Exploring the Perception Differences and Influencing Factors of Ecosystem Services Among Residents in Northeast China Tiger and Leopard National Park

Abstract

Local residents’ satisfaction plays a crucial role in the successful management of national parks. However, limited attention has been paid to residents’ preferences in the management of national parks, which hinders the sustainable development and optimization of management systems. To address this gap, we focused on the Dongning area of Northeast China Tiger and Leopard National Park (NCTLNP) as a case study and employed the importance–performance analysis (IPA) framework to assess residents’ perceptions and cognitive rankings of current ecosystem services. Additionally, we examined how demographic and socio-economic factors influence these perceptions. Our findings reveal that local residents prioritize ecosystem services that directly impact their livelihoods and that their material, social, spiritual, and cultural needs are not fully met. Satisfaction and importance ratings varied across regions, with significant influences occurring from the residents’ sex, occupations, and livelihoods. Based on these results, we recommend strengthening the institutional framework for national park management and enhancing the scientific effectiveness of management policies by incorporating residents’ perspectives into decision-making processes.

1. Introduction

Ecosystem services (ESs) refer to all the environmental conditions and processes formed, maintained, and realized by natural ecosystems and the species living within them, which are essential for human life. They are the benefits humans directly or indirectly obtain from ecosystem functions, including the goods and services provided by ecosystems [1,2]. The United Nations Millennium Ecosystem Assessment (MA) classifies ecosystem services into four categories: provisioning, regulating, supporting, and cultural services, a classification still in use today [3]. Some scholars categorize them into intermediate services, final services, and benefits [4,5].

Sustainable ecosystem services, ranging from providing clean water to offering recreational opportunities, are widely recognized as essential for human well-being [6]. However, a concerning trend has emerged, with reports indicating that more than half of all ecosystem types have experienced degradation [7]. Therefore, the relationship between ecosystem service and human well-being has become the focus of current research. Understanding the measurement of ecosystem services is fundamental for recognizing their contribution to human well-being and informing effective policy and management decisions [8].

Scholars have developed diverse methods to assess ESs, broadly categorized into value-based (monetary) and material-based (non-monetary) approaches. Monetary methods include the hedonic pricing model [9] and willingness-to-pay surveys [10,11,12,13], while non-monetary approaches encompass structural equation modeling (SEM) [14,15,16,17] and production function analysis [18,19]. Additionally, remote sensing has emerged as a powerful tool for natural assessments [20,21,22,23]. However, quantifying ESs—particularly their social value and intangible benefits—remains challenging due to their subjective nature and beneficiaries’ varying perceptions [24]. This complexity underscores the need for social science perspectives, such as perception assessments, to complement natural science methods and enhance sustainable management, especially in protected areas [25].

While ES assessments are well documented at global and national scales, actionable recommendations for regional sustainable management remain underexplored [26]. National parks, as complex socio-ecological systems, are critical components of conservation networks [27]. Existing research on national parks predominantly focuses on future development strategies [28,29,30], rare species conservation [31,32,33], tourism evaluation [34,35,36,37,38,39], and community dynamics surrounding these areas [40,41,42]. Studies addressing local communities often examine conflicts between park development and livelihoods [43,44,45], ecological compensation preferences [46,47], and residents’ willingness to engage in conservation [48,49,50]. However, few investigations center on local residents—the primary economic actors and a socially diverse group—whose perceptions of ES reflect the state and evolution of these services [51]. This gap is significant, as local perceptions shape eco-logical behaviors and socio-economic activities, influencing ES supply and conservation outcomes. Integrating residents’ perspectives as both beneficiaries and stakeholders is thus essential for effective, long-term ecosystem sustainability.

As one of the initial pilot national parks, NCTLNP is characterized by a significant resident population within its boundaries. This study aims to bridge the existing research gap by investigating local residents’ perceptions of ecosystem services (ESs) in the Dongning area of NCTLNP. Employing the importance–performance analysis (IPA) framework, we adapt the MA classification and integrate Maslow’s hierarchy of needs to categorize ESs into 17 items across three domains: basic security, ecological material, and spiritual culture. Our objectives are: (1) to measure residents’ perceptions of ES importance and satisfaction, including changes before and after the national park’s establishment; (2) to explore residents’ needs, preferences, and prioritization of ESs; and (3) to identify factors influencing their ES cognition. By incorporating local perspectives, this study seeks to inform the development of sustainable conservation strategies that are better aligned with regional contexts and community needs.

2. Materials and Methods

2.1. Study Area

This study was conducted in the Dongning area of NCTLNP, located at the China–Russia border region (42°38′45″~44°18′36″ N, 129°05′01″~131°18′52″ E), between Jilin and Heilongjiang provinces (Figure 1). This region represents one of Asia’s critical centers for temperate coniferous and broad-leaved mixed forest ecosystems. Its ecological significance is highlighted by hosting China’s only wild breeding population of Siberian tigers (Panthera tigris altaica) and Amur leopards (Panthera pardus orientalis). The establishment of the park has enhanced the protection of the ecosystem’s authenticity and integrity.

The Dongning area of NCTLNP covers approximately 51,800 hectares, with 38,300 hectares designated as forest and 11,800 hectares designated as cultivated land. This area encompasses 42 villages, with an agricultural population of 17,374, alongside a transient population of about 65,000 forest industrial workers. Since the initiation of the pilot project, the Dongning administration of NCTLNP has actively undertaken conservation and restoration efforts, resulting in significant improvements in local ecosystems and biodiversity.

