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Article

GIS-Based Suitability Assessment for the Ecological Restoration of Oyster Reefs: A Case Study of the Tianjin Coast in Bohai Bay

by
Yuxuan Zhao
,
Zifei Wang
,
Yunan Lin
,
Ruijia Jing
,
Zhiyun Wang
* and
Xianhua Liu
*
School of Environmental Science and Engineering, Tianjin University, Tianjin 300354, China
*
Authors to whom correspondence should be addressed.
Sustainability 2025, 17(11), 4759; https://doi.org/10.3390/su17114759
Submission received: 11 April 2025 / Revised: 9 May 2025 / Accepted: 17 May 2025 / Published: 22 May 2025
(This article belongs to the Section Sustainable Oceans)
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Abstract

:
The ecological restoration of oyster reef ecosystems enhances their ecological functions and strengthens carbon sequestration capacity in coastal zones. Identifying suitable restoration sites is a crucial prerequisite for initiating oyster reef restoration projects. This study developed an oyster reef restoration suitability index model for the Tianjin coast of Bohai Bay by integrating the Analytic Hierarchy Process (AHP) with the Geographic Information System (GIS). It was then applied to assess the region’s suitability for oyster reef restoration. The suitability analysis identified favorable environmental conditions for oyster reef restoration in most of the Tianjin coastal area, with high suitability for factors like dissolved oxygen, pH, and seabed slope. However, excessive water depth in the eastern bay mouth and strong currents in the southwestern region made these areas unsuitable. The northern and western coastal regions were deemed optimal restoration sites, while proximity to shipping lanes and industrial activities limited feasibility in some nearshore zones. The model outputs exhibited strong spatial concordance with existing oyster reef distributions, validating its predictive accuracy. This framework offers a robust foundation for oyster reef restoration planning, with an adaptable index system that allows for regional extrapolation. By leveraging this model, decision-makers can systematically evaluate site-specific restoration suitability, optimize resource allocation, and guide strategic conservation planning.

1. Introduction

Oysters are marine benthic filter-feeding organisms inhabiting estuarine regions, capable of forming oyster reefs—principal structural and ecological components in global estuaries [1]. Within diverse estuarine ecosystems, oyster reefs fulfill critical ecological functions. Firstly, as filter-feeding benthic organisms, oysters effectively reduce suspended particulates, nutrients, and algal biomass in estuarine waters, thereby enhancing water clarity [2], while concurrently accumulating substantial quantities of heavy metal ions [3]. Secondly, oyster reefs provide optimal habitats and foraging grounds for numerous benthic organisms and fish species [4]. Finally, oysters facilitate significant particulate matter deposition onto sediment surfaces, thereby supporting benthic detritus production [5]. Maintaining healthy oyster habitats constitutes an effective approach to address marine eutrophication and declining biological resources while concurrently attenuating wave energy and stabilizing coastlines through the protection of critical estuarine habitats [6,7,8]. However, in recent decades, overexploitation, environmental pollution, and frequent disease outbreaks have precipitated drastic reductions in wild oyster populations across temperate estuaries and coastal regions worldwide, with global oyster reef ecosystem losses estimated at 85% [9]. Numerous bays previously documented for abundant oyster reefs and fisheries have experienced severe degradation, characterized by habitat destruction, spatial reduction, or the complete loss of oyster reefs, thereby altering the structure and functionality of nearshore aquatic ecosystems. This exacerbates water eutrophication and the proliferation of toxic harmful algal blooms, posing substantial threats to the population maintenance and resource replenishment of economically significant fish species in estuarine and coastal regions [10]. Consequently, oyster reef restoration has emerged as a pivotal focus in global marine ecological conservation and rehabilitation initiatives.
A growing number of estuarine habitat restoration projects are underway around the world [11]. However, improving the efficiency of oyster reef restoration remains a challenge. Smith et al. [12] developed a physical habitat suitability model, informed by 12 years of monitoring data from 14 intertidal oyster reefs along Virginia’s coast, to optimize site selection for enhancing oyster biomass and guiding restoration/aquaculture efforts. Taryn Laubenstein et al. [13] identified 307 distinct threats to Australian marine and coastal systems during 2010–2020 through systematic analysis, categorized into three primary classes: utilization/extraction threats; environmental/anthropogenic stressors; and policy/sociopolitical challenges. Overton et al. [14] investigated the survival rates of intertidal flat oysters (Ostrea angasi) under extreme seasonal temperature fluctuations in southern Australia, demonstrating that survival probability depends on immersion duration, thermal conditions, and interactive effects between immersion time and shell length. Black et al. [15] established environmental evaluation metrics (temperature, salinity, dissolved oxygen, turbidity) in North Carolina oyster reefs, assessing restoration success through oyster density/size parameters and associated faunal community structures. Pollack et al. [16] analyzed the temporal development of multiple ecosystem services in Louisiana oyster reef restoration projects, concluding that restoration efficacy correlates with oyster growth performance, which is ultimately governed by localized environmental conditions.
Substantial natural oyster reefs have been found distributed across intertidal zones and shallow subtidal areas along China’s Bohai, Yellow, East China, and South China Sea coastlines. Along the northwestern Bohai Bay littoral plain encompassing Ninghe District, Baodi District, Binhai New Area of Tianjin Municipality, and Fengnan District of Tangshan City in Hebei Province, researchers have identified over 50 subfossil oyster reef formations, designating this region as the “Oyster Reef Plain” with a total area approximating 5000 km2 [17]. However, ecological degradation has affected most reefs in recent decades due to overexploitation and environmental alterations [9]. Fang Enjun et al. [18] conducted pioneering acoustic surveys in Tianjin’s Dashentang artificial reef zone, obtaining unprecedented spatial distribution details of reef structures to facilitate restoration efficacy assessments. Sha Wanxiao et al. [19] documented a 19.71-hectare oyster reef complex in Mabengkou, western Bohai Bay, analyzing the biotic parameters of Spartina alterniflora–oyster symbiotic communities in intertidal zones. Since the early 21st century, China has established Marine Special Protection Zones to enhance marine ecosystem conservation, implementing oyster habitat restoration through artificial reef deployment and marine ranching initiatives [20,21], though large-scale artificial oyster reef systems have yet to be established.
A foundational step in successful oyster reef restoration is the identification of suitable habitats that can support oyster growth, reproduction, and long-term stability [22]. For oysters, attachment and settlement are crucial stages in their life cycle. The type of substrate selected by the larvae during these stages significantly influences their growth, population establishment, community development, and ecological functions [23]. Habitat suitability is influenced by a combination of physicochemical, hydrodynamic, and anthropogenic factors, such as water quality, current velocity, seabed characteristics, and proximity to pollution sources or human activities [24]. Habitat suitability indices are commonly used by natural resource managers for habitat mapping, conservation, and restoration planning [25]. GIS is a useful tool for spatially explicit, data-driven planning of oyster reef restoration. It can also enhance decision-making by allowing stakeholders to visualize, prioritize, and manage ecological restoration efforts in complex coastal environments. GIS features an outstanding spatial data management system, an intuitive user interface, and powerful spatial analysis capabilities, providing effective technical support for the study of bay ecosystems [26]. Furthermore, GIS can extract and refine ecological information and process and regenerate it in order to achieve the goals, plans, and strategies for solving specific ecological issues. With the continuous advancement of marine monitoring technology, the increasing availability of monitoring data, and the widespread adoption and application of GIS in related fields, leveraging the powerful spatial data management and analysis functions of GIS has become increasingly important for bay ecosystem research. Its capacity to handle large volumes of data also makes it possible to develop precise and detailed mathematical models, providing a scientific basis for the protection and management decisions of nearshore ecosystems [27].
The Analytic Hierarchy Process (AHP) is a widely used multi-criteria decision-making method that supports the rational weighting of variables based on expert judgment and pairwise comparison [28,29,30]. When integrated with GIS, the AHP provides a robust framework for evaluating habitat suitability in a transparent, reproducible, and spatially explicit manner. Despite its demonstrated effectiveness in habitat modeling, the combined application of the AHP and GIS for oyster reef restoration remains underexplored in the Bohai Bay region. This study aims to develop and apply an AHP-GIS-based oyster reef habitat suitability model tailored to the Tianjin coast of Bohai Bay. By incorporating water quality indicators, hydrological features, and human impact factors, the model identifies optimal restoration zones and provides critical insights into ecological constraints and spatial restoration potential. The findings are expected to support science-based conservation planning and offer a transferable methodology for oyster reef restoration in other coastal regions. This study directly supports sustainability by promoting the ecological restoration of oyster reefs, which are vital for enhancing marine biodiversity and coastal ecosystem resilience. Identifying optimal restoration sites using AHP-GIS modeling contributes to efficient resource use and evidence-based environmental planning. Restored oyster reefs improve water quality through natural filtration and support blue carbon sequestration, aiding climate change mitigation efforts. The exclusion of areas near industrial zones and shipping channels ensures a balanced approach to coastal development and conservation.

