Enhancing Wildlife Park Environmental Management Through an Integrated Evaluation Framework: A Non-Human-Centered Perspective

Abstract

Wildlife parks play a crucial role in biodiversity conservation and environmental education. However, their management effectiveness remains under-evaluated from an ecological sustainability perspective. Existing evaluation frameworks for wildlife park management are largely human-centered and overlook wildlife as independent subjects. To address this gap, this study emphasizes the intrinsic value of wildlife as independent ecological actors, and proposes an evaluation framework for management effectiveness from a non-human-centered perspective. The framework encompasses five criterion layers subdivided into 24 evaluation indicators established using the analytic hierarchy process (AHP). Post-occupancy evaluation (POE) was subsequently employed as an example application to demonstrate the implementation of the framework at Beijing Wildlife Park (BWP), yielding a comprehensive evaluation index of 76.87%. The results indicate differentiated performance across the five evaluation dimensions without constituting a site-specific judgment. The example application demonstrates the feasibility and operability of the framework, addressing the shortcomings of conventional evaluation approaches in ethical and ecological dimensions. This study provides a decision-support tool to guide the enhancement of environmental management in wildlife parks and may inform evaluation in related animal-oriented spaces.

1. Introduction

1.1. Research Background

According to the United Nations Environment Programme (UNEP) 2021 report Making Peace with Nature, climate change, biodiversity loss, and environmental pollution have become the most pressing environmental challenges of our time [1]. Restoring the relationship between humans and nature and strengthening biodiversity conservation has become an urgent priority in global environmental governance. As key institutions connecting nature and society, wildlife parks play a crucial role by supporting wildlife conservation, scientific research, and public education [2,3,4].

The definition of wildlife park varies across countries and standards. According to the Collins English Dictionary, a wildlife park is “an enclosed area of land where uncaged wild animals roam fairly freely, in conditions designed to mimic their natural habitat as closely as possible” [5]. In Western contexts, wildlife parks are often referred to as Open Plan Zoos or Safari Parks, whereas in some African and Asian regions, they are identified as wildlife conservation areas or National Parks [6]. In China, wildlife parks are categorized as a type of urban park within the urban green space system, with group housing, mixed-species enclosures, and free-ranging displays serving as their primary exhibition modes [7].

In recent years, several wildlife parks have demonstrated strong management practices that attend to animal welfare and ecological conditions. For example, Sabi Sands Game Reserve in South Africa operates as an unfenced landscape contiguous with Kruger National Park, allowing wildlife to move freely across a large natural habitat; Zoofari Parks in the US integrate captive management with conservation programmes; and Tanganyika Wildlife Park in the US combines close-range animal encounters with structured staff supervision and educational interpretation aimed at fostering public awareness of animal care and conservation. However, despite such positive practices, recent cases suggest that significant challenges persist in wildlife park management. In 2022, captive red pandas in several Indian zoos showed stereotypic behaviours caused by insufficient environmental complexity, indicating long-term psychological stress [8]; in 2023, a young giraffe at the Greater Vancouver Zoo died due to poor enclosure design, lack of behavioural enrichment, and inadequate climate adaptation, which further intensified public criticism of captive conditions; in 2024, a commercial wildlife interactive exhibit located in shopping malls in Fort Worth, Texas and Las Vegas, Nevada was criticised for confining animals to limited spaces and exposing them to intensive human disturbance solely for entertainment purposes. These contrasting practices reveal substantial variation in management approaches across wildlife parks and highlight the need for systematic evaluation tools capable of assessing management effectiveness with respect to animal welfare, ecological integrity, and public education and ethical considerations.

As argued by Altvater et al., the underlying cause of the current environmental crisis lies in anthropocentrism [9]. Anthropocentrism means “interpreting or regarding the world in terms of human values and experiences” [10], which creates a dualism that separates the values and experiences of humans from those of nonhuman life forms. This dualistic perspective obscures the interconnectedness between human and nonhuman life [9]. With this shift in environmental philosophy, wildlife parks as hybrid spaces connecting nature and culture have played a growing role in ecological conservation and species breeding [11,12]. However, in practice, wildlife park management still requires further development toward more inclusive and ecologically responsible approaches.

