野生动物价值评估研究进展及展望

Research progress and prospects of wildlife value assessment

  • 摘要: 野生动物价值评估是连接生态保护与社会经济发展的关键纽带, 对于优化保护决策、协调人兽冲突、完善生态补偿机制具有重要意义。系统梳理了野生动物价值认知从人类中心主义、生态中心主义到“经济-社会-生态”综合主义的历史演进脉络, 剖析了当前评估体系在价值定义、分类逻辑、维度覆盖及研究对象等方面存在的不足。基于文献计量与内容分析, 首次构建了涵盖经济价值、生态价值、科研价值、休闲游憩价值、教育传播价值和非利用价值六大维度的综合评估框架, 并归纳了各维度的评估方法、研究对象及典型案例。该框架实现了术语的标准化整合与分类逻辑的统一, 填补了教育传播价值等新兴维度的评估空白, 拓展了非旗舰物种的研究覆盖面。最后, 提出未来需加强对于构建本土物种数据监测体系, 完善生态补偿机制和探索生物多样性银行制度等方面的研究, 为深化野生动物价值评估理论、优化保护决策及应对全球生物多样性危机提供理论支撑与科学依据。

     

    Abstract: Wildlife value assessment serves as a critical bridge linking ecological conservation and socioeconomic development. It contributes to the formulation of conservation strategies, the mitigation of human-wildlife conflicts, and the improvement of both the fairness and the practical effectiveness of ecological compensation mechanisms. This study traces the evolution of how human society has perceived wildlife value: from the early anthropocentric perspectives to the ecological-centered paradigm and ultimately to the current comprehensive assessment system that integrates economic, social and ecological dimensions. The conceptual transformation of the human-nature relationship from utilitarian exploitation to mutually beneficial coexistence is clearly revealed. Based on the relevant literature published between 1984 and 2024 as the research sample, this study conducts a systematic bibliometric analysis and thematic synthesis. At the current stage, the field of wildlife value assessment faces four persistent structural shortcomings: terminological ambiguity across disciplines, inconsistent conceptual classification logic, uneven representation across value dimensions, and pronounced taxonomic bias favoring flagship species. These problems significantly weaken the scientific validity of assessment results and their suitability for policy application. To address these research gaps, this paper establishes unified and standardized criteria for defining concepts and constructs a logically rigorous, dimensionally comprehensive, and practically applicable six-dimensional wildlife value assessment framework. The six assessment dimensions are detailed below: (1) Economic value covers the market-based revenues from live wildlife utilization and carcass-derived products. (2) Ecological value encompasses the roles wildlife plays in maintaining biodiversity, ensuring ecosystem stability, and enhancing ecological resilience. (3) Scientific research value includes the contribution to expanding fundamental theoretical knowledge and the potential for innovation in practical applications. (4) Leisure and recreation value is divided into two major types: consumptive use (such as regulated hunting and fishing) and non-consumptive use (such as wildlife observation and ecotourism). (5) Educational and communication value integrates digital communication outcomes, including social media engagement and the scale of cultural product dissemination. It also proposes a novel research approach that relies on internet-wide big data for relevant analyses. (6) Non-use value is quantified through stated preference methods such as the contingent valuation method. It explicitly incorporates three core components: option value, bequest value, and existence value. This assessment framework avoids logical overlaps by unifying conceptual definitions, clarifying conceptual boundaries, and establishing hierarchical and mutually exclusive value categories. It achieves full coverage of value dimensions and formally incorporates emerging value domains, such as digital communication, into standardized assessment. Furthermore, this study constructs an integrated research pathway consisting of three key aspects: data infrastructure, methodological innovation, and policy implementation. The wildlife value assessment outcomes can effectively serve ecological conservation practice. At the data level, it calls for the establishment and standardization of regional species-specific monitoring networks to strengthen the foundational data for value assessment. At the methodological level, it advocates the integration of internet big data analytics to build composite assessment models, thereby overcoming the inherent limitations of traditional assessment methods. At the application level, it emphasizes bridging the science-policy interface by institutionalizing assessment outputs within concrete governance instruments, optimizing ecological compensation payment standards based on empirical data, piloting biodiversity banking mechanisms centered on quantifying ecological benefits, and integrating value assessment conclusions into land-use planning, protected area management, and national biodiversity strategies. This comprehensive research approach not only strengthens the theoretical foundation of wildlife value assessment, but also enhances the practicality, policy coherence, and real-world governance effectiveness of ecological conservation decision-making.

     

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