2. Methods

2.1. Study Area

Bohai Bay, located in the western part of the Bohai Sea (latitude: 37°07′–41°00′, longitude: 117°35′–121°10′) (Figure 1), is one of China’s three major bays. It is bordered by Tianjin, Hebei Province, and Shandong Province [31]. Several rivers—including the Hai River, Yongding New River, Duliu Jianyue River, Jiyun River, Ziya New River, and Beipai Waterway—flow into the bay, supplying essential nutrients that support the growth of aquatic animals, plants, and microorganisms. The seabed topography slopes gradually from south to north and from the coast toward deeper waters. Water depths range from 0 to 22 m, providing favorable conditions for oyster reef habitat restoration. The bay’s sediments are predominantly composed of fine-grained silt and mud.
This study focuses on the Tianjin section of Bohai Bay. Tianjin is a densely populated coastal industrial city and hosts a range of marine industries along the Bohai Sea coastline, including the Bohai Oil field, and supports a well-developed marine fishery sector. However, rapid urban and industrial development has led to a significant accumulation of land-based nutrient inputs, contributing to eutrophication and environmental pollution. These changes have resulted in the degradation of marine ecosystems and a decline in water quality. Consequently, natural oyster reefs in the region have suffered extensive damage. The local reef resources have drastically decreased from approximately 35 square kilometers in the 1970s to about 3 square kilometers today, with an average annual reduction of about 1 square kilometer. At this rate, the muddy live oyster reefs of Dashentang could potentially disappear completely in three years. Furthermore, the remaining approximately 3 square kilometers of live oyster reef resources are composed of three scattered reef bodies, with a distance of up to 3 km between each pair of scattered reefs. More concerning is the emerging trend of these three small reef bodies being further fragmented into even smaller ones [32].

