and magnitude as external factors therefore seem to have an influence on the relative vul- nerability to floods. The context described in this section reminds of learning patterns in such a way that increasing repetition and intensity of an external stress3 potentially ad- vances the reaction of a system to this external stressor. Further support of the assumption that learning is an important determinant of vulnerability was found in theoretic approach- es of complex adaptive systems and collective learning processes and their influence on adaptation (cf. Duit and Galaz 2008; Pahl-Wostl 2009; Duit et al. 2010; Loef 2010; Gerlak and Heikkila 2011). Even though there is a majority in the academic literature, which sup- ports that learning processes in theory have a significant impact on the vulnerability of a society, empirical studies in this field are still rare or underway (cf. Pahl-Wostl 2009; Si- monsen 2010). The present thesis therefore aims to diminish gaps within this field of study.
The determinant of vulnerability that was chosen for further investigation within the present thesis will therefore be collective learning processes. The guiding research ques- tions are therefore: Do collective learning processes have a detectable influence on the vulnerability of a society to hazards? And subsequently: How did collective learning processes in Bangladesh and Pakistan influence the vulnerability of their respective socie- ties to flood hazards? In order to find answers to these questions the present thesis will proceed in a four-step manner.
Firstly, a review of the current state of literature on climate adaptation and disaster risk builds a base in order to classify the present analysis and therefore defining its scope. In line with this classification a theoretical framework was developed in order to further enhance the research scope and to conceptualize and define important key components of adaptation and learning. This step comprises of the first two subsections.
Secondly, the conceptualization made was used in order to determine the methods of the core analysis. In order to assess the influence of learning processes on vulnerability a mixed research design was established. Collective learning processes contain very complex interactions and therefore it is not feasible to analyze them thoroughly based on sets of quantitative indicators. Vulnerability on the contrary can be measured by quantitative indi- cators human physical security. The present analysis is therefore composed out of a qualit- ative research about collective learning processes that is connected to a qualitative assess- ment of vulnerability (cf. Creswell 2009). In order to make informed statements about the influence of collective learning processes on vulnerability two case studies have been cho- sen that are compared following the example of Mill’s Design of Difference (Ibid. 2009  ). The aim of this comparative method is to proof that higher vulnerability is con- nected to lower levels of collective learning. Major obstacle in this comparison was the identification of interfering variables, which had to be controlled. Collective learning processes on national level demand long periods of time and therefore can only be captured using information and data over extended time scales. In order to capture collective learn- ing processes an ex-post research was conducted that covers the major developments in the governance of flood and disaster management of the two case studies from the early 1900s. This research was done based on a review of existing primary and secondary literature in- cluding majorly field studies, sector studies, policy studies, reports and legal documents. In order to systematize the information gathered and to identify learning processes within the case studies a research framework developed by Claudia Pahl Wostl (2010) in the water management literature was considered.
The third step includes the actual analysis based on the previously outlined research design. The case studies of Bangladesh and Pakistan were chosen under defined criterion oriented towards Mill’s Design of Difference (Ibid. 2009  ) and firstly analyzed sepa- rately. Analyzing both case studies separately has the advantage that learning processes can be illustrated in a comprehensive manner. The disadvantage of this design draws clear- ly from the risk of falling into narrative analysis. In order to avoid this, the case studies already include cross references.
Lastly, the knowledge acquired about collective learning processes in the flood and disaster development of Bangladesh and Pakistan will be used to do a final comparison in order to draw conclusions on whether learning processes influenced the vulnerability of the populations in both countries. Furthermore, the question of how vulnerability and collective learning processes are related to each other will be discussed.
Since the early seventies increasing attention is being focused on the subject of climate change in the scientific world, leading to the first World Climate Conference by the World Meteorological Organization (WMO) in 1979. A long period of controversy, primarily led by the IPCC and skeptics, about the existence of global climatic change and the degree of influence by human activities, started during the intervening years. In 2005 the Kyoto Pro- tocol entered into force, indicating that a vast majority of countries consent on the ac- knowledgement of global climate change as an impact of human activities. The Fourth Assessment Report of the IPCC in 2007 reconfirms this consent and draws a sophisticated picture of observations of impacts that can be drawn back to climatic changes.
Parallel to a growing awareness and recognition of climate change and its mitigation, the problem of adaptation aroused attention since the early nineties. During this period of time, the IPCC started addressing the importance of adaptation until it was considered a priority area for research in the Third Assessment Report in 2001. Literature on climate change adaptation and its impact on vulnerability had been strongly increasing ever since.
The complexity of adaptation to climate change becomes apparent when scrutinizing its major fields of study like the physical science base of climate change, environmental governance systems, structures and determinants of adaptation processes and vulnerability or disaster risk management. Considering that this list is still only a rough picture of all components, clear systematizations and definitions are a crucial part of any study con- ducted in this field. The present thesis does not discuss the physical science base, but cov- ers all of the other areas mentioned above to different extents. It will therefore be based on the theorization of adaptation and governance, vulnerability and adaptive capacity while applying these underlying concepts to hazard-specific disaster risk management.
