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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
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).
© Copyright by Wm. Alex Webb November 15th, 2013 All Rights Reserved
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
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
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.
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.
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
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
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
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
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
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
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
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 `
Community Perspectives on Sustainability and Resilience in a Social-
Ecological Paradigm
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
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,
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.
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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
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
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
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
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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
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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
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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
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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
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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
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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
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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
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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
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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
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.
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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).
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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 ConditionsRank 6 Most Positive and Negative Drivers for
Future ScenarioDiscuss the Role of the Drivers in the Future
Scenario
Exercise #1 Choosing a Future Scenario
Choose and Describe Potential Future ScenarioChoose a Time Frame for Future Scenario
(5,10,15 Years)
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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
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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
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‘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
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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.
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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.
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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.
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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
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
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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.
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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
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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).
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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).
DPnR MPA Team
Eco-Outreach Group Rasta Farming Co-op
Hospitality Social Group
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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.
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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
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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
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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.
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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).
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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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This diagram illustrates not only the connected but reliant nature of concepts to take
different paths. In this case the individual would never arrive at the concept of ‘clouds’
after hearing or saying red without first thinking or discussing ‘sunsets’ or ‘sunrises’.
Follow up study of this phenomenon verified that ‘priming’, or the introduction of a
specific idea or stimuli, could greatly impact the spread of both automatic and
strategic associations in the discourse (Neely 1977). This research laid the foundation
for future research in semantic networks as descriptors of knowledge structures and
topical cohesion (Morris and Hirst 1991, Carley and Kaufer 1993).
Computationally, semantic networks are first created by extracting semantic
concepts based on a lexical library of words, in the case of the English language
Wordnet, without consideration for grammar. The connections based on the
associative use of the words are then calculated using a process of latent semantic
indexing to create a formal network. Latent semantic indexing is the process of
creating a term frequency matric based on the extracted concepts in which terms are
represented in rows and the documents (statements) they appear in are represented in
columns. From there, a singular variable decomposition (SVD) of each matrix is
performed which transforms each matrix into three other matrices (term by concept,
term by term, and concept by document) (Deerwester, Dumais et al. 1989). These
matrices tend to be large and sparse and require a great deal of computing power.
Which is why although many of these theories are over thirty years old, it is only since
the advent of modern computing that semantic networks could be created easily and
then studied for their structural motifs and properties. Recently there has been
substantial research which has established two fundamental characteristics of complex
networks in general but specifically of semantic networks as well: Small world
characteristics and scale free patterns of distribution.
4.3 Structural Motifs of Semantic Networks
Small World Dynamics
Small world dynamics refers to a common structure of complex networks in
which nodes can be connected to other nodes within the network by taking relatively
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short paths (measured by their shortest path length, termed geodesics). Complex
networks are decentralized, meaning they have numerous ‘central’ nodes, which
cluster, or have cliques, that are not completely ordered but are also not random
(Watts and Strogatz 1998). These properties have been specifically identified in large
scale semantic networks (Steyvers and Tenenbaum 2005). Small world dynamics
were first coined and discussed in relation to social networks by Stanley Milgram
(Milgram 1967). Milgram’s observation is the source of the classic example of small
world networks; the ‘six degrees of Kevin Bacon’ game in which any actor from any
time since the inception of film can be linked to being in a film with Kevin Bacon
through their co-stars within six steps. More recently, this small world phenomenon
has been identified as a common property of complex networks in both the natural and
social sciences. For an in-depth look at the prevalence of small world dynamics in
numerous real world complex systems see (Watts and Strogatz 1998) or (Barabási and
Frangos 2002). This phenomenon coupled with spreading activation theory implies
the potential for semantic networks as a tool for exploring how concepts in human
discussions are associated and subsequently linked (or not linked).
Scale Free Patterns of Connectivity
In addition to small world dynamics complex networks have also been found to
have scale free patterns of connectivity where a minority of the variables accounts for
the majority of the network’s connectedness (Barabási 2009). Specifically, scale free
patterns of connectivity have been found to be an inherent property of semantic
networks (Steyvers and Tenenbaum 2005). One of the indicators of scale free
dynamics is the ability to fit, or approximate, a power law distribution. This
dependency on fitting a power law distribution encapsulates the important network
property of preferential attachment, and/or the important principle from economics
and social sciences of the 80/20 principle or Pareto distribution. Using this research
as an example, when examining the log-log plot of the concept degree distribution (see
figure 4.2) calculated from the network derived from all the discussions combined, we
find a significant fit for a power law distribution (p= 0.028).
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Figure 4.2. Log-log plot of the distribution of node centrality of network created from
combined group conversations (p=0.028)
The scale free/power law distribution in semantic networks practically
translates to a degree of saturation in the emergence of semantic concepts and/or
patterns. Which means that adding more data is not likely to change the patterns
already observed in the existing data. Confidence for this proposition is analogous to
the tests of significance for the power law relationship. Due to the often high volume
of concepts typically extracted for semantic networks, scale free patterns then create
the potentially for highly efficient dimension reduction. Where those few concepts that
account for the greatest amount of the connectivity can be examined rather than each
individual concept. In order to do that there are a number of metrics that can be used
to analyze the network, both for its cohesive structure and its key concepts.
4.4 Analysis Metrics
Cohesion Metrics
This analysis relied on some cohesion metrics designed to examine the
structural properties of complex networks in general. In this context, cohesion can be
considered the degree to which nodes in a network are tightly connected. While there
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are numerous network measures of cohesion developed within other disciplines such
as social, biological and computer networks there are no formal cohesion metrics for
semantic networks specifically. However, there are a number of general network graph
metrics which can be examined to analyze the networks created from the semantic
extractions. The first of which is density or the proportion of how many links the
network exhibits compared to the maximum number of possible links in a graph
structure. Networks with higher density are thought to be more structurally cohesive.
While it has been shown that in typical social networks, the larger the network the
higher the density, making density a cautious measure, it is unclear whether that
relationship applies to semantic networks. In semantic networks the size of the
network can (and are) controlled based on weighting functions and therefore each
network should be approximately the same node size although total frequencies will
vary. Beyond density other measures such as average degree (the average number of
connections per node), average distance (average path length to for one node to reach
another), and the clustering coefficient were used. The clustering coefficient is a
measure to which the nodes tend to cluster together in triads. For instance if you know
person B and person B knows person C, do you know person C? If so you will exhibit
a cluster coefficient of 1. Sometimes this is referred to as the ‘friends of my friends are
my friends’ measure. The network cluster coefficient is the average of each nodes
individual cluster coefficient. A significant cluster coefficient, compared to randomly
generated networks with the same data, is an indicator of small world dynamics
(Barabási 2009).
Table 4.1. Definition of cohesion metrics and network structures used in analysis Metric Definition
Nodes (concepts) # of semantically relevant concepts extracted from discussions
Number of Links # of connections between nodes within the network
Density Proportion of actual links compared to maximum potential for links
Avg. Degree Calculates average # of nodes any given node shares a link with
Avg. Distance Calculates the average length between nodes using their shortest path
Cluster Coefficient Calculates degree to which nodes shared links between each other (i.e. friends of my friends are my friends)
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Centrality Measures
Once the structural properties of the network are confirmed to be a cohesive
system, centrality measures can be used to calculate the most important (connected)
nodes within the network. While there are numerous centrality measures, many
designed specifically for the discipline of the complex network of study, there are no
semantic network specific centrality measures. However, as these semantic networks
will be both directed and weighted graphs, this research will use the three most
prominent and basic centrality measures to explore the key concepts from the
discourse.
The first two measures are based on a node’s in-degree and out-degree. In-
degree refers to the number of nodes that connect to a given node whereas out-degree
calculates the number of links emanating from the node to other nodes. They are
sometimes called senders and receivers. For an in-depth look at these measures see
(Borgatti and Everett 2006). The third measure that will be used is the Betweenness
centrality metric. The Betweenness centrality calculates how often nodes act as the
bridging agent between two nodes that would otherwise be disconnected. For in-depth
look at the development of the Betweenness centrality measure (initially intended for
social networks) see (White and Borgatti 1994). A more update on the equations for
calculating Betweenness was developed by (Brandes 2001).
It is important to note however the difference between semantics and
pragmatics when analyzing centrality. While semantics can effectively communicate a
blueprint for the use and connections between broad concepts, they do not
communicate their inherent meaning, often referred to as pragmatics. Therefore a
degree of qualitative assessment of the concepts is necessary to draw specific
conclusions. This is particularly true when considering the concept of centrality in
regards to spreading activation theory. When concepts are highly central they are more
likely to contain multiple meanings. For instance, considering the example of ‘Red’,
someone could discuss the beauty of red rose they saw or the degree to which they felt
rage and ‘saw red’. These types of distinctions in meaning are not always intuitive
when examining a network of connections. This is in part why semantic networks
exhibit such hierarchical structures. Semantic concepts that are broader or contain
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multiple meanings are more likely to be connected to wider variety of other concepts,
increasing their centrality within the network. Therefore the more central a concept,
the broader and more multidimensional you can expect the interpretation to be.
Table 4.2. Definition for each centrality measure used in analysis Measure Definition
Out-Degree The proportion of outward directed links emanating from a concept, relative to the total number of nodes
In-Degree The proportion of inward directed links received by a concept, relative to the total number of nodes
Betweenness The number of shortest paths from all links to all others that pass through a concept
4.5 Processing Data
For this research project the creation of the network data was done entirely
with the software package by Provalis called QDAminer (Provalis 2013), QDA miner
functions by extracting all the concepts within the text using latent semantic indexing
and the Princeton developed lexical word database called Wordnet (Princeton 2013)
which has been developed an updated since the mid 1980’s.
Dictionary Modifications
While this process was almost entirely automated some additions had to be
made to account for unique local language use and differences among groups. For
instance, the term WAPA (Water and Power Authority) was often used when
discussing energy but was not included in the lexical dictionary. Also occasionally
groups would use the different words despite discussing identical concepts. For
instance, the use of the term ‘attitude’ was used by other groups in the form of
‘mentality’ or ‘mindset’. As individual groups would often contain these concepts in
their individual networks but it would be lost in the overall network since it was
divided multiple ways (based on different semantic choices). Therefore these were all
coded to read ‘attitude’, likewise the use of the term ‘decisions’ and ‘choices’ were
coded as ‘decisions’. Also occasionally participants would exhibit tics that were so
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severe that the words would appear significantly within the network despite having no
meaning and being generated by one individual. In these instances, if possible, the
word would be removed from the network. An example of this would be a participant
who used the phrase ‘sort of’, sometimes more than once in a sentence. Therefore
‘sort’ was considered an important word when in fact it had no particularly useful
meaning. All modifications to the dictionary in the ways described were kept to a
minimum.
Weighting Functions
Rather than rely exclusively on word frequency, once the concepts were
extracted each one was weighted based on the TF*IDF function (Term
Frequency*Inverse Document Frequency) which can be read as follows:
Equation 4.1. TF*IDF Statistic
TF*IDF( , , ) TF( , ) IDF( , )t d D t d t D
Where;
t= a given term from the term list (semantic concept, category or word);
d= a document (i.e., discourse instance or statement in the database);
D= the document text corpus (the discourse database);
TF= term frequency index; and
IDF= inverse document frequency index
The TF*IDF value reflects the proportion between the number of times a word
is recorded in a statement compared to the number of times the word appears in the
entire document. This way a concepts frequency within a discussion could be weighed
against the frequency of the other concepts throughout the entire document. Words
were given more weight if they appeared more frequently within a statement
compared to the overall discussion. This process has been demonstrated to be a
reliable method for extracting terms and semantic concepts most relevant to the
specific conversation (Ramos 2003).
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From this weighting scheme the top 80 most highly weighted (by their TF*IDF
value) concepts were included in the network structure. However; in each network
(unless otherwise specified) only those words with a minimum frequency of 10 were
included in the network. This resulted in some discussion networks having less than
80 concepts included. These concepts were put into a similarity matrix and given a
directed weighting coefficient based on the Jaccard Index. The Jaccard Index is a
similarity coefficient calculated by comparing the similarity and diversity (presence
and absence) of the relationships between the nodes. The equation is denoted by
dividing the absolute degree of intersection (statements which contain any two
concepts) divided by the absolute union of the same two concepts (total abundance of
concepts individually). This can be read as follows:
Equation 4.2. Jaccard Similarity Index
( , ) A BJ A BA B
Where;
A∩B = the absolute degree of intersection between these two concepts in the
text corpus
AB = the absolute degree of union among these two concepts in the text
corpus.
The weighted similarity coefficient was then used as the basis for calculating the
degree centrality for each node.