2.2. Evaluation System and Determination of Indicator Weights by Using the AHP Method

Based on the “Technical Guidelines for Coastal Ecological Disaster Reduction and Restoration, Part 6: Oyster Reefs” (China Ocean Engineering Consultation Association, 2020) [33], and the study on oyster reef habitat selection by Wang [34] and Xu [35], ten indicators were selected as suitability factors within the evaluation system. They can be categorized into three main types: water quality factors, hydrological factors, and management factors. This study employed the Analytic Hierarchy Process (AHP) to construct weights for the ecological restoration suitability evaluation index system of oyster reefs, with model calculations implemented using Yaahp 10.3 software (Beijing Yuanjue Technology Co., Ltd., Beijing, China) [36,37]. Based on the ecological requirements of oyster reefs and the characteristics of the Tianjin coastal area, the target layer was decomposed into criterion levels (water quality factors, hydrological factors, and management factors) (E1–E3) and ten indicator levels (F1–F10) (Figure 2). The overall target is the oyster reef suitability index (T), and expert scoring was employed to assess the relative importance of each factor. Ten experienced experts in marine ecology and GIS were invited to conduct pairwise comparisons of the relative importance of indicators within the same hierarchical level using a 1–5 scale method. Judgment matrices for each hierarchical level were sequentially input through the software interface, such as specifying that “water quality factors are rated 4 in importance relative to hydrological factors and 4 relative to management factors” at the criterion level. The judgment matrixes of the main criterion layer T-E and the sub-criterion layer E-F were analyzed and ranked (Tables S1–S4). By constructing the judgment matrix, the maximum eigenvalue of the matrix, λmax = 3.0536, was calculated. After normalizing the eigenvalue vector, the weights Wi for E1 to E3 were derived (Table 1), accompanied by a consistency check confirming a consistency ratio (CR = 0.0516 < 0.100), demonstrating satisfactory consistency in the judgment matrices.

2.3. Indicator Suitability Functions

Water quality parameters include dissolved oxygen (DO) [38], pH [39,40], total inorganic nitrogen (TIN) [41,42,43,44,45], chemical oxygen demand (COD) [46,47], and soluble reactive phosphate (SRP), all of which influence oyster growth and habitat conditions. Hydrological factors such as water depth [6], seabed slope [48], and current velocity [48] affect larval settlement, nutrient delivery, and survival. Management factors consider the proximity to shipping channels and marine industries, which pose risks due to pollution and physical disturbances [49]. A suitability function transforms these diverse environmental parameters into a standardized index ranging from 0.0 (unsuitable) to 1.0 (highly suitable), based on oyster ecological requirements (Figure S1). For example, optimal DO levels are above 5 mg/L, pH should remain between 7.8 and 8.5, and water depths between 0 and 5 m are ideal. Gentle seabed slopes (<5°) and moderate current velocities (10–80 cm/s) support oyster stability and growth, while high COD or eutrophication can be detrimental. Areas within 5 km of shipping lanes or industrial zones are considered unsuitable due to elevated risks from human activity.

2.4. Data Sources

Data for dissolved oxygen, pH, COD, inorganic nitrogen, and soluble reactive phosphates were obtained from the National Marine Environmental Monitoring Center’s seawater quality monitoring information system [50]. Based on data from the National Marine Environmental Monitoring Center, water quality monitoring data from 2023 and 2024 were selected, covering the Bohai Bay of Tianjin, with a focus on the Binhai New Area (117.5–118.5° E, 38.5–39.5° N) and a resolution of ≥1 km2, retaining indicators directly related to the survival of oyster reefs. Given the seasonal variations in water quality parameters and the oyster reproduction and growth period extending from April to November, statistical analyses were conducted separately for spring, summer, and autumn data across five water quality factors to account for their temporal dynamics. Water depth, defined as the vertical distance from the theoretical lowest tide level to the seabed, was sourced from seabed topography data available in the geographic and remote sensing datasets of the National Marine Science Data Center. These datasets are based on topographic information published by various international organizations and are compiled in the General Bathymetric Chart of the Oceans (GEBCO) [51], which offers global bathymetric and terrestrial elevation data at a 30″ (~900 m) resolution, with the selected dataset published in 2014. The bottom slope was calculated using the “Slope” geoprocessing tool in ArcGIS Pro, applied to the water depth data on a per-pixel basis. Current velocity data were also obtained from the National Marine Science Data Center through its integrated ocean current dataset, from which 31 data points in Bohai Bay were extracted. Information on the locations of shipping channels and marine industries in the Tianjin section of Bohai Bay was derived from the Tianjin Land Use Master Plan (2015–2020) [52], which is the latest announcement of land use planning data for Tianjin. According to the “Tianjin Land and Space Master Plan (2021–2035)” [53], a classification system for the protection and utilization of artificial coastlines is to be established, and efforts to implement coastal building retreat line management will be explored. The short-term target year for the plan is 2025, making the data on port and industrial conditions in the coastal zone still relevant in recent years.

