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Article

Using Public Participation Geographic Information Systems (PPGIS) to Identify Valued Landscapes Vulnerable to Sea Level Rise

by
Wayde C. Morse
1,*,
Cody Cox
2 and
Christopher J. Anderson
1
1
School of Forestry and Wildlife Sciences, Auburn University, Auburn, AL 36849, USA
2
Warnell School of Forestry and Natural Resources, University of Georgia, Athens, GA 30602, USA
*
Author to whom correspondence should be addressed.
Sustainability 2020, 12(17), 6711; https://doi.org/10.3390/su12176711
Submission received: 14 July 2020 / Revised: 12 August 2020 / Accepted: 16 August 2020 / Published: 19 August 2020
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Abstract

:
The U.S. Gulf of Mexico coast has a long history of intense and varied development, from energy infrastructure and seaports to vacation homes and tourism. Coastal populations and development are growing. Concurrently, global climate change will influence sea level rise, resulting in increased flooding, storm surge, and coastal erosion. Regional planners must prepare for sea level rise and develop adaptive solutions to maximize resiliency. Comprehensive coastal vulnerability mapping assessments (CVMA) can integrate social, economic, and physical vulnerability with spatial analysis of natural hazards for local place-based investigations. Public Participation Geographic Information Systems (PPGIS) are a potentially important tool for the spatial collection of stakeholder knowledge for CVMA. The objective of this study was to assess the locations of a range of landscape values, ecosystem services, and development preferences held and identified by the general public using PPGIS to determine if those valued locations are vulnerable to sea level rise. We found that PPGIS can be used to map a wide variety of landscape values and that they can be used to assess vulnerability to sea level rise. We conclude with a discussion on how to integrate PPGIS into participatory CVMA for sea level rise planning.

