Construction and Application of Marine Ecological Restoration Project Effect Assessment System Based on Analytic Hierarchy Process

Abstract

This study seeks to scientifically verify the actual effect of a marine ecological restoration project; according to the problems reflected in the assessment, the ecological restoration project can be corrected in time. This study constructs an assessment index system of marine ecological restoration effect from three aspects of ecological environment, social, and economic benefits, and uses the analytic hierarchy process (AHP) to determine the index weight. Taking the Pulandian Bay ecological restoration project and the Daling River estuary ecological restoration project as examples, the application analysis was carried out. The results showed that the Pulandian Bay project scored 77.18 and the restoration effect was ‘good’, while the Daling River estuary project scored 80.19 and the restoration effect was ‘excellent’. Both achieved the effects of improving the regional ecological environment, improving ecosystem service functions, improving the quality of life of residents, and driving regional economic development. The assessment method adopted not only reflects the impact of ecological restoration on the ecological environment and economic society but also visually displays the benefits of the project, reflecting the contribution of the ecosystem to human well-being, which can provide a reference for the evaluation of similar marine ecological restoration projects.

1. Introduction

The marine ecosystem is one of the most valuable ecosystems on Earth. It not only provides basic ecological services such as carbon sinks, fishery nurseries, feeding grounds, coastline protection, and nutrient cycling, but also has important values in leisure tourism and cultural services [1,2]. However, the excessive exploitation of marine resources by humans has significantly impacted the world’s oceans and coastal environments, leading to extensive degradation [3]. This degradation trend threatens the sustainable provision of ecosystem services and may have severe consequences for biodiversity and the livelihoods of coastal populations [4,5]. Against this backdrop, marine ecological restoration has emerged as a central issue in global environmental governance.

The United Nations General Assembly has declared 2021–2030 as the “UN Decade on Ecosystem Restoration.” This global initiative aims to address multiple challenges through large-scale restoration of degraded ecosystems, including combating climate change, ensuring food security, improving water supply, and safeguarding planetary biodiversity [6]. As a critical component of restoration practice, ecological restoration effectiveness assessment provides scientific quantification of recovery outcomes. This serves dual purposes: informing adaptive management of restoration projects while establishing an empirical foundation for subsequent policy formulation [7]. How to establish a systematic and standardized assessment framework for marine ecological restoration has become a critical scientific challenge requiring urgent resolution in the field of marine environmental management. Most of the existing evaluation system studies focus on the ecological environment and ecological benefits [8,9,10,11]. However, the marine ecological restoration project is a systematic project with both ecological and social economic benefits. From the ecological perspective, it enhances the ability of the ecosystem to provide ecological goods and services by maintaining, restoring, and rebuilding damaged or degraded marine ecosystems [12]. From the perspective of the social economy, marine ecological restoration projects usually require continuous investment from public finance. Its essence is to relieve the contradictions of the development of man and nature, improve the service ability of marine ecosystem, and eventually promote economic and social sustainable development [13]. Therefore, in the process of constructing the indicator system, it should also be considered to link social and economic benefits on the basis of ecological environment, so as to realize multi-dimensional assessment of restoration effects. In recent years, some research attempt to build ecological restoration effect evaluation system from many aspects. For example, Jones and Hanna [14] evaluated the effect of coastal ecological restoration from the perspectives of landscape, geotechnical design, and environmental and ecological factors, as well as social and economic factors. Lithgow et al. [15] constructed a coastal dune restoration index from the aspects of ecology, geomorphology, and social economy to evaluate the necessity and feasibility of coastal dune restoration. Jones et al. [16] considered not only the landscape, environment, and ecology of wetlands, but also the social level (mainly based on the social acceptance of the public) and the economic level (cost–benefit analysis) when evaluating the restoration economy of Loyola Beach, and made a comprehensive evaluation of wetlands before, during, and five years after ecological restoration.

Ecosystem services include the source of natural and artificial ecosystems’ functions, through methods such as tangible or intangible items and services to offer human benefit [17]. Ecological restoration can improve ecosystem services, so quantifying the value of ecosystem services can also provide a scientific basis for the evaluation of ecological restoration effects [18]. The existing research mainly involves the improvement effect of ecological restoration on individual functions such as biodiversity conservation [19], soil conservation [20], and climate regulation [21]. In addition, there is also research that attempts to conduct a comprehensive assessment from multiple dimensions such as natural, economic, social, and cultural services. For example, Gómez-Baggethun et al. [22] analyzed the changes of wetland ecosystem services caused by economic development from 1960 to 1989 and ecological restoration from 1990 to 2010 in the Danube Delta, and evaluated the value of ecosystem services in the Danube Delta from a total of 13 indicators including food production, tourism and recreation, science education, and biodiversity conservation.

In China, since the launch of marine ecological restoration projects such as the “Blue Bay Remediation Action” and the “Bohai Sea Comprehensive Management Battle”, the scale and quantity of ecological restoration in coastal areas have increased rapidly [23]. Research on the construction of the assessment system for marine ecological restoration projects has been carried out successively, most of which focus on the assessment of ecological restoration effect of a single ecosystem [24,25], a single project type [26,27], a local space [28], or the assessment of ecological restoration projects in coastal zones by monetizing ecosystem service value [29,30]. Although studies of China’s marine ecological restoration assessments provide an important reference. As a result, it is difficult to compare among different engineering types and regions, and there is a lack of a universal restoration effect assessment system.

This study aims to construct a scientific, comprehensive, and universal effect assessment system for marine ecological restoration projects to solve the problems existing in current evaluation practice. Firstly, this study combines the ecological, social, and economic dimensions to form a comprehensive assessment framework. This framework not only focuses on the degree of ecosystem restoration, but also takes into account social acceptability and economic feasibility so as to more fully reflect the actual effectiveness of ecological restoration projects. Secondly, in view of the problems such as inconsistent index selection and lack of universality of assessment methods in existing studies, this study constructs a standardized and quantifiable indicator system through the analytic hierarchy process to ensure that it is suitable for marine ecological restoration projects of different types and regions. In addition, this study also innovatively quantified the value of ecosystem services into the assessment system, and reflected the improvement effect of ecological restoration on ecosystem services by monetizing the value of ecosystem services, providing a scientific basis for the intuitive expression of restoration effects. Finally, in order to verify the universality of the assessment system, the ecological restoration projects in Pulandian Bay and Daling River Estuary were taken as examples to provide experience and guidance for similar ecological restoration projects.

