Social and Ecological Drivers of Behavior that Prevents Aquatic Invasive Species Transport

Social and Ecological Drivers of Behavior that Prevents Aquatic Invasive Species Transport | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Social and Ecological Drivers of Behavior that Prevents Aquatic Invasive Species Transport Alison Moore, Danika Ford, Elizabeth Golebie, North Joffe-Nelson, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-2869687/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 24 Mar, 2024 Read the published version in Biological Invasions → Version 1 posted 5 You are reading this latest preprint version Abstract Aquatic invasive species (AIS) have caused widespread damage to environmental and socio-economic systems across the globe. One vector of biological invasions is recreational boaters who are at risk of unintentionally introducing AIS when moving between freshwater ecosystems. The drivers of boater behaviors and belief systems therefore warrant careful research attention, yet surprisingly few studies have empirically tested how the ecological context of biological invasions influences the behavioral decisions of recreational boaters. We asked: what are the relationships among boater proximity to AIS, perceptions of risk and efficacy, familiarity with AIS, and engagement in AIS prevention behavior? Drawing from a survey of boaters administered across the U.S. state of Illinois, we quantified and spatially located where boaters lived and evaluated their behavioral patterns. We then combined these survey data with spatially explicit observations of AIS across four taxa, which were collated using secondary data sources. We observed high levels of perceived risks from biological invasions, strong beliefs that individuals could make a difference in minimizing the spread of AIS, and low AIS-related familiarity. Results from a structural equation path model indicated that proximity to invasive fish species, but not other types of AIS, was associated with higher risk perceptions, which in turn, influenced self-efficacy and the intended behaviors of boaters. This study offers new insights on how decision-makers can optimize their effort and direct attention toward high and low priority locations defined in both social and ecological terms. aquatic invasive species recreational boater behavior risk perceptions spatial analysis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Aquatic invasive species (AIS) are increasingly changing the face of ecosystems and responsible for losses to biodiversity, changes to water quality, and impediments to human recreation (Gallardo et al. 2016 ). The impacts of AIS in the Great Lakes region alone exceed $ 100 million USD on an annual basis (Rosaen et al. 2012 ). As recreational boaters move between water bodies, they have the potential to unintentionally transport AIS that are attached to boats or are present within livewells or bilge water (Ready et al. 2018 ). Given the difficulties of remediating an ecosystem that has been degraded by AIS due to the persistence of (re)introduction vectors, preventative measures are fundamentally important in aquatic ecosystem management (Vander Zanden and Olden 2008 ). Numerous outreach campaigns have consequently been developed by state and federal agencies to encourage boaters and anglers to clean, drain, and dry their boats, trailers, and fishing gear before travelling between waterbodies (Seekamp et al. 2016 ; Golebie and van Riper 2022 ). In support of these outreach campaigns, management agencies have installed wash stations at boat ramps (Cimino and Strecker 2018 ) and implemented watercraft inspection programs to detect aquatic invaders on recreational watercraft and prevent their spread (Nathan et al. 2014 ). Awareness and detection interventions are becoming more widely adopted (Sharp et al. 2011 ; Kemp et al. 2017 ; Cole et al. 2019 ), but limited financial resources prevent their implementation at every recreational facility (Beaury et al. 2020 ). Given funding constraints, there is a strong need for managers to prioritize the physical locations at highest risk due to both social and ecological factors. A large body of research has focused on understanding the ecology of AIS (e.g., Morisette et al. 2020 ; Gallardo and Aldridge 2018 ), whereas less attention has been directed to understanding recreationists (e.g., boaters, anglers) and developing behavior change strategies that target these audiences (Witzling et al. 2016 ; Nanayakkara et al. 2018 ; Cole et al. 2019 ). Even less research focus has been given to interdisciplinary approaches that explore how the combination of social and ecological factors affects the spread of AIS (Golebie et al. 2022 ). Integrating knowledge from multiple disciplines creates opportunities to provide more holistic guidance for fisheries management agencies (Arlinghaus et al. 2015 ; Hunt et al. 2013 ) and can improve spatial planning to prevent the spread of AIS (Rothlisberger et al. 2010 ; Ban et al. 2013 ). For example, previous research has indicated that distance to water (van Riper et al. 2017 ) and coastlines (Johnson et al. 2019 ) account for large degrees of variation in how water-based recreationists value their environments. Indeed, proximity to environmental features has shown promise in its ability to explain how people perceive their environments (Brody et al. 2004 ; Wilkins et al. 2018 ). However, previous research has yet to empirically estimate how proximity corresponds to the reported or intended behaviors of water-based recreationists that are at risk of spreading AIS. Psychological drivers of behavior To better understand boater engagement in AIS prevention behavior, psychological theories such as Protection Motivation Theory (Rogers 1975 ) can be used to guide research. According to Protection Motivation Theory, an individual’s response to potential threats such as biological invasions is rooted in two key factors: 1) risk perceptions - their perceptions of the riskiness of that threat and 2) self-efficacy - the individual’s ability to take action that mitigates the threat. Individuals must believe the threat is severe and that they are capable of mitigating the threat before choosing to act. If self-efficacy is low, individuals may reject the severity of the threat itself to avoid negative feelings of helplessness (Maddux and Rogers 1983 ). A substantial body of research informed by Protection Motivation Theory has provided support for the relationships among risk, efficacy, and behavior (Mongeau 2013 ), including multiple conservation-related behaviors (Kothe et al. 2019 ; O’Connor et al. 1999 ). One study indicated self-efficacy and risk perceptions determined behaviors (e.g., removal of invasive plants) associated with terrestrial invasive species (Clarke et al. 2021 ). Despite this robust body of work, few studies have examined possible predictors of risk and efficacy, such as familiarity. Knowledge of the antecedent that gives rise to risk and efficacy can provide insights on how to form appropriate management strategies to minimize behaviors that threaten aquatic ecosystems. Risk perceptions encompass both the perceived susceptibility and severity to harm caused by a particular hazard. In accordance with Protection Motivation Theory (Rogers 1975 ), the Health Belief Model (Rosenstock 1974 ), and the Global Risks Report (World Economic Forum 2022 ), there is indeed robust evidence that susceptibility and severity are essential to understand and measure risk perceptions (Akerlof et al. 2013 ; Smith and Leiserowtiz 2012). However, studies of risk perceptions in AIS prevention (e.g., Golebie et al. 2021 ; Estevez et al. 2015) have been limited to the consideration of risk severity, while the dimension of susceptibility has been largely ignored, thus creating a significant knowledge gap in this body of work. Furthermore, previous research has indicated that physical risks such as zoonotic viruses and injuries caused by moving AIS (Conn 2013; Kahler et al. 2019) are instrumental in accounting for variation in risk perceptions when risk reduction strategies are not employed (Adam 2015 ). Despite this knowledge, environmental social science research has predominantly focused on understanding how the severity of risks are perceived for individuals and groups e.g., (van Riper et al. 2016 ) rather than accounting for the social-ecological relationships that give rise to how people interpret their environments. The confidence of individuals to perform a behavior (i.e., self-efficacy) has emerged as a strong driver of behavior in past research (Bandura 1977 ). If people do not feel confident in their ability to perform a task, even if they have made it a personal goal, they are much less likely to follow through and perform a desired behavior. Past work has suggested that self-efficacy is a stronger predictor of health-related behavior than risk perceptions (Ferrer and Klein 2015 ). Similarly in the context of AIS, having high self-efficacy gives people the confidence needed to complete preventative behaviors such as Clean, Drain, and Dry. For example, one study of bait shop owners’ engagement in AIS outreach demonstrated that self-efficacy was the most important factor in determining whether the owners talked about AIS with their customers (Howell et al. 2015 ). Self-efficacy is therefore likely to be a key factor in predicting boater behaviors that can help to mitigate the spread of AIS. Environmental social science research on biological invasions has yet to identify the full suite of drivers of risk perceptions and self-efficacy despite the insights that could be provided on how to craft successful outreach messages. One factor that may be relevant in determining the perceived risks of AIS is familiarity. This idea encompasses awareness of impacts incurred on aquatic ecosystems (van Riper and Kyle 2014 ), how water users can prevent the spread of AIS (Gates et al. 2009 ), and the way in which AIS issues are managed by relevant authorities (Simberloff 2009 ). Familiarity with AIS tends to be higher for those who are more active in water-based recreation activities due to more hands-on exposure to AIS and more frequent interactions with other recreationists (Seekamp et al. 2016 ). Heightened familiarity has been shown to increase perceived risk severity and self-efficacy among boaters (Rogers 1975 ), thus indicated a higher likelihood of engagement in preventative behaviors. Ecological drivers of behavior An expansive body of previous research has investigated the relationships among ecological and environmental factors and risk perceptions. The study context has played an important role in determining how risk perceptions are related to the strength of connections that form between people and places (Bonaiuto et al. 2016 ), including both positive (Xu et al. 2018 ) and negative relationships (Mishra et al. 2010 ; Bird et al 2011 ). Proximity between people and objects of interest has also emerged as a helpful explanation for why and how environments are perceived. For example, a negative association was found between the distance that participants lived from creeks in San Antonio Watersheds and their awareness of the environmental risks threatening that context (Brody et al. 2004 ). Further, the actual risk of an environment such as flooding has been shown to affect behavior (Stancu et al. 2020 ); however, there is limited research considering both ‘actual risk’ or ecological context of AIS alongside risk perceptions. Study Purpose and Objectives With limited resources, environmental managers are challenged to prioritize investments such as wash station infrastructure and communication campaigns in areas that are at greatest risk for degradation. Research is therefore needed to generate spatially explicit representations of where AIS are located and the factors affecting their spread. Thus, this study was guided by three objectives: 1) understand the ecological presence of AIS in relation to boater risk perceptions, 2) examine the relationships between proximity to AIS and perceived risks of biological invasions, and 3) determine how proximity to AIS works in conjunction with perceived risk, familiarity, and self-efficacy to influence the intended