1. Introduction

The U.S. Gulf of Mexico coast has a long history of intense and varied development with energy infrastructure and seaports, marine and fishing industry, urbanization, and beach homes and tourism. The number of people moving to coastal areas has been increasing and that pattern is projected to continue [1]. Furthermore, the population across the Gulf Coast tends to be older, have higher poverty rates, and has a greater share of African Americans compared to the rest of the United States [2]. Concurrently, the Intergovernmental Panel on Climate Change (IPCC) projects that global climate change will influence sea level rise and potentially hurricane intensity, resulting in increased flooding, storm surge, and coastal erosion [3,4,5]. The Gulf Coast is undergoing some of the fastest rises in relative sea level in the United States [6] (accessed 2020). More people and more infrastructure along the coast results in increased vulnerability to climatic variation and sea level rise [3,7]. Promoting the resilience of coastal communities and maintenance of ecosystems services necessitates a better understanding of these coupled human–natural systems [7,8,9,10]. Planners need to understand how decisions about the built and natural environment affect vulnerability of these resources to coastal changes and how coastal changes are in turn influenced by conservation and development decisions. Planning for sea level rise and resilience to subsequent impacts has become an important component of coastal natural resource management [11,12,13,14].
The mean global sea level has been rising by approximately 1.77 mm/year since 1900 [15]. However, recent trends have been shown to speed up this process, resulting in sea levels rising at approximately 3.2 mm/year since the early 1990s [15,16]. The mean global sea level is predicted with greater than 90% confidence to rise between 0.2 and 2.0 m by 2100 [17]. Regional data show that the mean sea level of the Gulf of Mexico may actually be rising faster than the global trend, increasing by 3.3 ± 0.4 mm/year since 1992, though the exact cause is uncertain [6]. Based on these projections, coastal areas will face rising sea levels throughout the 21st century, resulting in the loss of coastal lands and coastal habitats [18], inundation and loss of wetlands [19], and loss of barrier island ecosystems [20,21]. Increasing sea levels, particularly if coupled with increased hurricane frequency and/or intensity, will contribute to barrier island loss by increasing the frequency and portion of island inundation [22,23]. These factors can ultimately result in landward migration of islands or conversion to submerged shoals [24]. Sea level rise increases both relative water depth and salinity for coastal and river riparian wetlands. Current intertidal wetlands may transition to subtidal environments while changes in upriver tidal extent cause changes to freshwater systems [25,26]. The possible inland and/or upslope migration of the intertidal wetland zone communities are dependent on whether natural land is available. In many areas along the Gulf coast, tidal wetlands are constrained from migrating upslope because of anthropogenic barriers such as seawalls and other hard structures which essentially get ‘squeezed out’ when the sea level ultimately rises [27].
It is important for regional managers at sites along the Gulf Coast to prepare for sea level rise and develop adaptive solutions that maximize resiliency [11,21]. Planners in coastal areas will be increasingly tasked with planning for continued growth and development while simultaneously mitigating the risks associated with sea level rise [28]. To develop comprehensive land-use plans, a clear understanding of potential impacts is necessary. Potential impacts include those to infrastructure and the built environment, to the lives and livelihoods of residents, to natural ecosystems and wildlife, and to historic, cultural and other aspects of the landscape that communities value. A recent survey of natural resource planners indicated that conflicts between societal and ecological priorities along with gaining societal support are some of the most pressing concerns planners face addressing sea level rise [13]. This group of researchers has been working in a participatory manner with stakeholders (natural resource managers, community planners, public officials, environmental communicators) to enhance the usability of their interactive sea level rise visualization tool for planning in the Northern Gulf of Mexico [13,29]. Planners can use these and other vulnerability assessment and mapping tools to help design more resilient systems [30]. Vulnerability is the level of susceptibility a system has to the adverse effects of natural hazards while resilience is the ability to recover from, adapt to, or cope with damage or change [31]. Natural hazards and vulnerability are geographically dependent, and mapping these attributes is a way to assess which human and natural systems are most susceptible [30,31]. Comprehensive coastal vulnerability assessments and mapping can integrate social, economic and physical vulnerability with spatial analysis of natural hazards for local place-based investigations [31]. Recently, Bukvic et al. (2020) provided a thorough and systematic review of coastal vulnerability assessment and mapping research. The authors found that, “most Coastal Vulnerability Mapping Assessments (CVMAs) are conducted at a local level using a range of methodologies, often with limited inclusion of social considerations and limited discussion of policy relevance” [30] (page 1). The authors found that many CVMAs were focused on ecological variables or on the social variables with fewer integrated or comprehensive assessments [30]. The most frequently used social variables in CVMAs were from the Social Vulnerability Index (SoVI) and included indicators of vulnerability such as age, gender, race, socioeconomic status, immigrants, and homelessness [32]. While citing a growing demand for vulnerability assessments, Buvik et al. (2020) suggest future CVMA should (among other recommendations): customize the methodological approach to match place-based needs, take a holistic perspective to include interdisciplinary perspectives, carefully consider policy-making processes and data needs, and include stakeholder participation.
To achieve these goals, there is a need for improved methodologies for community risk and impact assessments that acquire and then integrate stakeholder values and facilitate a two-way dialogue and exchange of information [12,33,34,35,36,37]. Stakeholder involvement is critical to accumulate and document local knowledge as an input and part of a co-production of knowledge that represents the diversity of values and perspectives on impacts and potential climate adaptation strategies [12,35,38,39,40]. Incorporating stakeholder opinions in the planning process has been reported to increase support for outcomes and trust in management while reducing tensions between stakeholders and managers [41,42,43,44,45]. The level of stakeholder participation can vary from coordination to collaboration through to joint actions (Basco–Carrera). It can be particularly beneficial to capture these stakeholder preferences and landscape values spatially to facilitate their comparison with other spatial management information such as biological and ecological data and inundated areas based on sea level rise projections [13,46,47,48,49]. Frequent constraints to collecting stakeholder participation include a lack of time, money, expertise, and the relevance and timeliness of the information [7]. Additionally, unique barriers can occur along the different phases of planning including the understanding, planning and management phases [50].
Public Participation Geographic Information Systems (PPGIS) has become a popular method for the spatial collection of stakeholder knowledge of landscape values for policy integration [51,52], is identified as a useful tool for coastal resource managers [53], has been cited in the CVMA literature as an important tool [30,31,38,41], and as a participatory valuation method for ecosystem services [54]. The central tenet of this method is that it allows participants to directly identify the locations of places across a landscape they value that can then be digitized into a GIS database for spatial analysis [55]. The values that participants identify on maps include items such as aesthetic, economic, recreation, biological, life-sustaining, spiritual, historic, and cultural, among others [51,56]. The methods of implementation have varied in PPGIS studies using qualitative, quantitative and mixed method studies [56]. Qualitative methods using focus groups, stakeholder interviews, or workshops allow participants to identify and define landscape values that are important to them and collect spatial data drawn on study area maps in the form of polygons [57]. Quantitative data collection utilizes traditional mail surveys or on-line formats and generally targets random samples of study area residents. These studies provide a list of landscape values with their definitions and ask participants to indicate on a map (frequently with sticker dots) the most important places for those associated values [51]. Thus, PPGIS inverts the frequently expert-led land use planning approach to spatial identification of important places to one that allows stakeholders to provide input on places they value using GIS software [58].
PPGIS studies have focused on a wide variety of natural resource management topics important for CVMAs including ecosystem services [59,60,61], coastal zoning [62,63,64,65], marine area planning [66,67,68], climate change and vulnerability [33,69], wildlife conservation [70,71], parks, tourism, and outdoor recreation [72,73,74], and development preferences [72,75]. There have been a number of studies assessing various qualitative and quantitative methodologies and identification of best practices [56,75,76,77]. The focus of much of this research has applied spatial analysis of landscape values [48,51]. Furthermore, many of the landscape values identified in this literature track closely with cultural values from the ecosystem services literature [56,78]. Brown and Fagerholm (2015) reviewed a full body of literature that has emerged with a focus on ecosystem services more broadly and cultural services in particular [79]. This body of literature provides the methodologies and background for the creation and integration of stakeholder spatial knowledge of landscape values and ecosystem services into a format conducive to climate vulnerability mapping (CVMAs) and resilience planning with local experts and policy officials [52,56].
Two participatory mapping studies that have directly addressed climate change have direct relevance to our project and potential application as a CVMA [33,80]. Raymond and Brown (2011) specifically addressed issues of climate change and sea level rise in South Australia using PPGIS [80]. The authors had participants identify locations for several landscape values and then had them identify places that they thought would be vulnerable to climate change by a future date. The climate-change-related hazards they had participants map included biodiversity loss, land erosion, brushfire, riparian flooding, storm surges, and sea level rise. The authors explored and quantified the spatial associations between participants’ landscape values and perceived risk and found that their perceptions of risk were partly driven by the values they held for the landscape [80]. Their results indicate, and the authors conclude, that identifying the suite of landscape values stakeholders hold and the places they are attributed to should be part of holistic comprehensive discussion of climate risk and land use planning efforts. The authors also suggest that future research should examine the correspondence between locally held landscape values and expertly assessed climate change risks [80].
Bitsura-Meszaros et al. (2019) designed a study with stakeholder engagement as the primary goal [33]. The authors used multiple sequential participatory GIS methods to examine stakeholder perceptions of climate risks to recreation-dependent communities. They used purposeful sampling to identify stakeholders with interest in and influence over local climate adaptation planning such as municipal officials, industry representatives and state and federal management agency employees [33]. Stakeholders were given a pre-survey with a mapping component where they were to identify three categories of places that they believed were susceptible to climate change: built infrastructure, natural amenities, and recreation destinations. Participants were also asked to explain why they felt these areas were susceptible to climate change. Stakeholders then participated in two focus groups where the results (density analysis) of the pre-survey mapping exercise were used to guide further discussions on risk severity and risk thresholds. The authors reported that the exercises generated productive and constructive discussions in the focus groups and that the maps helped to facilitate two-way dialogue between scientists and stakeholders. They also noted that while the pre-survey analysis from their purposeful sample was not generalizable to the larger population, the maps proved to be a valuable tool for discussion. The authors conclude with suggestions for future research including a tighter focus on focus group questioning and relating impacts to specific climate-related stressors [33].
The objective of our study is to assess the perceived locations of a range of landscape values, ecosystem services, and development preferences held and identified by the general public in the Apalachicola Bay region in Florida and the Mobile Bay region in Alabama and to determine if those valued locations are vulnerable to several expert-predicted scenarios of inundation from rising sea levels. These data are designed as an additional layer to complement expert analysis traditionally collected for CVMA. Our novel contribution is that we use PPGIS as a method to integrate stakeholder’s local knowledge with expert assessments of sea level rise as part of the vulnerability assessment. Our central research question was: Can PPGIS mapping be used to identify places of importance to the general public in a way that can identify which of those areas are vulnerable to different scenarios of sea level rise? We selected a variety of types of landscape values, ecosystem services, wildlife habitat and development preferences found in the PPGIS literature to examine our question for broad applicability. We use two study areas to test the utility of PPGIS to contribute to CVMA in various social and ecological contests. Based on previous research using PPGIS, our expectation is that it will effectively identify unique areas of importance on a variety of topics across these different contexts. While we were uncertain about which specific places would be highlighted by participants as being important for each topic, and thus which important places and topics would be most vulnerable to sea level rise, we conjectured that sea level rise would significantly impact the important places differently for each landscape value and differently across three sea level rise scenarios.