2. Materials and Methods

2.1. Constructing an Evaluation Indicator System Based on AHP

2.1.1. Construction of Indicator Hierarchy

The selection of indicators should follow principles such as scientificity, representativeness, and independence. We sorted out and analyzed a number of marine ecological restoration project cases and related studies [31,32,33,34,35,36,37,38,39], and based on the “Technical Specification Series of Marine ecological Restoration Effectiveness Evaluation Standards”, we constructed a marine ecological restoration effectiveness assessment system. The system is divided into three parts: ecological environment, social, and economic benefits.

The ecological environment aspect includes four elemental layers, specifically environmental quality, biological environment, spatial scale, and ecosystem services. They are employed to characterize the enhancement and regulation of the marine ecological environment through ecological restoration, as well as the recovery and augmentation of the functional services provided by marine ecosystems [13]. Each factor layer is further elaborated into specific indicators within the indicator layer, comprising a total of 11 established indicators. Among them, under the ecosystem service element layer, supply service selects the indicators of food supply and oxygen production service; regulation service selects the indicators of interference regulation and climate regulation service; and the cultural service selects the indicators of leisure and recreation as well as scientific research and education service. Ecological restoration projects play a positive role in promoting regional economic development and social harmony. As an important stakeholder in ecological restoration projects, residents’ perception and well-being change are an indispensable part of evaluating the effect of ecological restoration [40]. Therefore, this study evaluates social and economic benefit indicators based on residents’ perceptions. The constructed marine ecological restoration effect assessment index system is shown in

Table 1. Effectiveness assessment system of marine ecological restoration projects.

Target Layer	Criterion Layer	Factor Layer	Indicator Layer	Index Description
A Effectiveness of marine ecological restoration projects	B1 Ecological environment	C1 Environmental quality	D1 Strength of ebb	The average velocity change of surface ebb tide in sea area
			D2 Seawater quality	Change degree of seawater quality index
			D3 Sediment quality	Change degree of sediment quality
		C2 Biological environment	D4 Macrobenthos species diversity	Change of regional macrobenthos species diversity index
			D5 Zooplankton species diversity	Change of regional zooplankton species diversity index
			D6 Phytoplankton species diversity	Change of regional phytoplankton species diversity index
		C3 Space scale	D7 Shoreline ecologization rate	The change ratio of the proportion of the length of the continental ecological shoreline
			D8 Ecological restoration area	Restoration of ecological restoration area
		C4 Ecosystem services	D9 Supply service	Rate of change in total value of supply service
			D10 Regulation service	Rate of change in total value of regulation service
			D11 Cultural service	Rate of change in total value of cultural service
	B2 Social benefit	C5 Social satisfaction	D12 Repair effect satisfaction	Degree of public satisfaction with the ecological restoration projects in terms of improvement in the quality of the surrounding environment and enhancement of marine ecological functions
		C6 Social impact	D13 Public participation	Degree of public participation or intent to participate in ecological restoration projects
			D14 Degree of impact on productive life	Extent of impact of ecological restoration works on the production and living conditions of the population
	B3 Economic benefit	C7 Economic effect degree	D15 Income impact on residents	Extent of impact of ecological restoration on household income of the population
		C8 Social recognition of economic benefits	D16 Level of social recognition of economic benefits	Public recognition and acceptance of the project in terms of economic benefits

.

2.1.2. Determination of Indicator Weights

The analytic hierarchy process method (AHP) is a decision analysis method that organically combines qualitative and quantitative indicators. It takes the research object as a system and allocates weights for decomposition, comparison, and judgment, as well as synthesis, to quantify the influence degree of each factor at each level on the result [41]. The method is practical and effective in dealing with complex decision-making problems, so it is widely used in the field of marine ecological restoration effect assessment. In this study, we invited 16 experts in the field to conduct pairwise comparisons of the indicators in groups of two against two. Then, we constructed a consistency judgment matrix and conducted a consistency test on the judgment matrix. The main steps are as follows:

(1)

Constructing the discriminant matrix

Using the 1~9 scale method proposed by Saaty to compare the importance of two factors belonging to the same level two by two, according to the importance of each indicator, the judgment matrix $A=\left\{a_{ij}\right\}$ is constructed, where $a_{ij}$ represents the importance of factor i to factor j and $1/a_{ij}$ represents the importance of factor j to factor i. The form of the constructed judgment matrix is shown in Equation (1):

$$A=\left(\begin{array}{cccc}{a}_{11}& a_{12}& \cdots & a_{1n}\\ a_{21}& a_{22}& \cdots & a_{2n}\\ ⋮& ⋮& \ddots & ⋮\\ a_{n1}& a_{n2}& \cdots & a_{nn}\end{array}\right)=\left(\begin{array}{cccc}1& {\displaystyle \frac{a_1}{a_2}}& \cdots & {\displaystyle \frac{a_1}{a_n}}\\ & & & \\ {\displaystyle \frac{a_2}{a_1}}& 1& \cdots & {\displaystyle \frac{a_2}{a_n}}\\ ⋮& ⋮& \ddots & ⋮\\ {\displaystyle \frac{a_n}{a_1}}& {\displaystyle \frac{a_n}{a_2}}& \cdots & 1\end{array}\right)$$

(1)

(2)

Weight calculation and consistency test

By solving the eigenvalues of the judgment matrix, A, the maximum eigenvalue ${\lambda }_{max}$ is found, ${\lambda }_{max}$ is substituted into Equation (2) to find x, and the eigenvector ${\omega }^T$ is obtained by normalizing x. ${\omega }^T$ is the weight value of factors at a certain level. The weights from the target level to the criterion level, the criterion level to the factor level, and the factor level to the indicator level were calculated sequentially. Consistency index CI and consistency ratio CR were used, where CI and CR were calculated by Equations (3) and (4)

$$\left(A-\lambda E\right)x=0$$

(2)

$$CI={\displaystyle \frac{{\lambda }_{max}-n}{n-1}}$$

(3)

$$C.R.={\displaystyle \frac{CI}{R.I.}}$$

(4)

The consistency of the judgment matrix is considered good when C.R. < 0.1, otherwise the scores of the indicators should be re-determined. R.I. is the random consistency index, which is queried according to

Table 2. Stochastic consistency index.

n	1	2	3	4	5	6	7	8	9	10
R.I.	0	0	0.52	0.89	1.12	1.24	1.36	1.41	1.46	1.49

.

The weights of indicators at each level were calculated using the above method (

Table 3. Weights of evaluation indicators at various levels of marine ecological restoration projects.

