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Alex_Webb_Thesis_2013

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Alex_Webb_Thesis_2013

  1. 1. AN ABSTRACT of the THESIS OF Wm. Alex Webb for the degree of Master of Science in Marine and Environmental Sciences presented on November 15th , 2013 Title: Community Perspectives on Sustainability and Resilience in a Social-Ecological Paradigm Abstract approved: Kostas Alexandridis, P.h.d Abstract: Environmental sustainability has been an elusive and ambiguous concept from a management perspective since its inception in the mid 1980’s. Subsequent research has given rise to numerous observations of the complex and multi-dimensional (economic, cultural, social) interactions between human societies and their environments. Leading to the conclusion that considerable gaps in understanding of the specific social processes that define, promote and are associated with sustainability and resilience. This research takes a bottom up, community based approach to exploring community knowledge structures regarding social-ecological dynamics as they relate to concepts of sustainability and resilience as social constructs. Field work took place over a six month period with five distinct institutional and/or socially based community groups. This study was conducted exclusively with residents of the island of St. Thomas in the US Virgin Islands. Sampling strategies combined purposive and snowball processes to minimize researcher bias. Due to the inherent complexity within social-ecological dynamics this
  2. 2. research used mix methods including open ended scenario planning focus groups and an adapted version of the Q-method. Focus groups consisted of four to nine members per group with 32 total participants and took approximately two hours to complete. This thesis also takes an experimental approach to using semantic network analysis to analyze community knowledge structures as they relate to the critical drivers and complex associations within a closed system of interactions. The scenario planning discussions were audio recorded and transcribed verbatim into natural language text documents. Semantically relevant concepts were identified and extracted from the text and then weighted through a process of latent semantic indexing and the TF*IDF function. Jaccard Similarity coefficients were then calculated for each combination of concepts and used to create a network structure. The graph theoretic implications of cohesion metrics and centrality measures were then used to identify the structural composition and key themes in the discourse networks. Results from the analysis provide subjective participatory evidence supporting recent theory in natural resource management and social-ecological resilience and is linked to management considerations. Funding for this project was provided by NSF’s VI-EPSCoR Research Infrastructure Improvement Award No. 814417 and The Research Institute for Humanities and Nature (RIHN).
  3. 3. © Copyright by Wm. Alex Webb November 15th , 2013 All Rights Reserved
  4. 4. Community Perspectives on Sustainability and Resilience in a Social-Ecological Paradigm By Wm. Alex Webb A Thesis Submitted to the University of the Virgin Islands In partial fulfillment of the requirements for the Degree of Master of Science Presented November 15th , 2013
  5. 5. Dr Fyler Smith, Committee Member jil L_ d.....„..,./ , Master of Science thesis of Wm. Alex Webb Presented on November 15th, 2013 APPROVED: Dr. Kostas Alexandridis, Advisor Prof. Tetsu Sato, Committee Member Dr. Paul Jobsis, Director of MMES Program Dr. S dra Romano, College of Science and Mathematics I understand that my thesis will become part of the permanent collection of the University of the Virgin Islands Library. My signature below authorizes release of my thesis to any reader upon request wm. Alex Webb Wm. Alex Webb
  6. 6. ACKNOWLEDGEMENTS: I would personally like to thank VI-EPSCoR for not only providing the funding for my thesis project but for funding my Research Assistantship throughout my graduate school tenure as well. Specifically, VI-EPSCoR Research Infrastructure Improvement Award No. 814417. Additionally I would like to thank The Research Institute for Humanities and Nature (RIHN) for providing opportunities for me to learn from a broad range of international scientists while participating in the ILEK (Integrated Local Ecological Knowledge) project. I would also like to thank my tireless and enthusiastic advisor for always both pushing and supporting my intellectual development and for creating opportunities for me that I would have never experienced otherwise. And most importantly I would like to thank my patient fiancé and financier to allowing a homeless bum to live in her house while he tries to educate himself.
  7. 7. CONTRIBUTION OF AUTHORS Dr. Kostas Alexandridis was involved in the methodological design of this thesis as well as assisted with data collection and analysis. Prof. Tetsu Sato contributed to the intellectual development regarding the analysis and interpretation of data.
  8. 8. Table of Contents Chapter 1: Introduction _____________________________________________ 2 1.1 Overview____________________________________________________ 2 1.2 Background _________________________________________________ 3 1.3 Field Methods _______________________________________________ 4 1.4 Methods of Analysis __________________________________________ 5 1.5 Results _____________________________________________________ 5 1.6 Conclusions and Discussion ____________________________________ 7 Chapter 2: Background______________________________________________ 8 2.1 Broad Theory _______________________________________________ 8 Environmental Sustainability ________________________________________ 8 Social-Ecological Systems Theory and Environmental Sustainability_________ 9 Environmental Sustainability and Social-Ecological Resilience ____________ 11 2.2 Key Concepts _______________________________________________ 12 The Role of Legacies and Culture ___________________________________ 12 No Panaceas and the Bottom-up Approach ____________________________ 12 Polycentricism and Organizational Cooperation ________________________ 13 2.3 Study Site: The United States Virgin Islands (USVI) ______________ 13 Brief History of Development in the Caribbean Region __________________ 14 Brief History of the U.S. Virgin Islands _______________________________ 16 Current Conditions _______________________________________________ 17 Chapter 3: Field Methods___________________________________________ 19 3.1 Overview___________________________________________________ 19 3.2 Social-Ecological Framework__________________________________ 21 Framework _____________________________________________________ 21 Knowledgebase__________________________________________________ 22 3.3 Scenario Planning Focus Group Discussions _____________________ 22 Scenario Planning ________________________________________________ 22 Focus Groups ___________________________________________________ 24 3.4 Scenario Planning Exercises___________________________________ 25 Exercise #1 ‘Choosing a Future Scenario’ _____________________________ 25 Exercise #2 ‘Connecting the Scenario to Present Conditions’ ______________ 27 Exercise #3 ‘Defining Sustainability’_________________________________ 30 Exercise #4 ‘Preparedness for the Future Scenario’______________________ 30 3.5 Sampling Design ____________________________________________ 30 3.6 Notes from the Field _________________________________________ 34 Recruitment of Participants ________________________________________ 34
  9. 9. Table of Contents (Continued) Methodological Design____________________________________________ 35 Chapter 4: Methods of Analysis______________________________________ 37 4.1 Overview___________________________________________________ 37 4.2 Semantic Network Analysis ___________________________________ 37 4.3 Structural Motifs of Semantic Networks_________________________ 39 Small World Dynamics____________________________________________ 39 Scale Free Patterns of Connectivity __________________________________ 40 4.4 Analysis Metrics ____________________________________________ 41 Cohesion Metrics ________________________________________________ 41 Centrality Measures ______________________________________________ 43 4.5 Processing Data _____________________________________________ 44 Dictionary Modifications __________________________________________ 44 Weighting Functions______________________________________________ 45 Drawing Themes from the Most Central Concepts ______________________ 46 4.6 Semantic Network Analysis as Dimension Reduction Tool__________ 47 4.7 Preliminary Statistics ________________________________________ 48 Combined Discourses Network Statistics______________________________ 51 Exercise #1 ‘Choosing a Future Scenario’ Network Statistics______________ 52 Exercise #2 ‘Connecting Future Scenario to Present Conditions’ Network Statistics _______________________________________________________ 53 Exercise #3 ‘Defining Sustainability’ Network Statistics _________________ 54 Exercise #4 ‘Discussing Preparedness for the Future’ Network Statistics_____ 55 Chapter 5: Results _________________________________________________ 57 5.1 Overview___________________________________________________ 57 Section I: Universal Themes from the Discourse _______________________ 58 5.2 Universal Themes from the Focus Group Exercises _______________ 58 Sense of Place, Identity and Economic Disparity________________________ 60 The Role of the Environment _______________________________________ 73 Some Initial Conclusions from Universal Themes in the Discourse _________ 75 Section II: Analysis of Exercises _____________________________________ 76 5.3 Exercise #1: Choosing a Future Scenario and Time Frame_________ 77 Summary Conclusions ____________________________________________ 82 5.4 Exercise #2: Discussing and Ranking Drivers for the Future________ 82 Summary Conclusions from Q-method Statements ______________________ 96 Variation in Group Responses ______________________________________ 97 5.5 Exercise #3: Defining Sustainability and a Headline Indicator ______ 99
  10. 10. Table of Contents (Continued) Summary Conclusions ___________________________________________ 103 5.6 Exercise #4: Discussing Preparedness for the Future as a Measure of Social Resilience _________________________________________________ 103 Summary Conclusions:___________________________________________ 107 Chapter 6: Discussion and Considerations ____________________________ 108 6.1 Overview__________________________________________________ 108 6.2 ‘Top 5’ Takeaways _________________________________________ 108 6.3 Culture as an Abstract Semantic Artifact in Knowledge Structures _ 110 6.4 Sustainability and Resilience as they relate to Community Engagement and Management ________________________________________________ 111 6.5 Implications of Globalization on Social-Ecological Resilience ______ 112 6.6 Brief Review of methods used ________________________________ 113 References: ______________________________________________________ 115 Appendices ______________________________________________________ 121