1.2. Animal Welfare Evaluation Frameworks

The evaluation of animal welfare is based on the development of Animal Rights Theories and Animal Liberation [13,14], as well as the practical standards established by global animal protection organizations. Peter Singer proposed the theory of Animal Liberation, while Tom Regan introduced the Animal Rights Theory, both emphasizing that animals should possess independent rights to life and welfare [15,16]. Fraser proposed three perspectives for assessing animal welfare, including the natural living perspective, the biological functioning perspective, and the affective state perspective. The Natural Living Perspective advocates for providing animals with environments that closely resemble their natural habitats, enabling them to express normal behaviour. The Biological Functioning Perspective highlights the importance of keeping animals under conditions that promote health, growth, and reproduction, while the Affective States Perspective focuses on animals’ experiences of pain and other emotional states [17]. In 1979, the Farm Animal Welfare Council (FAWC) introduced the “Five Freedoms” principle, which has become a globally recognized standard for assessing animal welfare [18]. These freedoms include freedom from hunger and thirst, freedom from discomfort, freedom from pain and suffering, freedom to express normal behaviour, and freedom from fear and distress. This framework has been widely applied in wildlife parks, zoos, and other animal management institutions, serving as a fundamental benchmark for evaluating animal welfare; for example, Demartoto et al. applied the Five Freedoms framework to assess animal welfare practices in Indonesian zoos through observational and management-based evaluation [19]. In global zoo management, animal welfare standards centred on the “Five Freedoms” have been widely adopted by international organisations such as the Association of Zoos and Aquariums (AZA) and European Association of Zoos and Aquaria (EAZA), and have been incorporated into accreditation and evaluation systems.

1.3. Analytic Hierarchy Process and Post-Occupancy Evaluation

The Analytic Hierarchy Process (AHP) method was proposed by Saaty in the 1970s as a multi-criteria decision-making technique, integrating both qualitative and quantitative data for solving complex or ambiguous decision-making problems [20,21]. This method decomposes decision-making problems into hierarchical structures and assigns weights to each criterion based on expert judgment, ultimately quantifying the relative importance of different factors to assist decision-making. To mitigate potential subjectivity in the assignment of weights, the composition of the expert panel and the implementation of consistency tests are critical to ensuring methodological rigor and robustness. In the field of environmental planning and spatial management, AHP has been widely applied in landscape quality assessment, ecological restoration evaluation, environmental performance analysis, sustainability assessment, and land-use management, particularly in contexts involving multi-objective trade-offs and complex ecological systems [22,23,24,25]. AHP has demonstrated applicability in constructing and determining the priorities of multiple interrelated criteria. Wildlife parks, as a distinctive type of landscape and ecological space, require the integration of multiple interrelated considerations in the evaluation of environmental management, thereby making AHP a suitable methodological approach.

Post-Occupancy Evaluation (POE) originated in the 1960s from Environmental Psychology [26] and was initially used to evaluate how built environments meet the needs of human users, primarily relying on surveys and interviews to systematically collect user feedback [27]. In built environment research, POE has been widely applied in urban green space evaluation, public housing regeneration, and landscape performance assessment, serving as a post-implementation tool to examine spatial functionality, ecological quality, and stakeholder experience [28,29,30]. In zoo and wildlife park management, POE has been applied to assess the post-occupancy performance of exhibits, including their capacity to support animal welfare and enhance visitor educational experience [31]. In this study, POE is employed to illustrate how the evaluation framework can be applied and its indicators translated into measurable results within a practical management context.

1.4. Non-Anthropocentric Approaches in Wildlife Park Research

Non-anthropocentrism, a theoretical stance within environmental ethics, advocates for a more inclusive and respectful approach toward other living beings [32]. It posits that all living organisms and natural environments possess inherent value, independent of their utility or service to humans [33]. Recent studies in zoo and wildlife park management have begun to reflect ethical orientations increasingly attentive to animal welfare and intrinsic value. Studies on environmental enrichment and enclosure design indicate a growing recognition of animals’ behavioral preferences and thermal comfort as core evaluation criteria [34]. Likewise, the development of automated welfare monitoring systems and disease surveillance demonstrates that animal well-being is being institutionalized as a primary management objective [35,36,37]. Historical analyses of zoo governance further reveal a gradual shift toward recognizing animals as sentient subjects within legal and managerial frameworks [38]. In zoo planning and design, animals are increasingly regarded as stakeholders or even co-participants in the process [39]. These developments suggest that zoo and wildlife park research is progressively moving beyond human-centered managerial logics, embodying an ethical reorientation that foregrounds animals’ intrinsic value, behavioural agency, and welfare as central evaluative concerns.