Due to the Dongning area being a key region in the development of the national park, understanding the perceptions and preferences of local residents regarding ecosystem services is essential for informing institutional frameworks and guiding future management policies as park construction progresses. Therefore, this study selects the Dongning area of NCTLNP as the primary research site for field investigations. The core area (CA) includes Maying Village and Liangzichuan Village, and the general area (GA) includes Naozhigou Village, Hongxing Village, and Shimenzi Village.

2.2. Data Collection

In July–August 2023, we conducted a questionnaire survey to assess the “perception of ecosystem services of local residents in the Dongning area of the NCTLNP”. The local communities are primarily composed of two groups: forestry workers and farmers, both of whom have a significant influence on the local ecological environment and conservation efforts.

To enhance data collection, we employed a mixed-method approach, integrating both online and offline strategies. Given that forestry workers possess certain relevant ecological knowledge and a higher level of understanding, we distributed an electronic questionnaire with the assistance of the staff. For other residents, semi-structured and face-to-face interviews were conducted to gather more in-depth qualitative data. In total, 280 questionnaires were collected, with 261 valid responses received, yielding a response rate of 93.2%.

The survey content is mainly divided into two sections: the basic demographic information of the interviewed residents and their perception of local ecosystem services. The first section gathered data on sex, age, education level, family size, annual household income, per capita living space, daily Internet time, occupation type, participation in ecological and environment-related training, and the improvement of the living environment in the locality. The second part assessed satisfaction with ecosystem services before and after the establishment of NCTLNP and evaluated perceptions of the importance of current ecosystem services. This part utilized three five-point Likert scales, where respondents rated their agreement with statements ranging from “strongly agree” (5 points) to “strongly disagree” (1 point). This format facilitates a clearer expression of attitudes.

To minimize ambiguity in the questionnaire, we involved professional terms in simple and easy-to-understand daily language. Additionally, the questionnaire was interviewed by specialists to ensure consistency with the intended content, ultimately saving time and enhancing the accuracy of the feedback received.

2.3. Method

2.3.1. Importance–Performance Analysis

Traditional methods for assessing local perceptions of ecosystem services often rely on quantitative questionnaires, interviews, and focus groups to gather data [52,53,54,55,56]. However, these approaches have limitations in capturing residents’ subjective perceptions and complex social background. To overcome these limitations, this study employs the importance–performance analysis (IPA) as a structured and visual approach assessing residents’ perceptions. Unlike conventional techniques, IPA simultaneously evaluates the perceived importance and actual satisfaction of service attributes, offering a prioritized framework for decision-making. This methodology has been widely used in tourism management [57,58,59,60], consumer satisfaction studies [61,62,63], and service evaluation [64,65], but its application in ecosystem service management remains underexplored. By integrating IPA, we aim to provide a more effective tool for optimizing resource allocation and improving ecosystem services.

The core of the IPA method lies in constructing a two-dimensional matrix that analyzes services attribute priorities based on two dimensions: importance and performance (satisfaction) [66]. Each service attribute is plotted within a two-dimensional matrix, which categorizes attributes into four quadrants (Figure 2), each representing different categories of service attributes: (1) Quadrant I: Excellent Area, containing attributes that residents consider highly important and with which they are highly satisfied. These services should be maintained to ensure continued satisfaction; (2) Quadrant II: Surplus, including attributes perceived as less important but are with high satisfaction. While these services do not require immediate intervention, their relevance should be monitored; (3) Quadrant III: Careless, containing attributes with low importance and low satisfaction. Further analysis is needed to understand the reasons for low ratings; (4) Quadrant IV: To Be Improved Area, including attributes deemed important but with low satisfaction. These services should be prioritized in management efforts. In the matrix, the intersection point is typically set at the average scores or a predetermined target value, such as 4 or 3 on a 5-point scale, serving as a benchmark for evaluation [67]. Based on the distribution of each attribute within the matrix, targeted improvement strategies can be developed [68].

By applying IPA to ecosystem services, this study identifies priority areas for resources allocation, ensuring maximum return on investment. The findings provide policymakers with a data-driven approach to improve ecosystem service sustainability and resident satisfaction.

2.3.2. Statistical Analysis

(1) Reliability and validity test of questionnaire: Descriptive statistics were applied to analyze the collected questionnaire data. Given the use of multiple scales, reliability and validity assessments were conducted for the satisfaction and importance scales. Cronbach’s alpha was calculated to evaluate internal consistency, with values above 0.7 indicating high reliability. Factor analysis (rotation method) was performed using the maximum variance method, selecting principal components with eigenvalues greater than 1. Data suitability was confirmed using the Kaiser–Meyer–Olkin (KMO) test (>0.6) and Bartlett’s test of sphericity (p < 0.05).

(2) Analysis of residents’ perception degree: In order to quantify the satisfaction and importance ratings of ecosystem services and explore the changes in residents’ perception of ecosystem services before and after the construction of national parks, the ranking data were converted into numerical scores. A weighted sum was calculated using the following scale: a very important or very satisfactory service is weighted by 5, important or satisfied is weighted by 4, generally by 3, unimportant or dissatisfied by 2, very unimportant or very dissatisfied by 1, and then all values are added. The formula is as follows:

$${\mathrm{p}}_{\mathrm{i}}={\displaystyle \frac{1}{\mathrm{n}}}\sum {\mathrm{b}}_{\mathrm{i}\mathrm{j}}$$

(1)

in which p_i is satisfaction perception of importance; b_ij is the rating given by respondent; and n is the number of samples for ecosystem service.