  11. 11. List of Figures Figure 2.1. Visualization of social-ecological or human-coupled systems theory ...... 10 Figure 2.2. Map of the USVI in context of the Caribbean region................................ 14 Figure 3.1. Scenario planning protocol of compounding exercises............................. 20 Figure 3.2. Research team setting up and waiting for focus group participants to arrive to Rastafarian Farming Co-op focus group discussion in Bordeaux, St. Thomas USVI ...................................................................................................................................... 29 Figure 3.3. Community plot of relationships between focus group members ............. 32 Figure 3.4. Map of the distribution of participant’s residence in St. Thomas, USVI. . 33 Figure 3.5. Map of distribution of participant’s place of employment in St. Thomas, USVI. ........................................................................................................................... 34 Figure 4.1. The color red example of spreading activation theory from Collins and Loftus, 1975. ................................................................................................................ 38 Figure 4.2. Log-log plot of the distribution of node centrality of network created from combined group conversations (p=0.028).................................................................... 41 Figure 4.3. Distribution of degree centrality of concepts extracted from combined discussions ................................................................................................................... 47 Figure 4.4. Distribution of frequencies of concepts extracted from combined discussions ................................................................................................................... 48 Figure 5.1. The four emergent universal themes from the most central concepts derived from the overall combined network. Some sample concepts used to define each theme are listed underneath each title.................................................................. 59 Figure 5.2. Semantic network visualization of connected nature of concepts related to ‘Sense of Place’ and the ‘Social and Organization Dynamics’ theme. Node size based on out-degree................................................................................................................ 62 Figure 5.3. Total population of the U.S. Virgin Islands from 1960 to 2012................ 65 Figure 5.4. Population growth rates of high income Caribbean countries from 1960 to 2012.............................................................................................................................. 66 Figure 5.5. Percent of international migration population in Eastern Caribbean countries....................................................................................................................... 66 Figure 5.6. Percent of tourists as part of the general population averaged over the year in heavily visited Caribbean countries ......................................................................... 67 Figure 5.7. Economic disparity by estate in St. Thomas. Darker areas indicate higher incidences of poverty ................................................................................................... 70 Figure 5.8. Semantic network representation of relationship between concepts related to ‘Economic and Livelihoods’ and ‘Environment and Resources’ themes. Node size based on out-degree...................................................................................................... 72 Figure 5.9. Correspondence plot of phrases extracted from the exercise #1 discourse. Phrase extraction based on minimum frequency of five, R2 = 0.813........................... 79 Figure 5.10. Correspondence plot of semantic concepts extracted from exercise #1 discourse R2 = 0.661 ..................................................................................................... 80 Figure 5.11. Frequency distribution of statements across the SES meta-category framework Chi2 =0.0.................................................................................................... 84 Figure 5.12. Distribution of group’s percent of total frequency for each categorical driver ............................................................................................................................ 85
  12. 12. List of Figures (Continued) Figure 5.13. Correspondence plot of categorical drivers by group.............................. 86 Figure 5.14. Frequency with which categorical framework drivers were ranked as either negative or positive............................................................................................ 87 Figure 5.15. Frequency with which emerging themes related to Institutional Arrangements were ranked as either negative or positive ........................................... 88 Figure 5.16. Frequency with which emerging themes related to Well-Being were ranked as either negative or positive............................................................................ 91 Figure 5.17. Frequency with which emerging themes related to Economics were ranked as either negative or positive............................................................................ 93 Figure 5.18. Frequency with which emerging themes related to Perceptions of the Environment were ranked as either negative or positive ............................................. 95 Figure 5.19. Correspondence plot of concepts extracted from the exercise #2 discourse ...................................................................................................................................... 98 Figure 5.20. Correspondence plot of concepts extracted from the exercise #3 discourse .................................................................................................................................... 100 Figure 5.21. Correspondence plot of concepts extracted from the exercise #4 discourse .................................................................................................................................... 104 List of Tables Table 3.1. List of likely categorical drivers of a social-ecological system.................. 21 Table 3.2. List of eight potential future scenarios presented to community groups .... 27 Table 3.3. Number of participants per group by gender .............................................. 33 Table 4.1. Definition of cohesion metrics and network structures used in analysis .... 42 Table 4.2. Definition for each centrality measure used in analysis ............................. 44 Table 4.3. Breakdown of network structures created for analysis ............................... 49 Table 4.4. Summary statistics of combined natural language text documents ............ 50 Table 4.5. Total responses/statements by group .......................................................... 50 Table 4.6. Total extracted words by group .................................................................. 50 Table 4.7. Number of concepts discussed by group..................................................... 50 Table 4.8. Cohesion measures for network derived from all five groups’ combined discussions ................................................................................................................... 51 Table 4.9. Cohesion measures for each group’s network derived from their combined discussion..................................................................................................................... 52 Table 4.10. Cohesion metrics for the combined network derived from exercise #1 ... 53 Table 4.11. Cohesion measures of individual group’s networks derived from exercise #1.................................................................................................................................. 53 Table 4.12. Cohesion metrics for the combined network derived from exercise #2 ... 54 Table 4.13. Cohesion measures of individual groups networks derived from exercise #2.................................................................................................................................. 54 Table 4.14. Cohesion metrics for the combined network derived from exercise #3 ... 55 Table 4.15. Cohesion measures for each group ........................................................... 55
  13. 13. List of Tables (Continued) Table 4.16. Cohesion metrics for the combined network derived from exercise #4 ... 56 Table 4.17. Cohesion measures for each group ........................................................... 56 Table 5.1. Concepts comprising the ‘Spatial and Temporal Scales’ theme. Weighted scores based on Jaccard Index...................................................................................... 61 Table 5.2. Concepts comprising the ‘Social and Organizational Dynamics’ theme. Weighted scores based on Jaccard Index..................................................................... 63 Table 5.3. Concepts that comprise the ‘Economic and Livelihoods’ theme................ 71 Table 5.4. Concepts comprising the ‘Environment and Resources’ theme ................. 74 Table 5.5. Shows the summary information from the Q-Method statements.............. 83 Table 5.6. Total and cumulative percent of the categorical frequency distribution of Q- statements..................................................................................................................... 85 Table 5.7. The most critical drivers from the Q-Method portion of exercise #2......... 97 Table 5.8. Group responses to choosing a tangible indicator of sustainability.......... 100 List of Equations Equation 4.1. TF*IDF Statistic ...........................................................................................45 Equation 4.2. Jaccard Similarity Index ..............................................................................46 List of Boxes (Quotes) Box 5.1. MPA team participant discussing difficulty in managing distinct geographic and cultural systems..................................................................................................... 64 Box 5.2. Natural resource manager discussing planning in the USVI......................... 64 Box 5.3. Eco-outreach participant discussing tension regarding the identity of a ‘Virgin Islander’........................................................................................................... 64 Box 5.4.Eco-outreach participant discussing the division of communities based on spatial areas.................................................................................................................. 64 Box 5.5. Farming co-op participant discussing difficulty in preserving traditional culture in the face of the development and demographic change ................................ 68 Box 5.6. MPA Team participant discussing the ‘brain drain’ that results due to lack of opportunity................................................................................................................... 68 Box 5.7. Hospitality group participant discussing lack of opportunity and high cost of living on the island as a motivating factor to leave St. Thomas .................................. 68 Box 5.8. Hospitality group participant discussing links between economic development and community marginalization............................................................. 70 Box 5.9. Farming co-op participant discussing marginalization of local community groups for the benefit of economic development......................................................... 70 Box 5.10. Hospitality group participant discussing the need for financial intervention ...................................................................................................................................... 71
