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Article

Ecosystem Services and Vulnerability Assessments of Seagrass Ecosystems: Basic Tools for Prioritizing Conservation Management Actions Using an Example from Thailand

by
Ratchanee Kaewsrikhaw
1,
Tipamat Upanoi
2 and
Anchana Prathep
3,*
1
Department of Biology, Division of Biological Science, Faculty of Science, Prince of Songkla University, Songkhla 90110, Thailand
2
Marine and Coastal Resources Research Center (Central Gulf of Thailand), Chumporn 86000, Thailand
3
Seaweed and Seagrass Research Unit, Excellence Center for Biodiversity, Faculty of Science, Prince of Songkla University, Songkhla 90110, Thailand
*
Author to whom correspondence should be addressed.
Water 2022, 14(22), 3650; https://doi.org/10.3390/w14223650
Submission received: 27 September 2022 / Revised: 1 November 2022 / Accepted: 7 November 2022 / Published: 12 November 2022
(This article belongs to the Section Oceans and Coastal Zones)
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Abstract

:
Seagrass habitats are among the most valuable coastal ecosystems. They provide a wide array of ecosystem services (ES) that support the livelihoods of many people. However, seagrass habitats worldwide are at risk of being lost due to the alteration of coastal areas by many causes. Seagrass meadows around Thailand were assessed to evaluate their ecosystem services and vulnerability (VU) status. The ES and VU analyses could be used as basic tools to assess the status of individual seagrass meadows and to prioritize the action needed among several meadows. From 82 seagrass sites, the ES of seagrass habitats tended to be varied based on the areas of the seagrass beds. The vulnerability of the seagrass habitats was mainly influenced by the threat of boating accidents and the incidence of sedimentation. The final combined analysis suggested that a seagrass site at Ban Don (BD), in Surat Thani Province, should be the priority for intervention due to the importance of the ES provided at the site and the existence of a degree of threat from poor land-use management. This work allows us to understand more about the targeted management of seagrass ecosystems, which is very important for conservation and restoration because of its significant potential carbon offset.

1. Introduction

Seagrasses are flowering plants that are prominent in marine and estuarine environments [1,2] and distributed across a wide geographical range. They mainly inhabit the shallow waters along the coasts of every continent, except Antarctica [3,4]. Seagrass ecosystems are among the most valuable ecosystems on Earth [5], providing various goods and services that benefit environmental and human populations [6,7,8]. The ecosystem services (ES) of seagrass provide basic benefits, such as foraging and shelter areas for marine animals, especially during the juvenile life stages of commercially important fish and shellfish [9]. Thus, healthy seagrass meadows are globally recognized for their support for fisheries [10] and the food security of coastal populations [11].
As some of the most productive autotrophic communities on the planet [12], seagrasses have been reported to support high primary productivity [9]. Moreover, the structure of these plants helps to increase sediment deposition, stabilize sediment, and prevent coastal erosion [13,14,15]. Seagrasses can also enhance nutrient cycling and modulate biogeochemical processes [16,17,18,19]. Furthermore, as global warming and climate change begin to affect many organisms, seagrass habitats are considered major coastal carbon sinks, since carbon can be stored in both seagrass biomass and in the sediment of seagrass habitats [20,21,22]; healthy seagrass beds help to prevent the release of carbon back into the atmosphere [23], which has recently become known as blue carbon. The ecological importance of seagrass ecosystems is clearly no less important than the beauty of seagrass itself or its role as the habitat of economically valuable species or as an engine of tourism. The global economic value of seagrass/algae beds has been estimated at USD 28,916 ha−1 yr−1 [24].
Sadly, in recent years, many seagrass areas have been reported to be in decline. Large-scale losses have occurred as a consequence of rapid environmental change and the anthropogenic stresses induced by coastal populations [6]. Seagrass meadows are currently declining worldwide at a rate of 1.5% yr−1 [25]. This decline has resulted from various threats and places seagrass habitats under vulnerable conditions. Various kinds of threats potentially affecting seagrass ecosystems were suggested in previous studies. [25] reported that the main causes of seagrass decline were coastal development, poor water quality, and climate change. A two-decade study of seagrass–area change on Libong Island, Thailand, estimated the loss of seagrass area at 3.2% yr−1 between 2004 and 2009 and 0.6% yr−1 between 2009 and 2019 [26]. More effective management of seagrass ecosystems is necessary, regardless of whether these ecosystems are at risk of further decline or still in a healthy condition. To create policies related to this ecosystem management, the authors believe that all practitioners and stakeholders must employ the estimation and analysis of ecosystem services and vulnerability (VU) as a common language to improve the process of ecosystem-based management [27,28].
The assessments of ES and VU can be used to identify the overall view of a site. Both can show the main benefits provided by each specific area, as well as indicating the main anthropogenic threats experienced by seagrass meadows, which might cause the decline of plants. In real situations, in which time and resources are limited, these assessments could be basic management tools at the starting point from which to define priority areas for protection and to help identify appropriate actions in this regard [29]. In areas that have experienced losses that are considered difficult to overcome, the necessary improvements in environmental conditions could be designed to reduce these losses or induce restoration. This kind of analysis was previously carried out for Southeast Asian seagrass meadows by [30], whose analysis was conducted in seven seagrass sites from seven countries, including one site in Thailand. As part of mainland Southeast Asia, Thailand has coastal areas on both the Indian Ocean and the Western Pacific Ocean, which comprise numerous important seagrass meadows. The application of this analytical method to seagrass beds in Thailand would be very useful to identify the main ecosystem services or the anthropogenic threats to the area of interest. This could help to develop more robust conservation- or restoration-management strategies, if needed, for specific seagrass sites as the first step before searching for more details for initiating the action plan, especially given their potential for further carbon storage and carbon offset.