Drawing Themes from the Most Central Concepts
Once the degree centrality for each concept was derived key themes in the most
central concepts were analyzed. These themes were derived from examining the most
central concepts based on all three metrics (In-degree, Out-Degree and Betweenness
centrality). The cutoff for a concepts inclusion in this portion of the analysis was a
0.04 Jaccard weighted centrality coefficient or higher; or 0.001 in the case of
betweennness centrality. The concept inclusion cutoff rate is necessary in semantic
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networks given its hierarchical isomorphic structure. The cutoff inclusion rate must be
interpreted as the level of abstraction chosen for the analysis. Given the scale-free
structural equivalence of the semantic networks, such cutoff inclusion point should be
chosen so that it maintains to the possible extent the distributional characteristics of
the power-law structure. Once this requirement is met, it can be mathematically
proven that the cutoff inclusion point should have no theoretical or methodological
impact on the inferential power of the analysis itself. In this sense, it resembles the
statistical power test for traditional statistical analyses. In this context it accounted for
approximately 40% of the cumulative centrality being examined (see figure 4.3). This
organization of concepts will be referred to as ‘Tier 1’ in relation to the network
hierarchy for the remainder of this document.
Figure 4.3. Distribution of degree centrality of concepts extracted from combined discussions 4.6 Semantic Network Analysis as Dimension Reduction Tool
As discussed earlier, semantic network analysis shows great potential for
exploring qualitative data sets. This is in great part because semantic networks follow
a scale-free distribution. While this generally refers to the distribution of the degree
centrality it will be demonstrated that it can also be reflected in the term frequency of
concepts discussed. For instance, when all the conversations were processed and
combined there were a total of 2,404 different terms extracted from 13,274
0
0.01
0.02
0.03
0.04
0.05
0.06
0.07
0.08
1 4 7 10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 64 67 70 73 76 79
Cen
tralit
y Sc
ore
(bas
ed o
n Ja
ccar
d In
dex)
Concepts
Centrality Distribution from Overall Network
In-Degree
Out-Degree
Betweenness
P a g e | 48
linguistically relevant words. When the frequency distribution of these concepts is
examined it is clear that a small minority of the terms make up the majority of the
frequencies (see figure 4.4). When the top 80 concepts were extracted from the 13,274
words extracted they accounted for 5,241 of total word frequency which translates to
3% of the total concepts accounting for 39.5% of the total frequency of words used.
When the top 20 most central concepts were examined based on in-degree, out-degree
and Betweenness centrality measures data reduction became even more efficient. The
top 20 concepts (0.8% of the total concepts) accounted for 2,785 words or 21% of the
total extracted words. Therefore not only have the concepts which serve as the
cornerstones of the network been identified but they are also the ones that account for
a great deal of the conversational variability in general. This process was done for the
multiple network datasets derived from the discourses with similar results for each one
demonstrating the effectiveness of semantic network analysis as a dimension reduction
tool or methodological instrument.
Figure 4.4. Distribution of frequencies of concepts extracted from combined discussions
4.7 Preliminary Statistics
In total, the five groups provided 1,058 responses and 54,460 semantically
relevant words across all four exercises. Of those words, 13,274 (24.4% of total) were
extracted into 2,404 distinct semantic concepts. From these concepts 30 networks were
0
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350
1 82 163
244
325
406
487
568
649
730
811
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1135
1216
1297
1378
1459
1540
1621
1702
1783
1864
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2026
2107
2188
2269
2350
Con
cept
Inci
denc
e
Concept Frequency Distribution
Term Frequency
P a g e | 49
created: One network for each individual group’s responses to each exercise as well as
all the groups combined responses to all the exercises. In addition to that, networks
were created from each group’s combined responses to all the exercises as well as one
‘overall’ network combining all the groups’ responses to all the exercises (see table
4.3).
Table 4.3. Breakdown of network structures created for analysis Network Source Individual Combined
Exercise #1 5 1 Exercise #2 5 1 Exercise #3 5 1 Exercise #4 5 1 All exercise responses networks 5 1 Total 25 5
Although gender perspectives were not a variable of inquiry in this research
the balance between male and female participants was relatively equal at seventeen
female and sixteen male. When the contribution of words is examined by gender, the
ratio is similar with females contributing 54.2% of extracted concepts and males
contributing 45.7%. Since the networks are derived from these relatively evenly
contributed-to concepts, this suggests that there exists no significant gender bias
within the data set (see table 4.4). When the relative contribution or influence of each
group to the extracted concepts is examined it is not as clear. The groups with fewer
participants (four or five people) contributed between seventeen and eighteen percent
of the total but there is a contrast in the two larger groups, which each had nine
members. The Rastafarian Farming Co-op only contributed 17.9% of the total
extracted words whereas the Eco-Outreach group contributed 28.9% (see table 4.5 and
4.6). This is in great part due to the slow and hierarchical nature which with the
participants of the Rasta farming co-op focus group responded. Despite the contrast, in
total each group contributed approximately 20% suggesting that the assertion that this
analysis consists of a broad range of perspectives is satisfied.
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Table 4.4. Summary statistics of combined natural language text documents Summary Statistics Total__ Percent Total__ Total statements/responses: 1,058 100% Total number of words: 54,460 100% Total number of concepts/terms: 2,404 100% Total words extracted to concepts: 13,274 24.4% Total words extracted by females: 7,202 54.2% Total words extracted by males: 6,072 45.7%
Table 4.5. Total responses/statements by group Summary Statistics Total__ % Percent Total
#1 MPA Management Team 134 12.7 #2 Hospitality Social Group 245 23.2 #3 Local Government NRM 193 18.2 #4 Farming Food Co-op 78 7.4 #5 Environmental Educators 408 38.6 Total 1058 100
Table 4.6. Total extracted words by group Summary Statistics Words Total __%Percent Total__
#1 MPA Management Team 2,288 17.2 #2 Hospitality Social Group 2,339 17.6 #3 Local Government NRM 2,418 18.2 #4 Rastafarian Farming Co-op 2,382 17.9 #5 Eco-Outreach 3,847 28.9 Total 13,274 100
Table 4.7. Number of concepts discussed by group Summary Statistics # of different concepts discussed
#1 MPA Management Team 753 #2 Hospitality Social Group 731 #3 DPnR 856 #4 Rastafarian Farming Co-op 800 #5 Eco-Outreach 1,168 Total number of different concepts 2,404
When creating the network from text there were two different protocols used
based on network type. For large networks which either combined all the discussion
exercises per group or all the groups discussions together, the top 80 semantic
concepts based on the TF*IDF function were used. In addition to this, only concepts
which had been discussed at least 10 times were integrated into the network. For the
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smaller individual groups’ responses to specific questions networks, the minimum
frequency for integration was reduced to four.
Combined Discourses Network Statistics
The network created from all the combined discussions resulted in an 80 node
structure with 2,883 links, a density of 0.456, an average node degree of 36.038, a
significant clustering co-efficient of 0.927 (p=0.0; based on 132,000 iterations) and a
statistically significant power law goodness of fit (p=0.025) (See tables 4.8 and 4.9
for details). These metrics illustrate the connected and cohesive nature of the 80 most
relevant concepts discussed throughout the scenario planning process. Similarly the
cohesion metrics for each individual group’s networks, created from their responses to
all the exercises, exhibited high density and average degree in relation to the number
of nodes and links within the network as well as satisfying both scale-free and small
world property assumptions. This suggests that the networks captured both the
individual group and combined group’s semantic knowledge structures.
Table 4.8. Cohesion measures for network derived from all five groups’ combined discussions Measure Combined Network
Number of Responses 1,058 Nodes (concepts) 80 Number of Links 2,883 Density 0.456 Avg. Degree 36.038 Avg. Distance 1.086 Cluster Coefficient 0.927* Power Law (GoF) (0.025)
Cluster Coefficient p value based on 132,000 iterations
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Table 4.9. Cohesion measures for each group’s network derived from their combined discussion
Measure MPA Team
Hospitality Social DPnR Farming
Co-op Eco-
Outreach Number of Responses 134 245 193 78 408 Nodes (concepts) 43 39 40 45 68 Number of Links 741 583 648 835 1,475 Density 0.410 0.393 0.415 0.422 0.324 Avg. Degree 17.233 14.987 16.2 18.556 21.691 Avg. Distance 1.171 1.183 1.149 1.145 1.343 Cluster Coefficient 0.866* 0.842* 0.889* 0.894* 0.750* Power Law (GoF) (0.035) (0.005) (0.04) (0.005) (0.019)
*Reflects a value of p= (0.0); ** reflects a value of p= (.001); *** reflects an insignificant p-value
Exercise #1 ‘Choosing a Future Scenario’ Network Statistics
The first exercise involved participants conceptualizing a potential scenario
and time frame to use as their focal future state. Each group participated equally in this
exercise and used a handout of pre-analyzed global trends for reference when defining
their scenario (see field methods chapter 3 sections II for greater detail). When all the
conversations were combined, the first exercise of the scenario planning focus groups
yielded 298 responses and 7,484 words. Of which 1,368 were extracted into 61
semantic concepts. Similar to the overall network only those concepts with a
frequency of 10 were included in the network. The resulting 61 node network
consisted of 1,426 links, had a density of 0.389 with an average degree of 23.38, a
power law goodness of fit of p= (0.0) and a significant clustering coefficient of 0.832
(p= 0.0, based on 118,000 iterations) (See table 4.10 and 4.11). These measures, while
not as cohesive as the network derived from all the exercises, indicate a cohesive
knowledge structure. Similarly, the individual networks cohesion metrics describe
structured networks.
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Table 4.10. Cohesion metrics for the combined network derived from exercise #1 Measure Combined Network
Number of Responses 298 Nodes (concepts) 61 Number of Links 1,426 Density 0.389 Avg. Degree 23.378 Avg. Distance 1.205 Cluster Coefficient 0.832* Power Law (GoF) (0.0005)
Cluster Co-efficient p value based on 118,000 iterations
Table 4.11. Cohesion measures of individual group’s networks derived from exercise #1
Measure MPA Team
Hospitality Social DPnR Farming
Co-op Eco-
Outreach Number of responses 24 81 68 7 118 Nodes (concepts) 29 29 37 21 50 Number of Links 327 244 317 138 634 Density 0.403 0.30 0.238 0.329 0.259 Avg. Degree 11.27 8.414 8.56 6.57 12.68 Mean Distance 1.17 1.35 1.46 1.33 1.45 Cluster Coefficient 0.888* 0.826* 0.681* 0.836* 0.674* Power Law (GoF) (0.02) (0.06) (0.0) (0.01) (0.07)
Exercise #2 ‘Connecting Future Scenario to Present Conditions’ Network Statistics
After each group chose their focal scenario and time frame, groups began
exercise #2 which consisted of detailing the specific drivers of change (both positive
and negative) linking the current and future states. During this exercise participants
were presented with a handout of categorical drivers and variables that make up a
social-ecological system (for more detail see Chapter 3 Field Methods, Section II).
Exercise #2 generated the most conversation of all the exercises. In total it yielded 462
responses and 11,285 words, of which 2,639 were extracted into semantic concepts.
The resulting 90 node network consisted of 3,023 links, had a density of 0.377 with an
average degree of 33.589, and a clustering coefficient of 0.829 (p=0.0; based on
98,000 iterations) (See table 4.13 for a comparison of cohesion metrics between
individual group networks). This exercise, more so than the others, also resulted in a
greater variation of the number of concepts extracted across groups with the Eco-
outreach group having 88 and the Hospitality social group only 31. This may be due to
the amount of discussion each group engaged in during the adapted Q-method portion
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in which participants were writing down their statements on sticky notes. Some groups
chose to discuss this portion amongst themselves whilst others wrote their statements
silently and then shared them. Consequently, many of the groups did not meet the
power law assumption likely due to the brevity of the responses which typically only
included reading their statements. However, as the overall network did meet the
assumptions easily it indicates that there was a great deal of shared language in the
short responses across groups.
Table 4.12. Cohesion metrics for the combined network derived from exercise #2 Measure Combined Network
Number of Responses 462 Nodes (Concepts) 90 Number of Links 3,023 Density 0.377 Avg. Degree 33.589 Avg. Distance 1.237 Cluster Coefficient 0.829* Power Law (GoF) (0.0)
Cluster Coefficient p value based on 98,000 iterations
Table 4.13. Cohesion measures of individual groups networks derived from exercise #2
Measure MPA Team
Hospitality Social DPnR Farming
Co-op Eco-
Outreach Number of Responses 65 93 54 38 212 Nodes (Concepts) 71 31 47 45 88 Number of Links 1,567 341 889 629 1,654 Density 0.316 0.367 0.411 0.318 0.216 Avg. Degree 22.07 11 18.915 13.978 18.795 Mean Distance 1.351 1.223 1.173 1.32 1.56 Cluster Coefficient 0.756* 0.801* 0.887* 0.795* 0.67* Power Law (GoF) (0.07) (0.16) (0.17) (0.45) (0.06)
Exercise #3 ‘Defining Sustainability’ Network Statistics
Unlike the other two exercises, exercise #3 was very difficult for participants
to articulate and resulted in a small network of only 13 concepts. These conversations
were also typically limited to approximately 15 minutes due to the scarcity of ideas. In
fact, despite providing 45 and 25 responses, the MPA management team and Eco-
Outreach groups’ networks were too small to be created based on the frequency of
four minimum used for individual networks. The only exception was the farming –cop
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which had a cohesive and robust discussion. When all conversations were combined
there were not enough concepts to satisfy the power law assumption based on the
frequency of 10 requirements for concept inclusion. The difficulty in groups’
responses is evident in both the combined individual networks low cohesion metrics
(see tables 4.14 and 4.15). Although groups found it difficult to discuss the question
broadly they were able to agree on a specific indicator for sustainability which will be
discussed in greater detail in the results chapter.