(3) Analysis of influencing factors: Correlation and influence analyses were conducted using a single-factor analysis and multiple-factor analysis. Independent sample t-tests and one-way ANOVA were used for univariate analysis, while multiple linear regression analyzed the combined effects of variables. The regression model was:

$$\mathrm{Y}={\mathsf{\beta }}_0+{\mathsf{\beta }}_1{\mathrm{x}}_1+{\mathsf{\beta }}_2{\mathrm{x}}_2+\dots +{\mathsf{\beta }}_{\mathrm{i}}{\mathrm{x}}_{\mathrm{i}}$$

(2)

where Y is the dependent variable, ${\mathrm{x}}_1$, ${\mathrm{x}}_2$, ..., ${\mathrm{x}}_{\mathrm{i}}$ are independent variables, ${\mathsf{\beta }}_0$ denotes is the constant, and ${\mathsf{\beta }}_1$, ${\mathsf{\beta }}_2$, ..., ${\mathsf{\beta }}_{\mathrm{i}}$ are regression coefficients indicating the effect of each independent variable while holding others constant.

3. Results

3.1. Participants Characteristics

As shown in

Table 1. Demographic and economic information of respondents in the CA and GA.

Variable	Options	Number (CA,GA)	Percentage (%) (CA,GA)	Variable	Options	Number (CA,GA)	Percentage (%) (CA,GA)
Sex	Male	27,112	50.9,53.8	Average living space per person	<30 m2	10,73	18.9,35.1
	Female	26,96	49.1,46.2		30–40 m2	16,102	30.2,49
Age	18–40	14,47	26.4,22.6		41–50 m2	18,15	34,7.2
	41–65	35,130	66,62.5		51–60 m2	5,10	9.4,4.8
	>66	4.31	7.5,14.9		>60 m2	4,8	7.5,3.8
Education level	Primary	5,54	9.4,26	Time spent online per day	0 h	2,19	3.8,9.1
	Junior high	8,29	15.1,13.9		0–1 h	10,33	18.9,15.9
	Senior high and above	40,125	75.4,60.1		1–3 h	25,99	47.2,47.6
Type of occupation	Agriculture leading type	21,132	58.5,63.5		3–5 h	10,48	18.9,23.1
	Non-Agriculture leading type	22,76	41.5,36.5		Over 5 h	6,9	11.3,4.3
Household size	≤2	12,50	22.6,24	Degree of improvement in the living environment at the location	Very poor	0,0	0,0
	3	28,94	52.8,45.2		poor	2,9	3.8,4.3
	4	11,49	20.8,23.6		average	19,61	35.8,29.3
	5	2,10	3.8,4.8		good	25,105	47.2,50.5
	>5	0,5	0,2.4		Very good	7,33	13.2,15.9
Annual household income	≤CNY 50,000	37,105	69.8,50.5	Ecological environment-related training	yes	26,80	49.1,38.5
	CNY 50,000–100,000	14,84	26.4,40.4		no	27,128	50.9,61.5
	CNY 110,000–200,000	1,11	1.9,5.3
	>CNY 200,000	1,8	1.9,3.8

, the demographic profile of the respondents revealed a balanced sex distribution of 53.2% male and 46.7% female participants. Age distribution showed that the largest segment of participants (63.2%) fell within the 41–65 age range. Educational attainment was generally high, with over 63.3% of respondents having completed high school or achieved a higher level of education. Occupationally, a significant portion of the sample (62.4%) was engaged in agriculture-related activities, while the remaining 37.6% were involved in non-agricultural fields. Family size in both the CA and GA was predominantly small, with most households consisting of three members. Regarding economic status, 54.4% of surveyed residents reported an annual household income of less than CNY 50,000; in terms of Internet usage, 47.5% of respondents reported spending 1–3 h online daily, reflecting moderate Internet engagement. Furthermore, a significant majority of residents (65.1%) expressed a positive attitude towards improvements in their living environment, with the majority rating these enhancements as good or very good. There was a higher level of engagement with ecological education in CA, where 49.1% of residents attended courses related to the ecological environment, compared with 38.5% in the GA.

3.2. The Importance of Ecosystem Services

Regarding the importance of ecosystem services, ecological security services received the highest ratings when combining the responses of “important” and “very important”, as presented in Figure 3. These services, which are directly tied to the livelihoods and daily activities of local residents, were identified as the most critical to their well-being. Consequently, the decline or loss of these ecosystem services significantly impacts their quality of life. Six ecosystem services related to ecological security were ranked in the top 50% of importance, reflecting a clear priority for a stable and functional environment that supports both productive activities and daily life.

The overall perception score for indicators associated with ecological security (including air purification, biodiversity maintenance, erosion control, waste management, pest and disease control, climate regulation, and disaster prevention) averaged 3.945. This indicates a strong recognition of the importance of these services in supporting community well-being. This is followed by basic material services, with a perceptual score of 3.345, Among these, the provision of water resources scored particularly high, with an average of 3.9. However, if water resources are excluded from the basic material services category, the average score drops to 3.16, indicating that while basic material services are considered important, other services within this category are perceived as less critical by the residents. Spiritual and cultural services received the lowest average score of 3.17, suggesting that, while valued, these services are not as central to the residents’ immediate needs and concerns.

Residents living in the CA and GA share a consistent perception with the overall perception regarding the importance of ecosystem services, with ecological security services being rated higher than basic material services and spiritual and cultural services. However, it is noteworthy that the importance of perception among residents in the CA is significantly higher than that of those in the GA. This indicates a heightened awareness and valuation of ecosystem services, particularly ecological security, among residents in CA.