2.5. GIS Model Construction

(1) Study area delineation: Based on research objectives, a polygon feature class was created in ArcGIS Pro 2.5.2 to define the study area within the Tianjin section of Bohai Bay.
(2) Data preprocessing: Initial preprocessing involved the removal of outliers. For example, an abnormal pH value of 27 was excluded. No anomalies were identified in the datasets for DO, COD, inorganic nitrogen, soluble reactive phosphate, water depth, or bottom slope. Flow velocity data, consisting of eastward and northward components, were vectorially combined to yield overall current velocity. For management factors, a polygon feature class was developed based on the spatial distribution of shipping lanes and marine industries.
(3) Data import and interpolation: Point-based environmental data (e.g., DO, pH, COD, nutrients, and current velocity) were first imported into the database in the GIS pro project catalog. Using the “XY Table To Point” tool, these datasets were converted into point feature classes. The inverse distance weighting (IDW) method was selected as the interpolation approach through the cross-validation of multiple interpolation methods (Table S5). IDW, a distance-based spatial interpolation technique, estimates values at unknown locations by calculating a weighted average of surrounding known points, with weights inversely proportional to their distance. Parameters were configured in the Geostatistical Analyst module of ArcGIS, where the power value was set to 1 to ensure the gradual attenuation of neighboring point weights, resulting in smoothed interpolation surfaces with minimized root mean square error (RMSE) (Table S5). A variable search radius was implemented, specifying a minimum of 12 neighboring points and a maximum radius of 5 km to balance localized detail with global spatial trends, ultimately generating continuous raster surfaces through the interpolation process. Raster datasets, such as water depth, were directly imported. The bottom slope was derived using the “Slope” tool, with the depth raster as input. For proximity analysis, the “Euclidean Distance” tool was employed to calculate the distance to shipping lanes and marine industries, generating corresponding raster layers.
(4) Data clipping (masking): To ensure spatial consistency, all raster layers were clipped to the study area using the “Extract by Mask” tool, with the polygon feature class serving as the mask layer.
(5) Single-factor suitability index calculation: Suitability functions for each factor were applied using the “Raster Calculator” tool to generate standardized suitability index layers. Each factor was evaluated individually based on optimal ecological thresholds defined in the suitability curves.
(6) Reclassification: The “Reclassify” tool was used to classify each raster into five suitability levels: 0 (unsuitable), 0–0.25 (very low suitability), 0.25–0.5 (moderate suitability), 0.5–0.75 (high suitability), 0.75–1 (most suitable).
(7) Weighted overlay analysis: A weighted linear combination of the ten single-factor suitability layers was performed using the “Raster Calculator”. The Oyster Reef Suitability Index (RSI) was calculated using the following formula:
R S I = ∑ w i x i
where wi is the weight of the i-th factor derived from the AHP (Table 1) and xi is the corresponding suitability index.
(8) Exclusion mapping: To exclude areas unsuitable for oyster reef restoration, an exclusion map was created based on three criteria: (a) proximity to shipping lanes, (b) the presence of marine industrial zones, and (c) areas with a suitability index of 0 in any factor. These layers were combined to identify zones unsuitable for restoration.
(9) Final suitability map generation: The exclusion map was overlaid with the comprehensive suitability index map using the “Raster Calculator” with the “con” function. This integration yielded the final suitability map for oyster reef restoration.

2.6. Sensitivity Analysis and Validation of Suitability Index Maps

Sensitivity analysis evaluates how changes in input parameters affect model outcomes, thus assessing the model’s stability and reliability under varying conditions. It helps identify which parameters significantly influence results, supporting focused monitoring and a better understanding of key system drivers. Additionally, it reveals sources of uncertainty in evaluation results, enhancing their credibility and aiding in informed decision-making. Sensitivity analysis also guides future research and data collection by pinpointing critical data that reduce uncertainty. In this study, four weighting scenarios—equal importance, water quality priority, hydrological priority, and management priority—were applied to AHP-derived weights to generate corresponding suitability index maps (Table 2). These scenarios allowed for comprehensive testing of the GIS model’s responsiveness to different factor weightings. The comparison of outputs under varying scenarios demonstrated the robustness and stability of the site selection results. This confirms the model’s scientific value and supports its application in ecological restoration planning.
The location data of existing oyster reefs were imported into the suitability restoration maps—generated under different weighting scenarios—using the “XY Table To Point” geoprocessing tool in ArcGIS Pro. This step was undertaken to validate the model’s effectiveness in identifying appropriate sites for oyster reef restoration. By overlaying actual reef locations onto the suitability maps, the spatial consistency between predicted suitable areas and real-world oyster reef distributions could be assessed. A strong alignment between the two would indicate the model’s reliability and predictive accuracy. This validation enhances confidence in the model’s applicability for guiding future restoration efforts.

