Water Quality Risk, Local Ecological Knowledge, and Decision Making in Maine and New Hampshire’S Surfing Population

AN ABSTRACT OF THE THESIS OF

Sophia Quilliam Scott for the degree of Master of Environmental Science and Policy presented on May 10th, 2016.

Knowledge into action: Water quality risk, local ecological knowledge, and decision making in Maine and New Hampshire’s surfing population

Abstract approved

______Dr. Shannon H. Rogers

Water quality impairments and the subsequent beach advisories are significant problems in the Gulf of Maine. These advisories arise when water quality is below the accepted threshold for human health and safety. Surfers represent a culturally and economically important subpopulation of beachgoers who are subject to higher risks associated impaired water quality. This increased risk is related to the amount of time surfers spend in the water, the higher incidence of water ingestion, and the propensity for surfers to surf around storm events when water quality is the lowest.

In our research we surveyed 291 surfers and conducted 20 interviews with key informants in the surfing community. Though we approached our research from the angle of water quality risk and decision-making the major theme that emerged from our interviews through the process of latent content analysis is that surfers Maine and New Hampshire hold a wealth of local ecological knowledge (LEK) especially around issues of water quality. LEK has been heralded as an important knowledge source in the realm of sustainability science and has proven to be useful in coastal management.

In addition to the finding that Maine and New Hampshire surfers provide valuable insight on issues of water quality. We find that surfers indicate that water quality and pollution can impact an individual’s decision to surf. Given this, surfers should have equal access to water quality information at their local surf spots. With this research we hope to show that surfer's knowledge of their environment can prove useful to researchers and help drive policy changes related to water quality management.

Knowledge into action: Water quality risk, local ecological knowledge, and decision making in Maine and New Hampshire’s surfing population

Sophia Quilliam Scott

A THESIS

Submitted to

Plymouth State University

In partial fulfillment of the requirements for the degree of

Master of Environmental Science and Policy

Defended May 10, 2016 Degree Conferred June 2016

Master of Environmental Science and Policy thesis of Sophia Q. Scott presented on May 10, 2016

APPROVED:

______Dr. Shannon H. Rogers, Thesis Advisor, Assistant Professor of Environmental Science and Policy, Ecological Economist, Center for the Environment, Plymouth State University

______Mr. Douglas Earick, Center for the Environment, Plymouth State University, Education Consultant, New Hampshire Department of Education

______Dr. Bridie McGreavy, Assistant Professor of Environmental Communication, Department of Communication and Journalism, University of Maine

I understand that my thesis will become part of the permanent collection of Plymouth State University, Lamson Library. My signature below authorizes release of my thesis to any reader upon request

______Sophia Quilliam Scott, Author

ACKNOWLEDGEMENTS

This thesis is the result of a fruitful collaboration between researchers at Plymouth State University and the New England Sustainability Consortium’s Safe Beaches and Shellfish Project. Funding for this research was provided by NH EPSCoR and the National Science Foundation award #1330641. There are many people to acknowledge who have played a significant role in supporting me throughout my thesis research. First and foremost, I’d like to thank my advisor Dr. Shannon Rogers. Shannon is not only a brilliant scientist, researcher, and interdisciplinary scholar, she is an incredible mentor, teacher, and advisor to all of her students. I have learned a tremendous amount from her and am looking forward to building upon the relationship that we have formed while working together on this project. I’d also like to thank my thesis committee, Douglas Earick and Dr. Bridie McGreavy for all of their valuable insight, knowledge, and support they provided throughout this process. Thank you to all of the NEST researchers who gave me unlimited wisdom, support, and encouragement. Of the NEST folks I’d especially like to recognize Dr. Laura Lindenfeld and Dr. Kathleen Bell who consistently greeted me with kindness and enthusiasm and helped make me feel like an integral part of this expansive transdisciplinary project. I’d like to thank my entire Scott-Mucklestone family, particularly my mom and dad, for always believing in me and continuously supporting me throughout my academic career. Special shout out to the Rogers’ Research Group, Chelsea, Jonathon, and Carrie, for helping me navigate grad school life and always being there for whatever I needed. Big recognition also goes out to my writing group, Carly, for always keeping me sane, accountable, motivated, and providing all the puppy therapy needed! All the Rad Grads, as well as the entire PSU and CFE community, I’ve learned so much from all of you. Thank you for sharing your knowledge and guidance. Thank you to Morgan, Andrea, and Kaitlin for being my support system over the past two years, I couldn’t have done it without you. Lastly, this work couldn’t have been possible without the surfing community in Maine and New Hampshire. I have endless gratitude to all the surfers who participated in this our study, your contribution helped make this research happen.

TABLE OF CONTENTS

Page

Chapter One: General introduction…………………………………………………….… 1

1. Background……………………………………………………………….……. 1

1.1 Intro to sustainability science………………………………….…… 1

1.2 The New England Sustainability Consortium………………..……. 2

2. Study rational: Impaired water quality and surfers in the Gulf of Maine…. 2

2.1 Beach advisories and closures in the Gulf of Maine…………..… 2

2.2 Vulnerability of surfers to water quality and beach advisories.… 3

2.3 Surfers are important stakeholders in coastal ecosystems….…. 4

3. Research questions…………………………………………………….…….. 4

4. Thesis roadmap………………………………………………………….……. 5

Chapter Two: Manuscript one…………………………………………………….……… 6

Chapter Three: Manuscript two…………………………………………………………. 36 . Chapter Four: Summary statistics………………………………………………………. 53

Chapter Five: General Conclusion……………………………………………………… 55

Bibliography……………………………………………………………………………….. 57

APPENDICES………………………………………………………………….………….. 65

APPENDIX A: IRB approval letter……………………………………….………… 66

APPENDIX B: Study area map...... ………………….……. 67

APPENDIX C: Intercept survey script and instrument………………….……. 68

APPENDIX D: Interview questions…………………………………….………. 69

iii

LIST OF FIGURES

Figure Page

Figures in Chapter One

1. Representation of the triangulated multi and mixed method approach …...... 10

2. Diagram representing iterative process of our methodology development………………...... …..………………… 11

3. Examples of interview questions…………………...... ………………… 12

4. Examples of interview questions…………………...... ………………… 13

5. Image depicting the coding process employed in our analysis of interview data…………………..………………... 14

6. Sunburst graph representing Major theme (center), subthemes (middle), and parent codes…………………….…………………. 17

7. Chart illustrating range of LEK...... 21

8. Process of building logit model...……………………………...... …… 24

Figures in Chapter Two

1. Diagram representing iterative process of our methodology development……………………………………………... 39

2. Examples of questions used in the survey…………...... …………….... 39

3. Histogram of Likert scale of risk...... …………………………….……...……... 42

LIST OF TABLES

Tables Page

Tables in Chapter One

1. National Resource Defense Council Beach Action Value (BAV) exceedances for 2013 and number of issued beach advisories for 2015...... 10

2. Intercept survey sampling schedule...... 12

3. Overall interview sample characteristics (n=20)...... 15

4. Subthemes leading to the theory that surfers’ hold LEK...... 16

5. Emergent themes from interview data...... 18

6. Demographic information for counties and states where surveys were administered...... 21

7. Overall sample characteristics (n=291)...... 22

8. Selective and open codes within the survey data...... 23

9. Cross tabulation and chi square test of independence...... 24

10. Logit model of LEK and model predictability (Model 1)...... 25

11. Second logit model of LEK and model predictability (Model 2)...... 25

12. Logistic regression of predictor analyzed singularly...... 26

Tables in Chapter Two

1. National Resource Defense Council Beach Action Value (BAV) exceedances for 2013 and number of issued beach advisories for 2015...... 38

2. Intercept survey sampling schedule...... 40

3. Overall sample characteristics (n=291)...... 41

4. Top three risks identified by survey participants...... 42

LIST OF TABLES (CONTINUED)

Tables Page

5. Preferred method of water quality communication...... 43

Tables in Chapter Four

1. Overall interview sample characteristics (n=291)...... 52

2. Overall intercept survey sample characteristics (n=20)...... 53

Chapter One: General Introduction

1. Background

1.1 Introduction to Sustainability Science Human-nature relations have resulted in untold alterations to ecosystems and the services they provide. Evidence of anthropogenic environmental impairment is ubiquitous and spatially and temporally vast. The challenge facing sustainable development and the human-nature duality is the lack of science that actively informs policy, in a way that truly affects decision-making and ultimately, change (Clark 2007, Clark and Dickson 2003, Kates et al. 2001). Sustainability science is a burgeoning field of environmental research that aims to bridge the seemingly insurmountable gap between science and policy (Clark 2007, Clark and Dickson 2003).

The concept of sustainable development and sustainability has existed in the literature for decades. The Brudtland Report (1987) defined sustainable development as, “…development that meets the needs of the present without compromising the ability of future generations to meet their own needs.” (pg. 41). Since then, scientists around the world have sought to create research that informs and supports this idea. However, classical methods of trickle down research and one-way transfer fall short in delivering comprehensible reports that can inform decision makers and policy (Bettencourt and Kaur 2011, Weichselgartner and Kasperson 2010, Ostrom et al. 2007, Sarewitz and Pielke. 2007, Funtowicz and Ravetz 1993). Consequently, current science is not meeting the needs of stakeholders or policy makers (Funtowicz and Ravetz 1993). There is a clear need to conduct research that matters to society and that will strengthen the scientific basis for decision making. Sustainability science aims to attenuate many of problems associated with the hierarchy of traditional science strategies.

To strengthen the scientific basis for decision-making, sustainability science takes into account the many intricacies and complexities in the social-ecosystem relationship. This is accomplished through transdisciplinary work that tackles the entire scope of the issue, instead of examining individual pieces separately (Tengo et al. 2014, Lang et al. 2012, Robinson 2008). Sustainability science aspires to produce applicable research that matters to society. In this sense, sustainability science concentrates on place- based, problem driven, and solutions oriented research that yield informative results that can be put into action by decision makers and create effective policy (Miller et al. 2014, Miller 2013). Furthermore, to fully appreciate the full scope of a given issue, sustainability science invokes non-academic knowledge to gain insight from all angles.

The call for incorporation of less formal scientific knowledge is not novel (Cash 2003). Researchers have been studying the value of traditional ecological knowledge (TEK) for many years (Huntington 2000, Thornton and Maciejewski Scheer 2012). TEK knowledge, often obtained from indigenous or First Nations cultures, is acquired through extensive and intensive relationship with one’s environment or surroundings (McGregor 2004). While some state that TEK doesn’t necessitate obtaining knowledge from indigenous peoples (Huntington 2000) the inter- and intra- generational knowledge passing that occurs in First Nations communities is reflective of TEK (McGregor 2004). Local ecological knowledge (LEK) is in the same vein of TEK and

2 employs the knowledge of other local groups or communities. The knowledge systems of TEK and LEK are distinct yet have innumerable similarities, so much so that some researchers have married TEK and LEK into local and traditional ecological knowledge (LTK) (Thorton and Maciejewski Scheer 2012). In sustainability science the use of TEK or LEK adds saliency, legitimacy, and trustworthiness to the resulting findings (Miller et al. 2014, Nursey-Brag et al. 2014, Tengo et al. 2014, Tàbara and Chabay 2013). Including alternative types of knowledge in research introduces different viewpoints and generates a comprehensive vision of the scope of the issue at hand (Tàbara and Chabay 2013, Johnson 2011). The inclusion of local ecological knowledge requires building relationships with stakeholders, or those who have vested interest in the project at hand. Stakeholder engagement is a pertinent theme in sustainability science (Tengo et al. 2014, Tàbara and Chabay 2013, van Kerkoff and Lebel 2006). The call for place-based research that is focused on delivering results demands the use of specific local knowledge, which often comes from stakeholders. Stakeholders have a vested interest in the research and outcomes and therefore often cooperate and work along side scientists in solving real world problems. Mutual processes of knowledge generation, with stakeholder engagement at every step, yield results that are more likely to be implemented. The participatory nature of knowledge co-production allows for community based problem definition, research, and the resulting management systems.

1.2 The New England Sustainability Consortium Sustainability science has proven itself to be an apt method of tackling complex environmental problems. Its intent of solving place-based problems and informing policy is paramount and applicable to socio-environmental issues worldwide. The New England Sustainability ConsorTium (NEST) is one such project. It is a solutions-driven, outcome-oriented and place-based sustainability project focused on socio- environmental systems in the Gulf of Maine. The project is a transdisciplinary collaboration between eight universities and colleges in Maine and New Hampshire. The overarching goal of the consortium is to bridge the gap between science and decision making with respect to shellfish bed closures and recreational beach advisories in the Gulf of Maine. Success of the consortium in achieving its goals relies on collaboration between biophysical scientists and social scientists as well as integration across different institutions and states and between stakeholders and researchers.

By focusing on collaborative research between scientists and stakeholders, integration of local ecological knowledge, linking knowledge with action, and creating innovative solutions for complex socio-environmental problems, the NEST project hopes to contribute to and further the study of sustainability science. This thesis is the result of fruitful collaboration with NEST.

2. Study rational: Impaired water quality and surfers in the Gulf of Maine

2.1 Beach advisories and closures in the Gulf of Maine The Gulf of Maine is a resource rich region of the North Atlantic and home to an estimated 11.2 million people in Maritime Canada and New England (US Census 2015, Statistics Canada 2013). The economies of Maine and New Hampshire rely on ecosystems goods and services delivered by the Gulf of Maine. In 2009 tourism was the primary industry in Maine and New Hampshire, valued at over $1 billion and $256.5 million respectively (National Ocean Economics Program 2014). Tourism is expected

3 to grow and continue to be a major economic resource for these two states in the coming years. Coastal tourism and recreation represents a large portion of the tourist economies in Maine and New Hampshire. Between the two states the economic value of coastal recreation is estimated to be $120-480 million (Leeworth and Wiley 2001). Visits to beaches are a popular coastal tourist recreation activity. From 1999-2000 beach visitation days were 16.1 million in Maine and 8.1 million in New Hampshire, with estimations of an average of $207 spent on each visit in each state (Pendleton 2009). The wide variance in visitations between the two states is likely representative of coast length and beach number. Maine has 5,300 miles of coastline and NH has 18 miles (Pesch and Wells 2004).

