1. Introduction

2. Materials and Methods

2.1. Study Area

The Mulberry-Dyke and Fish-Pond System in Huzhou, Zhejiang Province (37°12′18″N and 120°17′40″E) is situated in the plains on the southern shore of Lake Taihu, characterized by a subtropical climate with an average annual temperature ranging from 17.8°C to 18.2°C and an annual precipitation of 1,348-1,723 mm. Designated as a Globally Important Agricultural Heritage Systems (GIAHS) in 2017. Digang Village, located within Nanxun District of Huzhou, is an important monitoring site for the Mulberry-Dyke and Fish-Pond System, with a total area of about 643 hm², consisting of arable land, garden land, forest land, grassland waters and water facilities land, construction land and other land, of which the area of the Mulberry-Dyke and Fish-Pond System is about 220 hm², and the main agricultural activities in the village are freshwater fish farming and mulberry silkworm cultivation. The most important agricultural species in the system include 2 types of silkworms, 4 types of mulberry trees, 7 types of fish species, and 3 types of fruits and vegetables, with a household population of about 1,141, of which the number of farmers providing heritage tourism services is about 280, and a per capita income of 6,500 yuan for farmers operating agro-cultural heritage. The village has a core conservation area for mulberry-based fish ponds, which covers an area of about 66 hm², of which the mulberry orchards cover an area of about 23-25 hm² and the fish ponds cover an area of about 33-35 hm². The study is based on the village of Dikgang and the core conservation area within the village within this scope.

Figure 1. Location of the core conservation area of Mulberry-Dyke and Fish-Pond System in Digang Village, Huzhou, China.

Figure 1. Location of the core conservation area of Mulberry-Dyke and Fish-Pond System in Digang Village, Huzhou, China.

2.2. Methodology and Data

2.2.1. Modeling the Valuation of ES

A scientific evaluation index system serves as the prerequisite and foundation for the effective evaluation of ecosystem services in Mulberry-Dyke and Fish-Pond System [18]. In the classification of ES by the MA [10], Provisioning Ecosystem Services (PES) encompass services produced or provided by ecosystems, such as food, fiber, genetic resources, etc. RES are benefits derived from the regulating function of ecosystem processes, including the regulation of atmospheric quality, climate, and the environment, etc. CES refer to non-material benefits obtained from ecosystems. Additionally, supporting services represent a function of ecosystems necessary for the provision of other services. In the context of Mulberry-Dyke and Fish-Pond System, PES, RES, and CES were specifically selected to construct a comprehensive ecosystem service evaluation system.

Building upon existing literature [19,20,21,22,23,24,25], results of discussions with 4 experts in ecology, and an assessment of the operational status of Mulberry-Dyke and Fish-Pond System, the evaluation index system was designed. Given the significance of mulberry harvesting and fish farming densities in these fishponds [26,27,28], the production of mulberries and fish was chosen to characterize the PES. Differences in temperature and humidity between Mulberry-Dyke and Fish-Pond System and downtown Huzhou City, as well as the air quality index of Mulberry-Dyke and Fish-Pond System, were used to characterize the climate regulation value of the RES, and its basal environmental regulation capacity was flanked by the pesticide and fertilizer use in Mulberry-Dyke and Fish-Pond System, thus characterizing the basal environmental regulation value of the RES [29,30,31,32]. CES were characterized with four aspects: aesthetics, education, leisure and entertainment, and cultural heritage [33,34]. The finalized evaluation index system comprises one objective, three guidelines, 8 indicators, and 29 factors. The specific framework of the index system is detailed in Table 1 below.

2.2.2. AHP-FCE Based Ecosystem Service Evaluation model For Mulberry-Dyke and Fish-Pond System

The evaluation model consists of two main parts. First, the Analytical Hierarchy Process (AHP) method is employed to establish the weights for the indicators within the ecosystem service evaluation system for Mulberry-Dyke and Fish-Pond System. Then, the multilevel Fuzzy Comprehensive Evaluation (FCE) method is applied to conduct a comprehensive assessment of the ecosystem services of Mulberry-Dyke and Fish-Pond System. The integrated AHP-FCE evaluation model is outlined as follows:

The evaluation model is divided into 2 parts, firstly, the AHP method is used to determine the weights of the indicators of the ecosystem service evaluation system of Mulberry-Dyke and Fish-Pond System, based on which the multilevel FCE method is used for the comprehensive evaluation of the ecosystem services of Mulberry-Dyke and Fish-Pond System. The evaluation model integrated AHP-FCE method is as follows:

(1) Establishment of evaluation factor domain and evaluation criteria

Establishment of the evaluation factor domain V for ecosystem services in Mulberry-Dyke and Fish-Pond Systems, divided into 5 Levels.