B Layer		C Layer		D Layer
Criterion Layer	A–B Weight	Factor Layer	B–C Weight	Index	C–D Weight	A–D Weight	Order
B1	0.7405	C1	0.2384	D1	0.4607	0.0813	4
				D2	0.2857	0.0504	9
				D3	0.2536	0.0448	14
		C2	0.1937	D4	0.3333	0.0478	11
				D5	0.3333	0.0478	11
				D6	0.3333	0.0478	11
		C3	0.3036	D7	0.5346	0.1202	1
				D8	0.4654	0.1046	2
		C4	0.2643	D9	0.2846	0.0557	7
				D10	0.4677	0.0916	3
				D11	0.2477	0.0485	10
B2	0.1406	C5	0.5614	D12	1	0.0789	5
		C6	0.4386	D13	0.4654	0.0287	16
				D14	0.5346	0.0330	15
B3	0.1890	C7	0.4254	D15	1	0.0506	8
		C8	0.5746	D16	1	0.0683	6

). The consistency parameter C.R. of the target layer, criterion layer, factor layer, and indicator layer are less than 0.1, which meets the consistency test requirements. The order of weights from the indicator layer to the target layer indicates the order of importance of the indicators in the system, and the top five indicators in the order of weights are: shoreline ecologization rate, ecological restoration area, regulation service, strength of ebb, and repair effect satisfaction.

2.2. Quantification and Evaluation Methods of Indicators

2.2.1. Quantification of Indicators

The methodology for calculating the indicators in the system is shown in

Table 4. Method for calculating indicators in monitoring category.

Indicator	Calculation of Indicator	Formula	Interpretation
Strength of ebb	Change rate of ebb flow velocity	$F_V={\displaystyle \frac{{\sum }_i^n{V^{″}}_m-{\sum }_i^n{V^{\prime }}_m}{{\sum }_i^n{V^{\prime }}_m}}\times 100\mathrm{\%}$	$F_V$$—\mathrm{Change} \mathrm{rate} \mathrm{of} \mathrm{ebb} \mathrm{flow} \mathrm{velocity} (\%); {V″}_m$$—\mathrm{Maximum} \mathrm{tidal} \mathrm{current} \mathrm{velocity} \mathrm{at} \mathrm{the} i\mathrm{th} \mathrm{observation} \mathrm{point} \mathrm{after} \mathrm{restoration}; {V\prime }_m$$—\mathrm{Maximum} \mathrm{tidal} \mathrm{current} \mathrm{velocity} \mathrm{at} \mathrm{the} i\mathrm{th} \mathrm{observation} \mathrm{point} \mathrm{before} \mathrm{restoration}; n$—Total number of detection stations.
Seawater quality	Change rate of seawater quality index	$R_{WQ}={\displaystyle \frac{{I^{\prime }}_{WQ}-{I^{″}}_{WQ}}{{I^{″}}_{WQ}}}\times 100\mathrm{\%}$	$R_{WQ}$—Change rate of seawater quality $\mathrm{index} (\%); {I^{\prime }}_{WQ}$$—\mathrm{Seawater} \mathrm{quality} \mathrm{index} \mathrm{after} \mathrm{ecological} \mathrm{restoration}; {I^{″}}_{WQ}$—Sea water quality index before ecological restoration.
		$I_{WQ}=\sum {\displaystyle \frac{N_i}{N}}\times S_{WQi}$	$I_{WQ}$$—\mathrm{Seawater} \mathrm{quality} \mathrm{index}; i$—Grade number of seawater quality, with reference to GB3097-1997 [42] “seawater quality standard”; the seawater quality is divided into five grades: class I, class II, class III, class IV, and inferior class IV; $S_{WQi}$$—\mathrm{The} \mathrm{seawater} \mathrm{quality} \mathrm{standard} \mathrm{assignment} \mathrm{for} \mathrm{seawater} \mathrm{of} \mathrm{category} i$$, \mathrm{and} \mathrm{the} \mathrm{water} \mathrm{quality} \mathrm{standard} \mathrm{assignment} \mathrm{for} \mathrm{seawater} \mathrm{of} \mathrm{category} \mathrm{I}, \mathrm{II}, \mathrm{III}, \mathrm{IV}, \mathrm{and} \mathrm{inferior} \mathrm{IV} \mathrm{are} 5, 4, 3, 2, \mathrm{and} 1 \mathrm{respectively}; N_i$$—\mathrm{The} \mathrm{number} \mathrm{of} \mathrm{monitoring} \mathrm{stations} \mathrm{for} \mathrm{seawater} \mathrm{quality} \mathrm{standard} \mathrm{of} \mathrm{category} i$$; N$—The total number of seawater quality testing stations [33].
Sediment quality	Change rate of sediment quality	$R_q=\left({\displaystyle \frac{Q_1}{Q_{1,T}}}-{\displaystyle \frac{Q_0}{Q_{0,T}}}\right)\times 100\mathrm{\%}$	$R_q$$—\mathrm{Change} \mathrm{rate} \mathrm{of} \mathrm{sediment} \mathrm{quality} (\%); Q_1$$—\mathrm{Number} \mathrm{of} \mathrm{stations} \mathrm{where} \mathrm{the} \mathrm{sediments} \mathrm{after} \mathrm{ecological} \mathrm{restoration} \mathrm{meet} \mathrm{the} \mathrm{quality} \mathrm{standard} \mathrm{of} \mathrm{Class} \mathrm{I} \mathrm{sediments}; Q_{1,T}$$—\mathrm{Total} \mathrm{number} \mathrm{of} \mathrm{sediment} \mathrm{monitoring} \mathrm{stations} \mathrm{after} \mathrm{ecological} \mathrm{restoration}; Q_0$$—\mathrm{Number} \mathrm{of} \mathrm{stations} \mathrm{where} \mathrm{the} \mathrm{sediments} \mathrm{before} \mathrm{ecological} \mathrm{restoration} \mathrm{meet} \mathrm{the} \mathrm{quality} \mathrm{standard} \mathrm{of} \mathrm{Class} \mathrm{I} \mathrm{sediments}; Q_{0,T}$—Total number of sediment monitoring stations before ecological restoration [43].
Macrobenthos species diversity	Rate of change of macrobenthos diversity index	${{\mathrm{H}}^{\prime }}_c={\displaystyle \frac{{{\mathrm{H}}^{\prime }}_{c1}-{{\mathrm{H}}^{\prime }}_{c0}}{{{\mathrm{H}}^{\prime }}_{c0}}}\times 100\mathrm{\%}$	${{\mathrm{H}}^{\prime }}_c$$—\mathrm{Rate} \mathrm{of} \mathrm{change} \mathrm{in} \mathrm{biodiversity} \mathrm{index} (\%); {{\mathrm{H}}^{\prime }}_{c1}$$—\mathrm{Post}-\mathrm{restoration} \mathrm{biodiversity} \mathrm{index}; {{\mathrm{H}}^{\prime }}_{c0}$—Pre-restoration biodiversity index; ${\mathrm{H}}^{\prime }$$—\mathrm{Species} \mathrm{diversity} \mathrm{index}; P_i$$—\mathrm{Ratio} \mathrm{of} \mathrm{the} \mathrm{number} \mathrm{of} \mathrm{individuals} \mathrm{of} \mathrm{species} i \mathrm{to} \mathrm{the} \mathrm{total} \mathrm{number} \mathrm{of} \mathrm{individuals} \mathrm{at} \mathrm{that} \mathrm{survey} \mathrm{station}; N_i$$—\mathrm{Number} \mathrm{of} \mathrm{individuals} \mathrm{of} \mathrm{species} i$$; N$—Number of all individuals at the survey station.
Zooplankton species diversity	Rate of change of zooplankton diversity index	${\mathrm{H}}^{\prime }=-\sum {\displaystyle \frac{N_i}{N}}ln{\displaystyle \frac{N_i}{N}}$
Phytoplankton species diversity	Rate of change of phytoplankton diversity index
Shoreline ecologization rate	Rate of change in shoreline ecologization rate	$R_{EC}={\displaystyle \frac{{A\prime }_{EC}-{A″}_{EC}}{{A″}_{EC}}}\times 100\mathrm{\%}$	$R_{EC}$$—\mathrm{Shoreline} \mathrm{ecologization} \mathrm{rate} (\%); {A\prime }_{EC}$$—\mathrm{Percentage} \mathrm{of} \mathrm{ecological} \mathrm{shoreline} \mathrm{length} \mathrm{after} \mathrm{ecological} \mathrm{restoration} (\%); {A″}_{EC}$—Percentage of ecological shoreline length before ecological restoration (%).
		$A_{EC}={\displaystyle \frac{L_{EC}}{L_{TC}}}\times 100\mathrm{\%}$	$A_{EC}$$—\mathrm{The} \mathrm{percentage} \mathrm{of} \mathrm{ecological} \mathrm{shoreline} \mathrm{length} (\%); L_{EC}$$—\mathrm{The} \mathrm{sum} \mathrm{of} \mathrm{natural} \mathrm{and} \mathrm{ecologically} \mathrm{restored} \mathrm{shoreline} \mathrm{length} \left(\mathrm{km}\right); L_{TC}$—Total shoreline length (km) [33].
Ecological restoration area	Wetland area restoration rate	$R_S={\displaystyle \frac{S_i}{S_j}}\times 100\mathrm{\%}$	$R_s$$—\mathrm{Rate} \mathrm{of} \mathrm{restoration} \mathrm{of} \mathrm{wetland} \mathrm{area} (\%); S_i$$—\mathrm{Area} \mathrm{of} \mathrm{wetland} \mathrm{added}/\mathrm{restored} \mathrm{after} \mathrm{ecological} \mathrm{restoration} \left({\mathrm{hm}}^2\right); S_j$—Area of wetland destroyed/occupied before ecological restoration (hm2).

