Boater’s Preference for Coral Reef Restoration and Sustainable Resource Management in Florida

Abstract

The Florida Reef is under intense pressure from excessive human disturbance and climate change. A group of Florida residents including boaters and fishers was surveyed about their concerns and willingness to pay (WTP) for restorative services. A discrete choice valuation experiment was conducted, involving nearly 1,300 respondents, to estimate WTP for coral reef restoration, wide beaches, and clean water. The boaters demonstrated a somewhat higher WTP for a more extensive beach size and coral restoration. The analysis allowed quantification of maritime transportation passengers’ preferences for sustainable resource management. The findings provide useful insights for maritime transportation and coastal management agencies wishing to finance conservation initiatives. Furthermore, the study offers valuable methodological contributions and policy relevant information to incorporate ecosystem service valuations into the decision-making process beyond the study areas.

Keywords

marine environment invasive species sustainability and resilience transportation and sustainability resource conservation and recovery

From maritime transportation to marine recreation to sport fishing to fisheries, activities near coral reefs contribute significantly to the coastal economies of the United States and countries all around the world ( 1 – 4 ). Estimates indicate that coral reefs play a significant role in the economy, providing economic goods and services valued at approximately $375 billion annually. National Oceanic and Atmospheric Administration’s (NOAA) National Marine Fisheries Service estimates that the value of coral reefs in southeast Florida alone is around $8.5 billion, including $2 billion in local income and 70,400 full- and part-time jobs ( 5 ). Moreover, nearly half of all federally managed fisheries rely on coral reefs, and the annual commercial value of U.S. fisheries from coral reefs exceeds $100 million ( 5 ).

As one of the most imperiled ecosystems on the planet, coral reefs are now experiencing immense stress and reaching their biological limits ( 6 ). They have emerged as potential candidates for global extinction ( 7 ). In particular, the entire coral reef ecosystem of the wider Caribbean, including Florida, has been officially designated as “endangered” by the International Union for the Conservation of Nature ( 7 , 8 ). For the sustainable use of coastal and marine resources such as coral reefs, and sustainable management strategies embedded within a blue ocean economy, this study follows an essential component of effective management, which is to access nonmarket economic values ( 9 ).

Previous research has examined the effects of maritime transportation operations such as boating, sailing, and shipping activities on environments and coastal ecosystems. With the increasing maritime transportation activities in the offshore area, it is essential to understand the consequences of maritime operations on the environment, and on coastal communities, as well as the potential governance challenges ( 10 ). Moreover, tourism activities such as boating, sailing, and sea fishing also have an adverse effect on the environment and on sustainable tourism ( 3 , 4 ). Most studies focus on the impact of air pollution and greenhouse gas emissions from oceangoing vessels such as boats, ferries, cruises, and container vessels ( 11 ). Some of these studies have confirmed that continued carbon emissions will increase the need for intensive care of coral reefs, and reducing carbon emissions for coral reefs will bring global ecological benefits ( 12 ).

An individual’s reaction to the degradation of coral reefs is a clear example of a social dilemma, whereby one’s immediate choices may conflict with principles of sustainability. For example, activities such as recreational boating and fishing near southeastern Florida’s coral reefs currently offer immediate gratification, yet the cumulative effect of hundreds of thousands of boaters and anglers using the ecosystem creates stress that degrades the system. Such loss will eventually have an impact on immediate gratification, because regular users will become discouraged by perceptions of impoverished water quality and fishing opportunities. However, this dilemma may motivate them to contribute financially or otherwise to protect and improve the ecosystem’s condition.

To contribute to the literature on the values of marine and coastal resources and the maritime transportation passengers’ preferences on the coastal environment, this study undertook a discrete choice experiment (DCE) to assess the conservation preferences of boaters who live in Florida. As the only nearshore coral reef in the continental United States, the Florida Reef stands out as one of the world’s most renowned and popular reef systems, attracting a substantial number of tourists from across the globe. The current study sought to understand if and how much Florida maritime transportation passengers might be motivated to conserve this natural resource. Using parametric (logit/multinomial logit estimation) methods, the DCE estimated the willingness to pay (WTP) for coral reef restoration and selected sustainable attributes. The results could reveal how environmental preferences and sustainability concerns of maritime transportation passengers affect maritime transportation and tourism demand. Furthermore, this study not only provides mechanisms for policy makers to raise conservation funds for coastal and marine resources but also offers valuable insights into incorporating ecosystem service valuations into the decision-making process of maritime transportation passengers for sustainable resource management.