behaviors of boaters. We hypothesized that those in closest proximity to AIS will perceive greater risks than those who are farther away, and that familiarity will also play a role in positively predicting risk perceptions. We also hypothesized that both heightened risk perceptions and self-efficacy would lead to more AIS-preventative behaviors, in line with Protection Motivation Theory. These hypotheses were tested through 14 predictions depicted in Fig. 1 . Methods Ecological data procedures Data on AIS presence were retrieved from the United States Geological Survey (USGS) Nonindigenous Aquatic Species (NAS) Database. The database was cleaned to include only established populations throughout the state of Illinois for the years 1997–2021 for further analysis. Established populations were defined as those which successfully reproduced and overwintered according to the USGS NAS. The final database included 14,828 records of invasive species divided into four taxa: plants, crustaceans, fishes, and mollusks (Fig. 2 ). All of these data were utilized to identify the locations of organisms across the four taxa. As of 2016, 60 non-native aquatic species (or AIS) were considered established in Illinois waterbodies with an additional 39 species having their presence recorded though not yet established (Jacobs and Keller 2016). Survey data procedures Social science data were obtained using an online survey conducted from May-June 2021. Survey respondents were drawn from a Qualtrics panel and deemed eligible to participate in the study if they lived in the state of Illinois and had reported fishing or engaging in a recreational water activity (i.e., sailing, kayaking, canoeing, boating, jet skiing, etc.) at least once since 2018. A total of 507 individuals completed the survey. Because we wanted to understand AIS prevention behavior completed on boats (i.e., clean-drain-dry), we excluded 54 individuals who only engaged in shoreline angling and did not use boats or other watercraft as well as 7 individuals who had incomplete surveys, resulting in a total of 446 individuals who were analyzed in this study. Respondents were dispersed across 60 of the 102 counties in the state of Illinois. Respondents were on average 44.2 years old, and more than half were female (59%) (Table 1 ). Additionally, respondents reported a mean of 13 days boating per year and 20.8 years of experience. This study was approved under protocol #20679 by the Office for the Protection of Research Subjects at [identity withheld for blind peer-review]. Table 1 Demographics and boating experience of survey respondents. Variable Total Sample Age [M (SD)] 44.20 (17.49) Gender [N (%)] Female 252 (59.6) Male 171 (40.4) Other 0 (0) Total days boating/year [M (SD)] 12.51 (20.97) Total years of experience [M (SD)] 20.80 (18.77) Respondents were asked to report their perceived risks of AIS, self-efficacy related to AIS prevention, familiarity with AIS, and intended behavior to prevent AIS transport (Table 2 ). Two types of perceived risk were measured (Rogers 1975 ). First, risk susceptibility, defined as the perceived likelihood of species invasions, was assessed using two questions on a scale from 0%-100%. Given the importance of timescales in risk perceptions (Akerlof et al. 2013 ; Smith and Leiserowtiz 2012), respondents were asked to report the percent chance of species invasions occurring on two different timescales: within the next year and within the next 10 years. Second, risk severity, defined as the intensity of impacts caused by AIS, was assessed using nine items, three for each dimension including personal, environmental, and social risk. Self-efficacy was measured using a three-item scale (Bandura 1977 ) and was adapted to the context of AIS management. Three dimensions of familiarity were assessed, using three items for each dimension, including familiarity with invasion biology, relationships between recreation and AIS, and AIS management. Intended behavior was measured using a six-item scale (Pradanhanga et al. 2015) that was modified to resemble the goals of Illinois-Indiana Sea Grant and Illinois Natural History Survey’s Be A Hero – Transport Zero program (“Be a Hero!” 2021, TransportZero.org). These items were measured on a 5-point Likert scale ranging from ‘never’ (1) to ‘every time I go boating’ (5). We tested the validity and reliability of the risk, efficacy, familiarity, and behavior scales using factor loading scores (scores above 0.40 accepted; Hair et al. 2011 ), Cronbach’s alpha (coefficients above 0.60 were accepted; Cortina 1993 ) and MacDonald’s Omega (coefficients above 0.60 were accepted; Bagozzi and Yi 1988 ). All items and scales met acceptable thresholds and were included in further analysis. Table 2 Factor loading scores, means, and standard deviations for survey items evaluated by survey respondents. Factor loading M (SD) Intended behavior 1 (α = 0.901; Ω = 0.902; AVE = 0.605) 3.99 (1.00) Drain all standing water from the boat 0.747 4.10 (1.22) Conduct visual inspections of boats for invasive species 0.770 3.90 (1.28) Remove plants, animals, and mud from boat 0.834 4.18 (1.13) Rinse boat and trailer 0.777 3.98 (1.19) Wipe down hull with a towel 0.762 3.77 (1.28) Allow boat to dry before entering a different body of water 0.784 3.99 (1.25) Perceived risk susceptibility 2 (Spearman-Brown Coefficient = 0.836) 58.27 (22.22) How likely is it that invasive species will spread to your waterbody within the next year? 1.017 52.02 (23.77) How likely is it that invasive species will spread to your waterbody within the next ten years? 0.707 64.52 (24.27) Perceived risk severity 3 3.41 (0.79) Environment (α = 0.823; Ω = 0.824; AVE = 0.611)) Quality of habitat and natural environments 0.815 3.51 (0.90) Environmental processes (e.g., water cycle) 0.798 3.45 (0.95) Survival of plants and animals 0.729 3.71 (0.91) Personal (α = 0.815; Ω = 0.816; AVE = 0.598) Your appreciation of the beauty of the landscape 0.743 3.33 (1.10) Your own enjoyment of recreational activities 0.764 3.40 (1.07) your own access to the waterbody 0.807 3.24 (1.16) Social (α = 0.841; Ω = 0.860; AVE = 0.677) The local economy 0.858 3.17 (1.12) The community in the region 0.897 3.16 (1.13) Recreational opportunities for future generations 0.672 3.68 (1.02) Self-efficacy 4 (α = 0.864; Ω = 0.864; AVE = 0.680) 4.15 (0.74) I understand what I need to do in order to remove AIS from my boat or equipment 0.821 4.14 (0.85) I am capable of performing the tasks required to remove possible AIS from my boat and equipment 0.831 4.21 (0.83) I feel confident in performing procedures necessary to prevent AIS from spreading 0.822 4.09 (0.82) Familiarity 5 Invasion biology (α = 0.886; Ω = 0.887; AVE = 0.723) 2.67 (1.09) The biological characteristics that make a species “invasive” 0.858 2.85 (1.26) Names of species that are considered invasive 0.844 2.58 (1.19) Ways that invasive species affect the environment 0.849 3.01 (1.25) Relationship between invasive species and recreation (α = 0.914; Ω = 0.914; AVE = 0.780) How boaters and anglers can spread invasive species 0.839 2.82 (1.34) Types of actions you can take to prevent invasive species from spreading 0.906 2.69 (1.28) How to complete recommended preventative actions 0.905 2.58 (1.35) Invasive species management (α = 0.921; Ω = 0.923; AVE = 0.799) Agencies that are responsible for managing invasive species 0.869 2.56 (1.25) Management actions that reduce invasive species impacts 0.931 2.51 (1.29) The current state of invasive species management at your most frequented waterbody 0.879 2.45 (1.30) Note: Model fit was acceptable χ 2 = 868.663, df = 341, p < 0.001; CFI = 0.942; TLI = 0.931; RMSEA = 0.059; SRMR = 0.047 1 Measured on a 5-point scale from ‘never’ (1) to ‘every time I go fishing’ (5). 2 Measured on a 100-point scale representing likelihood of AIS spread from 0–100%. 3 Measured on a 5-point scale from ‘no impacts’ (1) to ‘very severe impacts’ (5). 4 Measured on a 5-point scale from ‘strongly disagree’ (1) to ‘strongly agree’ (1). 5 Measured on a 5-point scale from ‘not at all familiar’ (1) to ‘extremely familiar’ (1). Analysis Data were mapped in ArcMap 10.8.1 using zip codes for respondent location and coordinates for AIS location. The near analysis function was used to determine Euclidean distance between each respondent and the nearest invasive species in kilometers (km). Euclidean distance is often used in spatial analyses to determine straight-line distance from one object to another (Brown et al. 2002 ). Distance analyses were performed for the whole AIS database as well as for each taxon: plants, crustaceans, fishes, and mollusks. To understand relationships among distance, risk, efficacy, familiarity, and intended behavior, a path model was estimated in R version 3.6.1 (R Core Team 2020 ) using lavaan and semTools packages. Mean values scores for perceived risk severity, perceived risk susceptibility, self-efficacy, familiarity, and intended behavior were used, as well as the calculated Euclidean straight-line distance described above. Although the three dimensions of familiarity and risk were modeled, we combined the three dimensions in the path model to ensure parsimony in our analysis and examine broader trends in our data. Model fit was assessed using a chi-square test of significance, root mean square error approximation (RMSEA), comparative fit index (CFI), the Tucker-Lewis index (TLI) and standardized root mean square residual (SRMR) (Kline 2011 ). Results Perceived risk susceptibility was moderately high with a mean of 58.27 ( SD = 22.22). Perceived risk severity and intended behavior were moderate with means of 3.41 ( SD = 0.79) and 3.99 ( SD = 1.00) respectively. Self-efficacy was high ( M = 4.15; SD = 0.74), and familiarity with AIS was moderately low ( M = 2.67; SD = 1.09). The mean distance of survey respondents (N = 446) to an invasive species record was 3.59 km ( SD = 3.18) with a range from 0.195 km to 29.592 km (Fig. 4 ). The mean distance to AIS varied among taxa; mean distances to invasive mollusk and fish species were the shortest, at 5.57 km ( SD = 5.424 and 8.92 km ( SD = 8.242) respectively. Distance to invasive plant species was moderately higher ( M = 11.1 km, SD = 5.424), and distance to invasive crustacean species was the largest with a mean of 34.12 kilometers ( SD = 54.501). Our path model demonstrated good fit (χ 2 = 21.321, df = 9, p = 0.011; CFI = 0.963; TLI = 0.893; RMSEA = 0.055; SRMR = 0.028) (Fig. 5 ). Recreational water user distance from invasive species was negatively associated with perceived susceptibility ( β = -0.153, p = 0.006) (Table 3 ). Familiarity positively predicted perceived severity ( β = 0.398, p < 0.001), susceptibility ( β = 0.231, p < 0.001), and self-efficacy ( β = 0.215, p < 0.001). This combination of variables explained 27% of the variance in intended behavior. Specifically, severity ( β = 0.136, p = 0.002), susceptibility ( β = 0.075, p = 0.082), and self-efficacy ( β = 0.436, p < 0.001) were positively correlated with the intended activities among recreational boaters. Table 3 Results from a path model, including standardized regression coefficients (β) and standard error (SE) Dependent variable Independent variable β SE R 2 Intended Behavior 0.270 Risk severity 0.136*** 0.057 Risk susceptibility 0.075* 0.002 Self-efficacy 0.436*** 0.058 Self-efficacy 0.046 Familiarity 0.215*** 0.031 Risk Severity 0.160 Distance from fish -0.005 0.005 Distance from mollusks -0.030 0.007 Distance from crustaceans -0.009 0.001 Distance from plants 0.032 0.005 Familiarity 0.398*** 0.032 Risk susceptibility 0.076 Distance from fish -0.153*** 0.152 Distance from mollusks -0.006 0.203 Distance from crustaceans 0.071 0.021 Distance from plants 0.074 0.158 Familiarity 0.231*** 0.943 *, **, *** indicate significance at the 90%, 95%, and 99% level, respectively. Discussion Human behavior is instrumental in the unintentional spread of aquatic invasive species (AIS), yet there remains limited knowledge of how the combination of social and ecological factors motivate behavior to minimize the likelihood of biological invasions. Empirical evidence of how people perceive and act in relation to AIS is urgently needed to develop more effective management strategies that rely in part