稳定同位素模型在水生生态系统食物网中的研究进展

水生生态系统食物网具有错综复杂的营养关系。稳定同位素技术的发展对了解生物间的摄食关系和食物网结构发挥着极为重要的作用。其中，稳定同位素混合模型(stable isotope mixing models, SIMMs)近年来的迅猛发展为进一步解决水生食物网的复杂性问题提供了有力的手段，尤其是在确定食物来源贡献和构建营养生态位方面。在本研究中，作者综述了稳定同位素模型的发展历程、主要模型的特点以及运行这类模型的条件；同时，对稳定同位素混合模型在水生生态系统食物网领域中的应用前景与局限性进行了总结与展望，以期为相关研究者提供参考

Research progress of stable isotope models in aquatic ecosystem food webs

The aquatic ecosystem is essential for human survival and development. Food web studies on aquatic ecosystems describe many key processes, such as material cycling and energy flow processes. The results are of great significance for protecting the diversity, stability, and functionality of biological and ecological systems. However, the extreme complexity of aquatic ecosystem food webs has puzzled ecological researchers. The development of stable isotope technology has contributed significantly to our understanding of intricate feeding relationships and structure of food webs. The carbon and nitrogen-stable isotope compositions of animal tissues are closely related to their food sources, reflecting the comprehensive characteristics of all food isotopic compositions assimilated over a period of time by animal tissues. The carbon isotope composition of animals can indicate their food source, while the nitrogen-stable isotope composition can reflect the trophic structure. However, the animal diet is not composed of a single food source, and the complexity and unpredictability of food sources complicate the interpretation of carbon and nitrogen-stable isotope data regarding the contribution of food sources. In recent years, the rapid development of stable isotope mixing models (SIMMs) has provided a powerful means to solve the complexity of aquatic food webs, particularly with regard to determining the contribution of food sources and comparing consumer niches. In this study, we reviewed the historical evolution of stable isotope models, the characteristics of the most prominent models, and factors to consider when utilizing such models. This study summarized the application prospects and limitations of stable isotope mixing models in the research field of aquatic ecosystem food webs in order to provide a reference and scientific basis for subsequent research.The development of stable isotope models can roughly be divided into three stages: the early initial stage (1976–2001), which mainly involved the development of linear models; the supplementary stage (2001–2008), during which numerous uncertain factors were added to the model analysis as a result of the advancement of computer technology; the Bayesian mixed model stage (2008–current). The mixed model stage is based on mass conservation, and the Bayesian framework greatly improves the accuracy and credibility of model analysis. Simmr, MixSIAR, and SIBER have become the primary isotope models used today.Stable isotope technology has a long history of development, and the emergence of various stable isotope models has expanded the application of isotope technology in the research field of food webs. These models have powerful analytical capabilities and provide researchers with a powerful means for analyzing the structure of the food web. However, owing to the limitations of isotope analysis and models, researchers should pay more attention to the relevant prerequisites and practical ecological significance when selecting models to analyze isotope data. Researchers should also devise reasonable field investigation and experimental treatment plans based on their own experimental conditions and economic capacity in order to avoid the error analysis and misuse of isotope models and reduce the uncertainty of model analysis results as much as possible.Based on the previous research progress, the authors share their experience and understanding of the application of isotope mixing models. The purpose of this study was to assist fellow researchers in quickly understanding the development process and matters requiring the attention of isotope models, as well as to provide fundamental data and theoretical support for related research.