Table 4.14. Cohesion metrics for the combined network derived from exercise #3 Measure Combined Network
Number of Responses 151 Nodes (concepts) 13 Number of Links 61 Density 0.391 Avg. Degree 4.69 Avg. Distance 1.10 Cluster Coefficient 0.912 (p=0.005) Power Law (GoF) p= (2.831)
Cluster Coefficient p value based on 94000 iterations
Table 4.15. Cohesion measures for each group
Measure MPA Team
Hospitality Social DPnR Farming Co-
op Eco-
Outreach Number of Responses 45 45 25 11 25 Nodes (Concepts) 1 13 8 29 4 Number of Links N/A 29 15 332 N/A Density N/A 0.186 0.268 0.409 N/A Avg. Degree N/A 2.23 1.88 11.45 N/A Mean Distance N/A 1.47 1.25 1.16 N/A Cluster Coefficient N/A 0.786* 0.754** 0.862* N/A Power Law (GoF) N/A (0.05) (0.0) (0.07) N/A
Exercise #4 ‘Discussing Preparedness for the Future’ Network Statistics
Similar to exercise #3, exercise #4, which involved participants discussing
their individual and shared preparedness for the future, was typically short
(approximately 20 minutes) and did not yield a high number of concepts. Similar to
exercise #3 the combined network did not meet the power law assumption indicating
that more conversation would be needed to create a significant semantic network.
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However, qualitatively the themes were more cohesive and individual network were
able to satisfy the assumptions (see tables 4.16 and 4.17).
Table 4.16. Cohesion metrics for the combined network derived from exercise #4
Measure Combined Network Number of Responses 147 Nodes (concepts) 19 Number of Links 134 Density 0.392 Avg. Degree 7.05 Avg. Distance 1.18 Cluster Coefficient 0.858 (P=0.0) Power Law (GoF) (1.1)
Cluster Coefficient p value based on 94000 iterations
Table 4.17. Cohesion measures for each group
Measure MPA Team
Hospitality Social DPnR Farming
Co-op Eco-
Outreach Number of Responses N/A 26 46 22 53 Nodes (Concepts) N/A 7 23 24 16 Number of Links N/A 8 115 218 53 Density N/A 0.190 0.227 0.395 0.221 Avg. Degree N/A 1.14 5 9.08 3.31 Mean Distance N/A 1.2 1.37 1.17 1.37 Cluster Coefficient N/A 0.60* 0.805* 0.853* 0.593**
Power Law (GoF) N/A (0.0) (0.03) (0.0) (0.0)
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Chapter 5: Results
5.1 Overview
The results chapter is broken into two sub chapter sections: 1) Universal
themes from the discussions, 2) analysis of the exercises and, due to the nature of the
large date set
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 exercise 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
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 analyzed each exercise independently and reiterated 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,
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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 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.
Section I: Universal Themes from the Discourse
5.2 Universal Themes from the Focus Group Exercises
When analyzing the overall combined network compared to the individual and
question specific networks, four universal tier 1, hierarchical concept-based themes
arose: 1) concepts related to temporal and spatial scale 2) concepts related to social
and organizational dynamics 3) concepts related to economics and livelihoods 4)
concepts related the environment and natural resources (see figure 5.1).
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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
When the connections between these broad themes were examined in detail
qualitatively, some clear factors influencing group perspectives emerged. a) The first
was the role of sense of place, identity and purpose. The role of place (both social and
physical) was manifested through the use of ‘Island’ and was heavily connected to
social and organizational concepts such as ‘People’ and ‘Community’ (see figure 5.2).
Emerging through these connections was not only the importance of context and place
as a means of discussing change and sustainability but also a conflict regarding
community and economic identity and purpose. Some of these issues of identity
appeared to be related to changing demographics over time, specifically the high
immigration rates and tourism volume diminishing the sense of what a “Virgin
Islander” is. Another contributing driver that was connected to issues of identity was
the economic inequality and disempowerment expressed by many participants.
Especially when discussing a future trend, the role of economic disparity between
local groups and corporations was considered a limiting factor in the success of the
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island. ‘Local’ and ‘Business’ in general were strongly connected to each other (see
figure 19) and often reflective of the lack of control participants felt over externalities
related to global economic trends impacting the island in the form of tourism
development.
The second factor influencing groups’ perspectives was b) the role of the
environment in their collective knowledge structures. The natural environment was
generally discussed in broad terms of economic and/or environmental impacts and
frequently connected to energy costs. Some distinct differences between groups
emerged regarding how they discussed the environment. The farming co-op and
hospitality social groups were like to discuss agriculture in relation to either
connecting livelihoods to the environment or as a measure of a healthy sustainable
environment. Management groups on the other hand were more likely to use ‘Water’
as an environmental focal point.
Sense of Place, Identity and Economic Disparity
As the basis of the scenario planning exercise was for groups to choose and
explore a potential future scenario and time frame it is no surprise that the first theme
identified is comprised of concepts related to I. Temporal and Spatial Scales (see table
5.1). However, the presence and high centrality scores of at least some of these
concepts in every question network both combined and individual, emphasizes the
importance of sense of place and time in participants’ perspectives on concepts such as
sustainability, social preparedness and their valuation of the factors driving the system.
It could also be considered an indicator of participant’s commitment to the scenario
planning process.
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Table 5.1. Concepts comprising the ‘Spatial and Temporal Scales’ theme. Weighted scores based on Jaccard Index
I. Temporal and Spatial Scales
Centrality Metric Concept Frequency Centrality Score
Weighted Score
In-Degree
Time 89 .937 .073
Year 117 1 .061
Term 50 .911 .054
Virgin 40 .899 .047
Out-Degree
Change 113 .873 .065
Big 61 .911 .060
Island 116 .582 .055 Area 35 .949 .048
Happen 70 .658 .045
Node Betweenness
Lot 174 .0013 n/a
Place 76 .0012 n/a Small 43 .0012 n/a Land 48 .0011 n/a
In general concepts such as ‘Time’, ‘Change’, ‘Term’ ‘Happen’ and ‘Year’
were instances of groups discussing appropriate time frames for envisioning various
potential changes or to discuss past events. These concepts are the most highly
connected and are nested throughout every conversation. In fact the term ‘Year’ was
linked to every other concept in the network at least once.
Similarly, the concepts related to space, in many instances both physical and
social, were highly connected and nested throughout the network. The concept of
‘Island’ however; had a more specific role in the network (see figure 5.2 below)
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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
When the patterns of connections were examined certain connections appeared
intuitive; for instance strong links between ‘Island’ and ‘Virgin’, ‘Small’ and ‘St
Thomas’. Less intuitively however; was that the strongest connections between
‘Island’ were primarily social drivers such as ‘People’, ‘Make’ and ‘Decision’ and the
short paths to concepts of ‘Government’, ‘Care’, ‘Attitudes’ and ‘Community’. While
there was some discussion of the physical limits of living on a small island, such as
traffic and room for continuing development, it was the social constraints and
dynamics that were more strongly connected to the concept of ‘Island’. ‘Island’ then
was used more as a descriptor for sense of place, as opposed to a literal physical
description. This sense of place was heavily linked with the second Tier 1 theme from
the overall network which was II. Social and Organizational Dynamics (see table 5.2).
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Table 5.2. Concepts comprising the ‘Social and Organizational Dynamics’ theme. Weighted scores based on Jaccard Index
II. Social and Organizational Dynamics
Centrality Metric Concept Frequency Centrality Score
Weighted Score
In-Degree
Work 70 .975 .063
People 327 .684 .056
Talk 69 .911 .051
Out-Degree
Community 164 .861 .062
Government 70 .671 .046
Attitude 74 .899 .043 Education 50 .759 .042
Care 60 .823 .042
Node Betweenness Knowledge 42 .001 n/a
People 327 .001 n/a Make 171 .001 n/a
As noted in chapter 4, highly central concepts often have multi-dimensional
meanings within a network. This is certainly true when examining the connections
between ‘Island’ and the concepts from the second theme of the overall network.
When analyzing the nature of the conversations across these broader concepts a series
of interconnected perspectives embedded in the discourse emerged. One of which was
the multi-layered issue of Identity. Identity emerged as affective topic of discourse
relating to issues sense of place, sense of purpose and sense of community. The
discussions around these topics differed across groups and were often influenced by
the nature of the group’s organization and cultural background.
For instance, the issue of planning and identity was common among the
management groups, often citing the lack of a comprehensive land use management
plan or any planning as evidence of a lack of vision and/or consensus.
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Box 5.1. MPA team participant discussing difficulty in managing distinct geographic and cultural systems “You know the Virgin Islands are a unique dynamic because of the fact that all three islands, even the fourth island is - it is extremely different within each one. The vision for each island actually has to be different but yet we are supposed to think about the territory as one and so it is a pretty difficult question to actually have and answer for. I mean I think that in the planning for St. Thomas, there should be an acceptance for what it is we are and how to better manage these things” – MPA Team Participant Box 5.2. Natural resource manager discussing planning in the USVI “Lack of planning, again, no land use plan, we do not work together. We do not work together within the department. We do not plan for next week or next year or anything. There is zero planning in the Virgin Islands.” – DPnR Participant
While management groups frequently struggled with issues of planning and vision as
they related to a cohesive identity for the purpose of the island (i.e. an island of eco-
tour operations vs. the Cruise ship capital of the Caribbean vs. increased mass
development vs. increased cultural tourism). The outreach and community groups
were more likely to discuss identity in terms of defining relevant cultural and spatial
dimensions.
Box 5.3. Eco-outreach participant discussing tension regarding the identity of a ‘Virgin Islander’ “…when it comes to the people of the community, the local community, to say …what makes you a Virgin Islander, even that question is a problem…that question is a problem because [diverse, outside] society’s want to determine what should be when it should be about the people within this community. If you are born here…that is it you know… that is it. Plain and simple.” – Eco-Outreach Participant
Box 5.4.Eco-outreach participant discussing the division of communities based on spatial areas “And, knowledge ,I think the communities of the Virgin Islands, of St. Thomas - where I live - and the various communities all over the north side, east side, west side - all over. They have different communities…” – Eco-Outreach Participant
There were two variables cited by groups during the discussions that related to the
struggle for community and territorial identity. The first was the rapidly changing
population demographics on the island and the second was economic disparity.
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Changing Population Demographics:
Throughout the sixties, seventies and early eighties the Virgin Islands
experienced rapid population growth due to international migration. In 1960, the
population of the US Virgin Islands was 32,000 but grew to and stabilized at over
100,000 by 1982 (WorldBank 2013) (see figure 5.3). However; while the overall
population growth rate of the island stabilized by the late 1980’s (see figure 5.4) the
percentage of international migration to the island continued to increase. This has
resulted in the USVI having the second highest percent migration stock in the Eastern
Caribbean at nearly 60%, behind only the Cayman Islands (see figure 5.5)
(WorldBank 2013). This means that currently approximately 60% of the resident
population in the Virgin Islands migrated to the island from elsewhere.
This has resulted in a population structure that includes approximately 44% of
the population being born in the USVI, 35% of the population immigrating from other
Caribbean islands, 15% migrating from the continental U.S. and 6% immigrating from
elsewhere in the world (U.S. Census 2010).
Figure 5.3. Total population of the U.S. Virgin Islands from 1960 to 2012
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Figure 5.4. Population growth rates of high income Caribbean countries from 1960 to 2012
Figure 5.5. Percent of international migration population in Eastern Caribbean countries
When the changing demographic in relation to international immigration is
coupled with the density related to tourism visitors the number of international or
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foreign individuals in the population at any given time is even higher. Averaging the
number of tourist visitors per year between 2002 – 2011 shows that the Virgin Islands
experiences approx. 2.5 million visitors a year, 2.3 million of which visit St. Thomas
exclusively (Research 2013) . If this number was averaged over the year (annual
tourist/365), added to the total population of St. Thomas and then considered as a
distinct demographic group within the population, tourists account for approx. 10% -
12% of the population on any given day. This number is deflated considering
approximately 600,000 of those visitors arrive by plane and stay in hotels for longer
than a 1 day. This equation was done for other small islands that receive high tourism
volume for comparison (see figure 5.6).