Out of the variety of literature on adaptation, vulnerability, resilience or adaptive ca- pacity4 derives a vast amount of definitions that often cover different concepts with similar terminology. Most of these differences in meanings exist because terms are used context- specific and sometimes authors do not explicitly refer to other uses of the term in order to differentiate their own concepts from others. If unnoticed by the reader this variety of meanings can cause confusion and misinterpretations.
An illustrative example for this ambiguity is the use of the term adaptive capacity, a very often used term within the adaptation literature. Whereas the practically-oriented adaptation literature5 (e.g. Smit and Wandel 2006; Handmer 2003; IPCC 2001) stresses materialistic capacities to adapt in their definition, theoretically-oriented adaptation litera- ture6 (Pahl-Wostl 2009; Armitage et al. 2010; Diduck 2010) tends to stress the ability to adapt by itself. Also there exists a mélange out of both streams defining adaptive capacity as “ the ability or capacity of a system to modify or change its characteristics or behavior so as to cope better with existing or anticipated external stresses. ” (Adger et al. 2004: 34). Again, the use of many terms in adaptation literature is very context-specific and should always be considered in this way.
In order to reduce complexity and enhance transparency in the adaptation literature, a number of authors developed typologies sorting literature by purpose, research design or other criteria. Smit and Wandel (2006) distinguish four types of climate change adaptation literature according to their purpose: measuring the effectiveness of given adaptation measures (e.g. Fankhauser 1998; Parry 2002); comparing the utility of different adaptation measures to a specific system (e.g. Winters et al. 1998; Parry et al. 2001); prioritization of geographical areas by measuring vulnerability (e.g. Adger et al. 2004; Brooks et al. 2005) or investigating adaptive capacity or needs of a certain area in order to derive policy rec- ommendations (e.g. Keskitalo 2004; Ibid. 2010). Even though this distinction provides a decent overview in the practical field, it leaves out literature that rather concentrates on the process of adaptation in a systemic context (overview in: Van Nieuwaal et al. 2009). In other words, parallel to the research on adaptation in practice, a section of literature is con- cerned with the human behavior that is the underlying driver of adaptation (Pelling and High 2005: 1).
Governance-centered studies on climate change adaptation are of importance for a better understanding of the process of adaptation within a governance system. Governance systems within most of this literature are treated as complex systems that are confronted with non-linear external stressors that create uncertainty (e.g. Levin 2003; Holland 2006;
Bauer and Schneider 2007; Duit et al. 2010; Loef 2010). The major subject of study is a system’s response to stressors and the effectiveness of certain settings within a system like actor constellations.
Within the present thesis the literature on governance and adaptation from a concep- tual perspective is of special interest. General aim of literature on conceptual frameworks is “to converge the inherent complexity and unpredictability of ecosystem dynamics into new governance or management concepts” (Van Nieuwaal et al. 2009: 15). Van Nieuwaal, Driessen, Spit and Termeer (2009) attribute the concepts of adaptive governance; resilience management; adaptive management; adaptive co-management; adaptive collaborative management; environmental governance; and earth system governance to this section of literature. Focus of these analyses is the transformation in a system that is targeted on adapting it to an external stressor. Since this implies that a system recognizes a threat and actively tries to defend itself against it, these approaches impose high standards to the sys- tems of concern.
In transformation studies, concepts on collective learning are an important field of analysis. Also different conceptual frameworks in the governance and adaptation literature identify learning processes as parts of adaptation processes (e.g. Armitage et al. 2008; Pahl-Wostl 2009; Loef 2010). Learning is assumed to be a social phenomenon occurring at multiple levels in such papers (Pahl-Wostl et al. 2007; Ibid. 2009; Diduck 2010). Even though it is widely recognized that learning processes are important for governance sys- tems in order to sustain (Allen 2001; Armitage et al. 2008; Duit and Galaz 2008), only few studies exist on how these processes occur in practice and what factors foster them (Gerlak and Heikkila 2011: 2). The present thesis aims on further closing this gap and therefore relies on an existing approach.
The “Conceptual framework for analyzing adaptive capacity and multi-level learning processes in resource governance regimes” developed by Pahl-Wostl (2009) is a corner- stone for the empirical analysis of the present thesis. Major objective of Pahl-Wostl’s paper is to develop a framework allowing researchers to systematically analyze changes within resource governance systems as multi-level learning processes (Ibid. 2009: 355). The en- tire paper draws back to a preceding empirical study on water resource governance regimes in different industrial and developing countries on behalf of the European Commission (Huntjens et al. 2008). Thus, it is a very relevant framework of the present thesis for it fo- cuses on a similar objective of study.
Resource governance systems are characterized by four major features:
i. “ the influence of formal and informal institutions,
ii. the role of state and non-state actors,
iii. the nature of multi-level interactions and
iv. the relative importance of bureaucratic hierarchies, markets and networks. ” (Pahl-Wostl 2009: 356).