2. Materials and Methods

Data for the ES and VU assessment of 82 seagrass meadows across Thailand (Figure 1) were obtained from expert opinions of all research stations under the responsibility of the Department of Marine and Coastal Resources. The number of experts attending the workshop was around 30. Seagrass meadows were situated on both the Gulf of Thailand (50 sites) and the Andaman Sea (32 sites).
The scores for each site were given by specialists who work directly in each seagrass area and were based on their experiences and the data available in their research area. Data were obtained in September 2018 during a workshop on ecosystem services of seagrass ecosystems. The categories and criteria that guided the scores for ES and VU were adopted from [30], with some categories added from the reference in the VU assessment. The categories of ES and VU used are described in the following section.

2.1. Scoring of Ecosystem Goods and Benefits (ES)

Thirteen ecosystem goods and benefits were taken into consideration, classified into three major categories of service: (1) provisioning services, such as food and fisheries; (2) regulatory services, such as the regulation of the healthy climate and the prevention of erosion; and (3) cultural services, such as tourism, education, and scenic beauty. Some ecosystem services are presented in Figure 2a,b.
For each meadow, each ecosystem good and benefit was scored based on the significance of its contribution and the confidence level of the assessment. The significance of the contribution of each benefit was scored from 0 to 4, based on factors such as meadow size and the number and the type of species present. The condition of change of an area was classified at three levels, from −0.5 to 0.5, with −0.5 indicating a degraded meadow, 0 indicating a stable, unchanged meadow, and 0.5 indicating an improving meadow. The confidence level in the source of information for each ecosystem service was given from 1 to 3, with 1 indicating expert opinion or obvious, 2 indicating moderate-gray literature, and 3 indicating high-level, peer-reviewed research.
The ES score of each seagrass meadow was the summation of the scores for the significance of the contribution of all 13 goods and benefits. The final ES score for each site was based on the ES score awarded and the condition of the meadow, calculated as the summation of these two factors (ES score = Significance + Condition).

2.2. Scoring Threats and Vulnerability Analysis (VU)

To evaluate the VU of each seagrass meadow, 17 threats were taken into consideration and classified into five categories: (1) factors driving habitat loss, such as land reclamation; (2) pollution and nutrient input, such as runoff from urban and agricultural activities; (3) sediment input; (4) fisheries and mariculture; and (5) other commercial activities, such as shipping and boating accidents. The VU score of each meadow was compiled from five VU factors, which were spatial scale, frequency, functional impact, resistance, and recovery time. One additional threat was included in this study to suit the situation in Thailand: land-use change, which was added under the category of habitat loss. This study estimated all 17 threats compared with the 16 threats of the reference paper from which we adopted our methodology. In addition, this intensive study could provide a notable example for further implementation in other countries, which will be very important once the management and conservation priorities determined in this study are considered at the national level. The VU scores of all the threats were summed to give the final VU score for each seagrass site. Some threats are presented in Figure 2c,d.

2.3. Combined Analyses

To assess priorities for conservation and management, ES and VU scores from the previous section were used to perform the combined analysis. This combined analysis was conducted by ranking both ES and VU scores of all meadows from the lowest (rank 1) to the highest (rank 82). The final score was the value obtained by multiplying the ES and VU ranks of the same meadow. This value indicates the priority of each site and specific remedial actions. The priority for conservation was expected to be given to seagrass meadows that provided the most valuable ecosystem services and experience the greatest threats. This expectation acknowledged the concern that the loss of seagrass area in some sites could entail the loss of more valuable ecosystem services. Following the multiplication of ES and VU rankings, all sites were ranked from the highest to the lowest number. In these new rankings, the highest scores indicated sites that might have showed the most urgent need for management or conservation actions.