  14. 14. List of Boxes (Quotes) (Continued) Box 5.11. MPA team participant discussing globalization’s impact on the local economy....................................................................................................................... 72 Box 5.12. Hospitality group participant discussing the lack of local ownership of business and its relationship to St. Thomas’s kinship with the United States ............. 72 Box 5.13. DPnR participant discussing lack of reinvestment in the community and the tendency for profits to leave island.............................................................................. 73 Box 5.14. Farming co-op participant discussing the need for more local business to create a self-sustaining community.............................................................................. 73 Box 5.15. Eco-outreach participant discussing pressure local businesses face due to increasing energy costs ................................................................................................ 73 Box 5.16. Eco-outreach participant discussing the role of community groups creating awareness of environmental and energy impacts......................................................... 74 Box 5.17. Eco-outreach participant linking economics as driving force for sustainable energy........................................................................................................................... 74 Box 5.18. Eco-outreach participant discussing lack of community control ................ 75 Box 5.19. MPA team participant describing the range of potential future changes .... 77 Box 5.20. Eco-outreach participate describing hope that the community will have more power in the future.............................................................................................. 78 Box 5.21. Eco-outreach participant describing energy as a driver for the ‘Pushed to the Limit’ scenario ............................................................................................................. 80 Box 5.22. MPA team participate describing past development strategies as contributing to local disempowerment......................................................................... 81 Box 5.23. DPnR participant describing the role of development in decision making processes ...................................................................................................................... 81 Box 5.24. Hospitality group participant describing how rising crime may begin to impact tourism.............................................................................................................. 81 Box 5.25. Participant discussing exclusion as a driver for ‘Pushed to the Limit’ scenario ........................................................................................................................ 82 Box 5.26. Examples of statements ranked by participants relating to ‘small community dynamics’..................................................................................................................... 88 Box 5.27. Examples of statements ranked by participants relating to ‘enforcement’.. 89 Box 5.28. Examples of negative statements ranked by participants relating to ‘leadership, planning and corruption’ .......................................................................... 89 Box 5.29. Examples of positive statements ranked by participants relating to ‘leadership, planning and corruption’ .......................................................................... 89 Box 5.30. Examples of positive statements ranked by participants relating to ‘community decision making’...................................................................................... 90 Box 5.31. Examples of statements ranked by participants relating to ‘poverty dynamics’..................................................................................................................... 91 Box 5.32. Examples of participants’ statements relating to ‘education’...................... 92 Box 5.33. Example of a participant’s statement related to ‘attitudes’ as a driver........ 92 Box 5.34. Examples of participants’ statements related to ‘economic disparity’ as a driver ............................................................................................................................ 93
  15. 15. List of Boxes (Quotes) (Continued) Box 5.35. Examples of participants’ statements related to ‘local economy supporting community’ as a driver................................................................................................. 94 Box 5.36. Examples of participants’ statements related to ‘business education’ as a driver ............................................................................................................................ 94 Box 5.37. Example of participants’ statements related to ‘environmental business’ as a driver ............................................................................................................................ 94 Box 5.38. Examples of participants’ statements related to ‘environmental awareness’ as a driver..................................................................................................................... 96 Box 5.39. Examples of participants’ statements related to ‘environmental ownership’ as a driver..................................................................................................................... 96 Box 5.40. Examples of participants’ statements related to ‘attitudes’ as a driver ....... 96 Box 5.41. Farming co-op participant describing sustainability in St. Thomas.......... 101 Box 5.42. Farming co-op participant discussing Rastafarian culture as it relates to stewardship................................................................................................................. 101 Box 5.43. Eco-outreach participant expressing anger towards the cost of energy in St. Thomas....................................................................................................................... 102 Box 5.44. Hospitality group participant discussing an idealistic version of sustainability .............................................................................................................. 102 Box 5.45. MPA team participant discussing sustainability as a process of decision making........................................................................................................................ 102 Box 5.46. DPnR participant discussing sustainability as a process of decision making .................................................................................................................................... 102 Box 5.47. Farming co-op participant linking a bottom up approach of governance to sustainability .............................................................................................................. 102 Box 5.48. Hospitality group participant discussing preparedness for the future ....... 105 Box 5.49. Hospitality group participant discussing preparedness for the future ....... 105 Box 5.50. Hospitality group participant discussing preparedness for the future ....... 105 Box 5.51. Hospitality group participant discussing preparedness for the future ....... 105 Box 5.52. Farming co-op participant discussing preparedness for the future............ 105 Box 5.53. Farming co-op participant discussing preparedness for the future............ 106 Box 5.54. Farming co-op participant discussing preparedness for the future............ 106 Box 5.55. DPnR participant discussing preparedness for the future ......................... 106 Box 5.56. DPnR participant discussing preparedness for the future ......................... 106 Box 5.57. Eco-outreach participant discussing preparedness for the future.............. 107 `
  16. 16. Community Perspectives on Sustainability and Resilience in a Social- Ecological Paradigm
  17. 17. P a g e | 2 Chapter 1: Introduction 1.1 Overview Environmental sustainability has become a paramount agenda for many nations across the globe (Jansen 2003, Jahn, Becker et al. 2009). As the earth’s population continues to grow exponentially, greater demands are being placed on its natural resources. The combined effect of population growth and the trend for globally dependent economies and natural resource use patterns (Young, Berkhout et al. 2006) have left the earth’s ability to continue to provide for human consumption and well- being in doubt (Hueting 2010). Historically, there has been limited research regarding the human dimensions and social science aspects of the relationships between natural resource health, management and conservation (Holling and Meefe 1996, Becker and Research 1997). However; the impact of humans on environmental processes and quality is nearly unavoidable (Vitousek, Mooney et al. 1997, Zalasiewicz, Williams et al. 2008). It is therefore an imperative to promote science and evidence-based methods for identifying, investigating and analyzing the complexity inherent in human- environment relationships in order to acquire resilient environmentally sustainable approaches to ecological problems. This need is certainly evident in the U.S. Virgin Islands, which is home to unique and bio-diverse coral reef habitats which have been negatively impacted by anthropogenic activity in the form of nutrient enrichment, sedimentation, increased disease, and coral bleaching (Noori and Taylor, 2008, Rothenberger, Blondeau et al. 2008). This thesis explores the collective knowledge dynamics of social and institutional groups as they relate to sustainability and resilience within a social- ecological system (SES) paradigm. This research serves as a pilot study to explore the use of participatory community based scenario planning exercises and semantic network analysis as a framework for capturing and understanding social knowledge dynamics relating to complex system trajectories and drivers as well as conservation stewardship. Field work for this project was done exclusively with long term residents
  18. 18. P a g e | 3 of the island of St. Thomas, USVI who comprised distinct social and/or institutional groups. This research has three primary objectives: a) to test the efficacy of scenario planning as a method of capturing social knowledge representations and mental models surrounding social-ecological dynamics, sustainability and resilience b) to explore the effectiveness and accuracy of using semantic network analysis as a means of quantifying and analyzing large bodies of qualitative natural language text and finally c) to examine similarities and differences in distinct community groups knowledge representations of the processes and structures that facilitate conditions positively or negatively related to sustainability and resilience. The broad research questions of this research are: 1) What are the collective perspectives of stakeholder and institutional groups regarding social-ecological dynamics as they relate to sustainability and resilience in St. Thomas specifically? 2) Do separate groups exhibit distinct and/or opposing perspectives of SES dynamics and sustainability as a defined and localized social construct? 3) Is there a common appropriate focal scale when considering the boundaries of SES dynamics within and across stakeholder and institutional groups? 4) What is the role of the natural environment and conservation embedded within these collective knowledge representations? 1.2 Background The basis and rationale for these questions is rooted in adopting social- ecological systems (SES) or Coupled Human-Nature Systems (CHN) perspective on sustainability and resilience as well as including recent findings related to system legacies, culture as a mediator of change, participatory natural resource management,
  19. 19. P a g e | 4 and polycentrism. The chapter will end with a brief discussion of the history and current state of the study site. 1.3 Field Methods Due to the complex nature of the research objectives mixed methods (i.e. both qualitative and quantitative methodologies) are used in order to provide greater breadth and depth to the analysis of the data gathered (Mathison 1988, Berg and Lune 2004). The research adopts a scenario planning focus group methodology and the protocol followed a script divided into four compounding exercises. The Q-Method (Brown 1996) was adapted and nested within one of the exercises to add quantifiable categorical data related to participant perspectives during the discussion. The four exercises included: 1) a conceptualization of the future direction of St. Thomas, 2) a ranking and discussion of the categorical drivers of change for that future direction (Q-Method) 3) discussing a collective definition of sustainability within the localized system and 4) discussing participants’ personal and shared preparedness for this expected future as a measure of social resilience. All four exercises combined took approximately one and a half to two hours to complete for each group. Focus groups were organized among stakeholder and/or institutional groups with social ties. To accomplish this, the research used a purposive strategic sampling method (Wilmot 2005) of identifying pre-existing group leaders and then relied on a snowball process methodology (Atkinson and Flint 2001) for the leaders to recruit other participants. In addition to the scenario planning exercises an analytical social-ecological framework was developed and consisted of eight (8) categorical drivers identified in the literature as likely primary drivers for social, economic and environmental systems (Larson, Alexandridis et al. 2009). The framework was used to gather quantified local and regional data to compliment the qualitative information obtained from the focus groups. Prominent drivers and variables that emerged during the focus group discussions were examined in the greatest depth and detail.