3. Results and Discussion

3.1. Single-Factor Suitability Index Analysis for Oyster Reef Restoration

This study performed analytical evaluations of individual factors within the oyster reef restoration suitability index framework. The spatial distributions of these suitability factors are visualized in Figure 3, Figure 4, Figure 5, Figure 6, Figure 7 and Figure 8, providing insights into their geographic variability across the study area. The resulting suitability indices, calculated using the established index system, are displayed in Figure 9, Figure 10, Figure 11, Figure 12, Figure 13 and Figure 14. These indices integrate multiple environmental and management factors to assess restoration potential. Together, Figure 15 and Figure 16 offer a comprehensive spatial representation of the conditions influencing oyster reef restoration suitability along the Tianjin coast of Bohai Bay.
The dissolved oxygen (DO) concentration ranged from 5.99 to 11.04 mg/L. Spatially, except during summer 2023, the northern Tianjin section of Bohai Bay exhibited significantly lower DO levels compared to the southern region, while central Bohai Bay demonstrated slightly higher DO concentrations during summer 2023. Temporally, spring and autumn 2024 recorded marginally elevated DO levels, exceeding 10 mg/L at peak values, whereas summer 2024 showed reduced DO concentrations, potentially attributable to elevated temperatures and increased phytoplankton biomass. However, all study areas maintained DO concentrations above 5 mg/L, resulting in a uniform suitability index of 1 for dissolved oxygen across the entire region, confirming optimal conditions for oyster reef restoration.
Seawater pH exhibited relatively minor fluctuations, remaining weakly alkaline with values ranging from 7.90 to 8.40. Seasonal temperature variations, the biological activity of phytoplankton, and CO2 solubility collectively contributed to spatially inverse seasonal pH patterns during summer and autumn. Despite these spatiotemporal variations, most areas maintained pH within the optimal range for oyster growth (7.8–8.2), with marginally elevated pH levels exerting negligible adverse impacts on reef restoration. Suitability assessment revealed pH-related indices exceeding 0.75 throughout the study area, indicating high suitability and confirming that seawater pH provides a favorable environment for oyster reef growth and recovery.
The inorganic nitrogen concentration in the Tianjin section of Bohai Bay ranged from 0.03 mg/L to 0.54 mg/L. While most areas exhibited relatively low concentrations, significantly elevated levels were observed near the western coastline, indicating pronounced spatial heterogeneity likely attributable to terrestrial pollution inputs. Temporally, summer months demonstrated markedly higher inorganic nitrogen concentrations compared to other seasons, potentially driven by increased rainfall and surface runoff. Suitability assessment revealed that most regions maintained suitability indices between 0.75 and 1.00 throughout the study period, except for summer 2024 when the northeastern bay showed reduced suitability (0.25–0.75) due to lower concentrations. Overall, the area exhibited high suitability across most periods, suggesting that inorganic nitrogen levels do not critically impede oyster reef restoration.
Chemical oxygen demand (COD) in the Tianjin section of Bohai Bay varied from 0.93 mg/L to 2.90 mg/L, with elevated concentrations similarly clustered along the western coastline, likely associated with industrial discharges from the Binhai New Area. COD levels peaked during spring 2024, potentially reflecting organic matter accumulation from slowed winter degradation. Suitability indices exceeded 0.75 in most western nearshore areas except during spring and summer 2024, when values remained above 0.5. The southeastern offshore region in autumn 2023 recorded lower suitability (0.25–0.50). While COD levels generally showed moderate suitability for oyster reef growth, nearshore zones—primary oyster habitats—maintained favorable concentrations during most periods.
Soluble reactive phosphate concentrations in the Tianjin section of Bohai Bay remained relatively low (0.002–0.021 mg/L), exhibiting a gradual northward increase with the highest levels in northern coastal areas, potentially linked to agricultural, industrial, and aquaculture effluents. Autumn 2023 saw northern coastal concentrations approaching 0.02 mg/L. Suitability indices predominantly ranged between 0.00 and 0.50 due to overall low phosphate levels, with marginally better conditions in northern waters compared to southern regions. This suggests slightly favorable phosphate conditions for reef restoration in the north, while southern areas may experience nutrient limitations. The water depth in the Tianjin section of Bohai Bay ranges from −22 to 2 m. The deepest area is located at the eastern bay mouth, where depth gradually increases from the shoreline toward the open sea. The shallowest point is found at the northernmost nearshore area of the study region. Suitability for water depth spans from 0 to 1. Due to depths exceeding 10 m, the eastern bay mouth is deemed unsuitable for oyster reef restoration. Moving from the bay mouth toward the coast, the suitability index remains steady at first, then gradually rises to 1. In contrast, nearshore areas with water depths above sea level (greater than 0 m) have a suitability index of 0.
Overall, the seabed slope in the study area is very gentle, with all values below 0.4°, indicating a relatively flat terrain. The lowest slope occurs several kilometers offshore, while nearshore regions display slightly more variation in seabed contours. However, these changes are minimal, and the slope across the Tianjin section of Bohai Bay remains under 5°, making it highly suitable for oyster reef restoration. Accordingly, the suitability index for slope is 1.
The maximum velocity within the study area ranged from 10.4 cm/s to 32.2 cm/s, exhibiting significant spatial variability with northern regions demonstrating higher velocities compared to southern sectors. Maximum velocities occurred at the northeastern bay mouth where the water depths were greatest, while a general trend of increasing velocity was observed from nearshore to offshore zones across most areas. Suitability indices for current velocity spanned 0 to 0.73, with optimal restoration potential localized in high-velocity northeastern bay mouth subregions. Conversely, southwestern areas displayed minimal suitability, reflecting the suboptimal hydrodynamic conditions prevalent throughout the study area despite the presence of marginally favorable zones in the northeast.
Shipping lanes and traffic land are mainly concentrated in the northwestern part of the study area. The distribution of shipping lanes is relatively concentrated, indicating that this area is a primary shipping route. The suitability of areas within 5 km of shipping lanes correlates positively with proximity. Beyond 5 km, the suitability index is 1. In areas within 5 km of shipping lanes, suitability increases as the distance decreases, likely due to increased ship traffic, which may introduce noise, vibration, and hydrodynamic impacts harmful to oyster growth. However, in areas more than 5 km away, the suitability scores are all 1, suggesting that the impact of shipping lanes on oyster reef suitability is minimal or negligible.
Marine industries are primarily located in the northwestern and southwestern regions of the study area. These industries are concentrated nearshore, especially along the coast. These areas tend to have lower suitability due to greater interference and management factors. In contrast, areas further from the coast generally have higher suitability, as they are less impacted by marine industrial activities and human disturbances. These regions are more likely to remain natural and pristine, making them more favorable for oyster reef restoration.

3.2. Oyster Reef Restoration Suitability Evaluation

Before performing the final evaluation, it is essential to create an exclusion map (Figure 15a). The primary purpose of this map is to eliminate areas unsuitable for oyster reef restoration, ensuring that only viable locations are considered. By analyzing the suitability indices of various influencing factors, regions where restoration is unfeasible under specific conditions can be clearly identified. The exclusion map includes two main categories: areas where oyster reef restoration is inherently impossible and areas with a suitability index of zero. The former may involve legal or regulatory restrictions, environmentally sensitive zones, or other non-negotiable constraints. The latter represents regions deemed unsuitable based on the evaluated environmental and management factors.
By excluding these unsuitable areas, restoration zones can be more accurately identified, allowing for the optimization of restoration plans and management strategies. The exclusion map serves as a valuable visual tool for decision-makers and stakeholders, clearly indicating areas that are more or less suitable for specific activities. This approach helps prevent resource waste and unnecessary environmental impacts while improving the overall success rate and effectiveness of the project. During the study, suitability indices were calculated for factors such as water depth, proximity to shipping lanes, and distance from marine industries. Areas with a suitability index of zero were extracted and excluded. The results indicate that the eastern bay region of the Tianjin section of Bohai Bay is unsuitable for oyster reef restoration. Additionally, small portions of the northern and southern nearshore areas are also deemed unsuitable for restoration efforts.
After generating the exclusion map, it was overlaid with the suitability index map to calculate the final oyster reef restoration suitability index for the Tianjin section of Bohai Bay. The weight coefficients for each influencing factor were determined using the AHP, resulting in a final suitability index ranging from 0 to 0.78. The suitability index map (Figure 15b) reveals that the northern and western regions of the study area are the most favorable for oyster reef restoration.