Table 2. The evaluation criteria for the Mulberry-Dyke and Fish-Pond System ecosystem services.

Table 2. The evaluation criteria for the Mulberry-Dyke and Fish-Pond System ecosystem services.

Level	Score range	Definition
Ⅰ	4~5	High ecosystem services
Ⅱ	3~4	Relatively high ecosystem services
Ⅲ	2~3	General ecosystem services
Ⅳ	1~2	Relatively low ecosystem services
Ⅴ	0~1	Low ecosystem services

Table 3. Quantitative Factor Assessment Criteria.

Table 3. Quantitative Factor Assessment Criteria.

Criterion Layer	Index Layer	Factor Layer	Level
			5	4	3	2	1
B1 Provisioning ecosystem services	C1 Mulberry land production value	D1(t / hm²) Mulberry leaf production	≥75.00	52.50~75.00	45.00~52.50	37.50~45.00	≤37.50
		D2(t / hm²) Mulberry fruit production	≥75.00	60.00~75.00	42.00~60.00	36.00~42.00	≤36.00
	C2 Fishpond production value	D3(t / hm²) Conventional fish farming production	≥90.00	67.50~90.00	45.00~67.50	22.50~45.00	≤22.50
		D4(t / hm²) Ecological fish farming production	≥45.00	33.80~45.00	22.50~33.80	11.3~22.50	≤11.30
B2 Regulating ecosystem services	C3 Basal environment regulation value	D5(kg/hm²) Fertilizer application intensity	<200.00	200.00~250.00	250.00~350.00	350.00~450.00	>450.00
		D6(kg/hm²) Pesticide application intensity	<2.50	2.50~3.00	3.00~4.00	4.00~4.50	>4.50
	C4 Climate regulation value	D7 (%) Relative humidity adjustment range	>4.00	3.00~4.00	2.00~3.00	1.00~2.00	<1.00
		D8 (℃) Average temperature regulation	>4.00	3.00~4.00	2.00~3.00	1.00~2.00	<1.00
		D9 Air quality index	<50.00	50.00~100.00	100.00~150.00	150.00~200.00	>200.00

Based on the aforementioned evaluation factor domain V, in conjunction with relevant criteria and references [35,36,37,38], the quantitative factor evaluation standards were established. The data related to mulberry leaf production (D1), mulberry fruit production (D2), Conventional fish farming production (D3), ecological fish production (D4), as well as fertilizer and pesticide usage, were sourced from the Huzhou agricultural science and technology development center academician and expert workstation specializing in Mulberry-Dyke and Fish-Pond System. Additionally, the air quality index (D9) was determined based on China's "Ambient air quality standards" GB3095-2012.

Qualitative data is characterized by five levels of satisfaction (very familiar, quite familiar, moderately familiar, slightly familiar, unfamiliar) to represent the membership degree of evaluation indicators to the evaluation factor domain V.

Table 4. Qualitative Factor Definitions.

Table 4. Qualitative Factor Definitions.

Criterion Layer	Index Layer	Factor Layer	Definition
B3 Culture ecosystem services	C5 Aesthetics value	D10 Plant landscape richness	Hierarchical sense of trees, shrubs, and ground cover vegetation; diversity of species.
		D11 Seasonal changes in the landscape	Seasonal changes in trees, shrubs, and ground cover vegetation, including both woody and herbaceous plants.
		D12 Overall harmony	The overall sense of harmony within the village, formed by the cultural landscapes, streets, alleys, architecture, and vegetation within the village.
		D13 Water clarity	The condition of water bodies in the environment.
		D14 Leveling and hardening of road surface	Whether the road conditions are in accordance with the environment, including within the village and inside the Mulberry-Dyke and Fish-Pond System, with visual comfort as the criterion.
	C6 Education value	D15 Fish and mulberry culture education	The educational significance or value brought by fish-mulberry culture and the research-oriented activities centered around it.
		D16 Humanistic tradition	The existing stories of prominent individuals, their spirit, and character within the village that possess propagational and educational significance.
		D17 Cultural propaganda and exhibition	The educational significance or value brought by the promotion and display of folk culture.
		D18 Religious culture propaganda	The spiritual connotations brought by the religious culture atmosphere, as well as the level of understanding and acceptance of it.
	C7 Leisure and entertainment value	D19 Location conditions	The accessibility of the village's geographical location, transportation convenience, and natural environment.
		D20 Sanitary conditions	Environmental hygiene conditions.
		D21 Tourism infrastructure	Basic infrastructure including toilets, signage, parking spaces, medical service facilities, etc.
		D22 Agricultural Diversity Experience	Diverse experiences provided by agricultural products such as freshwater fish, mulberry leaf tea, fruits, rice, sesame oil, etc., based on the raw materials produced in Digang Village, which are either processed or directly sold.
		D23 Experience the diversity of tourism products	Satisfy diversified tourism needs by visiting Digang Village.
		D24 Visual and psychological perception	Experiences of visual and psychological sensations brought about by exploring Digang Village.
	C8 Cultural heritage value	D25 Village architectural style	Whether the architectural style within the village conforms to the characteristics of the Jiangnan water town and rural farming.
		D26 Village Traditional customs	Whether traditional folk customs within the village are fully preserved, whether the atmosphere of folk customs is good, and whether they have distinctive features.
		D27 Ancient bridges and other historical and cultural features	The distinctiveness of cultural landscapes such as ancient bridges, celebrity memorial halls, and the scenic beauty of Nantiao.
		D28 Food culture characteristics	The distinctiveness of Di Gang cuisine, exemplified by the Chen family's dishes and local snacks.
		D29 Fish and mulberry culture characteristics	The distinctive features of the fish-mulberry culture.