2.4. Statistical Analysis

Linear regression analysis was used to test the relationship between seagrass area and ES/VU scores. Data of the 82 seagrass sites were transformed using log(x + 1) as the best function to reduce the variance-to-mean relationship. Normality of data was quickly visualized using qq plot prior to performing the linear regression analysis. Principal component analysis (PCA) was also conducted on group study sites based on multiple VU (17 threats) scores given for each site. Both statistical analyses were performed using R Studio 2015.

3. Results

3.1. Scoring of Ecosystem Goods and Benefits (ES)

The scores were based only on the ES analysis. Out of the 82 seagrass sites, the 10 highest ES scores were from 16 seagrass meadows. Seven of these sites were in the Gulf of Thailand, and nine were in the Andaman Sea. The meadow which obtained the highest ES score, 39.50 points (with direction of change), was at Koh Samui (SM). The second-highest score of 35.00 points was given to a meadow at Koh Libong (LB). Two sites, at Koh Pa Ngan (PN) and Kung Krabaen Bay (KB), obtained the third-highest score of 33.50 points. All four sites were given the highest ES score for education and research, which is in the subset of cultural services. The fourth- to the ninth-highest ES scores ranged from 33.00 to 29.00 points, and the meadow which obtained the tenth-highest ES score, of 28.50 points, was at Makham Pom Bay (MPB) (Table 1). Twelve seagrass sites showed a positive direction of change, which indicates that the condition of the beds was improving. The positive direction of change ranged from +0.5 to +2.0, and the site which showed the highest positive direction of change was Bandon (BD), which also obtained the fourth highest ES score (33.00) and exhibited a positive change in all three ES categories of provisioning services, regulatory services, and cultural services. Meanwhile, the condition of three of the 16 sites showed no change, whereas one site showed a negative direction of change, which indicated that the meadow was under some degree of degradation (Figure 3). Among all 82 sites, Bang Jak was the lowest-ranked site, gaining the lowest ES score (11.00 points), having received 1 point for most of its services and 0 for spiritual and cultural wellbeing, education, and research (cultural services).

3.2. Vulnerability Analysis (VU)

These scores were based only on the VU or threats analysis. The 10 highest scores were from 13 seagrass meadows out of the 82 seagrass sites. Nine of the sites were situated in the Gulf of Thailand and four were in the Andaman Sea. Three seagrass meadows were in the highest rank: Thap Lamu (TL), Koh Loan-Yon Bay-Chalong Bay (KL-YB-CB), and Ban Pak Bara (BPB) were given the highest VU score of 33.00 points. The second-ranked and third-ranked sites were Na Thap (NT) and Pattani Bay (PB), with scores of 30.00 points and 26.87 points, respectively. The fourth-ranked to ninth-ranked sites were scored from 26.53 down to 23.33 points. The tenth-ranked sites, Pathio (PT) and Chala Lai Beach (CLB), demonstrated scores of 22.73 points. The main threats for the top three ranks were sedimentation, boating accidents involving grounding or propeller damage, land reclamation, and dredging. Sedimentation was the most frequent threat and was reported in 9 out of the 13 meadows. Some of the sites were affected by land reclamation, nutrient loading, urban or agricultural runoffs, untreated sewage, physical damage from fishing methods, and overharvesting. Of all 82 seagrass sites, Koh Khai Yai received the lowest VU score (0.93 points). Sedimentation was the only threat that was suggested as occurring in the area (Table 2). The scores for each threat reported in the 13 most vulnerable meadows are presented in Table 3.

3.3. Combined Analysis

The combined ES and VU scores of 82 seagrass meadows across Thailand showed that 12 seagrass meadows were classified in the 10 highest final-assessment ranks. From the highest- to the lowest-ranked, the 12 meadows were: Ban Don, Middle Songkhla Lake, Koh Pha Ngan, Pattani Bay, Lower Songkhla Lake, Koh Tha Rai, Koh Pha–Koh Prathong, Koh Yao Yai–Yao Noi, Paklok Bay–Koh Maprao, Pathio, Koh Tapao Yai–Tang Khen Bay–Makham Bay, and Thungka-Sawi. The 10 highest ranks in the final assessment included 13 sites, which were scored from 5850 points (rank 1) down to 3654 points (rank 10) (Table 4). The lowest-ranked site was Koh Khai Yai, with a combined analysis score of 3 points.