and

Table 5. Methodology for calculating ecosystem service category indicators.

Ecosystem Services	Service Value Elements	Assessment Methodology	Formula	Interpretation
Supply service	Food supply	Market price method	$V_{SM}=\sum Q_{S{M}_i}\times P_{M_i}\times S$	$V_{SM}$$—\mathrm{Value} \mathrm{of} \mathrm{food} \mathrm{supply} (\mathrm{million} \mathrm{CNY}/\mathrm{a});Q_{S{M}_i}$$—\mathrm{Production} \mathrm{of} \mathrm{category} i\mathrm{aquatic} \mathrm{products} (\mathrm{kg}/{\mathrm{hm}}^2); P_{M_i}$$—\mathrm{Average} \mathrm{market} \mathrm{price} \mathrm{of} \mathrm{aquatic} \mathrm{products} \mathrm{of} \mathrm{category} i (\mathrm{CNY}/\mathrm{kg}); S$—Sea area (hm2).
	Oxygen production	Substitute cost method	$$\begin{gathered} V_{{\mathrm{O}}_2}=Q_{PP}\times P_{{\mathrm{O}}_2}\times 2.67 \\ \times S\times 365\times {10}^{-7} \end{gathered}$$	$V_{{\mathrm{O}}_2}$$—\mathrm{Value} \mathrm{of} \mathrm{oxygen} \mathrm{production} (\mathrm{million} \mathrm{CNY}/\mathrm{a}); Q_{PP}$—Primary productivity of phytoplankton (327 mgC/m2d [44];$P_{{\mathrm{O}}_2}$—Unit cost of artificially production of oxygen (CNY/t) (CNY 400/t); 2.67—Coefficient of oxygen release from phytoplankton; S—Sea area (km2).
Regulation service	Interference regulation	Substitute cost method	$$\begin{gathered} {\mathrm{V}}_C=L_N\times P_B÷n \\ +L_M\times P_M \end{gathered}$$	${\mathrm{V}}_C$$—\mathrm{Interference} \mathrm{regulation} \mathrm{value} (\mathrm{million} \mathrm{CNY}/\mathrm{a}); L_N$$—\mathrm{Natural} \left(\mathrm{ecological}\right) \mathrm{shoreline} \mathrm{length} \left(\mathrm{km}\right); P_B$—Artificial shoreline construction cost (30 million/km [45]); $n—\mathrm{Artificial} \mathrm{shoreline} \mathrm{service} \mathrm{life} (50 \mathrm{years}); L_M$$—\mathrm{Artificial} \mathrm{shoreline} \mathrm{length} \left(\mathrm{km}\right); P_M$—Annual maintenance cost (CNY 4.49 million/km [46])
	Climate regulation	Substitute cost method	$$\begin{gathered} V_{{\mathrm{C}\mathrm{O}}_2}=Q_{PP}\times P_{{\mathrm{C}\mathrm{O}}_2}\times 3.67 \\ \times S\times 365\times {10}^{-7} \end{gathered}$$	$V_{{\mathrm{C}\mathrm{O}}_2}$$—\mathrm{Climate} \mathrm{regulation} \mathrm{value} (\mathrm{million} \mathrm{CNY}/\mathrm{a}); Q_{PP}$$—\mathrm{Primary} \mathrm{productivity} \mathrm{of} \mathrm{phytoplankton} (327 \mathrm{mgC}/{\mathrm{m}}^2\mathrm{d}); P_{{\mathrm{C}\mathrm{O}}_2}$$—\mathrm{Market} \mathrm{trading} \mathrm{price} \mathrm{of} \mathrm{carbon} \mathrm{dioxide} \mathrm{emission} \mathrm{rights} (\mathrm{CNY} 770/\mathrm{t}$ [47]); 3.67—Phytoplankton carbon dioxide fixation coefficient; S—Sea area (km2)
Cultural service	Leisure and recreation	Result-checking method	$V_{re}=P_{re}\times S$	$V_{re}$$—\mathrm{Recreational} \mathrm{value} (\mathrm{million} \mathrm{CNY}/\mathrm{a}); P_{re}$$—\mathrm{Recreational} \mathrm{function} \mathrm{value} \mathrm{per} \mathrm{unit} \mathrm{area} (\mathrm{CNY} 4910.9/{\mathrm{hm}}^2\mathrm{a}$ [48]); S—Sea area (hm2)
	Scientific research and education	Direct Cost Method	$V_{SR}=Q_{SR}\times P_R$	$V_{SR}$$—\mathrm{Value} \mathrm{of} \mathrm{scientific} \mathrm{research} \mathrm{and} \mathrm{education} (\mathrm{million} \mathrm{CNY}/\mathrm{a}); Q_{SR}$$—\mathrm{Quantity} \mathrm{of} \mathrm{scientific} \mathrm{research} \mathrm{and} \mathrm{education} \mathrm{material} (\mathrm{piece}/\mathrm{a}); P_R$—Input of scientific research funding per marine scientific and technological thesis (based on the China Marine Statistical Yearbook 2017 to obtain the funding for a single marine scientific and technological thesis in 2016, taking into account the year of general inflation and corrected calculated that the funding for thesis in 2020 is about CNY 1,554,700/paper).