Changes in resource governance regimes are conceived as societal and social learning processes (Ibid.:358). Societal learning is not understood as a change within an entire pop- ulation (in contrast to Diduck 2010), but as a change taking place in the part of a society that experiences a common obstacle either as persons affected, organizations in charge or as decision-makers. Social learning refers to a way of learning that is particularly important in this framework because the involvement of various actors at multiple levels is supposed to lead to a higher adaptive capacity in a system (Folke et al. 2005; Pahl-Wostl et al. 2007; Ibid. 2009).
The concept of learning is based on a stepwise model that divides learning into three levels. This concept of multi-level learning derives from organizational theory and presumes that organizations undergo transformations of different qualities (Argyris and Schön 1978). The different learning levels an organization or society can undergo are characterized by their degree of change (Table 1).
Table 1: Definitions in the Concept of Triple-Loop Learning
illustration not visible in this excerpt
Source: Author’s design derived from Argyris and Schön 1978; Pahl-Wostl 2009.
In order to make learning patterns detectable within governance regimes, Pahl-Wostl (2009) creates a matrix that analyzes changes in governance regimes and attributes them to the three levels of learning. Within this matrix the four major features of governance and the capacity of dealing with uncertainty are focused upon. Additionally, the manner in which uncertainty is treated within these governance systems is considered. The indicators of change derive from the conceptualization of learning as well as the empirical back- ground and thereby provide a balanced scope on learning processes. Additionally, a critical evaluation of Pahl-Wostl’s framework is integrated in the conclusion of the present thesis. This evaluation includes the underlying theoretical concepts as well as the empirical di- mension.
Disaster risk management or in short disaster management is another relevant field of study to this thesis for it relates to the empirical case studies that include flood risk man- agement. Disaster management is a considerably new area of study (GTZ 2002), which is mainly due to a paradigm shift away from reactive strategies towards more preventive ap- proaches (Yodmani 2001). Literature on disaster risk management is often of a practical nature, concentrating on case studies and strategies towards a better management of risk (Mercer 2010:248). Besides empirically oriented studies there is also literature on theoreti- cal aspects of disaster risk. Wisner, Blaikie, Cannon and Davis explain for instance how risk is constructed through environmental, economical, social and political influences (Wisner et al. 2003).
The present research question, in general, focuses on the interaction of a dynamic external stressor with a given society. Additionally, uncertainty about the external stressor is strengthened through projections of further uncertainty, in this case climate change. Since this requires the analysis of highly complex and non-linear interlinkages (cf. Duit and Galaz 2008: 312), a systemic approach is used as theoretical base throughout the analysis. The concepts of governance and governance systems, vulnerability and collective learning are in the centre of focus for they help explaining how collective learning processes can be detected and understood within the following case studies.
The following subsection aims on highlighting factors within social-ecological systems that are relevant for this system’s ability to adapt to external shocks like natural disasters. It therefore starts with a brief introduction to important concepts in the governance research.
Subsequently, specific components of governance systems are highlighted, which build the basis for the analysis of the two case studies.
From a systems theory perspective, the functioning of a social system cannot be solely seen as a consequence of the political system or state7 (Luhmann 1975; Ibid. 2000). The present thesis connects to this notion and draws back to a governance concept that considers hierarchical and non-hierarchical modes of social coordination, which may or may not include governmental involvement (Mayntz 2004; Risse and Lehmkuhl 2006; Börzel 2010). Throughout this study the term governance refers to “the entirety of all co-existing modes of collectively regulating social matters”8 (Mayntz 2004: 66). This definition includes different modes of social coordination, state and non-state actors and multi-level coordination that are going to be discussed further.
Governance is an often used, but nevertheless blurry term within the social sciences. Though, it is often confused with government, the actual meaning of both terms differ sig- nificantly. From a political science perspective, government and governance have similar outputs9, while differences derive from the mode of establishing rules or steering collective action. In contrast to hierarchical structures that are a defining feature of government, go- vernance refers to less restrictive mechanisms of governing, which can also include private actors (Stoker 1998: 17). Governance perspective can therefore explain to certain extends how hierarchical and non-hierarchical patterns can be part of one system simultaneously.
For the past decades a paradigm shift from ‘government’ to ‘governance’ became apparent within social sciences (Van Nieuwaal 2009: 9), which is furthermore an indicator that a change in perceptions has occurred (Benz 2004: 13). This shift can mainly be explained by the observation that there exist spaces like the international system, weak states or Public-Private Partnerships that cannot be explained by state structures and hierarchical bureaucracies (Ibid. 2004). Especially when focusing on the developing world, this concept plays an important role because it provides explanations on how a weak state with limited steering capacity can still be able to rule a country.