Figure 5.6. Percent of tourists as part of the general population averaged over the year in
heavily visited Caribbean countries
While that number is likely higher during the high season (November to
August) and lower in the off season (September and October), if combined with the
migrant population trend this visualization could aid in explaining participants
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perspectives regarding cultural graying. One participant remarked “There are more
Texans in the Virgin Islands than Virgin Islanders”, if we consider the influx of
tourism as additional continental population this statement’s impact, while still not
true, is more easily understood. The impacts of globalization on local culture were
often expressed by focus groups group participants such as a Rastafarian farming co-
op participant:
Box 5.5. Farming co-op participant discussing difficulty in preserving traditional culture in the face of the development and demographic change Not only we will see the dilution of the available farm land, but the same thing is happening to the local culture, the identity of the Virgin Islander. With the influx of it being a melting pot, eventually we going to be talking to one of two of the last few Virgin Islanders still speak the local twang and still some of the folklore of the island because the influx of all these new technology, information, peoples is like a diluting of our culture or way of life. And the same thing happened in the agriculture scene, sadly. It is like you are stifling the identity of our people. – Rastafarian Faming Co-op Participant
Beyond the influx of tourism, the high presence of migrant population in relation to
the local population was discussed as a result of high emigration rates by local
residents due to lack of both educational and economic opportunities: Box 5.6. MPA Team participant discussing the ‘brain drain’ that results due to lack of opportunity “So it sounds like - you touched upon a point that it is - the educated individuals that are typically leaving the island are those seeking more education, have the opportunities to seek education that leave, pursue jobs or future elsewhere. And then we are left with the community of you know, generally uneducated, or lesser educated folks?” - MPA Team Participant
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 “Honestly, so I grew up without my pops, and my mom is not here so it is just me and my girl here. [we]… talk about having kids and staying here and she is constantly asking me if I want to move, she does not see it staying here. The moves we make here we could make twice as much up there [States]. It is just not, there is no vision, due to what is going on in the island. There is just no vision. For me personally, I am ok but I do not know how far I can go.” - Hospitality Social Group Participant
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Participants discourse concentrated towards the changing demographic profile of the
island were also reflected in the most recent 2012 USVI constitution proposal which
included an amendment that only allowed those citizens born and raised within the
USVI to participate in local elections. This was the first constitution in nearly 40 years
to be presented to the US Congress but was inevitably vetoed due in part to the
unconstitutional nature of the amendment.
Economic Disparity:
Another potential driver for these identity issues discussed by groups was the
perception of economic disparity within the island driven in part by global economics.
Throughout the U.S. Virgin Island approximately 20% of the population lives under
the poverty line based on the national average (U.S. Census Bureau, 2013). Although
the USVI does not have a separate poverty criteria like non-mainland states such as
Alaska or Hawaii, so this number is likely slightly deflated. When poverty is examined
in relation to resident’s origin some of the disparity expressed by participants becomes
clearer. When high poverty area populations are examined by three populations: born
in the USVI, born in the continental US and foreign born, it is clear that those either
foreign born (94% of which are of Afro-Caribbean origin) and those born in the USVI
comprise the vast majority of the poverty on the island, accounting for 44% and 45%
of the total poverty respectively (see figure 5.7). Additionally onl7 8% of those of
Afro-Caribbean descent make over 100,000 a year annually whereas 22.4% of white
continental immigrants do.
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Figure 5.7. Economic disparity by estate in St. Thomas. Darker areas indicate higher
incidences of poverty
This has resulted in feelings of exploitation and marginalization expressed by some
participants:
Box 5.8. Hospitality group participant discussing links between economic development and community marginalization “I have the feeling that a lot of investors want that to happen. They want St. Thomas to hit rock bottom so they can monopolize, drive up land costs, they want all the locals to sell and then this will be their profit paradise with no locals. It reminds me of those - all those rent to own nice apartments, AKA ‘future projects’ at the other end of the island that is taking away the locals from town and from the main districts. To…take them away from tourist places. I think they want to filter out the tourists areas from as many locals as possible so they can control the land. They want the land.” – Hospitality Social Group Participant Box 5.9. Farming co-op participant discussing marginalization of local community groups for the benefit of economic development “We need to stop the hotels from destroying and pumping all kind of things into the sea. We just let them take back Botany Bay and lock it out to people of the Virgin Islands. One of the most beautiful places you can go on this island.” – Rastafarian Faming Co-op Participant
The concepts of ‘Big’ and ‘Lot’ from the first theme were often expressed in a
manner which conveyed disempowerment. They were frequently used as qualifiers for
the magnitude of intervention required to change the current trajectory or the
magnitude of development and globalization. It was occasionally used to describe the
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magnitude of issues and problems present in describing a potential future state as well.
This ultimately communicated that externalities related to global economic dynamics
were perceived as having more control of the island than its internal mechanisms.
From a social-ecological systems perspective this demonstrates a weakened system or
at best a lack of cohesion. Box 5.10. Hospitality group participant discussing the need for financial intervention “I think everything here is going to get a lot worse and it is either going to take a big investor who really is from here or cares about the island to change it around. I do see a more positive outlook for St. Thomas but not in 15 years, maybe like in 30 years” – Hospitality Social Group Participant
Although not as strongly connected in the network, these issues of economic
disparity, identity and disempowerment are thematically related to the third ‘Tier 1’
theme form the network III. Economics and Livelihoods (Table 5.3). This theme is
neither as prolific nor as connected as the other two however there are some dynamics
evident when examining the network graph that can inform the relationships between
them (Figure 5.8).
Table 5.3. Concepts that comprise the ‘Economic and Livelihoods’ theme
III. Economics and Livelihoods
Centrality Metric Concept Frequency Centrality Score
Weighted Score
In-Degree Make 171 .582 .045
Out-Degree
Business 69 .886 .048
Agriculture 38 .772 .044
Economic 36 .759 .041
Node Betweenness Pay 36 .001 n/a
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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
In this context ‘Economic’ was typically discussed in the theoretical or global
sense and was only weakly connected to ‘Business’. Whereas the concept of
‘Business’ was strongly connected to the concept of ‘Local’. The relationship between
these concepts illustrates some of the issues of identity and economic disparity but
discussed from a different dimension.
Box 5.11. MPA team participant discussing globalization’s impact on the local economy “The business that stands is still not employing majority local. And so they are - anything that they are consuming - everything it is - it is local but then it is just geared off and it is corded off.” – MPA Team Participant
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 “... You could talk about businesses but if you get outside investors and one thing about outside investors I have noticed from my experience living on St. Thomas, people that are not from here do not stay here. They stay here for five years the most and they end up leaving. So unless you put the businesses in the hands of the people that from here it is going to be the same thing happening - okay, this business is going
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to open for five years and then close. And then they are going to move off island and the next person that is not from here is going to come, open a business - why is that Tortola is more successful and a lot other countries are more successful then American countries because they take pride in local ownership and not monopolizing on this whole I love America, land of the free. Land of the free basically means that anybody can do whatever, shit on it and leave, so it is a cycle.” – Hospitality Social Group Participant
Box 5.13. DPnR participant discussing lack of reinvestment in the community and the tendency for profits to leave island “Businesses are my number three negative. All of a sudden there is - a lot of the money goes somewhere, it goes off island. So our - that - you know, they are overtaxed and they are over WAPA and not able to thrive and reinvest in the community. So as much as I am not pro ad hoc development, I am pro-business. I think that they really reinvest in communities and I think that there are a lot of actions that prevent businesses from thriving. So we would take action to prevent that.” – DPnR Participant
Box 5.14. Farming co-op participant discussing the need for more local business to create a self-sustaining community “I have seen, in bags at Cost-You-Less, they have frozen mangoes. We can freeze our own mangoes. They have mangoes in St. Croix dropping off the trees and when that [chain] store closed everyone was all upset in St. Croix, but if you look at that you could take that building and turn it into some type of self-sustaining business for your community. Tamarind over there drops off, and yet you still can see in the stores tamarind balls from Jamaica and things like that, it does not make any sense. We should be doing it so that we can be self-sufficient and so that we can send that to the cruise ships and let them know and more people will want to come and I could keep going on and on, so I will stop.” – Rastafarian Faming Co-op Participant
Box 5.15. Eco-outreach participant discussing pressure local businesses face due to increasing energy costs “Local small businesses. Do I think more is going to close? Yes, if we do not find a proactive way of finding more energy efficient ways or leaders do not become better leaders to find ways to find sufficient ways for costs to drop or...small businesses are going to go out of business.” – Eco-Outreach Participant
The Role of the Environment
While not as highly central as the other themes, concepts related to the
environment and natural resources were still integral to the discussion networks (see
table 5.4). However; as the discussion was centered on environmental sustainability it
is interesting that environmental concepts were not more central or specific. In fact the
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concepts of ‘Environment’ or ‘Environmental’ were generally used broadly and were
most strongly connected to ‘Impact’, ‘Resources’, ‘Economics’ and ‘Energy’ (see
figure 5.8). These connections were often self-contained within the network as well. Box 5.16. Eco-outreach participant discussing the role of community groups creating awareness of environmental and energy impacts “We have reached this point, I think we have been to points before where it has been fire, fire and then the fire is out. But, we have gotten to that point now where you have to seriously take account of the energy and the cost because we are at that point right now… and looking at different programs and how to address them. We have agencies such as …the hotel association now where they have the environmental committee and really trying to move our community forward and be more aware of the impacts, environmental impacts that all of these different things…when you look at it, when we talk about energy, where it impacts the business community.” – Eco-Outreach Participant
The connections and conceptualization serve to frame the role of economics when
considering the environment: Box 5.17. Eco-outreach participant linking economics as driving force for sustainable energy “We are seeing now the solar, the wind, and all those that are coming pretty strong…as far as the public accepting it and actually wanting it. The demand now is being set. I do not know necessarily that is in the name of being sustainable and more in the name of economics, but the bottom line or the result being that the technologies that are being explored are lower impact on the environment and hopefully more sustainable in the long run and hopefully economically - which is what is really the driving force I think from a community stand point to move in that direction.” – Eco-Outreach Participant
Table 5.4. Concepts comprising the ‘Environment and Resources’ theme
IV. Environment and Resources
Centrality Metric Concept Frequency Centrality Score
Weighted Score
In-Degree Water 46 .937 .044
Out-Degree
Environment 33 .747 .049
Sustainability 64 .861 .049
Agriculture 38 .772 .044
Node Betweenness Environment 33 .001 n/a
Environmental 93 .001 n/a
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The use of term ‘Sustainability’ was mostly associated with the farming co-op
who frequently discussed it in terms of ‘Growing’ ‘Food’. In fact, in general there
were some distinct differences in how groups discussed the environment beyond its
relationship with economics. The term ‘Agriculture’ was primarily associated with the
farming co-op and the hospitality social group, whereas the management groups were
more likely to discuss ‘Water’ (referring to the ocean) when talking about the
environment. This suggests differences in sense of place regarding the considering the
role of the natural environment. This may have cultural or livelihoods based roots as
the management groups tended to have more continentally born members and worked
in marine management whereas the farming and hospitality groups were exclusively
locally born.
Some Initial Conclusions from Universal Themes in the Discourse
When evaluating the universal themes from the discussion there are some clear
conclusions. The first is the primary role that sense of place, Identity and planning
played in participants’ evaluation of the system. This suggests that environmental
outreach and education programs would likely greatly benefit from understanding and
contextualizing their message and efforts to align with the pre-existing social and
physical sense of place shared by the target audience.
The second is the strength of the shared perspectives of globalization as a
driver for the system. This was evidenced by the discussions relating to changing
demographics, graying local culture, perceived lack of business engagement at the
local level and the general economic disparity and lack of control of participants to
impact the system. Considering that the environment was often discussed in relation to
economics, these connected issues may impact groups’ perceived power regarding
stewardship. As one participant noted:
Box 5.18. Eco-outreach participant discussing lack of community control “We all want the same thing. It’s just that none of us have the power or money to do it.” – Eco-Outreach Participant
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The tendency for each group to focus on social and economic issues rather than
environmental ones when considering the sustainability of the system suggests that
there may be an hierarchy similar to ‘Maslow’s Hierarchy of Needs’ in which social
groups that experience disempowerment often do not perceive themselves as capable
of stewardship activities or power. This may be evidenced by the more central nature
of the social and organization themes related to disempowerment, identity and sense of
place compared to concepts related to the natural environment.
The third conclusion from this initial analysis is that there may be differences
in ways that groups discuss and relate to the natural environment itself. This is
evidenced by the frequent connection of locally born participants with terrestrial
(primarily agricultural) relationships between livelihoods and stewardship compared
to continental migrant resource managers who tend to focus on ‘Water’ as a source of
livelihoods and conservation ethic.
Section II: Analysis of Exercises
Section II of the results chapter will analyze each exercise individually. The
findings within this section echo many of the universal factors informing participants’
perspectives. For instance, in 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.
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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 concept were identified as more effective. There was also further evidence
of differences in 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.
5.3 Exercise #1: Choosing a Future Scenario and Time Frame
The first exercise involved participants conceptualizing a potential scenario
and time frame to use as their focal future state. Although there was a difference in the
range of scenarios each group explored, overwhelmingly they all chose the “Pushed to
the Limit” scenario as the focus for the scenario planning process. The general
consensus from each group was that due to the past economic development patterns on
St. Thomas that the future of the island is headed towards a negative critical state.