3.4. Relationship between Seagrass-Area Extent and ES/VU Scores

The ES score was influenced by the seagrass-meadow size. The ES score was significantly higher when the meadow area was larger (p < 0.001, R2 = 0.231, Figure 4a). The largest seagrass meadow (40.00 km2) was at Phang-Nga Bay (PB), which obtained an ES score of 30.50 points. The smallest seagrass meadow (0.002 km2) was at Koh Samet, which obtained an ES score of 20.00 points.
The VU score was also significantly higher when the seagrass-meadow area was larger (p < 0.05, R2 = 0.054, Figure 4b). The largest seagrass meadow (40.00 km2) at Phang-Nga Bay (PB) was not the site that gained the highest VU score (33.00 points), obtaining only 14.73 points. The highest VU scores were observed at Thap Lamu (TL), Koh Loan–Yon Bay–Chalong Bay (KL–YB–CB), and Ban Pak Bara (BPB). The seagrass meadow at Koh Samet gained a VU score of 15.00 points, which was not the lowest VU score.

3.5. Group of Seagrass Meadows Based on VU

The principal component analysis (PCA) of 82 seagrass meadows can primarily be grouped based on multiple VUs (17 threats) in the scores of each site. The individual PCA biplot included components 1 and 2. Dimension 1 (Dim1) and dimension 2 (Dim2) of the PCA explain 38.5% and 20.8% of the variation, respectively. Some of the seagrass sites with strong positive correlations with both Dim1 and Dim2 were seagrass beds from the Gulf of Thailand. Some of the seagrass sites that showed strong positive correlations with only Dim1 were the seagrass meadows from the Andaman Sea. However, some of the seagrass beds that only showed positive correlations with Dim2 could not be explained to any significant degree by Dim2 (Figure 5).