Background

The Florida Reef system is divided into two distinct sections: the biologically less robust northern third and the more vibrant southern two-thirds that extend alongside the Florida Keys archipelago. These two sections have been managed separately, with limited protections in place for the northern section, whereas the entire southern section has fallen under the safeguard of the Florida Keys National Marine Sanctuary since 1997 ( 13 ). Within the boundaries of the Sanctuary, seagrasses dominate, particularly in the Gulf of Mexico, providing essential and integrated functions for the reef system in the Atlantic. Although scientific literature often categorizes the northern and southern sections based on geomorphology and differences in the reef-building corals, the reef-building staghorn coral (Acropora cervicornis), federally listed as “threatened,” can still be found across the entire system. Notably, the relatively cooler waters in the northern section, which are largely included in the federal designation of critical habitat, may offer favorable conditions for the future growth of staghorn coral (refer to Figures 1 and 2).

Survey Design and Implementation

Most respondents were selected from Florida Fish and Wildlife Commission databases of holders of Florida commercial or recreational saltwater fishing licenses who reside within the contiguous region of Monroe, Miami-Dade, Broward, Palm Beach, and Martin counties. Nonresidents and residents without email were excluded, and this list produced 90,086 fishers, of whom 88,809 were recreational. Randomized selection to reach a quota resulted in 31,691 license holders with a functional email address. The stratified sample was enhanced with 460 diverse stakeholders, including those involved in diving, boating, fishing, and education, compiled in close collaboration with the Southeast Florida Coral Reef Initiative, for a total sample of 32,151. Stakeholders are defined as those who are dependent on the coral reefs economically or culturally. A survey instrument was distributed by email and was completed by 824 respondents, of whom 703 came from the database for holders of a recreational saltwater fishing license. Only 10 individuals reported having a residential zip code outside of Florida, and only one respondent claimed no activities in the ocean.

With regard to the connection to coral reefs and the ocean in general, only 1 of 1,157 respondents claimed no activity in the ocean, and many respondents indicated participation in multiple activities. A composite Ocean Activity score produced a median of 12 out of a total possible 40 (based on 10 activities with a high score of 4 each). Average engagement for the 10 activities is presented in Figure 3. Boat ownership is presented in Figure 4: nearly 78% owned a vessel that operated either with a motor (68.3%) or without a motor (9.5%).

Of the 10 activities listed, a majority practiced the top five at least annually. Therefore, most respondents spend time both “on the water” and “in the water.” Boating with a motor was the most common activity, followed closely by fishing (no distinction was made between types of fishing). Motorboating, fishing, and beach visiting were practiced annually by greater than 94% of respondents. Snorkeling registered high participation at the annual rate but only moderate participation at the monthly rate, meaning that it is pervasive yet practiced infrequently by this sample.

One section of the survey instrument presented the DCE, a primary referent of which was a DCE employed in a study of the U.S. Virgin Islands ( 14 ). DCEs have proven to be an efficient method of assessing WTP for the management of a complex ecosystem, such as coral reefs, while considering a diverse range of socioeconomic factors that interact with one another ( 14 ). Based on choice modeling, a DCE incorporates the tradeoffs between several attributes by forcing the reconciliation of complex attributes into a distinct, legible decision. It assesses multiple attributes efficiently and may be used to address nonmarket benefits ( 15 ). Respondents forced to choose between Plan A or Plan B are predicted to decide based on the perceived level of total utility, which assesses a plan’s attributes as opposed to its immediate cost ( 16 ). Moreover, by limiting the ability of respondents to ascertain preferred answers, a DCE reduces the potential bias of strategic response behavior ( 14 ).

This study’s choice cards forced the respondent to make one selection from a menu of three options, Plan A, B, or C, while considering divergent, multidimensional attributes that were depicted with graphical and textual equivalency to facilitate efficient comparison (Figure 5). To address various concerns of stakeholders, each plan contained a set of four attributes: 1) beach size, 2) navigable water quality, 3) coral reef restoration levels, and 4) monthly reef management fees. The seven management fees varied by $5 increments, whereas other attributes varied by three levels apiece (Table 1).

Table 1.

Attributes and Levels in Choice Experiment

Note: Areas outlined in bold were held constant.