3.3. Sensitivity Analysis and Verification

In the suitability assessment for oyster reef restoration, multiple scenarios were considered, including equal weighting, the prioritization of water quality, the prioritization of hydrological factors, and the prioritization of management factors. The calculated suitability indices under these scenarios are presented in Figure 16. Sensitivity analysis reveals some differences between the model-derived suitability index and those calculated using alternative weightings, with deviations of 0.02, 0.03, 0.01, and 0.09, respectively. Despite these variations, areas with higher suitability indices are consistently located in the northern part of the study area, while unsuitable areas are primarily concentrated along the eastern, southwestern, and northwestern coastal zones. This indicates that the northern region remains highly suitable for oyster reef restoration under all weighting scenarios, whereas the other regions show limited suitability. These findings demonstrate the stability and robustness of the evaluation model across different scenarios. Although slight variations in suitability indices exist, the overall spatial distribution remains consistent, providing valuable guidance for decision-makers and stakeholders in identifying priority areas for restoration and developing effective management strategies to support the recovery and sustainable development of oyster reef ecosystems.
Further validation of the GIS-based oyster reef restoration suitability model shows that existing oyster reefs are mainly distributed near Dashentang, Xinmapengkou Village, and Relict Gull Park [17,54]. Under the equal-weight scenario, the Dashentang site and Relict Gull Park are classified as optimally suitable, while Xinmapengkou Village is located in a highly suitable area. In the hydrology-prioritized scenario, the Dashentang site is classified as optimally suitable, while Xinmapengkou Village and Relict Gull Park are located in highly suitable areas. In both the water quality and management-prioritized scenarios, all three locations are situated in optimally suitable zones. These results indicate that the output of the suitability model aligns well with the actual distribution of oyster reefs in the Tianjin section of Bohai Bay [18,55]. The significant overlap between existing oyster reef locations and the areas identified as suitable by the model suggests that the model effectively captures real-world environmental conditions and can serve as a reliable tool for guiding future restoration efforts. This consistency is highly valuable for decision-makers and managers, as it affirms the reliability and accuracy of the suitability assessment model. The model delivers stable evaluation results across different scenarios, demonstrating strong robustness in assessing the potential for oyster reef restoration. This provides a solid scientific foundation for informed decision-making. However, it is important to recognize that while the model’s output closely aligns with the current distribution of oyster reefs, additional factors and datasets should be integrated to ensure a comprehensive and accurate decision-making process. Suitability assessment represents only one aspect of restoration planning. The strategy is comprised of three dimensions: the first is the improvement in the ecology in order to meet the requirements of oyster reefs; the second is the enhancement of economic potential through the development of value-added fishery and tourism; and the third is the addressing of social needs by supporting the livelihoods of fishermen and strengthening cultural conservation. Guided by field investigations and historical data, stakeholder consultations involving government, communities, enterprises, and environmental organizations are organized to jointly delineate priority action zones—designating oyster reef-dense areas as core protected zones, adjacent waters as eco-economic compatibility zones, and peripheral transitional belts as dynamic monitoring zones. Comprehensive assessments of resource input costs and long-term benefits, including disaster mitigation effects and carbon sequestration value, inform the implementation of cost-effective measures such as deploying artificial reef substrates to enhance habitats, establishing seasonal fishing moratoriums to balance harvesting demands, creating oyster-themed ecotourism routes to generate employment, and instituting community-based compensation mechanisms, such as subsidizing fishermen based on ecological restoration area. A dynamic evaluation framework is established, integrating water quality monitoring, economic revenue statistics, and public satisfaction surveys to ensure optimal balance between technical feasibility and social acceptance, thereby achieving coordinated ecological and socioeconomic outcomes.