4. Discussion

Many criteria can be used to identify areas that require management actions. In this study, we used the analysis of ES and VU, which are criteria that have already been suggested for this purpose [30]. These analyses allow the separation of project objectives and actions in terms of ES or VU. Moreover, after multiplying the ES and VU ranking of the same site, the combined ES–VU rank can be used to indicate which seagrass meadows are in urgent need of management actions based on the final scores of the combined assessments. This discussion is focused mainly on the sites that were ranked among the 10 highest final ES scores, VU scores, and combined ES–VU score. Some of the lowest-ranked sites are also mentioned.
The ES scores indicate which seagrass sites provide the best ecosystem goods and benefits. Among the sites ranked as having the 10 highest final ES scores, Koh Samui (SM) was indicated as the first priority for the protection of its valuable ecosystem services. The highest ES score given to this site was for the cultural services of education and research, followed by regulatory and provisioning services. Koh Libong (LB) was the second-highest priority, while Koh Pha Ngan (PN) and Kung Krabaen Bay (KB) were the joint-third-highest priority, as both sites presented the same final ES score. The three highest-priority sites provided benefits in all categories: provisioning services, regulatory services, and cultural services. Furthermore, they gained the highest ES scores for the same types of ecosystem services. For these three highest-ranked sites, all the highest scores were given to the cultural services of education and research, especially the site at the Royal Development Study Center initiated at Kung Krabaen Bay. The many reports and research articles conducted in these meadows support the very solid confidence levels in the information that verified the scores they obtained. For example, [31] reported that a total of 38 fish species were found in seagrass beds at Kung Krabaen Bay, Chanthaburi Province, Koh Samui, and Koh Pha Ngan, Surat Thani Province. [32] described seagrass in a report on the payment for ecosystems services (PES). One action that the PES pilot project suggested could be used to lead to the provision of ES is producing organic fertilizer from seagrass. Dugong is one of key animal species to have been presented in the many studies conducted at Koh Libong, Trang Province, on the Andaman coast of Thailand. The area around Koh Libong supports foraging habitats for the largest population of dugong in Southeast and Eastern Asia [33]. Some publications investigated the seagrass beds in this area, focusing on the reproductive behavior of dugong and dugong feeding trails using drones [34,35]. Further studies on other animals living in seagrass ecosystems, such as sea cucumbers and the gastropod, Strombus canarium, were published [36,37,38]. Seagrass beds at Koh Libong were mentioned in a study related to carbon storage in seagrass ecosystems in Thailand [39]. Some information from the area of Kung Krabaen Bay, Chanthaburi Province, on the Gulf of Thailand coast, has been published, including information on benthic fauna biodiversity, hydrodynamics, and seagrass mapping using remote sensing [40,41,42].
When examining the direction-of-change scores, most of the sites presented some degree of improvement in their ecosystem services; a few meadows were stable, and only one seagrass site, Koh Sriboya (SBY), experienced degradation. Specifically, the Koh Sriboya (SBY) meadow demonstrated degradation in the provisioning of food (wild and farmed); this service was given a high score for its significance. The degradation of this meadow could have multiple causes, as suggested by the high VU scores obtained at this site. The anthropogenic threats that potentially influenced the negative direction of change for this site could arise from land-use change, nutrient loading, urban runoff, agricultural runoff, untreated sewage, sedimentation, or boating accidents. The seagrass meadows that were ranked 8th, 9th, and 10th in the ES ranking were Koh Tha Rai (TR), Middle Songkhla Lake (MSL), Koh Payam–Koh Chang (PY–C), and Makham Pom Bay (MPB).
Out of all the 82 seagrass meadows across the country, Bang Jak provided the fewest ecosystem services and received the lowest ES score. Most of the services provided there were considered to be in a stable condition of change but were rated as non-significant or negligible, while spiritual and cultural well-being/education and research were not assessed. Other services were given significance scores of 1 point. Although its meadow-size and ES scores showed a significant relationship, which implied that lower ES scores would be given to smaller meadows, Bang Jak was not the smallest seagrass bed studied. It was, nevertheless, still categorized as a small area of less than 1 km2 (0.20 km2). However, the small seagrass meadows did not always receive very low ES scores, as the data showed some degree of variance (Figure 4a). In this case, the low score awarded to the meadow at Bang Jak might have been due to its low scores for significance and confidence. Its ES score might improve if the information confidence level increases as the result of more research or monitoring.
When the vulnerability of each seagrass site to anthropogenic threats is assessed separately, the results allow us to understand how seagrass meadows are directly degraded by human activities in the area or indirectly degraded by activities nearby areas. Among the 13 sites ranked in the 10 highest final VU scores, Thap Lamu (TP), Koh Loan-Yon Bay–Chalong Bay (KL, YB, CB), and Ban Pak Bara (BPB) were the highest priorities for the close examination of the impact of the anthropogenic threats, which put these meadows at high risk. The highest VU scores given to these three sites were for the effects of boating accidents and sedimentation. These incidents were consequences of the movement of people or of fishing from boats and, since the three sites tend to experience such activities frequently. They were designated as the outstanding factors that damage these seagrass habitats. Na Thap (NT) and Pattani Bay (PB) were the second and the third priorities for management action to minimize anthropogenic threats.