The primary subject to this study will be the water- and flood management sector10 and the disaster management sector, whilst the influence of other relevant sectors like agri- culture and forestry will be considered subsequently in the two case studies. Both these sectors form an environmental governance system that is a social-ecological system, whose purpose it is to govern human behavior towards a particular ecological system. In order to analyze the structures of environmental governance systems it is useful to divide them into their respective institutions, actors and their interactions and finally modes of governance (Pahl-Wostl 2009: 356).11
Institutions refer to rules, which have been set up in order for a social entity to coor- dinate different kinds of interactions in order to reduce uncertainty for its members and also external actors (cf. North 1990: 1-6). These rules can either be established formally or practiced informally, whereas informal institutions can be transformed into formal institu- tions and both types influence each other. Most importantly, formal and informal institu- tions differ in the ways they can be enforced (cf. Ibid. 1990: 4). Legislative frameworks can help individuals to enforce their rights at higher levels like it was the case after the floods of 2010 in Pakistan when numerous petitioners held governmental agencies and authorities responsible for not fulfilling their duties which have been defined in the Disas- ter Management Ordinance and the respective Act (cf. section 3.2.2). Before these compe- tencies were not formalized in a law, it was not possible for the aggrieved party to claim for compensation and responsibilities. Within the analysis of the case studies particular emphasis is placed on formal institutions and prevailing paradigms in flood- and disaster management. In contrast to Pahl-Wostl’s framework normative institutions are not consi- dered within the present analysis, because these refer to informal habitual norms at the micro-level. The following analysis though, concentrates on macro-level developments with emphasis on the national level.
As environmental governance systems include a vast range of actors at different le- vels, competencies and responsibilities become blurred. The case study analysis indicates that international donors and agencies, the federal government, local governments, civil society and various kinds of stakeholders are key actors involved in these complex gover- nance systems to different extents. Participatory approaches have become important for environmental governance, which has been recognized by academics as well as practition- ers (cf. Ostrom 1999; Sultana et al. 2008; Pahl-Wostl 2009; Ibid. 2007). Especially in envi- ronmental governance systems knowledge of local individuals can contribute to a large extent to reduce uncertainty (Ostrom 1999: 520-21). Though participation is generally re- garded as the second way besides national government especially in developing countries, it also includes weaknesses. Especially problems of legitimacy, lack of representing poor locals and the notion that what locals want does not necessarily mean that it is the solution benefiting the largest share of all stakeholders are hindering the positive effects of partici- pation. Decisive for the impact of participatory processes are the degrees to which affected segments of society match with those who take action in building, maintaining or operating flood protection facilities for instance. In Bangladesh autonomous flood management by local stakeholders has been connected to some degree with formal governmental organiza- tions (cf. Sultana et al. 2008). Diverse actor networks do not automatically generate broad benefits within societies but they are certainly a prerequisite for reducing uncertainty by ensuring multiple sources of knowledge and experience. Therefore, diversification of ac- tors enhances the capacity of a system to adapt to external influences (Pahl-Wostl 2009; Folke et al. 2005).
Multi-level interactions are a forming characteristic of environmental governance systems since governance may include actors from supranational- down to individual level (cf. Hooghe and Marks 2003; Benz 2004). Interactions can emerge between actors of one level, which is often referred to as horizontal coordination, and also between actors of dif- ferent levels, known as vertical coordination (van Nieuwaal et al. 2009; Scharpf 1997). Consequently, vertical coordination is the more decisive process when analyzing multi- level interactions. From a normative perspective a system’s capability to react to non-linear external shocks is getting increased when it includes more than one centre of governance that is able to operate independently (cf. Ostrom 2001; Duit and Galaz 2008; Pahl-Wostl 2009). The reason behind this suggested correlation is that these polycentric systems can counterbalance failures and provide multiple sources of knowledge and experience in order to mitigate, react and respond to external shocks (cf. Ostrom 2001; Pahl-Wostl 2009). Like Claudia Pahl Wostl points out: “ Multi-level governance in polycentric systems im- plies that decision making authority is distributed in a nested hierarchy and does not re- side at one single level ” (Ibid. 2009: 357). Decentralization is therefore a crucial characte- ristic of systems that are more resilient towards external shocks. It is important to note in this context that whilst the different centers of governance are able to act independently from one another, they need to exercise vertical and horizontal coordination and coopera- tion in order to create a functioning system (cf. Kooiman 2000; Pahl-Wostl 2009; Ibid. 2008).
The major driver of governance systems is interactions among their respective actors. Out of the constellation of actors and the ways they interact, different modes of governance can be derived. Kooiman identifies three major modes of governance that is self- governance, co-governance and hierarchical governance (Ibid. 2007: 10). These three types relate to the degree of formality of institutions, whilst self-governance is the most informal arrangement. A second central dimension of governance is the involvement of state and non-state actors (Thompson et al. 1991: 228-29). By considering the two dimen- sions of governance modes like discussed above, networks, markets and bureaucratic hie- rarchies can be classified as the major modes of governance (Thompson et al. 1991). With- in the two case studies bureaucratic hierarchies were the dominant mode of governance, whilst networks and markets existed but had only limited or no access to decision-making. Bureaucratic hierarchies are driven by state actors through formalized channels, while net- works are organized in a very informal manner including only a limited proportion of state actors. Markets are dominated by non-state actors and regulated by formal as well as in- formal institutions (Thompson 1991; Pahl-Wostl 2009). Following Pahl-Wostl’s frame- work, equilibrium of all three modes of governance is the most desirable constellation for a system in order to adapt to sudden external changes (Ibid. 2009: 358).