However, these developments remain conceptually dispersed rather than methodologically consolidated. As noted by Kopnina et al., there is currently no fully developed non-anthropocentric conservation guideline that translates ethical commitments into concrete management tools [40]. Moreover, animal welfare assessments are typically conducted independently from overall park performance evaluation systems and are rarely integrated into mainstream management effectiveness frameworks [41].

Based on the above, this study develops an innovative evaluation framework for wildlife park management effectiveness grounded in a non-anthropocentric perspective, specifically focusing on large-scale suburban parks that preserve natural landscapes, simulate wild animal habitats, and feature open-style exhibits. The framework enhances the capacity to conduct comprehensive assessments of wildlife parks from the standpoint of non-human value. It further demonstrates the operationalisation of this framework through an example application, illustrating how evaluation results can inform management reflection and improvement, thereby facilitating the broader adoption of perspectives beyond humanity in future sustainability research and practice.

2. Materials and Methods

2.1. Research Framework and Process

This study first conducted a systematic literature review of animal welfare evaluation frameworks and non-anthropocentric approaches in wildlife park research, establishing the theoretical foundation and identifying a preliminary pool of candidate indicators. Based on this preliminary indicator set, the Delphi method was employed to conduct expert consultation, during which experts evaluated, revised, and refined the indicators. Indicators with low importance or insufficient consensus were removed, resulting in the final hierarchical evaluation framework consisting of a target layer, criterion layer, and indicator layer. The Analytic Hierarchy Process (AHP) was subsequently applied to determine the weights of the retained indicators. A consistency test was conducted to assess the logical coherence of the judgment matrix. Finally, using the Post Occupancy Evaluation (POE), Beijing Wildlife Park (BWP) was selected as an example application to demonstrate the operationalisation of the proposed framework and to conduct a comprehensive assessment of its management effectiveness (Figure 1).

2.2. Selection of Evaluation Indicators

In this study, two key criterion layers were constructed based on Fraser’s theory of animal welfare to evaluate the effectiveness of wildlife park management. First, the habitat environment criterion layer (B1) was developed based on the Natural Living Perspective to evaluate the extent to which wildlife parks support habitat restoration. Second, the animal behaviour and health criterion layer (B2) was designed based on the Biological Functioning Perspective to comprehensively evaluate it in terms of animals’ psychological and physical health, and behavioural expression. The Five Domains Model further conceptualizes animal welfare as comprising four physical–functional domains—nutrition, physical environment, health, and behavioural interactions—and a fifth domain, the mental state. The model emphasizes that environmental conditions and management practices are not equivalent to welfare states per se; rather, they influence welfare indirectly by affecting animals’ physiological stability and behavioural expression [42,43]. Contemporary welfare science recognises that barren or spatially restrictive environments may generate negative affective states such as fear, frustration, or boredom, whereas structurally enriched and ecologically appropriate habitats promote positive engagement and exploratory behaviour [44,45].

Accordingly, following consultation with experts, six indicators were identified to reflect the structural and ecological characteristics of wildlife park habitats under the Habitat Environment criterion layer (B1). These include habitat area (C1), similarity to natural habitat features (C2), biological community complexity (C3), vegetation coverage (C4), water quality (C5), and the availability of shelters and hiding places (C6), which assess the extent to which the habitat approximates natural environmental conditions. Similarly, under the Animal Behaviour and Health criterion layer (B2), seven indicators were identified to reflect animals’ biological functioning and behavioural expression, including physiological health status (C7), animal safety conditions (C8), stress-related behaviours (C9), respect for animal rights (C10), diversity of natural behaviours (C11), social interactions (C12), and reproductive success (C13).

Secondly, healthy ecosystems provide animals with more stable living environments, enhancing their behavioural expression and adaptive capacity [46]. Thus, this study introduced Ecological Sustainability as the third criterion layer (B3), focusing on the long-term stability of ecosystems and biodiversity conservation within wildlife parks. Ecosystem sustainability is commonly evaluated in terms of biodiversity, resilience, species interactions, and ecosystem functioning. Extensive research has shown that biodiversity supports ecological stability and system resilience [47,48,49,50]. Five indicators were specified to reflect the long-term stability and sustainability of wildlife park ecosystems. These include species conservation and biodiversity maintenance (C14), ecological restoration capacity (C15), inter-species interactions and ecological balance (C16), demonstration of ecosystem services (C17), and environmental pollution control and waste management (C18).