4. Conclusions

This study integrates the AHP with GIS techniques to develop an Oyster Reef Restoration Suitability Index Model, applied to the Tianjin section of Bohai Bay. The AHP was used to quantify the relative importance of various suitability factors, while GIS enabled spatial processing and visualization through ArcGIS Pro. Univariate suitability analysis revealed that dissolved oxygen, pH, inorganic nitrogen, COD, and bottom slope all scored within the optimal range (0.75–1.00) across most of the study area, indicating favorable conditions for oyster reef restoration. Reactive phosphate levels showed moderate suitability overall, with higher suitability in the north and lower values in western coastal zones. Water depth showed the highest spatial variability, with deep waters near the eastern bay mouth proving unsuitable, while shallower nearshore areas exhibited excellent potential. Suitability indices for current velocity remained suboptimal, particularly in the southern sector, with only northern areas exceeding 0.75. Over 90% of the area maintained distances greater than 5 km from shipping channels and marine industries, achieving maximum suitability (index = 1), while coastal areas closer to anthropogenic activities showed reduced restoration viability. Model validation and sensitivity analysis indicate that the approach effectively captures the spatial distribution of key restoration factors. The results highlight the northern and western shores of the Tianjin section as the most suitable zones for oyster reef restoration, while the eastern and southwestern coastal regions are less favorable. Water depth and proximity to shipping lanes and marine industries emerged as major limiting factors.
By combining the AHP with GIS, the study presents a comprehensive and practical framework for evaluating and visualizing restoration suitability. AHP facilitates objective weight assignment based on expert judgment, while GIS provides powerful spatial analysis and mapping capabilities, producing a visual suitability index map that assists decision-makers in identifying priority areas for restoration and avoiding unsuitable zones. This integrative model accommodates diverse environmental and anthropogenic factors—such as hydrology, water quality, and human activity—offering a robust tool for restoration planning. However, it is important to adapt the model to the unique geographical and environmental context of each study area. The accuracy and relevance of the suitability assessment depend on the quality of input data and proper calibration for local conditions. Therefore, while this model offers a valuable decision-support tool, it should be flexibly tailored to specific regional contexts to guide effective and sustainable oyster reef restoration strategies.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/su17114759/s1, Text S1: The evaluation factors for the oyster reef restoration suitability and suitability functions; Text S2: The process of calculating weights by using the AHP; Text S3: Cross-validation of interpolation methods and parameters; Figure S1: Suitability indicator chart for each factor in the oyster reef restoration evaluation indicator system; Table S1: T-F judgment matrix and weight calculation table; Table S2: E1-F judgment matrix and weight calculation table; Table S3: E2-F judgment matrix and weight calculation table; Table S4: E3-F judgment matrix and weight calculation table; Table S5: Table of cross-validation results for interpolation methods.