The economic value of Maine and New Hampshire’s coastal beaches is apparent. Given the extent of the services coastal systems provide, there has been a strong call for the sustainable management of these ecosystems. With anticipated increases in coastal tourism and recreation it is important to maintain these valuable environments, not only for the socio-economic benefits they provide, but also to preserve these fragile and vulnerable ecosystems for future generations (Springuel 2000).

There are many factors that impact the socio-economic and environmental services of coastal ecosystems. These include, among others, increased development, management of stormwater pollution, climate-induced sea level rise and spread of invasive species (Pesch and Wells 2004). Additionally, a significant problem facing the Gulf of Maine is the impact of beach advisories and closures. Beach advisories and closures arise when water quality is below an accepted threshold for human health and safety (Jones 2011). Coastal waters, especially those with high levels of recreation activity and development are known to be more contaminated than less used areas (Dwight et al. 2004, Turbow et al. 2003). Beach advisories and closures can have significant impacts on socio-economic systems through perception and value of place, health implications due to exposure to contaminated water, and loss of revenue from unwarranted beach closures (Jones 2011, Porter et al. 2010).

Beach advisories/closures and the corresponding diminished water quality, is related to the presence of microbial pathogens. Pathogens are of concern to beachgoers because they cause adverse health effects (Boehm et al. 2009). Pathogens are both naturally occurring and are fecal-borne from human and/or animal sources (Jones 2011). When beachgoers enter waters that contain pathogens, they are at risk for associated illnesses, which range from gastrointestinal illnesses to death (Jones 2011, Wade et al. 2003). There are many types of beachgoers and the different groups use the beaches for a variety of reasons. Beachgoers can be categorized into several stakeholder groups, including locals and tourists, families with young children, dog owners, those who enter the water and those who simply take a walk along the beach. Beachgoers who enter the water to swim or play in the intertidal sands are at the highest risk of exposure to pathogens.

2.2 Vulnerability of surfers to water quality and beach advisories

Surfers are a sub population of beachgoers that have a higher risk of suffering from the effects of microbial pathogens (Harding et al. 2014, Stone et al. 2008). This occurs for a number of different reasons. Surfers are in the water for longer periods of time and become fully submerged (versus wading). Surfers participate in the sport year round and thus are subject to seasonal variation in rainfall as well as potential changes in

4 wastewater treatment plant outputs. Given the nature of the sport, surfers are more apt to ingest water or get cuts or scrapes through which microbial pathogens can enter. Finally, surfers often surf during or after storm events when the waves are the best but water quality is the poorest. Though surf literature is still nascent, studies have shown that surfers can ingest up to ten times more water than the average beach goer (Stone et al. 2008) and are at higher risks for pathogens (Dickinson et al. 2013, Dwight et al. 2004). Similarly, Harding et al. (2014) found a relationship between risky surf behaviors, such as surfing after it rains or near an outfall, and an increased incidence of self reported water borne illnesses. The results from this study clearly demonstrate the relationship between coastal water quality and public health implications from water-borne pathogens.

2.3 Surfers are important stakeholders in coastal ecosystems

In addition to surfers being a high-risk sub population of beachgoers, recent studies have shown that they play an active socio-economic role in coastal communities (Wagner et al. 2011, Lazarow et al. 2009, Slotkin et al. 2009, Nelsen et al. 2007, Lazarow 2007). Nationally, the projected estimated of surfers in 2010 was 3.8 million (Leeworthy et al. 2005). Though surfers represent only a small population of total beachgoers, they average almost twice as many visits per year (Leeworthy and Wiley 2001). The act of surfing is in itself a human-environmental relationship and some argue this makes surfers better stewards of the coastal environment (ASBPA 2011, Taylor 2007). In surveys, surfers ranked environmental issues such as water quality as top priorities (Martin 2014), indicating that most surfers have environmental sentiments. Indeed, there are many national and international surf groups that stand on a platform of environmental sustainability. These include Save the Waves, Surfers Against Sewage, and the Surfrider Foundation organization.

3. Research questions

The aggregate surfer population is a group that is economically significant, at high risk for water-borne pathogens, and ecologically minded. These factors make them an ideal demography to study in the Gulf of Maine. The Gulf of Maine faces surmounting environmental challenges that will only be exacerbated by the effects of climate change. Gulf of Maine water quality is an important issue and needs to be urgently addressed as it has serious consequences. Given the level of pathogen exposure and the corresponding health risk and coupled with a strong sense of environmental sustainability, Maine and New Hampshire surfers may provide valuable insight and LEK into water quality issues. Surfers in Maine and New Hampshire are no strangers to cold water and good surf can also be infrequent. Consequently, surfers often enter the water during storm events when water quality is the lowest and risk of pathogens is the highest.

We were interested in understanding the relationship between surfers’ perceptions of risk and water quality and whether these play a role in the decision to enter the water to surf at any given time. Specifically, we were interested in whether knowledge of water quality or pollution would impact a surfer’s decision to enter the water. Given the potential for surfers’ increased vulnerability to water pollution, we also sought to understand how surfers thought about risk, how risk impacted their decision to surf,

5 and whether surfers considered water quality to be a risk. We addressed the following questions in our research:

To what extent are surfers in Maine and New Hampshire aware of the potential risk of pathogens and diminished water quality? Where does the knowledge of pathogens come from (what are the sources of this knowledge)?

What are the attitudes and behaviors of this group towards perceived risk of harmful pathogens? How does knowledge of pathogens drive the decision to surf or not to surf during storm events?

To address these questions we sought to actively engage with the surfing community and use them as our primary source of knowledge to support our research. Specifically, we relied on qualitative and quantitative research methods of interviews and surveys to obtain both a smaller sample of in-depth and rich qualitative data and a wide reaching sample that was capable of reaching a larger population of surfers.

4. Thesis road map

This thesis represents the research that I’ve been conducting with my advisor Dr. Shannon Rogers as part of the New England Sustainability Consortium’s (NEST) Safe Beaches and Shellfish project. This is a manuscript based thesis and by design is repetitive in nature. A general introduction is presented followed by two manuscripts and a general conclusion. The two manuscripts have been prepared for submission to academic journals and provide enough information to be understood on their own. The general introduction and general conclusion sections act as bookends and tie the thesis together into a comprehensible form.

Chapter 2: Manuscript One Manuscript submitted to PLoS One

RIDING THE WAVE OF LOCAL ECOLOGICAL KNOWLEDGE IN COASTAL RESEARCH AND MANAGEMENT

Sophia Scott and Shannon Rogers Center for the Environment, Plymouth State University, MSC #63, 17 High Street, Plymouth, New Hampshire, 03264, United States

ABSTRACT

Water quality impairments and subsequent beach advisories/closures are significant problems in the Gulf of Maine. These advisories/closures arise when water quality is below the accepted threshold for human health and safety. Surfers represent a culturally and economically important subpopulation of beachgoers who are subject to higher risks associated with impaired water quality. This increased risk is related to the amount of time surfers spend in the water, the higher incidence of water ingestion, and the propensity for surfers to surf around storm events when water quality is the lowest.

We approached our research from the angle of water quality and decision-making and conducted 20 in depth interviews with key informants in the surfing community. We also surveyed 291 surfers on 12 surf beaches in southern Maine and New Hampshire. We found that given the level of environmental exposure coupled with a strong sense of environmental sustainability within the local surfing community, the major theme that emerged through the process of latent content analysis is that Maine and New Hampshire surfers hold a wealth of local ecological knowledge (LEK) especially around issues of water quality. LEK has been heralded as an important knowledge source in many science disciplines and has proven to be useful in coastal management. With this research we hope to show that surfers' knowledge of their environment can prove useful to researchers and practitioners to help drive policy changes related to water quality management.

1. Introduction

The coastal zone has economic, social, and cultural importance across the globe. These salient ecological systems are biodiversity hot spots [1], significant carbon sinks [2], and producers of ecosystem services [3]. Coastal regions represent a nexus of human-nature interaction, ecosystems intrinsically connected with the anthropogenic element [4]. Nearly half (44%) of the world’s population lives in coastal regions [5], which places additional stresses on already compromised systems. Climate change and the resulting sea level rise further compound the vulnerability of coastal regions. Evident in these problems is the surmounting need for the development of sound policy that, among other things, can adequately address the coastal challenges of declining fisheries [6], storm and flood management [7], erosion [8], and issues of water quality [9].

The coastal regions of Maine and New Hampshire are not immune to the global factors impacting these social ecological systems. The Gulf of Maine is a particularly vulnerable region given that its waters are warming faster than 99% of the world’s oceanic water bodies [10]. Improved policy for coping with these issues is especially important to those regions whose economies are reliant on the coastal zone. In Maine and New Hampshire the coastal zone directly contributes a combined $3.8 billion to the state’s GDP and an additional $2.2 billion in wages [11].

Tourism is a significant contributor to the coastal economy in Maine and New Hampshire, representing 65% of the ocean economy jobs in Maine and 43% of the ocean economy jobs in New Hampshire [11]. Beach visits are a popular coastal tourist recreation activity in the two states with estimations of an average of $207 spent on each visit in each state [12]. Thus, a significant problem facing the Gulf of Maine is the impact of beach advisories and closures, which arise in times of poor water quality [13].

Coastal waters, notably those in recreational and developed areas, are more likely to experience water quality issues [14, 15]. Given the importance of beaches in Maine and New Hampshire’s economies, advisories and closures can have significant impacts on socio-economic systems; through perception and value of place, health implications due to exposure to contaminated water, and loss of revenue from unwarranted beach closures [13, 16]. There is a categorical need for improved monitoring of coastal regions to collect data that can inform policy. This is needed to ensure that sound natural resource decisions are made to sustain the social, economic, cultural, and environmental integrity of the Gulf of Maine coast.

A variety of knowledge systems are warranted to make sound decisions around the issue of coastal water quality in the Gulf of Maine. From the biophysical knowledge of geographies and land cover classes that influence water quality, to the microbiologist’s knowledge of the most effective indicator bacteria, to the knowledge of the socio- economic impacts that beach closures and advisories have on coastal communities; different knowledge types are needed to make informed decisions that can adequately and comprehensively deal with the problem at hand.

A knowledge system often overlooked in coastal management decisions is local ecological knowledge (LEK). LEK is knowledge derived from extended exposure and experience between an individual and her environment. Though the call for incorporation of LEK in sustainability science is a growing concept [17, 18], the inclusion of traditional knowledge in natural resource decision-making is not novel [18, 19]. Indeed, traditional ecological knowledge (TEK) has been proven useful in a variety of coastal decisions from understanding species distribution [20-22] to improving management practices in fisheries [23, 24]. The use of (LEK) can add saliency, legitimacy, and trustworthiness to research findings [19, 25-27].

There is a wide array of beach users and stakeholders in the Gulf of Maine who can serve as purveyors of LEK. Within this category are local beach residents, in state visitors and tourists, families with young children, dog owners, those who enter the water and those who simply take a walk along the beach. However, when concerned with the issue of water quality, there is a subpopulation of the coastal zone stakeholder group that is arguably better suited for the role of providing LEK focused on issues of coastal water quality: surfers. Given their propensity for the

8 coastal environment, surfers are capable of providing LEK about water quality and the environment of their local surf spot. Compared to other beachgoers surfers frequent the beaches more often and spend longer periods of time in the water. Surfers also surf year round, especially in Maine and New Hampshire where the surf conditions tend to be better during the winter months and shoulder seasons. Thus, they are apt to understand and notice if water quality changes throughout the year. Surfers are also more at risk for issues of water quality [28,29]. Compared to swimmers surfers can ingest up to 10 times more water [30] and are more susceptible to cuts and scrapes through which microbial pathogens can enter [14, 31]. Moreover, surfers surf during and after storm events when the waves are the best but the water quality is poor [14, 30].

In addition to their inclination for the coastal environment and their exposure to water quality risk, surfers are arguably excellent candidates as providers of LEK given their environmental ethic. Though there are many connotations associated with surf culture and the participants in this group [32], ranging from beach bum to extreme athlete [33], surfers have proven to be environmentally minded [34-36] and have potential as citizen scientists [37]. Despite this, within the scientific realm, surfers are an underrepresented group even with their great potential as contributors to research in coastal regions. Surfers have the potential to inform science through the contribution of important data. Furthermore, surfers are a distinct beachgoer population who recreate in a coastal zone that is not utilized by other coastal use groups. The surf zone is beyond the zone where beachgoers venture and often too close to shore for recreational and commercial fishing boats. Hence, surfers occupy a region of the coast frequented only by other wave riders. This exclusivity presents the opportunity to study an area of the coast where research is not extensive. Surfers have already been employed in the gathering of coastal monitoring data, supporting their role as citizen scientists and making a case for their role as environmental stewards [37].

Surfers’ role of environmental stewardship is supported in the literature, through both the exploration of the social ecological roots of surfing to the present day environmental activism. Throughout its history, surfing has always represented a nexus of human- natural systems. Indeed, the act of surfing is in itself a human-environmental relationship and some argue this makes surfers better stewards of the coastal environment [38, 39]. Martin and Assenov [40] found that surfers placed high values on environmental issues such as water quality. In England, a small group of surfers triggered by local water quality issues took political action, changed policy, and transformed into an international environmental activism group Surfers Against Sewage [35, 41]. Other international surf-based environmental groups include Save the Waves, dedicated to preservation and protection of the coastal environment and the Surfrider Foundation, an organization that takes an activism approach to protect the ocean, waves, and beaches. The existence of these large international environmentally focused surf groups sheds light on the eco-centric role of surfers in coastal preservation and demonstrates stewardship of their environment.