3.3. The Satisfaction of Ecosystem Services

According to Figure 4, currently, 96.5% of respondents express satisfaction with biodiversity, while 88.8% report satisfaction with climate regulation. Despite a minority voicing dissatisfaction with climate regulation, their average perception score remains above four. However, satisfaction related to housing, employment, and raw materials is notably low, with an average score of less than four, likely due to development constraints and wildlife attacks.

In terms of service classification, ecological security services receive the highest satisfaction scores, followed by spiritual and cultural services and basic material services, which are consistent with the overall perception rankings in general districts. Residents in the core area, due to its remote location and heightened protective measures, show weaker perceptions of spiritual and cultural ecosystem services, with satisfaction for basic material services being slightly higher.

The trend analysis indicates a decline in basic material services, an increase in spiritual and cultural services, and a decrease in satisfaction with ecological security services overall (Figure 5). Notably, erosion control, natural disaster prevention, and pest control have shown varying degrees of improvement. The trends in satisfaction across different regions reflect these overall patterns; however, the decline in basic materials is more pronounced in the CA compared with the GA, while the increase in spiritual and cultural services is less significant in the CA.

Overall, local residents in the general area perceive basic material services and spiritual and cultural services more than residents in CA. Combined with the actual local situation, policy control, life and production methods, and geographic location are important factors influencing the perceptions of residents in different areas. Residents living in the GA have more diversified production styles, a higher number of migrant workers, and a higher number of farmers engaged in black fungus production. Because there may be more economic activities and industries in this area, residents of the area may have easier access to a stable source of income and solve certain employment problems. At the same time, due to the relatively loose management policy, more human activities exist, including the acquisition of raw materials, the rational development of scientific research, education and recreational functions, etc., all of which have led to a smaller rise in the CA than in the GA.

3.4. IPA Analysis of Ecosystem Service

Based on the proposed analytical framework and operational flow, we constructed a two-dimensional mental map to position various attributes across four quadrants. This study analyzed three dimensions and 14 evaluation indicators from the questionnaire. As indicated in

Table 2. Results of the confidence analysis.

Dimensions	Satisfaction Survey	Importance Survey
	Cronbach’s α	Cronbach’s α
Basic material services—GA	0.787	0.793
Ecological security services—GA	0.825	0.833
Spiritual and cultural services—GA	0.886	0.849
Basic material services—CA	0.801	0.735
Ecological security services—CA	0.824	0.856
Spiritual and cultural services—CA	0.867	0.874

, all dimensions achieved a Cronbach’s alpha of greater than 0.7, indicating high reliability and confidence in the questionnaire’s results.

SPSS 27.0 was used for a validity analysis, utilizing factor analysis to assess residents’ expectations and satisfaction with ecosystem services. Under the condition that the significance is less than 0.001, the KMO value for the importance of residents’ satisfaction is greater than 0.6, as displayed in

Table 3. Results of the effectiveness analysis.

Dimensions	Importance Survey	Satisfaction Survey	Importance–Satisfaction Survey
	KMO Value	KMO Value	KMO Value
GA	0.793	0.774	0.759
CA	0.675	0.728	0.608
All areas	0.799	0.771	0.763

, indicating that the information on local people’s satisfaction and the importance of ecosystem services can be effectively extracted.

The independent samples t-test and one-way ANOVA were conducted to compare residents expected and perceived values of ecosystem services in both the general area and core area of NCTLNP. A significance level of p < 0.05 was used to evaluate differences between the importance and satisfaction of each assessment indicator. Additionally, paired samples t-tests were applied to identify significant differences between residents’ expectations and their actual perceptions. Using the survey data, an importance–satisfaction analysis (IPA) matrix model was developed, with the X- and Y-axes being defined by the mean values of importance and satisfaction, respectively (

Table 4. Mean results for importance and satisfaction.

	All Area	CA	GA
Mean of the satisfaction dimension	3.33	3.24	3.36
Mean of the importance dimension	3.49	3.56	3.47
Mean of the satisfaction item	3.40	3.31	3.42
Mean of the important item	3.61	3.66	3.59

). This intersection point facilitated the creation of the IPA quadrant diagram, allowing for the positioning of each indicator based on its importance and satisfaction scores. The information provided in

Table 5. The importance and satisfaction relative value of all areas.

No.	Items	I	p	Zones
1	providing food	3.74	3.46	excellent
2	providing water	3.9	3.69	excellent
3	provision of raw materials	2.86	2.5	careless
4	provision of a place of residence and employment	2.88	2.59	careless
5	biodiversity maintenance	3.99	4.3	excellent
6	air purification	4.11	3.83	excellent
7	climate regulation	3.88	4.07	excellent
8	erosion control	3.95	3.21	to be improved
9	waste management	3.95	3.45	excellent
10	prevention of natural disasters	3.85	3.35	to be improved
11	pest and disease control	3.88	3.25	to be improved
12	ecotourism value	3.61	3.38	to be improved
13	aesthetic value	3.13	3.33	careless
14	scientific value	2.79	3.21	careless

reveals that the 14 indicators were categorized into three regions: Surplus, Careless, and To Be Improved, with no indicators being identified as requiring moderate regulation. The findings indicate that most indicators fall within quadrants one and four, suggesting that a significant majority of ecosystem services are considered essential by residents. Based on the survey data, we construct an IPA quadrant diagram and locate each indicator based on its I and p values. The 14 indicators were categorized into three areas: Surplus, Careless, and To Be Improved, with no indicators being identified as requiring moderate regulation.