Based on a full factorial, the combination of attributes resulted in 729 potential scenarios. From this excessive set, a practical, representative subset of 20-choice cards was selected to avoid extremes and to dramatize compelling tradeoffs ( 14 ). The 20 cards were organized into 10 pairs whereby Plan A varied from Plan B by two or more attributes, and Plan C was held constant along with the attribute of water quality at the levels of 30% improvement in water quality for Plan A, 10% improvement for Plan B, and “poor” for Plan C. Plan C served as the control plan with no monthly fees charged, and respondents were told that its attributes represented the status quo, which were less desirable, for example, a 10% smaller beach size and coral restoration at the “current level.” Plan B offered more favorable attributes than Plan A, except for water quality, and had an average fee that was $2.75 lower than Plan A. Note that the beach size attribute was on average 1.2 times better, and the coral restoration attribute was 1.5 times better in Plan B compared with Plan A. The questionnaire’s instructions explained that the fee would be assessed as part of a utility bill because stakeholders have shown resistance to direct payments for marine activities ( 17 ). The proposed monthly fee combined the costs of the other three attributes into a single total, and these costs considered recent practices and literature. For example, Brevard County, FL proposed 18 years of annual household fees across a range from $16 to $626 per year for beach nourishment ( 18 ). In comparison, a monthly fee of $10 would result in $120 annually.

For nearshore water quality issues, wastewater treatment is paramount and costly. The three largest counties in southeast Florida—Palm Beach, Broward, and Miami-Dade—face a 2025 deadline to decommission their ocean outfalls, which release partially treated sewage into the ocean ( 19 ). A 2008 law, The Leah Shad Memorial Ocean Outfall Program, specifies that the costs for treatment upgrades, operation, and maintenance would be covered by certain utility customers in the three counties through various means like monthly rates, impact fees, connection fees, assessments, or other mechanisms ( 19 ). This law cites a study that calculates a representative monthly household fee at $19.80, and this level was reflected in the median fee of $15 on the choice cards. As for the percentage of water quality improvement on the choice cards, at either 30% for “significant improvement” or 10% for “slight improvement,” these were based on Broward County’s mid-range scenarios for improvement levels of 24% or 11% after decommissioning their ocean outfalls ( 20 ).

Although the practices of coral husbandry and coral reef restoration have expanded greatly in the past decade, they were less developed at the time of this survey. Then, the annual cost to generate and manage an individual Acroporid coral in Florida was $75 to $135, according to the Coral Restoration Foundation ( 21 ). Florida’s Coral Reef Protection Act of 2009 generates income through charges for damage to corals across the Florida Reef in the range of $150 to $1,000 per occurrence ( 22 ). Considering that reef restoration requires millions of dollars to accomplish ( 21 ), the proposed fees are modest.

Such considerations and calculations were not explained in the survey. Respondents had to decide quickly if a fee associated with a preferred plan was acceptable, and they may have decided that the fee was not paramount. The lowest level of $5 per month would not cover all projected costs, and even the highest level of $30 could be inadequate given the extensive, systemwide degradation.

Model Specification

As stated, for valuing coral reef ecosystems, we employed a DCE framework to estimate the respondents’ stated preferences in a designed contingent market scenario ( 23 ). Analysis of the choices made in the DCE were examined using the random utility modeling (RUM) framework ( 24 ). In a RUM framework, the individual, n, faces a choice among j alternatives in a choice set, t. The individual, n, obtains a certain level of utility, $U_{njt}$ , from the jth alternative and chooses the alternative with the highest utility ( 25 ).

Accordingly, in this study, we assumed that the nth respondent’s decision could be expressed as his/her evaluation of the utility of the choices at three states: status quo ( $U_{n 0}$ ), Option A ( $U_{n 1}$ ) and Option B ( $U_{n 2}$ ). If the respondent, n, attaches the highest utility to Option B (i.e., $U_{n 2}$ > $U_{n 1}$ and $U_{n 2}$ > $U_{n 0}$ ), then we would expect Option B to be chosen by respondent n ( 26 ). Respondent n is assumed to know his/her utility ( $U_{nj}$ ). However, the researcher was not able to observe the respondent’s utility, having only information on attributes related to j alternatives and some characteristics of the respondent. This was reflected by decomposing the model into two parts: 1) the deterministic (observable) component $V_{nj}$ , and 2) the random (unobservable) component, $ε_{nj}$ . The utility ( $U_{nj}$ ) of restoration to the Florida Reef stakeholder, n, derived from his/her choice of payment for the attributes of restoration alternative j can therefore be written as

U_{nj} = V_{nj} + ε_{nj}

(1)

where $ε_{nj}$ , the unobserved part of $U_{nj}$ , captures the effects of random factors and is assumed to follow a random distribution ( 27 ). $V_{nj}$ , the observable part, pertains to the measurable component of $U_{nj}$ . The deterministic part, $V_{nj}$ , is generally assumed to be a linear function of the attributes of the restoration alternatives and the characteristics of the stakeholders, often modeled as represented in Equation 2,

V_{nj} = X_{nj}^{'} β + S_{n}^{'} α

(2)

where

$X_{nj}^{'}$ is vector of attributes of the coral reef ecosystem,

$S_{n}^{'}$ is vector of socioeconomic characteristics of the stakeholder, n, and

$β$ and $α$ are vectors of unknown coefficients to be estimated.