2. Materials and Methods

2.1. Study Area

This study compares two areas of similar extent along the U.S. Gulf Coast dominated by relatively large bays: the Mobile Bay region, Alabama and the Apalachicola Bay region, Florida (Figure 1). The Mobile Bay study area was 11,932 km2, which included nearly all of Mobile and Baldwin counties, AL. The Apalachicola Bay study area was slightly smaller, at 9869 km2, and included the majority of Gulf and Franklin counties and a small portion of adjacent Liberty County, FL. Both study areas include sizeable areas that are protected at both the state and federal levels, and each include a National Estuarine Research Reserve (NERR) site: Weeks Bay NERR, AL and Apalachicola Bay NERR, FL. Both study areas have extensive coastlines and low-elevation coastal areas that are predicted to be vulnerable to inundation as a result of sea level rise. However, the two study areas differ considerably in their populations. The two counties that comprise the Mobile Bay study area (Mobile and Baldwin counties) have a combined population of 599,294, including the Mobile Metropolitan Statistical Area, which is inhabited by 412,992 people [81]. Conversely, the total population of Gulf and Franklin counties (Apalachicola Bay) is only 27,427 [81], and includes some of the last remaining sizeable stretches of undeveloped coastline in the state of Florida. We use two study areas to demonstrate the utility of PPGIS to contribute to CVMA in various social and ecological contests.

2.2. Data Collection

We mailed 1971 survey packets to randomly selected residents of Gulf and Franklin counties, FL. The number of residents selected per county was proportional to its percentage of the total population (Gulf County 58%, Franklin County 42%). We mailed 988 randomly selected residents in Mobile and Baldwin counties in Alabama, also reflecting their population distribution (Mobile County 69%, Baldwin 31%). We used a modified version of the Dillman four contact approach to distribute these surveys [82]. Residents of the four counties were randomly selected and sent a pre-notice letter informing them of their selection for participation in the study and providing them with information about the objectives of the study and what would be asked of them. Two weeks later, participants were mailed a survey packet, including a questionnaire and PPGIS mapping activity. After an additional two weeks, participants who had not yet returned their questionnaires and maps were sent a reminder postcard. Finally, after another two weeks, participants who had still not responded were sent a final reminder letter.
The survey packet included a questionnaire and PPGIS mapping activity. In the questionnaire, participants were asked about their length of residence and knowledge of places in the region, opinions on a range of natural resource management issues, and socio-demographic and economic information. In the PPGIS mapping activity, participants were asked to use a set of color-coded 0.635-cm sticker dots to identify places on a map of the study area that they thought were important for a range of natural resource management topics [51]. Our topics included three of the traditional landscape values/cultural services (economic/livelihood, recreation/tourism, historic), two ecosystem service regulating values (storm protection, flood protection), two specific wildlife conservation values (sea turtles, wading birds), and two planning preferences (no development, for development) (Table 1). Only five stickers were provided for each topic, forcing participants to prioritize their identification of important places and minimizing the ability of a few highly engaged individuals from identifying large numbers of places, which might skew the data. Participants did not have to use all the stickers. The maps used were 60.96 × 91.44 cm true-color aerial imagery of the region at a scale of 1:136,000 with cities, major roads, and protected areas identified to provide spatial references for the participants.