on changing human behavior to protect freshwater ecosystems. This study generated new knowledge of the relationships among the proximity of people to established AIS populations, risk perceptions, familiarity, self-efficacy, and intended behavior. We observed that invasive fishes were the only taxa in our study that correlated with perceived risk susceptibility. Furthermore, as risk severity, risk susceptibility, and self-efficacy increased, boaters’ intentions to take action increased, regardless of distance from AIS. This is one of the first studies to harness social-ecological data in an effort to prioritize which management actions are needed. Our model revealed that people who live closer to invasive fish species are more likely to believe that there is a risk that AIS will invade their waterbody. Similarly, proximity has led to increased levels of awareness, which can influence how people perceive environmental quality (Brody et al. 2004 ; van Riper et al. 2017 ). This relationship likely indicates that the boaters engaged in our study were most attuned to invasive fish species, relative to other taxa. We contend that fish can function as a flagship taxon given their visibility and a possible predisposition among recreational anglers to recognize invasions from fish, and in turn, feel compelled to support prevention and mitigation strategies. We suggest resource management agencies should keep in mind boaters’ heightened risk perceptions near established populations of invasive fishes and work within spatially distributed social networks to communicate about AIS (Davis et al. 2018 ). Utilizing these networks can quickly disseminate risk-related information to boaters who live far from observed AIS. Furthermore, recreational boaters who do not live near AIS are at risk of transporting aquatic invaders when they travel between waterbodies (Cole et al. 2019 ), thus still requiring management attention despite not residing near invaded waterbodies. Perceived risk and respondent distance from invasive mollusks, crustaceans, or plants were not correlated in our study, in that people who lived closer to these taxa did not have elevated risk perceptions. This may indicate that people are less familiar with invasive mollusks, crustaceans, and plants, as opposed to fish species. Corroborating our findings, recreational boaters in Illinois have indicated that the majority of survey respondents can correctly identify Asian carp ( Hypophthalmichthys molitrix, Mylopharyngodon piceus, Hypophthalmichthys nobilis, Ctenopharyngodon idella ) as invasive, but fewer are able to accurately identify hydrilla ( Hydrilla verticillata ), spiny water flea ( Bythotrephes longimanus ), or rusty crayfish ( Faxonius rusticus ) as invasive (Golebie et al. 2021 ). In addition, invasive fish species were one of the most recognizable AIS taxa and some of the first aquatic invasive species to enter Lake Michigan (Kemp et al. 2017 ). Fishes are an historically important example of AIS in Illinois, which has likely contributed to people being more familiar with these taxa and therefore, more likely to believe they pose a risk. As predicted, familiarity with AIS positively influenced risk perceptions and self-efficacy. Familiarity was most strongly correlated with risk susceptibility, alongside weaker correlations to self-efficacy and risk perceptions. These results emphasize the importance of raising general awareness of the threats posed by AIS to recreational boaters. The more boaters are informed about the recreational, ecological, and management implications of AIS, the more severe they view the associated risks and the more confident they are to carry out AIS preventative behaviors. Results in our study thus extend previous research that has demonstrated the strength of the relationship between familiarity with AIS and intended behavior as well as the importance of familiarity in increasing self-efficacy among boaters (Morris et al. 2007 ; Van Dinther et al. 2011 ). Given that environmental communication and outreach strategies are most effective when emphasizing the practical steps that are needed to perform simple mitigative behaviors (e.g., recycling, sustainable seafood consumption) (McKenzie-Mohr and Schultz 2014 ), we suggest that discrete actions be highlighted by agencies rather than focusing on the importance or consequences of performing those behaviors. Our study revealed that self-efficacy had a positive influence on behavioral intentions to minimize the spread of AIS. Specifically, self-efficacy was the strongest of the three exogenous predictor variables. This relationship indicates that the most important factor in driving boaters to take action is confidence in performing preventative behaviors. Likewise, self-efficacy has been shown to be a powerful correlate of behavior in psychology (Vancouver et al. 2008 ), specifically involving water-based recreationists (Howell et al. 2015 ). When considering how managers should focus outreach efforts, increasing self-efficacy among boaters should be a high priority. If boaters are knowledgeable on how to perform preventative behaviors, they will be more likely to engage in these behaviors, even if they do not believe AIS are a great threat or are likely to spread to their local waterways. We found that risk severity and risk susceptibility led to higher intended behaviors among boaters, with risk severity resulting in a higher impact on intended behavior relative to risk susceptibility. The relevance of risk as a predictor of behavior aligns with past work guided by Protection Motivation Theory (Rogers 1975 ; Mongeau 2013 ) as well as research indicating boaters with higher risk perceptions are more likely to try to prevent AIS spread (Golebie et al. 2021 ). While we did not distinguish between different types of AIS risks in this study, the connection between distance from invasive fish and risk perceptions indicates that people may be better able to understand the risk of AIS to themselves given exposure to these species at a local level. Therefore, we contend that risk perceptions contribute to a boater’s likelihood of performing preventative behaviors and could be used by managers to increase execution of these behaviors. Management Implications Our results can be used to facilitate data driven recommendations for management agencies that are responsible for mitigating biological invasions. The campaigns currently used by managers are important to minimize the spread of AIS but can be modified in response to our findings. First, it is important to prioritize the inclusion of boaters that live far from invaded areas. Remote areas currently receive less attention when it comes to AIS outreach, however these recreationists are known to travel long distances for recreation (Cole et al. 2019 ) meaning they are at high risk of AIS transport. Additionally, these boaters are less likely to perceive AIS as a risk, further emphasizing the importance of disseminating outreach to this group. Second, distance from invasive fishes is a significant predictor of risk perceptions. This finding indicates that prevention campaigns focusing on fish species such as Asian carp ( H. molitrix, M. piceus, H. nobilis, C. idella ) and other fishes could be important in the prevention of the transportation of those species and could be used to raise awareness of less well-known AIS taxa (i.e., plants, mollusks, crustaceans). Third, self-efficacy was the strongest predictor of intended behavior, highlighting the need to provide instructions on how to perform AIS preventative behaviors and instill a sense of confidence among boaters. Trainings can be given at water-based recreation sites to show boaters how to perform AIS preventative behaviors such as clean, drain, dry. Even if boaters are informed about AIS and their dangers, if they do not know how to properly perform preventative behaviors or are not confident in their ability to do so, they will not likely engage in these behaviors. Limitations and future research Throughout our study, we faced several limitations that can aid in the expansion of future research. First, it is important to understand that the intended behaviors reported by respondents may not be the same as the actions they execute (Baumeister et al. 2007 ). For example, if someone reports that they drain all standing water from their boat, but, in practice, water remains, AIS transport could occur. Second, the spatial resolution of our analyses needs to be considered when interpreting the study results because boater location was at the zip code extent. With a more precise location like home address, coupled with data on where a boater typically travels to recreate, driving distance could replace straight-line Euclidean distance, which would provide a better representation of the functional distance between AIS populations and recreationists (Brody et al. 2004 ). Finally, we relied on zip codes reflecting home addresses rather than known recreational locations where boaters were accessing waterways. Spatial information on recreation site would allow for a better understanding of the AIS that people interacted with during their outings. Future studies on this topic could benefit from tools such as participatory mapping or GPS tracking (e.g., Chang et al. 2023) to understand travel patterns in relation to place-based preferences, as a way to gain more spatially explicit information on the effects of exposure to biological invasions. Conclusions Aquatic invasive species pose major threats to the biotic integrity of freshwater resources across the globe, especially in the Midwestern US where there is an abundance of human activities that span freshwater ecosystems. An increasing number of environmental social science studies involving recreational boaters in this context provides a fruitful basis for understanding how to shape behavior and most effectively mitigate environmental impacts. We extend this body of work by providing resource management agencies with new insights on the drivers of human behavior that may influence the spread of AIS. The spatial dynamics of recreation activities in relation to ecological conditions not only support the theoretical development of behavioral antecedents but also enable agencies to target recreationists in high and low priority areas that support fishing experiences. Declarations Funding for this study was provided by the USDA National Institute of Food and Agriculture Hatch program (accession #: 7000939), Illinois Department of Natural Resources (Grant number F69R36Q3), and the Great Lakes Restoration Initiative, US Fish and Wildlife Service, Illinois Department of Natural Resources (Grant number CAFWS-144A). Thanks are extended to the individuals who shared their experiences and knowledge in support of this research process. The authors have no relevant financial or non-financial interests to disclose. Theory development, data collection and analysis were all performed by Alison Moore and Danika Ford with input from Elizabeth Golebie, and North Joffe-Nelson. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-2869687","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":217443810,"identity":"aae7e174-810e-4681-940f-dc015e9928a8","order_by":0,"name":"Alison Moore","email":"","orcid":"","institution":"University of Illinois at Urbana-Champaign","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Alison","middleName":"","lastName":"Moore","suffix":""},{"id":217443811,"identity":"2cc87442-22ab-4c98-b038-ecc3cec9631d","order_by":1,"name":"Danika Ford","email":"","orcid":"","institution":"University of Illinois at Urbana-Champaign","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Danika","middleName":"","lastName":"Ford","suffix":""},{"id":217443812,"identity":"f84234c7-c9c6-4393-9e13-122bdbf19e35","order_by":2,"name":"Elizabeth Golebie","email":"","orcid":"","institution":"University of Illinois at Urbana-Champaign","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Elizabeth","middleName":"","lastName":"Golebie","suffix":""},{"id":217443813,"identity":"fc00bf34-f6a1-4577-bcb3-2f4da4de0b9f","order_by":3,"name":"North Joffe-Nelson","email":"","orcid":"","institution":"University of Illinois at Urbana-Champaign","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"North","middleName":"","lastName":"Joffe-Nelson","suffix":""},{"id":217443814,"identity":"b876ba39-c6f0-4615-843c-d904482fd92a","order_by":4,"name":"Greg Hitzroth","email":"","orcid":"","institution":"Illinois-Indiana Sea Grant","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Greg","middleName":"","lastName":"Hitzroth","suffix":""},{"id":217443815,"identity":"b737e310-d92b-43a5-b144-58bd6acdfa21","order_by":5,"name":"Amanda Huegelmann","email":"","orcid":"","institution":"Boy Scouts of America","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Amanda","middleName":"","lastName":"Huegelmann","suffix":""},{"id":217443816,"identity":"a7a6f1ee-5611-46fd-9d03-99e387c08d1f","order_by":6,"name":"Sarah King","email":"","orcid":"","institution":"University of Illinois at Urbana-Champaign","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Sarah","middleName":"","lastName":"King","suffix":""},{"id":217443817,"identity":"170d1686-4611-45c7-95c8-771637108909","order_by":7,"name":"Jeffrey Stein","email":"","orcid":"","institution":"University of Illinois at Urbana-Champaign","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jeffrey","middleName":"","lastName":"Stein","suffix":""},{"id":217443818,"identity":"f1c71c6a-1416-40c7-857a-285e0dd0a887","order_by":8,"name":"Carena Joleen van Riper","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3klEQVRIiWNgGAWjYNACAwYGfmbmxgMJDAw8IL4EUVokmxkbSNEC0nUAqAXGwauFf0bys8cVBXfkjI8DtTzcYSMj38B88DYPHi0SN9LMDc8YPDM2OwzUkngmjcfgAFuyNT4tBjwHzCQbDA4nbgNraTvMY8DAYyaNX8vxbyAt9ZuboVrkG/i/4dfC3gO2JcGAGaqF4QAPG14tEsd7yoBanhnOgDgM6JfDbMaWc/Bo4W9m3ybZ8OeOPH//4YMPf7bZ2Mu3Nz+88QaPFig4gMRmJqwcXcsoGAWjYBSMAjQAAMsmTGwHzDSsAAAAAElFTkSuQmCC","orcid":"https://orcid.org/0000-0002-6200-8855","institution":"University of Illinois at Urbana-Champaign","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"Carena","middleName":"Joleen van","lastName":"Riper","suffix":""}],"badges":[],"createdAt":"2023-04-27 16:53:34","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-2869687/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-2869687/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s10530-024-03287-5","type":"published","date":"2024-03-24T15:00:58+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":40039763,"identity":"5f0e7ee3-53f3-4881-ab3c-63ebe46ded9b","added_by":"auto","created_at":"2023-07-14 14:55:34","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":96212,"visible":true,"origin":"","legend":"\u003cp\u003eHypothesized model showing predicted relationships between respondents’ distance to invasive species, perceived risk, efficacy, familiarity, and intended behavior. Plus (+) and minus (-) signs indicate positive and negative relationships, respectively.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-2869687/v1/7a957b42d01a0a1d5a2a9c8e.png"},{"id":40039764,"identity":"3dfcc970-eb83-48cf-920e-bbd9ee34bf45","added_by":"auto","created_at":"2023-07-14 14:55:34","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":37004,"visible":true,"origin":"","legend":"\u003cp\u003eRecorded points of aquatic invasive species observed over the past 25 years across the state of Illinois. Data retrieved from the United States Geological Survey Nonindigenous Aquatic Species (NAS) Database.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-2869687/v1/659b0a3c672226e91b982195.png"},{"id":40039762,"identity":"63fa3f3c-5572-4c0e-9b72-788a4946fd04","added_by":"auto","created_at":"2023-07-14 14:55:34","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":29308,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cem\u003eBeliefs about the risks posed by aquatic invasive species among boaters in the state of Illinois. Each point represents the residence of a respondent; shading indicates degree of risk that was perceived.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-2869687/v1/1a4db2b4c90058981d4b2d92.png"},{"id":40039766,"identity":"23cfb8c9-e8fe-44fd-82bf-1b5fe6418ff8","added_by":"auto","created_at":"2023-07-14 14:55:34","extension":"jpeg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":162837,"visible":true,"origin":"","legend":"\u003cp\u003eHistograms representing distances of recreationists from a) Aquatic Invasive Species (AIS), b) plants, c) crustaceans, d) fishes, and e) mollusks.\u003c/p\u003e","description":"","filename":"floatimage4.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-2869687/v1/3b9f472e191c0f97e8341b62.jpeg"},{"id":40039765,"identity":"6c655eda-02b3-4214-b818-0842723c9402","added_by":"auto","created_at":"2023-07-14 14:55:34","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":138191,"visible":true,"origin":"","legend":"\u003cp\u003eRelationships among proximity to aquatic invasive species across four taxa, familiarity, perceived risk severity, self-efficacy, and risk susceptibility, and intended behavior to prevent the spread of aquatic invasive species among recreational boaters in Illinois (N = 446). Standardized path coefficients (β) are denoted by solid lines whereas nonsignificant paths are denoted as dashed lines.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-2869687/v1/5314d95221905dfb6f6d56cc.png"},{"id":53403840,"identity":"f6ace98c-6322-453d-91be-7c37ca53daca","added_by":"auto","created_at":"2024-03-25 15:14:53","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":641158,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-2869687/v1/4cb49b19-afae-4eca-a2cc-79ca0fd8d7b0.pdf"}],"financialInterests":"","formattedTitle":"Social and Ecological Drivers of Behavior that Prevents Aquatic Invasive Species Transport","fulltext":[{"header":"Introduction","content":"\u003cp\u003e Aquatic invasive species (AIS) are increasingly changing the face of ecosystems and responsible for losses to biodiversity, changes to water quality, and impediments to human recreation (Gallardo et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). The impacts of AIS in the Great Lakes region alone exceed \u003cspan\u003e$\u003c/span\u003e100\u0026nbsp;million USD on an annual basis (Rosaen et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). As recreational boaters move between water bodies, they have the potential to unintentionally transport AIS that are attached to boats or are present within livewells or bilge water (Ready et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Given the difficulties of remediating an ecosystem that has been degraded by AIS due to the persistence of (re)introduction vectors, preventative measures are fundamentally important in aquatic ecosystem management (Vander Zanden and Olden \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2008\u003c/span\u003e). Numerous outreach campaigns have consequently been developed by state and federal agencies to encourage boaters and anglers to clean, drain, and dry their boats, trailers, and fishing gear before travelling between waterbodies (Seekamp et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Golebie and van Riper \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). In support of these outreach campaigns, management agencies have installed wash stations at boat ramps (Cimino and Strecker \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) and implemented watercraft inspection programs to detect aquatic invaders on recreational watercraft and prevent their spread (Nathan et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Awareness and detection interventions are becoming more widely adopted (Sharp et al. \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Kemp et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Cole et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), but limited financial resources prevent their implementation at every recreational facility (Beaury et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Given funding constraints, there is a strong need for managers to prioritize the physical locations at highest risk due to both social and ecological factors.\u003c/p\u003e \u003cp\u003eA large body of research has focused on understanding the ecology of AIS (e.g., Morisette et al. \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Gallardo and Aldridge \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2018\u003c/span\u003e), whereas less attention has been directed to understanding recreationists (e.g., boaters, anglers) and developing behavior change strategies that target these audiences (Witzling et al. \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Nanayakkara et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Cole et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Even less research focus has been given to interdisciplinary approaches that explore how the combination of social and ecological factors affects the spread of AIS (Golebie et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Integrating knowledge from multiple disciplines creates opportunities to provide more holistic guidance for fisheries management agencies (Arlinghaus et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Hunt et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) and can improve spatial planning to prevent the spread of AIS (Rothlisberger et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Ban et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). For example, previous research has indicated that distance to water (van Riper et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) and coastlines (Johnson et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) account for large degrees of variation in how water-based recreationists value their environments. Indeed, proximity to environmental features has shown promise in its ability to explain how people perceive their environments (Brody et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Wilkins et al. \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). However, previous research has yet to empirically estimate how proximity corresponds to the reported or intended behaviors of water-based recreationists that are at risk of spreading AIS.\u003c/p\u003e \u003cdiv id=\"Sec2\" class=\"Section2\"\u003e \u003ch2\u003ePsychological drivers of behavior\u003c/h2\u003e \u003cp\u003eTo better understand boater engagement in AIS prevention behavior, psychological theories such as Protection Motivation Theory (Rogers \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e1975\u003c/span\u003e) can be used to guide research. According to Protection Motivation Theory, an individual\u0026rsquo;s response to potential threats such as biological invasions is rooted in two key factors: 1) risk perceptions - their perceptions of the riskiness of that threat and 2) self-efficacy - the individual\u0026rsquo;s ability to take action that mitigates the threat. Individuals must believe the threat is severe and that they are capable of mitigating the threat before choosing to act. If self-efficacy is low, individuals may reject the severity of the threat itself to avoid negative feelings of helplessness (Maddux and Rogers \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e1983\u003c/span\u003e). A substantial body of research informed by Protection Motivation Theory has provided support for the relationships among risk, efficacy, and behavior (Mongeau \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), including multiple conservation-related behaviors (Kothe et al. \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; O\u0026rsquo;Connor et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e1999\u003c/span\u003e). One study indicated self-efficacy and risk perceptions determined behaviors (e.g., removal of invasive plants) associated with terrestrial invasive species (Clarke et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Despite this robust body of work, few studies have examined possible predictors of risk and efficacy, such as familiarity. Knowledge of the antecedent that gives rise to risk and efficacy can provide insights on how to form appropriate management strategies to minimize behaviors that threaten aquatic ecosystems.