Most of the 13 sites experienced problems related to sedimentation. Pathio (PT) and Chalalai Beach (CLB) were the two sites that were the least vulnerable to anthropogenic threats out of the ten highest-ranked sites. They suffered from sedimentation, damage from fishing methods, and overharvesting. Out of all the 82 seagrass sites, Koh Khai Yai was the least vulnerable. Sedimentation was the only threat addressed for this site, and it was on a very small scale. The impact of sedimentation was rarely felt, and this was seen in single species with high resistance that can recover in short periods of time. The small scale of the threat to the seagrass meadow on this island might be the result of the protection afforded to the location to encourage its enjoyment by tourists. The site is part of the Laem Son National Park. The main activities of the tourists that visit the island are related to coral-reef exploration, while tourists are prohibited from entering some parts of the island. However, as the seagrass beds at this site covered only a small area (0.01 km2), regular monitoring and some conservation efforts are needed to prevent any future loss of seagrass cover. The seagrass-meadow size and VU score also presented an overall significant positive relationship. Dam Hok–Dam Khwan was the second-smallest meadow, gaining the lowest VU scores.
The combined analysis indicated that the priorities for management action were sites which had high ES and moderate-to-high VU scores. The results of the combined analysis revealed that the highest-priority site was the seagrass meadow at Ban Don (BD) in Surat Thani Province in the Gulf of Thailand. This site scored quite high for the provision of many ecosystems goods and benefits while facing some level of nutrient loading/enrichment, pollution, urban runoff, agricultural runoff, and untreated sewage. These high levels of anthropogenic threats have increased due to the management of the land use around the bay. The land around the bay has been exploited by increasing numbers of people, possibly illegally. New constructions for fisheries and aquaculture have appeared in many places. The intensive use of coastal land can eventually cause high degrees of damage to seagrass ecosystems. As the area has been overexploited by large numbers of people, conservation or restoration efforts might experience difficulty in recreating environments; better, more sustainable management is required. Intensive law enforcement might need to be applied to all activities in public areas to ensure legality and fairness for all stakeholders. At the same time, education should also be encouraged to increase local awareness of the environment and marine resources.
In terms of seagrass-ecosystem services, most sites in Thailand should generally be similar to other areas in the SE Asian region, due to the similarities between seagrass species, species richness, and species abundance. As is the case in many other countries in the region, a common threat found in many sites around Thailand is sedimentation. The importance of seagrass-ecosystem services is receiving increasing attention. In India, strategies for coastal management and seagrass conservation have been developed from the knowledge base of ecosystem services [43]. Historically, reports about seagrass habitats in the region have emphasized both anthropogenic and natural threats. The most common anthropogenic impacts were from sedimentation and its associated nutrient loading, as well as other types of pollution [44]. In a comparison of seven Southeast Asian countries, two, Vietnam and Thailand, had addressed sedimentation as a threat to seagrass beds. However, the highest number of publications from Thailand referred to natural factors [45]. The impact of boating activities, such as anchoring, can contribute to seagrass decline. To reduce the impact of boating, alternative seagrass-friendly moorings have been proposed [4].
Above all, the maintenance of seagrass habitats requires the increase in seagrass resilience to long-term change on global scale. Recent findings suggest that seagrass-meadow resilience benefits from the most suitable assessment of seagrass status, the best processes, and the acquisition of feedback. The awareness of environmental managers and regulators of important threats is crucial, and the required levels of protection must be applied [4]. Unfortunately, an overall study of ecosystem services revealed knowledge gaps that implied geographical, service, and disciplinary biases. There is a need to expand this kind of research to the coastline of Southeast Asia, the eastern and western coasts of South America and the west coast of Africa [46]. The method we have presented can be a powerful tool for the rapid assessment of seagrass meadows. The level of information we have recently obtained can help to identify seagrass areas that should be given priority for intervention to conserve healthy beds, as well as helping to improve local environmental conditions in areas that show signs of future seagrass-habitat loss and to clarify general conservation-policy considerations in specific areas. This also provides significant information on the prioritization of conservation and restoration when blue carbon reaches its major potential for carbon offset, as well as other benefits, such as biodiversity and livelihoods.