2.3. Data Analysis

Each returned map from the PPGIS activity was digitized as a separate layer into a GIS database using the technique of heads up digitizing. Heads up digitizing is the process of adding points to the digital map to correspond to the stickers on the physical maps as closely as possible [83]. To reduce digitizing error, we set the digital map at a 1:1 size ratio with the physical map during the digitizing process. Each point in the GIS database was coded to identify which topic it represented. We then were able to identify the number of points used by participants to identify places for each topic. The percent of available points used by respondents (you did not have to use all the points) for each value is presented in Figure 2.
To determine where participant-identified points for each value clustered spatially on the landscape, we performed a kernel density analysis [84], which uses a moving window approach to “fit a smoothly curved surface (grid) over each point producing a circular area (kernel) of a certain bandwidth (or search radius)” [85] (p. 463) to create a density grid for standardized comparison between layers with different numbers and spatial distributions of points. We used a 3000 m search radius and 500 m grid cell size to construct the kernel density grid [76]. Higher kernel density values represent greater levels of respondent consensus about which places are important for that topic [85]. For this study, we used a 0.67 kernel density threshold for identifying hotspots, which represent areas with significant levels of point clustering and thus, respondent consensus, meaning that the areas with the highest 33% of the kernel density values were included in the hotspots [76]. This analysis allowed us to determine which places in the study area were most often identified by participants as being important for each topic (Figure 3). This is in contrast to other statistical approaches, such as Ripley’s k function [86], which describe patterns of point density in the landscape, but do not produce location-specific data, such as places on the landscape where patterns of point clustering occur [79]. While an assessment of all participant-identified points for a landscape value can provide insight into the full scope of respondent preferences, hotspots highlight areas with high levels of stakeholder consensus, which helps management to prioritize areas with high support for that action relating to that value. Figure 4 presents data for the total area covered by the hotspots for the different topics in each study area. Figure 5 is an example of the spatial distribution and an outline of both the points and hotspots for outdoor recreation.
Finally, we assessed how sea level rise might impact places that participants identified as being important for each topic. We analyzed this by developing a map highlighting land area that is projected to be inundated by 2100 using three different scenarios describing sea level rise projections, the first being the lowest likely Scenario (1), which is a 0.3 m rise in sea level, the second being an average of the lowest and highest likely scenarios, which is Scenario (2), a 0.9 m rise in sea level, and the third being the highest likely scenario, which is Scenario (3), a 1.8 m rise in sea level [6]. We used a modified bathtub-type model, which also accounts for hydroconnectivity in identifying flooded areas, developed by the National Oceanic and Atmospheric Administration’s (NOAA) Coastal Services Center to identify land in the study area that would be inundated using each of these scenarios based on elevation [17]. These models were developed using a mosaic of LiDAR-derived Digital Elevation Models (DEM) of the region, which all have no greater than 18.5 cm root mean square error (RMSE) in low relief terrain and 37.0 cm RMSE in high relief terrain, along with a tidal surface model that accounts for the spatial variability in the tides. However, this model does not account for erosion, subsidence, or changes in hydrodynamics. Thus, land with an elevation of less than 0.3, 0.9, and 1.8 m that was adjacent to water or other inundated land was considered to be inundated by sea level rise (Figure 6). Additionally, this model does not account for extreme weather events, such as storm surge and hurricanes, which could also result in the inundated area being underestimated. Thus, this sea level rise model serves as a relatively conservative estimate of which areas might be flooded under different scenarios. The model also does not account for waves, which are a key source of uncertainty in coastal flooding models that can have a greater effect on model flood results than greenhouse gas emission projections [87], which could reduce model accuracy. We used the NOAA model to predict which areas would be submerged by sea level rise under the three scenarios by classifying the land into four categories based on elevation: Scenario (1)—land with an elevation of less than or equal to 0.3 m—Scenario (2) land with and elevation greater than 0.3 m and less than or equal to 0.9 m—and Scenario (3)—land with an elevation of greater than 0.9 m and less than or equal to 1.8 m—and then land with an elevation of greater than 1.8 m which does not get inundated [6,17]. We then examined the number of participant-identified points for each topic that fell within this zone for each scenario (Figure 5). Similarly, we overlaid the hotspots for each topic with each of the sea level rise scenarios to determine the percent of the hotspots that fell within the inundation zone (Figure 6). Thus, we identified areas that were identified by participants as being important for a range of landscape values that are potentially the most vulnerable to direct impacts from sea level rise.

3. Results

We mailed 1971 survey packets to randomly selected residents of Franklin and Gulf counties, FL. However, 463 packets were returned due to being undeliverable by the U.S. Postal Service. Of the remaining sample population, 217 (14.39%) chose to provide answers to the questionnaire, with 89.86% (n = 195) of those electing to participate in the PPGIS mapping activity. The respondents who participated in the PPGIS mapping exercise identified a total of 8909 points for places in the study area that they thought were important for a range of natural resource topics. In Mobile and Baldwin counties in Alabama, we mailed 988 surveys, of which 75 (7.6%) were undeliverable. We received 242 surveys who completed the PPGIS mapping activity for a response rate of 26.5%. These respondents identified a total of 11,391 points for all the attributes combined. In both states, the responses overrepresented certain socio-demographic groups including Caucasians, males, those over 65, those with higher income and those with higher education (Table 2). Results from a selected number of attributes that represent the range of landscape values, ecosystem services, and policy preferences are presented along with the definitions used for these values and the total number of points identified by participants in Table 1.

3.1. Inundation Results

Using the NOAA model to illustrate which land is likely to be submerged by sea level rise [6,17], we found that 2.5% of the land in the Mobile Bay study area and 3.5% of the land in the Apalachicola Bay study area would be submerged with a 0.3 m rise in sea level for scenario 1. Additionally, 6.1% of the land in the Mobile Bay study area and 7.1% of the land in the Apalachicola Bay study area would be submerged with a scenario 2, a 0.9 m rise in sea level. For scenario 3 with a 1.8 m rise in sea level, 8.16% of the land in the Mobile Bay study area and 10.8% of the land in the Apalachicola Bay study area would be submerged (Figure 6).
The total hotspot areas (km2) that were calculated for different landscape values and for the different study areas vary substantially (Figure 4). This is a reflection of the different social and ecological context for each analysis and is expected. The percentage comparisons of points and hotspots inundated under the different sea level rise scenarios provide analysis of the relative impact across the landscape values and across the study sites. However, a small percentage impact on a valued area that can only be provided by small number km2 can be meaningful due to its scarcity, but a small percentage impact on a large valued area can also be impactful because so many km2 are impacted. We present both the percentage data and the km2 information as managers can use each to make their conservation recommendations as the topic and context requires. Both the point and hotspot analyses provide us quantifiable assessments of impacts of sea level rise on terrestrial areas of importance for different values. The points give us reference to all the areas identified by study participants while the hot spots identify those areas with the most consensus.
We overlaid the PPGIS points with three sea level rise scenarios. We determined that sea level rise will lead to the submergence of many of the places identified by participants as being important for natural resource management—in particular, places that provide important watershed services, such as storm protection and flood protection (Figure 7). The data show that a 0.3 m rise in sea level will have a minimal impact on many of the valued places, while higher rises will have a much more significant impact, as expected. We also overlaid the kernel density hotspots with the three sea level rise projections to determine the impacts of sea level rise on the places with the highest level of participant consensus about their importance (Figure 8). Similarly, we found that a 0.3 m rise in sea level had very little impact on the hotspots, but that greater rises in sea level did inundate large portions of the hotspots for most items. When there is a higher percentage of the points inundated compared to the percentage of hotspots at the different scenario levels, that signifies that more of the non-consensus points fell in lower lying areas (and vice versa). While the level of impact varied as expected across the three sea level rise scenarios, the impact and scale of impacts was different across each of the different values.
For the following section, Mobile Bay, Alabama will be identified as MB and Apalachicola Bay, Florida as AB. The total hotspot area is presented on Figure 4, the point inundation percentages in Figure 7 and the hotspot inundation percentages in Figure 8. Higher percentage point and hotspot inundations indicate higher vulnerability to sea level rise for each landscape value. The analysis considers only terrestrial points and hotspots.