(2) Determination of weight values

Applying the AHP method to determine the weights of each index. Comparisons are made pairwise among indicators at the same level to construct a judgment matrix. The normalization of weight values and weight vectors is then accomplished through relevant calculation formulas. The weight vector set is obtained through the verification steps [39,40].

(3) Constructing the affiliation matrix

Determine the membership degree of the evaluated object to the evaluation factor domain and obtain the fuzzy relationship matrix. In this study, the membership degree of quantitative data to the evaluation factor domain was determined through a trapezoidal function, and the membership degree of qualitative data to the evaluation factor domain was obtained through statistical analysis [41].

(4) Obtaining a composite score for the overall goal

Building on the aforementioned analysis, the overall goal composite score (F) was calculated using the weighted average method, expressed as F = W·R.

Where W represents the weight vector set, and R represents the membership matrix.

2.2.3. Data

Table 5. Quantitative Data Acquisition.

Table 5. Quantitative Data Acquisition.

Name	Unit	Data	Data sources
Mulberry land production	t/hm²	75.00	Huzhou Agricultural Science and Technology Development Center Academician and Expert Workstation
Mulberry fruit production	t/hm²	75.00
Conventional fish farming production	t/hm²	90.00
Ecological fish farming production	t/hm²	45.00
Fertilizer consumption	t	4.00
Pesticide consumption	CNY	34500.00
Change in relative humidity (July-September 2022)	%	-1.42	Internal level meteorological information of Huzhou Municipal Meteorological Bureau
Change in average temperature (July-September 2022)	℃	-0.42
AQI	/	64.90	http://www.weather.com.cn/

Data related to Mulberry-Dyke and Fish-Pond System in 2022 were collected through various methods, including interviews, questionnaires, field trips, and applications. The quantitative indicators were primarily sourced from the Huzhou agricultural science and technology development center academician and expert workstation. This data encompassed mulberry and fish production, as well as the quantities of fertilizers and pesticides used. Air quality index data were obtained from the weather network (http://www.weather.com.cn/). Qualitative indicators were gathered through a one-to-one questionnaire survey conducted with tourists and villagers engaged in activities at Digang Village Mulberry-Dyke and Fish-Pond System. A total of 109 questionnaires were initially collected, with 100 valid questionnaires selected after screening to exclude those completed in less than 2 minutes.

3. Results

3.2. Fuzzy Comprehensive Evaluation and Results

Refer to Appendix B for the calculation process. According to the principle of the maximum affiliation function of the FCE method, the affiliation degrees of ecosystem services of Mulberry-Dyke and Fish-Pond System are as follows: high level: 0.44, relatively high level: 0.32, general level: 0.10, relatively low level: 0.03, and low level: 0.11. The weighted average result is calculated as [0.44, 0.32, 0.10, 0.03, 0.11] × [5, 4, 3, 2, 1] = 3.97, indicating that the ecosystem services of Mulberry-Dyke and Fish-Pond System belong to the relatively high level. Multiply the membership degrees of each criterion, index, and factor by the normalized weights of each layer, as shown in Figure 2.

The evaluation results of the indicators at the normative level are presented in Figure 2a. Both PES (B1) and CES (B3) exhibit high performance, predominantly at the high and relatively high levels. In contrast, RES (B2) demonstrate a comparatively lower performance, mainly at the relatively low and low levels.