Similar to the findings from the overall discussion issues of economic disparity and
disempowerment were seen as a major driver for the future direction of the island.
The impact of legacies on the potential future of the system appeared intuitive
and essential to groups’ formulation of a future state. Most groups acknowledged an
either present of past trend of “Money Matters” economic development as a primary
driver for the “Pushed to the Limit” state. The contribution of issues such as local
employment and business patterns on participant’s outlook of the future is covered
more extensively in the overall themes section of the results chapter.
Box 5.19. MPA team participant describing the range of potential future changes “…It seems like there is this struggle between money matters. Maybe in the past…what has driven things is this money matters and that is what sort of got us
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pushed to the limit. And that maybe these other areas are taking precedence and I would hope that the future… that there is more influence from these other areas and I would hope that we would pay more attention to community and to science and technology …using knowledge based decisions “ – MPA Team Participant
Several participants acknowledged the growing potential of a “Community
Rule” scenario due to a perceived increase in community action groups and
environmental programs although they believed it would not happen within the 15
year time frame.
Box 5.20. Eco-outreach participate describing hope that the community will have more power in the future “Yea, pushed to the limit in five years...it will be the community that will be taking control the fix it though. I feel like we are on a downward spiral but I feel like we have some community leaders that are voicing concern.” – Eco-Outreach Participant
A correspondence analysis of phrases with at least two words and a minimum
frequency of five illustrate some of the differences in groups’ consideration of a future
state. A correspondence analysis functions by using the similarity coefficients for each
semantic concept in the network to create a Cartesian coordinate system. The concepts
are then plotted with respect to their relative positive to each other. This results in the
most commonly associated and shared concepts centered in the middle of the two-
dimensional coordinate system. Each concept’s two dimensional factor scores (based
on similarity matrix) are used to compute the concept coordinates in space. Finally the
overlapping correspondence attributes (in this case the community groups) are also
positioned in relation to each other and the concepts with respect to their group
average similarity coefficient for these concepts. For a comprehensive explanation of
correspondence analysis see (Greenacre 2010).
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Figure 5.9. Correspondence plot of phrases extracted from the exercise #1 discourse. Phrase
extraction based on minimum frequency of five, R2 = 0.813
The two management groups, MPA Team and DPnR, were more likely to
consider “Science and Technology” or “Community Rule” whereas the Eco-outreach
group focused on “Small Business” and the Hospitality Social Group were the most
dramatic considering a “Rock Bottom” scenario. In the center of the plot we see that
the reoccurring sense of place “Virgin Islands”, as well as “Knowledge and
Application”, “Money Matters” and “Pushed to the Limit” were all relatively shared
by the groups. In general the management groups were more likely to consider the
theoretical implications of the future trends whereas the livelihood and outreach
groups were more likely to consider their day to day realities (see figure 5.9 above).
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Figure 5.10. Correspondence plot of semantic concepts extracted from exercise #1 discourse
R2= 0.661
When we examine the correspondence plot of all concepts discussed during
exercise #1, it is clear there is a great deal of shared language among the groups. As
could be expected, differences often existed based on the goal and nature of the
community group (see figure 5.10). For instance the Eco-outreach group discussed
issues involving energy costs, economics, businesses and education as many of the
members are small business consultants and educators. Box 5.21. Eco-outreach participant describing energy as a driver for the ‘Pushed to the Limit’ scenario “I definitely agree. I was going to say, with the energy. I think energy if anything is the one that is pushing us to the limit. It is impacting in every arena you know whether it is the business community, whether it is waste, whether it is water quality, whether it is … I think we are at the push the limit with the community as a whole of just being fed up. We are seeing now the solar, the wind, and all those that are coming pretty strong. You know as far as the public accepting it and actually wanting it. The demand now is being set. I do not know necessarily that is in the name of being sustainable and more in the name of economics, but the bottom line or the result being
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that the technologies that are being explored are lower impact on the environment and hopefully more sustainable in the long run and hopefully economically …which is what is really the driving force I think from a community stand point to move in that direction.” Eco-Outreach Participant
The two management groups, DPnR and the MPA Team were more likely to
discuss development, system dynamics and planning.
Box 5.22. MPA team participate describing past development strategies as contributing to local disempowerment “…Historically… we invite the opportunity …to drive this sort of industry because yes, we are going to create jobs and this and that, but then when you turn around and you assess that five years later you know, even if you are looking at it from the development standpoint the jobs that created mostly were not local. People came in to do them.” – MPA Team Participant
Box 5.23. DPnR participant describing the role of development in decision making processes “…It comes back to money matters in the sense that that investment, that initial investment from this construction company when they were coming in and building a new development weighs a lot on people who are in power right now. Anyway, you know they want that. They want that development to happen. They do not care about moving to long term goals and having a STEER [Marine Protected Area], or having a place for people to go see that natural environment here in the Virgin Islands. They really just want that hotel bill so they can tax it.” – DPnR Participant
The Hospitality Social Group, whom took the most pessimistic outlook on the
future, discussed issues of hitting “Rock Bottom” due to poor attitudes and increasing
economic disparity resulting in increased crime.
Box 5.24. Hospitality group participant describing how rising crime may begin to impact tourism “I do not think that it is going to get rock bottom …. but more home invasions, robbery, crime and it is already on that path right now...instead of the crimes staying to more urban places and I think the crime is going to branch out into main streets, more robberies on tourists.” –Hospitality Social Group Participant
The Rastafarian Farming Co-op had a holistic outlook that included many of
the core themes discussed by the other group. Specifically, participants from this
group expressed concern regarding issues of exclusion and development.
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Box 5.25. Participant discussing exclusion as a driver for ‘Pushed to the Limit’ scenario “What I am saying we do not come in because they are not planning it for we... they plan this thing excluding we. They pushing we out. Their society is pushing we out, plain and simple. And pushing us out economically, that is why everything is so high. Somebody here, all the people love this place more than we. This is our push back; this organization is a push back to say that we are not accepting that. We basically underdeveloped and when I say underdeveloped, I am not saying we are not developed. Under developed in my definition is the fact that development is there, but we are not there with the development and that is there on purpose… we are pushing back because agriculture is that important. But we are even more important and we must take a stand.” - Rastafarian Faming Co-op Participant
So while there were some optimistic responses regarding increased community
development and participation in decision making overwhelmingly groups shared a
fatalistic future of the island in the near future. Many of the reasons for these
perspectives relate to disempowerment, economic disparity and cultural exclusion as
discussed in great detail in the first section of the results chapter.
Summary Conclusions
Ultimately, due to many of the issues discussed in the overall themes,
participants chose a “Pushed to the Limit” scenario within a five to ten year time
frame.
5.4 Exercise #2: Discussing and Ranking Drivers for the Future
The second exercise yielded the longest and most engaged discussions from
the scenario planning protocol. During this discussion participants were asked to
consider and rank the three most positive and three most negative drivers of the
“Pushed to the Limit” future they described in exercise #1. In total during this adapted
Q-method portion, participants wrote down a total of 176 separate statements with an
average of 5.87 statements per participant (See table 5.5).
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Table 5.5. Shows the summary information from the Q-Method statements Categorical Driver Statements (n) 176
Average # of Drivers per Participant 5.87
Std. Deviation 1.74
Participant min contribution 0; 4*
Participant max contribution 11
*One group member did not participant in this portion, the next lowest min.
was four
Following the focus group session, the statements derived from the exercise #2
were coded according to Social-Ecological framework’s eight categorical drivers.
When all the statements were considered together without ranking, overwhelmingly
Institutional Arrangements were the most frequently cited categorical driver (see
figure 5.11). In fact statements relating to Institutional Arrangements accounted for
33% of the total statements. Estimating both a runs test (p=0.0) and a one-way chi
square (p=0.0) found that there was structure to the data. Statements relating to Well-
being, Economics and Perceptions of the Environment were also frequently considered
as critical drivers. Combined these four categorical drivers accounted for 76.1% of the
total statements (see table 5.6). When each individual group’s frequency distribution
was examined, there were similar trends across groups with the exception of the
Rastafarian farming co-op whom tended to focus on Environment and Resources more
heavily than other groups (20% of total compared to 5-10% for other groups) most of
which was related to farming (see figure 5.12). While most groups tended to focus on
Institutional Arrangements this was especially true for the MPA Team and the Eco-
Outreach group, who discussed these drivers approximately 50% of time. A
correspondence plot (see figure 5.13) also illustrates the similarities and differences
between groups with the only substantial difference being the farming co-ops tendency
to list statements relating to Environment and Resources and Cultural Properties more
often than other groups. It also demonstrates the degree to which the eco-outreach
group chose Institutional Arrangements compared to other drivers.
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Figure 5.11. Frequency distribution of statements across the SES meta-category framework
Chi2 =0.0
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Table 5.6. Total and cumulative percent of the categorical frequency distribution of Q-statements
Categorical Drivers Frequency Percent Cumulative
Percent
Institutional Arrangements 58 33.0 33.0 Well-Being 29 16.5 49.4 Economics 24 13.6 63.1 Perceptions of Environment 23 13.1 76.1 Environment and Resources 18 10.2 86.4 Infrastructure and Services 13 7.4 93.8 Population Demographics 6 3.4 97.2 Cultural Properties 5 2.8 100.0 Total 176 100.0
Figure 5.12. Distribution of group’s percent of total frequency for each categorical driver
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Figure 5.13. Correspondence plot of categorical drivers by group
Although initially participants were asked to rank their statements using an
ipsative scale (three most positive and three most negative drivers), this portion of the
focus group proved to be rather complicated and perhaps due to lack of experience of
the facilitator, genuine rankings were not always provided. In fact some participants
preferred not to participate fully in this portion and their statements were written
verbatim by the facilitator. Additionally, by allowing participants to create their own
Q-sorts, it was often difficult to compare scale rankings as participants would choose
similar topics but opposite qualifiers. (I.e. more government support +3, lack of
government support -3). This made it difficult to uniform each statements and
compare based on a factor analysis. Therefore only the general ranking of statements
as either positive or negative was used for the analysis. When the statements were
examined based on a general negative or positive ranking, it is clear that issues related
to Institutional Arrangements and Population Demographics were more often viewed
as a negative. Potential for positive changes were often viewed in context of Well-
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being, Infrastructure and Services, and Perceptions of the Environment (see figure
25).
Figure 5.14. Frequency with which categorical framework drivers were ranked as either
negative or positive
In order to give greater clarity to the drivers each individual category was
further reduced to distinct themes, both positive and negative. These themes emerged
and were coded as a result of the content of the statements themselves.
The 58 total statements relating to Institutional Arrangements that were ranked
by participants were then coded by the research team into six semantically distinct but
ultimately related themes: planning, leadership, enforcement, corruption, small island
dynamics and community decision making (see figure 5.14).
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Figure 5.15. Frequency with which emerging themes related to Institutional Arrangements
were ranked as either negative or positive
As noted earlier, the majority of drivers related to Institutional Arrangements
were perceived as negative, specifically the aspects related to a lack of enforcement,
poor or uninformed leadership, small community dynamics and institutional
corruption. Small island dynamics in this context referred to both the segregation of
small communities from each other as well as favoritism or nepotism among
community and familial relations. For instance: Box 5.26. Examples of statements ranked by participants relating to ‘small community dynamics’ “Segregation or uncoordinated communities impedes progress” “Strong clash of interest between different sections of community” “Small community allows nepotism”
Lack of enforcement was cited by both DPnR and Eco-outreach groups exclusively and contained some overlap with small community dynamics and leadership.
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Box 5.27. Examples of statements ranked by participants relating to ‘enforcement’ “No Enforcement, friends and family have no accountability” “Lack of Enforcement of existing regulations and lack of interest to update regulations”
Leadership, planning and corruption were all related and focused on the role of
the government. Participants’ statements perceived the government as either corrupt
and/or amoral and in general displayed a minimal amount of trust in government
officials. Statements were often phrased indicating a lack of government
environmental and financial planning. Subsequently, a lack of proper, competent or
informed leadership was a critical driver discussed by each group.
Box 5.28. Examples of negative statements ranked by participants relating to ‘leadership, planning and corruption’ “Leadership without knowledge of impact on resources” “Improved leadership, experts for the people” “Overall accountability systems implemented” “Need for a land management policy” “Corrupt government officials looking out for their own best interests”
When these issues were ranked as positive it typically involved a change in the future
in order to create a positive driver. Box 5.29. Examples of positive statements ranked by participants relating to ‘leadership, planning and corruption’ “Taking a stand against negative government” “Leadership to marry technology and farming practices” “Leadership has to prioritize the environment in decision making policies”
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While the negative drivers consisted of segregated communities and a lack of
enforcement, planning, proper leadership and corruption the only exclusively positive
driver related to community decision making. Box 5.30. Examples of positive statements ranked by participants relating to ‘community decision making’ “Government more involved in community action groups” “Development of community Action committee and their involvement in policy making and implementation” “Community continuing to work together to build agricultural production” “Science based decisions: communities' needs and wants are integrated into best known practices stemming from available science and technology”
The dominance of Institutional Arrangements during the ranking of drivers by
participants illustrates the importance of perceptions regarding decision making and
political systems. When the statements were examined in more detail a clear narrative
emerges in which participants perceived the island as suffering from insufficient
governance and support, fragmented social and community groups, exhibit a lack of
trust towards government officials, and see increased community involvement and
decision making as critical positive for the future.