All four elements are important to be considered in order to observe substantial changes in environmental governance systems. Within this section the basic components and concepts of governance and environmental governance systems were explained. The next subsection will address approaches that are concerned with how these systems interact with their complex environment.
Environmental governance systems are considered to be complex adaptive systems. This is due to the extremely high levels of uncertainty and complexity that evolve while governing ecological systems. Changes in such systems are occurring on a frequent basis and are hardly predictable (Duit and Galaz 2008: 312-13). Human behavior has a great influence on ecological systems causing further changes. Whether a social system is vulnerable to the changes in its natural environment is not solely determined by exogenous factors. In order to fully understand vulnerability, endogenous factors like dependence of a society on agriculture play an important role (Adger and Vinecent 2004; Brooks 2003).
Each social entity has a certain coping range, which indicates to what degree it is re- silient to external stresses (Smit and Pilifosova 2003: 12-14). This coping range is a prod- uct of factors like the sensitivity, the resilience and the adaptive capacity of a system. The following example shall clarify the relationships among these factors. A quarter of the Dutch territory lies beneath sea level making it extraordinarily sensitive to any rise of the sea water level. Planners were commissioned to build dykes and other flood protection structures over a thousand years ago in order to build up resilience. Sensitivity in this case emerges on one hand out of the geographical conditions on the territory and on the other hand out of the circumstance that humans settled within this particular location. The adap- tive capacity of this system lies in the mental and physical capability of the planners and workers firstly to find a solution and secondly to construct proper structures in the right locations. The process of planning and constructing dykes is considered adaptation. Through the capability to adapt and the actual adaptation, the system improved its resi- lience to sea floods. As long as the coping range of a country to a specific stressor is not exceeded, meaning the resilience of a system is able to absorb the negative effects, a socie- ty is in balance to its environment (cf. figure 1).
Figure 1: Scheme of an Adaptation Process
illustration not visible in this excerpt
Source: Author’s design derived from Smit et al. 2000; Smit and Pilifosova 2003; Adger and Vinecent 2004; Smit and Wandel 2006.
(-) stands for negative effects
(+) stands for positive effects
Vulnerability emerges when the coping range of a system is exceeded meaning that the existing resilience is not sufficient in order to absorb the negative effects of the external stressor. This is a very much simplified view on vulnerability and how it develops. Vulne- rability implies very many dimensions referring to the ways it develops and the ways it is reduced in societies. A more specified definition of vulnerability must therefore include what type of stressor is considered (Brooks 2003: 3). The focus of the present analysis lies on the external stressor of natural disasters, which is considered an extreme case. Following Wisner, Blaiki, Cannon and Davis vulnerability is defined as:
“ [ … ]the characteristics of a person or group and their situation that in fluence their capacity to anticipate, cope with, resist and recover from the impact of a natural hazard [ … ] ” (Ibid. 2003: 11).
This definition represents socially constructed vulnerability. Besides this type of vulnerability the present analysis also highlights biophysical determinants of vulnerability that derive from the intensity and frequency of a natural hazard (cf. Brooks 2003; Wisner et al. 2003). The assumption therefore is that high intensity and frequency of a hazard contribute positively to the adaptive capacity of an affected society. Improvements in adaptive capacity, in turn, decreases vulnerability of a system (cf. Armitage and Plummer 2010). Accordingly, vulnerability is by no means a static condition within any system.
The approach of complex adaptive systems assumes that external stress will at a cer- tain point result in internal change of the affected system in order for it to adapt (cf. Duit and Galaz 2008). The point at which adaptation measures are taken up is hardly predicta- ble, especially due to the complexity in the relations between key actors in highly differen- tiated governance systems. In these systems the group of people that are affected by a natu- ral disaster for instance does not necessarily match the group that holds the powers and capacity of initiating adequate counter measures (Sultana et al. 2008: 360-61). The path from the perception of the risk to collective action can therefore be extremely challenging, especially under conditions of low compliance and communication among stakeholders and decision-makers (Ostrom 1998: 16-18). Sultana, Johnson and Thompson furthermore highlight how natural hazards combined with advanced media coverage can accelerate pol- icy debates and therefore enhance communication about risk (Ibid. 2010).