The quadrant analysis data summarized in Table 5 reveals perceptions among local residents regarding their needs and the importance of various ecosystem services. Generally, respondents feel they adequately meet their own needs while recognizing the significance of services such as food provision, water supply, biodiversity maintenance, air purification, climate regulation, and waste management, all of which they believe should be maintained. In contrast, services related to the provision of raw materials, housing, employment, aesthetic value, and scientific value are categorized in Quadrant III, indicating that residents perceive these as neither essential nor important. This suggests a decline in reliance on the direct procurement of timber and other raw materials from national parks, alongside a lack of effective fulfillment of residents’ material, social, and spiritual needs. Attributes in Quadrant III are not perceived as critical by residents but present an opportunity for gradual development. Conversely, Quadrant IV highlights services such as erosion control, natural disaster prevention, pest and disease management, and ecotourism, which residents consider important but feel do not meet their own needs. This mismatch indicates that the current management policy may not be compatible with sustainable development. Among these, the value of ecotourism stands out as a priority, positioned at a critical point within the IPA matrix. There is a satisfactory foundation for this service, with a relatively small gap between reality and expectations. Therefore, it is advisable to revise policies to better align with resident needs, starting with enhancing the value of ecotourism. Among them, the value of ecotourism stands out as a priority, positioned at the critical point within the IPA matrix. There is a certain satisfactory basis, with a relatively small gap between reality and expectation. Therefore, it is advisable for policies to better align with the needs of residents.

The content of the IPA quadrant varies slightly among residents in different regions. As detailed in Figure 6 and Figure 7, in the GA, waste management and ecotourism values are positioned in the first quadrant, indicating that residents place significant importance on these services and have a high degree of satisfaction. Conversely, in CA, waste management falls into the fourth quadrant, suggesting a need to be improved, while the ecotourism value is situated in the third quadrant, indicating that it is a low-priority area. However, compared with satisfaction before the construction of the national park, the improvement of waste management in the CA has been a measurable improvement. And it is close to the X-axis, indicating that the satisfaction gap with the overall means is small. This improvement is likely attributed to ongoing efforts in recycling and properly disposing of pesticide waste packaging and waste fungus bags, which are expected to enhance satisfaction further. The fragile ecology in the CA necessitates stringent management control, while the GA permits moderate, non-disruptive human activities. Additionally, the CA’s remote location and transportation challenges limit the availability of ecotourism programs, contributing to a lower satisfaction rate. Furthermore, the surveyed residents in the CA tend to be older, resulting in limited tourism opportunities and awareness, and they generally perceive ecotourism as unimportant.

3.5. Factors That Influence Participants’ Ecosystem Services

3.5.1. Single Factor Analysis of Influencing Factors

Our findings indicate that perceptions of ecosystem services vary significantly based on key sociodemographic characteristics. Taking the mean of satisfaction items as the dependent variable, and examining factors such as sex, age, education level, occupation type, family size, annual household income, per capita living area, daily Internet access, environmental improvement, eco-environment-related training, and regional division as independent variables, the results showed that the satisfaction of local residents was significantly different in age, occupation type, annual household income, per capita living area, daily Internet access time, and environmental improvement.

Table 6. Single-factor analysis of local residents’ perceptions.

Item	Satisfaction		Importance
	Statistical Value	p Value	Statistical Value	p Value
Sex	t = −0.889	0.375	t = −15.789	<0.001
Age	F = 5.459	0.005	F = 30.499	<0.001
The education level	F = 1.918	0.92	F = 38.329	<0.001
Type of occupation	t = −4.994	<0.001	t = 3.082	0.002
Household size	F = 1.257	0.287	F = 0.505	0.732
Annual household income	F = 41.394	<0.001	F = 1.656	0.177
Average living space per person	F = 5.716	<0.001	F = 1.984	0.097
Time spent online per day	F = 12.008	<0.001	t = 13.321	<0.001
Degree of improvement in the living environment at the location	F = 25.078	<0.001	F = 9.737	<0.001
Ecological environment-related training	t = 2.136	0.034	t = 12.83	<0.001
Regional division	t = 2.007	0.046	t = −1.283	0.201

presents that there were statistically significant differences in eco-environment-related training and regional division (p < 0.05). In contrast, no statistical differences were observed for sex, education level, and family size (p > 0.05).

Specifically, the analysis reveals the following trends: (1) Residents aged 18–40 reported higher satisfaction with ecosystem services compared with those aged 41–65 and older; (2) individuals in non-agricultural occupations expressed greater satisfaction with ecosystem services than those in agricultural occupations; (3) residents with an annual household income of more than CNY 200,000 demonstrated significantly higher satisfaction levels than those earning below this threshold; (4) the larger the per capita living area, the more satisfied the residents are with the services provided by the local ecosystem; (5) greater daily Internet access correlated positively with higher satisfaction score; (6) residents who perceived improvements in their living environment due to the establishment of the national park reported higher satisfaction levels; (7) residents who participated in eco-environment-related training were more satisfied with ecosystem services than those who did not participate in relevant training; and (8) residents living in the GA were more satisfied with ecosystem services than those living in CA.

Similarly, the mean value of the importance item was used as the dependent variable, and the results showed statistically significant differences in the importance of local residents with ecosystem services in sex, age, education level, occupation type, daily Internet access time, environmental improvement degree, and eco-environment-related training (p < 0.05). As indicated in Table 6, there was no significant difference in household size, annual household income, per capita living area, and regional division with a p value exceeding 0.05.

