最大熵模型在植物生态评估领域的应用

Application of Maximum Entropy Model in the Field of Plant Ecological Assessment

最大熵(MaxEnt)模型能够高效评估植物种群响应环境变化导致的适宜生境变迁问题。为深入了解MaxEnt模型在植物生态评估领域的应用现状与前沿趋势,检索Web of Science数据库2001—2023年该领域的相关文献,利用VOSviewer、HistCite TM和R-Studio等软件,系统总结并分析了该领域的研究国家、机构、作者、关键词以及结构概念等。结果显示,中国(410篇,22.82%)、美国(231篇,12.85%)和印度(81篇,4.51%)是发文量排名前3的国家。中国科学院、墨西哥国立自治大学以及陕西师范大学是高产量的研究机构。Smith M.J.、Wan J.和Kumar S.分别是引文量排名第1,发文量最多和发文持续时间最长的学者。社会结构分析揭示,该领域整体呈现小世界,分散未网络化的合作特征,来自同一个国家的机构之间合作更为密切,国际间合作较为匮乏。关键词分析揭示11个热门关键词的频率≥150次,如气候变化(252次)、植物(247次)。MaxEnt模型在该领域主要被用于解决植物应对气候和环境胁迫、种群多样性和适宜生境分布范围的扩张或收缩变化的问题。3个热点方向值得被重点关注,即优化物种分布模型存在的缺陷、单一模型评估植物应对气候变化的响应模式、多种模型联合评估植物响应环境变化的生境变迁规律。该研究为MaxEnt模型在植物研究领域的应用提供了新的评估数据和潜在的研究方向。

The MaxEnt(maximum entropy)model efficiently evaluates the shift in suitable habitats of plant populations in response to environmental changes.To gain deeper insights into the current applications and future trends of the MaxEnt model in the field of plant ecological assessment,we conducted a comprehensive review of relevant literature from 2001 to 2023 using the Web of Science database.Employing various software tools such as VOSviewer,HistCite TM and R-Studio,we systematically summarized and analyzed the research countries,institutions,authors,keywords and structural concepts in this domain.The results showed that China(410 articles,22.82%),the United States(231 articles,12.85%)and India(81 articles,4.51%)were the top 3 countries with high productivity of published papers.Chinese Academy of Sciences,National Autonomous University of Mexico,and Shaanxi Normal University were high-output institutions.Smith M.J.,Wan J.and Kumar S.were the scholars with the highest number of citations,the highest publications and the longest duration of publications,respectively.Social structure analysis revealed that the field exhibits an overall small-world characteristic,characterized by dispersed and non-networked collaboration.Collaboration between institutions from the same country was more closely knit,while international collaboration was relatively scarce.The keyword analysis showed that 11 hot terms had a frequency of≥150 occurrences,such as climate change(252 occurrences),plants(247 occurrences)and predictions(215 occurrences).The main problem addressed in this field involved dissecting how plant populations respond to environmental stress,the expansion or contraction of biodiversity and the potential range of suitable habitats.Trend analysis showed that three hot investigative directions deserved focus and further improvement,including optimizing the shortcomings of species distribution models,evaluating the response patterns of plants to climate change using single models and jointly assessing the habitat transition patterns of plant responses to environmental changes using multiple models.In conclusion,this study provided new evaluation data and potential research directions for the application of the MaxEnt model in the field of plant research.