  20. 20. P a g e | 5 In total five focus groups took place over a six month period and included 32 long term residential participants, with a range of four to nine individuals per group. The project took place exclusively in St. Thomas, USVI. 1.4 Methods of Analysis Analysis of the focus groups followed a semantic network analysis process. Each focus group was audio recorded and transcribed verbatim into natural-language text documents. Following the identification of concepts and a latent semantic indexing process (Deerwester, Dumais et al. 1989), they were weighted based on the TF*IDF function (Ramos 2003) and a similarity matrix was created from the most important concepts and each relationship was given a Jaccard similarity coefficient. The resulting weighted matrix was then used as the basis of a network structure. Analysis consisted of examining the graph theoretic implications of cohesion metrics and centrality measures to identify the structural composition and key themes in the discourse. This chapter ends by demonstrating the superior nature of semantic network analysis in reducing large sets of qualitative text as well as some preliminary statistical results from the analysis. 1.5 Results Due to the large nature of the dataset the results chapter is broken into two sub chapter sections: 1) Universal themes from the discussions and 2) analysis of the individual exercises Section I: Findings from the first section indicated a great deal of shared knowledge regarding the drivers of St. Thomas as a social ecological system as well as regarding social resilience to the future scenario. From the semantic networks created from the combined exercises four broad themes emerged: 1) Temporal and Spatial Scales 2) Social and Organizational Dynamics 3) Economics and Livelihoods and 4) The Environment and Resources. When the patterns of connections of these themes were examined based on 25 semantic networks derived from the conversations some consistent and embedded factors emerged that appeared to inform the majority of each group’s discussion
  21. 21. P a g e | 6 regardless of the exercise. The first was the central nature of sense of place into participants’ perspectives on the potential changes that could occur. This sense of place was not only limited to the physical attributes of the island but the historical and cultural history of decision making, and interaction between communities within the island. Along with this were descriptions of disempowerment and economic disparity driven in part by a lack of identity and cohesion due to changing demographic profiles and a lack of a unified vision at the institutional level. Additionally there appeared to be cultural variations in how certain groups related to the natural environment. Groups whose members typically emigrated from the continental US tended to focus on the marine environment as their environmental reference point. Whereas groups comprised of locally born members tended to focus on agriculture and upland vegetation when linking the environment to livelihoods and stewardship. Section II: The second section, which analyzed each exercise independently, reiterates many of the universal factors informing participants’ perspectives. For instance, during exercise #1, due to the historic issues of economic disparity and disempowerment the consensus of all the groups was to choose a future scenario entitled ‘Pushed to the Limit’ in which social, economic and environmental limits are pushed to a critical state. Each group envisioned this taking place in a relatively short time frame within the next 5 – 15 years. During the Q-method portion of exercise #2, statements related to decision making, community development, local business, attitudes and governance were considered the most critical drivers. Specifically, increasing community decision making capacity, values, ownership and understanding were considered the most positive critical drivers whereas ineffective or incompetent governance and business patterns that exclude local participation were considered the most negative. The third exercise, which consisted of participants defining and describing sustainability in St. Thomas was the most difficult exercise for participants to engage in and produced the fewest responses and semantic concepts. However when asked to agree on a social indicator of sustainability groups reached consensus quickly, suggesting that the broader theoretical concepts such as sustainability may not be as effective for engaging communities, whereas place based real world concepts were identified as more effective. There was also further evidence of differences in
  22. 22. P a g e | 7 participants’ sense of place as it relates to the natural environment. The management teams, whose members are primarily transplants from the continental US, focused on the marine environment when asked to choose an indicator of sustainability whereas the other groups focused on alternative energy. The final exercise which comprised of participants discussing their preparedness for the future, concluded with feelings of vulnerability due to changing demographics, cultural loss, and the high cost of living. 1.6 Conclusions and Discussion The final chapter will discuss management considerations, a review of the methods used, some implications regarding globalization, culture and sustainability as a social construct as well as detail the ‘Top 5’ takeaways from the results of this research: 1) Despite the differences in livelihood and cultural backgrounds all the groups shared the same perspective regarding the future of the island. 2) People may need to feel hopeful about the future in order to plan for it. 3) When discussing the future in more detail, the most dominant social-ecological drivers included sense of place, the incorporation of community values and culture into decision making and economic processes and increased accountability at both the social and institutional level. 4) Management strategies need to include specific place-based items when engaging communities and solutions have to be customized to the community that is being addressed. 5) In addition conservation should be expressed using cultural and place-based ideals as opposed to theoretical or academic ones
  23. 23. P a g e | 8 Chapter 2: Background This Chapter will discuss some of the broad theoretical assumptions and key concepts informing the research questions and methods. The chapter will end with a brief discussion of the history and current conditions of the study site, St. Thomas, USVI. 2.1 Broad Theory Environmental Sustainability Throughout the 1960’s and 70’s the confluence of economic growth and environmental degradation became an issue of scientific and public concern (Czech 2000). This concern was in part spurred by such books such as “The Silent Spring” (1962), which documented the negative environmental effects of pesticides, “The Closing Circle” (1971), and the Club of Rome’s seminal 1972 paper “The Limits to Growth” which modeled and predicted that if the current rates of population and economic growth continued, the earth would experience significant social and environmental collapse by the mid-21st century (Meadows, Meadows et al. 1972, Czech 2000). This movement resulted in an intensive investigation into the framing and defining of environmental sustainability or ‘sustainable development (which included environmental, sociopolitical and economic stability as separate but equal partners) culminating in the UN sponsored 1987 Brundtland report entitled “Our Common Future” in which sustainable development was formally defined as development able to “meets the needs of the present without compromising the ability of future generations to meet their own needs” (World Commission on Environment and Development 1987). However, the lack of operational and theoretical specifics within this definition demonstrate that environmental sustainability as a concept is complex, subjective and includes a certain degree of ambiguity or volatility (Mebratu 1998, Loorbach, Frantzeskaki et al. 2011) This ambiguity has often led to misunderstandings or disagreements of measurements, indicators, inherent values and conceptual
  24. 24. P a g e | 9 definitions (Becker and Research 1997). These disagreements have in part been fueled by the prevalence of the multiple failures of management strategies based on perspectives from a single academic discipline such as species extinction and fisheries collapses related to ecologically based maximum sustainable yield (MSY) (Legović and Geček 2010, Legović, Klanjšček et al. 2010) and top down economic based environmental regulation resulting in market failure (Bromley 2007). Consequently, contemporary scientific approaches to natural resource management have largely come to understand that there are substantial gaps in understanding the patterns of human and environmental interactions from a trans-disciplinary perspective (Chapin, Kofinas et al. 2009, Jahn, Becker et al. 2009). A trans-disciplinary approach has recently been explored within the realms of complexity science which seeks to include human actors and systems within an environmental perspective (Berkes 2003, Folke 2005). This perspective is essential as humans are not simply biological actors within a system but are also psycho-social contributors to the construction of society and therefore its natural resource use (Samet 2011). In addition to this, both the objective biological and physical realities combined with the social constructs about them influence how we interact, learn and exchange knowledge and information within and across social groups and roles. Social-Ecological Systems Theory and Environmental Sustainability A complexity science approach towards environmental sustainability invites some non-traditional perspectives on environmental sustainability. For instance, traditionally, environmental sustainability has referred to the positive normative quality of an ecological system to persist efficiently within equilibrium. Positive normative quality in this context refers to sustainability being an ideal standard based on the values and rational of a contemporary society (Becker and Research 1997). This is at odds with the complexity science perspective that asserts that both human and natural systems are frequently out-of-equilibrium systems that persist based on a constant flux of dissipative interactions and adaptations at varying temporal and spatial scales, rather than steady state equilibrium based systems (Samet 2011). The latter preposition coincides with the notion that societies co-evolve with their
  25. 25. P a g e | 10 environment and are therefore not only inseparable, but function within an hierarchical complex adaptive system (Holling 2001). Within this hierarchical system, change occurs on different layers at varying temporal and spatial scales based on the feedbacks, threshold, and social learning mechanisms of human systems as they relate to, impact and are impacted by their environment (Holling 2001, Sawyer 2005). This has been supported empirically in research that has observed that not only do humans largely dominate natural ecological processes (Vitousek, Mooney et al. 1997, Zalasiewicz, Williams et al. 2008) but that natural processes and ecological conditions also shape (i.e. act as boundary or anchoring mechanisms for) human behavior and decision making processes (Hammer 2003, Lambin and Meyfroidt 2010). In Europe this conceptualization of a hierarchical complex adaptive system is referred to as Social-Ecological Systems (SES) Theory, and in the United States it is referred to as Coupled Human and Natural Systems (CHNS) Theory. Formally, the term Social- Ecological System is used to emphasize, “that the delineation between social and ecological systems is artificial and arbitrary.”(Folke 2005). (See figure 2.1) Figure 2.1. Visualization of social-ecological or human-coupled systems theory (Source: NSF, 2012) This theoretical perspective serves to emphasize that since concepts such as ecological thresholds, biodiversity, inter and intra-generational equity and human well-being are all important aspects of environmental sustainability; the relationships
  26. 26. P a g e | 11 between the social, cultural, economic and ecological systems are inherent contributors to understanding environmental sustainability from a real world perspective (Walker, Anderies et al. 2006, Moldan, Janoušková et al. 2011). This conceptualization of environmental sustainability has led to substantial research that has sought to not only include but link sustainability and resilience as independent but related constructs (Holling 2001, Walker, Holling et al. 2004, Derissen, Quaas et al. 2011, Loorbach, Frantzeskaki et al. 2011). Environmental Sustainability and Social-Ecological Resilience While environmental sustainability encompasses the stability of interactions within the SES, social-ecological resilience refers to the capacity of the SES to adapt to change, absorb, fend off, and/or mitigate disturbances (Holling 2001, Olsson 2003). The concept of resilience originates from C.S. Holling (1973) and was initially used to describe an ecological system’s ability to ‘bounce’ back to an equilibrium state after a disturbance. This has since been re-defined as ‘engineering resilience’ (Walker, Anderies et al. 2006). Within SES theory, resilience refers to a SES’s ability to “buffer a great deal of change or disturbance” and is “synonymous with ecological, economic and social sustainability.” (Berkes 2003). However; within this definition there is no one equilibrium state to return to as there are multiple domains of attraction and equilibriums that are in the process of change and adaptation. From this perspective resilience is promoted by nurturing diversity, variability, and functional redundancy instead of maximizing efficiency of any one given system or sector. As noted earlier, this approach is validated by the frequent failure of quantitative environmental targets within sustainability management and linear equilibrium based modeling within SES (Berkes 2003). Social-Ecological resilience is largely informed by the inherent complexity of the system as a whole and the inevitability of disturbances and change (Holling 2001, Anderies, Janssen et al. 2004). However, what is not well understood are the social structures and processes that increase the adaptive capacity of a SES (Olsson 2003). To understand how to successfully manage a sustainable system one must not only understand the dynamics and complexities of the