Among them: (1) the perception of the importance of ecosystem services was significantly higher among female residents than that of male residents; (2) residents aged 18–40 had a higher perception of the importance of ecosystem services than those aged 41–65 and above; (3) residents with a bachelor’s degree had the highest perception of the importance of ecosystem services; (4) the perception of the importance of ecosystem services was higher among residents with non-agricultural occupations than that of residents with agricultural occupations; (5) the longer the daily time spent online, the higher the importance perception score; (6) it was believed that the better the degree of improvement of the living environment of the residents in the area where the establishment of national parks was established, the higher the perception score of importance; and (7) the perception of the importance of ecosystem services was higher than that of those who did not participate in the training.

3.5.2. Multivariate Analysis of Influencing Factors

A multiple linear regression analysis was conducted with the mean of satisfaction score as the dependent variable. The study included several statistically significant independent variables: age, occupation type, annual household income, per capita living area, daily Internet access, degree of environmental improvement, eco-environment-related training, and regional division. The results in

Table 7. Multiple linear regression analysis of local people’s perception of ecosystem service satisfaction.

	Unstandardized Coefficients		Standardized Coefficients	T	p Value	Collinearity Diagnostics
	B	Stderr	Beta			Tolerance	VIF
(Constant)	2.532	0.161		15.706	<0.001
Sex	0.007	0.042	0.01	0.163	0.871	0.594	1.684
Age	−0.029	0.03	−0.048	−0.946	0.345	0.802	1.247
The education level	−0.056	0.013	−0.24	−4.143	<0.001	0.609	1.641
Type of occupation	0.181	0.036	0.243	4.99	<0.001	0.858	1.165
Household size	−0.004	0.019	−0.009	−0.189	0.85	0.915	1.093
Annual household income	0.132	0.025	0.269	5.2	<0.001	0.76	1.315
Average living space per person	0.042	0.018	0.122	2.376	0.018	0.779	1.283
Time spent online per day	0.07	0.02	0.188	3.462	0.001	0.691	1.448
Degree of improvement in the living environment at the location	0.113	0.024	0.238	4.677	<0.001	0.787	1.271
Ecological environment-related training	−0.12	0.045	−0.164	−2.685	0.008	0.549	1.821
Regional division	−0.087	0.043	−0.097	−2.013	0.045	0.881	1.135
Adjusted R2	0.469
F	21.886
D-W	1.725

suggest several positive indicators: occupation type (B = 0.181), annual household income (B = 0.132), per capital living area (B = 0.042), daily Internet access time (B = 0.07), and the degree of improvement of the living environment in the location (B = 0.113). Conversely, negative indicators included education level (B = −0.056), household size (B = −0.004), eco-environment-related training (B = −0.12), and regional division (B = −0.087).

Table 7 shows that the independent variables explain 46.9% of the variance in the dependent variable, with an adjusted goodness of fit of 0.469, indicating that the model fits well; Durbin–Watson values were between 1.5 and 2.5, suggesting no serial autocorrelation among the independent variables. Additionally, the VIF values are below 5, indicating no significant multicollinearity issues.

Multiple linear regression was performed with the mean of importance items as the dependent variable, and the statistically significant variables (sex, age, education level, occupation type, daily Internet time, environmental improvement degree, and eco-environment-related training) were used as independent variables. As demonstrated in

Table 8. Multiple linear regression analysis of local peoples’ perception of the importance of ecosystem services.

	Unstandardized Coefficients		Standardized Coefficients	T	p Value	Collinearity Diagnostics
	B	Stderr	Beta			Tolerance	VIF
(Constant)	3.097	0.116		26.634	<0.001
Sex	0.257	0.031	0.371	8.432	<0.001	0.594	1.684
Age	−0.093	0.022	−0.162	−4.262	<0.001	0.802	1.247
The education level	0.074	0.01	0.332	7.627	<0.001	0.609	1.641
Type of occupation	−0.071	0.026	−0.099	−2.707	0.007	0.858	1.165
Household size	−0.022	0.014	−0.056	−1.592	0.113	0.915	1.093
Annual household income	−0.018	0.018	−0.039	−0.994	0.321	0.76	1.315
Average living space per person	0.003	0.013	0.009	0.229	0.819	0.779	1.283
Time spent online per day	0.049	0.015	0.137	3.344	0.001	0.691	1.448
Degree of improvement in the living environment at the location	0.044	0.017	0.096	2.518	0.012	0.787	1.271
Ecological environment-related training	−0.093	0.032	−0.132	−2.874	0.004	0.549	1.821
Regional division	−0.029	0.031	−0.033	−0.917	0.36	0.881	1.135
Adjusted R2	0.7
F	56.277
D-W	2.127

, the results identified several positive indicators, including sex (B = 0.257), education level (B = 0.074), daily Internet access time (B = 0.049), and the degree of improvement of the living environment in the location (B = 0.044), while the negative indicators included age (B = −0.093), type of occupation (B = −0.071), and eco-environment-related training (B = −0.093).

It can be seen from Table 8 that the degree of explanation of the independent variables to the dependent variables is 70%, and the adjusted goodness-of-fit is 0.7, indicating that the model fits well; Durbin–Watson values were between 1.5 and 2.5, and there was no serial autocorrelation among the independent variables. VIF value < 5, meaning that the model does not have serious multicollinearity problems.

