生物多样性

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物种分布模型在宏观生态学和生物地理学中应用的思考

乔慧捷   

  1. 中国科学院动物研究所动物多样性保护与有害动物防控全国重点实验室, 北京 100101 中国
  • 收稿日期:2025-06-20 修回日期:2025-08-28
  • 通讯作者: 乔慧捷
  • 基金资助:
    国家重点研发计划(2021YFD1400200); 自然科学基金(32271732)

Thoughts on the Application of Species Distribution Models in Macroecology and Biogeography

HUIJIE QIAO   

  1. State Key Laboratory of Animal Biodiversity Conservation and Integrated Pest Management, Institute of Zoology, Chinese Academy of Sciences 100101, China
  • Received:2025-06-20 Revised:2025-08-28
  • Contact: QIAO, HUIJIE
  • Supported by:
    National Key Research and Development Program of China?(2021YFD1400200); National Natural Science Foundation of China(32271732)

摘要: 物种分布模型(Species Distribution Models, SDMs)已成为宏观生态学和生物地理学研究不可或缺的工具,广泛应用于预测物种分布、评估气候变化影响和指导保护规划。然而,该领域的快速发展也伴随着理论与实践的脱节,尤其体现在对“生态位”概念的混淆上。本文系统梳理了生态学中三个核心的生态位概念:格林内尔生态位 (Grinnellian Niche),关注环境条件与物种分布的宏观关系;埃尔顿生态位 (Eltonian Niche),强调物种在群落中的功能角色和生物互作;以及哈钦森生态位 (Hutchinsonian Niche),提供了“n维超体积 (n-dimensional hypervolume)”的数学框架,并区分了基础生态位与实际生态位。本文进一步探讨了与各生态位概念相对应的建模方法,包括标准的物种分布模型、多物种联合分布模型(JSDMs)和n维超体积分析。通过分析当前研究中存在的概念混淆(如将基于存在记录的物种分布模型等同于基础生态位模型)、模型误用(如忽视非平衡状态和采样偏差)等常见问题,本文强调了明确研究的理论基础、匹配建模方法与研究问题、审慎解读模型结果的重要性。最后,本文提出,未来的研究应致力于概念的清晰化、方法的整合化以及理论与应用的深度融合,从而更科学、规范地应用物种分布模型,推动生态学理论的发展。

关键词: 生态位理论, 生态位模型, 基础生态位与实际生态位, 模型可迁移性

AbstractBackground & Aims: Species distribution models (SDMs), often synonymous with ecological niche models (ENMs), have solidified their position as indispensable tools in modern macroecology, biogeography, species invasion and conservation. Their utility in predicting a species’ potential geographic range, evaluating the impacts of climate change, and guiding targeted conservation efforts has led to a remarkable surge in their popularity and application over the last three decades. However, this rapid expansion has also exposed a significant and persistent conceptual gap: a growing disconnect between the practical application of modeling techniques and the foundational ecological theory that should guide them. A primary source of this issue is the widespread confusion surrounding the concept of the “ecological niche”. This ambiguity has led to conceptual errors, inappropriate method use, and potentially flawed ecological inferences. This paper addresses this critical gap by systematically reviewing the core niche concepts, linking them to specific modeling paradigms, diagnosing prevalent issues in current research, and offering recommendations to promote a more theoretically grounded and robust application of SDMs. Review Results: The term “ecological niche” is not a single, unified concept. It encompasses three distinct yet complementary ideas. The Grinnellian niche defines a species’ existence based on the abiotic environmental conditions and habitat requirements that allow it to persist. As a “scenopoetic” or habitat-based framework, it is most closely aligned with standard SDMs, which statistically correlate species occurrence records with broad-scale climatic and environmental variables. The Eltonian niche, conversely, focuses on a species’ functional role within a community, emphasizing biotic interactions such as resource consumption, predation, and competition. This concept is central to community ecology and is better represented by methods like joint species distribution models (JSDMs) that account for residual correlations between species, or through explicit network analysis. The Hutchinsonian niche provides the most formal definition, conceptualizing the niche as an “n-dimensional hypervolume” encompassing all environmental and resource variables. Different modeling approaches correspond to these niche concepts. Standard correlative SDMs (e.g., MaxEnt, random forest) are primarily used to model the Grinnellian niche, generating a map of environmental suitability based on abiotic variables. To explore the Eltonian niche, JSDMs simultaneously model multiple species to infer interspecific interactions. The Hutchinsonian framework, particularly the concept of the hypervolume, is directly operationalized by analytical methods that quantify niche breadth, overlap, and centrality in multidimensional space. Mechanistic models, which use principles of physiology to predict survival and reproduction, offer a valuable complementary approach to approximate the fundamental niche. Despite these advances, the application of SDMs is fraught with common pitfalls. The most critical error is the fundamental vs. realized niche fallacy, where researchers mistakenly interpret the output of a standard SDM, which is trained on a species’ actual distribution, as a representation of its full fundamental niche. In reality, these models typically capture only a portion of the realized niche, constrained by unmeasured biotic factors and dispersal limitations. Additionally, many studies violate the core assumptions of SDMs, such as the assumption that species are in equilibrium with their environment or that sampling is unbiased. Ignoring biotic interactions and failing to account for non-equilibrium dynamics (e.g., recent invasions) further limits the accuracy and reliability of these models. Conclusion: To advance species distribution modeling, this paper advocates for a multi-pronged approach grounded in ecological theory. First, researchers must strive for greater conceptual clarity, explicitly stating which niche concept their study addresses and interpreting results within that defined framework. Second, there is a clear need for enhanced methodological rigor and integration, encouraging the development of hybrid models that combine the strengths of different modeling paradigms, such as incorporating biotic interactions or dispersal dynamics into standard SDMs. Furthermore, adherence to best practices in data collection, model selection, and rigorous validation is paramount. The future of the field lies in transcending simple correlative methods and embracing a more integrative science that synthesizes Grinnellian, Eltonian, and Hutchinsonian perspectives. By leveraging new data streams and grounding our work in a deep understanding of ecological theory, we can ask more complex questions and provide more robust guidance for biodiversity management in an era of rapid environmental change.

Key words: Niche Theory, Ecological Niche Models, Fundamental vs. Realized Niche, Model Transferability