\u003c/p\u003e \u003cp\u003eRisk perceptions encompass both the perceived susceptibility and severity to harm caused by a particular hazard. In accordance with Protection Motivation Theory (Rogers \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e1975\u003c/span\u003e), the Health Belief Model (Rosenstock \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e1974\u003c/span\u003e), and the Global Risks Report (World Economic Forum \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2022\u003c/span\u003e), there is indeed robust evidence that susceptibility and severity are essential to understand and measure risk perceptions (Akerlof et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Smith and Leiserowtiz 2012). However, studies of risk perceptions in AIS prevention (e.g., Golebie et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; Estevez et al. 2015) have been limited to the consideration of risk severity, while the dimension of susceptibility has been largely ignored, thus creating a significant knowledge gap in this body of work. Furthermore, previous research has indicated that physical risks such as zoonotic viruses and injuries caused by moving AIS (Conn 2013; Kahler et al. 2019) are instrumental in accounting for variation in risk perceptions when risk reduction strategies are not employed (Adam \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Despite this knowledge, environmental social science research has predominantly focused on understanding how the severity of risks are perceived for individuals and groups e.g., (van Riper et al. \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) rather than accounting for the social-ecological relationships that give rise to how people interpret their environments.\u003c/p\u003e \u003cp\u003eThe confidence of individuals to perform a behavior (i.e., self-efficacy) has emerged as a strong driver of behavior in past research (Bandura \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1977\u003c/span\u003e). If people do not feel confident in their ability to perform a task, even if they have made it a personal goal, they are much less likely to follow through and perform a desired behavior. Past work has suggested that self-efficacy is a stronger predictor of health-related behavior than risk perceptions (Ferrer and Klein \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Similarly in the context of AIS, having high self-efficacy gives people the confidence needed to complete preventative behaviors such as \u003cem\u003eClean, Drain, and Dry.\u003c/em\u003e For example, one study of bait shop owners\u0026rsquo; engagement in AIS outreach demonstrated that self-efficacy was the most important factor in determining whether the owners talked about AIS with their customers (Howell et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Self-efficacy is therefore likely to be a key factor in predicting boater behaviors that can help to mitigate the spread of AIS.\u003c/p\u003e \u003cp\u003eEnvironmental social science research on biological invasions has yet to identify the full suite of drivers of risk perceptions and self-efficacy despite the insights that could be provided on how to craft successful outreach messages. One factor that may be relevant in determining the perceived risks of AIS is familiarity. This idea encompasses awareness of impacts incurred on aquatic ecosystems (van Riper and Kyle \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), how water users can prevent the spread of AIS (Gates et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2009\u003c/span\u003e), and the way in which AIS issues are managed by relevant authorities (Simberloff \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Familiarity with AIS tends to be higher for those who are more active in water-based recreation activities due to more hands-on exposure to AIS and more frequent interactions with other recreationists (Seekamp et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Heightened familiarity has been shown to increase perceived risk severity and self-efficacy among boaters (Rogers \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e1975\u003c/span\u003e), thus indicated a higher likelihood of engagement in preventative behaviors.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eEcological drivers of behavior\u003c/h2\u003e \u003cp\u003eAn expansive body of previous research has investigated the relationships among ecological and environmental factors and risk perceptions. The study context has played an important role in determining how risk perceptions are related to the strength of connections that form between people and places (Bonaiuto et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2016\u003c/span\u003e), including both positive (Xu et al. \u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) and negative relationships (Mishra et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Bird et al \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Proximity between people and objects of interest has also emerged as a helpful explanation for why and how environments are perceived. For example, a negative association was found between the distance that participants lived from creeks in San Antonio Watersheds and their awareness of the environmental risks threatening that context (Brody et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Further, the actual risk of an environment such as flooding has been shown to affect behavior (Stancu et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2020\u003c/span\u003e); however, there is limited research considering both \u0026lsquo;actual risk\u0026rsquo; or ecological context of AIS alongside risk perceptions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStudy Purpose and Objectives\u003c/h2\u003e \u003cp\u003eWith limited resources, environmental managers are challenged to prioritize investments such as wash station infrastructure and communication campaigns in areas that are at greatest risk for degradation. Research is therefore needed to generate spatially explicit representations of where AIS are located and the factors affecting their spread. Thus, this study was guided by three objectives: 1) understand the ecological presence of AIS in relation to boater risk perceptions, 2) examine the relationships between proximity to AIS and perceived risks of biological invasions, and 3) determine how proximity to AIS works in conjunction with perceived risk, familiarity, and self-efficacy to influence the intended behaviors of boaters. We hypothesized that those in closest proximity to AIS will perceive greater risks than those who are farther away, and that familiarity will also play a role in positively predicting risk perceptions. We also hypothesized that both heightened risk perceptions and self-efficacy would lead to more AIS-preventative behaviors, in line with Protection Motivation Theory. These hypotheses were tested through 14 predictions depicted in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eEcological data procedures\u003c/h2\u003e \u003cp\u003eData on AIS presence were retrieved from the United States Geological Survey (USGS) Nonindigenous Aquatic Species (NAS) Database. The database was cleaned to include only established populations throughout the state of Illinois for the years 1997\u0026ndash;2021 for further analysis. Established populations were defined as those which successfully reproduced and overwintered according to the USGS NAS. The final database included 14,828 records of invasive species divided into four taxa: plants, crustaceans, fishes, and mollusks (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). All of these data were utilized to identify the locations of organisms across the four taxa. As of 2016, 60 non-native aquatic species (or AIS) were considered established in Illinois waterbodies with an additional 39 species having their presence recorded though not yet established (Jacobs and Keller 2016).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eSurvey data procedures\u003c/h2\u003e \u003cp\u003eSocial science data were obtained using an online survey conducted from May-June 2021. Survey respondents were drawn from a Qualtrics panel and deemed eligible to participate in the study if they lived in the state of Illinois and had reported fishing or engaging in a recreational water activity (i.e., sailing, kayaking, canoeing, boating, jet skiing, etc.) at least once since 2018. A total of 507 individuals completed the survey. Because we wanted to understand AIS prevention behavior completed on boats (i.e., clean-drain-dry), we excluded 54 individuals who only engaged in shoreline angling and did not use boats or other watercraft as well as 7 individuals who had incomplete surveys, resulting in a total of 446 individuals who were analyzed in this study. Respondents were dispersed across 60 of the 102 counties in the state of Illinois. Respondents were on average 44.2 years old, and more than half were female (59%) (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Additionally, respondents reported a mean of 13 days boating per year and 20.8 years of experience. This study was approved under protocol #20679 by the Office for the Protection of Research Subjects at [identity withheld for blind peer-review].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eDemographics and boating experience of survey respondents.\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTotal Sample\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge [M (SD)]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44.20 (17.49)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGender\u0026nbsp;[N (%)]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e252 (59.6)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e171 (40.4)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOther\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal days boating/year [M (SD)]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12.51 (20.97)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTotal years of experience\u0026nbsp;[M (SD)]\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20.80 (18.77)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eRespondents were asked to report their perceived risks of AIS, self-efficacy related to AIS prevention, familiarity with AIS, and intended behavior to prevent AIS transport (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). Two types of perceived risk were measured (Rogers \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e1975\u003c/span\u003e). First, risk susceptibility, defined as the perceived likelihood of species invasions, was assessed using two questions on a scale from 0%-100%. Given the importance of timescales in risk perceptions (Akerlof et al. \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Smith and Leiserowtiz 2012), respondents were asked to report the percent chance of species invasions occurring on two different timescales: within the next year and within the next 10 years. Second, risk severity, defined as the intensity of impacts caused by AIS, was assessed using nine items, three for each dimension including personal, environmental, and social risk. Self-efficacy was measured using a three-item scale (Bandura \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e1977\u003c/span\u003e) and was adapted to the context of AIS management. Three dimensions of familiarity were assessed, using three items for each dimension, including familiarity with invasion biology, relationships between recreation and AIS, and AIS management. Intended behavior was measured using a six-item scale (Pradanhanga et al. 2015) that was modified to resemble the goals of Illinois-Indiana Sea Grant and Illinois Natural History Survey\u0026rsquo;s Be A Hero \u0026ndash; Transport Zero program (\u0026ldquo;Be a Hero!\u0026rdquo; 2021, TransportZero.org). These items were measured on a 5-point Likert scale ranging from \u0026lsquo;never\u0026rsquo; (1) to \u0026lsquo;every time I go boating\u0026rsquo; (5). We tested the validity and reliability of the risk, efficacy, familiarity, and behavior scales using factor loading scores (scores above 0.40 accepted; Hair et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), Cronbach\u0026rsquo;s alpha (coefficients above 0.60 were accepted; Cortina \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e1993\u003c/span\u003e) and MacDonald\u0026rsquo;s Omega (coefficients above 0.60 were accepted; Bagozzi and Yi \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e1988\u003c/span\u003e). All items and scales met acceptable thresholds and were included in further analysis.