3.2. Economic/Livelihood

The total terrestrial area that provides economic and livelihood value varied significantly between the study sites, with the MB study identifying nearly double the terrestrial area than the AB study. As seen on the maps, this is, in part, due to the fact that much of the economic area mapped in Apalachicola was marine points, attesting to the heavier reliance on the bay for their livelihood (Figure 9a). While scenario 1 sea level rise impacts are in the low single digits for both points and hot spots, a scenario 2 rise brings the percentage inundated to near 15% in AB and 10% for MB. Nearly a quarter of the total areas identified as hot spots in both study sites are inundated under scenario 3. Importantly, several areas identified as important economically in MB are on the barrier islands that are already significantly impacted under Scenario 2.

3.3. Recreation/Tourism

Both study sites identify the barrier islands and immediate coastal settings as key for this landscape value and all are significantly impacted (Figure 9b). Areas identified as important for recreation and tourism follow a similar rise in inundation across the scenarios, but at a steeper rate. Approximately 20% of recreation areas are submerged with Scenario 2 (0.9 m) of sea level rise using both points and polygons. At 1.8 m or Scenario 3, approximately 40–45% of lands providing this value are lost. In AB, a higher percentage of the recreation points are above the highest water line compared to the hotspots, indicating that the more dispersed recreation areas identified are more inland. The reverse is true in MB.

3.4. Historic

Historic area hotspots are concentrated in more urban areas and on forts or historic military sites, some of which are on barrier islands (Figure 9c). While only a few hotspot areas or points are inundated in Scenario 1, approximately 10–15% are under Scenario 2. At the highest sea level rise, approximately 25% of hotspots are inundated in both study sites. An additional 10% of dispersed points identifying other historic areas are lost to the sea in MB at this highest level, indicating that the impact of historic areas may be higher than an assessment of only hotspots might suggest.

3.5. Watershed Services

Two watershed services were analyzed, storm protection and flood protection. Participants primarily identified the barrier islands as critical storm protection in both study sites (Figure 9d). In AB, Scenario 1 sea level rise did not have much impact on the land inundated (~5% or points or hotspots), while the impact was significant in MB (~15–17% of points and hotspots). By Scenario 2, these values rise rapidly into the 20s for AB and low 30s for MB. At the highest level scenario 3, 72% (AB) and 61% (MB) of hotspots were inundated. For both study sites, the percentage of points submerged was less than the hotspots, indicating that many places identified as storm protection were still above water even at the highest level. Many of these points identified inland forests as important for storm protection.
Flood control hotspots were identified at the mouths of rivers entering the bays in both study sites and covered the least amount of physical area of any of the landscape values measured (Figure 9e). The lowest percentage of points were used by stakeholders to identify this variable, indicating that participants had less confidence in locating this value or did not find many places in the landscape that provided that value. Understandably, flood control areas were quickly inundated under even the lowest Scenario 1, with nearly a fifth of the points and 28% (AB) and 48% (MB) of the hotspots under water. There are significant differences in the points and hotspot measures for this value as the points were much more spread out up the rivers and along the banks and into forested areas further inland for both sites. While over half of all points were submerged under Scenario 3 in both sites, 90% (AB) and nearly 100% (MB) of flood control hotspots were under water.

3.6. Wildlife

Two coastal wildlife groups were considered for this analysis, wading birds and sea turtles. Most of the points and the hotspots for sea turtles are located on the barrier islands and these measures correspond cleanly (Figure 9f). While minimal impact was recorded under Scenario 1, by Scenario 2 nearly a quarter of all hotspots are submerged. By the highest sea level rise, nearly 60% of hotspot and point data for both sites are submerged. Site identified by respondents as important for wading birds are also significantly impacted (Figure 9g). Scenario 1 indicates that 15–20% of points and hotspots would be inundated by the smaller sea level rise. The points and hotspot indicators tend to separate, with a lower percentage of points being submerged under the next two scenarios, indicating that more dispersed points are on higher ground than the hotspots. By Scenario 2, over 50% of the hotspots in both study areas are submerged, while 82% (AB) and 74% (MB) are under Scenario 3.

3.7. Development/No Development

Participants were asked about areas where they think future development should occur and where it should be curtailed (Figure 9h). The barrier islands were primary places identified for no future development for both study sites. Approximately, 7–10% of points and hotspots identified as no-development areas would be submerged by Scenario 1. The points and hotspots remain fairly consistent in terms of percentages for Scenario 2 with 29% (AB) and 35% (MB) inundated. Scenario 3 indicates that 70% (AB) and 67% (MB) of hotspots would be submerged. The lower percentages of points under water in this scenario indicates that many more points for non-development identified areas for conservation are a bit further inland. The high rate of inundated land in the no-development zone is likely a good thing since it indicates that participants do not want more development right on the waterfront where the risks of sea level rise are the highest. The locations where participants wanted development to happen also identify a positive trend in that they are mostly located away from the waterfront (Figure 9i). The consensus hotspots only have 7% (AB) and 5% (MB) as submerged even under the highest seal level rise, scenario 3. There is more diversity when points are measured, with 11% (AB) and 17% (MB) of points submerged under the highest sea level estimates. This indicates that there are still individuals preferring development (especially in MB) in areas that are more vulnerable to sea level rise.