Within the Well-Being categorical driver there were six themes identified:
General well-being, poverty dynamics, employment, education, community values,
and attitudes. It was two key themes that dominated the rankings however; education
was frequently cited as a positive driver for the future whereas statements related to
poverty dynamics were cited as negative drivers (see figure 5.16).
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Figure 5.16. Frequency with which emerging themes related to Well-Being were ranked as
either negative or positive
Poverty dynamics in this instance included statements such as:
Box 5.31. Examples of statements ranked by participants relating to ‘poverty dynamics’ “Poor access to health services” “Access to affordable food and utilities decreases” “Crime, poor health and lack of community cohesion” “Dependence on government, lack of self-reliance” “Discipline: parenting and laws to be stricter all rules should apply to everyone” “Cost of living compared to current agricultural production”
Education was considered a potential positive but participants were discussing
a change in education not a continuation of something pre-existing in the system.
Education was also discussed broadly, in both environment and general terms. It was
also extended beyond the school system to include community education.
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Box 5.32. Examples of participants’ statements relating to ‘education’ “Education system improves giving children positive choices” “More Education both environmental and other” “Community Education” “Environmental education incorporated in education system”
Similar to the statements related to Institutional Arrangements, increasing and
understanding community values were also seen as a potential positive driver to the
future. Finally attitudes were seen as a negative due a: Box 5.33. Example of a participant’s statement related to ‘attitudes’ as a driver “General Lack of Caring of the People” – Eco-Outreach Group Participant
Well-Being as a dominant driver communicates the role of health, security, and
education into the future state of the island. Specifically the degree to which groups
refer to community cohesion, health and education builds on the existing narrative
from the previous driver regarding the need for the community to play a greater role in
decision making processes.
When the role of Economics was analyzed there were five themes that
emerged: planning, local economy supporting the community, environmental friendly
businesses, economic disparity and business education (see figure 5.17).
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Figure 5.17. Frequency with which emerging themes related to Economics were ranked as
either negative or positive
The most negative theme from this driver was economic disparity. This was
also reflected strongly in the discourse analysis from the combined focus group
transcripts as well as similar to the reasons stated for choosing the “Pushed to the
Limit” scenario.
Box 5.34. Examples of participants’ statements related to ‘economic disparity’ as a driver “When big money rules (i.e. tourism), usually community needs are cast aside, and only a few benefit”
“Strong monopoly of economic resources in the hands of a selected few”
“Economic Development, money over values”
Much of the discussion surrounding these drivers revolved around the nature of
tourism development on the island. Related to economic disparity was the theme of
local economy supporting the community.
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Box 5.35. Examples of participants’ statements related to ‘local economy supporting community’ as a driver “Local economy will support community needs/wants to create decisions and plans, and institutions and policy support that” “Pertaining towards business endeavors and investments with local partnerships” “Support local cultural aspects through economic development”
This theme was also strongly emphasized in the overall network analysis.
Participants generally felt that due to economic disparity caused by traditional
development, in order to create a more positive potential future state that business
patterns need to shift to a more locally driven and supporting process. In addition to
this increased business education for the local population was a positive driver for the
future. Box 5.36. Examples of participants’ statements related to ‘business education’ as a driver “Better education, training, and counseling” “Lack of education towards the tourism market”
The final theme for this category is primarily considered a positive and is the
development of environmentally friendly business practices. In general this theme
involved the increase in eco-tour tourism, supported responsible business patterns and
encouraging local participation in environmentally related businesses and jobs, such as
eco-tours and agriculture.
Box 5.37. Example of participants’ statements related to ‘environmental business’ as a driver “Increased Ecotourism (i.e. leads to protection of resources)” “Increased opportunity for employment/training in natural resource and environmental fields for local population” “Supplying agriculture products to local shops and grocery stores”
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Perceptions of the Environment emerged as the final critical categorical driver and had
four themes within it: science communication, environmental ownership,
environmental awareness, and attitudes (see figure 5.18)
Figure 5.18. Frequency with which emerging themes related to Perceptions of the
Environment were ranked as either negative or positive
Increasing environmental awareness was the most overwhelming positive from
this categorical driver. These statements revolved around increasing the social,
economic, cultural and spiritual values of the natural environment. This theme could
be thought of the inverse of the environmental ownership in which participants saw a
lack of community and environmental ownership which was perceived as critical to
reach a more positive potential future state. In part this was thought to be due to poor
individual attitudes towards the environment. These themes, although frequently
discussed, were the most abstract and difficult to define. When engaged regarding
changing attitudes it was difficult for participants to describe what causes or promotes
a change in attitude.
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Box 5.38. Examples of participants’ statements related to ‘environmental awareness’ as a driver “Regaining our appreciation of the earth” “Increased awareness and understanding of cultural background and social values of environment” “Increased Awareness of Economic Value of Ecosystems”
Box 5.39. Examples of participants’ statements related to ‘environmental ownership’ as a driver “Residents become more responsive to stewardship” “Not accepting ownership of outcome derived from action”
Box 5.40. Examples of participants’ statements related to ‘attitudes’ as a driver “Negative mindsets and attitudes towards environments” “Change of attitudes and perceptions towards the environment” “Attitudes need to change”
While the other categorical drivers were not listed as frequently some themes
arose from them as well. Discussions surrounding population demographics mirrored
themes from the overall network regarding immigration rates and “brain drain”
resulting from high emigration rates. Cultural properties were often seen as a positive
regarding a need to increase the understanding and economic development
surrounding cultural history and heritage sites. Infrastructure and services almost
exclusively focused on a need for increased government support of agriculture and
alternative energy sources. Environment and resources again was heavily discussed in
relation to agricultural needs as well as the potential negative consequences of natural
disasters and climate change.
Summary Conclusions from Q-method Statements
There were some clear conclusions from the analysis of the statements
regarding participant’s perceptions of the drivers of the system. Overwhelmingly,
statements related to increasing community decision making capacity, values,
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ownership and understanding were some of the most frequent and the most positive
drivers. Based on analyzing the negative drivers, there appears to be a perceived lack
of competent, supportive and fair governance and business policies and decisions (see
table 5.7).
Table 5.7. The most critical drivers from the Q-Method portion of exercise #2
Variation in Group Responses
As evidenced by both the frequency distributions of each groups statement and
a correspondence plot of concepts extracted during the exercise #2 discussion, there
was a great deal of agreement by groups of the drivers of St. Thomas as a social-
ecological system (see figure 5.19).
Value Key Drivers
Positive
Community Decision Making
Education (community and individual)
Community Ownership/Increase social values
Local Economy that Supports the Community
Business Education
Environmentally Friendly Business (Eco-tour, etc.)
Environmental Awareness (Individual and Institutional Levels)
Improved Infrastructure
Economic Development Around Cultural History and Heritage Sites
Negative
Insufficient Government Leadership
Lack of comprehensive planning and vision for Island Development
Lack of enforcement/accountability at Institutional and Social levels
Economic Disparity
Poverty Dynamics
Poor Attitudes
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Figure 5.19. Correspondence plot of concepts extracted from the exercise #2 discourse
R2= 0.62
There were however some distinctions between groups. The three non-
management groups are all located on the bottom of the plot and were more likely to
share concepts such as ‘attitude’, ‘local’, ‘energy’ (WAPA), ‘Virgin’ and ‘investment’.
These concepts related to a lot of cultural and place specific issues whereas the
management groups are more likely to share concepts such as ‘economic’,
‘opportunity’ ‘population’ and ‘social’ which are more theoretical conceptualizations.
The third quadrant hold the Hospitality social group and the farming co-op both of
which shared concepts such as ‘market’ ‘agriculture’, ‘food’ and ‘grow’. This is
reflective of the shared understanding of these groups linking agriculture, culture and
livelihoods that was explored in the overall themes results section. The Hospitality
social group was more likely to discuss local and cultural business. For instance
‘sugar’ refers to a lengthy discussion by the group regarding cultural tourism
development in the form of refurbishing old sugar mills.
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5.5 Exercise #3: Defining Sustainability and a Headline Indicator
Following the detailed discussion of the positive and negative drivers of
change the pushed to the limit focal scenario, groups were asked to define and
describe sustainability in St. Thomas given all the variables they had just discussed.
This exercise, by far, was the most difficult for groups to answer. It produced the
fewest responses and the smallest network. In fact, even when all the conversations
were combined there were only 13 concepts extracted that satisfied the minimum
frequency of ten requirements. Participants had a difficult time summarizing or
encapsulating all the complexities they had just discussed. This may have been a
product of overstimulation due the previous hour and a half long discussion of the
future and its key drivers. Although however, when groups were asked to choose a
specific indicator of sustainability (see Chapter 3 Field Methods Section IV)
consensus was typically reach easily. In the case of the Hospitality Social Group they
chose two separate indicators electing to distinguish between social and environmental
sustainability.
This phenomenon was true for each of the five groups. Groups had difficulty
defining sustainability in general terms but could easily identify an indicator for it.
This may be in large part due to the ambiguity surrounding sustainability as a
theoretical concept discussed in the background chapter of this thesis. There was a
division regarding the choices of the drivers which relates to previous findings
regarding sense of place and environment. Both the hospitality social and the eco-
outreach groups chose alternative energy as a potential indicator of sustainability
whereas the two management groups chose a reduction in sedimentation as a potential
sign of sustainability (see table 5.8). In fact the DPnR group chose the anthem
“Bottom of Benner Bay” as their focal point. Benner Bay is the largest bay in the
recently created MPA site which is often plagued by poor water quality. The
Rastafarian farming co-op didn’t have time to respond the specific indicator question.
Some general themes that arose from the discussion were the role of governance and
decision making in sustainability as well the rising cost of energy. This was the only
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exercise where sense of place concepts were not present reflecting the more abstract
nature of sustainability as a social construct.
Table 5.8. Group responses to choosing a tangible indicator of sustainability
Tangible Indicator of Sustainability
MPA Tea Reduced Sedimentation, Plumes, etc.
Social Hospitality
Group
Social: less government corruption; Environmental: Energy
Alternatives
DPnR Reduced Sedimentation, “See the Bottom of Benner Bay”
Rasta Farming Co-op n/a
Eco-Outreach Reduced energy cost and energy alternatives.
Figure 5.20. Correspondence plot of concepts extracted from the exercise #3 discourse
R2 = 0.773
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Groups found it difficult to find a cohesive vision for what they felt a
sustainable future would look like despite having enthusiastically provided detailed
lists of potential future directions and causes for negative and positive outcomes (see
figure 5.20). The one slight exception to this was the Rastafarian Farming Co-op
group which took a literal and culturally based take on sustainability: Box 5.41. Farming co-op participant describing sustainability in St. Thomas “When you say sustainable, that is real interesting because that is what we are about. That is what we have become. We are trying to sustain, at least this way of life. The agriculture aspect of life, see, when you ask where we are going to be five or ten years, that is a horror story at least for me. As I look at things, because I live here all my life and things are getting tougher and tougher and tougher for local people, people like us. It is just getting harder and harder to live.” – Rastafarian Faming Co-op Participant
Much of the farming co-op’s discussing of sustainability revolved around sustaining a
‘way of life’ and cultural heritage which they tied into stewardship ethic.