  27. 27. P a g e | 12 system but understand how to manage for uncertainty, adaptation and change often within a polycentric social environment. 2.2 Key Concepts The Role of Legacies and Culture One of the defining characteristics of complex adaptive systems and therefore social-ecological systems is that of legacies and path dependence. Social-ecological systems, both the ecological and social aspects, are shaped by events in their history creating a legacy. These legacies create a path dependence where past events and decisions strongly guide and shape future action (Chapin, Kofinas et al. 2009). Consequently, trends or patterns that are more severe or difficult to reverse create stronger path dependence as returning to an earlier state becomes more difficult. It is for this reason that culture can act as a primary driver of a system’s reaction to change as it is the history, values, beliefs and norms of the society that are going to inform their behavior and therefore the changes, and reactions to changes, within and to the system. This subject was extensively considered in the collection of essays entitled “Culture Matters” that demonstrated that the success and failures of many nations and societies lie not only on their interactions with other nations, geographic location and natural resources reserves but on the way they interpret and respond to crisis, change and opportunity (Harrison and Huntington 2001). This can explain, to a degree, why although economic development and regulation has the potential to create conducive environments for democratization and equitability within a given society, top down forcing can be ineffective without proper culturally appropriate consultation and dissemination at the local level (Hartter and Ryan 2010). No Panaceas and the Bottom-up Approach Further research has also established that the contextual nature of culture, legacy and path dependence suggests that panaceas, or globally optimal solutions applied to localized problems, are insufficient and ineffective and that a bottom up approach, or the very least bottom up support and value alignment, is necessary to
  28. 28. P a g e | 13 establishing self-regulating sustainable management regimes (Dietz, Ostrom et al. 2003, Ostrom 2007). Nobel Laureate Eleanor Ostrom’s work demonstrates that those communities where self-regulating behavior and ideals were embedded into the culture were more equitable and more successful stewards of the environment than those who were managed with a top down approach. These empirical findings emphasize the scientific imperative to understand community dynamics, local knowledge, beliefs, norms and visions as well as natural environmental science when considering sustainability. Polycentricism and Organizational Cooperation The complexity within social systems is further compounded when considering that most commons and resources are used by polycentric communities. Polycentric refers to community dynamics which are characterized by many centers of authority and institutional organization. These centers could be represented by different ethnic, social or cultural groups as well as management groups at varying scales. Such communities may interpret system dynamics, quality and uses differently depending on their organizational and governance structure, relationship with the environment, livelihoods and cultural history. This lends itself to the potential that even within local social-ecological scales, different stewardship, livelihood and social groups may require different strategies and approaches to achieve sustainable solutions. However; research has suggested that success greatly relies on social cohesion and the ability of different stewardship and resource related livelihood groups to collaborate or co-exist effectively, especially in areas with diverse populations (Sherman, Snodgrass et al. 2010). 2.3 Study Site: The United States Virgin Islands (USVI) The United States Virgin Islands, like much of the Caribbean, exists as an “imaginary of paradise” for many people around the globe; conjuring up images of sandy beaches, idyllic weather, rum and clear blue ocean. But beyond the oasis of a tropical Eden, is an island culture that has been shaped by a long history of changing
  29. 29. P a g e | 14 occupancies, globally dependent economic trade, and to a large degree, slavery and colonialism (Pattullo 1996). The United States Virgin Islands is an unincorporated territory of the United States that consists of approximately 50 cays and islands. They are located in the Caribbean Sea between 18º 20N and 64º 50W and are part of the Virgin Islands archipelago located in the Leeward Islands of the Lesser Antilles (see figure 2.2). The USVI has three main populated islands; St. Croix, St. Thomas, and St. John. St. Croix is the largest, and geographically flat, of the islands at 82.88 square miles with a maximum elevation of 1,165 ft. St. Thomas is the second largest at 31.24 square miles and is characterized by a steep topography with a maximum elevation of 1,555 ft. St. John is the smallest of the three main islands at only 19.61 sq. miles, 60% of which is national park, and a maximum elevation of 1,277 ft. Figure 2.2. Map of the USVI in context of the Caribbean region Brief History of Development in the Caribbean Region Over the centuries following Columbus’s first visit to the Caribbean in the 15th century, the majority of Caribbean islands were settled as colonies by various European countries and nearly all islands were under European jurisdictions by the
  30. 30. P a g e | 15 18th century. The first settlers primarily consisted of wealthy white investors and indentured servants, with the aim of producing tobacco. Following a collapse in the tobacco market in the 1600’s however, most islands converted to plantation economies that produced sugar cane on a global scale (Cornwell, Stoddard et al. 2007). During this period population dynamics shifted dramatically from almost exclusively white European settlers to predominantly Africans whom were forced to the islands as slave laborers. The sudden rise in population created a strong dependence on fisheries for coastal communities including subsistence, artisanal and semi-industrial types (Salas, Chuenpagdee et al. 2011). The dependence of these communities on fisheries contributed to both the transformation and diminished resilience of critical coral reef habitats throughout the region (Hawkins and Roberts 2004). Although the vast majority of economic activity was dedicated to agriculture, and would continue to be for the next three centuries, tourism began to develop in the 18th century with the first hotel erected in 1778 in Nevis, Bahamas. From there, luxury tourism grew slowly throughout the 19th Century predominantly in the Bahamas and along the Windward islands. Due to the financial cost and time it took to traverse to the Caribbean from Europe, the typical tourist was very wealthy and often only visited islands within their respective colonies. Starting in the 18th through to the 20th century many colonies became sovereign independent nations, with their own evolving political, economic and cultural systems. Despite their independence however, Caribbean islands uniquely share a common heritage, “molded by slavery, colonialism and the plantation.” (Pattullo 1996). While many islands became independent nations, their economic structure remained tied to global markets. Agricultural production remained the core export even as slavery was abolished and labor markets shifted. However; the rising costs of labor and decline in global sugar prices coupled with increasing development and education of the workforce made sugar cane production less tenable. As sugarcane production weakened, islands shifted to mass tourism based economies requiring large scale infrastructure and hotel development (The Caribbean Centre for Development
  31. 31. P a g e | 16 Administration, 2007). Despite the general elevated education of the working class and development of the region, the type of tourism that flourished had a direct connection to the plantation era. As an economic enterprise tourism still served those outside the region, namely wealthy North Americans and Europeans. (Cornwell, Stoddard et al. 2007). Beginning in the late 60’s the branding of tourism in the Caribbean centered around “Sun, Sand and Sea” which developed into what has been referred to as tropical or “Natural Hedonism” (Sheller 2004). Where Caribbean islands and environments were conjectured to be “pieces or paradise” or “the garden of Eden before the fall” (Pattullo 1996). The Caribbean was not only then prized for its pristine and exotic natural environments but for the “temptations and corruptions of the new Eden” with tourism marketing emphasizing “sensual stimulation, luxuriant corruption, ease and primitivism” (Sheller 2004). This has had an objectively detrimental effect on the environment (Pattullo 1996). As air travel and cruise ships became cheaper access to the Caribbean increased bringing an influx of visitors each year resulting in an estimating 37 million annual visitors to the region by 2005. However; just like sugar cane production, dependence on the global market has left the region vulnerable. In part due to the global recession, annual tourism visitors have been declining in recent years resulting in only 23 million in 2011 (Caribbean Tourism Organization, 2013). Brief History of the U.S. Virgin Islands The settlement and development of the Virgin Islands mirrored that of much of the Caribbean. Christopher Columbus first visited the islands in 1493, and subsequently gave them the name ‘Virgin Islands’. But it wasn’t until the 17th century that Denmark formally settled St. Thomas and St. John in 1672 and 1694, respectively. In 1773 they purchased St. Croix from France and combined the three islands together as the Danish West Indies. Similar to other islands the importation of slave labor was directly related to mass agricultural development in the form of plantations which were predominantly on St. John and St. Croix. St. Thomas was, and still is, primarily a center of trade and tourism. When slavery was abolished in the mid 1800’s many
  32. 32. P a g e | 17 plantation owners abandoned their property and the populations St. John and St. Croix declined substantially. In 1917, the US purchased the three islands and used it as a military outpost governed by naval administration. It wasn’t until the Organic act in 1936 that the islands officially became a US territory and native Virgin Islanders were given citizenship. Since then five separate constitutional conventions have taken place but none have been accepted by the President or congress of the United States. Despite being part of the United States, the Virgin Islands economy continued to rely heavily on global sugar cane markets. Agricultural production continued throughout the 20th century in St. Croix but in 1956 the majority of St. John was given to the National Park Service and today nearly two-thirds of St. John is national park. Like most of the Caribbean, by the mid-20th century as the price of sugar dropped there was a substantial shift towards tourism. Subsequently, tourism has taken over as the primary economic activity with approximately 2.3 million visitors flocking to the USVI annually to indulge in the three S’s of tropical vacationing: Sun, Sand and Sea. In fact, according to the Caribbean Tourism Organization approximately 10% of tourists visiting the Caribbean will visit the USVI (Caribbean Tourism Organization, 2013). Current Conditions According to the 2010 United States census, the population of the US Virgin Islands is approximately 106,405 residents. This is evenly split between St Thomas with 51, 634 (48% of total) and St. Croix with 50,601 (48% of total). St. John is significantly less populated with only 4,051(4% of total) residents. Of that population, approximately 44% were natively born in the USVI, 35% emigrated from Afro- Caribbean countries and 17% immigrated from either the continental United States or Puerto Rico. In 2011, tourism’s total contribution to the USVI’s GDP was 35% accounting for approximately 40% of the total jobs including those indirectly supported by the industry. The island receives approximately 2.3 million tourism visitors each year, 2.2 million from cruise ships and approximately 600,000 from air arrivals. Of these visitors 2.2 million arrive and stay on St. Thomas exclusively (VI