.

The assessing indicators of social and economic benefit index is calculated by the following formula:

$$\overline{S}={\displaystyle \frac{{\sum }_{n=1}^5{(S}_i{\times N}_i)}{T}}$$

(5)

In the formula, $\overline{S}$ is the index of social and economic benefit index; taking the repair effect satisfaction (D12) as an example, $S_i$ is the score of the ith evaluation grade (i = 1, 2, 3, 4, 5 correspond to very satisfied, more satisfied, general, unsatisfied, very dissatisfied); $N_i$ denotes the number of people who choose the ith rating; and T represents the total number of people. The results are graded (

Table 6. Classification standard of repair effect satisfaction grade.

Satisfaction Level of Restoration Effect	Assessment Criteria
very satisfied	(80,100]
more satisfied	(60,80]
general	(40,60]
unsatisfied	(20,40]
very dissatisfied	[0,20]

), and the scores and grades of the remaining indicators are calculated in the same way.

2.2.2. Indicators Score Determination

For the quantitative and qualitative indicators in the system, the standards for evaluation scores are provided by referring to relevant industry standards and combining a large number of marine ecological restoration project cases.

Table 7. Marine ecological restoration project effect assessment index score standard.

Score	100	75	50	25	0
Strength of ebb (%)	≥30	[20,30)	[10,20)	[0,10)	<0
Seawater quality (%)	≥10	[6,10)	[3,6)	[0,3)	<0
Sediment quality (%)	≥10	[6,10)	[3,6)	[0,3)	<0
Macrobenthos species diversity (%)	≥30	[20,30)	[10,20)	[0,10)	<0
Zooplankton species diversity (%)	≥30	[20,30)	[10,20)	[0,10)	<0
Phytoplankton species diversity (%)	≥30	[20,30)	[10,20)	[0,10)	<0
Shoreline ecologization rate (%)	≥20	[10,20)	[5,10)	[0,5)	<0
Ecological restoration area (%)	≥40	[25,40)	[10,25)	[0,10)	<0
Supply service (%)	≥40	[25,40)	[10,25)	[0,10)	<0
Regulation service (%)	≥40	[25,40)	[10,25)	[0,10)	<0
Cultural service (%)	≥40	[25,40)	[10,25)	[0,10)	<0
Repair effect satisfaction	very satisfied	more satisfied	general	unsatisfied	very dissatisfied
Public participation	high participation or willingness to participate	higher participation or willingness to participate	general	lower participation or willingness to participate	low participation or willingness to participate
Degree of impact on productive life	obvious positive impact	some positive impact	general	some negative impact	obvious negative impact
Income impact on residents	obvious positive impact	some positive impact	general	some negative impact	obvious negative impact
Level of social recognition of economic benefits	very agree	comparative agree	general	disagree	very disagree

gives the score reference value of each indicator of marine ecological restoration project effect evaluation.

2.2.3. Comprehensive Assessment Method for the Effects of Marine Ecological Restoration Projects

The comprehensive assessment index of the effect of marine ecological restoration project is calculated by the following formula:

$$RI=\sum _{i=1}^3{X}_i\sum _{j=1}^8{Y}_j\sum _{k=1}^{17}{Z}_k\times S_k$$

(6)

In the formula, RI is the comprehensive evaluation index of effect, $X_i$ is the weight of the first-level index of i, $Y_j$ is the weight of the second-level index of j, $Z_k$ is the weight of the third-level index of k, and $S_k$ is the corresponding score of the third-level index of k.

To intuitively reflect the results of the effect evaluation of marine ecological restoration projects, it is necessary to classify the comprehensive assessment index, and the classification standard is shown in

Table 8. Classification standard of marine ecological restoration project effect grade.

Marine Ecological Restoration Effect Grade	Assessment Criteria
excellent	(80,100]
good	(60,80]
general	(40,60]
worse	(20,40]
bad	[0,20]

. An index score of 60 or above indicates that the restoration project has achieved certain results and the effect is good. A score of 80 or above suggests that the restoration effect is excellent and significant achievements have been made. A score between 40 and 60 indicates that the effect is average. A score between 20 and 40 means that no significant results have been achieved and the effect is poor. A score below 20 indicates that the project has had a negative impact on the surrounding environment after implementation and the restoration effect is very poor.

2.3. Case Study

Pulandian Bay is located on the west side of Liaodong Peninsula. The bay is triangular, the mouth of the bay faces southwest, and the main development and utilization mode in history is the periphyton aquaculture and salt industry. It has been one of the important aquaculture areas and sea salt production areas in Dalian City. As the 35 km of shoreline in the area have all been replaced by artificial dykes formed by enclosure ponds, the tidal channels and deep-water troughs on both sides of the bay mouth are blocked by the enclosure aquaculture ponds, resulting in weakening of the exchange capacity of the water body, and the water quality pollution and eutrophication are serious. Therefore, the municipal government has carried out the ecological restoration project of Pulandian Bay (PLD) in response to the marine ecological environment problems such as coastal wetland degradation and natural shoreline damage caused by marine development in Pulandian Bay. The project started in September 2020, restoring 396.4 hm² of coastal wetland area, among which 263.8 hectares of coastal wetland area was restored through the thorough removal of the dike surrounding the sea breeding pool; then the internal dike was completely removed, and the outer dike adjacent to the sea was removed in sections, restoring 133.9 hm² of coastal wetland area. In addition, the project restored 6.65 km of shoreline, including 2123 m of shoreline exposed to the rear bedrock after dike removal, the way down the slope, and so on, restoring a natural coastline of 1899 m; for the shoreline exposed after the removal of the dike, the slope surface was cleaned along the shape of the aquaculture pond dike, forming the ecological restoration shoreline of 1502 m; and using landscape stone for ecological protection of the shoreline, an ecological protection shoreline of 1126 m was formed.