We assumed that the stakeholder n would select the restoration option, j, if and only if $U_{nj} > U_{nk}$ ( 28 ). Accordingly, we can express the probability, P, of respondent n choosing alternative j over another alternative, k, as follows:

P_{nj} = Prob (U_{nj} > U_{nk})

(3)

Substituting Equation 1 into Equation 3, we have

P_{nj} = Prob (V_{nj} + ε_{nj} > V_{nk} + ε_{nk}, k \neq j)

(4)

The expression $P_{nj}$ depends on the assumptions made about the distribution of the stochastic error terms, $ε_{nj}$ , considering the deterministic components of the utility function, $V_{nj}$ . This expression can be solved by assuming a distribution for the stochastic error term. The choice probability of restoration scenario j for stakeholder n, assuming the error terms are independently and identically distributed and follow the Gumble (extreme value) distribution, can be estimated using the multinomial logit (MNL) choice model as follows ( 24 , 29 ):

P_{nj} = \frac{e^{V_{nj}}}{\sum e^{V_{nk}}} = \frac{e^{X_{nj}^{'} β + S_{n}^{'} α}}{\sum e^{X_{nk}^{'} β + S_{n}^{'} α}}

(5)

The MNL model, formulated by McFadden ( 24 ), is a widely used multinomial response model ( 30 , 31 ). The primary strength of the MNL model lies in its simplicity, making it easy to estimate, interpret, and operate ( 32 ). For solving Equation 5 and estimating coefficients α and β, we employed MNL regressions using the responses from the DCE.

Based on the MNL regression analyses of the respondents’ choices in the coastal resource restoration scenario, we constructed four models to estimate coefficients for each attribute. For all models, the monthly fee of a restoration plan was considered an attribute of the plan (i.e., the price attribute). Using the derived estimates of the MNL model parameters ( $β)$ , we were able to calculate the WTP for a change in the attribute levels. In the DCE framework, the WTP is described as the maximum amount of money an individual is willing to give up for the improvement of the restoration attributes by keeping the utility constant. The mWTP (marginal willingness to pay) for a change in the restoration attribute levels can be calculated as the marginal rate of substitution between changes in a specific restoration attribute and the price attribute,

WTP = \frac{α_{i} (A_{i 1}) - α_{i} (A_{i 2})}{α_{f}}

(6)

where

$α_{i}$ is estimated coefficient for a specific restoration attribute, I,

$A_{i 1}$ is reference level of attribute i,

$A_{i 2}$ is subsequent level of the attribute, and

$α_{f}$ is estimated coefficient for the monthly fee attribute ( 28 , 33 ).

Results

We had two rounds of responses from each respondent because we constructed 20 different choice cards that were organized into 10 pairs. Each pair included Plan A and Plan B, differing in at least two attributes and shown randomly to each respondent. Therefore, we built three data sets based on Round 1, Round 2, and the combined full sample. We obtained 859 valid responses in Round 1 and 845 responses in Round 2, for a total of 1,704 responses in our full sample. In the full sample, 54.64% of respondents selected Plan A, with 10.45% coral restoration improvements on average. The average choice of coral restoration improvements was 14.15%, and the average monthly fee was $13.98 (see Table 2).

Table 2.

Descriptive Statistics for All Sample

Plan	Choice number	Percentage	Beach size, %	Coral restoration improvements, %	Water quality, %	Fee ($)
A	931	54.64	−3.34	10.45	30	15.94
B	623	36.56	−0.35	23.08	10	14.41
C	150	8.80	−10	0	0	0
Total	1,704	100	−2.83	14.15	19.17	13.98

Table 3 summarizes the main variables used in the estimation of the full sample. The participants in our study spanned from 18 to 85 years old, with an average age of 46.6 years. Modes (and percentages) revealed that the typical respondent was 47 years old, White (81.6%), male (82.4%), identified as a Republican (84.2%), and held a 4-year college degree (56.3%). Approximately 17.2% of respondents reported an annual household income greater than $200,000. The average monthly fee the respondents chose to pay was around $14 with an average coral restoration improvement of 14%. A reported 74% of respondents had donated money or contributed their time to an environmental cause in the past year, and 59.4% of respondents used a motorboat monthly.

Table 3.