Author Contributions

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

Funding

This research was funded by the Royal Golden Jubilee (RGJ) Ph.D. Program, grant number PHD/0061/2560; the National Research Council of Thailand (NRCT); the Thailand Research Fund (TRF).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Acknowledgments

This study was supported by the specialists of the Department of Marine and Coastal Resources (DMCR), who study seagrass meadows around Thailand, as well as by the Seaweed and Seagrass Research Unit, Prince of Songkla University. Our thanks go out to the organizers of the 6th Marine Science Conference, hosted by Burapha University, the DMCR, and the Marine Science Association of Thailand for the opportunity to run a workshop on ecosystem services and vulnerability analysis. This article was also supported by the Royal Golden Jubilee (RGJ) Ph.D. Program (grant no. PHD/0061/2560), through the National Research Council of Thailand (NRCT) and the Thailand Research Fund (TRF).

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Map of eighty-two studied seagrass areas used for ecosystem services (ES) and vulnerability (VU) analyses.
Figure 1. Map of eighty-two studied seagrass areas used for ecosystem services (ES) and vulnerability (VU) analyses.
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Figure 2. Some important ES and VU of seagrass meadows presented in this study: (a) shelter for marine animals; (b) importance of seagrass meadows for local fisheries; (c) sediment cover on seagrass leaves; and (d) scar on seagrass beds from boat accident.
Figure 2. Some important ES and VU of seagrass meadows presented in this study: (a) shelter for marine animals; (b) importance of seagrass meadows for local fisheries; (c) sediment cover on seagrass leaves; and (d) scar on seagrass beds from boat accident.
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Figure 3. The total scores for ecosystem goods and benefits (ES) for the sixteen highest-ranked seagrass meadows, with and without direction of status change. The number on top of the bar indicates the direction of the meadow and its ecosystem-services provision. See Table 1 for site codes.
Figure 3. The total scores for ecosystem goods and benefits (ES) for the sixteen highest-ranked seagrass meadows, with and without direction of status change. The number on top of the bar indicates the direction of the meadow and its ecosystem-services provision. See Table 1 for site codes.
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Figure 4. Relationship between seagrass-area extent (km2) and ES/VU scores: (a) ES score and (b) VU score. Data were transformed using (log(x) + 1), n = 82.
Figure 4. Relationship between seagrass-area extent (km2) and ES/VU scores: (a) ES score and (b) VU score. Data were transformed using (log(x) + 1), n = 82.
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Figure 5. Principal-component-analysis biplot of the first two principal components (PC; 59.3% of the variance) of 82 seagrass meadows across Thailand based on multiple VU (17 threats) scores given for each site. Circle size indicates the percentage of contributions to PCA 1 and PCA 2. Letters A and G, after site code, indicate seagrass beds on the Andaman Sea coast and Gulf of Thailand coast, respectively.
Figure 5. Principal-component-analysis biplot of the first two principal components (PC; 59.3% of the variance) of 82 seagrass meadows across Thailand based on multiple VU (17 threats) scores given for each site. Circle size indicates the percentage of contributions to PCA 1 and PCA 2. Letters A and G, after site code, indicate seagrass beds on the Andaman Sea coast and Gulf of Thailand coast, respectively.
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Table
Table 1. Ten highest final ES scores (16 sites) from 82 seagrass sites across Thailand and the most important services of each site (1 = highest ES rank; 10 = 10th highest ES rank).
Table 1. Ten highest final ES scores (16 sites) from 82 seagrass sites across Thailand and the most important services of each site (1 = highest ES rank; 10 = 10th highest ES rank).
Site NameThe Most Important Services of Each MeadowFinal
ES Score
1◆ Koh Samui (SM)◆ Education and research 39.50
2◆ Koh Libong (LB)◆ Education and research35.00
3◆ Koh Pha Ngan (PN)
◆ Kung Krabaen Bay (KB)		◆ Education and research
◆ Education and research		33.50
4◆ Ban Don (BD)◆ Food, wild and farmed33.00
5◆ Koh Sriboya (SBY)
◆ Koh Muk (MK)		◆ Healthy climate/sea defense/waste burial, removal, neutralization/prevention of coastal erosion/education and research
◆ Food, wild and farmed/healthy climate/sea defense/waste burial, removal, neutralization/prevention of coastal erosion		32.50
6◆ Koh Pha–Koh Prathong (P–PT)
◆ Koh Yao Yai–Yao Noi (YY–YN)
◆ Paklok Bay–Koh Ma Prao (PK–MP)		◆ Food, wild and farmed/healthy climate/sea defense/waste burial, removal, neutralization/prevention of coastal erosion
◆ Food, wild and farmed/healthy climate/sea defense/waste burial, removal, neutralization/prevention of coastal erosion
◆ Food, wild and farmed/healthy climate/sea defense/waste burial, removal, neutralization/prevention of coastal erosion		31.50
7◆ Phang-Nga Bay (PB)
◆ Bang Bane Bay (BB)		◆ Food, wild and farmed/healthy climate/sea defense/waste burial, removal, neutralization/prevention of coastal erosion
◆ Food, wild and farmed/healthy climate/sea defense/waste burial, removal, neutralization/prevention of coastal erosion		30.50
8◆ Koh Tha Rai (TR)