Daling River Estuary Wetland Nature Reserve is distributed in the lower reaches of Daling River and the estuary delta, with a total area of 119,000 hm², including the sea, beaches, and marshes, and belongs to the coastal composite wetland. It is one of the important wetlands in Liaoning Province and the largest reed coastal wetland in China. Along with the gradual implementation of the industrialization strategy, the original coastal wetlands of reed and Alpinia on both sides of the estuary of Daling River alternately appeared, and the tidal flats of the river channel were narrowed and the estuarine wetlands disappeared due to the occupation of the aquaculture sea. At the same time, because the artificial dikes block the tidal water system, the tidal gullies are not connected, the ecological environment of estuarine coastal wetlands is seriously damaged, the purification function of wetlands is seriously degraded, and the ecosystem service function is seriously damaged. In response to the marine ecological environment problems such as damage to the coastal wetland and shoreline caused by the overdevelopment of the sea area near the mouth of the Daling River in Jinzhou City, an ecological restoration project for Daling River Estuary (DLH) in Jinzhou City was carried out in April 2020, and the project is located at the mouth of the Daling River in Linghai City. The artificial dam of the aquaculture cofferdam was removed over a distance of 3.2 km. The restoration of the estuary shoreline, previously occupied by the original cofferdam, involved the construction of approximately 1 km of ecological revetment. Additionally, 190 hm² of coastal wetlands were rehabilitated through tidal creek dredging, which included the planting of reeds across an area of 37 hm² within the original aquaculture cofferdam site. Furthermore, an online monitoring station and a comprehensive monitoring network were established in the upper reaches of the Daling River’s mainstream to facilitate real-time monitoring of water quality, hydrology, and meteorology within the basin.

The geographical location and general situation of the project are shown in Figure 1.

2.4. Data Source and Processing

The assessment scope of this paper is delineated by the outer edge line of the area involved in the restoration project, and the monitoring data of two time nodes before and after the construction of the project are selected for assessment and analysis. The monitoring data were obtained from the monitoring report of the project in Pulandian Bay and Daling River Estuary; the wetland area and shoreline length were obtained by ArcGIS 10.8 software; the ecosystem service assessment data were obtained from the Statistical Yearbook of Jinzhou New District of Dalian City, Jinzhou City Statistical Bulletin, etc.; and the results of the social and economic benefit indicators were obtained by questionnaires distributed to the residents in the vicinity of the project.

3. Results and Analysis

3.1. Monitoring Indicators

The Pulandian Bay (PLD) project was monitored in the pre-construction period (April 2020), the construction period (September 2020), and the stage completion (November 2020). The monitoring included the hydrodynamic environment, seawater quality, sediment, and marine life ecology. The results of typical monitoring indicators for the PLD project are presented in Figure 2. After the removal of the cofferdam, the hydrodynamic environment has significantly improved. The average strength of ebb increased from 0.3 m/s to 0.42 m/s. Additionally, wetland restoration reached an area of 396.4 hectares, and shoreline recovery extended for 6.65 km, leading to enhance habitat conditions. The project area adheres to the II Class seawater quality standards outlined in the “Seawater Quality Standards” (GB3097-1997 [42]). Water quality monitoring indicates that inorganic nitrogen (IN) and chemical oxygen demand (COD) are the primary pollutants exceeding permissible limits. After the repair, the IN concentration changed from (568~977 μg/L) to (684~944 μg/L), but still reached IV Class. In contrast, the COD concentration decreased from (1.28~3.48 mg/L) to (0.76~0.968 mg/L) and reached I Class. A comparison of these two factors with seawater quality standards is illustrated in Figure 3. In terms of sediment quality, the monitoring factors of each station were in line with the I Class of Marine Sediment Standard (GB 18668-2002 [49]) before and after construction. In combination with the excellent background conditions and the improvement of some factor data after construction, the indicator was assigned 75 points. As shown in Figure 4, the diversity index of plankton and macrobenthos decreased due to the impact of construction, especially the diversity index of benthic organisms, and the biodiversity index rebounded after the completion. With reference to the assessment results of [27] of other restoration cases, it is estimated that the biodiversity will be improved to a certain extent in 5 years after the restoration implementation. Therefore, this paper sets the increase rate of the diversity index at 10%~20% and assigns 50 points.

The Daling River Estuary (DLH) project was monitored before construction (November 2019) and after construction (July 2020). Typical indicator monitoring data show (Figure 2) that after the removal of the cofferdam, the average strength of ebb increased by about 0.2 m/s, the project restored 1 km of ecological shoreline, restored 190 hectares of wetlands, and improved the hydrodynamic and habitat conditions simultaneously. The project area implemented the I Class seawater water quality standard in the Seawater Water Quality Standard (GB3097-1997). Before the restoration, the COD concentration of some survey stations exceeded I Class but reached II Class seawater quality standards, and the IN content exceeded IV Class standards. After the restoration, the COD content increased from (1.44~2.81 mg/L) to (2.28~2.96 mg/L). IN concentration decreased significantly from (608~968 μg/L) to (194.8~200.8 μg/L) (Figure 3). In the sediment evaluation, the restoration project had a certain impact on the sediment in the surrounding sea area, but the degree is very limited. It did not change the original excellent state of the quality standard of I class sediment, which is also awarded 75 points. As shown in Figure 4, both plankton and macrobenthos biodiversity have declined. Considering that they are also affected by the construction period, biodiversity will recover after a certain period of time, so they are both assigned 50 points.

3.2. Ecosystem Services

Figure 5a shows the change of ecological service in the PLD project. In the PLD project, the value of supply service was greatly decreased by 53.15% after the restoration. Contrary to the supply service, the regulating service has been greatly improved after repair, increasing by 259.82%. The value of cultural services was increased by 58.79%. The ecosystem service value before ecological restoration was CNY 59.89 million/a, and after restoration was CNY 39.72 million/a.

Refer to Figure 5b for changes of ecological service indicators of Daling River. The value of supply services decreased by 13.43%. The project restored the ecological coastline by 1 km, which increased the value of regulating service by 65.94%. The value of cultural services has increased by 36.89%. The value of ecosystem services before restoration was calculated to be CNY 15.24 million/a, and it was CNY 15.38 million/a after restoration.