4. Discussion

A large body of the PPGIS literature supports the ability of the general public to spatially identify places that are important to them for a variety of landscape values [56], ecosystem services [49,59,61,79], wildlife conservation [70,71], coastal planning and zoning [33,63,65], and development preferences [72]. This research reaffirmed this approach to local knowledge development by identifying unique places that the general public have selected for this wide variety of different types of valued places in two coastal zones: Mobile Bay, Alabama and Apalachicola Bay, Florida. These important places were compared with three scenarios of sea level rise using the National Oceanic and Atmospheric Administration’s (NOAA) Coastal Services Center models to identify land in the study area that would be inundated [6,17]. This comparison allowed the construction of Coastal Area Vulnerability Maps (CVMA) that identify the areas that are important to local stakeholders which are the most vulnerable to sea level rise. We were successful regarding our central objective of this project and developed a CVMA integrating local knowledge of important places with expert assessments of sea level rise. Our overarching research question regarding the utility of PPGIS to identify places of importance to the general public that would be vulnerable to different scenarios of sea level rise was answered affirmatively: the level of impact varied across the three sea level rise scenarios and the impact and scale of impact was different across each of the different valued areas.
The barrier islands in both study sites were identified as important for a number of different landscape values: economic and historic in MB, recreation, storm protection, and wildlife conservation in both MB and AB. These islands are particularly vulnerable to sea level rise. Barrier islands do provide physical protection from storm surges, and their potential loss, in part due to sea level rise, is of great concern. In some areas along the Gulf coast such as Louisiana, there is active submergence and current loss of these islands [22]. Future loss of these barrier islands along Mobile and Apalachicola Bays would certainly represent the loss of an important ecosystem service in terms of inland storm protection, subsequent flooding, and maintaining bay salinity regimes important to oyster fisheries (economic livelihood values identified in the bay). Even without complete barrier island loss, sea level rise and increasing tidal connections are expected to change the hydrodynamics of bays along the Gulf coast, thus affecting circulation, sediment transport and other important processes [88]. We should view the impacts registered under our three sea level rise scenarios as the minimum impacts to the landscape that they value for these reasons.
There is also continued concern regarding the loss of important wildlife habitats that will occur due to sea level rise. Our analyses showed that sea level rise would directly affect both sea turtle and wading bird habitats. Nesting habitats for both animal groups are expected to be lost or altered and the loss of barrier islands, sandier shorelines, and other coastal environments through increased erosion and inundation has been identified as a threat to sea turtles [89] and wading birds [90]. A recent PPGIS study specifically focused on important wading bird habitats in the Mobile Bay region showed that public participants recognized many (but not all) of the important habitat features of the region [90]. These areas identified that wading birds’ hotspots were affected in particular, even at the lowest sea level rise scenario. Coastal forests associated with the delta of both bay systems may be particularly vulnerable. Similar modeling exercises have yielded that areas such as greater Mobile Bay and Apalachicola Bay regions may be under severe risk for sea level rise impacts. In analyzing their SLAMM results in five different regions along the Gulf of Mexico, Geselbracht et al. (2013) predicted the Mobile Bay region would lose the greatest amount (41,147 ha) of coastal forest under a 1-m sea level rise scenario [91]. As distinguished here, most of this would be associated with increased tidal flooding in the Mobile-Tensaw River delta that would impact the tremendous freshwater biodiversity there. Further, this study focused on direct impacts caused by lands altered by inundation. The local habitat for most organisms is also dependent upon sustaining other ancillary and supporting habitats in the surrounding area as well, and indirect impacts to various coastal organisms is likely even when not directly impacted by increased inundation.
The most common social variables used to identify populations and social systems vulnerable to sea-level rise and other natural hazards in CVMA are built infrastructure, population, demographics, and socioeconomic factors [30,31,32]. These social items are relatively easy to conceptualize and visualize spatially [30]. While natural areas are considered important for the ecosystem services provided in CVMA [31], they are not often considered as vulnerable areas for conservation of other dimensions of social importance [30]. PPGIS mapping of landscape values provides an opportunity to identify a wide variety of indicators of importance (built and natural) to local communities beyond the traditional CVMA models [34,56]. The examples in this manuscript include local perceptions of areas important for economic, historic and recreation values, but PPGIS can also be used to identify other landscape values/cultural services such as areas providing aesthetics, spirituality, sense of place, and cultural heritage [56]. Identification of these types of cultural services and socially important areas for vulnerability mapping is not possible without eliciting information from stakeholders and the general public. Furthermore, many of the areas identified for cultural services are natural areas—natural areas with social importance that might not be identified in traditional CVMA. A number of PPGIS studies have focused on the full suite of ecosystem services using a variety of methods that can act as guides for this process [59,60,61,63,79].
While it is clear that many areas valued for cultural services require stakeholder input, it can be asked why one would want to collect general public perceptions of areas valued for watershed services and other ecological functions or biodiversity habitat when ecologists and biologists can provide specific scientific data and spatial delineations of these landscape attributes. While it has been shown that the general public can identify these natural areas with substantial accuracy, they often do not identify all of the important areas for these services [70,71,92]. However, the accuracy of the identification of landscape values and other cultural and ecosystem service are considered as accurate enough to contribute to broad based conservation planning [93,94]. A participatory layer of a CVMA should be combined with expert-derived maps for a full vulnerability analysis. Expert-derived priority areas for watershed, habitat, local infrastructure (recreation and tourism) and others are still essential. That said, a critical benefit of having stakeholders identify valued landscapes is that understanding public knowledge and perceptions regarding the ecology and biology of a region can help with buy-ins on conservation programs regarding locations where both the public and scientists agree, for targeting outreach and education where they differ, and for the co-development of knowledge [70,92]. This approach can also increase efficiency in the conservation planning process by allowing stakeholder preferences to be overlaid with ecological data, such as habitat maps, to identify areas of alignment, which can be prioritized for conservation action and highlight areas where other stakeholder land use preferences might conflict with management [70]. Perhaps more significant is the opportunity for PPGIS to be a format or source for participatory governance and to integrate public spatial knowledge and reflect diverse perspectives [38,52]. The benefits of stakeholder engagement include increased public support, equitable accounting of risk, facilitating collaborative planning, the application of local place-based knowledge, trust, and credibility in the collaborative process in general [36,37], and as specifically applied to CVMA and coastal planning [28,31,33,41,65]. An advantage of PPGIS survey distributed to a random sample of stakeholders is that the information can be generalized as representative to the general public while stakeholder participation through focus groups and workshops cannot. Integration into policy making has been a long-sought goal of PPGIS, but too often it has not been achieved [56,79]. Recommendations to facilitate inclusion of PPGIS are to incorporate mapping activities early in the process, to do so as part of group-based planning and decision-making, and to use them as a foundation for two-way discussion as part of a deliberative process [28,56]. Within the CVMA literature, additional recommendations include taking a holistic approach to include interdisciplinary perspectives, using methods to match place-based needs, and carefully considering the policy process at the outset [30].
This manuscript is a proof of concept for collecting and synthesizing local knowledge through PPGIS to develop a CVMA for sea level rise, however, there are some specific recommendations for future research and application of these methods. While we presented a wide range of landscape values, ecosystem services, and development preferences, an initial scoping exercise with policy stakeholders would help to ensure specific coastal place-based issues and values are elicited in the general public PPGIS mapping effort [30]. In their article focused on understanding adaptation barriers, Moser and Ekstrom (2010) identify existence of signal, or detecting a problem, as one of the first phases of understanding for addressing climate change adaptation [50]. A holistic PPGIS mapping exercise (from the scoping phase combined with insights from the past PPGIS literature) would ensure that there would be data (the signal) on community perspectives on landscape values, ecosystems services, wildlife conservation, development preferences or any other locally relevant management issue. The research presented by Bitsura-Meszaros et al. (2019) outlines methods to use PPGIS data as input to policy stakeholder (resource managers, agencies, planners, academics, etc.) focus groups where the presentation of the maps was found to facilitate discussion and debates over trade-offs. The PPGIS maps used in their focus groups were prepared by those same policy stakeholders, and therefore lacked generalizability to the larger community [33]. We would suggest that PPGIS data collected from the general public like the one presented in this paper would provide a more representative and diverse base of local knowledge for focus group discussions by policy stakeholders. Similarly, it could provide a representative base layer for policy stakeholder workshops that compare different scenarios of sea level change like those conducted along the Florida Coast [28]. Selecting to highlight just the overlap data between different topic hot spots (or points) and sea-level rise scenarios would allow discussion about specific spatial contexts and can be done with these data. Additionally, topic areas that are spatially compatible for conservation or likely to lead to conflict (i.e., area identified as important for flood control and as an area for future development) can be identified [95]. The type of data collection and presentation presented here would help to facilitate a two-way discussion at the beginning of the planning process [12]. Other exemplary participatory CVMA work has been done designing interactive visualizations of vulnerability and sea level rise maps has been conducted along the Gulf of Mexico by Stephens and colleagues [13,29]. These authors worked directly with policy stakeholder groups to design their interactive visualization tools to best accommodate community planners and policy makers. The lessons they present from participatory development of their interactive visualization tools and understanding of community planning and adaptation activities [29] could be applied to better incorporate locally gathered PPGIS data and make it more policy relevant. While focus groups with policy stakeholders (resource managers, agencies, planners, academics, etc.) are a critical form of two-way dialogue, using PPGIS to co-develop an initial data layer representative of the perspectives of the general public could enhance broader credibility, salience, support, power and trust by the local community (puts everyone in the room where it happened) [50]. In this way, the general public becomes a co-creator of knowledge instead of simply an audience receptive to planning efforts.
There are a number of limitations to this study for the sea level rise modeling and the PPGIS data collection and analysis. While this assessment highlighted areas and associated respondent-identified important places that are most vulnerable to inundation from sea level rise, it is important to note that the actual sea level rise by 2100 may not coincide exactly with these projections at specific locations, but presents an idea of what places might be most vulnerable. Similarly, sea level rise will not affect all mapped topics evenly. Additionally, sea level rise could have indirect impacts on places not listed as being inundated, for example, a place deemed important because it represented inland forest might become a coastal forest or even wetland, and thus not provide the same services. Furthermore, data may not be completely representative of the opinions of all Apalachicola Bay or Mobile Bay residents due to older, male, Caucasians who were slightly more well-off responding at higher rates than other demographics. The response rates were relatively low, but not uncharacteristic of PPGIS surveys [75], and increasingly of surveys in general [96]. The size and shape of the hotspots in this study were also influenced by the use of a 3000 m search radius and 500 m grid cell size for calculating kernel densities and 0.67 percentile threshold for defining hotspots [84]. The accuracy of the LiDAR data also could impact the results of this study. Furthermore, only using elevation data to project submergence due to sea level rise does not account for additional factors, such as increased erosion, subsidence, vegetation types, or man-made preventative structures, all of which could have effects on which areas are inundated [30]. While the focus of this paper was to identify the effects of sea level rise on stakeholder-identified places of landscape value, future research should identify correlations between landscape gradients (percent forest cover, distance from roads, etc.) and PPGIS data to determine how participant values are shaped by landscape features.