Author Contributions

Methodology, investigation, data curation, writing—original draft preparation: Y.Z. and Z.W. (Zifei Wang); investigation, resources: Y.L. and R.J.; conceptualization, resources, supervision, project administration, funding acquisition, writing—review and editing: Z.W. (Zhiyun Wang) and X.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research was partially financially supported by the Natural Science Foundation of Tianjin City (#21YFSNSN00180).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are available on request from the corresponding authors.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Location map of Bohai Bay.
Figure 1. Location map of Bohai Bay.
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Figure 2. Chart of the AHP evaluation system for evaluating oyster reef restoration suitability. DO denotes dissolved oxygen; TIN denotes total inorganic nitrogen; COD denotes chemical oxygen demand; SRP denotes soluble reactive phosphates; WD denotes water depth; and V denotes flow velocity.
Figure 2. Chart of the AHP evaluation system for evaluating oyster reef restoration suitability. DO denotes dissolved oxygen; TIN denotes total inorganic nitrogen; COD denotes chemical oxygen demand; SRP denotes soluble reactive phosphates; WD denotes water depth; and V denotes flow velocity.
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Figure 3. Interpolated map layers of dissolved oxygen (DO) concentrations (mg/L) from the suitability indicator system: (a) summer 2023; (b) autumn 2023; (c) spring 2024; (d) summer 2024; (e) autumn 2024.
Figure 3. Interpolated map layers of dissolved oxygen (DO) concentrations (mg/L) from the suitability indicator system: (a) summer 2023; (b) autumn 2023; (c) spring 2024; (d) summer 2024; (e) autumn 2024.
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Figure 4. The interpolation map layers of pH from the suitability indicator system: (a) summer 2023; (b) autumn 2023; (c) spring 2024; (d) summer 2024; (e) autumn 2024.
Figure 4. The interpolation map layers of pH from the suitability indicator system: (a) summer 2023; (b) autumn 2023; (c) spring 2024; (d) summer 2024; (e) autumn 2024.
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Figure 5. The interpolation map layers of total inorganic nitrogen (TIN) from the suitability indicator system (mg/L): (a) summer 2023; (b) autumn 2023; (c) spring 2024; (d) summer 2024; (e) autumn 2024.
Figure 5. The interpolation map layers of total inorganic nitrogen (TIN) from the suitability indicator system (mg/L): (a) summer 2023; (b) autumn 2023; (c) spring 2024; (d) summer 2024; (e) autumn 2024.
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Figure 6. The interpolation map layers of chemical oxygen demand (COD) from the suitability indicator system (mg/L): (a) summer 2023; (b) autumn 2023; (c) spring 2024; (d) summer 2024; (e) autumn 2024.
Figure 6. The interpolation map layers of chemical oxygen demand (COD) from the suitability indicator system (mg/L): (a) summer 2023; (b) autumn 2023; (c) spring 2024; (d) summer 2024; (e) autumn 2024.
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Figure 7. The interpolation map layers of soluble reactive phosphates (PO43−) from the suitability indicator system (mg/L): (a) summer 2023; (b) autumn 2023; (c) spring 2024; (d) summer 2024; (e) autumn 2024.
Figure 7. The interpolation map layers of soluble reactive phosphates (PO43−) from the suitability indicator system (mg/L): (a) summer 2023; (b) autumn 2023; (c) spring 2024; (d) summer 2024; (e) autumn 2024.
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Figure 8. The interpolation map layers of factors from the suitability indicator system; (a) water depth (WD); (b) bottom slope (θ); (c) flow velocity (V); (d) distance to shipping channels; (e) distance to marine industries.
Figure 8. The interpolation map layers of factors from the suitability indicator system; (a) water depth (WD); (b) bottom slope (θ); (c) flow velocity (V); (d) distance to shipping channels; (e) distance to marine industries.
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Figure 9. Suitability index map layers of dissolved oxygen (DO) from the suitability indicator system: (a) summer 2023; (b) autumn 2023; (c) spring 2024; (d) summer 2024; (e) autumn 2024. The different colors in the legend represent the suitability index of the region.
Figure 9. Suitability index map layers of dissolved oxygen (DO) from the suitability indicator system: (a) summer 2023; (b) autumn 2023; (c) spring 2024; (d) summer 2024; (e) autumn 2024. The different colors in the legend represent the suitability index of the region.
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Figure 10. Suitability index map layers of pH from the suitability indicator system: (a) summer 2023; (b) autumn 2023; (c) spring 2024; (d) summer 2024; (e) autumn 2024. The different colors in the legend represent the suitability index of the region.
Figure 10. Suitability index map layers of pH from the suitability indicator system: (a) summer 2023; (b) autumn 2023; (c) spring 2024; (d) summer 2024; (e) autumn 2024. The different colors in the legend represent the suitability index of the region.
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Figure 11. Suitability index map layers of total inorganic nitrogen (TIN) from the suitability indicator system (mg/L): (a) Summer 2023; (b) autumn 2023; (c) spring 2024; (d) summer 2024; (e) autumn 2024. The different colors in the legend represent the suitability index of the region.
Figure 11. Suitability index map layers of total inorganic nitrogen (TIN) from the suitability indicator system (mg/L): (a) Summer 2023; (b) autumn 2023; (c) spring 2024; (d) summer 2024; (e) autumn 2024. The different colors in the legend represent the suitability index of the region.
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Figure 12. Suitability index map layers of chemical oxygen demand (COD) from the suitability indicator system (mg/L): (a) summer 2023; (b) autumn 2023; (c) spring 2024; (d) summer 2024; (e) autumn 2024. The different colors in the legend represent the suitability index of the region.
Figure 12. Suitability index map layers of chemical oxygen demand (COD) from the suitability indicator system (mg/L): (a) summer 2023; (b) autumn 2023; (c) spring 2024; (d) summer 2024; (e) autumn 2024. The different colors in the legend represent the suitability index of the region.
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Figure 13. Suitability index map layers of soluble reactive phosphates (PO43−) from the suitability indicator system (mg/L): (a) summer 2023; (b) autumn 2023; (c) spring 2024; (d) summer 2024; (e) autumn 2024. The different colors in the legend represent the suitability index of the region.
Figure 13. Suitability index map layers of soluble reactive phosphates (PO43−) from the suitability indicator system (mg/L): (a) summer 2023; (b) autumn 2023; (c) spring 2024; (d) summer 2024; (e) autumn 2024. The different colors in the legend represent the suitability index of the region.
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Figure 14. Suitability index map layers of factors from the suitability indicator system; (a) water depth (WD); (b) bottom slope (θ); (c) flow velocity (V); (d) distance to shipping channels; (e) distance to marine industries. The different colors in the legend represent the suitability index of the region.
Figure 14. Suitability index map layers of factors from the suitability indicator system; (a) water depth (WD); (b) bottom slope (θ); (c) flow velocity (V); (d) distance to shipping channels; (e) distance to marine industries. The different colors in the legend represent the suitability index of the region.
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Figure 15. (a) Oyster reef restoration exclusion map; (b) oyster reef restoration suitability map for the Tianjin section of the Bohai Bay.
Figure 15. (a) Oyster reef restoration exclusion map; (b) oyster reef restoration suitability map for the Tianjin section of the Bohai Bay.
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Figure 16. Sensitivity analysis: (a) equal weight; (b) prioritization of water quality; (c) prioritization of hydrology; (d) prioritization of management.
Figure 16. Sensitivity analysis: (a) equal weight; (b) prioritization of water quality; (c) prioritization of hydrology; (d) prioritization of management.
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Table 1. Oyster reef restoration suitability assessment and weighting indicator system calculated based on the AHP method.
Table 1. Oyster reef restoration suitability assessment and weighting indicator system calculated based on the AHP method.
First LevelWeightSecond LevelWeight
Water quality factors66.08%DO27.83%
pH14.44%
TIN13.75%
COD12.36%
SRP9.83%
Hydrological factors20.81%WD5.97%
Slope5.19%
Velocity4.09%
Management factors13.11%Distance to the shipping channel3.28%
Distance to the marine industries3.27%
Table 2. Weight distribution for the four scenarios in sensitivity analysis.
Table 2. Weight distribution for the four scenarios in sensitivity analysis.
ScenarioWeight
Water Quality FactorsHydrological FactorsManagement Factors
Equal importance33.30%33.30%33.30%
Water quality priority50.00%25.00%25.00%
Hydrological priority25.00%50.00%25.00%
Management priority25.00%25.00%50.00%
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Zhao, Y.; Wang, Z.; Lin, Y.; Jing, R.; Wang, Z.; Liu, X. GIS-Based Suitability Assessment for the Ecological Restoration of Oyster Reefs: A Case Study of the Tianjin Coast in Bohai Bay. Sustainability 2025, 17, 4759. https://doi.org/10.3390/su17114759

AMA Style

Zhao Y, Wang Z, Lin Y, Jing R, Wang Z, Liu X. GIS-Based Suitability Assessment for the Ecological Restoration of Oyster Reefs: A Case Study of the Tianjin Coast in Bohai Bay. Sustainability. 2025; 17(11):4759. https://doi.org/10.3390/su17114759

Chicago/Turabian Style

Zhao, Yuxuan, Zifei Wang, Yunan Lin, Ruijia Jing, Zhiyun Wang, and Xianhua Liu. 2025. "GIS-Based Suitability Assessment for the Ecological Restoration of Oyster Reefs: A Case Study of the Tianjin Coast in Bohai Bay" Sustainability 17, no. 11: 4759. https://doi.org/10.3390/su17114759

APA Style

Zhao, Y., Wang, Z., Lin, Y., Jing, R., Wang, Z., & Liu, X. (2025). GIS-Based Suitability Assessment for the Ecological Restoration of Oyster Reefs: A Case Study of the Tianjin Coast in Bohai Bay. Sustainability, 17(11), 4759. https://doi.org/10.3390/su17114759

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