Box 5.42. Farming co-op participant discussing Rastafarian culture as it relates to stewardship “Now, as far as for me personally with agriculture, I love agriculture. People ask where you were born in this city, you were not even... well, even as I begin to know myself and understand a whole process of environment, I have been studying and working towards farming since the seventies, taking classes, learning more, reading books more about our environment... I have planned everything from when my children were babies and I told them we are going to live on a farm and it was like everything came true when I came to St. Thomas. I did not realize this was going to be my place. I never ever thought this would be my place, but it is and it is a good place. There is plenty of sun; our community is a strong community as far as the love for the environment. And within Rastafarians, that is the important thing is our environment. It is not like the abuse of the environment that goes on in other part of the world or even St. Thomas... there is a lot of abuse to the environment. In order to sustain the community, you have to first sustain your environment because man is not in control and nature is in control, and you see it all the time with the weather pattern and what has happened with the weather pattern due to man is greed of wanting to build and have factories and manufacturing. If you look over in the countries now, like China, Viet Nam, you will see the cycle... more damage done to people, more illnesses are going to occur, because again, they turned their back on their environment and the environment eventually is going to catch up with you.” – Rastafarian Faming Co-op Participant
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While the farming co-op had a clearer vision of sustainability the Eco-outreach
group’s discussion devolved into a rant regarding the cost of power on the island as
charged by the Water and Power Authority (WAPA):
Box 5.43. Eco-outreach participant expressing anger towards the cost of energy in St. Thomas “And, I am burning a WAPA bill. You know that…” – Eco-Outreach Participant
The Hospitality Social group discussed sustainability from a simpler, broader and
idealistic perspective:
Box 5.44. Hospitality group participant discussing an idealistic version of sustainability “Everyone would - the majority of people would have good paying jobs in what they want to do.” –Hospitality Social Group Participant
And the management groups discussed sustainability in terms of decision making:
Box 5.45. MPA team participant discussing sustainability as a process of decision making “I mean I guess this decision - this information based decision making would be by some sort of dispassionate objective as much as possible analysis of - huh?...” – MPA Team Participant
Box 5.46. DPnR participant discussing sustainability as a process of decision making “I think it is thinking with a longer term vision. So I am going to think fifty years from now what I want the Virgin Islands to look like and I want - I think the choices are big. I think the ability of people to make positive choices because they either can or they have that knowledge so I want to choose in fifty years to have access to clean water. And I think waste management is going to be huge in fifty years. So I think it is the ability to make those choices on a longer term but also the knowledge to not make necessarily shooting for bottom choices but social and ecological, positive choices. I do not know it is hard I guess.” – DPnR Participant
This more abstract conceptualization of sustianability as a series of long term
decisions was also echoed by the rastafarian farming co-op: Box 5.47. Farming co-op participant linking a bottom up approach of governance to sustainability “… It is a mindset, but I believe it is a mindset of the people understanding the government because I do not believe in the top down approach as a solution to anything. If the people demand it, we will have to supply it. And if supplying it, we will get help from the government eventually because the people who elect them, who
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only elect people that will be in their best interest. And so the issue is when we think about sustainability as a people the Virgin Islands will never be able to sustain themselves if we do not change our mindset. Because we are so crippled by this being a territory of the U.S. government because we always were comfortable with the fact that everything was always coming to us and aid will never stop. I would not say aid because we are not a third world country at this time, but we do not know what the future holds. If the US decides to pack up and ship today, we are screwed. I think we will be even worse off than countries like Haiti because in terms of spacing, for the population that we have, can we really sustain ourselves with the little land we have with the population? I am not so sure about that.” – Rastafarian Faming Co-op Participant
Summary Conclusions
Ultimately it was these themes of attitudes, decision making and a long term
vision that informed groups loose definition sustainability. However, regarding
indicators the only group that touched on those themes was the hospitality social group
which elected to have a social and environmental indicators. The social indicator they
chose was less government corruption which was also discussed heavily during
exercise #2. Once again there was a cultural divide regarding the environment in terms
of the sustainability indicators. The locally born groups both agreed on alternative
energy as an indicator whereas the continentally born management teams focused on
the marine environment by choosing a reduction in sedimentation as their indicator.
The lack of sense of place concepts throughout the discussion illustrates the vague
nature of sustaianbility as a social construct. When considered in combination with the
more robust responses during exercise #1 and #2, using the term or conceptualization
of sustainabilty for engaging stakeholders or resource managers may not be as
effective as place based discussion points and references.
5.6 Exercise #4: Discussing Preparedness for the Future as a Measure of Social
Resilience
The final exercise of the scenario planning focus group comprised of asking
participants to describe their personal as well their perceived community’s preparation
for the future scenario they chose. Due to time constraints the MPA Team was not
able to participate in this exercise. Similar to exercise #3 this exercise did not yield a
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lot of responses nor results. In fact, only 19 concepts were extracted based on the
minimum frequency of ten requirements from the final exercise. However, there was a
great deal more clarity of themes and vision regarding groups’ preparedness for the
future. In general none of the groups expressed a great deal of security or optimism for
the future which could be expected considering the fatalistic scenario they were
exploring. The two primary themes that emerged from the conversation were cost of
living and graying or displaced culture. Both of these themes were also reflected in
the overall discussion analysis from section one of the results chapter.
Figure 5.21. Correspondence plot of concepts extracted from the exercise #4 discourse
R2 = 0.791
In general the hospitality and farming co-op groups were more likely to discuss
preparedness in context of ‘local’ vs. non local and from a cultural standpoint.
Whereas DPnR and the Eco-outreach groups were more likely to discuss issues related
to ‘jobs’ and how much they could ‘make’ (see figure 5.21).
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The hospitality social group expressed a lack of both personal and perceived
community preparedness for the future based on lack of opportunity, training,
economics and poor attitudes. Box 5.48. Hospitality group participant discussing preparedness for the future “… It is like nobody cares, everyone feels they know, from young, you go to high school, you never had good counselors, and you never had good direction, nobody like gives a shit when you go to the public high schools down there. A lot of kids leave the high school, not really knowing what they want to do. Even if they know what they want to do, they do not have a direction to go there.” – Hospitality Social Group Participant
Box 5.49. Hospitality group participant discussing preparedness for the future “Let us just put it this way, give it about 10 more years and Florida and Atlanta will be the new St. Thomas. Everybody will move up here and you will get a bunch of old people down here.” – Hospitality Social Group Participant
Box 5.50. Hospitality group participant discussing preparedness for the future “Speaking from like my age group because I am a lot younger then pretty much everybody else at this table, my age group looks at everything negatively like we could spit those ideas at them and the first thing they are going to say is nothing is going to change.” – Hospitality Social Group Participant
Box 5.51. Hospitality group participant discussing preparedness for the future “Honestly, so I grew up without my pops, and my mom is not here so it is just me and my girl here. Yea basically, me and my girl talk about having kids and staying here and she is constantly asking me if I want to move, she does not see it staying here. Basically what he said, the moves we make here we could make twice as much up there. It is just not, there is no vision, due to what is going on in the island. There is just no vision. For me personally, I am ok but I do not how far I can go.” –Hospitality Social Group Participant
Similarly the Rastafarian farming co-op’s outlook was bleak, albeit less so than
the hospitality group. For them the future depends heavily on reinvestment both from
the government as well as other members of the community. Box 5.52. Farming co-op participant discussing preparedness for the future “We do not look good presently. Presently our average farmer age is fifty-five years old and we do not have a young set coming along. We have nobody coming along, so that is where we at right now. So if we stay on the same trend in twenty years we probably will have no farmers. That is our push back. We pushing back to change that
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trend. Our intent is to grab some of our young people and train them into farming that is our only hope because... what we do have is we have farmers presently who have the experience. But of course, their legs are not young anymore, so we definitely need some young legs to turn that knowledge on to continue this process.” – Rastafarian Faming Co-op Participant
Box 5.53. Farming co-op participant discussing preparedness for the future “Like I say, look who is coming now... Taiwanese or whoever come here, they come here and they want to develop selling us this tamarind, but we have tamarind all over here that is like Dominica, you have breadfruit, in Dominica, they picking the fresh breadfruit and the fresh fruits they send to London and they send it back in a can or in a box. So it is like it is the people who running the place are to blame for all this going on because they could do better and make it better, but if you have... if we try to make it, they could break us or make us.” – Rastafarian Faming Co-op Participant
Box 5.54. Farming co-op participant discussing preparedness for the future “And they say that this culture... and you end up putting the culture, homes and the specific nature of your home, then all cultures has already been lost. You have culture in their life, they do not know. People are like what is this food? They have no idea. So the culture is the knowledge that is of this particular part of the land and of the things you do, then our culture has already been lost. What we do is we recite it and tell stories of it. The culture of our ancestors from twenty-four, twenty-five years ago, we all remember that. The talk is... and most of them have no idea.” - Rastafarian Faming Co-op Participant
The DPnR group discussed the cost of living burden based on funding availability and
the salaries as they compare to other areas in the states:
Box 5.55. DPnR participant discussing preparedness for the future “I think that the cost of living and the cost of education here make it really hard to have a family and thrive, definitely. They can be done. I mean you just have to - it is all about balance and, once again, figuring out how you can afford it, so. But it is definitely a major, major handicap in living there.” – DPnR Participant
Box 5.56. DPnR participant discussing preparedness for the future “Well, I think it is because we have another potential like breaking point on the negative side would be the federal funding decreased to the territory or the U.S. decides the federal funding decreased because there are a lot of salaries and divisions that are supported by federal dollars. The problem is it could be if actually the feds started paying attention to where their money was going, they mature, and their accountability was actually improved.” – DPnR Participants
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And finally the Eco-outreach group was the most optimistic of the four groups:
Box 5.57. Eco-outreach participant discussing preparedness for the future “I believe it is going to get a little more…a little tougher than it presently is. But I also believe…I also see that it is going to cause our community to become a little more realistic about what we…what our limitations are. And, to actually focus, there are some positives and some negatives. I believe it will push us to the point where we will become a little more…where we will become more focused on what is important and prioritize those things. Among them, I think I see the fact that lets go to WAPA. I think that is an area that will force the policymakers to become much more able and push them into the point where they will put the investments where it is necessary. We have to be pushed towards sustaining mechanisms that will enable us to keep as semblance of I guess a measure of affordable livelihood. But at the same time there will be shrinkage. We are going to shrink and be more realistic. We cannot live like the mainlanders. We cannot live like the Americans.” – Eco-Outreach Participant
Summary Conclusions:
From this discussion some apparent trends emerged. Participants in every
group regardless of occupation felt that sustainable livelihoods were going to become
even more difficult in the future. Much of the discussions during this exercise were
framed based on the overall themes from the discussions in which participants felt that
the growing economic disparity coupled with the rapidly changing demographic
profile of the island is making their future on the island uncertain or negative.
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Chapter 6: Discussion and Considerations
6.1 Overview
Findings from this research provide subjective participatory evidence that
supports previous research regarding social-ecological systems, sustainability,
resilience and the bottom up approach to natural resource management. While a great
deal of data was obtained through this study, this chapter will highlight the ‘Top 5’
takeaways from this research as well as contain a brief discussion of management
implications and the methods used.
6.2 ‘Top 5’ Takeaways
Despite the differences in livelihood and cultural backgrounds all the groups
shared the same perspective regarding the future of the island. “Pushed to the Limit”
was the common future scenario chosen by each group because they believed it was
the most likely to occur within the 5 – 10 year time frame. Each group expressed that
they felt the island was not moving in a desirable direction. The reasons for which was
generally due to the islands legacy of historical mass tourism development associated
with the globalization of the island. A natural extension of this was the shared feelings
unpreparedness and vulnerability to the future during the social resilience exercise.
This suggests a system with low social-ecological resilience.
People may need to feel hopeful about the future in order to plan for it. The
role of sense of place vs. globalization was the most central driver across groups.
Changing demographic patterns, sustainable livelihoods and a feeling of exclusion
from the dominant business patterns and government planning had a major impact on
groups’ perceived empowerment and ability for participants to conceptualize a
positive and successful future state, environmental or otherwise. This suggests that
without addressing issues of disempowerment, and economic disparity people may not
be able to envision, much less plan for a positive and successful future. Subsequently,
although not always intuitive, there may be dependencies between sustainable
livelihoods, civic empowerment and stewardship.
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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 the decision making process and increased accountability at both the social and
institutional level. Both the statistics derived from the semantic network
representations and the adapted Q-method found that understanding the nature of
people and how we make decisions is central to how groups conceptualized both the
potential for the future and interpret present conditions. Specifically groups were more
likely to rank issues related to increasing community capacity, education and
livelihoods as the most positive drivers of the system. Conversely issues of
globalization, local exclusion from the dominant business patterns, and a lack of
competent of supportive leadership at the institutional level were considered the most
negative drivers.
Management strategies should include specific place-based items when
engaging communities and solutions might be more effective if they are customized to
the community that is being addressed. The use of broad theoretical (read: scientific)
concepts were not very effective in engaging groups but specifics were very resonant.
This is evidenced by the difficulty in groups describing the theoretical concept of
sustainability even when applied to their specific place and the ease with which groups
could discuss the drivers of change and important aspects of society specifically.
Similarly this was evidenced by the ability for groups to reach consensus quickly on
an indicator of sustainability without being able to define sustainability during
exercise #3. Therefore when pursuing either management and/or conservation
outreach, incorporating specific examples and goals generated from the bottom up
might prove more beneficial than trying to apply theoretical goals to a given situation.
In addition conservation might be more effective if expressed using cultural
and place-based ideals as opposed to theoretical or academic ones. Scientists may
benefit from considering sense of place while approaching conservation. Sense of
place and cultural history may be a determining factor in how conservation is
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expressed at the community level. Groups with different cultural and occupational
backgrounds discussed and related to the natural environment from varying
perspectives. Those who originated from the continental U.S. were more likely to
reference the natural world in relation to the marine environment. The locally born
participants were more likely to identify with the environment through agriculture or
terrestrial environments and alternative energy. Likewise groups tended to discuss
issues in relation to the nature of their organization. As the Eco-outreach groups
membership largely involved government employees who dealt with small businesses,
they discussed business opportunities, enforcement and alternative energy, whereas
the social hospitality group was more likely to discuss business education and tourism
development. Likewise the Rastafarian farming co-op was more likely to discuss
globalization and other issues in relation to farming whereas DPnR discussed these
issues in relation to land and water use planning and community engagement.