  33. 33. P a g e | 18 Bureau of Economic Research, 2013). Despite this enormous relative influx of visitors, the USVI suffers from a high cost of living and at least 20% of the population subsists under the poverty line based on the national average (U.S. Census Bureau, 2013). This subsequent increase of development to accommodate the high density of tourists visiting St. Thomas each year has resulted in undesirable environmental impacts. The mass tourism development coupled with the steep topography (the island raises from sea level to 1,500 feet despite being only three miles wide) and impacts from global warming have resulted in significant coral reef decline in the territory. St Thomas is nearly entirely surrounded by hard bottom coral reef cover, including both near and off shore reefs. Three separate assessments over the last nine years have found the state of the VI’s coral reefs to be in steady decline, primarily from anthropogenic sources and the effects of climate change (Rothenberger, Blondeau et al. 2008). Poor land development, non-point sources of sedimentation, dirt roads and disturbed areas are the largest pollutant sources by volume to St. Thomas watersheds (Noori and Taylor, 2008). These problems are exacerbated by a two tier coastal development plan. This two tier system persists despite the fact that the steep topography assures that activity higher up will immediately effect or compound impacts at the coastal level (Rothenberger, Blondeau et al. 2008). Currently there is no comprehensive integrated coastal and land management plan in effect (Noori and Taylor, 2008). The severity and nature of the environmental problems facing the island (i.e. non-point source pollution, sedimentation, etc.) suggests that direct and traditional management efforts may be difficult to enforce and implement. This also suggests that a greater understanding of the community’s perspective of the complex systemic issues facing the island may create space for efficient and effective management actions.
  34. 34. P a g e | 19 Chapter 3: Field Methods 3.1 Overview Due to the complex nature of the research objectives mixed methods (i.e. both qualitative and quantitative methodologies) were used in order to give greater breadth and depth to the data gathered. (Mathison 1988, Berg and Lune 2004). For this study we developed a focus group interview protocol that was approved by the University of the Virgin Islands Institutional Review Board (IRB). The focus group protocol was centered on scenario planning methodologies. The protocol followed a script divided into four compounding exercises. The Q Method (Brown 1996) was adapted and nested within the second exercise to add quantifiable data related to participant perspectives during the discussion. The four exercises included: 1) a conceptualization of the future direction of St. Thomas, 2) a ranking and discussion of the categorical drivers of change for that future direction (Q-Method) 3) discussing a collective definition of sustainability within the localized system and 4) discussing participants’ personal and shared preparedness for this expected future as a measure of social resilience. (See figure 3.1 below).
  35. 35. P a g e | 20 Figure 3.1. Scenario planning protocol of compounding exercises All four exercises combined took approximately one and a half to two hours to complete. Focus groups were organized among stakeholder and/or institutional groups with social ties. To accomplish this, the research used a purposive strategic sampling method (Wilmot 2005) of identifying pre-existing group leaders and then relied on a snowball process methodology (Atkinson and Flint 2001) for the leaders to recruit other participants. In addition to the scenario planning exercises an analytical social-ecological framework was developed and consisted of eight (8) categorical drivers identified in the literature as likely primary drivers for social, economic and environmental systems. The framework was used in the form of a handout to operationalize, and provide a common background and starting point, of the concept of a SES within and between focus group discussions. When possible quantified local and regional data relating to these categorical drivers was used to compliment the qualitative information obtained from the focus groups. Prominent drivers and variables that Exercise #4 Preparedness for the Scenario Discuss Social Preparedness for Future Scenario Discuss Personal Preparedness for Future Scenario Exercise #3 Defining Sustainability Define Sustainability in St. Thomas Choose Visible ‘Indicator’ Exercise #2 Connecting Scenario to Present Conditions Rank 6 Most Positive and Negative Drivers for Future Scenario Discuss the Role of the Drivers in the Future Scenario Exercise #1 Choosing a Future Scenario Choose and Describe Potential Future Scenario Choose a Time Frame for Future Scenario (5,10,15 Years)
  36. 36. P a g e | 21 emerged during the focus group discussions were examined in the greatest depth and detail. In total five focus groups took place over a six month period and included 32 long term residential participants, with a range of four to nine individuals per group. The project took place exclusively in St. Thomas, USVI. This chapter ends with a brief discussion of experiences and lessons learned from the field regarding recruitment and study design. 3.2 Social-Ecological Framework Framework As environmental sustainability could have many meanings to many people it was an issue of concern regarding how to create an interview protocol that could capture a multiplicity of perspectives and introduce the concept of complexity (i.e. social-ecological systems theory) into environmental sustainability; a necessary component for an accurate assessment (Becker and Research 1997). In order to operationalize the complexities of sustainability within an SES paradigm during the focus group process we created a handout of categorical drivers and related variables that participants could consider and discuss during the second and third portion of the scenario planning exercises (See appendix A). More will be discussed about the use of this handout in subsequent sections. The categories included: Table 3.1. List of likely categorical drivers of a social-ecological system Population Demographics Economics Infrastructure and Services Institutional Arrangements Individual Well-Being Environment and Resources Cultural Properties Perceptions of the Environment The categorical drivers identified were adapted from ones previously reported in the relevant literature (Larson, Alexandridis et al. 2009) and were developed as a
  37. 37. P a g e | 22 suggestive synthesis of social, environmental and economic assessment criteria. The use of this framework structured the discussions in such a way that the boundaries of the variables being discussed were consistent and therefore comparable across stakeholder groups. The framework also established an analytical foundation of the concepts discussed that aided a shared understanding of the focus group discourse among group participants. Knowledgebase For critical categories identified through the scenario planning process, a knowledgebase of quantified real world information was developed to compliment the qualitative nature of the fieldwork data analysis. In this way, the perspectives regarding the variables within the system were compared to real-world quantified data to aid in the identification of, as well as assess the capacity and/or efficiency of, both social and economic drivers within the closed social-ecological system. Simultaneously, this comparison process was used to assess the accuracy of participants’ assumptions regarding the internal mechanism of the social-ecological system. 3.3 Scenario Planning Focus Group Discussions Scenario Planning Scenario planning became a popular methodology for corporate businesses after it was successfully utilized by Shell Oil during the OPEC oil embargo in the 1970’s. Since then it has been adopted by scientific as well as private and international government and non-governmental organizations in efforts to create a shared vision of the future, a shared vision for reaching that future and as a method of embracing uncertainty. Scenario planning is described as “contemplating your future to better understand your present” (Hammond 1998). In this vein, scenario planning typically operates by envisioning multiple plausible future states based on potential circumstances resulting from current trends or world views. A technique referred to as
  38. 38. P a g e | 23 ‘back casting’ (Vergragt and Quist 2011) is then implemented, where participants and/or researchers attempt to better understand the specific processes that would link the present and future states. This is to say; by considering how future changes might affect the system we can learn a great deal about how the system currently operates. In the case of Shell Oil, the management groups considered the potential variability of oil prices. They ran scenarios based on dramatic changes in the cost of a barrel of oil and then considered the likely behavior of the government as well as their competition in order to structure loose action plans in the event of any given scenario occurring. They used this process to great success through both the oil embargo in the 70’s and extreme fluctuations in prices during the mid to late 1980’s (Chermack, Lynham et al. 2001) More recently, this process was used by researchers in Arizona to engage stakeholders on water management issues resulting from rapid urban development. By generating potential growth patterns and waste use availability and changes using GIS, researchers were able to engage and better understand stakeholder perspectives on the complexities surrounding historically divisive problems and development prioritization related to water use (Scott, Bailey et al. 2012). These successes are due in part to the emotional and intellectual preparation of unforeseen events occurring as well as the incidental social and institutional learning that takes place during the scenario planning process. Findings from (Stout, Cannon-Bowers et al. 1999) indicated that the use of scenario planning with focus group teams improved social learning and efficiency within collaborative projects and could be used to assess the ability of groups to construct a shared mental model regarding the dynamics of the systems examined. The theory follows that this process can create an opportunity for participants to holistically consider inter system variables, externalities and expand their bounded rationality (Chermack 2005). Scenario Planning has been considered particularly useful when examining sustainability within a system’s context (Lempert, Popper et al. 2003). This is due, in part, because scenario planning is designed to assess uncertainty by exploring the range of potential for change (Chermack 2005). This is a paramount concern, as the complexities inherent within a social-ecological system, and therefore within environmental sustainability, creates a high degree of uncertainty. When examining
  39. 39. P a g e | 24 the system as a whole the potential directions for change are multiple and difficult to predict (Newman 2005, Folke 2006). Focus Groups Focus groups were exclusively used in an effort to investigate the collective frame of references for environmental sustainability. Focus groups are increasingly becoming a popular way to capture social perspectives in qualitative data (Berg and Lune 2004). In general, focus groups create a ‘brainstorming’ effect in which participants challenge or expand each other’s mental models regarding the discussion topic. Due to the highly intellectualized concepts within this research design, focus groups were considered especially critical as they create an environment that promotes an iterative process that moves beyond heuristics. Ideally, to a deeper understanding and perhaps alteration of participants’ mental models (Chermack 2005). For instance, it is unlikely in this research design that a single individual would have the capacity to fully imagine the causal layers and relationships of environmental sustainability and SES resilience (Lempert, Popper et al. 2003). The use of focus groups has also been shown to facilitate a collective intelligence greater than any one individual contributor and a more robust generation of ideas (Woolley, Chabris et al. 2010). In addition to a higher collective intelligence, focus groups often capitalize on what has been termed ‘crowd wisdom’ in which group of non-experts combined answers to issues of spatial reasoning, quantity estimation, impact and general knowledge are often more accurate than a single expert, see (Surowiecki 2005) for a comprehensive look at this phenomenon. The expectation then was that the combined use of scenario planning, a SES framework, and focus groups would increase the potential for the exposure of non-transparent, hidden and unintuitive relationships or associations between drivers as well as the perceived strength in the relationship between those drivers. This process also allows for the research to investigate the relative degree of pluralism or conflict in perspectives is exhibited both within and across groups.