In this study, which we believe to be the first in-depth examination of the surfing community in the Gulf of Maine, and only the second to identify surfers as purveyors of LEK [42], we show that in addition to the contribution of important scientific data,

9 surfers’ experiences in coastal regions make them valuable resources and providers of LEK which can be used to inform researchers, scientists, and policy makers. Despite the cold waters, short summers, and intermittent waves, surfers in Maine and New Hampshire brave the elements to pursue their sport. There are no numbers quantifying Maine and New Hampshire surfers however, estimates range from between 2.4 and 3.3 million surfers in the United States [43-45]. Though we approached our research from the angle of risk and decision-making, specifically asking questions about water quality, water quality risk, and the influence of this on the decision to surf, what emerged from our study was the presence of LEK in the study population of our surfers. Specifically, we were interested in surfers’ knowledge of the environment in which they surf. We wanted to know if surfers in our study area are aware of the factors that could potentially impact water quality and the subsequent beach advisories.

2. Methods

2.1 Study Area

This research focused on 12 surf beaches in the Gulf of Maine from May 2015 to October 2015. Of the surfable beaches included in the study 7 beaches are located in southern Maine and 5 beaches are in New Hampshire. The beaches of southern Maine and New Hampshire are popular tourist destinations during the summer months [46]. The economic impact of the coastal tourist economy is significant for both Maine and New Hampshire. It is estimated that tourists contribute respectively $1.2 billion and $256 million to the Maine and New Hampshire coastal economies [11]

While southern Maine and New Hampshire are geographically close, the two states have significant differences in beach water quality. In their 2013 report, the National Resource Defense Council (NRDC) ranked the 30 states with coastline by beach water quality based on the national Beach Action Value (BAV) safety threshold [47].

In the report New Hampshire ranked 2nd for the cleanest beaches while Maine was ranked 27th, three shy from having the least clean beaches in the nation [47]. The beaches included in our study demonstrate this contrast (Table 1). During our data collection period (May-October 2015) there were 47 advisories issued at the study beaches in Maine and zero issued in New Hampshire [48, 49] (Table 1).

2.2 Methods

We set out to understand the knowledge held within the surfing community of Maine and New Hampshire. We were interested in their knowledge of their environment, notably the quality of the water in which they are surfing. Additionally, we wanted to understand if knowledge of water quality or pollution would impact a surfer’s decision to enter the water.

Table 1. National Resource Defense Council Beach Action Value (BAV) exceedances for 2013 and number of issued beach advisories for 2015 [47-49]. Beaches Percent BAV exceedance Number of advisories

New Hampshire Jenness 0% 0 Bass 4% 0 North Hampton 1% 0 The Wall 1% 0 Seabrook 0% 0

Maine Higgins 19% 12 Old Orchard 10% 3 Fortune’s Rock 0% 0 Gooch’s 38% 14 Wells 22% 3 Ogunquit n/a* 0 Long Sands 22% 15 *NRCD percent BAV exceedance was not available for this beach.

We took a multimethod approach to this question, combining the qualitative and quantitative research Literature methods of literature review, interviews, and surveys review [50] (Figure 1). We were approved by the Plymouth State University Institutional Review Board for the use Multi- method of human subjects in our research. The development approach of our interview and survey questions was an iterative In-depth Intercept process (Figure 2). Preliminary findings from our in- interviews survey depth interviews informed the development of our survey instrument. Field-testing of our survey resulted Figure 1. Representation of the in changes and modifications to the instrument. triangulated multi and mixed method approach

Figure 2. Diagram representing iterative process of our methodology development

The triangulated nature of our multimethod approach strengthened the validity of our findings as our three methods (interviews, surveys, and literature review) converged to support our conclusions [51]. Validity is strengthened in this way by not relying on a single qualitative method from which to deduce our conclusion [51]. Additionally, we believe our research to be trustworthy given that its methods are applicable and transferable to other studies, consistent (so that replication would produce similar results) and neutral, in that we were objective in our approach and careful to limit possible biases [52].

2.2.1 Interview protocol We investigated the LEK of water quality awareness in Maine and New Hampshire surfers with semi-structured, open-ended interviews with key informants in the community. Written consent was given by all interview subjects. We conducted interviews with willing surfers using a purposeful sampling scheme that employed both opportunistic and snowball sampling techniques [53]. To identify interview participants we used an opportunist sampling strategy by visiting surf shops up and down the coast. Interview recruitment was attempted at 9 surf shops in the study area from Portland, ME to Hampton, NH. Further interviewees were identified via snowball sampling strategy [54]. The interview protocol was semi-structured and questions were designed to understand surfer’s perception of risk and water quality and whether this influenced a surfer’s decision to surf or not to surf and offered ample opportunity for surfers to display any local ecological knowledge they had about the Gulf of Maine system. We interviewed a total of 20 key informants including surf shop owners, surf shop employees, regular surfers, a surf blogger, a surf coach, and an employee of the Surfrider Foundation over the time period of May 2015-February 2016. Interviews lasted approximately 30 minutes, were digitally recorded, and later transcribed for analysis. We asked questions pertaining to surfers’ knowledge of surfing spots and surfing behaviors as well as knowledge of water quality and the role this played in the decision to surf (Figure 3).

We used latent content analysis to  Where do you go surfing? Why? Where do you get disseminate results from our your information about surfing conditions? interview transcriptions. Latent  What are the most popular surf spots? What makes content analysis is a qualitative these spots popular?  Have you ever noticed anything in or about the water data analysis technique used to that would make you question its quality? Has this retrieve important knowledge from impacted your decision to surf?  Have you heard about water lengthy datasets such as interview quality/pollution/contamination issues? If so, where transcriptions [55]. Through latent did this information come from? Does it make you content analysis themes present concerned? Why or why not?  Do you surf in storms, high rainfall events, or during a within the rich and verbose posted beach advisory? interview transcriptions emerge  Have you attributed getting sick to surfing? Does this from the data [55]. This knowledge impact any of your decisions about where or when to surf? methodology allows for themes to  Are there any questions that we should be asking reveal themselves versus being surfers that we haven’t addressed? explicitly stated [56]. Grounded  Is there anything else that you’d like to add to this conversation that we haven’t addressed? theory methodology allows themes that emerge from the latent content Figure 3. Examples of interview questions analysis method to manifest in an

12 overarching theme or theory [57, 58]. Coding is the primary method of identifying and managing themes within the dataset [59]. To aid in coding and the analysis process we used the computer software program NVivo for Mac (Version 10.2.2). This program makes the management and analysis of large datasets more feasible [60, 61]. Once identified, codes aid in analysis through interpretation of themes, theme occurrence, and uncovering any relationships between different themes.

2.2.2 Survey protocol

Initial interviews (methodology described above) conducted in the spring of 2015 informed the design of our survey instrument. From May-October of 2015 we conducted a 10-question intercept survey on the 12 surf beaches of our study area. The target participant was a surfer above the age of 18 who was present at a beach within our study area. We focused solely on the surfing population and excluded other wave riders such as boogie boarders, body surfers, stand up paddle  Have you surfed… o During storms? boarders, and wind surfers. We o During a posted beach water quality advisory? approached surfers exiting the  Have you ever noticed anything in the water that water and after verbal consent would make you question its quality?  Do water pollution concerns impact your decision to was given we administered the surf? survey. Survey participants were o Is this a risk? thanked with a gift of surf wax.  Have you ever attributed getting sick to surfing?  Would you be interested in knowing about water The survey was designed to elicit quality conditions at your local surf spot? a surfers’ knowledge of water  How would you like this knowledge shared with the quality and whether this impacted surfing community? the decision to surf (Figure 4). Figure 4. Examples of survey questions Surveys typically took about 5 minutes to complete.

We recorded demographic information as well as involvement in an environmental or surf group and surf experience (in number of years surfing). Our survey also contained open-ended questions about water quality. During our data collection period we visited the beaches in our study area a total of 64 times (Table 2). Over the course of the field season n=291 surfers were surveyed with a 90.6% response rate.

Table 2. Intercept survey sampling schedule

Beach Total survey Failed survey No. surfers No. surfers declined attempts attempts surveyed survey Jenness 9 1 68 5 Bass 2 1 1 0 North Hampton 2 2 0 0 The Wall 9 3 37 6 Seabrook 4 4 0 0 Higgins 7 1 78 8 Old Orchard 5 5 0 0 Beach Fortune’s Rock 4 0 16 0 Wells 6 4 4 1 Long Sands 4 1 33 4 Gooch’s 7 2 42 3

Total 64 25 291 30

We manually recorded survey answers with a pen and paper on the beach and entered responses into the Microsoft program Excel. Quantitative survey data were analyzed for descriptive statistics and cross tabulations. Qualitative survey data obtained from the open-ended survey questions were analyzed using the same qualitative methods used in the interview data.

2.3 Data analysis

Two types of data resulted from our study: qualitative data derived from interviews and a combination of quantitative and qualitative data from surveys. A different data analysis approach was used for each dataset. Interview transcriptions employed the qualitative research method of latent content analysis and grounded theory while survey data was analyzed using quantitative methods of descriptive statistics, cross tabulations, chi squared test of independence, and logistic regression.

2.3.1 Interview data

Once transcribed from audio recordings we analyzed the interview data by employing both grounded theory methodology and the data analysis method of qualitative latent content analysis. This method allows the researchers to understand ideas or themes that are not directly stated in the data. Coding methods are used in both grounded theory and latent content analysis to group key concepts and ideas that are pulled from the text [57]. Grounded theory casts a broader net than latent content analysis in that it results in formation of a theory whereas latent content analysis reveals codes and themes to answer research questions [62]. We conducted an in depth analysis of our interview transcriptions and once familiar with the data we began the process of coding. Coding is a way in which a researcher can categorize key concepts or ideas within the data. We used the computer program NVivo to aid us in our coding and analysis process [60, 61]. In this analysis we employed the use of both ‘First Cycle’ coding methods of ‘Initial’ coding and ‘Second Cycle’ coding methods of ‘Axial’ and ‘Theoretical’ coding [59]. The rationale behind utilizing this method of coding is that in the initial approach to the data the researcher is not looking for preconceived codes or ideas within the data. Instead, the ‘Initial’ coding method is one in which the data is allowed to speak for itself [57]. The ‘Second Cycle’ ‘Axial’ coding method is a process in which ‘First Cycle’ ‘Initial’ codes are grouped together into similar categories [59]. ‘Theoretical’ coding groups codes into larger parent code umbrellas and helps to uncover the overarching theme present within the dataset, thus revealing the central finding of the research [59]. This process is illustrated in Figure 5.

2.3.2. Survey data

We recorded survey responses into the Microsoft program Excel. Answers that could be easily coded into binary or other numerical data were transformed to allow for easier statistical analysis. Open-ended questions were left unaltered and were coded using a process similar to our analysis of interview data. To provide some congruity in our analysis of interview and survey data, when deemed appropriate answers to open- ended survey question were coded using the ‘Second Cycle’ coding method of ‘Selective’ coding [59]. This method allowed us to group our ‘First Cycle’ ‘Initial’ codes into the same coding categories revealed through our interview data analysis. This allowed for consistency between both data sets and easier comparison when

Figure 5. Image depicting the coding process employed in our analysis of interview data.

disseminating results. While our survey instrument had a range of questions, we identified the following as most relevant to our analysis of LEK within the surfing community. These were the queries of noticing questionable water quality, the surfing behaviors of surfing in a storm or advisory, and the inquiry on the relationship between surfing and sickness.

We used statistical analysis to test for association with the dependent variable of surfer LEK. The choice of using surfer LEK as our dependent variable stemmed from our interest in understanding what variables had a significant correlation with surfer LEK; are some surfers more apt than others to have LEK and what factors that we tested for drive this? Using the question ‘Have you ever noticed something in the water that would make you question its quality?” as our precursor for surfer LEK we looked at the association between this dependent variable and a number of other responses including whether a surfer had surfed during or after a storm event or during a posted beach water quality advisory. We also explored the association between surfer LEK and education, membership in an environmental group, and the belief that water pollution was a risk. We employed cross-tabulations and chi-squared test of independence for our statistical analysis. We used logistic regression analysis to test for significant association between surfer LEK and the continuous independent variables of age and number of years surfing. Once a significant correlation was found between surfer LEK and other variables we utilized a logistic regression analysis that

15 included all significant variables. Using this method we created a model that was capable of predicting membership in our dependent variable (surfer LEK).

3. Results

3.1 Interview respondent characteristics

A total of 20 key informants in the southern Maine and New Hampshire surfing community were recruited for participation in our in-depth interviews. Demographic information is outlined in Table 3. The number of years surfing is not reported here, as this question was not asked to all participants. After conducting a number of interviews we discovered that understanding a surfer’s experience measured by the number of years spent surfing would be a useful and informative parameter to include and we therefore added this question to our survey instrument. This is one example of the ways in which preliminary results from our interviews informed the development of our survey instrument.

Table 3. Overall interview sample characteristics (n=20) Characteristic Frequency Percentage (%)

Gender Male 18 90 Female 2 10 Residence ME 13 65 NH 6 30 MA 1 5 Education High school 2 10 Some college 6 30 Associates 1 5 Bachelors 10 50 Masters 1 5 Membership in environmental or surf group Yes member 8 40 Not a member 8 40 Not a member but participate 4 20 Continuous variables Mean, (median), [min-max] Age 35.9, (31.5), [18-64]

3.1.2 Presence of local ecological knowledge

The ideas and concepts that arose in our coding and analysis process led us to the conclusion that the prevailing theme of our interview data was the idea that the surfers in our study hold a great deal of local ecological knowledge. The five subthemes that emerged from our parent codes and led us to the conclusion of LEK in the surfing population are: ‘Experience-Awareness-Knowledge’, ‘Lifestyle’, ‘Stewardship’, ‘General Environmental Observations’, and ‘Factors Influencing Water Quality’. The Subthemes of ‘Factors Influencing Water Quality’ and ‘General Environmental Observations’ had almost total participation from interviewees (19 and 17 interviewees contributed to ‘Factors Influencing Water Quality’ and ‘General Environmental Observations’ respectively), while the membership within the Subthemes of Experience-Awareness-Knowledge’, ‘Lifestyle’, and ‘Stewardship’ were less populated accounting for 10, 7, and 10 interviewee contributors, respectively. Subthemes are summarized in Table 4. Under the umbrella theme of ‘Evidence of Local Ecological

Knowledge’ all 20 interviewees contributed codes. The Codes, Parent Codes, Subthemes, and Major Theme and corresponding respondent and reference numbers are outlined in Table 5.