3.5.3. Analysis of Regression Results

Occupational diversity among local residents influences their awareness of ecosystem services. Those engaged in non-agricultural activities often have reduced dependence on farmland and ecological conditions, whereas residents in agriculture-dominated occupations remain closely tied to farming for their livelihoods. For these agricultural communities, ecosystem services are directly linked to their economic well-being, making them particularly sensitive to environmental change.

Smallholder production has the dual nature of ecological exchange and social exchange, in which smallholder production first obtains material or energy from the ecosystem and then transfers this material or energy to a certain degree to the social organization system [69], which highlights the direct impact ecosystems have on agricultural productivity. Consequently, residents reliant on agriculture may experience diminished satisfaction with ecosystem services, especially in the face of frequent natural disasters that disrupt agriculture processes.

Residents with a large per-capita living area typically possess greater physical capital, which reflects the productivity level of rural households to a certain extent. Higher productivity and economic status correlate with greater satisfaction regarding ecosystem services. Financial capital refers to the income expenditure and borrowing of rural households in the process of production and life [70], which also affects the perception of ecosystem services.

Those with higher annual incomes are often engaged in diverse livelihood strategies, such as non-agricultural employment or ecological public welfare positions, enhancing their economic stability and satisfaction levels. Conversely, residents with lower incomes remain largely dependent on agriculture, leading to reduced satisfaction with ecosystem services.

Daily online time has a positive impact on the satisfaction and importance of ecosystem services. There is a close relationship between the increase in online time and the improvement of residents’ satisfaction and awareness of ecological protection. The role of the Internet in information dissemination and education should not be underestimated.

Degree of improvement in the living environment at the location becomes a positive index that affects the local residents’ awareness of ecosystem services. When people can directly feel the benefits of ecosystem services, they tend to be more supportive of national parks and understand and subscribe to the concept of development.

After the training, the residents’ cognition has been greatly improved, and their cognition and satisfaction with ecosystem services have also been significantly improved. Ecological training has provided a mass foundation for the construction of national parks.

4. Discussion

Incorporating residents’ ideas and needs into the decision-making enables policymakers to create more targeted policies and enhance the system of the NCTLPN. Similar to the results drawn by J Zhang [71], the material and social needs of the people have not been effectively met. In this study, the satisfaction and importance of “provision of a place of residence” and “provision of raw materials” are relatively low and need further improvement. The difference is that his cultural services fall into the fourth quadrant, where basic needs are not met, while in this study, aside from the “ecotourism value” in the general area, which falls into the first quadrant, all other indicators fall into the third quadrant. This indicates that the residents in the study area place low importance on spiritual and cultural aspects, which may be related to the local residents’ lifestyle and the strict regulatory policies.

4.1. Socio-Economic Conditions Have a Certain Degree of Influence on Cognition

The survey results reveal that respondents’ value preferences for ecosystem services are influenced by their socio-economic characteristics. This section discusses the more prominent socio-economic factors.

Specifically, the respondent’s sex plays a significant role in shaping these perceptions (B = 0.257). Existing research highlights that men often report greater awareness of ecosystems, partly due to patriarchal societal structures that position them as household heads and primary respondents in surveys [52,72]. This traditional role may amplify their perceived understanding of ecosystem services. However, studies such as Zhao et al. (2024) indicate that women demonstrate stronger environmental concern and natural connectedness, exhibiting a greater emphasis on services like water purification, soil conservation, habitat preservation, and biodiversity maintenance [73,74]. The findings of this study align with existing research, reinforcing the argument that women generally perceive ecosystem services as more important. Women’s stronger connection to nature and heightened sensitivity to environmental issues may stem from their direct interaction with ecosystem services affecting daily well-being [75]. This aligns with prior analyses showing that local communities focus on services with immediate personal benefits. The observed gendered divergence in perception underscores the necessity of inclusive policy frameworks that integrate both perspectives to enhance sustainable ecosystem management and conservation strategies.

An individual’s ecological worldview influences the perceived importance of ecosystem services [76]. In contrast to He et al. [68], the findings indicated that individuals with greater educational attainment tend to report lower satisfaction with ecosystem services (B = −0.056), likely due to residents with more and higher levels of cultural education often setting higher standards to assess satisfaction with ecosystem services. In contrast, residents with lower education levels from primary and junior high school backgrounds receive basic education; their standards are relatively low, and they are more likely to feel satisfied. Individuals with lower educational levels also have a stronger local identity and dependency, which may influence their perceptions positively.

4.2. The Negative Effects of Human–Animal Conflicts

The research highlights that human–animal conflicts pose a significant threat to the livelihoods, safety, and well-being of residents in NCTLNP. Conservation efforts have led to population increases of species such as Siberian tigers, Amur leopards, and wild boars. However, as human populations and activities expand, interactions with wildlife have intensified. With the national park’s establishment, habitat restoration and anti-poaching measures have increased wildlife numbers, leading to more frequent conflicts. These include wildlife encroaching on villages, damaging crops, preying on livestock, and posing direct safety risks. Such conflicts have undermined agricultural productivity and caused psychological distress, affecting the community’s economic stability.

To address these issues, several strategies are necessary. First, educational programs should raise awareness about wildlife behavior and coexistence strategies, reducing fear and promoting positive interactions. Second, a compensation system for damages is critical, covering crop loss, livestock depredation, and personal injury while ensuring transparency and accessibility to foster trust among residents. This should be paired with stronger wildlife conservation measures, such as wildlife sanctuaries and enhanced monitoring protocols. Lastly, management strategies must focus on clearly delineating human habitats from wildlife habitats, with preventative measures like barriers and warning signs to reduce conflict risks.