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003e\u003cem\u003eFactor loading scores, means, and standard deviations for survey items evaluated by survey respondents.\u003c/em\u003e\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFactor loading\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eM (SD)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntended behavior\u003csup\u003e1\u003c/sup\u003e (α\u0026thinsp;=\u0026thinsp;0.901; Ω\u0026thinsp;=\u0026thinsp;0.902; AVE\u0026thinsp;=\u0026thinsp;0.605)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e3.99 (1.00)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDrain all standing water from the boat\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.747\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.10 (1.22)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eConduct visual inspections of boats for invasive species\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.770\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.90 (1.28)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRemove plants, animals, and mud from boat\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.834\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.18 (1.13)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRinse boat and trailer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.777\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.98 (1.19)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWipe down hull with a towel\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.762\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.77 (1.28)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAllow boat to dry before entering a different body of water\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.784\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.99 (1.25)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePerceived risk susceptibility\u003csup\u003e2\u003c/sup\u003e (Spearman-Brown Coefficient\u0026thinsp;=\u0026thinsp;0.836)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e58.27 (22.22)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHow likely is it that invasive species will spread to your waterbody within the next year?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e1.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e52.02 (23.77)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHow likely is it that invasive species will spread to your waterbody within the next ten years?\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.707\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e64.52 (24.27)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePerceived risk severity\u003csup\u003e3\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e3.41 (0.79)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eEnvironment\u003c/em\u003e (α\u0026thinsp;=\u0026thinsp;0.823; Ω\u0026thinsp;=\u0026thinsp;0.824; AVE\u0026thinsp;=\u0026thinsp;0.611))\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQuality of habitat and natural environments\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.815\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.51 (0.90)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnvironmental processes (e.g., water cycle)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.798\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.45 (0.95)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSurvival of plants and animals\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.729\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.71 (0.91)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003ePersonal\u003c/em\u003e (α\u0026thinsp;=\u0026thinsp;0.815; Ω\u0026thinsp;=\u0026thinsp;0.816; AVE\u0026thinsp;=\u0026thinsp;0.598)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYour appreciation of the beauty of the landscape\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.743\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.33 (1.10)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYour own enjoyment of recreational activities\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.764\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.40 (1.07)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eyour own access to the waterbody\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.807\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.24 (1.16)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eSocial\u003c/em\u003e (α\u0026thinsp;=\u0026thinsp;0.841; Ω\u0026thinsp;=\u0026thinsp;0.860; AVE\u0026thinsp;=\u0026thinsp;0.677)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe local economy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.858\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.17 (1.12)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe community in the region\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.897\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.16 (1.13)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRecreational opportunities for future generations\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.672\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.68 (1.02)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelf-efficacy\u003csup\u003e4\u003c/sup\u003e (α\u0026thinsp;=\u0026thinsp;0.864; Ω\u0026thinsp;=\u0026thinsp;0.864; AVE\u0026thinsp;=\u0026thinsp;0.680)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e4.15 (0.74)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI understand what I need to do in order to remove AIS from my boat or equipment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.821\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.14 (0.85)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI am capable of performing the tasks required to remove possible AIS from my boat and equipment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.831\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.21 (0.83)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eI feel confident in performing procedures necessary to prevent AIS from spreading\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.822\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e4.09 (0.82)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFamiliarity\u003csup\u003e5\u003c/sup\u003e\u003c/p\u003e \u003cp\u003e\u003cem\u003eInvasion biology (α\u0026thinsp;=\u0026thinsp;0.886; Ω\u0026thinsp;=\u0026thinsp;0.887; AVE\u0026thinsp;=\u0026thinsp;0.723)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e\u003cb\u003e2.67 (1.09)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe biological characteristics that make a species \u0026ldquo;invasive\u0026rdquo;\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.858\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.85 (1.26)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNames of species that are considered invasive\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.844\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.58 (1.19)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWays that invasive species affect the environment\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.849\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e3.01 (1.25)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eRelationship between invasive species and recreation (α\u0026thinsp;=\u0026thinsp;0.914; Ω\u0026thinsp;=\u0026thinsp;0.914; AVE\u0026thinsp;=\u0026thinsp;0.780)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHow boaters and anglers can spread invasive species\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.839\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.82 (1.34)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTypes of actions you can take to prevent invasive species from spreading\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.906\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.69 (1.28)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHow to complete recommended preventative actions\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.905\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.58 (1.35)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cem\u003eInvasive species management (α\u0026thinsp;=\u0026thinsp;0.921; Ω\u0026thinsp;=\u0026thinsp;0.923; AVE\u0026thinsp;=\u0026thinsp;0.799)\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAgencies that are responsible for managing invasive species\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.869\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.56 (1.25)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eManagement actions that reduce invasive species impacts\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.931\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.51 (1.29)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe current state of invasive species management at your most frequented waterbody\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e0.879\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2.45 (1.30)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"3\"\u003eNote: Model fit was acceptable χ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;868.663, df\u0026thinsp;=\u0026thinsp;341, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; CFI\u0026thinsp;=\u0026thinsp;0.942; TLI\u0026thinsp;=\u0026thinsp;0.931; RMSEA\u0026thinsp;=\u0026thinsp;0.059; SRMR\u0026thinsp;=\u0026thinsp;0.047\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003e \u003csup\u003e1\u003c/sup\u003eMeasured on a 5-point scale from \u0026lsquo;never\u0026rsquo; (1) to \u0026lsquo;every time I go fishing\u0026rsquo; (5).\u003c/p\u003e \u003cp\u003e \u003csup\u003e2\u003c/sup\u003eMeasured on a 100-point scale representing likelihood of AIS spread from 0\u0026ndash;100%.\u003c/p\u003e \u003cp\u003e \u003csup\u003e3\u003c/sup\u003eMeasured on a 5-point scale from \u0026lsquo;no impacts\u0026rsquo; (1) to \u0026lsquo;very severe impacts\u0026rsquo; (5).\u003c/p\u003e \u003cp\u003e \u003csup\u003e4\u003c/sup\u003eMeasured on a 5-point scale from \u0026lsquo;strongly disagree\u0026rsquo; (1) to \u0026lsquo;strongly agree\u0026rsquo; (1).\u003c/p\u003e \u003cp\u003e \u003csup\u003e5\u003c/sup\u003eMeasured on a 5-point scale from \u0026lsquo;not at all familiar\u0026rsquo; (1) to \u0026lsquo;extremely familiar\u0026rsquo; (1).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eAnalysis\u003c/h2\u003e \u003cp\u003eData were mapped in ArcMap 10.8.1 using zip codes for respondent location and coordinates for AIS location. The near analysis function was used to determine Euclidean distance between each respondent and the nearest invasive species in kilometers (km). Euclidean distance is often used in spatial analyses to determine straight-line distance from one object to another (Brown et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2002\u003c/span\u003e). Distance analyses were performed for the whole AIS database as well as for each taxon: plants, crustaceans, fishes, and mollusks.