Moreover, non-anthropocentrism advocates for transcending human interests. To promote a shift in public attitudes from anthropocentrism to non-anthropocentrism and to ensure ethical and transparent wildlife park management, this study added two additional criterion layers: Education and Advocacy (B4) and Ethics and Transparency (B5). Environmental education is not merely about knowledge dissemination but also about driving cultural change and reshaping values to foster greater understanding and respect for ecosystems and animals [51,52]. Furthermore, Peter Singer in Animal Liberation underscores humanity’s moral responsibilities in animal management, while ecological ethicist Callicott posits that policy-making and implementation of animal welfare standards should be conducted with openness and transparency [15,53]. These theories collectively affirm that effective environmental education, along with responsible and transparent management practices, can safeguard animal welfare and enhance ecosystem health. Thus, under the Education and Advocacy criterion layer (B4), four indicators were specified to reflect wildlife parks’ role in conservation communication and public engagement. These include support for conservation projects and research (C19), community and public engagement (C20), frequency and diversity of educational activities (C21), and visitor satisfaction and knowledge improvement (C22). Under the Ethics and Transparency criterion layer (B5), two indicators were specified to capture governance responsibility and ethical management. These include the implementation of animal welfare standards (C23) and transparency of policies and management measures (C24), reflecting a commitment to ethical and transparent wildlife park governance grounded in non-anthropocentric values.

Five criterion layers were identified from a non-anthropocentric perspective: habitat environment, animal behaviour and health, ecological sustainability, education and advocacy, and ethics and transparency. Following the Delphi consultation, six preliminary indicators were removed. The exclusions were based on expert panel judgement that these indicators were not fully aligned with the conceptual focus of the evaluation framework or were considered redundant in relation to retained indicators. Detailed reasons for exclusion are provided in

Table 1. Excluded Indicator.

Excluded Indicator	Reason for Exclusion
Adequate exercise space	Overlaps with C1; its content has been integrated into the retained indicators.
Noise within animal living areas	Substantially overlaps with C8 and C10; its content has been integrated into the retained indicators.
Animal freedom	Conceptually abstract and difficult to operationalise in a reliable and measurable manner; its underlying aspects are indirectly reflected in C11 and C12.
Use of environmentally friendly materials in habitat facilities	Represents a management measure rather than an outcome-based evaluation indicator, and was therefore excluded from the final framework.
Rationality of spatial zoning and layout	Pertains to management structure and implementation strategies rather than observable management effectiveness outcomes.
Staff attitudes toward animals	Difficult to assess objectively through questionnaire-based methods and considered insufficiently operational.

. Ultimately, 24 indicators were retained, constituting the final comprehensive evaluation framework for wildlife park management effectiveness (Figure 2).

2.3. Weight Values and Consistency Tests

The next step focused on determining the weight values for each evaluation criterion. These weight values were derived through systematic expert scoring, creating pairwise comparison matrices to generate eigenvectors and establish the relative importance of each criterion, thereby reflecting their contribution to the overall evaluation objective.

The expert panel consisted of two professors and three doctoral researchers in landscape architecture, all with research experience related to wildlife parks and environmental management, and therefore capable of making informed judgments on the evaluation indicators.

In this study, a matrix-based questionnaire was used to consult experts on the relative importance of the evaluation criteria. Experts were asked to conduct pairwise comparisons between indicators at the same hierarchical level using Saaty’s 1–9 scale (

Table 2. 1–9 Scale values and their connotations.

Scale Value	Degree of Importance	Concrete Meaning
1	Equally important	The evaluation indexes A and B are equally important.
3	Slightly important	The evaluation indexes A and B are slightly important.
5	Obviously important	The evaluation indexes A and B are obviously important.
7	Highly important	The evaluation indexes A and B are highly important.
9	Absolutely Important	The evaluation indexes A and B are absolutely important.
2, 4, 6, 8	Median	The importance is somewhere in between.

). For each pair of indicators, experts assessed which indicator was more important and to what extent, forming reciprocal judgment matrices.