Variables Used in Estimation of Full Sample

Description	Abbreviation	N	Mean	SD	Min.	Max.
Fee per month	fee	1,704	13.98	8.67	0	30
Beach size	beach	1,704	−0.03	0.08	−0.1	0.1
Coral restoration	coral	1,704	0.14	0.13	0	0.3
Importance of water attribute	planwater	1,666	4.4	0.92	1	5
Effect of climate change on reefs	clireef	1,654	3.72	1.11	1	5
Democrat	dem	1,510	0.16	0.36	0	1
Environmental orientation	enviro	1,540	6.09	2.40	1	10
Coral Reef Concern Scale	coral	1,632	25.3	5.10	9	35
Donor to environment	donor	1,622	0.74	0.44	0	1
Birthplace	born	1,624	1.81	0.62	1	3
Education in three categories	edu	1,614	2.10	0.65	1	3
Race	race	1,606	1.51	1.24	1	7
Boating, by motor	boating	2,300	1.54	0.60	0	2
Climate Concern Scale	climate	1,654	17.14	5.12	5	25
Sex	sex	1,628	0.82	0.38	0	1
Age in years	age	1,620	46.59	12.17	18	85
Income	inc	1,544	6.23	2.99	1	11

Note: SD = standard deviation; Min. = minimum; Max. = maximum.

Table 4 presents three models of the MNL regression analyses of the coastal resource restoration scenario selections among all respondents. Our results indicated that the payment attribute (fee per month) had a statistically significant impact on respondents’ preferences for various plans within the coral restoration scenario. Moreover, the extent of coral restoration improvements played a crucial role in influencing the scenario selection among all respondents. The beach size was also a significant factor in scenario selection because the coefficients of beach size were significant in all models. Both the importance of water attributes and the effect of climate change on coral reefs had a significant effect on the coral restoration scenario in Models 1 and 2. “Democrat” had an impact on scenario selection in Models 1 and 3, and “donor” to the environment was a significant factor in Models 2 and 3.

Table 4.

Estimates for Multinomial Logit Regression Analyses of the Coastal Resource Restoration Scenarios among All Respondents

Variables	Model 1	Model 2	Model 3
	Plan A to B	Plan A to C	Plan B to C
fee	−0.09*** (0.01)	−6.70*** (0.07)	−6.61*** (0.07)
beach	11.70*** (1.07)	−56.91*** (7.27)	−68.61*** (7.31)
coral	18.17*** (1.09)	−23.40*** (3.12)	−41.57*** (3.31)
planwater	−0.57*** (0.13)	−0.35** (0.14)	0.22 (0.17)
clireef	−0.31* (0.18)	−0.51** (0.23)	−0.20 (0.28)
dem	−0.57** (0.23)	0.17 (0.38)	0.74* (0.42)
enviro	−0.05 (0.04)	−0.04 (0.06)	0.02 (0.07)
coral	0.01 (0.02)	−0.16*** (0.03)	−0.18*** (0.03)
donor	−0.29 (0.22)	0.79** (0.33)	1.07*** (0.38)
born	0.02 (0.14)	0.01 (0.22)	−0.01 (0.25)
edu	0.10 (0.14)	−0.41* (0.21)	−0.51** (0.25)
race	0.00 (0.08)	0.05 (0.10)	0.05 (0.12)
boating	−0.18 (0.15)	−0.02 (0.22)	0.15 (0.25)
climate	0.04 (0.04)	0.03 (0.05)	−0.01 (0.06)
sex	−0.05 (0.21)	0.74* (0.40)	0.80* (0.44)
age	−0.00 (0.01)	−0.00 (0.01)	0.00 (0.01)
inc	0.00 (0.03)	−0.08* (0.04)	−0.08 (0.05)
Constant	3.03*** (1.01)	31.94*** (1.55)	28.91*** (1.68)
Observations	1,362	1,362	1,362

Note: Robust standard errors in parentheses.

p < 0.1; **p < 0.05; ***p < 0.01.

Table 5 shows the mWTP (derived using Equation 3) per month for positively valued beach size or coral restoration improvement scenarios in Models 1 to 3. Among the coral restoration improvement scenarios, all subsample groups displayed a WTP a positive monthly fee for larger coral restoration improvements. For all respondents, the highest mWTP was $25.18, with mean levels of improvement ranging from 10.45% to 23.08%. For all respondents, mWTP was higher ($ 0.36 to $1.45) if respondents chose larger improvements (10.45% to 23.08%) from the current level (0%). Among the beach size selection scenarios, all samples showed a WTP a positive monthly fee for a larger beach size. For all respondents, there was a positive mWTP for avoiding beach size shrinkage (−3.34% to −0.35%, −10% to −3.34%, −10% to −0.35%). With approximately 1 million registered recreational boats in Florida in 2022 ( 34 ), we estimated a statewide aggregate mWTP of boaters for a larger beach size, ranging from $ 0.57 million to $3.84 million monthly under varied selection scenarios; estimations for coral restoration improvements ranged from $ 0.36 million to $25.18 million monthly under varied improvement scenarios.