In conclusion, while human–animal conflicts remain a challenge, through education, compensation, conservation, and improved management, a more harmonious relationship between humans and wildlife can be achieved, benefiting both local livelihoods and the environment.

4.3. Comparing the Perceptions of People Living in Different Areas

The analysis reveals a significant difference in residents’ satisfaction with ecosystem services before and after the construction of national parks in the GA and CA. In general, residents in the GA reported higher satisfaction regarding basic material, spiritual, and cultural services compared with those living in the CA. Key factors influence these perceptions, including policy control, economic diversification, and geographical location. Residents in the GA benefit from a more diversified economy, with significant engagement in sectors such as migrant labor, forestry, and black fungus cultivation. These economic opportunities provide stable incomes and mitigate employment concerns. In contrast, CA residents rely more heavily on natural resources, with livelihoods closely tied to the environment. However, strict land-use regulations, including restrictions on large-scale agriculture and livestock farming, limit access to essential resources and economic opportunities. Additionally, the CA’s geographical remoteness, poor infrastructure, and limited facilities further constrain social, cultural, and economic activities.

Interestingly, GA residents report higher satisfaction with biodiversity maintenance than those in the CA, contrasting with previous studies. This can be attributed to differences in pre-construction ecological conditions. The establishment of NCTLNP has led to significant ecological restoration, increasing wildlife populations. Residents in the GA, who previously experienced lower biodiversity, now perceive these improvements more positively, leading to greater satisfaction due to higher marginal utility.

Consistent with He’s view, a one-size-fits-all policy approach is not advisable [77]. Regional differences must be considered when formulating policies, ensuring that ecological protection efforts align with local socio-economic conditions. Strengthening social feedback mechanisms can improve policy effectiveness and resource allocation, preventing unintended disruptions to local livelihoods. Policies tailored to regional contexts can better balance conservation goals with community development needs, avoiding the inefficiencies and inequalities that arise from uniform approaches.

4.4. Limitations and Future Research Directions

If residents’ opinions are to be incorporated into policymaking, the most direct method is through surveys to assess preferences, which can improve resource utilization and reduce resistance to policy implementation. However, being a subjective concept, preference does not provide a comprehensive procedural basis for decision-making. Preferences can only partially explain people’s interactions with the current ecosystem, and they are often time-sensitive, subject to change over time, and have environmental developments [78]. Preferences may not reflect long-term benefits; the preferences of residents might be based on their current lifestyle and short-term needs, often prioritizing immediate benefits while neglecting the park’s long-term development. There is a possibility that residents may be more inclined to use park resources to support their livelihoods, but this could conflict with the ecological conservation goals of the national park.

In this context, dynamic monitoring of preferences should be implemented to track the specific mechanisms behind these changes. Policies should be regularly updated based on new data, and a regular policy evaluation and feedback mechanism should be established. Preference surveys should be conducted periodically, and policies should be adjusted as needed. When analyzing preferences, it is important to consider historical trends and long-term development plans, avoiding decisions based solely on short-term preference changes to ensure the continuity and stability of policies. Preference levels should not be the sole basis for policy improvement. Future research should integrate residents’ preferences, natural monitoring, and economic development, establishing a multidimensional data system. By conducting a comprehensive analysis of various data, policy improvements can be more thorough.

In addition, future research can conduct an in-depth study of the perceptions of ecosystem services by various stakeholders to provide a more comprehensive perspective for national park policymaking. This will help find a balance between park residents who directly depend on the park’s resources, government officials who are focused on ecological protection, and tourists who are more concerned with spiritual services, thus avoiding the situation where excessive development in one area neglects other important ecosystem services.

5. Conclusions

To ensure the sound and sustainable development of NCTLNP, it is imperative to explore local residents’ perceptions of ecosystems. Our findings suggest that: (1) residents’ perceptions of local ecosystem services and the direction of policy improvements are highly complex and interconnected; (2) socio-economic characteristics play a significant role in shaping residents’ preferences and values regarding ecosystem services; (3) the development of NCTLNP has a notable impact on the perceptions of ecosystem services among local residents; and (4) communities in different regions exhibit varying levels of satisfaction and perceived importance of ecosystem services.

During the construction of national parks, primary attention should be given to the ecosystem services preferred by residents, but we should not ignore the services that fall in the areas of continuous maintenance and oversupply; the impacts and contributions of different ecosystem services to residents are different, efforts should be made to achieve a dynamic balance of satisfaction with each service, and the formulation of policies should be carried out with holistic thinking. Secondly, it should be noted that the perception of residents is dynamically changing, and the needs will change with the implementation of policies and the passage of time, so it is necessary to continuously adapt, revise, and adjust existing policies promptly to achieve the sustainable development of national parks.

Specifically: (1) We should actively encourage and invite local residents to participate in the decision-making process and establish a multi-level platform for resident engagement. Through seminars and regular visits and surveys, residents can directly communicate with policymakers, researchers, and so on, thereby gaining a thorough understanding of the current needs and perspectives of the local community. The selection of village representatives to attend park management meetings ensures that the voice of local residents can be directly communicated to the decision-making level and that the interests of all parties can be better demonstrated and discussed. (2) A multi-channel feedback mechanism should be established, encompassing platforms such as village committee bulletin boards, the national park’s official website, and community forums, to update information and collect diverse suggestions in a timely manner. (3) It is essential to establish a scientific dynamic monitoring system and use big data and artificial intelligence to organize and analyze the changing trend of ecological environment and perception. This system will evaluate policy effectiveness and adjust policies in a timely manner to achieve a balance between ecological protection and social development.