Once a risk has been acknowledged and collective action was taken in order to adapt, the considered measure must not necessarily be an adequate solution to the problem. Adap- tation measures can be harmful itself (cf. Fig. 1) like in the Bangladeshi case where large- scale embankment structures were viewed as final solution to the flood problem. In con- trast, they turned out to be harmful due to their lack of flexible regulation of water flow
(Section 2.2.2). The manner in which adaptation takes place influences the sustainability of the measures that are undertaken. Firstly, adaptation can take place as autonomous reaction to a certain event with limited long-term problem solving capacity. The present analysis, in turn, concentrates on adaptation as a consciously planned activity that is rather subject to collective action than autonomous adaptation. Planned adaptation activities can be either reactive or anticipatory (cf. Smit and Wandel 2006; Smit et al 2000; Nykvist and Hahn 2011). Anticipatory adaptation is the more advanced type and demands high levels of co- operation and knowledge generation among other factors in order to emerge (cf. Smit and Wandel 2006; Berkes et al. 2008: 11-12). In conclusion, for this type of adaptation a sys- temic structure is needed that has the capacity of overcoming reactive adaptation.
Adaptive capacity is considered to be the key concept in order to reduce vulnerability in a system. As already mentioned, adaptive capacity refers to all sorts of resources within a system that enable it to adapt to its environment (cf. Section 1.1). The example of the Netherlands reveals that adaptive capacity implies ‘physical’ and ‘mental’ capacities of a governance system.12 The present analysis stresses the importance of ‘mental’ capacities since they are needed to build up physical capacities like finances and infrastructure for instance. In accordance, the present analysis draws on Pahl-Wostl’s definition of adaptive capacity as a working definition, because it highlights skills. Adaptive capacity is therefore referred to as:
“ the ability of a resource governance system to [ … ] alter [ … ] and [ … ] convert structural elements as response to experienced or expected changes in the societal or natural environment ” (Pahl-Wostl 2009: 355).
Learning processes are closely related to the adaptive capacity of environmental governance systems, since they enable them to govern in an anticipatory manner. Through the collective acquisition of knowledge and experience, maladaptations are less likely to occur and easier to accommodate (Lebel et al. 2010).
Collective learning is an important subject to the present analysis for it is presumed to be a very relevant determinant of vulnerability. This subsection seeks to highlight this nexus and establish a clear picture of what learning is in particular and what factors encourage it.
It will therefore only focus on concepts of collective learning, which are particularly rele- vant for environmental governance systems. Theories and models on learning processes, also within collectives, are necessarily diverse whereas topics range from methodological aspects of learning processes to cognitive patterns of individual learners over to learning processes in international organizations.13 Out of these theories and models only a limited array is relevant to the present analysis.
Within the many concepts of learning, two dimensions of learning are especially hig- hlighted (Gerlak and Heikkila 2011: 3). Firstly, collective learning implies a step-wise process, which mainly consists of the acquisition of knowledge, the dissemination and processing of information and the transformation of knowledge within an organizational framework (Argyris and Schön 1996: 2-3). This process has different facets depending on whether learning occurs in an experimental or in a targeted manner (Henry 2009). The process of collective learning is furthermore to be delineated from plain reaction to an ex- ternal change (Löf 2010: 531-32). In contrast to reactive behavior, collective learning is considered more sustainable with regard to its time scale and the depth of change. In the present analysis the process described here is not regarded as being sufficient without transferring knowledge into substantial results in order to achieve learning. Collective learning is therefore a process in which knowledge is transferred into different kinds of changes, also called products of learning (Argyris and Schön 1996: 2-3). It is important to notice that learning does not necessarily lead to improved products, since experimental learning for instance even relies on trial and error schemes (Gerlak and Heikkila 2011: 3- 4). Therefore failed trials can lead to new understanding and reconsiderations of strategies. In order to decide which event is considered a collective learning process and which is not, the present analysis proceeds in a two-step fashion. Firstly, sustainable changes within the scope of the case studies are detected, which is followed by an analysis of the process that led to the observed change. For instance, a fundamental change in policies, which is not based on newly acquired knowledge or experiences14, is likely to be a plain product of political or economic interests but not learning. Also policy that lacks the at- tempt of its implementation is not considered learning according to the understanding of the present thesis. In summary, learning is expected to be a purposeful activity as opposed to fast and reactive decisions that are not based on past developments or lack any attempt to be put into practice.
Collective learning processes differ in their depth of change (Argyris and Schön 1978). The concept of multiple learning loops as illustrated in Table 1 characterizes the different stages of learning that ranges from single to triple-loop learning. Single-loop learning is merely an adaptation to external change that implies changes of existing struc- tures but not underlying beliefs. As the level of learning increases, the extent of change also increases (Pahl-Wostl 2009: 359). It is assumed that the quality of learning has fur- thermore an impact on vulnerability. This assumption is based on the finding that higher levels of learning indicate that a system is able to encounter non-linear external changes in a more flexible manner (cf. Argyris and Schön 1978; Pahl-Wostl 2009; Löf 2009).