5. Conclusions

Agencies involved in efforts to address the sea level rise threat and increase community resilience rely a variety of tools and analyses to increase awareness and knowledge of risks while also promoting the adaptation of strategies to preserve natural and cultural resources along the Gulf of Mexico. The state of Florida is largely recognized as being most engaged in sea level rise planning across the Gulf of Mexico region [97]. A recent report from the Florida Department of Environmental Protection [98] emphasized that municipalities planning for sea level rise should understand their adaptive capabilities that include regulatory and planning, administrative and technical, fiscal and infrastructure. Once sea level rise risk to resources is understood, options may include protection, accommodation, avoidance, or retreat from vulnerable areas. Stakeholder workshops along the Gulf of Mexico have yielded potential planning and action recommendations to counter sea level rise including buffering shorelines through local land acquisitions shoreline while national or regional strategies may include insurance reform for building outside future impact areas [91]. Several reports have been generated highlighting the potential impacts of sea level rise on various coastal communities and emphasizing the trade-offs between various sectors of society that depend on coastal resources [97,99]. Funding for sea level rise mitigation and planning initiatives has been a primary concern [97]. Natural resource planners anticipate some challenges in public participation and possible conflict with plans to manage coastal areas for sea level rise [13]. This is encouraging, as planners and stakeholders engage with the public to emphasize plans to counter sea level rise impacts to conserve habitats.
Coastal Area Vulnerability Maps can be easily understandable but there is need for further social and ecological integration, as currently there is no agreed upon method for selecting which social and ecological indicators should be measured [30]. The use of diverse methods is suggested and PPGIS may be useful tool for local discussion and planning for sea level rise and climate change [31,80]. Few PPGIS’ offer specific policy recommendations or are integrated early enough in the decision process to be influential [56]. A careful consideration of policy relevance and the utility to policy stakeholders needs to occur throughout the process [13,30]. We suggest that the process demonstrated here, and the vast body of the literature on PPGIS, can help to further the use and application of local public participation in the planning process for CVMA.