  40. 40. P a g e | 25 3.4 Scenario Planning Exercises While Scenario Planning lacks a unified theoretical and methodological foundation there are several schools of practice and thought within the discipline (Chermack, Lynham et al. 2001). Within this variation, scenario planning was executed as exploratory assessment tool rather than a policy or planning oriented series of exercises. The focus group research design we employed consisted of four primary compounding exercises and took approximately one and a half to two hours to complete. Each group was facilitated by the same researcher and followed a standardized basic script for the introduction and framing of each exercise. Exercise #1 ‘Choosing a Future Scenario’ One of the most fundamental aspects to scenario planning is the consideration of plausible future states. As the concepts being investigated would not benefit from exploring ungrounded or extreme scenarios, participants were presented with a list and description of eight (8) potential future states based on previously analyzed global trends (see appendix B for a copy of the handout). Each plausible scenario had a theme that dominated that potential future state. The futures presented were: Money Matters – Imagine a future where market forces drive decision making at a local and global level. Economic markets and livelihoods become increasingly globally dependent. (Theme originally proposed as ‘Market Forces’ by (Hammond 1998)). Community Rules – Imagine a future where power and decision making is increasingly in the hand of local communities, neighborhoods etc. The community in general is empowered and engaged in both political and institutional activity. This theme is derived from trends based on participatory community based management, See (Chambers 1990) for example.
  41. 41. P a g e | 26 Science and Technology – Imagine a future where science and technology is the driving force behind decision making. In this future state science is directly incorporated into management and government decision making. Social media and the internet are accessed and utilized by leaders and stakeholders alike to shape the future. (Theme originally proposed by (Hammond 1998)). Knowledge and Application – Imagine a future where education is heavily emphasized and prioritized. The spread and transfer of knowledge is streamlined and encouraged among decision makers and users alike. This theme is based on recent ideas on the co-production of knowledge from the bottom up. See (Sato et al, 2012) for example. Eco-Matters – The most idealistic of the future trends, imagine a future where the whole is considered above the individual. In this trend people tend to prioritize the needs of the environment over their individual needs. This theme is based on the tradition of eco-activism, often prominent among action based researchers, NGO’s and active environment movement program. Regional Development – Imagine a future where decision making emphasis is at the regional level and rather unconnected at national or global scales. This theme is based on regional management, governance and policy approaches often used (e.g. the European Union). Pushed to the Limit – Imagine a future characterized by decision makers and communities that do not respond to change or issues until there is a collapse or once a limit has been reached. In this trend there is a great deal of reactionary behavior and very little proactive planning. This theme is a spin-off of the tipping-point and complex adaptive systems school of thought. See (Gladwell 2006) for a comprehensive look at this phenomenon.
  42. 42. P a g e | 27 Fooled by Randomness – This future scenario was used a control scenario in that it has no discernible trend or theme dominating it. Imagine a future where all changes are unexpected and their causes are not understood. Table 3.2. List of eight potential future scenarios presented to community groups Money Matters Community Rules Science and Technology Knowledge and Application Eco-Matters Regional Development Pushed to the Limit Fooled by Randomness During this exercise participants were asked to collectively consider the future state that they would like to focus on for the subsequent exercises. Participants were instructed that the future states provided were merely guidelines to keep the conversation within the bounds of the plausible and that they may mix and match potential trends and even create their own unique localized state if they chose to. During this exercise the group was also asked to define the appropriate scale of examination, with the explicit mention of either a specific watershed, St. Thomas as a whole or the entire USVI. Participants were then asked to 1) briefly describe the future based on the trend they chose 2) choose an approximate time frame for this future (either 5, 10 or 15 years in the future) as well as 3) a rationale for why they chose that future and time frame. Exercise #2 ‘Connecting the Scenario to Present Conditions’ Once the initial time frame and scenario had been chosen the next exercise involved defining the critical drivers that would contribute to the future described. At the start of this exercise participants received the SES framework handout that detailed the categorical drivers along with lists of potential variables for each category to consider. However, they were instructed that they were not limited to discussing the specific variables listed and could explore any relevant variable. We also adapted and nested the Q-method in this exercise by asking participants to use sticky pads to write
  43. 43. P a g e | 28 down the 6 most critical variables using an ipsative scale in which they qualified and ranked the drivers from the three most negative to the three most positives. An ipsative scale refers to a measure in which participants ranks statements in relation to each other. Which is to say that the third most negative statement is inherently more negative than the second most negative statement. In this context the statements are not compared across individuals but instead in relation to each other. This is in line with the notion that Q-method should always use factor analysis as opposed to means testing when examining rankings. The Q-method was first developed by William Stephenson in the mid-20th century and established the “Science of subjectivity” (Brown 1997). In short, Q- method functions under the assumption that subjectivity itself is both ubiquitous and axiomatic. Therefore there is substantial value in investigating and understanding subjective “states of mind” compared to the limiting and sometimes tautological traditional variables derived from pre-existing test or measuring devices. Q-method uses a theory coined operant subjectivity to capture individual perspectives on a phenomenon or topic. Typically this occurs by a researcher gathering 20 or 30 Q-sorts (or statements related to the topic of inquiry) from previous interviews on the subject within the target audience. The subjects are then presented with the Q-sorts and asked to rank them in importance to the topic on a scale of -3 to +3 (sometime -5 to +5, depending on number of sorts). The scores are then evaluated on an individual basis and factor analysis is used to determine emerging perspectives on the topic based on how participants ranked the statements. Factor analysis is the only appropriate method of analysis for this method as its underlining theory dictates that the Q-sorts have no pre-existing meaning and the process itself is meant to investigate the emerging perspectives of participants without value assumptions. Therefore it would be inappropriate to use variance based statistics to evaluate answers. For a comprehensive look at the Q-method see (Brown 1996). This method is suitable to this project as it a naturalistic method to capture states of mind regarding a complex topic. This research process deviated from traditional approach in that, instead of using pre-determined Q- sorts, participants were asked to create and rank their own Q-sorts within the activity. The goal of doing this process was to minimize participant time and energy within the
  44. 44. P a g e | 29 process and to capitalize on the “crowd wisdom” effect discussed earlier by creating the statements from aggregate responses from the group. For this reason, following the individual rankings, participants were asked as a group to reach a consensus on a ranking scheme for each other’s statements. Because the Q-sorts were not pre-determined there were no (or few) identical statement provided by participants. Therefore the categorical drivers outlined in the SES framework handout were used as an analytic framework. During analysis, each variable written down and ranked was coded to match one of the eight (8) categorical drivers from the framework. Any variables ranked that were not explicitly listed on the handout were grouped into the category that best encompassed the intention of the statement provided. Figure 3.2. Research team setting up and waiting for focus group participants to arrive to Rastafarian Farming Co-op focus group discussion in Bordeaux, St. Thomas USVI After each participant wrote the drivers down they presented them to the rest of the focus group, following everyone’s presentation a general discussion of the topics addressed was held.