Table 4. Factors that influence the formation of LEK in surfers

Primary subthemes Explanation Experience-Awareness-Knowledge The idea that experience drives knowledge. Experienced surfers develop LEK from time spent in the water and years of experience. Additionally, awareness of surroundings builds LEK. When surfers are constantly aware and paying attention to their surrounding it makes them more conscious of the ecosystem and environmental changes around them. Lifestyle The lifestyle that surfers chose to pursue is conducive to the acquisition of LEK. Given the nature of the sport surfers spend long periods of time in the coastal environment. Stewardship Surfers depend on the coastal ecosystem to pursue their sport. Considering that the inherent link between surfing and the natural environment surfers have a sense of stewardship for the ecosystem in which they recreate. General Environmental Observations Bearing in mind the amount of time spent in the water surfers notice many things about the water. Some observations are necessary to understand the sport such as swell height, wind, tides, and coastal bathymetry. Factors Influencing Water Quality Given that surfers are in the water so frequently; they notice changes in the water quality. Storms often accompany periods of high surf and surfers are aware of factors such as rain and runoff that influence coastal water quality. Surfers are also aware of the anthropogenic impacts on water quality.

The ‘Factors Influencing Water Quality’ Subtheme is comprised of the Parent Codes of ‘Animals and animal waste’, ‘Sewage and WWTP’, and ‘Processes impacting water quality’. It was clear from the responses from the interviewees that surfers in Maine and New Hampshire are aware of factors that influence coastal water quality. For instance, the Codes that make up the Parent Code of ‘Processes Impacting Water Quality’ included ‘Storms’, ‘Rain’, and ‘Runoff’. One respondent noted “[Getting sick] is a given if it has rained hard or the conditions have made the sewer system be taxed, you know there’s going to be crap in the water.” (Interviewee #6). Another said, “And you know sometimes the water can get really dirty after heavy rains and stuff. And you’ll realize, you’ll be out and you’ll be like ‘Woof!’ you can’t see your feet (Interviewee #7). There were a total of 104 coded references to ‘Factors Influencing Water Quality’ throughout our interview data; this represents 43.5% of the total references coded under the umbrella theme of ‘Evidence of Local Ecological Knowledge’ (Figure 6).

In addition to the factors that influence water quality, surfers also demonstrated that they were aware of general environmental conditions at their surf locale. This is represented in the Subtheme of “General Environmental Observations” which includes the Parent Codes of “Other Anthropogenic Influence’, ‘Environmental Conditions’, ‘Sensory Observations’, and ‘Trash and Debris’. Surfers recognized environmental factors that could potentially influence water quality such as fertilizers and pesticides as well as trash and debris. They also used their own sensory observations to draw conclusions about the water where they surfed such as smells, tastes, and water appearance and color. One respondent was recorded saying, “[I’ve gotten sick] many, many times. After big storms the color, the smell, and how you feel when you get out sometimes. Like, the earaches, the sinus, throat, and nasal stuff that you get [from surfing in the water].” (Interviewee #19) Another noted, “It is to that point here though,

CHART TITLE

Experience Animals & Awareness animal waste Knowledge 5% 7% Lifestyle 5%

Experience Stewardship Awareness Knowledge Lifestyle 9% 7% 5% Processes impacting water quality Stewardship 9% 31% Factors Trash and debris influencing 4% water quality LEK 44%

General environmental observaitions 35% Sensory observations 19%

Sewage and WWTP 8% Other anthropogenic Environmental factors conditions 7% 5%

Figure 6. Sunburst graph representing Major theme (center), subthemes (middle), and parent codes (outer). Each level is equal to 100% and all percentages refer to contribution to the major theme of LEK.

if the water is really gross and the wind is onshore I can smell it when I walk out the door here – and we’re two miles from the beach.” (Interviewee #3). Within our interview data there were 61 references included in the Subtheme of ‘General Environmental Observations’ representing 35.3% of the major finding of ‘Evidence of Local Ecological Knowledge’ (Figure 6).

Other factors that contributed to surfer LEK were the Subthemes of ‘Stewardship’, ‘Lifestyle’, and ‘Experience-Awareness-Knowledge’ which were all derived from Parent Codes of the same name. Respectively there were 19, 10, and 15 references for these three Subthemes. Some surfers in our study spoke to how their experience in the water shaped the formation of their knowledge. The idea that knowledge comes from experience is supported by the Parent Code of ‘Experience-Awareness-Knowledge’ which included the First Cycle codes of ‘Experience drives knowledge’ and ‘Awareness

Table 5. Emergent themes from interview data. Number of sources, (number of references). Examples of supporting quotes Codes Parent codes Subthemes Major theme

“[I’m worried about] the number of dog walkers, don’t know how many people are Shellfish bed closures 1, (1) cleaning up after their dogs Maggots 1, (2) Animals and animal #2 Animals and animal waste 3, (4) waste Dogs and dog waste 4, (4) 6, (11)

“A few people have gotten sick in Ogunquit after strong rains. We all are mindful after Fresh water 3, (6) strong rains. OOB is safest after strong rains because some reason the way the Saco Storms 6, (9) Processes impacting river current comes out after a strong rain.” Runoff 8, (15) water quality #6 River, rivermouths 8, (15) 18, (63) “On any big rain the water dumping out from all of the inland waterways; river, Rain 11, (18) streams, marshes, everything changes the water quality.” Factors influencing #12 water quality “Pretty much any river mouth that you surf, after a storm especially, [will have poor 19, (90) water quality]. A couple days ago after the storm I could smell it here.” #18

“We talk about the capacity for waste treatment. It just depends where the outflow is Sewage, WWTP 11, (16) and how the currents are blowing, I’ve seen corn in the water in OOB and I’m like, eh, Sewage, WWTP I’m getting out, cause you know how it is this corn.” 11, (16) #6 “Sewage, it’s a concern, I don’t like being out there when it’s that bad.” #1

“I worry about runoff from farms.” Boating industry 1, (3) Other anthropogenic #16 Population 3, (5) influences Evidence of local I have smelled a kind of petroleum product smell at Higgins, there is a lot of agriculture on the Fertilizers, other chemicals 6, (6) 8, (14) ecological knowledge banks of the river that comes down 20, (207) #6 there's tons of runoff on an outgoing tide, so much sometimes that you can taste that’s its Currents, winds 3, (3) Environmental different on a certain day Tides 5, (8) conditions #13 6, (11) it stunk for a long time until the tide shifted and started going back in and then we got a break, #3 General “After big storms the color, the smell, and how you feel when you get out sometimes. Foam, scum, unusuals 2, (3) environmental Like, the earaches and the sinus and throat-nasal stuff that you get from it.” Taste 3, (4) observations #19 Sensory Water color and appearance 8, (9) 18, (73 “We get super foul water at Higgins. When I was surfing the last storm at a rivermouth observations Smells 7, (15) [there was] 2-3” of this brown foam on the surface that smelled like toilet.” 14, (40) #3 “Yeah there’s multiple times this summer where I’ve done surf lessons and picked up Debris 1, (1) trash out of the water.” Pollution 1, (2) Trash and debris #15 Trash 5, (6) 7, (8) “There’s trash in the water and everything. Especially in the summer. When you walk down the beach and look at the seaweed piles it’s just trash all over it. #14

Table 5 continued Emergent themes from interview data. Number of sources, (number of references)

Examples of supporting quotes Codes Parent codes Subthemes Major theme “This sport has given me a huge interest in the coastline, the beach, property ‘The Ocean’, ‘Mother Nature’ 5, (9) Stewardship Stewardship development and just a respect of nature really, especially where water is so 10, (19) 10, (19) dangerous you have to have respect for it.” Stewardship 8, (9) #17 “[Surfing] demands having a rhythm in the ocean and a respect for the ocean and stuff like that.” #7

“The ocean’s definitely not doing as well as it could and the environment itself is really becoming sick” #9

“The thing about surfing that’s cool is it’s not just a sport, it’s an all-encompassing Lifestyle 7, (10) Lifestyle Lifestyle lifestyle, it’s the only thing that’s taken hold in my life, as much as anything else has. 7, (10) 7, (10) It’s a super health activity, hobby, lifestyle; it is all encompassing. A lot comes with it. And comes with it a responsibility that comes with it just by doing it and I’m aware of that. It’s tricky but it’s fun. #17

“We go out there to enjoy it, to enjoy nature.” #13

“I think people surf because it’s an escape from reality, but you know once you’re out in the water you leave all your emails and all that behind you’re just worrying about catching the next wave. It’s so nice to be able to get in the water, catch waves and leave all the land stuff behind.” #7 Evidence of local ecological knowledge “So being at the beach a lot, you’re aware of your surroundings a lot, most people are Awareness and knowledge of surroundings 5, Experience, awareness, Experience, 20, (207) aware of their surroundings, but when you’re surfing you’re immersed in your (5) Knowledge awareness, environment and you love it.” 10, (15) knowledge #17 Experience drives knowledge 8, (10) 10, (15) “It’s just because they weren’t knowledgeable, they’re just not knowledgeable of the ocean. I think the cool thing about surfing is that you get that, which makes you a more competent person in the water.” #7 “Being a surfer the majority of my life, you just start to pick up on things and you know, old timers pass on knowledge and stuff like that. “ #10 “Just being a wise old man, I am 64 this will be my 51st year of surfing 51 years is that possible? Yeah, so I am you know if you did anything in your life, if you were a gardener, if you did it for 50 years you would have it down I would think. So it’s just learning and seeing what's out there and experiencing, I have surfed up and down the east coast, so just experience.” #11

“[Water quality would] absolutely impact decision to surf now that I’m older and wiser, not when I was younger. If water is all nasty, I won't go out.” #19

20 and knowledge of surroundings’. One respondent noted, “When you’re surfing you’re immersed in your environment and you love it. Usually people love it. I remember from some movie, you never see a basketball player staring at a basketball court, but surfers are always staring at the water” (Interviewee #17). While another stated, “[You acquire knowledge] from time in the water. And the more time you spend in the water, the more confident you’re going to be as a waterman. You know you’re not just going to watch a guitar video and be a ripping guitar player, you have to put in the time. This is the same with surfing, you have to put the time in. You’re always learning, you’re always getting better.” (Interviewee #7). The ‘Stewardship’ Subtheme contributed 9% to the ‘Evidence of Local Ecological Knowledge’ finding, the ‘Lifestyle’ references represented 4.8%, and the ‘Experience-Awareness-Knowledge’ was accountable for 7.2% (Figure 6).

3.1.3 Spectrum of LEK in interviewees

We find it important to note here that interviewees contributed to the overarching theme of surfer LEK in varying degrees. That is, surfer LEK is not uniform across the participants in our study, nor should it be expected to be in the general surfing population. What we show in our study is a spectrum of surfer LEK. Indeed, one of our interviewees (#9) only contributed a single reference to the overarching theme of surfer LEK, representing 0.6% of the total contribution, while another (#7) contributed 17 references, accounting for 10% of the total contribution to surfer LEK (Figure 7). It should also be noted that interviewees contribute differently in terms of subthemes. Some surfers only noted one subtheme while others touched on multiple. Only 4 of the surfers we interviewed mentioned all 5 subthemes (Figure 7).

3.2 Intercept survey respondent characteristics

Our intercept survey recruited a total of 291 participants with a response rate of 90.4%. Respondents were primarily male (80%) and had a bachelors degree or higher (67%). The age of the surfer ranged from 18-79 with a mean age of 33.6 years. Surfing experience ranged from first time surfers to surfers with over a half century of experience (52 years surfing). The mean number of years surfing was 11.4 years. The majority of surfers surveyed were from either Maine or New Hampshire (60.2%). Of the surfers surveyed in Maine, a majority of them were from Maine (60.9%) while the opposite was true of surfers surveyed in New Hampshire, with only 39.3% New Hampshire resident surfers. Demographic information about the counties where we conducted the surveys and for each state can be found in Table 6. A summary of the demographic information is presented in Table 7.

Contribution to LEK by interviewee

Interviewee #1

Interviewee #2

Interviewee #3

Interviewee #4

Interviewee #5

Interviewee #6

Interviewee #7

Interviewee #8

Interviewee #9

Interviewee #10

Interviewee #11

Interviewee #12

Interviewee #13

Interviewee #14

Interviewee #15

Interviewee #16

Interviewee #17

Interviewee #18

Interviewee #19

Interviewee #20

0.00% 2.00% 4.00% 6.00% 8.00% 10.00% 12.00% Percent of total LEK showing Subtheme codes

Experience, Awareness, and Knowledge Factors influencing water quality

Lifestyle Other observations

Stewardship

Figure 7. Chart illustrating range of contributions to the major theme of surfer LEK by interviewees including subtheme delineation. The x-axis represents the percentage each interviewee contributed to the major theme of surfer LEK

. Table 6. Demographic information for counties and states where surveys were administered

2014 Estimates York County, Cumberland Maine Rockingham New ME County, ME County, NH Hampshire Population 200,710 287,797 1,330,089 300,621 1,326,813 Bachelors degree or higher 28.8% 41% 27.9% 37.2% 33.7% Median Income 57,348 57,461 48,453 77,348 64,916 Median housing cost 227,800 241,800 174,500 282,100 239,900 Median age 43 41 42.7 37.2 41.1

Table 7. Overall sample characteristics (n=291) Characteristics n Frequency Percentage (%) Gender 291 Male 232 79.9 Female 59 20.3 Residence 291 MA 63 21.6 ME 116 39.9 NH 59 20.3 QC 29 10 Other 24 8.2 Education 291 HS 28 9.6 Some college 56 19.2 Associates/technical 12 4.1 Bachelors 130 44.7 Graduate 65 22.3 Membership in an environmental or surf group 291 Not a member 215 73.9 Yes, a member 76 26.1 Surfing during storms 291 No, I have not surfed during/after storms 64 22 Yes, I have surfed during/after storms 227 78 Surfing during posted water quality advisory No, I have not surfed during an advisory 185 63.6 Yes I have surfed during an advisory 106 36.4 Noticing something questionable about the water quality 291 No, I have not noticed questionable water quality 147 50.5 Yes, I have noticed something questionable 123 42.3 Not here 21 7.2 Attributing surfing to sickness 291 No, I have never attributed surfing to sickness 206 70.8 Yes, I have attributed surfing to sickness 85 29.2 Interest in knowing about local surf spot water quality 291 Yes, I am interested in local water quality 281 96.6 No, I am not interested in local water quality 6 2.1 Other 2 0.6 Continuous Variables Mean, (median), [min-max] Age 33.6, (31), [18-69] Number years surfing (surfing experience) 11.4, (9), [0-52] *In-state meaning that surveyed surfer was a resident to the state in which the surfer was surveyed. For instance, if a surfer was surveyed at Higgins Beach in Scarborough, ME and indicated that they were a resident of Maine, this classified them as ‘In-state.’