\u003c/p\u003e \u003cp\u003eTo understand relationships among distance, risk, efficacy, familiarity, and intended behavior, a path model was estimated in R version 3.6.1 (R Core Team \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2020\u003c/span\u003e) using lavaan and semTools packages. Mean values scores for perceived risk severity, perceived risk susceptibility, self-efficacy, familiarity, and intended behavior were used, as well as the calculated Euclidean straight-line distance described above. Although the three dimensions of familiarity and risk were modeled, we combined the three dimensions in the path model to ensure parsimony in our analysis and examine broader trends in our data. Model fit was assessed using a chi-square test of significance, root mean square error approximation (RMSEA), comparative fit index (CFI), the Tucker-Lewis index (TLI) and standardized root mean square residual (SRMR) (Kline \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2011\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003ePerceived risk susceptibility was moderately high with a mean of 58.27 (\u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;22.22). Perceived risk severity and intended behavior were moderate with means of 3.41 (\u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.79) and 3.99 (\u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.00) respectively. Self-efficacy was high (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;4.15; \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.74), and familiarity with AIS was moderately low (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;2.67; \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;1.09).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe mean distance of survey respondents (N\u0026thinsp;=\u0026thinsp;446) to an invasive species record was 3.59 km (\u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;3.18) with a range from 0.195 km to 29.592 km (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e). The mean distance to AIS varied among taxa; mean distances to invasive mollusk and fish species were the shortest, at 5.57 km (\u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5.424 and 8.92 km (\u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;8.242) respectively. Distance to invasive plant species was moderately higher (\u003cem\u003eM\u003c/em\u003e\u0026thinsp;=\u0026thinsp;11.1 km, \u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5.424), and distance to invasive crustacean species was the largest with a mean of 34.12 kilometers (\u003cem\u003eSD\u003c/em\u003e\u0026thinsp;=\u0026thinsp;54.501).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eOur path model demonstrated good fit (χ\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;21.321, df\u0026thinsp;=\u0026thinsp;9, p\u0026thinsp;=\u0026thinsp;0.011; CFI\u0026thinsp;=\u0026thinsp;0.963; TLI\u0026thinsp;=\u0026thinsp;0.893; RMSEA\u0026thinsp;=\u0026thinsp;0.055; SRMR\u0026thinsp;=\u0026thinsp;0.028) (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e). Recreational water user distance from invasive species was negatively associated with perceived susceptibility (\u003cem\u003eβ\u003c/em\u003e = -0.153, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006) (Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Familiarity positively predicted perceived severity (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.398, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), susceptibility (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.231, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), and self-efficacy (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.215, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). This combination of variables explained 27% of the variance in intended behavior. Specifically, severity (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.136, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002), susceptibility (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.075, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.082), and self-efficacy (\u003cem\u003eβ\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.436, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were positively correlated with the intended activities among recreational boaters.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eResults from a path model, including standardized regression coefficients (β) and standard error (SE)\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDependent variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIndependent variable\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eβ\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSE\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eIntended Behavior\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.270\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRisk severity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.136***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.057\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRisk susceptibility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.075*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSelf-efficacy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.436***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.058\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSelf-efficacy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.046\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFamiliarity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.215***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRisk Severity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.160\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDistance from fish\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDistance from mollusks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.030\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDistance from crustaceans\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.009\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDistance from plants\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.005\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFamiliarity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.398***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.032\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRisk susceptibility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.076\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDistance from fish\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.153***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.152\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDistance from mollusks\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e-0.006\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDistance from crustaceans\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.071\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eDistance from plants\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.074\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.158\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFamiliarity\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.231***\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.943\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e*, **, *** indicate significance at the 90%, 95%, and 99% level, respectively.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eHuman behavior is instrumental in the unintentional spread of aquatic invasive species (AIS), yet there remains limited knowledge of how the combination of social and ecological factors motivate behavior to minimize the likelihood of biological invasions. Empirical evidence of how people perceive and act in relation to AIS is urgently needed to develop more effective management strategies that rely in part on changing human behavior to protect freshwater ecosystems. This study generated new knowledge of the relationships among the proximity of people to established AIS populations, risk perceptions, familiarity, self-efficacy, and intended behavior. We observed that invasive fishes were the only taxa in our study that correlated with perceived risk susceptibility. Furthermore, as risk severity, risk susceptibility, and self-efficacy increased, boaters\u0026rsquo; intentions to take action increased, regardless of distance from AIS. This is one of the first studies to harness social-ecological data in an effort to prioritize which management actions are needed.\u003c/p\u003e \u003cp\u003eOur model revealed that people who live closer to invasive fish species are more likely to believe that there is a risk that AIS will invade their waterbody. Similarly, proximity has led to increased levels of awareness, which can influence how people perceive environmental quality (Brody et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; van Riper et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). This relationship likely indicates that the boaters engaged in our study were most attuned to invasive fish species, relative to other taxa. We contend that fish can function as a flagship taxon given their visibility and a possible predisposition among recreational anglers to recognize invasions from fish, and in turn, feel compelled to support prevention and mitigation strategies. We suggest resource management agencies should keep in mind boaters\u0026rsquo; heightened risk perceptions near established populations of invasive fishes and work within spatially distributed social networks to communicate about AIS (Davis et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Utilizing these networks can quickly disseminate risk-related information to boaters who live far from observed AIS. Furthermore, recreational boaters who do not live near AIS are at risk of transporting aquatic invaders when they travel between waterbodies (Cole et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), thus still requiring management attention despite not residing near invaded waterbodies.\u003c/p\u003e \u003cp\u003ePerceived risk and respondent distance from invasive mollusks, crustaceans, or plants were not correlated in our study, in that people who lived closer to these taxa did not have elevated risk perceptions. This may indicate that people are less familiar with invasive mollusks, crustaceans, and plants, as opposed to fish species. Corroborating our findings, recreational boaters in Illinois have indicated that the majority of survey respondents can correctly identify Asian carp (\u003cem\u003eHypophthalmichthys molitrix, Mylopharyngodon piceus, Hypophthalmichthys nobilis, Ctenopharyngodon idella\u003c/em\u003e) as invasive, but fewer are able to accurately identify hydrilla (\u003cem\u003eHydrilla verticillata\u003c/em\u003e), spiny water flea (\u003cem\u003eBythotrephes longimanus\u003c/em\u003e), or rusty crayfish (\u003cem\u003eFaxonius rusticus\u003c/em\u003e) as invasive (Golebie et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In addition, invasive fish species were one of the most recognizable AIS taxa and some of the first aquatic invasive species to enter Lake Michigan (Kemp et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). Fishes are an historically important example of AIS in Illinois, which has likely contributed to people being more familiar with these taxa and therefore, more likely to believe they pose a risk.\u003c/p\u003e \u003cp\u003eAs predicted, familiarity with AIS positively influenced risk perceptions and self-efficacy. Familiarity was most strongly correlated with risk susceptibility, alongside weaker correlations to self-efficacy and risk perceptions. These results emphasize the importance of raising general awareness of the threats posed by AIS to recreational boaters. The more boaters are informed about the recreational, ecological, and management implications of AIS, the more severe they view the associated risks and the more confident they are to carry out AIS preventative behaviors. Results in our study thus extend previous research that has demonstrated the strength of the relationship between familiarity with AIS and intended behavior as well as the importance of familiarity in increasing self-efficacy among boaters (Morris et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Van Dinther et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Given that environmental communication and outreach strategies are most effective when emphasizing the practical steps that are needed to perform simple mitigative behaviors (e.g., recycling, sustainable seafood consumption) (McKenzie-Mohr and Schultz \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), we suggest that discrete actions be highlighted by agencies rather than focusing on the importance or consequences of performing those behaviors.