  45. 45. P a g e | 30 During a focus group discussion with a group from a Rastafarian farming Co- op, the discussion took place in an outdoor place which did not lend itself to using sticky notes. In this instance, the nine (9) participants discussed the drivers in a free form manner and their exact text was later used to approximate a driver and ranking. Exercise #3 ‘Defining Sustainability’ Following the in-depth discussion of the negative and positive drivers of the future state, participants were asked to describe and define sustainability within the SES paradigm using St. Thomas as the focal scale. Along with this discussion they were asked to agree by consensus on one visible, tangible indicator of sustainability. This concept was largely borrowed from (Levett 1998)’s ‘Headline Indicator’ in an effort to explore the potential for creating visible short term management goals of socially derived sustainability indicators. Exercise #4 ‘Preparedness for the Future Scenario’ In the final exercise, participants were asked to discuss issues of social resilience regarding the future state they discussed. The discussion was divided into three scale related sub-questions: 1) how prepared is the island for this future? 2) How prepared is your social group (friends, occupation and industry) and 3) how prepared is your family and yourself personally? 3.5 Sampling Design Participant recruitment began in August, 2012 and ended January, 2013. As this thesis is a pilot intended to feed into a larger project, this research approach used purposive sampling (Wilmot 2005) that was limited in scope but targeted social and institutional groups that are characterized by natural resource dependent livelihoods in St. Thomas, USVI. Recruitment of participants followed a ground-up snowballing process methodology (Atkinson and Flint 2001). In this case, the combination of purposive and snowball methodology involved the targeted contact of a leader within a specific social or institutional group and then that leader would invite or bring
  46. 46. P a g e | 31 between three to eight other members to participate. This established a randomization procedure and minimized researcher bias in sampling. When possible the facilitator only met with one member of the group prior to facilitating the discussion. All participants were required to be at least 18 years of age. The minimum size of an accepted group was four participants. In total, 32 individuals took part in the study comprising five livelihood or natural resource management groups. Each group had between four (4) to nine (9) participants. The five groups were: 1) the core management team of a recently developed MPA site (MPA Team) 2) an informal social group of members who worked in tourism related occupations (Hospitality Social Group) 3) Local government natural resource managers (DPnR) 4) Members of a Rastafarian Farming Co-op (Rastafarian Farming Co-op) and 5) a group of volunteer environmental educators, many of which were members of federal environmental management agencies (Eco-Outreach Group). There was some connectedness between the participants regarding group membership. In fact, the recruitment of the fifth group was the result of suggested contacts from participants in the first and third groups whom were also members of the fifth group. However; no one participated in more than one group. A community plot network graph illustrates the connected professional nature of the relationships between participants. In this graph nodes indicate a participant ID number and the links represent relationship between participants (see figure 3.3).
  47. 47. P a g e | 32 Figure 3.3. Community plot of relationships between focus group members Following the focus group discussion, participants were issued an exit survey asking for comments regarding the process and their basic demographic information. Of those that participated, 25 were born locally or grew up on the island, five (5) were from the continental US but had lived on the island for five plus years and two (2) emigrated from international countries. The five continental and one of the international immigrants were divided between the MPA Team and DPnR groups. The other three groups were comprised of nearly entirely participants who were born in the USVI. Additionally, within the first six months of organizing these focus groups, four of the five participants who were from the continental United States either moved off island or no longer work/associated with their respective focus group. The change in participant’s status is indicative of issues discussed during the focus groups relating to the transient or short term nature of immigrant residency on the island. Sampling was relatively evenly divided between male and female with 17 female participants and 15 male (see table 3.3). DPnRMPA Team Eco-Outreach Group Rasta Farming Co-op Hospitality Social Group
  48. 48. P a g e | 33 Table 3.3. Number of participants per group by gender Group Participants Male Female Livelihood/Orientation #1 4 1 3 MPA Management Team #2 5 4 1 Hospitality Social Group #3 5 2 3 DPnR #4 9 7 2 Rastafarian Farming Co-op #5 9 1 8 Eco-Outreach Group Total 32 15 17 Both participants areas of residence and areas of employment were relatively evenly distributed across island (see figures 3.4 and 3.5) Figure 3.4. Map of the distribution of participant’s residence in St. Thomas, USVI.
  49. 49. P a g e | 34 Figure 3.5. Map of distribution of participant’s place of employment in St. Thomas, USVI. 3.6 Notes from the Field Recruitment of Participants Recruitment of participating groups for this study was a learning process. Initially the ‘DPnR’ group was identified and recruited to be a more intensive and eventually policy oriented group compared to other groups. As they were directly linked to the management process they would ideally not only benefit from going through the process themselves but by comparing their results to other community groups they could better integrate community perspectives into their management goals and processes. However, three of the five participants with continental origins who left the island and/or their respective occupations were from this group. So this process was never repeated beyond the first focus groups discussion. Recruitment consisted of cold emailing, phone calls, or showing up at community group meetings. A general flyer was also created and distributed to target groups (see appendix C). The flyer went through roughly a dozen iterations based on advice from local outreach workers before it was sent out, and even then was edited through trial and errors after
  50. 50. P a g e | 35 questions and comments from recipients. The Community Foundation of the Virgin Islands as well as experienced staff within UVI provided the contact information for most of the groups approached. Each group was asked to suggest any other groups they felt might be interested in participating but this only resulted in one successful ‘snowball’ group. In total 26 community groups were approached to participate in this study. On average it was approximately six weeks between the time of first contact and facilitating a focus group. Most group leaders were contacted roughly eight to ten times through email or phone throughout that period. Many groups stated they would appreciate a speaker to present to their group but expressed hesitation about participating in the study. Other than the reticence to participant and/or forgetfulness the most limiting factor in recruiting participants was the focus group design. Many participants expressed interest in either doing one on one interviews or felt they could not recruit enough other members to constitute a focus group. Methodological Design Overall the scenario planning process succeeded in producing a wealth of mixed data used for this analysis. Groups were engaged throughout the entire process, sometimes even over two hours. However; the placement of the adapted Q Method became complicated and difficult for participants to stay engaged in. Condensing the Q-method exercise into a single emergent exercise may be better suited for applications that involve a certain level of professional involvement in the process and perhaps less suitable for open-ended group discourse. A traditional Q-method done with pre-existing Q sorts may be more appropriate. While writing down positive and negative statements was intuitive; the process of ranking them became somewhat complicated and many participants either did not rank their statements or appeared uncommitted to the ranking scheme. Given that the level of confidence for the ranking results of the assessment is rather low, a choice was made to exclude them from the current state of analysis. Also two groups were unwilling and/or /uninterested in doing the group rankings following the individual
  51. 51. P a g e | 36 rankings. It would likely be more effective to do a more traditional version of the Q- method in which participants discuss the internal mechanisms of the system and the researcher reduces them to a key 30 statements and then returns to each group and asks them to rank them in order of importance or impact.
  52. 52. P a g e | 37 Chapter 4: Methods of Analysis 4.1 Overview Analysis of the focus groups followed a semantic network analysis process. Each focus group was audio recorded and transcribed verbatim into natural-language text documents. The text responses were then data mined using Provalis QDAminer (Provalis 2013) for linguistically identified concepts defined within Wordnet (Princeton 2013). Following the identification of concepts, they were weighted based on the TF*IDF function and a similarity matrix was created using latent semantic indexing and each relationship was given a Jaccard similarity coefficient. The resulting weighted matrix was then used as the basis for network structure, the analysis of which was done using UCINET (Borgatti, Everett et al. 2002) and Net miner (Cyram 2013). Analysis consisted of examining the graph theoretic implications of cohesion metrics and centrality measures to identify the structural composition and key themes in the discourse. This chapter will end by demonstrating the superior nature of semantic network analysis as a method of dimension reduction in qualitative analysis as well as some preliminary statistics from the analysis. 4.2 Semantic Network Analysis While semantic network analysis is still a nascent science in many ways, it is rooted in a long history of graph theoretic and computational methods related to complex network analysis that has been developed since the turn of the 20th century. Broadly speaking, complex networks are mathematical abstractions, or graphs, that represent a system of dynamic elements and the connections between them. These systems often have irregular structures but are also not random (Milo, Shen-Orr et al. 2002) They are often characterized by both scale free distributions and small world system properties, which will be discussed in great detail in subsequent sections. Complex network analysis has had numerous applications in physics, molecular biology, ecology, computer science and the social sciences as well as other disciplines. For an in depth look at the history and common properties of complex networks see (Boccaletti, Latora et al. 2006).
  53. 53. P a g e | 38 Complex networks are characterized by nodes and vertices, with the nodes representing the element and vertices being the links between them. In the case of semantic networks; they refer to the system of connections between semantic concepts, or terms, derived from written or transcribed text from human discourses. The theoretical foundation of semantic networks originates from spreading activation theory which purports that language and memory processing follows an associative network mechanism (Collins and Loftus 1975). Collin and Loftus described these associative networks as hierarchical where the associations between ideas are based on the personal experiences of the individuals. See (Sharifian and Samani 1997) for empirical evidence supporting the hierarchical nature of spreading activation. In short this theory establishes that the use of language or semantics is structured by the associations an individual has surrounding a given topic. For instance, a classic example is the associative network related to the color red (see figure 4.1): Figure 4.1. The color red example of spreading activation theory from Collins and Loftus, 1975.

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