To construct the group judgment matrix, the geometric mean aggregation method was adopted to integrate individual expert matrices. The aggregated matrix is expressed as:

$$A=\left[\begin{array}{cccc}1& a_{12}& \cdots & a_{1n}\\ {\displaystyle \frac{1}{a_{12}}}& 1& \cdots & a_{2n}\\ ⋮& ⋮& \ddots & ⋮\\ {\displaystyle \frac{1}{a_{1n}}}& {\displaystyle \frac{1}{a_{2n}}}& \cdots & 1\end{array}\right]$$

where $aij$> 0, $aii$ = 1, and $aji$= 1/$aij$, indicating a reciprocal judgment matrix.

After obtaining the group judgment matrix, the weight vector was calculated using the eigenvalue method. The priority weights were derived from the principal eigenvector of matrix A:

$$Aw={\lambda }_{\mathrm{m}\mathrm{a}\mathrm{x}}w$$

where $w$ is the normalized weight vector and ${\lambda }_{\mathrm{m}\mathrm{a}\mathrm{x}}$ is the maximum eigenvalue of matrix A.

Secondly, to ensure the reliability and logical validity of the weight derivation process, a consistency ratio (CR) test was conducted for each pairwise comparison matrix constructed by the experts. The CR examines the internal logical coherence of each judgment matrix within the Analytic Hierarchy Process (AHP), testing whether the assigned relative importance satisfies the transitivity requirement.

The consistency ratio is calculated as:

$$\mathrm{C}\mathrm{R}={\displaystyle \frac{\mathrm{C}\mathrm{I}}{\mathrm{R}\mathrm{I}}}<0.1$$

where the Consistency Index (CI) is defined as:

$$\mathrm{CI}={\displaystyle \frac{{\lambda }_{\mathrm{m}\mathrm{a}\mathrm{x}}-n}{n-1}}$$

The Random Consistency Index (RI) values used in this study were adopted from the simulation results originally reported by Saaty, which were obtained through extensive random matrix experiments (

Table 3. Value table of RI.

Random Consistency Index (RI)
n	3	4	5	6	7	8	9	10	11	12	13	14	15	16
RI	0.52	0.89	1.12	1.26	1.36	1.41	1.46	1.49	1.52	1.54	1.56	1.58	1.59	1.5943

). RI represents the average consistency index of randomly generated reciprocal matrices of the same order. By comparing CI with RI, the CR indicates whether the observed inconsistency level is acceptably small relative to random judgment. According to Saaty’s criterion, a CR value below 0.1 indicates acceptable logical consistency [54]. If the CR exceeded this threshold, the Delphi method was employed to revise the pairwise comparisons until acceptable consistency was achieved.

2.4. Application of the Evaluation Framework

2.4.1. Research Object Selection

Beijing Wildlife Park (BWP) is a comprehensive wildlife park that employs open-range and mixed-species display methods (Figure 3 and Figure 4). With its rich diversity of animal species and varied exhibit zones, the park provides an ideal setting for evaluating (

Table 4. Basic information of Beijing Wildlife Park.

Name	Date of Establishment	Area (hm2)	Number of Thematic Zones
Beijing Wildlife Park	2001	240	32
	Number of Animal Species	Number of Animals	Number of Foreign Species
	200	10,000	42

). The framework is illustrated through an example implementation in BWP, where environmental management is assessed using the integrated POE–AHP procedure.

2.4.2. Evaluation Procedure

To demonstrate the applicability of the proposed evaluation framework, a structured questionnaire was developed in alignment with the established hierarchical system. Each questionnaire item was formulated to correspond directly to a specific indicator within the criterion and indicator layers, ensuring alignment between the questionnaire design and the evaluation framework. A five-point Likert scale was employed, with responses ranging from ‘very poor’ to ‘very good’ assigned values of 1 to 5 respectively. The survey was conducted online. It was distributed to general visitors who had visited the BWP, researchers in relevant fields, and staff members of the wildlife park, and a total of 270 questionnaires were distributed. After data cleaning, incomplete and invalid questionnaires were excluded, and 214 valid responses were retained for analysis.

For each indicator, the mean score was calculated based on the valid responses. The overall weighted score was computed by multiplying the mean score of each indicator by its corresponding weight and summing across all indicators.

$$\mathrm{S}=\sum {\mathrm{F}}_{\mathrm{i}}\times {\mathrm{X}}_{\mathrm{i}}$$

where F_i denotes the mean score of indicator i based on valid responses, and X_i denotes the weight assigned to indicator i.