The survey question that was best suited to incur presence of LEK was the open ended question, ‘Have you ever noticed anything in the water that would make you question its quality?’ Hence, this survey question was our indicator of LEK in the population of surfers in Maine and New Hampshire. To support this we utilized the ‘Second Cycle’ coding process of ‘Selective’ coding to group our survey responses into the same Parent codes as found in our interview data. As to not over simplify our results we did not force all initial ‘Open’ codes in our survey data to conform to codes realized in the interview data and left them intact. The majority of the codes (78.6%) within this section of the survey data were assigned to the same Parent codes that emerged from the interview data (Table 8). suited to incur presence of LEK was the open ended question, ‘Have you ever noticed anything in the water that would make you question its quality?’ Hence, this survey question was our indicator of LEK in the population of surfers in Maine and New Hampshire. To support this we utilized the ‘Second Cycle’ coding process of ‘Selective’ coding to group our survey responses into the same Parent codes as found in our interview data. As to not over simplify our results we did not force all initial ‘Open’ codes in our survey data to conform to codes realized in the interview data and left them intact.

The majority of the codes (78.6%) within this section of the survey data were assigned to the same Parent codes that emerged from the interview data (Table 8).

Table 8. Selective and open codes within the survey data

Code References Percentage (%) Total percent (%)

Codes present in interview data (Selective coding) Animals and animal waste 12 3.9 General environmental conditions 7 2.3 Processes impacting water quality 53 17.3 Sensory observations 67 21.9 78.6 Sewage and WWTP 39 12.7 Trash and debris 53 16.9 Stewardship 1 0.3 Other anthropogenic 10 3.3 Others codes (Open coding) Surfing and sickness 6 2 Region 28 9.2 Descriptive positive 4 1.3 21.4 Descriptive negative 8 2 Factors not associated with local water quality (e.g. 21 6.9 seaweed, ‘not here’)

Given this, we use the survey question ‘Have you ever noticed anything in the water that would make you question its quality?’ as a proxy for evidence of LEK in our survey results. By doing this it allows us to investigate and understand what factors or variables are associated with surfer LEK. With the emergence of the major theme of surfers as purveyors of LEK, we wanted to understand what types of factors influence LEK in the surfing population. This is especially relevant given that presence LEK is not uniform across the surfing population and this type of analysis would help to identify those surfers who are more likely to have LEK. We were interested in what variables could be associated with the presence of LEK in surfers in our study. There were many questions that we wanted to answer: Is there an association between LEK and age of the surfer? Is there an association between LEK and the state of residence of a surfer? Are surfers at certain beaches more likely to see something questionable in the water? Given this, we use the survey question ‘Have you ever noticed anything in the water that would make you question its quality?’ as a proxy for evidence of LEK in our survey results. By doing this it allows us to investigate and understand what factors or variables are associated with surfer LEK. With the emergence of the major theme of surfers as purveyors of LEK, we wanted to understand what types of factors influence LEK in the surfing population. This is especially relevant given that presence LEK is not uniform across the surfing population and this type of analysis would help to identify those surfers who are more likely to have LEK. We were interested in what variables could be associated with the presence of LEK in surfers in our study. There were many questions that we wanted to answer: Is there an association between LEK and age of the surfer? Is there an association between LEK and the state of residence of a surfer? Are surfers at certain beaches more likely to see something questionable in the water? Does membership in an environmental organization have an impact? Are surfers who participate in riskier surf behavior such has surfing during or after a storm or surfing during an advisory more likely to notice water quality? We explored this relationship with the use of statistical analysis. Using the chi-squared test of independence we found a significant association between surfer LEK and membership in an organization,

24 surfing during a storm, surfing during a posted beach water quality advisory, and attributing sickness to surfing (Table 9).

Table 9. Cross tabulation and chi-squared test of independence showing column percentage and number of respondents (n). Dependent Independent variables variable Surfers’ Membership Surfing in storm Surfing in advisory Sickness due to LEK surfing

No Yes Total No Yes Total No Yes Total No Yes Total No 60.0 38.6 54.4 79.0 47.1 54.4 67.3 33.3 54.4 87.1 12.9 100 (120) (27) (147) (49) (98) (147) (113) (34) (147) (128) (19) (147)

Yes 40.0 61.4 45.6 21.0 52.9 45.6 32.7 66.7 45.6 51.2 48.8 100 (80) (43) (123) (13) (110) (123) (55) (68) (123) (63) (60) (123)

Total 100 100 100 100 100 100 100 100 100 70.7 79 100 (200) (70) (270) (62) (208) (270) (168) (102) (270) (191) (29.3) (270)

Chi 9.600a 19.617b 29.457c 41.594d squared statistic p value 0.002 0.000 0.000 0.00 a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 31.89 b. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 28.24 c. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 46.47 d. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 35.99

We also found a correlation between surfer LEK and a surfer’s experience in number of years surfed by using logistic regression log(π/1- π)=β0+ β1X) where x=number years surfing. Using this analysis we find that the variable of number of years surfing was found to be statistically significant (β1=0.074, p=0.000) meaning that surfers with more experience (in number of years surfing) are more likely to have LEK. Furthermore, to understand how these independent variables that were found to be significant can act together to influence presence of surfer LEK we built a regression model (Figure 8).

Figure 8. Process of building a logit model

The process of building the logistic model is illustrated in Figure 8. Using the independent variables already found to have a significant association with our target dependent variable we constructed a logistic regression to help predict the presence of surfer LEK, or what variables contribute to the probability of a surfer noticing something questionable in the water. The logistic regression is built using the equation:

log(π/1- π)= β0+ β1X1+…+ βp-1Xp-1

Here X1=membership, X2=surfing experience, X3=surfing in storms, X4=surfing in advisory, and X5=sickness due to surfing. The results from the model show that all included variables with the exception of surfing during storms are significant predictors of the probability of surfer LEK and that the model has an overall correct predictability of 72.6% (Table 10).

Table 10. Logit model of LEK and model predictability (Model 1)

Predictor β Wald 2 p Odds ratio (eβ) Membership 0.655 4.110 0.043* 1.926 Surfing experience (years) 0.032 4.018 0.045* 1.032 Surfing in storms 0.447 1.290 0.256 1.564 Surfing in advisory 0.930 9.384 0.002* 2.534 Sickness due to surfing 1.410 18.057 0.000* 4.095

Predictability of Model Overall percent correct (%) 72.6 R2 (Cox and Snell) 0.240 *significant

We built a second logistic regression excluding X3=surfing in storms which was found to be insignificant in Model 1 (Table 10). Using the same process and assigning X1=membership, X2=surfing experience, X3=surfing in advisory, and X4=sickness due to surfing we find that all predictor variables in this second model are significant and the model has an overall predictability of 71.9% (Table 11).

Table 11. Second logit model of LEK and model predictability (Model 2)

Predictor β Wald 2 p Odds ratio (eβ) Membership 0.703 4.781 0.029* 2.020 Surfing experience (years) 0.034 4.679 0.031* 1.035 Surfing in advisory 1.028 12.152 0.000* 2.795 Sickness due to surfing 1.470 19.944 0.000* 4.348

Predictability of Model Overall percent correct (%) 71.9 R2 (Cox and Snell) 0.236 *significant

Model 2 (Table 11) tells us that the odds of surfer LEK increases when a surfer has attributed sickness to surfing (eβ= e(1.470)=4.328), a surfer has surfed during an advisory (eβ= e(1.028)=2.795), and if a surfer was a member of a surf or environmental group (eβ= e(0.703)=2.020). Additionally, Model 2 shows that the odds of surfer LEK increases as surf experience increases (eβ= e(0.034)=1.035).

Analysis of the fitted coefficient values from Model 2 indicate that when other variables are held constant, the odds of surfer LEK is greater for those surfers who have attributed sickness to surfing (sickness=1) than those surfers who have not attributed

26 sickness to surfing (sickness=0) (eβ= e(1.470)=4.328). Similarly, the odds of surfer LEK is greater for surfers who have surfed during an advisory (advisory=1) than those surfers who have not (advisory=0) (eβ= e(1.028)=2.795). The odds of surfer LEK are also greater for those surfers who are members of an environmental or surf group (membership=1) than those surfers who are not (members=0) (eβ= e(0.703)=2.020). Finally, the odds of surfer LEK is greater for surfers with more experience. That is, as surfing experience increases the odds of surfer LEK increases as well (eβ= e(0.034)=1.035).

Furthermore, the logit model illustrated the difference in the predictability of a model with multiple variables (Model 2, Table 11) and the predictability of a logistic regression analysis with a single predictor variable (Table 12).

Table 12. Logistic regression of predictor analyzed singularly

Predictor variables Surfing Membership Surfing in Suring in Sickness due to experience storms advisory surfing Statistic (years) p 0.000* 0.002* 0.000* 0.000* 0.000* β 0.074 0.871 1.442 1.413 1.859 e β 1.077 2.389 4.231 4.109 6.416 Model 61.1 60.4 58.9 67.0 69.6 predictability (%) *significant

4. Discussion

This research yields important insights into the surfing population of southern Maine and New Hampshire. We show through multiple lines of evidence that surfers are very knowledgeable about the ecosystem in which they recreate. Through the process of in- depth interviews and intercept surveys on the beaches, we discovered that surfers in our study area know a great deal about the water in which they surf; they hold LEK. Recent research on California surfers described surfers’ LEK with respect to wave knowledge, illustrating that the idea of surfers’ holding a comprehensive understanding of their local environment is not unfounded [42]. Given the fact that surfing itself is such an intertwined relationship between the natural coastal systems and the human environment, it is well reasoned that this population would have a deep understanding about the ecosystem in which they recreate. While Reinemann [42] explores the wave knowledge inherent within the surfing population, we demonstrate in this study that surfers’ local knowledge extends beyond an understanding of the factors that influence wave formation, wave rideability and the conditions that produce the best waves. We show here that surfers are knowledgeable of much more nuanced aspects that are inherently experienced in the sport of surfing. Surfers are constantly evaluating the conditions that produce waves, because waves are needed to participate in the sport. They are aware of the various tides, currents, and bathymetry that influences where waves break [42]. What is less obvious, and what we show here, is that given their propensity of the surfsphere, the coastal zone where wave riders recreate, they develop greater understanding of a number of environmental factors around them, beyond the elements that unite to compose a rideable wave.

While not explicitly tailored to test multiple aspects of local ecological knowledge, our research shows that surfers in our study area hold a wealth of LEK when making the

27 assumption that water quality observations are a proxy for one type of LEK. They are aware of the factors that contribute to water quality such as animals and animal waste [63], sewage and WWTPs [64], and the processes that impact water quality such as rain, runoff, and rivers [65, 66]. Though the majority of surfers in our study are highly educated (Table 7), this education was not significantly associated with our proxy for LEK. Instead we find that surf experience and membership in an environmental or surf group have a significant association with LEK. Indeed, ‘Experience-Awareness- Knowledge’ a subtheme that emerged from our interview analysis and more specifically, the idea of the relationship between experience and knowledge was cited by half of our interviewees (Table 3). This idea that experience drives knowledge, especially LEK is supported in the literature [17-19]. Our study supports this idea by demonstrating a significant association between surfing experience (in number of years surfed) and surfer LEK. This is supported by the recent work by Reinemann [42] who in his research he relied on only surfers with significant surf experience (35 years or more) to contribute to local wave knowledge.

Given that when surfers participate in their sport they become fully immersed in and have a greater exposure to their environment supports the idea that they would have a more holistic understanding of their ecosystem. Moreover, the amount of time spent surfing, and thus the amount of time spent in the coastal environment as well as the frequency of visits to the surfsphere, supports the acquisition of LEK by surfers. Though not tested in this study, it could also be argued that because some surfers view the sport, not as that, but as a way to become one with nature [39, 67] they gain knowledge about their environment by means of engaging in a different type of relationship with the coastal ecosystem. Furthermore, the association between membership within an environmental or surf group and surfer LEK that we show in this study supports the notion that surfers are stewards of their environment and thus more in tune to their natural surf ecosystem. Indeed, the formation of the environment surf group Surfers Against Sewage formed because local surfers were noticing inclement water quality conditions at their local surf spot [35].

LEK in our surfing population was also significantly associated with the surf behaviors of surfing during a storm, surfing during a posted beach water quality advisory and the incidence surfers reporting on attributing surfing to sickness. These parameters demonstrate reasons why surfers would be more in tune with factors that contribute to water quality. It is well documented that storms can have impacts on coastal water quality [14, 29]. Thus, surfers who surf during storms may have more opportunity to notice something about the water that would make them question its quality. One survey respondent noted, “After lots of rain there is runoff. I purposefully won’t surf near a river mouth after storms.” Surfers who attest to surfing during an advisory are also likely to notice water quality. Given that an advisory has been issued, surfers who are in the water at that time are more likely to notice differences in the water. Furthermore, the association between LEK and attributing surfing to sickness may indicate that surfers who have experienced adverse impacts from surfing in contaminated water may be more tuned in to the factors they associate with poor water quality such as smells or water color. These surfers have been directly impacted by water quality and thus, they may be more likely to notice differences in the water because they are concerned about the possibility of becoming ill. This further supports the idea that experience drives surfer LEK. It is reasonable to conclude that surfers who have attributed surfing to sickness would be more aware of water quality because they have first-hand experience with the repercussions.