Table 5.

mWTP Values per Month for Positively Valued Restoration Attributes

Options	Mean levels of improvements	mWTP for all respondents (2013 USD)	Statewide WTP^a (in million dollars)
Beach size
Plan A to B	−3.34% to −0.35%	3.84	3.84
Plan C to A	−10% to −3.34%	0.57	0.57
Plan C to B	−10% to −0.35%	1.00	1.00
Coral restoration
Plan A to B	10.45% to 23.08%	25.18	25.18
Plan C to A	0% to 10.45%	0.36	0.36
Plan C to B	0% to 23.08%	1.45	1.45

Extrapolated values based on marginal willingness to pay (mWTP) × 1 million (number of registered recreational boats in Florida in 2022).

In Figure 6, we divided the total sample into two groups by boat ownership: respondents who owned a boat versus those who did not. The MNL regression analyses were the same as those reported in Table 5, and the variable coefficient estimates used for the calculation of mWTP per month for beach size or coral restoration improvement scenarios varied by boat ownership (see Tables A1 and A2 in the Appendix). The estimated mWTP from the three different coral restoration improvement and beach size selection scenarios were used to calculate the average mWTP (see Table A3 in the Appendix).

In Figure 6, among the coral restoration improvement scenarios, both groups displayed a WTP (a positive monthly fee) for larger coral restoration improvements. For respondents who owned a boat, the average mWTP was $13.96; for respondents who did not own a boat, the average mWTP was $7.85. Among the beach size selection scenarios, for both groups, there was a positive average mWTP for avoiding beach shrinkage. The average mWTP was $6.81 for boatowners and $1.72 for nonboatowners. Compared with the average mWTP between boatowners and nonboatowners, boatowners’ average mWTP values were higher than those of nonboatowners in both coral reef restoration improvements and beach size selection scenarios. These results indicated that Florida boatowners had a heightened appreciation for environmental quality as stakeholders of Florida Reef, making them more likely to pay a substantial fee for conservation initiatives.

Aside from fishing and boating, other recreational activities also exert pressure on the Florida Reef system. To investigate the effects of these activities on the Florida Reef system and beaches, we estimated the WTP of participants engaged in various recreational activities listed in Figure 2. Figure 7 presents the mWTP for significant coral restoration improvements and beach size maintenance by recreational activities. For both scenarios, coral restoration improvement and beach size preservation, all groups showed a positive WTP (a monthly fee) to support these initiatives. Notably, respondents who participated in recreational activities such as scuba diving, snorkeling, freediving, motor boating, surfing, paddling, distance swimming, and sailing exhibited a higher mWTP than those who did not engage in these activities. This trend was consistent across both coral reef restoration and beach size preservation scenarios. These findings indicated that participants in recreational activities had a higher level of appreciation for environmental quality, underscoring their key role as stakeholders of the Florida Reef ecosystem. Consequently, they were more inclined to pay a substantial fee for conservation initiatives, which reflected their commitment to preserving this unique ecosystem.

Discussion

Unlike previous valuation studies that have focused on a single attribute, this study considered the nonmarket values of multiple attributes of a marine and coastal resource in Florida. The respondents indicated their active involvement in marine and coastal recreation. Our study yielded intriguing findings that hold valuable implications for conserving the coral reefs and nourishing the beaches in Florida and around the world. We found mWTP for a larger beach size ranged from $ 0.57 million to $3.84 million (monthly) under different scenarios; and coral restoration improvements, ranging from $ 0.36 million to $25.18 million (monthly) for further improvement scenarios. The results indicated the significant potential of fundraising for marine and coastal reef conservation from the boaters.

Our findings confirmed the results from other related research focusing on maritime transportation passengers’ WTP for marine and coastal resources in Florida and other regions worldwide. We found a difference in the WTP (conservation fees) between the total sample and subsample, which indicated that boaters had different preferences for diverse improvement scenarios. These results were similar to outcomes reported by Casey et al., in which the typical tourist’s WTP for marine conservation in Mexico ranged from US$20 to $80 ( 35 ), and Xiao et al., who found that the WTP for marine and coastal resources in China for six subsamples ranged from US$27 to $52 ( 36 ).