3.3. Questionnaire

A total of 80 questionnaires were distributed to residents near the PLD project, and 67 questionnaires were recovered. A total of 80 questionnaires were distributed to residents near the DLH project, and 73 were recovered. The evaluation results of social and economic benefits are shown in

Table 9. Social and economic benefits questionnaire survey results.

Indicator	PLD		DLH
	Evaluation	Score	Evaluation	Score
Repair effect satisfaction	very satisfied	95.52	very satisfied	96.92
Public participation	higher participation or willingness to participate	84.70	higher participation or willing-ness to participate	86.64
Degree of impact on productive life	some positive impact	60.45	some positive impact	60.27
Income impact on residents	general	51.86	general	53.77
Level of social recognition of economic benefits	very agree	90.67	very agree	93.15

.

3.4. Comprehensive Assessment

The ecological restoration project in Pulandian Bay was assessed to have a comprehensive score of 77.18, with a restoration effect of “good”. The assessment results and scores of the indicators are shown in

Table 10. Assessment results of ecological restoration project in Pulandian Bay.

Indicator	Score	A–D Weight	Indicator Score	Factor Layer Score	Criterion Layer Score	Result
Strength of ebb	100	0.0813	8.13	C1 12.75	B1 56.41	A 77.18
Seawater quality	25	0.0504	1.26
Sediment quality	75	0.0448	3.36
Macrobenthos species diversity	50	0.0478	2.39	C2 7.17
Zooplankton species diversity	50	0.0478	2.39
Phytoplankton species diversity	50	0.0478	2.39
Shoreline ecologization rate	100	0.1202	12.02	C3 22.48
Ecological restoration area	100	0.1046	10.46
Supply service	0	0.0557	0	C4 14.01
Regulation service	100	0.0916	9.16
Cultural service	100	0.0485	4.85
Repair effect satisfaction	95.52	0.0789	7.54	C5 7.54	B2 11.96
Public participation	84.70	0.0287	2.43	C6 4.42
Degree of impact on productive life	60.45	0.0330	1.99
Income impact on residents	51.86	0.0506	2.62	C7 2.62	B3 8.81
Level of social recognition of economic benefits	90.67	0.0683	6.19	C8 6.19

. The ecological restoration project of the Daling River estuary scored a comprehensive score of 80.19, and the restoration effect is “excellent”. The results and scores of the indicator assessment are shown in

Table 11. Assessment results of ecological restoration project in Daling River estuary.

Indicator	Score	A–D Weight	Indicator Score	Factor Layer Score	Criterion Layer Score	Result
Strength of ebb	100	0.0813	8.13	C1 16.53	B1 58.98	A 80.19
Seawater quality	100	0.0504	5.04
Sediment quality	75	0.0448	3.36
Macrobenthos species diversity	50	0.0478	2.39	C2 7.17
Zooplankton species diversity	50	0.0478	2.39
Phytoplankton species diversity	50	0.0478	2.39
Shoreline ecologization rate	100	0.1202	12.02	C3 22.48
Ecological restoration area	100	0.1046	10.46
Supply service	0	0.0557	0	C4 12.8
Regulation service	100	0.0916	9.16
Cultural service	75	0.0485	3.64
Repair effect satisfaction	96.92	0.0789	7.65	C5 7.65	B2 12.13
Public participation	86.64	0.0287	2.49	C6 4.48
Degree of impact on productive life	60.27	0.0330	1.99
Income impact on residents	53.77	0.0506	2.72	C7 2.72	B3 9.08
Level of social recognition of economic benefits	93.15	0.0683	6.36	C8 6.36

. The scores for each indicator are presented in Figure 6.

4. Discussion

This study aims to build an effect assessment system for marine ecological restoration projects with comprehensive indicator coverage and intuitive restoration effects, reveal problems in project implementation and propose optimization strategies through scientific assessment. We conducted an assessment of the ecological restoration projects at Pulandian Bay in Dalian and Daling Estuary in Jinzhou. The results indicated that the comprehensive score for Pulandian Bay (PLD) was 77.18, reflecting a “good” restoration effect, while the score for Daling Estuary (DLH) was 80.19, indicating an “excellent” restoration effect.

From the perspective of ecological and environmental effects, the two projects have improved the hydrodynamic conditions, but have little impact on the sediment environment. DLH seawater quality remained unchanged, but compared with PLD seawater, quality improvement effect is better. Both projects caused short-term disturbance to regional species diversity, but the restoration effect of wetland area and ecological shoreline length was very significant. In terms of ecosystem service value, the cofferdam removal measures were taken in both projects, resulting in the reduction of mariculture area and the decline of food supply value. However, wetland restoration enhances ecological functions such as oxygen production and climate regulation, and increases the value of ecosystem services. Since the natural shoreline’s disturbance regulation value is much higher than the artificial shoreline, the two projects have restored the natural shoreline, and the disturbance regulation value has been significantly increased. In addition, the significance of ecological restoration research has become increasingly pronounced. The average annual number of publications in this field has also risen, thereby enhancing the value of scientific research and educational services. Therefore, in addition to the reduction of supply service value caused by the removal of aquaculture cofferdams, the regulation service and cultural service value of PLD and DLH projects have been increased. From the perspective of social benefits, the surrounding residents are very satisfied with the effects of the two ecological restoration projects, the public has a high willingness to participate, and the projects have a certain positive impact on the improvement of production and living conditions of residents. From the perspective of economic benefits, the project demolition of aquaculture cofferdams has little impact on residents’ income, and residents strongly agree with the economic benefits brought by ecological restoration projects. In general, the implementation of the two ecological restoration projects has restored the ecological shoreline and wetland area in the region, which has improved the environmental status of the region, enhanced the value of ecosystem services, and had a good social and economic impact.

Compared with the assessment results of other studies using the AHP method [27], there is a good consistency with the results of this paper. It is believed that the ecological restoration projects adopted have certain effects, which to a certain extent verifies the feasibility of the evaluation method in this paper. Furthermore, restoration will improve the ecological environment and bring about broader social and economic benefits. This result is also consistent with the current focus of marine ecological restoration under discussion [13,37,50].