◆ Middle Songkhla Lake (MSL)		◆ Prevention of coastal erosion/tourism and nature watching/education and research
◆ Food, wild and farmed/fish feed, wild, farmed and bait/healthy climate/sea defense/waste burial, removal, neutralization/prevention of coastal erosion/education and research		30.00
9◆ Koh Payam–Koh Chang (PY–C)◆ Food, wild and farmed/healthy climate/sea defense/waste burial, removal, neutralization/prevention of coastal erosion 29.00
10◆ Makham Pom Bay (MPB)◆ Education and research28.50
Table
Table 2. Ten highest final VU scores (13 sites) from 82 seagrass sites across Thailand; information is provided together with the most important threats of each site (1 = highest VU rank; 10 = 10th highest VU rank).
Table 2. Ten highest final VU scores (13 sites) from 82 seagrass sites across Thailand; information is provided together with the most important threats of each site (1 = highest VU rank; 10 = 10th highest VU rank).
RankSite NameThe Most Important Threats of Each MeadowFinal
VU Score
1◆ Thap Lamu (TL)
◆ Koh Loan–Yon Bay–Chalong Bay (KL–YB–CB)
◆ Ban Pak Bara (BPB)		◆ Sedimentation/boating accidents (grounding or propeller damage)
◆ Boating accidents (grounding or propeller damage)
◆ Sedimentation/boating accidents (grounding or propeller damage)		33.00
2◆ Na Thap (NT)◆ Sedimentation30.28
3◆ Pattani Bay (PB)◆ Land reclamation/dredging/sedimentation26.87
4◆ Koh Nok Pao (NP)◆ Sedimentation/shipping accidents (oil spills)26.53
5◆ Middle Songkhla Lake (MSL)◆ Land reclamation/sedimentation25.73
6◆ Ban Don (BD)◆ Nutrient loading/pollution/urban runoff/agricultural runoff/untreated sewage/sedimentation24.73
7◆ Klong Yamu (KY)◆ Sedimentation24.33
8◆ Lower Songkhla Lake (LSL)◆ Land reclamation23.67
9◆ Koh Chang (KC)◆ Commercial fisheries (physical damage from fishing methods and overharvesting)23.33
10◆ Pathio (PT)
◆ Chala Lai Beach (CLB)		◆ Sedimentation/subsistence fisheries (destructive fishing methods and overharvesting)
◆ Commercial fisheries (physical damage from fishing methods)		22.73
Table
Table 3. Vulnerability scores for each threat at each seagrass site.
Table 3. Vulnerability scores for each threat at each seagrass site.
ThreatTLKL-YB-CBBPBNTPBNPMSLBDKYLSLKCPTCLBAv. Score
Land reclamation3.003.003.002.332.270.002.330.001.732.270.000.001.731.67
Dredging3.003.003.002.332.271.532.131.531.732.071.931.331.532.11
Land use change3.003.003.001.931.471.731.931.671.731.670.001.401.731.87
Nutrient loading/enrichment 3.003.003.002.131.471.932.131.731.731.672.132.271.332.12
Pollution2.872.872.871.331.671.931.131.730.931.472.001.730.731.79
Urban runoff3.003.003.002.331.871.732.131.731.931.872.001.731.132.11
Agricultural runoff2.872.872.872.331.671.732.131.731.931.871.671.730.932.03
Untreated sewage3.003.003.002.531.871.732.131.731.731.272.001.731.132.07
Sedimentation3.133.133.132.732.272.132.331.732.331.872.132.331.932.40
Commercial—physical damage from fishing methods0.000.000.001.531.671.000.131.530.131.272.600.602.130.97
Commercial—overharvesting0.000.000.000.530.271.000.131.530.130.472.600.601.330.66
Subsistence—destructive fishing methods0.000.000.002.131.871.731.931.532.131.470.002.331.931.31
Subsistence—overharvesting0.000.000.001.331.071.732.131.532.131.070.002.331.131.11
Gleaning/collection0.000.000.002.131.871.531.731.531.731.271.470.131.531.15
Algae culture/mariculture0.000.000.001.131.671.000.931.331.130.670.001.000.730.74
Shipping accidents—oil spills3.003.003.001.531.672.130.931.531.131.471.870.931.731.84
Boating accident—grounding/propeller damage3.133.133.130.000.001.930.000.600.000.000.930.530.001.03
Table
Table 4. Twelve sties ranked as the ten highest combined scores for ecosystem services and vulnerability (from 82 sites). The sites are ranked 1 to 10, from the highest to the lowest final assessment score.
Table 4. Twelve sties ranked as the ten highest combined scores for ecosystem services and vulnerability (from 82 sites). The sites are ranked 1 to 10, from the highest to the lowest final assessment score.
BDMSLPNPBLSLTRP–PTYY–YNPK–MPPTTY–TK–MKBTS
ES rank786979586169737373546258
VU rank757662787364565656706063
Final assessment score585052444898452444534416408840884088378037203654
Combined Es-VU rank1234567778910
Note(s): Site code as follows: BD = Ban Don, MSL = Middle Songkhla Lake, PN = Koh Pha Ngan, PB = Pattani Bay, LSL = Lower Songkhla Lake, TR = Koh Tha Rai, P–PT = Koh Pha–Koh Prathong, YY–YN = Koh Yao Yai–Yao Noi, PK–MP = Paklok Bay–Koh Maprao, PT = Pathio, TY–TK–MKB = Koh Tapao Yai–Tang Khen Bay–Makham Bay, and TS = Thungka–Sawi.
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Kaewsrikhaw, R.; Upanoi, T.; Prathep, A. Ecosystem Services and Vulnerability Assessments of Seagrass Ecosystems: Basic Tools for Prioritizing Conservation Management Actions Using an Example from Thailand. Water 2022, 14, 3650. https://doi.org/10.3390/w14223650

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Kaewsrikhaw R, Upanoi T, Prathep A. Ecosystem Services and Vulnerability Assessments of Seagrass Ecosystems: Basic Tools for Prioritizing Conservation Management Actions Using an Example from Thailand. Water. 2022; 14(22):3650. https://doi.org/10.3390/w14223650

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Kaewsrikhaw, Ratchanee, Tipamat Upanoi, and Anchana Prathep. 2022. "Ecosystem Services and Vulnerability Assessments of Seagrass Ecosystems: Basic Tools for Prioritizing Conservation Management Actions Using an Example from Thailand" Water 14, no. 22: 3650. https://doi.org/10.3390/w14223650

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