Finally, factors that supposedly support collective learning in environmental governance systems are summarized in order to explain how change in the highlighted components of these systems is interpreted within the framework of analysis. Major factors constraining collective learning in governance systems are therefore centralized systems, rigid bureaucracies, poor access to information by decision makers and the population and a lack of vertical integration (Pahl-Wostl et al. 2007; Mostert et al. 2007; Huntjens et al. 2008; Pahl-Wostl 2009). These assumptions are based on multiple empirical studies mainly in European countries and are an important input of Pahl-Wostl’s framework of analysis (Ibid 2009). Based on these assumptions important conclusions on how learning is shaped within environmental governance systems have been drawn.
A central weak point in organizational learning theory and in general learning theory is that concepts tend to be quite blurry and overlapping (Lähteenmäki et al. 2001). For the purpose of the present thesis a relatively limited range of concepts of organizational learn- ing was considered in order to avoid over complexity, which leads to blurred conceptuali- ties.
It is important to notice that all of the theories, models and concepts introduced in this section are not entirely new and have been considered in the research of systems theory, organizational theory and other fields of research before. Climate change and more particularly adaptation to climate change opened new channels of applying this existing knowledge to a new context, whilst some areas have been highlighted or regarded under a new perspective. A reconsideration of existing knowledge and its application to new con- texts can be an important way in order to achieve advanced systems and modes of gover- nance.
Inherently, this thesis seeks to substantiate the nexus between vulnerability and collective learning processes. It thereby lays open in what particular ways vulnerability is influenced by collective learning processes. Starting point of the analysis is the paradox that develop- ing countries with low levels of physical exposure to flood hazards tend to be more vulner- able than developing countries suffering from higher levels of physical exposure. The un- derlying analysis goes beyond the plain assessment of social, economic and geographic indicators that may determine vulnerability. It does so by focusing on the actual processes that decide how vulnerable two different societies are to extreme flood events.
Before attempting an operationalization in the area of flood disaster management it is important to highlight some obstacles in this respect. Social-ecological systems are charac- terized by a high degree of complexity, which is even getting increased if it comes to natu- ral disasters (Birkland 2006). This in turn means that each attempt to convert such systems into a model or theory has to accept a high degree of simplification. In order to avoid over- simplification though, it is important to reflect empiricism in the models and highlight li- mitations in order to further enhance their applicability. This thesis majorly works deduc- tive by testing already achieved assumptions and theoretical frameworks in two empirical case studies using comparative method.
Applying learning theory to social-ecological governance systems implies the diffi- culties described in advance. The present thesis tries to provide a more holistic picture of collective learning by using an analytical framework that is based on theory as well as em- piricism. An analysis of collective learning patterns in socio-ecologic systems may there- fore not be able to cover aspects of the individual level. In the case of collective learning in flood management this means that not the single learning of a member in a community is in the centre of observation. In turn, informal networks are considered in this analysis and in this way can balance the fading-out of the individual level to some degree (cf. Pahl- Wostl 2009).
A key challenge of the present study is to make collective learning processes detect- able because not every change means that collective learning processes have been taken place (Newig et al. 2010: 8). In order to meet this challenge, the following section aims to conceptualize learning processes in social systems following the conceptual framework of Pahl-Wostl (2009). The social systems of concern are resource governance systems which are characterized by their institutions, actors, multi-level interactions and governance mod- es (Ibid.: 356). In the scenario of reoccurring extreme weather events these systems are exposed to an unpredictable external stressor. Climate change further increases the uncer- tainty about this hazard for it causes increasing frequency and magnitude of extreme weather events. In such a scenario adaptation to the external stressor appears to be a logical reaction.
Adaptation is therefore closely interlinked with learning processes within the present framework for it analyzes learning processes that foster lower levels of vulnerability. Learning in the context of adaptation relates to a system’s ability to adapt to a changing environment, which is referred to as adaptive capacity in this conceptual framework. Adaptive capacity is understood as “ [ … ] the ability of a resource governance system to first alter processes and if required convert structural elements as response to expe- rienced or expected changes in the societal or natural environment. ” (Pahl- Wostl 2009: 355).
However, adaptation cannot be regarded as an automatism that begins as an external stress starts interfering and causes capacity-building to adapt in future. Before planned adaptation can take place at national level, the interplay of a stimulus and how it is per- ceived and the political commitment (cf. Thompson and Gaviria 2004: 53) decide whether or not a system starts reacting as a whole. The nature of the stimulus can have some influ- ence on the commitment of a system to react. Single natural disasters of high magnitude for instance tend to have higher influence on the agenda setting process than a series of similar events with lower magnitude (Birkland 2006: 19), which is a crucial factor in the Pakistan case study. Though in general it is almost impossible to predict at what point a political system will start reacting to an external stress or whether it reacts at all. Accor- dingly, adaptation and therefore learning can only be detected but not predicted in the cur- rent state of knowledge.