\u003c/p\u003e \u003cp\u003eOur study revealed that self-efficacy had a positive influence on behavioral intentions to minimize the spread of AIS. Specifically, self-efficacy was the strongest of the three exogenous predictor variables. This relationship indicates that the most important factor in driving boaters to take action is confidence in performing preventative behaviors. Likewise, self-efficacy has been shown to be a powerful correlate of behavior in psychology (Vancouver et al. \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2008\u003c/span\u003e), specifically involving water-based recreationists (Howell et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). When considering how managers should focus outreach efforts, increasing self-efficacy among boaters should be a high priority. If boaters are knowledgeable on how to perform preventative behaviors, they will be more likely to engage in these behaviors, even if they do not believe AIS are a great threat or are likely to spread to their local waterways.\u003c/p\u003e \u003cp\u003eWe found that risk severity and risk susceptibility led to higher intended behaviors among boaters, with risk severity resulting in a higher impact on intended behavior relative to risk susceptibility. The relevance of risk as a predictor of behavior aligns with past work guided by Protection Motivation Theory (Rogers \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e1975\u003c/span\u003e; Mongeau \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) as well as research indicating boaters with higher risk perceptions are more likely to try to prevent AIS spread (Golebie et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). While we did not distinguish between different types of AIS risks in this study, the connection between distance from invasive fish and risk perceptions indicates that people may be better able to understand the risk of AIS to themselves given exposure to these species at a local level. Therefore, we contend that risk perceptions contribute to a boater\u0026rsquo;s likelihood of performing preventative behaviors and could be used by managers to increase execution of these behaviors.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eManagement Implications\u003c/h2\u003e \u003cp\u003eOur results can be used to facilitate data driven recommendations for management agencies that are responsible for mitigating biological invasions. The campaigns currently used by managers are important to minimize the spread of AIS but can be modified in response to our findings. First, it is important to prioritize the inclusion of boaters that live far from invaded areas. Remote areas currently receive less attention when it comes to AIS outreach, however these recreationists are known to travel long distances for recreation (Cole et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) meaning they are at high risk of AIS transport. Additionally, these boaters are less likely to perceive AIS as a risk, further emphasizing the importance of disseminating outreach to this group. Second, distance from invasive fishes is a significant predictor of risk perceptions. This finding indicates that prevention campaigns focusing on fish species such as Asian carp (\u003cem\u003eH. molitrix, M. piceus, H. nobilis, C. idella\u003c/em\u003e) and other fishes could be important in the prevention of the transportation of those species and could be used to raise awareness of less well-known AIS taxa (i.e., plants, mollusks, crustaceans). Third, self-efficacy was the strongest predictor of intended behavior, highlighting the need to provide instructions on how to perform AIS preventative behaviors and instill a sense of confidence among boaters. Trainings can be given at water-based recreation sites to show boaters how to perform AIS preventative behaviors such as clean, drain, dry. Even if boaters are informed about AIS and their dangers, if they do not know how to properly perform preventative behaviors or are not confident in their ability to do so, they will not likely engage in these behaviors.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eLimitations and future research\u003c/h2\u003e \u003cp\u003eThroughout our study, we faced several limitations that can aid in the expansion of future research. First, it is important to understand that the intended behaviors reported by respondents may not be the same as the actions they execute (Baumeister et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). For example, if someone reports that they drain all standing water from their boat, but, in practice, water remains, AIS transport could occur. Second, the spatial resolution of our analyses needs to be considered when interpreting the study results because boater location was at the zip code extent. With a more precise location like home address, coupled with data on where a boater typically travels to recreate, driving distance could replace straight-line Euclidean distance, which would provide a better representation of the functional distance between AIS populations and recreationists (Brody et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). Finally, we relied on zip codes reflecting home addresses rather than known recreational locations where boaters were accessing waterways. Spatial information on recreation site would allow for a better understanding of the AIS that people interacted with during their outings. Future studies on this topic could benefit from tools such as participatory mapping or GPS tracking (e.g., Chang et al. 2023) to understand travel patterns in relation to place-based preferences, as a way to gain more spatially explicit information on the effects of exposure to biological invasions.\u003c/p\u003e \u003c/div\u003e"},{"header":"Conclusions","content":"\u003cp\u003eAquatic invasive species pose major threats to the biotic integrity of freshwater resources across the globe, especially in the Midwestern US where there is an abundance of human activities that span freshwater ecosystems. An increasing number of environmental social science studies involving recreational boaters in this context provides a fruitful basis for understanding how to shape behavior and most effectively mitigate environmental impacts. We extend this body of work by providing resource management agencies with new insights on the drivers of human behavior that may influence the spread of AIS. The spatial dynamics of recreation activities in relation to ecological conditions not only support the theoretical development of behavioral antecedents but also enable agencies to target recreationists in high and low priority areas that support fishing experiences.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eFunding for this study was provided by the USDA National Institute of Food and Agriculture Hatch program (accession #: 7000939), Illinois Department of Natural Resources (Grant number F69R36Q3), and the Great Lakes Restoration Initiative, US Fish and Wildlife Service, Illinois Department of Natural Resources (Grant number CAFWS-144A). Thanks are extended to the individuals who shared their experiences and knowledge in support of this research process.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eThe authors have no relevant financial or non-financial interests to disclose.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eTheory development, data collection and analysis were all performed by Alison Moore and Danika Ford with input from Elizabeth Golebie, and North Joffe-Nelson. The first draft of the manuscript was written by Alison Moore and Danika Ford. Greg Hitzroth, Amanda\u0026nbsp;\u003c/em\u003eHuegelmann, Sarah King, and Jeffrey Stein offered conceptual guidance and edited the manuscript. Carena van Riper secured funding for this research and provided overall direction in all aspects of the study.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAdam I (2015) Backpackers' risk perceptions and risk reduction strategies in Ghana. 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Int J Disaster Risk Sci 9:167\u0026ndash;180. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s13753-018-0170-0\u003c/span\u003e\u003cspan address=\"10.1007/s13753-018-0170-0\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"biological-invasions","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"binv","sideBox":"Learn more about [Biological Invasions](https://www.springer.com/journal/10530)","snPcode":"10530","submissionUrl":"https://submission.nature.com/new-submission/10530/3","title":"Biological Invasions","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"aquatic invasive species, recreational boater behavior, risk perceptions, spatial analysis","lastPublishedDoi":"10.21203/rs.3.rs-2869687/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-2869687/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eAquatic invasive species (AIS) have caused widespread damage to environmental and socio-economic systems across the globe. One vector of biological invasions is recreational boaters who are at risk of unintentionally introducing AIS when moving between freshwater ecosystems. The drivers of boater behaviors and belief systems therefore warrant careful research attention, yet surprisingly few studies have empirically tested how the ecological context of biological invasions influences the behavioral decisions of recreational boaters. We asked: what are the relationships among boater proximity to AIS, perceptions of risk and efficacy, familiarity with AIS, and engagement in AIS prevention behavior? Drawing from a survey of boaters administered across the U.S. state of Illinois, we quantified and spatially located where boaters lived and evaluated their behavioral patterns. We then combined these survey data with spatially explicit observations of AIS across four taxa, which were collated using secondary data sources. We observed high levels of perceived risks from biological invasions, strong beliefs that individuals could make a difference in minimizing the spread of AIS, and low AIS-related familiarity. Results from a structural equation path model indicated that proximity to invasive fish species, but not other types of AIS, was associated with higher risk perceptions, which in turn, influenced self-efficacy and the intended behaviors of boaters. This study offers new insights on how decision-makers can optimize their effort and direct attention toward high and low priority locations defined in both social and ecological terms.\u003c/p\u003e","manuscriptTitle":"Social and Ecological Drivers of Behavior that Prevents Aquatic Invasive Species Transport","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2023-07-14 14:55:29","doi":"10.21203/rs.3.rs-2869687/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"","date":"2023-10-13T15:51:31+00:00","index":0,"fulltext":""},{"type":"reviewersInvited","content":"","date":"2023-07-10T21:28:18+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"Biological Invasions","date":"2023-05-17T15:08:18+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2023-04-28T12:24:51+00:00","index":"","fulltext":""},{"type":"submitted","content":"Biological Invasions","date":"2023-04-27T12:53:06+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"biological-invasions","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"binv","sideBox":"Learn more about [Biological Invasions](https://www.springer.com/journal/10530)","snPcode":"10530","submissionUrl":"https://submission.nature.com/new-submission/10530/3","title":"Biological Invasions","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"f61eba9e-ce3d-48b3-ae31-0f54d7ec7d5f","owner":[],"postedDate":"July 14th, 2023","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-03-25T15:09:41+00:00","versionOfRecord":{"articleIdentity":"rs-2869687","link":"https://doi.org/10.1007/s10530-024-03287-5","journal":{"identity":"biological-invasions","isVorOnly":false,"title":"Biological Invasions"},"publishedOn":"2024-03-24 15:00:58","publishedOnDateReadable":"March 24th, 2024"},"versionCreatedAt":"2023-07-14 14:55:29","video":"","vorDoi":"10.1007/s10530-024-03287-5","vorDoiUrl":"https://doi.org/10.1007/s10530-024-03287-5","workflowStages":[]},"version":"v1","identity":"rs-2869687","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-2869687","identity":"rs-2869687","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}