Management ought to then consider general sense of place and cultural sensitivity as
well as the specific polycentric goals and structures of communities being addressed.
6.3 Culture as an Abstract Semantic Artifact in Knowledge Structures
Both the roles of culture and polycentric perspectives were integral
considerations when analyzing the results of this research. Through the use of
semantic text mining and correspondence analysis the differences in abstract concepts
discussed by groups were clearly illustrated. It was also evident that the variations in
concepts discussed were strongly tied to the nature of each group’s organization
and/or cultural history as noted in the beginning of this chapter. Furthermore these
patterns of knowledge variation across groups suggest that cultural framing and
emphasis could influence group responses and behavior to management regimes. This
research does not however investigate in detail the degree to which the abstract
concepts discussed by group’s impacts how they relate to the world around them.
Merely that these concepts were more integrated and central to the individual groups
compared to those concepts that were equally central to all the groups. However;
many of these concepts were both intangible and undefined such as the central role of
‘Attitudes’ and ‘Care’ among the local community groups. While these concepts were
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central to some groups but not others, a specific understanding of how community
groups interpret ‘Attitudes’ and how that impacts sustainability was not clear. Further
research regarding how these conceptual variations influence the valuation, behavior
and decision making of distinct social and community groups could illuminate patterns
in the relationship between knowledge and behavior within community dynamics.
6.4 Sustainability and Resilience as they relate to Community Engagement
and Management
Some authors have argued that sustainability and resilience may be linked but
should be considered separate and distinct concepts that are not necessarily
interdependent (Derissen, Quaas et al. 2011). However; this research suggests that
may not entirely be true within a social-ecological paradigm. One of key findings from
this research was lack of cohesion and integration of the concept of ‘Sustainability’
within community knowledge representations. There is a considerable case that this
lack of cohesion also exists at the academic and theoretical level, in large part due to
the value laden nature of its definition. This proposes that ‘Sustainability’ may not be
a useful banner with which to approach communities. However; as demonstrated
through the Scenario Planning process, community groups provided a great amount of
detail when considering future social-ecological changes and evaluating internal
system dynamics. Additionally by asking community members to evaluate, rank and
assess the components of their social-ecological system they provide specific
examples for increasing social resilience which inherently includes the positive
normative qualities that evade theoretical conceptualizations of sustainability.
Combining the responses of multiple communities groups within a given social-
ecological system may give rise to a ‘sustainability sum’ for the system and/or
uncover conflicts. Therefore changing focus from sustainability to a resilience
approach to communities may invariable lead to sustainability. This is especially true
considering the inevitable change and uncertainty associated with the complexities of
a social-ecological system (Anderies, Janssen et al. 2004). This supports Hollings
assertion that sustainability can ultimately be defined as the processes that stabilize
and promote resilience (Holling 2001).
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6.5 Implications of Globalization on Social-Ecological Resilience
This research design served to demonstrate the effectiveness of participatory
scenario planning as an assessment tool for community knowledge structures. While
previous research developed sets of indicators for social-ecological resilience, see
(Berkes 2003) for example, an emergent finding from this research was the multiple
dimensions in which globalization has had a negative impact on the perceived
resilience of the system by community groups.
Many of the perspectives described by participants have been echoed in previous
research regarding immigration and economic disparity. Research has suggested that
the co-occurrence of poverty and high diversity may contribute to a diminished sense
of civic identity and engagement (Schwartz, Luyckx et al. 2011). Additionally,
residency time has been linked to place attachment and positively correlated with
community revitalization and organization efforts (Manzo and Perkins 2006). This
research suggests that the ubiquitous poverty, diversity and social fractionalization
across the island could potentially contribute to a diminished sense of place
attachment and civic identity. These findings were unanticipated during the methods
design phase and expose some inadequacies of this research pilot. Since the seasonal
nature of the economy on the island encourages many short term residents the research
team chose to focus primarily on native born St. Thomas residents or management
members whose residency time was approximately 5 years. However; as this research
continues it might benefit from targeting specific cultural and occupational groups
related to the high influx of regional Caribbean immigrants who, in total, now
comprise 56% of the islands total population (U.S. Census Bureau, 2013).
Many participants in this study strongly identified themselves as Virgin
Islanders and expressed feelings of loss relating to pre-existing cultural specific
values, language, knowledge, power and identity due to both regional Caribbean and
continental immigration and its impact on the economy. This leaves a blind spot in the
study: how do immigrant groups view their identity and relationship to stewardship on
the island? There is evidence that proximity to country of origin can encourage
immigrants to maintain their traditional cultural values and norms as opposed to
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adopting those of the country immigrated to (Schwartz, Luyckx et al. 2011). How do
their perspectives effect the broader issues related to sustainability and resource use?
Do their perspectives on the internal system dynamics of the island share the same
vision as the groups sampled?
Considering that demographic and economic globalization will only likely
continue into the future, and the potential impacts it has on the resilience of
communities based on this research; emphasizes the need to prioritize community
empowerment and the incorporation of communities into business and management
regimes. Especially in small island communities such as St. Thomas which are
experiencing high immigration rates and historically globally dependent economies.
Subsequently, while a great deal of the economic activity can be considered a result of
the plentiful and unique natural resources on the island, the links between livelihoods
and the environment may not always be present due to the economic disparity across
the island. It would then be recommended to couple and associate conservation and
management goals with the broader goals of the communities of interest.
6.6 Brief Review of methods used
While scenario planning methodologies have existed formally for decades and
are commonly used by governmental and non-governmental organizations in their
planning efforts, the use of it as a research tool at the community level is less
common. In this instance, the scenario planning process combined with the Q-Method
was very effective at engaging groups and gathering their collective views on the
drivers of the system. This thesis provides evidence that the use of scenario planning
fits comfortably within the theoretical parameters created by social-ecological
systems, sustainability and resilience theory. It also acts as a comprehensive tool to be
used in a participatory framework when investigating SES dynamics from the social
perspective. Theoretically and evidentiary, there appears to be a strong case for using
visioning exercises to engage communities regarding sustainability and transformation
in SES systems. For future research it would be useful to use the findings from the
focus group sessions conducted during this research to develop a formal Q-sort to do
as a survey for a larger audience.
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While still a nascent method, this research illustrates great promise in Semantic
Network Analysis as a method of quantifying and reducing large datasets of qualitative
data. However; due to nature of spreading activation theory, more central concepts are
also most ambiguous, requiring qualitative interpretation of the most central semantic
concepts. Further research into common patterns within semantic network specifically
in order to develop specific cohesion and centrality metrics may increase the methods
ability to be objective and standardized.
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Appendices
Categories Variables Specifics
Population
Demographic Characteristics/ratios/percentages
Demographic distribution throughout and within islands
Settlement patterns Household Composition
i.e. population growth trends, emigration rates, # of people per household, etc. )
Economic Employment Labor Businesses
Business Patterns
Investment
i.e. employment rate by sector, etc.
Infrastructure and Services
Transportation Community Serves Recreational and
Other Services
Housing Utility Services Health Services
i.e. airports, low income housing, hospitals, etc.
Institutional Arrangements
Access to Natural Resources
Local/Regional Government Entities
Community Organizations
Social Cohesion
NGO’s and Religious Groups
i.e. churches, recreational clubs, co-management programs, etc.
Individual Wellbeing
Education Health
Poverty Characteristics
Social Ills
i.e. obesity rates, school retention rates, etc.
Environment and Resources
Water Supply and Use
Environmental Risk Pollution and
Waste Disposal
Agricultural Productivity
Biophysical Characteristics
i.e. topography, distribution of resources, water and air quality, coral bleaching, etc.
Cultural Properties
Anthropological Cultural Sites
Historical Land Ownership
National Parks, MPA’s
i.e. traditional/historical fishing practices, etc.
Perceptions of Marine and Environmental Conservation
Social Values of Environment
Economic Value of Environment
Attitudes and Perceptions of Environment
i.e. recreational use, economic use, attitudes towards reefs, etc.
In this future there is a strong emphasis on the power of market forces. Market forces acts as the authoritative driving force for decision making. Large scale commercial development dominate sectors such as aqua and agriculture. Their ultimate focus is global markets- imports and exports. Communities are comprised entirely of commercialized profitable industries. Populations are divided into laborers and buyers. In this community-money matters.
In this future there is a strict emphasis on environmental resource management. But governance takes place within a regional or local scale. There is no other outside governing force so each community stays within its own jurisdiction and is managed entirely on its own.
This future emphasizes full participation and engagement. They believe strongly in environmental, social, economic and cultural value. The main community focus is on democratic values and collectivity. They portray and live by “close nit" attitudes. Community is one standing unified body. In this society-community rules.
In this future the dynamics of change are emphasized greatly. Redefining environmental, social, economic and cultural changes based on technological purposes. Visions for the future are driven by pure innovation, science and technology. This is a highly technologically advanced and "connected" world. This society is all about-science and technology.
Directions for the Future
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To Each Their Own
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Community Rules
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Science and Technology
The enhancement of environmental, social, economic and cultural values is top priority in this future. Their goal is to target cultural identity, environmental conservation and spiritual values and make changes based entirely on the environment. The collective interests for the environment are more important than the individualistic goals of the people. In this community eco matters for the greater good.
Education and learning is the driving force for the future. The goal is to incorporate decision-support mechanisms for citizens, communities, groups, and institutions in a way that would stimulate their knowledge and information flow enabling them to make informed changes based on learning from experience. The dynamics of empowerment, experience and knowledge is tremendously effective. This future is defined by the flow and application of knowledge.
In this future populations are reactionary. Changes typically only take place after resources have been exploited or degraded to a significant degree often after thresholds have been passed. This future is characterized by change that only occurs when situations have been pushed to the limit.
Changes are completely random, unpredictable and chaotic and they are based around nature. Any attempt to manage the complexity of mother nature in its entirety, results in failure. Scientists seek to harness and control the power of natural forces in order to create an effective approach to societal change. However this future is consistently fooled by randomness.
Directions for the Future
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What is the SERV Project? The SERV Project is a University of the Virgin Islands study de-signed to create a space for community members to share their per-spectives, expertise and knowledge on the potential future of St. Thomas. This study involves scenario planning exercises that imag-ine the potential future directions for St. Thomas and explore locally-based ideas regarding environmental sustainability. The aim of this study is to better understand the social processes that promote envi-ronmental health, encourage stewardship, support related jobs, and increase environmental security. The SERV project considers environmental sustainability to be the health and stability of not only the environment but of the economic, cultural and social systems that comprise St. Thomas. However; spe-cifically what health and stability is should be defined by the values and wishes of the community and it is the hope that this project will help give voice to those values to be incorporated into resource man-agement decisions. What is Scenario Planning? Scenario planning is a process of thinking about the future to better understand the present. It is a technique used both in science and in various private, public, non-government and government organiza-tions as a method of creating a shared vision of the future as well as a shared vision for reaching that future. This process gives people a voice and an opportunity to express their thoughts and visions through small group discussions.
Contact Info:
If you have any ques-tions or are interested in participating please contact: Alex Webb (340) 642-8312 [email protected]
S UP PORTE RS O F TH IS
S TUDY :
The SERV Project SSocialocial--EEcologically cologically RResilient esilient VVisionsisions
Why participate? To better understand the nature of the potential threats being posed to St. Thomas, a deeper understanding of the processes within our socie-ty that contribute, facilitate or sustain them is necessary. Your partici-pation in this study creates the opportunity for the community to ex-press their views and have their perspectives incorporated into re-source management strategy and planning. How does it Work?
This study will be conducted through a series of focus group discus-sions that last approximately 1.5 - 2 hours and involve five to seven people. The interviews will be both video and audio recorded and then transcribed into text documents. To safeguard your confidentiali-ty and anonymity, you will be given a participant code, and any and all personal identifying information will be removed. You have the right to withdraw from the study at any time. If you withdraw from the study, any data that you have contributed will be removed from the dataset.
How will the information be used? The data will be analyzed and used both for a graduate student’s mas-ter’s thesis and to create a decision support mechanism for natural re-source managers that incorporates community perspectives into man-agement goals. Social-Ecologically Resilient Visions (SERV) Project Who is Sponsoring this study? UVI Center for Marine and Environmental Studies University of the Virgin Islands; NSF VI-Experimental Program to Stimulate Competitive Research (VI-EPSCoR) RII Award # 0814417
Contact Info:
If you have any ques-tions or are interested in participating please contact: Alex Webb (340) 642-8312 [email protected]
S UP PORTE RS O F TH IS
S TUDY :
The SERV Project
SSocialocial--EEcologically cologically RResilient esilient VVisionsisions