Uncertainty is a crucial factor within this analysis for it creates obstacles that can barely be overcome by traditional means and therefore demands rethinking existing forms of collective action (Duit and Galaz 2008). Complex phenomena like extreme weather events create high levels of uncertainty especially because they are assumed to increase in intensity through climate change. Under these prospects habitual means are hardly suffi- cient anymore in order to manage risk. In order to maintain its status quo or even benefit from changes, a governance system needs to change its own structures and modes of coordination. These particular changes are identified as collective learning processes within this conceptual framework.
So far, the environment of collective learning in resource government systems has been considered, which is now followed by its operationalization. Analyses of collective learning patterns can focus on the process as well as the products of learning (Gerlak and Heikkila 2011: 3). Accordingly, the present thesis uses the following strategies in order to “measure” collective learning processes:
i. Out of existing empirical and conceptual studies identifying factors that foster learning. Based on these factors drawing conclusions to the process of learning in the case studies chosen.
ii. Focusing on potential outcomes of learning processes15 that serve as indicators for successful completion of collective learning processes.
Outcomes of collective learning processes in governance regimes are not measured by their relative success since experimental learning like by trial and error can be an indicator for learning processes (cf. Fazey et al. 2005; Gerlak and Heikkila 2011). The present thesis supports the notion that collective learning processes, also if they imply changes that are not successful16, in long-term perspective support the process of adaptation and thereby make systems less vulnerable to hazards.
Changes in governance regimes are of different impact and can therefore be attributed to different levels of learning. Pahl-Wostl attributes changes in governance regimes to different levels of learning in a matrix. Therefore all four major features of governance regimes are taken into consideration. The present thesis will analyze the empirical case studies following the criteria established in this matrix.
Institutional changes are the first important indicator of learning processes since they imply that attention has been directed to a certain problem and new ways of handling it have been considered (cf. Table 2).
Table 2: Institutional Changes in Governance Systems
illustration not visible in this excerpt
Source: Pahl-Wostl 2009: 360
Participation of different stakeholders is a key feature in order to encourage collec- tive learning processes that aim on increasing resilience in resource governance systems (cf. Kilvington 2005; Pahl-Wostl 2007; Newig et al. 2010). Even though broad participa- tion in different stages of the policy process is not a guarantee for successful learning, it is a prerequisite for multiple resources of information and communication between key stakeholders (cf. Sabatier and Jenkins-Smith 1993; Cooney and Lang 2007; Pahl-Wostl 2009). Not only the variety of actors decides whether collective learning takes place but also the roles the actors and how they develop and transform over time. Accordingly, changes in actor constellations are considered another indicator for collective learning processes (Pahl-Wostl 2009: 357; cf. Table 3).
Table 3: Changes in Actor Networks in Governance Systems
illustration not visible in this excerpt
1 Physical exposure refers to the average number of people that have been exposed to floods form 1980- 2000 (UNDP 2004).
2 Relative vulnerability refers to the number of fatalities (annual average from 1980 until 2000) in one million people exposed to floods (annual average from 1980 until 2000) in a country (UNDP 2004).
3 External stress is used here as a neutral term.
4 In this thesis, papers focusing on adaptation, vulnerability or resilience are referred to as adaptation litera- ture. Other designations like resilience literature (eg. Loef 2010) for instance are also used, referring to a similar field of study.
5 Practically-oriented literature refers to papers that primarily focus on concrete solutions in order to adapt to climate change or measuring vulnerability.
6 Theoretically-oriented literature refers to literature that focuses on structures and “behavior” of systems that lead to adaptation or steer adaptation.
7 The term ‘state’ in this context describes the organization of a political system for the purpose of self- construction and self-sustaining in a society.
8 This translation was derived from Risse and Lehmkuhl (2006: 7).
9 he SFB 700 (2009) distinguishes between the provision of rules and collective goods as common out- puts of governance, which coincides with outputs of government. Differences derive from the ways these goods are provided, which have nevertheless also influences on the actual outputs.
10 Flood management is part of the water sector. Therefore, the present analysis mainly focuses on a re- source governance regime (cf. Pahl- Wostl 2009), which is referred to more broadly as environmental go- vernance system in the following sections.
11 Based on Pahl-Wostl’s framework of analysis these four dimensions of governance systems will be the leading concept of analyzing structures and changes within environmental governance systems (Ibid. 2009).
12 Physical capacities here refer to technologies, manpower and the financial resources in order to employ these two. Mental capacities refer to managerial skills, knowledge generation and appliance and more specifically learning skills.
13 For a sophisticated overview of theories and models of learning Blackmore is very recommendable (Ibid. 2007:520-23).
14 New knowledge refers to newly induced studies or studies that have not been considered before for in- stance. New experiences can be previous failures of policies or external experiences like best practice ex- amples that are relevant for the system of concern.
15 These outcomes are changes detected in the four major components of the environmental governance systems of Bangladesh and Pakistan.
16 Success in this thesis is measured by the ability of a country to reduce its relative vulnerability.
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