Author Contributions

Conceptualization, W.C.M., C.C. and C.J.A.; methodology, C.C. and W.C.M.; software, C.C.; validation, C.C.; formal analysis, C.C.; investigation, W.C.M. and C.C.; resources, W.C.M.; data curation, C.C.; writing—original draft preparation, W.C.M., C.C. and C.J.A.; writing—review and editing, W.C.M., C.J.A. and C.C.; visualization, C.C.; supervision, W.C.M.; project administration, W.C.M.; funding acquisition, W.C.M. All authors have read and agreed to the published version of the manuscript.

Funding

The authors express their gratitude to the U.S. Forest Service (Grant # 10-JV-11330144-147) and the Mobile Bay National Estuary Program for providing original funding for this research.

Acknowledgments

The authors are grateful for the assistance with article preparation and revision provided by anonymous reviewers and by the editor. The authors also thank the residents of Mobile Bay, Alabama and Apalachicola Bay, Florida who elected to participate in our survey.

Conflicts of Interest

The authors declare no conflict of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results.

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Figure 1. Study Areas: Apalachicola Bay Region, FL and Mobile Bay Region, AL.
Figure 1. Study Areas: Apalachicola Bay Region, FL and Mobile Bay Region, AL.
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Figure 2. Percent of available points used by participants for each landscape value.
Figure 2. Percent of available points used by participants for each landscape value.
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Figure 3. Kernel density maps by landscape value.
Figure 3. Kernel density maps by landscape value.
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Figure 4. Hotspot area for each landscape value.
Figure 4. Hotspot area for each landscape value.
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Figure 5. Points and Hotspot Polygons with Recreation example.
Figure 5. Points and Hotspot Polygons with Recreation example.
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Figure 6. Sea level rise scenarios.
Figure 6. Sea level rise scenarios.
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Figure 7. Percent of terrestrial PPGIS points inundated under each sea level rise scenario.
Figure 7. Percent of terrestrial PPGIS points inundated under each sea level rise scenario.
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Figure 8. Percent of terrestrial hotspots inundated under each sea level rise scenario.
Figure 8. Percent of terrestrial hotspots inundated under each sea level rise scenario.
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Figure 9. (a) Economic value hotspots. (b) Recreation value hotspots. (c) Historic value hotspots. (d) Storm protection hotspots. (e) Flood Protection hotspots. (f) Sea turtles hotspots. (g) Wading birds hotspots. (h) No development hotspots. (i) Development preferred hotspots.
Figure 9. (a) Economic value hotspots. (b) Recreation value hotspots. (c) Historic value hotspots. (d) Storm protection hotspots. (e) Flood Protection hotspots. (f) Sea turtles hotspots. (g) Wading birds hotspots. (h) No development hotspots. (i) Development preferred hotspots.
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Table
Table 1. Value definitions, points, and value hotspot area.
Table 1. Value definitions, points, and value hotspot area.
ItemDefinition:
These Places Are Important to Me…		Number of Points Used
ApalachicolaMobile
Economic/
Livelihood		For the economic benefits they provide, such as timber, fisheries, or oil.634727
Recreation/
Tourism		Because they provide outdoor recreation or tourism opportunities.771955
HistoricBecause they are a significant part of human cultural legacy to me, others, and/or the nation.535805
Storm ProtectionBecause they provide protection and buffering against the effects of hurricanes and storm surge.598578
Flood ProtectionBecause they minimize flooding from rivers and streams.306319
Sea TurtlesMaintained for the conservation of sea turtles.636651
Wading BirdsMaintained for the conservation of wading birds (cranes, herons, egrets, etc.).611715
No DevelopmentPlease indicate places where any future development should be prohibited.594665
Residential DevelopmentPlease indicate places where you think residential development could occur with a well-designed plan.423485
Table
Table 2. Respondent Demographics.
Table 2. Respondent Demographics.
CategoryMobile BayApalachicola Bay
2010 Census DataSurvey Respondents2010 Census DataSurvey Respondents
% Male48%64%53%70%
% Female52%30%47%30%
% Caucasian69%91%84%91%
% African American27%7%12%4.5%
% Persons 65 years and over14%29%25%51%
% High school diploma84%96%83%97%
% Bachelor’s degree22%48%17%43%
Median household incomeUSD 43,832USD 50,000–74,999USD 43,686USD 50,000–74,999

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Morse, W.C.; Cox, C.; Anderson, C.J. Using Public Participation Geographic Information Systems (PPGIS) to Identify Valued Landscapes Vulnerable to Sea Level Rise. Sustainability 2020, 12, 6711. https://doi.org/10.3390/su12176711

AMA Style

Morse WC, Cox C, Anderson CJ. Using Public Participation Geographic Information Systems (PPGIS) to Identify Valued Landscapes Vulnerable to Sea Level Rise. Sustainability. 2020; 12(17):6711. https://doi.org/10.3390/su12176711

Chicago/Turabian Style

Morse, Wayde C., Cody Cox, and Christopher J. Anderson. 2020. "Using Public Participation Geographic Information Systems (PPGIS) to Identify Valued Landscapes Vulnerable to Sea Level Rise" Sustainability 12, no. 17: 6711. https://doi.org/10.3390/su12176711

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