The evaluation results at the indicator and factor levels are depicted in Figure 2b,c. Notably, the four indicators related to the production value of mulberry land (C1) and fishponds (C2) excel, predominantly at the high level. This suggests that the production capacity of mulberry leaves, mulberry fruits, black carp, and eco-fish in Mulberry-Dyke and Fish-Pond System is robust. On the other hand, the basal environmental regulation value (C3) and climate regulation value (C4) exhibit lower performance, largely at the relatively low and low levels. This is primarily influenced by factors such as the intensity of pesticide application (D6), relative humidity regulation (D7), and average temperature regulation (D8). These results indicate deficiencies in pesticide use and the regulation of humidity and temperature in Mulberry-Dyke and Fish-Pond System. In contrast, the evaluation results for the four values of aesthetic value (C5), educational value (C6), leisure and entertainment value (C7), and cultural heritage value (C8) demonstrate a high degree of affiliation to high and relatively high, signifying high performance in these aspects. Among the five main values of ecosystem services in Mulberry-Dyke and Fish-Pond System, the climate regulation value (C4) is at the low level, indicating an important aspect that requires improvement. However, the top eight indicators in the factor hierarchy largely perform at the high or relatively high levels, suggesting a positive role in promoting the ecosystem services of Mulberry-Dyke and Fish-Pond System.

Table 7. Matrix of Quantitative Factor Memberships.

Table 7. Matrix of Quantitative Factor Memberships.

Factor Layer	Membership Matrix
	5	4	3	2	1
D1 Mulberry leaf production	1.0000	0.0000	0.0000	0.0000	0.0000
D2 Mulberry fruit production	1.0000	0.0000	0.0000	0.0000	0.0000
D3 Conventional fish farming production	1.0000	0.0000	0.0000	0.0000	0.0000
D4 Ecological fish farming production	1.0000	0.0000	0.0000	0.0000	0.0000
D5 Fertilizer application intensity	0.6970	0.3030	0.0000	0.0000	0.0000
D6 Pesticide application intensity	0.0000	0.0000	0.0000	0.0000	1.0000
D7 Relative humidity adjustment range	0.0000	0.0000	0.0000	0.0000	1.0000
D8 Average temperature regulation	0.0000	0.0000	0.0000	0.4200	0.5800
D9 Air quality index	0.0000	0.7020	0.2980	0.0000	0.0000

Table 8. Matrix of Qualitative Factor Memberships.

Table 8. Matrix of Qualitative Factor Memberships.

Factor Layer	Membership Matrix
	5	4	3	2	1
D10 Plant landscape richness	0.3600	0.5900	0.0500	0.0000	0.0000
D11 Seasonal changes in the landscape	0.3200	0.5900	0.0800	0.0000	0.0100
D12 Overall harmony	0.3100	0.5700	0.1000	0.0200	0.0000
D13 Water clarity	0.1100	0.5000	0.2900	0.0900	0.0100
D14 Leveling and hardening of road surface	0.2800	0.5100	0.1800	0.0300	0.0000
D15 Fish and mulberry culture education	0.3200	0.4700	0.1600	0.0400	0.0100
D16 Humanistic tradition	0.3500	0.5000	0.1100	0.0400	0.0000
D17 Cultural propaganda and exhibition	0.3000	0.4400	0.2200	0.0400	0.0000
D18 Religious culture propaganda	0.1200	0.2500	0.2500	0.3100	0.0700
D19 Location conditions	0.2800	0.4700	0.2200	0.0300	0.0000
D20 Sanitary conditions	0.3300	0.4900	0.1500	0.0200	0.0100
D21 Tourism infrastructure	0.2500	0.4900	0.2400	0.0200	0.0000
D22 Agricultural Diversity Experience	0.2100	0.6100	0.1800	0.0000	0.0000
D23 Experience the diversity of tourism products	0.1800	0.5900	0.2000	0.0300	0.0000
D24 Visual and psychological perception	0.3500	0.5300	0.0900	0.0300	0.0000
D25 Village architectural style	0.3700	0.4600	0.1600	0.0100	0.0000
D26 Village Traditional customs	0.3500	0.4900	0.1500	0.0100	0.0000
D27 Ancient bridges and other historical and cultural features	0.4200	0.4500	0.1200	0.0100	0.0000
D28 Food culture characteristics	0.3000	0.5100	0.1700	0.0200	0.0000
D29 Fish and mulberry culture characteristics	0.3000	0.5500	0.1400	0.0100	0.0000

4. Discussion

5. Conclusions

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