Our estimations further revealed that boaters showed a greater WTP for coral reef restoration compared with beach nourishment. This observation aligns with previous research ( 36 ), which suggests that the public tends to assign a higher value to conserving relatively scarce resources than abundant ones within the same study site. Many coastal cities and islands in Florida have comparatively high-quality beach resources. However, reefs in Florida are relatively scarce and limited to specific regions. The reef stakeholders such as maritime transportation passengers are more likely to pay for these exceptional and limited resources.

Specific maritime transportation passengers possessing Florida commercial or recreational saltwater fishing licenses had a heightened appreciation for environmental quality within the state, making them more likely to pay the required fee for conservation initiatives. This observation aligns with existing research, such as the study by Wallmo and Lew, which found that respondents from coastal regions in the United States exhibit a higher WTP value for the restoration of marine and coastal resources ( 37 ). Moreover, visitors who have made more prior trips to the island and coastal regions demonstrated a greater WTP for the conservation of marine and coastal resources, as shown by Cazabon-Mannette et al. ( 38 ).

Unlike previous research that mainly focused on marine life resources ( 39 ), our research took a distinctive approach by examining the maritime transportation passengers’ WTP for marine and coastal resources from a multiattribute perspective. By delving into public preferences for conserving the nonmarket values of these resources, our study not only offers valuable insights into sustainable resource demand and maritime transportation passengers’ preferences but also provides essential propositions for making sustainable resource management decisions. On the one hand, owing to the limitation of the conservation fund, the study of public preference offers support for sustainable resource management decisions about priority conservation resources and effective fund allocations ( 40 ). Conversely, the marine and coastal resources that are relatively rare and distinct, accompanied by greater nonuse values, hold a pivotal position in conservation decision-making, and sustainable resource management departments may be wise to focus more on them. Nature-based resource policy makers could put more emphasis on relatively attractive resources in policy design, which could, in turn, improve public awareness and their participation in restoring these marine and coastal resources.

The methodology we employed could serve as a guiding framework for conducting similar studies in other areas and could be applied to a much broader scope. By adapting our survey instrument and data collection methods to other coastal states, researchers could gather valuable data that could be analyzed and compared to understand public preferences for coral reef restoration and coastal resource management. Conducting comparative studies across regions could provide a comprehensive understanding of public preferences and values related to coastal and marine resource management. It is also important to recognize that localized studies offer detailed insights into specific contexts that can inform larger, more generalized research efforts for benefit transfer ( 41 , 42 ), as they provide essential data points that contribute to the overall mosaic of understanding in environmental resource management.

The transferability of value estimates can be achieved via the benefit transfer approach, which uses meta-analysis of numerous context-specific localized valuation studies to generate value estimates for other locations for which no primary data-based analysis exists. Moeltner et al. demonstrate how insights from localized study-specific heterogeneity can provide insights to perform locally weighted analyses that could substantially improve the performance of meta-regression models to predict out-of-sample nonmarket value estimates ( 43 ). More valuation research/case studies with unique samples and diverse geographies would enrich the meta-data for benefit transfer to produce more reliable value estimates for locations with no primary data or valuation studies. The uniqueness (i.e., of samples and geographies) of these valuation studies should be considered positively, as they provide inputs to uncover how local conditions influence global preferences for ecosystem service valuation in general, and maritime transportation in particular, and they further help with the generalizability and applicability of such valuation exercises.

To ensure the robustness of the scenario choice cards, we conducted pilot studies and iterative testing. Feedback from these pilot studies was used to refine the scenarios and ensure they were understandable and meaningful to the respondents. This iterative process enhanced the validity of the scenarios presented in the choice cards and the final set of choice cards was randomly assigned to respondents in the survey. Although the current set of scenario choice cards was carefully designed and validated with an established methodology, we recognize that there is always room for improvement. Although there was some uncertainty with the current set of choice scenarios, our methodology was grounded in the literature, and provided a solid foundation that could be further refined in future research to enhance the validity and applicability of the findings.

To account for individual heterogeneity in responses, we used the RUM framework, which includes both the deterministic and stochastic components of utility. The stochastic part is used for capturing unobserved variations in preferences across individuals. We additionally included interaction terms and individual-specific characteristics in the model to represent the diversity of responses. For analysis, we used random coefficients mixed logit models to allow for individual heterogeneity in preferences. Although linearity is a widely used practical assumption, we recognize that preferences may exhibit nonlinear relationships with attributes of the restoration alternatives. For instance, individuals’ marginal utility for certain attributes may change at different levels. In future research, this model could be extended to explore nonlinear relationships by including polynomial terms or piecewise linear functions to better capture these complexities.