Though not a majority, over a quarter of surfers surveyed indicated they had attributed surfing to sickness (Table 7). Though not an epidemiological study, this shows that surfers in Maine and New Hampshire are attributing sickness to surfing. This shows that even in the Gulf of Maine surfers are linking surfing to sickness, demonstrating a need for improved beach management and communication of water quality risk to this vulnerable population. Given the extent of their LEK and their vulnerability to water quality risk surfer should be considered as important stakeholders in coastal management decisions.

5. Conclusion

Our work sheds light on an often overlooked beach stakeholder group. We show here that surfers not only can contribute valuable data to the field of science and are capable of providing useful insights for beach and water quality management, they also hold knowledge of the social ecological systems in which they surf. Given that surfers frequent the beaches during times of poor water quality, their contribution of LEK is of value to beach managers and policy makers. LEK is an important factor to include in coastal management decisions and when interested in knowledge pertaining to local water quality experienced surfers are arguably the one best provider of that information. This study did not explore many of the other components of local ecological knowledge and given the insights we were able to glean from a focused look at water quality, we would suggest that further research could be done on other aspects of LEK in the surf zone.

By providing LEK about water quality at their local surf spots, surfers can act as the ‘canaries in the coal mine’. Surfers are at the front lines of the social ecological system that is our coastal environment. The love of the sport and the reliance on a healthy coastal system for the continuation of their form of coastal recreation make surfers ideal candidates not only for the contribution of valuable LEK, but as strong stewards of coastal health. Indeed, environmental advocacy-surf groups are a worldwide phenomenon and the Surfrider foundation has active chapters in both Maine and New Hampshire. Engaging with this important stakeholder group could prove invaluable to beach managers and their efforts to maintain healthy and clean waters for all.

Acknowledgements: We wish to thank all of the surfers who participated in our research, the Plymouth State Center for the Environment, and New England Sustainability Consortium. Funding for this research was provided by the National Science Foundation award #1330641. The findings represent the views of the authors only and not the NSF or its employees.

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Chapter 3: Manuscript Two Submitted to Journal of Coastal Management

WATER QUALITY IMPACTS ON SURFER PERCEPTIONS OF RISK

Sophia Scott and Shannon Rogers Center for the Environment, Plymouth State University, MSC #63, 17 High Street, Plymouth, New Hampshire, 03264, United States

ABSTRACT

Water quality and the subsequent beach advisories resulting from impaired quality are significant problems throughout the world and specifically in the Gulf of Maine where our study took place. Surfers represent a culturally and economically important subpopulation of beachgoers who are subject to higher risks associated with impaired water quality. This increased risk is related to the amount of time surfers spend in the water, the higher incidence of water ingestion, and the propensity for surfers to surf around storm events when water quality is the lowest.

In our research we surveyed almost 300 surfers and conducted 20 interviews with gatekeepers in the surfing community in the Gulf of Maine. We found that given the level of environmental exposure coupled with a strong sense of environmental sustainability within the local surfing community, Maine and New Hampshire surfers provide valuable insight on issues of water quality. We find that surfers indicate that water quality and pollution can impact an individual’s decision to surf. Given this, surfers should have equal accesses to water quality information at their local surf spots. Surfer's knowledge can prove useful to researchers and help drive policy changes related to water quality management.

KEYWORDS Risk and decision-making, water quality, coastal management, surf science, stakeholders

1. Introduction

Coastal areas and communities are some of the most vulnerable regions worldwide. In addition to being home to 44% of the world’s population (UN Atlas of the Oceans 2010), coastal regions are likely to be significantly impacted by climate change and the advent of sea level rise (Nicholls et al. 2010). The coastal regions of our world face challenges such as saltwater inundation (Barlow and Reichard 2010), coastal erosion and beach loss (Zhang et al. 2004), and excess nutrients flowing off the land and polluting coastal waters (Rabalais et al. 2009). Indeed, coastal water quality is a growing issue worldwide (Gilbert et al. 2006). Impaired coastal water quality not only has implications on natural plant and animal communities, but also has significant impacts on the human dimension. Impaired coastal water quality can cause closures in shellfish and other fisheries and as well as advisories and closures on recreational beaches (Grant and Sanders 2010, Given et al. 2006, Glasoe and Christy 2004, Boehm et al. 2002).

Beach recreation is one of the most popular American pastimes with a projected estimation of 70.9 million Americans visiting beaches for a total of 969.6 million

36 visitation days in 2010 (Leeworthy et al. 2005). Despite its chilly reputation, the northern New England region of southern Maine and New Hampshire is a popular beach hub for the surrounding areas. The significance of tourism to the coastal economy is notable, representing 64.7% of the ocean economy jobs in Maine and 43% of the ocean economy jobs in New Hampshire (NOEP 2014). Combined, the coastal zone in Maine and New Hampshire contributes $3.8 billion to the states’ GDP and an additional $2.2 billion in wages (NOEP 2014). Thus, beach advisories and closures pose significant economic impacts for Maine and New Hampshire.

Maintaining and preserving beach water quality is important for the continued and sustained use of our coastal beaches. Not only do coastal systems provide ecosystem services and natural habitats they also produce important socio-economic benefits for costal residents and tourists alike. Noting the importance of clean coastal recreational waters, the USEPA passed the BEACH Act in 2000. This Act placed more stringent standards on coastal water quality with specific attention to pathogens that are harmful to human health (Boehm et al. 2009). Through the implementation of monitoring standards the EPA decreased the water quality risk and potential human health implications for the average beachgoer. The level of water quality risk can differ between groups of beachgoers; for instance, young children tend to be more susceptible to the harmful pathogens associated poor water quality (Wade et al. 2008). In addition to inhabiting coastal waters, levels of pathogen have also been found in the sand (Heaney et al. 2009) and seaweed (Quilliam et al. 2014). However, the greatest risk for exposure to harmful pathogens occurs in beach-going populations who chose recreation activities that involve water contact such as swimming, bathing, or surfing.

Among these activities, surfers are arguably more at risk to impaired water quality for a number of reasons. Compared to other beachgoers, surfers frequent beaches more often and spend longer periods of time in the water (Turbow et al. 2008). Surfers surf year round, especially in the northeast where the surf conditions tend to be better during the winter months. There is evidence that some regions experience more rainfall and poorer water quality during these ‘off’ months (Bradley and Hancock 2003). Surfers also tend to surf during and after storm events when the waves are the best, but the water quality is at its lowest (Tseng and Jiang 2012, Nelson et al. 2007, Bradley and Hancock 2003). Lastly, surfers are more apt to ingest water or get cuts or scrapes through which microbial pathogens can enter (Tseng and Jiang 2012, Stone et al. 2008). For these reasons, surfers are more at risk for issues associated with water quality.

Though not extensively studied, we do know a bit about surfers’ exposure to the risk of impaired water quality. These studies have shown that there is higher incidence of illness in surfers when compared to other beachgoers and that this was likely influenced by the amount of ingested seawater (Tseng and Jiang 2012, Stone et al. 2008). Furthermore, Harding et al. (2014) investigated the relationship between risky surf behaviors such as surfing near an outflow or surfing after storms and an increased incidence in self-reported illnesses. This knowledge, along with the growing body of literature on illness caused by exposure to coastal waters (Tseng and Jiang 2012, Turbow 2008, Dwight et al. 2004), illustrate the need for a greater understanding of risky surf behaviors and decision making processes in the surfing community as to lessen the incidence of illness and ensure the safety for all water recreators.

All this begs the question, what do surfers consider to be risky and do any of these risks impact a surfers’ decision to enter the water? Risks that are commonly associated with surfing include injury, drowning, sharks and other sealife, and other surfers in the water (Nathanson 2012). Surfing also has the reputation for being a risky sport. Some have argued though that this associated risk comes from the thrill seeking or ‘surfing high’ that is an experience of some surfing participants (Stranger 1999). However, though surfing is perceived as a risky sport (Stranger 1999) there is evidence that compared to other sports it has a relatively low risk of injuries (Taylor et al. 2004). There are few studies that actively examine risk and decision making in the surfing community as it relates to coastal management. To the best of the authors’ knowledge this study is the first of its kind investigating what surfers in the northeast United State perceive as risky, whether they consider water quality a risk, and whether or not this impacts a surfers’ decision to enter the water and how we might engage with and communicate better with this vulnerable group.

Knowledge of beachgoers behavior in response to water quality is important information for beach managers and policy makers. This research will help to improve risk communication to a particularly vulnerable group so that they are able to make more informed decisions on when to enter the water. Risk communication is an effort to provide information so individuals can make informed decisions (Morgan 2002). It relies upon appropriate, comprehensible, and available communication for all users and relies on an effective message for success. The lack of effective risk communication can degrade trust and empowerment in a stakeholder group, which in turn can create opportunity for conflict (Morgan 2002). Unbiased and trustworthy risk communication is an effective tool for stakeholders and other users to make more informed decisions regarding risk, in our case the risk of surfing during periods of poor water quality. An understanding of the perception of risk and decision-making in the particularly risk prone group of surfers not only sheds light on an understudied population in the Gulf of Maine but also yields knowledge around the issue of beach users’ perceptions of water quality risk and whether or not this impacts a surfers’ decision to surf. This knowledge will yield valuable insights for beach managers and policy makers to improve future risk communication so that all beach goers can make informed decisions about when to enter the water.

2. Methods

2.1 Study Area

This research focused on 12 surf beaches in the Gulf of Maine from May 2015 to October 2015. The Gulf of Maine is of particular interest given that its waters are warming faster than 99% of the world’s oceans (Pershing et al. 2015) making it at the epicenter of a changing climate’s impacts on the oceans. Of the surfable beaches included in the study 7 beaches are located in southern Maine and 5 beaches are in New Hampshire. The beaches of southern Maine and New Hampshire are popular tourist destinations during the summer months (Pesch and Wells 2004).

The economic impact of the coastal tourist economy is significant for both Maine and New Hampshire. It is estimated that tourists contribute respectively $1.2 billion and $256 million to the Maine and New Hampshire coastal economies (NOEP 2014). While southern Maine and New Hampshire are geographically close, the two states have significant differences in beach water quality. In their 2013 report, the National

Resource Defense Council (NRDC) ranked the 30 states with coastline by beach water quality based on the national Beach Action Value (BAV) safety threshold (Dorfman and Haren 2013). In the report New Hampshire ranked 2nd for the cleanest beaches while Maine was ranked 27th, three shy from having the least clean beaches in the nation (Dorfman and Haren 2013). The beaches included in our study demonstrate this contrast (Table 1).

Table 1. National Resource Defense Council Beach Action Value (BAV) exceedances for 2013 and number of issued beach advisories for 2015 (Dorfman and Haren 2013, MHB 2015, NHDES 2015). Beaches Percent BAV exceedance Number of advisories

New Hampshire Jenness 0% 0 Bass 4% 0 North Hampton 1% 0 The Wall 1% 0 Seabrook 0% 0

Maine Higgins 19% 12 Old Orchard 10% 3 Fortune’s Rock 0% 0 Gooch’s 38% 14 Wells 22% 3 Ogunquit n/a* 0 Long Sands 22% 15 *NRCD percent BAV exceedance was not available for this beach.

During our data collection period (May-October 2015) there were 47 advisories issued at the study beaches in Maine and 0 issued in New Hampshire (Table 1). It should be noted that beach management varies between the two states. In Maine the Maine Healthy Beaches program is responsible for water quality testing and beach advisories. Maine Healthy Beaches is funded by the State but heavily reliant on volunteers for sampling and posting advisories. In New Hampshire, beach management falls under the authority of the state’s Department of Environmental Services and has a professional staff that oversees this process. In both states water quality testing and monitoring occurs only between Memorial Day (late May) and Labor Day (early September).

2.2 Methods

We set out to understand the relationship between surfers’ perceptions of risk and water quality and whether these play a role in the decision to enter the water at any given time. Specifically, we were interested in whether knowledge of water quality or pollution would impact a surfer’s decision to enter the water. Given surfers’ potentially increased vulnerability to water pollution, we also sought to understand how surfers thought about risk, how risk impacted their decision to surf, and whether surfers considered water quality to be a risk.

We took a multimethod approach to this question, combining the qualitative and quantitative research methods of literature review, interviews, and surveys. Preliminary interviews conducted in the spring of 2015 informed the development of our survey instrument. Field-testing of our survey resulted in changes and modifications to the instrument. Though the results from our interviews are not included in this analysis of

39 risk, water quality, and decision-making in the surfing population, preliminary knowledge gained from the interviews informed the development of our survey instrument (Figure 1). Specifically, after conducting a number of interviews we discovered that understanding a surfer’s experience measured by the number of years surfing would be a useful and informative parameter to include. Therefore, we added this question to our survey instrument. This is one example of the ways in which preliminary results from our interviews informed the development of our survey instrument.

Figure 1. Diagram representing iterative process of our methodology development 2.2.2 Survey protocol

From May-October of 2015 we conducted a 10-question intercept survey on the 12 surf beaches of our study area. The target participant was a surfer above the age of 18 who was present at a beach within our study area. We focused solely on the surfing population and excluded other wave riders such as boogie boarders, body surfers, stand up paddle boarders, and  Have you surfed… wind surfers. We would o During storms? approach surfers exiting the o During a posted beach water quality advisory? water and after consent was  Have you ever noticed anything in the water that would make you question its quality? given would verbally administer  Do water pollution concerns impact your decision to the survey. Survey participants surf? were thanked with a gift of surf o Is this a risk?  Have you ever attributed getting sick to surfing? wax. The survey was designed  Would you be interested in knowing about water to elicit a surfer’s knowledge of quality conditions at your local surf spot? risk, water quality, and whether  How would you like this knowledge shared with the these impact the decision to surf surfing community?