To enhance interpretability and comparability, a Comprehensive Evaluation Index (CEI) was calculated by standardising the overall score against the theoretical maximum score and converting it into a percentage value.

$$\mathrm{C}\mathrm{E}\mathrm{I}={\displaystyle \frac{\mathrm{S}}{{\mathrm{S}}_0}}\times 100\%$$

Because each indicator was measured on a five-point Likert scale (1–5), and the sum of all indicator weights equals 1, the theoretical maximum value of S is 5.

3. Results

3.1. Weights of the Evaluation Framework

The AHP analysis results presented in

Table 5. Weights of evaluation indicators.

Target Layer	Criterion Layer	Indicator Layer
Evaluation of Wildlife Park Management Effectiveness A	Habitat Environment B1—0.4935	Habitat area C1—0.1589
		Similarity between the geographical features of the habitat and natural habitat C2—0.1501
		Complexity of biological community structures (e.g., population numbers of species) C3—0.0835
		Natural vegetation coverage C4—0.0526
		Water quality levels C5—0.0342
		Availability of shelters and hiding places C6—0.0143
	Animal Behaviour and Health B2—0.2784	Physiological health indicators (e.g., disease occurrence, lifespan) C7 —0.0930
		Animal safety (e.g., compliance of noise levels, fencing, lighting with species’ natural habits) C8—0.0682
		Frequency and intensity of stress behaviours C9—0.0452
		Animal rights and respect (e.g., viewing methods, presence of animal performances) C10—0.0307
		Diversity of natural behaviours (e.g., foraging, playing, grooming) C11—0.0200
		Social behaviours among animals (e.g., interactions and playfulness) C12—0.0130
		Reproductive behaviour and success rate C13—0.0084
	Ecological Sustainability B3—0.1422	Species conservation and biodiversity maintenance (e.g., numbers of rare species and flora/fauna species) C14—0.0610
		Ecological restoration and regeneration capacity C15—0.0393
		Inter-species interactions and ecological balance (e.g., birds and mammals foraging together, fish and waterbirds sharing the same water body, different mammal species sharing a habitat) C16—0.0234
		Demonstration of ecosystem services (e.g., pollination by bees, pest control by birds) C17—0.0109
		Environmental pollution control and waste management C18—0.0076
	Education and Advocacy B4—0.0506	Support for conservation projects and research C19—0.0260
		Community and public engagement C20—0.0156
		Frequency and diversity of educational activities (e.g., lectures, workshops, science exhibits) C21—0.0065
		Visitor satisfaction and knowledge improvement C22—0.0025
	Ethics and Transparency B5—0.0353	Implementation of animal welfare standards C23—0.0282
		Transparency of policies and management measures (e.g., ease of access to information for visitors) C24—0.0071

indicated that all CRs were below 0.1, thus ensuring the reliability of the expert panel responses. At the criterion layer, Habitat Environment ranks first, followed by Animal Behaviour and Health and Ecological Sustainability, whereas Education and Advocacy and Ethics and Transparency receive relatively smaller weights (Figure 5). Under a non-human-centered perspective, this distribution indicates that the framework primarily prioritizes ecological conditions and animal well-being, while social communication and managerial transparency function as complementary dimensions.

At the indicator layer, among all indicators, habitat area and similarity between the habitat and natural habitat rank first and second, respectively. This indicates that the framework evaluates environments according to their ecological suitability for animals, emphasizing habitat naturalness and adequacy as the primary basis for wildlife park environmental management. The high ranking of physiological health indicators further shows that animal welfare remains a central component in the evaluation framework under a non-human-centered perspective. Following these are indicators related to ecosystem structure and safety, including biological community complexity, animal safety, and biodiversity conservation. These results suggest that environmental management is evaluated not only through individual animal status but also through the stability and functionality of the surrounding ecological system. Mid-level weights are assigned to indicators describing ecological processes and welfare implementation, such as ecological restoration capacity, water quality, animal rights respect, and welfare standard implementation. These indicators function as operational expressions of management practices that maintain long-term environmental stability of the wildlife park. In contrast, indicators associated with human-oriented functions, including public engagement, educational activities, visitor satisfaction, and policy transparency, rank at the lowest positions. This distribution suggests that communication, interpretation, and managerial disclosure are regarded as supportive mechanisms under a non-human-centered perspective (Figure 6).