4.1. Indicator Weight Analysis

In the assessment system of marine ecological restoration effect established in this study, the weights of criteria layers for ecological environment, social benefit, and economic benefit are 0.7405, 0.1406, and 0.1189. This weight allocation is based on the analytic hierarchy process (AHP) and expert judgment, reflecting the core goal of marine ecological restoration project—ecological environment restoration as the leading consideration, while taking into account social acceptance and economic feasibility. The high weight reflects that the fundamental task of the ecological restoration project is to enhance the service function of the ecosystem by restoring the natural shoreline, wetland area, and biodiversity. For example, in the PLD and DLH projects, indicators with high weight, such as shoreline ecological rate (D7, weight 0.1202) and ecological restoration area (D8, weight 0.1046), contributed significantly to the comprehensive score, and were highly consistent with the actual results of the projects (396.4 hectares and 190 hectares of wetland restoration area). In addition, although the weight of sea water quality (D2, weight 0.0504) and biodiversity (D4–D6, weight 0.0478) is relatively low, their changes still provide a key basis for assessment. The weight of social benefits is slightly higher than that of economic benefits, indicating that the restoration project should give priority to protecting public interests and social recognition. The satisfaction of the public is the core factor of whether the restoration project can get long-term support, and the impact of production and life is directly related to the daily well-being of the residents. Because the economic benefits through the improved environment gradually release, the short-term quantification is difficult. Therefore, the system emphasizes more on residents’ “social identity” to economic benefits (D16, weight 0.0683), rather than direct economic benefits (D15, weight 0.0506).

4.2. Analysis of Reasons for Differences in Assessment Results

According to the evaluation results, the scores of the Pulandian Bay and Daling River projects were 77.18 and 80.19 respectively, and the overall restoration effect of the DLH project was better than that of the PLD project, which may be attributed to the following reasons: (1) The content of inorganic nitrogen in water body varies seasonally, usually lowest in summer, peaking in winter, and relatively high levels in spring and autumn. The monitoring of PLD project before and after construction in two seasons with relatively high inorganic nitrogen content obscure the actual improvement effect of the restoration project on inorganic nitrogen level to a certain extent. In contrast, the DLH project conducted pre-construction monitoring in autumn and post-construction monitoring in summer (the season with the lowest inorganic nitrogen content). As a result, the monitoring value may be more conducive to highlight the positive impact of the restoration project on the inorganic nitrogen content, resulting in higher seawater quality index after restoration than PLD. (2) According to the results of the questionnaire survey, the evaluation of the PLD project is lower than that of the DLH project. The main reason is that the demolition area of the culture cofferdam in Pulandian Project is large. Although it is conducive to the long-term restoration of the ecological environment, it has a direct impact on the income of some fishermen in the short term, and then affects their overall evaluation of the project. In view of this situation, it is suggested that the government departments should strengthen communication with the affected fishermen, consider establishing a reasonable compensation mechanism, and explain the importance and long-term benefits of ecological restoration projects in detail, so as to reduce their economic burden and win their understanding and support.

4.3. Significance of Restoration Project Assessment and Improvement Recommendations

From the perspective of restoration project assessment, timely evaluation of such projects can help accurately measure their success and ensure that the project restoration objectives meet expectations. Through comparative analysis of the changes of various indicators, the improvement of ecological environment in the restoration area can be intuitively displayed. As for the problems and deficiencies found in the assessment process, certain measures and management means can be adopted to carry out follow-up adjustment and planning of the project. For example, after the implementation of the two restoration projects, their species diversity has declined due to construction interference, but the restoration of the wetland area provides more habitats for organisms, so the biodiversity will be improved to a certain extent, but it will take 3 to 5 years. In view of this, in order to minimize the negative impact during construction, a series of measures should be taken, such as choosing a season with less impact on the ecosystem to avoid the peak of biological reproduction. At the same time, the scope of construction should be minimized to avoid the impact on the larger sea area, but also after the completion of the project, appropriate artificial proliferation and stocking should be undertaken to accelerate the recovery of the ecosystem.

4.4. Recommendations for the Sustainability of Ecological Restoration

To ensure the effectiveness and sustainability of the restoration work, it is recommended that the relevant departments implement ecological restoration projects under the guidance of the “Guidelines for Ecological Protection and Restoration Projects of Mountains, Waters, Forests, Fields, Lakes and Grasses (Trial)”, as well as the provincial ecological restoration plans for land space [51]. Ecological restoration of coastal zones with “natural restoration as the main” should be advocated for, emphasizing the use of technologies to optimize spatial layout and resource management in land-sea interlace areas. The process and mechanism of natural restoration of coastal ecosystems should be fully considered to improve the efficiency of ecological restoration [52]. Local governments should also actively coordinate resources and vigorously promote marine ecological restoration projects. At the same time, the public is encouraged to actively participate in and cooperate with the project. For the residents affected by the project, the government can provide direct economic compensation, ensure the livelihood of residents through policy guidance and financial support, and promote the sustainable development of the community. Before formulating the ecological restoration plan, the current situation of resources and environment in the sea area where the restoration area is located should be fully investigated, and the ecological fragile and functional areas should be identified. On this basis, assess the possible environmental impact of the project implementation, take into account the short-term and long-term effects brought by the project, strengthen the management and maintenance of the later stage of the project, regularly monitor the change of the ecological environment, timely adjust the restoration strategy, and ensure the realization of the project objectives.

5. Conclusions

This study focuses on marine ecological restoration projects and preliminarily constructs an assessment indicator system by integrating ecosystem services from three aspects: ecological environment, social benefits, and economic benefits. The analytic hierarchy process (AHP) is used to determine the weights of indicators at each level. The effectiveness of the restoration projects is evaluated using the cases of the Pulandian Bay and the Daling River Estuary ecological restoration projects as examples. The following conclusions can be drawn:

(1)

The assessment results show that the ecological restoration project of Pulandian Bay scored 77.18, with a “good” restoration effect, and the ecological restoration project of Daling River Estuary scored 80.19, with a “excellent” restoration effect. Both projects realized the goals of improving the regional ecological environment, upgrading the ecosystem service function, improving the quality of life of the residents, and improving the ecosystem service functions.

(2)

Compared with the previous evaluation system, the system constructed in this paper has the following advantages: on the one hand, the indicators covered in the system can fully reflect the impact of ecological restoration on the ecological environment and economic society; on the other hand, by calculating the value of ecosystem services, the benefits of this marine ecological restoration project can be intuitively displayed, reflecting the contribution of the ecosystem to human well-being.

(3)

However, the applicability of the system to specific restoration projects still needs to be further explored. For example, vegetation restoration projects need to increase vegetation coverage indicators, and sandy coastal projects need to consider beach resource indicators. In addition, management indicators (such as project progress, construction quality, tracking and monitoring) can be added to fully reflect the implementation of the project. In the future, more case optimization indicators and quantitative standards will be combined to further improve the comprehensiveness and applicability of the system.

(4)

In addition, this assessment is based on the periodic survey data before and after restoration, which only reflects the short-term effect, and some restoration effects (such as species diversity restoration) need long-term monitoring to fully reflect. It is recommended that follow-up studies extend the assessment time to 3–5 years or longer, and continue to monitor data to assess the repair effect more comprehensively and accurately.