(Figure 2). Surveys typically Figure 2. Examples of survey questions took about 5 minutes to complete.

During our data collection period we visited the beaches in our study area a total of 64 times. Of those sampling attempts, surfers were present to survey 39 out of the 64 efforts, representing a sampling success rate of 6.51% (Table 2). A successful beach visitation (survey attempt) occurred when there were surfers present to survey. Over the course of the field season n=291 surfers were surveyed with a 90.6% response rate.

Table 2. Intercept survey sampling schedule

Beach Survey Failed survey No. surfers No. surfers declined attempts attempts surveyed survey Jenness 9 1 68 5 Bass 2 1 1 0 North Hampton 2 2 0 0 The Wall 9 3 37 6 Seabrook 4 4 0 0 Higgins 7 1 78 8 Old Orchard Beach 5 5 0 0

Fortune’s Rock 4 0 16 0 Wells 6 4 4 1 Long Sands 4 1 33 4 Gooch’s 7 2 42 3 Total 64 25 291 30

2.3 Data analysis

Relevant survey answers were transformed into numeric codes to allow for easier data analysis. Answers that could be easily coded into binary or other numerical data were transformed to allow for easier statistical analysis. For example, the categories of ‘Male’ and ‘Female’ were coded into ‘0’ and ‘1’. Similar codes were created for ‘Yes/No’ answers. Survey questions with answers that had more than two categorical options such as ‘Education’ and ‘Residence’ were coded using a numbering scheme. For the more qualitative-based, open-ended questions such as ‘Top risks associated with surfing’ or ‘How would you like [water quality] information shared with the surfing community?’ we grouped similar categories together and assigned them a numeric code to allow for a coherent analysis.

Where applicable we employed the use of statistical analysis for our survey data. We conducted descriptive statistics for all appropriate survey variables. Categorical variables were analyzed through cross-tabulations and significance was tested using the chi-square test of independence. For comparison between our dependent binary categorical variables and the continuous independent variables of age and number of years surfing we conducted logistic regression analysis. Additional logistic regression analyses were conducted between dependent binary categorical dependent variables and independent categorical variables with greater than 2 categories.

Results

A total of 291 surfers participated in the survey with a 90.4% response rate. Respondents were primarily male, which is characteristic of the global surfing population, and had a bachelors degree or higher with in rage in ages of 18-79 and an average of 11.4 years surfing. The majority of surfers surveyed were from either Maine or New Hampshire (60.2%). A summary of the demographic information is presented in Table 3.

Table 3. Overall sample characteristics (n=291) Characteristics n Frequency Percentage (%) Gender 291 Male 232 79.9 Female 59 20.3 Residence 291 MA 63 21.6 ME 116 39.9 NH 59 20.3 QC 29 10 Other 24 8.2 In-state surfers* In-state ME 184 112 60.9 In-state NH 107 42 39.3 Education 291 HS 28 9.6 Some college 56 19.2 Associates/technical 12 4.1 Bachelors 130 44.7 Graduate 65 22.3 Membership in an environmental or surf group 291 Not a member 215 73.9 Yes, a member 76 26.1 Surf risk 291 No, surfing is not risky 80 27.5 Yes, surfing is risky 133 45.7 Risk is dependent on conditions 78 26.8 Surfing during storms 291 No, I have not surfed during/after storms 64 22 Yes, I have surfed during/after storms 227 78 Surfing during posted water quality advisory No, I have not surfed during an advisory 185 63.6 Yes I have surfed during an advisory 106 36.4 Noticing something questionable about the water quality 291 No, I have not noticed questionable water quality 147 50.5 Yes, I have noticed something questionable 123 42.3 Not here 21 7.2 Impact of water pollution on the decision to surf 291 No, water pollution does not impact my decision to surf 127 43.6 Yes, water pollution does impact my decision to surf 167 47.1 Not here 27 9.3 Water pollution risk 291 No, water pollution is not a risk 44 15.1 Yes, water pollution is a risk 206 70.8 Not here 41 14.1 Attributing surfing to sickness 291 No, I have never attributed surfing to sickness 206 70.8 Yes, I have attributed surfing to sickness 85 29.2 Interest in knowing about local surf spot water quality 291 Yes, I am interested in local water quality 281 96.6 No, I am not interested in local water quality 6 2.1 Other 2 0.6 Continuous Variables Mean, (median), [min-max] Age 33.6, (31), [18-69] Number years surfing (surfing experience) 11.4, (9), [0-52] *In-state meaning that surveyed surfer was a resident to the state in which the surfer was surveyed. For instance, if a surfer was surveyed at Higgins Beach in Scarborough, ME and indicated that they were a resident of Maine, this classified them as ‘In-state ME

The majority of surfers surveyed stated that surfing is a risky sport (45.7%) while others said that risk was dependent on conditions (26.8%) or that surfing is not risky (27.5%). Of those who expressed that surfing is a risky sport, when asked to report on the riskiness of surfing using a 10 point Likert scale (1 meaning safe and 10 meaning dangerous) the mean risk was ~5 (Figure 3). When asked to rank the top three risks associated with surfing the highest identified risk was drowning (27.8%) followed by injury (14.8%), and others in the water (13.4%) Figure 3. Histogram of Likert scale of risk. 1=safe, (Table 4). 10=dangerous

Table 4. Top three risks identified by survey participants

Rank Stated risks No. 1 risk Drowning (27.8%) Injury (14.8%) Others in the water (13.4%) No. 2 risk Injury (16.8%) Others in the water (14.4%) Rocks, reefs, shallow bottom (14.1%) No. 3 risk No other risks (17.2) Others in the water (16.2%) Injury (14.4%)

Water quality is not viewed as a top risk for surfers in our study area. Indeed, when asked to list the top three risks associated with surfing, water quality was identified only twice over the entire 291 sample, once as the number one top risk and once as the third risk. However, when asked directly if water pollution was risk, a large majority of surfers (70.8%) stated that yes, water pollution is a risk. As to whether or not this risk translated to decision-making around the choice to surf in polluted water, the reaction is more split, with 47.1% indicating that water pollution would impact their decision to surf, 9.3% of surfers stating that it wouldn’t impact there decision to surf here (‘Not here’ category) and 43.6% noting that water pollution would not deter them from surfing. Despite this almost all surfers (96.6%) indicated that they were interested in knowing about water quality at their local surf spot and specified the best way that this information could be shared with the surfing community with the most popular method recorded as the online resources of surf forecasting websites such as magicseaweed.com, swellinfo.com, or surfline.com (Table 5).

Table 5. Preferred method of water quality communication

Knowledge sharing method Percentage (%) Online 55.0 Posted at beach 18.4 Social media, text, app 11.8 Surf shop 8.6 News outlet or local government 3.5 Surfrider Foundation 2.0 Other 0.7

In terms of risky surf behaviors 78% of surfers reported surfing during or after storms and 37% of surfers surfed during a posted beach water quality advisory (Table 3). We were interested in understanding why surfers would choose to participate in these risky surf behaviors of surfing during a storm or water quality advisory. We wanted to know if any of the variables we tested for would have a significant association with these behaviors. Surprisingly, neither behavior had a significant correlation with general surf risk. Nor was there any significant association between risky surf behaviors and water pollution impacting the decision to surf or the consideration that water quality is a risk.

We were also interested in determining what variables had a significant association with water quality risk. Specifically, we were interested in knowing if surfers with certain characteristics were more or less likely to believe that water quality was a risk. When evaluating the variables that have an association with water quality risk, the results from the chi-squared test of independence show that the variables of surf risk and water pollution impacting the decision to surf have significant correlation, x2(1, n=182)=5.829, p=0.016 and x2(1, n=234)=6.003, p=0.014, respectively.

Additionally, we wanted to know if there were any significant relationships with the question about water pollution impacting the decision to surf. Other than the association already determined between water quality risk and the decision to surf, age was the only other factor that had a significant association.

Variables that were significantly associated with general surfing risk were the variable of risk of water pollution (x2(1, n=182)=5.829, p=0.016), as well as gender (x2(1, n=213)=5.722, p=0.017), Maine residents compared against non-Maine residents (x2(1, n=213)=5.624, p=0.018) and Quebec residents compared against non-Quebec residents x2(1, n=182)=4.740, p=0.029).

4. Discussion

This study sheds light on an underrepresented group that is more prone to water quality risks than other beachgoer groups. Though surf research exists, many of the studies are focused on west coast surfers and Australia (Scarfe et al. 2009). To the best of our knowledge this is the first study to focus on the surfing population in the Gulf of Maine and eastern North Atlantic. Over the past several decades the popularity of surfing has increased throughout all sectors of society, some even calling it the ‘new golf’ in

44 business circles (Stone 2015, Boddy 2014). Additionally, with better technology in terms of surf gear, specifically wetsuits, surfing is becoming more and more popular in regions with cold water temperatures (Callard 2014, Bodry 2012). Given this, it is important for beach managers and other policy makers to understand this population, who not only frequents beaches more often, but are also more likely to visit a beach and enter the water during periods of poor water quality. Furthermore, surfers deserve to have equal access to water quality information so that they are able to make informed decisions about when to enter the water.

Anecdotal accounts may spread the idea that surfers are a laid back group without a care or worry, however this study demonstrates that surfers are generally an engaged population who think constructively about issues of risk. Our research shows that although it is rarely explicitly stated when asked to rank the top risks associated with surfing, when asked directly the majority of surfers in our study, state that water pollution is a risk (Table 3). Why surfers indicate that water pollution is a risk, but do not mention it in their top risks may stem from the difference between risk perceptions with regards to risk severity versus the risk probability (Boholm 1998). Drowning and death are severe outcomes that may arise from surfing activity. However, there is arguably a small probability that these outcomes actually occur in the average surf session. For example, the rates of drowning and death in surfing are no more than of skiing (Nathanson 2012). The way that individuals think about risk in terms of severity is a likely reason why surfers don’t mention water pollution when listing their top surfing risks. Indeed, when administering the survey on the beach when asking questions pertaining to water pollution risk or the occurrence of becoming ill due to surfing we would hear remarks such as “Oh, I’m much more likely to become sick than drown” or “Yeah, water quality is definitely a risk, I should have listed it before”. Though the risk associated with impaired water quality can be quite serious ranging from diseases such as staph, norovirus, and giardia (Wade et al. 2008, Pond 2005) to the possibility of death from an infection contracted during surfing (Hlavsa et al. 2015), the majority of the risks associated with water quality and surfing are generally non-life threatening (Turbow et al. 2008, Dwight et al. 2004). Therefore, it is not unusual that water quality risk is not associated with risk severity and falls within the category of risk probability, and not mentioned in the top three risks.

This study also shed light on the incidence of ‘risky surf behaviors’ in the surfing population of southern Maine and New Hampshire. These risky behaviors are surfing during or after a storm and surfing during an advisory (Harding et al. 2014). Surfing during storms and during a posted advisory is related to an increased risk of exposure to water borne pathogens (Harding et al. 2014, Tseng and Jiang 2012, Stone et al 2008). We found that a majority of surfers surfed during storm events and over a third knowingly surfed during a posted beach water quality advisory (Table 3). Our results are similar to those of Harding et al. 2014 who found that 29% of surfers knowingly surfed during a posted water quality advisory. Another study looked at both surfer and other beachgoer responsiveness to water quality advisories and found that there was no significant decline in beach visits during a posted advisory (Busch 2009). This demonstrates that a proportion of surfers will knowingly surf during an advisory. Are surfers willingly surfing during a posted advisory knowing the risks of impaired water, do they understand the risks but question the science or policy behind the advisories, or are they unaware of the risks that are associated with surfing in an advisory? Our research did not address these questions, however, future research could investigate the reasons behind the choice to knowingly surf during a water quality advisory.

In terms of how risk perception relates to the decision to surf or not to surf, almost half of the surfers in our study indicate that water pollution impacts their decision to surf while fewer than ten percent responded “Not Here” (Table 3). The “Not Here” answer may indicate that in general water pollution would impact their decision to surf but it doesn’t ‘here’. This ‘Not here’ answer could reflect that in comparison to other areas, the beaches in our study are relatively clean. By nature, surfers are a mobile population who often travel to other regions for pursuit of the sport (Buckley 2002). Thus, they are exposed to many different types of water across the country and the world. Compared to other regions of the United States, notably California which is home to 29% of the surfers in the US (SurferToday.com 2011) and known for its acclimate water quality (Dwight et al. 2004), the Gulf of Maine and specifically beaches in Maine, and especially New Hampshire (a state which was ranked as 2nd cleanest by the NRDC) (Dorfman and Haren 2013) are perhaps viewed has having good water quality in comparison to other regions. Also, urban coastal areas tend to have poorer water quality (Dwight et al. 2004) and because our coastline has relatively low coastal development could be another reason why some surfers in Maine and New Hampshire indicate that they’re concerned with water quality, just ‘Not Here’.

From a management standpoint, given that nearly half of the surfers surveyed in this study indicated that water pollution would impact their decision to surf, it is important that water quality information be shared with the surfing community. Surfers overwhelmingly want to know about water quality at their local surf spot (Table 3) yet this information is not always easily accessible. For instance, during one sampling session we surveyed surfers at a beach where there was an active beach water quality advisory. Of the sample of surfers that were surveyed that day, all reported that they had never surfed during a posted water quality advisory, despite just surfing in one. Another example of surfers not having equal access to water quality information occurred during another sampling session. At this particular beach surfers are only allowed to surf before 11am or after 5pm. There were many surfers in the water that morning but it wasn’t until after 11am that a volunteer posted the water quality advisory sign and flag. By that time surfers had already been exposed to the water without the option of making an informed decision. Though not empirical, this anecdotal evidence tells the story that water quality information may not be available or easily accessible to surfers in our study region.