3.2. Results of the Framework Application

Based on 214 valid responses to BWP, the integrated evaluation framework generated a comprehensive evaluation index of 76.87%. The scores obtained under the evaluation framework are presented in

Table 6. Mean scores of indicator layer.

Indicator Layer	Mean Score
Habitat area C1	4.0311
Similarity between the geographical features of the habitat and natural habitat C2	3.6266
Complexity of biological community structures C3	3.8485
Natural vegetation coverage C4	4.0815
Water quality levels C5	3.7030
Availability of shelters and hiding places C6	3.7327
Physiological health indicators C7	4.2346
Animal safety C8	3.9305
Frequency and intensity of stress behaviours C9	3.9461
Animal rights and respect C10	4.1601
Diversity of natural behaviours C11	3.8777
Social behaviours among animals C12	3.9825
Reproductive behaviour and success rate C13	3.3821
Species conservation and biodiversity maintenance C14	4.1495
Ecological restoration and regeneration capacity C15	3.7979
Inter-species interactions and ecological balance C16	3.8318
Demonstration of ecosystem services C17	3.3029
Environmental pollution control and waste management C18	4.0065
Support for conservation projects and research C19	2.9160
Community and public engagement C20	3.7059
Frequency and diversity of educational activities C21	3.8350
Visitor satisfaction and knowledge improvement C22	3.8935
Implementation of animal welfare standards C23	3.8864
Transparency of policies and management measures C24	3.5748

, and the mean scores of criterion layer are summarised in

Table 7. Mean scores of criterion layer.

Criterion Layer	Mean Score
Habitat Environment B1	3.836
Animal Behaviour and Health B2	3.930
Ecological Sustainability B3	3.817
Education and Advocacy B4	3.588
Ethics and Transparency B5	3.731

.

The habitat environment shows moderate performance, with relatively lower scores in natural similarity, water quality, and shelter availability, indicating limitations in replicating natural living conditions. Animal behaviour and health achieved the highest overall dimension score; however, reproductive behaviour and success rate remain comparatively low. Ecological sustainability shows lower values in ecosystem restoration and ecosystem service display, whereas pollution control and waste management performed relatively better. Education and advocacy is the weakest dimension, mainly due to the very low score in support for conservation projects and research together with limited public engagement. Ethics and transparency shows moderate performance, with relatively lower policy transparency and welfare standard implementation.

4. Discussion

This study incorporates a non-anthropocentric perspective into the structure of management effectiveness evaluation. Through an example application, the framework organises habitat conditions, animal behaviour, ecological functioning, social communication and governance factors into parallel evaluative domains, emphasising that animals are evaluated through welfare and behavioural indicators rather than treated solely as components of an ecosystem or human-use objects. In this way, ethical considerations are translated into measurable criteria within the assessment structure, thereby integrating non-anthropocentric values into the evaluation framework.

Such integration requires a defined methodological structure. The integration of AHP and POE supports this operationalisation. AHP establishes a transparent hierarchical relationship among criteria and allows weighting adjustment under different management priorities, while POE provides a structured mechanism for collecting performance information from stakeholders. Together, the two approaches transform qualitative management conditions into structured quantitative outcomes. This combination supports multi-objective evaluation and accommodates diverse stakeholder perspectives within a unified assessment procedure.

This methodological structure enables practical contexts within wildlife park settings. The example application demonstrates how performance differences across management dimensions can be systematically identified. The framework may also inform evaluation in related animal-oriented places, including urban zoos, ecological parks, and managed conservation facilities involving public access and human–animal interaction.

5. Conclusions

This study constructs an evaluation framework for wildlife park management effectiveness from a non-anthropocentric perspective and demonstrates its implementation through an example application to Beijing Wildlife Park. Building upon traditional animal welfare assessment, the framework expands evaluation to multiple domains, including habitat conditions, ecological functioning, social communication, and governance factors, thereby providing a systematic and operable evaluation structure. Compared with conventional animal welfare assessments, the framework emphasises the intrinsic value and ethical subjectivity of animals and ecosystems within an integrated management context. By integrating POE and AHP, the study establishes a quantifiable and adaptable framework that may also inform evaluation in related animal-oriented facilities such as zoos and ecological parks. The framework links wildlife park management with environmental ethics while supporting conservation-oriented decision-making in practice, enabling management procedures to better align with conservation objectives.