Conclusion

The primary objective of this study was to estimate maritime transportation passengers’ WTP for coral reef restoration and sustainable resource management in Florida. Using the data collected through emails with regional boaters with fishing licenses, we estimated MNL models and found that boaters were willing to pay a positive value for a larger beach size and coral restoration improvements. The results indicated boaters would pay on average $7 per month for larger beach size or $14 per month for coral restoration improvements. Extending the WTP of boaters in our sample to the approximately 1 million registered recreational boats in Florida (assuming one boat owned per household), these results suggest the state could potentially collect on average $84 million/year for sustainable beach management and $168 million annually for coral reef management programs from boaters. The statewide aggregate WTP values of boaters for all different components of coral reef restoration could reach an impressive $2.5 billion over a period of 10 years.

The degradation of the Florida Reef presents a significant challenge, and the restoration efforts needed are likely to be costly. However, there is encouraging news from maritime transportation passengers of southeastern Florida who directly use the coral reefs and nearby ocean habitats, the boaters, as they show a willingness to support measures such as taxes to enhance the quality of Florida’s coral reefs. While it remains uncertain whether this support extends statewide, to other states, or to the public, the opinions of direct users, who possess intimate knowledge of the system, could be influential. A hopeful precedent can be seen in the restoration efforts for another severely degraded ecosystem in Florida: the Everglades. The multibillion dollar Comprehensive Everglades Restoration Plan enjoys broad support at the local, national, and even international levels, emphasizing the importance of collective commitment to environmental restoration. Notably, there are established connections between the two ecosystems, the Everglades and the Florida Reef ( 44 ). Drawing from this example, a systemwide restoration endeavor for the Florida Reef could similarly adopt the principles of ecosystem-based management, creating a collaborative and holistic approach to safeguarding this invaluable marine ecosystem.

By integrating existing local data sets with our DCE methodology, we enriched our analysis. This integration enabled identification of broader trends and patterns that may not have been apparent from the survey data analysis alone. Moreover, it allowed for a more robust analysis. For instance, the historical environmental data helped us understand the long-term changes in coral reef health and their impact on public preferences. The economic data provided insights into how economic conditions influenced WTP for restoration efforts. The demographic information could help us tailor our analysis to different population segments, enhancing the generalizability of findings. Moreover, previous survey results on related topics could be linked to validate our findings and identify consistent patterns or discrepancies ( 45 , 46 ). This holistic approach is likely to lead to more accurate and comprehensive evaluations of public preferences for coral reef restoration and sustainable resource management.

In this study, we investigated the maritime transportation passengers’ preference for coral reef restoration and sustainable resource management in Florida and analyzed whether people hold these values for coastal and marine resources. Future research holds the potential to replicate and expand the current study to encompass a broader population, such as other coastal states within the United States or even other coastal countries in the Caribbean islands and beyond. Furthermore, employing the DCE methodology in future studies could offer insights into the distinctions between intermediate and final ecosystem services and -benefits. Furthermore, incorporating other relevant attributes into the choice scenarios could lead to a more in-depth understanding of how various factors influence maritime transportation passengers’ decision-making processes. This type of study could provide significant advantages for sustainable resource management with regard to the integration of ecosystem service valuations into the maritime transportation passenger’s decision-making processes.

Supplemental Material

sj-docx-1-trr-10.1177_03611981241283450 – Supplemental material for Boater’s Preference for Coral Reef Restoration and Sustainable Resource Management in Florida

Supplemental material, sj-docx-1-trr-10.1177_03611981241283450 for Boater’s Preference for Coral Reef Restoration and Sustainable Resource Management in Florida by Fan Jiang, Mehrnoosh Asadi, James W. Harper and Pallab Mozumder in Transportation Research Record

Footnotes

Acknowledgements

The authors acknowledge the support provided by the National Science Foundation.

Author Contributions

The authors confirm contribution to the paper as follows: study conception and design: F. Jiang, P. Mozumder; data collection: P. Mozumder; analysis and interpretation of results: F. Jiang, J.W. Harper; draft manuscript preparation: F. Jiang, M. Asadi, J.W. Harper, P. Mozumder. All authors reviewed the results and approved the final version of the manuscript.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was supported by the National Science Foundation (Award no. 1832693: CRISP 2.0 Type 2: Collaborative Research: Organizing Decentralized Resilience in Critical Interdependent-Infrastructure Systems and Processes (ORDER-CRISP).

ORCID iDs

Fan Jiang

Pallab Mozumder

Supplemental Material

Supplemental material for this article is available online.

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