Surfers frequent the beach at different times than the typical beachgoer (Bradley and Hancock 2003). They’ll go early in the morning, later in the evening, in the shoulder seasons and during the winter months. Thus, the typical method of information sharing may not be appropriate for the surfing population. Surfers in this study were asked the ways in which they’d like to see water quality information shared with their community. The most preferred method of communication was through surf forecasting websites (Table 5). Surfers make frequent use of these websites to check for surf conditions, such as wave height, wind direction, and swell interval, at specific surf locales. Providing water quality information on the same sites where surfers check the surf forecast would allow surfers better access to water quality information. Integration of water quality information with the surf forecasting websites would require collaboration and communication between state agencies and private companies. Though this is a good idea in principle, it may not be the most practical method of communication given the methodology and technologies used in sampling for water quality. Currently, the state of water quality sampling relies on technologies that do not deliver results until

46 the next day. By then, the coastal water quality has changed. What can result from this current method is a beach advisory that either shouldn’t be issued, yet is, or should be issued, but is not. Despite this incongruity in beach advisory methodologies, surfers should still be afforded the same access to water quality advisories as other beachgoers. This means at the very least insuring that when water advisory signs are posted at the beaches, they are posted at times when all beachgoers have access to them. Additionally, local municipalities should work with the state organizations to ensure that beach advisory signs are available at all points of beach access and in clear view to those entering the beach.

When devising beach management strategies around the issue of water quality it is important to target populations who are more at risk. This is observed in other forms of risk communication, for example air quality alerts from the National Weather Service target individuals such as children, the elderly, and individuals suffering from asthma (NWS 2016). While some may contemplate the risks and benefits in a certain surfing situations, there is evidence that surfers will choose riskier decisions despite the alternative of a less risk prone option (Taylor et al 2005). So for some surfers the benefits of catching that gnarly wave may outweigh the costs of exposing one’s self to polluted water. Despite this aversion to behaviors that reduce risk, water quality information should still be available to the surfing population so that they are at least afforded the opportunity to make informed decision about whether or not to enter the water.

Lastly, this work yields important knowledge and information to set the stage for future work. Surfers are a vulnerable population of beach goers and our work demonstrates that there is a heightened need for a broader communication effort to ensure that all stakeholders are provided with information concerning risk. We have learned throughout this research that local surf shops are a hub of surf activity along the coast and could potentially be an important and centralized point of connection when communicating with the surfing population. The results of our research will be shared with the surf shops along the coast and we hope will begin to pave the way for an ongoing conversation and collaboration around water quality risk and risk communication in the surfing population.

5. Conclusion

Surfers are an important, yet often overlooked population of coastal stakeholders. In terms of water quality risk they are one of the most vulnerable beachgoing populations given the length of time spent in the water, frequency of beach visits and water contact, likelihood of water ingestion, and propensity to surf during conditions of poor water quality. Though some surfers may not take into account water quality risk in the decision to go surfing, this study shows that over 95% of surfers in our study are interested in knowing about water quality at their local surf spot. This has implications for beach management on the coast. Beach managers and local municipalities in towns that have surfable beaches should work together to ensure that water quality information is easily accessible by all populations who visit beaches.

Additionally, it may be prudent to further investigate the way risk is communicated to the surfing population. Though not a majority, almost 40% of surfers we surveyed knowingly surfed during a beach water quality advisory. It may be that surfers in our study area are unaware of the potential impacts of surfing during an advisory. To

47 address this, a method of communicating risk should be developed to ensure that surfers are at least aware of the risks that they could potentially encounter when surfing during an advisory.

Further investigation into the knowledge around issues of water quality and risk in the surfing community could illuminate reasons why surfers knowingly choose to surf in advisories. New studies that seek to understand the knowledge of water quality risks in the surfing population could provide useful insights into new methods of risk communications, especially in this region where water quality is an issue of growing concern.

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Chapter 4: Summary Statistics

Overall interview sample characteristics (n=20) Characteristic Frequency Percentage (%)

Overall intercept survey sample characteristics (n=291) Characteristics n Frequency Percentage (%) Gender 291 Male 232 79.9 Female 59 20.3 Residence 291 MA 63 21.6 ME 116 39.9 NH 59 20.3 QC 29 10 Other 24 8.2 In-state surfers* In-state ME 184 112 60.9 In-state NH 107 42 39.3 Education 291 HS 28 9.6 Some college 56 19.2 Associates/technical 12 4.1 Bachelors 130 44.7 Graduate 65 22.3 Membership in an environmental or surf group 291 Not a member 215 73.9 Yes, a member 76 26.1 Surf risk 291 No, surfing is not risky 80 27.5 Yes, surfing is risky 133 45.7 Risk is dependent on conditions 78 26.8 Surfing during storms 291 No, I have not surfed during/after storms 64 22 Yes, I have surfed during/after storms 227 78 Surfing during posted water quality advisory No, I have not surfed during an advisory 185 63.6 Yes I have surfed during an advisory 106 36.4 Noticing something questionable about the water quality 291 No, I have not noticed questionable water quality 147 50.5 Yes, I have noticed something questionable 123 42.3 Not here 21 7.2 Impact of water pollution on the decision to surf 291 No, water pollution does not impact my decision to surf 127 43.6 Yes, water pollution does impact my decision to surf 167 47.1 Not here 27 9.3 Water pollution risk 291 No, water pollution is not a risk 44 15.1 Yes, water pollution is a risk 206 70.8 Not here 41 14.1 Attributing surfing to sickness 291 No, I have never attributed surfing to sickness 206 70.8 Yes, I have attributed surfing to sickness 85 29.2 Interest in knowing about local surf spot water quality 291 Yes, I am interested in local water quality 281 96.6 No, I am not interested in local water quality 6 2.1 Other 2 0.6 Continuous Variables Mean, (median), [min-max] Age 33.6, (31), [18-69] Number years surfing (surfing experience) 11.4, (9), [0-52] *In-state meaning that surveyed surfer was a resident to the state in which the surfer was surveyed. For instance, if a surfer was surveyed at Higgins Beach in Scarborough, ME and indicated that they were a resident of Maine, this classified them as ‘In-state ME

Chapter 5: General Conclusion

Sustainability science has proven itself to be an apt method for tackling complex environmental problems. Its intent to solve place-based problems and inform policy is paramount and applicable to socio-environmental issues worldwide. Collaboration and knowledge production across research disciplines, institutions, stakeholders, community groups, and states is essential to ensure the future health of the Gulf of Maine. By examining Maine and New Hampshire surfers as a population vulnerable to water pollution this study highlighted an often overlooked but important beach stakeholder group. Very few studies have actively examined the relationship between surfers, their environment, and the perceived or real risks of water quality. Not only did this research aim to address this gap in the literature it also uncovered the reality of surfers as sources of local ecological knowledge (LEK).

To the best of our knowledge, this is the first research of its kind to study the surfing population in Maine, New Hampshire, or the Gulf of Maine. Though typically not thought of as a favored spot in the cool water of northern New England the surfing culture in Maine and New Hampshire is alive and well. There is no good data on the number of surfers in this region as no solid research attempt has been made to quantify surfers in our area. However, given our experience in this research there is little evidence to believe that this population is insignificant. Leaning on the social media platforms to illuminate some figures of surfing popularity in the region we note here that Facebook ‘likes’ on the Maine and New Hampshire pages are 351 and 458 respectively. On the Twittersphere the New Hampshire chapter has 636 followers while the Maine 190. Moreover, anecdotal evidence from talking with surfers throughout the course of this study indicates that the sport has grown immensely over the past few decades and will likely continue to spread in this region.

It is well documented that surfers play an important socio-economic role in coastal communities. They contribute to local economies through travel to surf beaches, dollars spent in parking fees, and through purchases at local stores, especially surf shops that populate the coastline from Hampton, NH to Portland, ME. Surfers in our region have also demonstrated interest in environmental issues through participation in the Surfrider Foundation events and initiatives. Given this, surfers should already be an important stakeholder group to include in beach management decisions. One important example of how surfers could influence coastal management is related to the length of the water quality monitoring season. Currently monitoring only occurs from Memorial Day to Labor Day in both Maine and New Hampshire. The reasoning behind this is that no beachgoers are entering the water outside this period and certainly not participating in any swimming or water contact activities where water quality would be of concern. However, surfers in this reason participate in the sport year round and especially in the shoulder seasons of the fall and spring when conditions yield the best waves. A change in how water quality risk is communicated to beach users, specifically surfers would be an important step forward in proactive beach and water quality risk management.

Our research has shown that surfers are valuable, informative, and influential members of the beachgoing community. Surfers can contribute valuable scientific data, provide useful insights for beach and water quality management, and share their wealth of LEK to scientists and policy makers alike. The presence of LEK in the surfing community

55 gives the opportunity for surfers to act as the ‘canaries in the coal mine’ with respect to water quality conditions at their local surf spots.

Furthermore, this study shows that surfers in our study region are overwhelmingly interested in water quality at their local surf spot and therefore this stakeholder group should have access to the information needed to make an informed decision about when and where to enter the water. This study also sheds light on the potential lack of risk communication reaching this population. Beach managers and local municipalities in towns that have surfable beaches should work together to ensure that water quality information is not only easily accesses by all populations who visit beaches but that methods of communicating this risk are developed so that all beachgoers and especially the vulnerable population of surfers are aware of the risks that they could encounter when surfing during an advisory.

Surfers are at the front lines of the socio-economic system that is our coastal environment. The love of the sport and the reliance of a healthy coastal system for the continuation of their form of coastal recreation make surfers ideal candidates, not only for the contribution of valuable LEK to researchers and policy makers, but as strong stewards of coastal health. Engaging with this important stakeholder group could prove invaluable to beach managers and their efforts to maintain healthy and clean waters for all.

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APPENDICES

APPENDIX A: IRB APPROVAL LETTER

Plymouth State University Institutional Review Board

June 19, 2015

Dear Sophia Q. Scott and Shannon Rogers,

On behalf of the Institutional Review Board (IRB) at Plymouth State University, your project entitled Risk Perception in Maine and New Hampshire’s Surfing Population: New England Sustainability Consortium has been granted approval for one year, ending June 19, 2016. Be sure to complete the Final Report Form when your research is finished.

If, during the course of your project you intend to make changes that may significantly affect the human subjects involved (particularly methodological changes), you must obtain IRB approval prior to implementing these changes. Any unanticipated problems related to your use of human subjects must be promptly reported to the IRB. The IRB may be contacted through Dr. Kathleen Norris, Chair of the IRB. This is required so that the IRB can update or revise protective measures for human subjects as may be necessary.

You are expected to maintain as an essential part of your project records, any records pertaining to the use of humans as subjects in your research. This includes any information or materials conveyed to and received from the subjects as well as any executed forms, data and analysis results. If this is a funded project (federal, state, private, other organization), you should be aware that these records are subject to inspection and review by authorized representatives of the University, State of New Hampshire, and/or the federal government.

Please note that IRB approval cannot exceed one year. If you expect your project to continue beyond this approval period, you must submit a request for continuance to the IRB for renewal of IRB approval. IRB approval must be obtained and maintained for the entire term of your project or award.

Please notify the IRB in writing when the project is completed. We may ask that you provide information regarding your experiences with human subjects and with the IRB review process. Upon notification we will close our files pertaining to your project. Any subsequent reactivation of the project will require a new IRB application. I have attached the Project Completion Form for your convenience.

Please do not hesitate to contact the IRB if you have any questions or require assistance. We will be happy to assist you in any way we can. Thank you for your cooperation and efforts throughout this review process. We wish you success in this endeavor.

Sincerely,

Kathleen Norris, Chair Institutional Review Board Plymouth State University [email protected]

APPENDIX B: STUDY AREA MAP

APPENDIX C: INTERCEPT SURVEY SCRIPT AND INSTRUMENT

The script used was as follows:

Researcher: Hello, my name is Sophia Scott and I’m a graduate student studying surfers. Would you be interested in participating in a quick 2-3 minute survey?” If participant agreed the researcher would then state: “By answering the survey questions you agree to participate in the study, would you like to continue?”

Names of the individuals were not asked and the only potentially identifying information received was the demographic information of age, gender, and residence

Demographics: Age: Gender: Residence: Date: Education: Beach: Number of years surfing: Weather: Member of surfrider/envr group: Surf Conditions:

1. Where do you get information on surf spots or conditions?

2. Do you think surfing is a risky sport? (YES/NO) If YES (safe) 1 2 3 4 5 6 7 8 9 10 (dangerous)

3. What risks, if any, do you associate with surfing? (OR: Can you rank the top three risks you associate with surfing) 1.

4. Have you surfed… a) during storms (Y/N) b) during a posted beach water quality advisory (Y/N)

5. Have you ever noticed anything in the water that would make you question its quality?

6. Do water pollution concerns impact your decision to surf? Do you consider this a risk?

7. Have you ever attributed getting sick to surfing? Where?

8. Would you be interested in knowing about water quality conditions at your local surf spot?

9 .How would you like this knowledge to be shared with the surfing community?

10. Do you consume raw shellfish?

APPENDIX D: INTERVIEW QUESTIONS

1. Where do you go surfing? Why? (Where do you get your information about surfing conditions?)

2. What are the most popular surf spots? What do you think makes these surf spots popular (quality of surf, environmental parameters, number of people)?

3. When you go surfing, what if anything, do you worry about?

4. Do you think surfing is a risky sport?

5. How would you define risk?

6. What are the risks you associate with surfing? How would you rank the top three risks?

7. Do any of these risks impact your decision to surf or not to surf? If so, how?

8. Have you ever noticed anything in or about the water that made you question its quality? (Prompts if needed: e.g. any strange smells, objects, colors, foam, etc.) Has this impacted your decision to surf and how?

9. Have you heard about water quality/pollution/contamination issues? If so, where did this information come from? Does it make you concerned? Why or why not?

10. Do you surf during storms or high rainfall events or during a posted beach advisory?

11. Have you ever attributed surfing to getting sick? Do you know of others who have? Where did they get sick and what do you believe are the reasons why? Does this knowledge impact any of your decisions about where and when to surf?

12. This is a jump, but we are interested in understanding a range of risks, so do you consume raw shellfish?

13. Demographic information (Age/Gender/Residence/Level of education/member of Surfrider, surf group, environmental group)

14. Any questions that I should be asking surfers that I haven’t asked?

15. Anything else you’d like to add to this conversation that I haven’t asked about?

lxix