Journal of Plant Ecology ›› 2024, Vol. 17 ›› Issue (6): 1-11.DOI: 10.1093/jpe/rtae094

• • 上一篇    

PPDC: 中国植物物种分布预测服务平台

  

  • 收稿日期:2024-08-21 接受日期:2024-09-29 出版日期:2024-12-01 发布日期:2024-12-25

PPDC: an online platform for the prediction of plant distributions in China

Jinshui Qiu1,2,3,*, Jianwen Zhang1, Yanan Wang4,5, and Huifu Zhuang1,2,3,5,*   

  1. 1Science and Technology Information Center, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China
    2Key Laboratory of Phytochemistry and Natural Medicines, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming 650201, China
    3National Wild Plant Germplasm Resource Center, Kunming 650201, China
    4Biodiversity Data Center of Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming 650201, China
    5University of Chinese Academy of Sciences, Beijing 100049, China

    *Corresponding author. E-mail: qiujinshui@mail.kib.ac.cn (J.Q.); zhuanghuifu@mail.kib.ac.cn (H.Z.)
  • Received:2024-08-21 Accepted:2024-09-29 Online:2024-12-01 Published:2024-12-25
  • Supported by:
    This research was supported by the Technical Innovation Talents of Yunnan Province (202405AD350053/202305AD160021), the CAS Technology Talent Program, Major Science and Technique Programs in Yunnan Province (202102AA310055), the Yunnan Ten-Thousand Talents Plan Young & Elite Talent Project (YNWR-QNBJ-2019-154), and the Network Security and Informatization Project of Chinese Academy of Sciences (CAS-WX2022SDC-SJ01).

摘要: 植物能否在特定区域生存和繁衍与其生态位密切相关。通过基于生态位原理构建的物种分布模型,可以有效预测植物的潜在分布区,从而为濒危植物的保护、入侵植物的防治以及植物的引种与迁地保护等工作提供重要指导。然而,传统的植物潜在分布区预测方法和流程相对繁琐复杂,需收集和处理大量数据,并通过人工操作多个软件工具,导致工作效率较低,难以大规模应用于植物分布预测工作。为此,我们整理了大量中国植物的基础数据、植物出现记录及环境因子数据,基于物种分布模型和地图整饰技术,构建了一个能够自动预测中国植物潜在分布区的工作流系统,成功完成了对中国3.2万种植物的潜在分布区预测。我们还基于可视化技术开发了一个在线的中国植物分布预测服务平台(PPDC),并将中国植物的潜在分布区预测结果向科研人员开放共享,用户可以便捷地查询到中国植物的潜在分布区信息,帮助他们快速了解植物的分布状况。同时,该平台还支持用户根据需求,快速预测某种植物在中国特定区域范围内的潜在分布区,为植物分布预测工作提供了技术支持,并为生物多样性保护工作提供智力支持。

关键词: 中国植物, 植物分布预测, 潜在分布, 物种分布模型, 分布预测服务

Abstract: The survival and reproduction of plants in a particular region are closely related to the local ecological niche. The use of species distribution models based on the ecological niche concept to predict potential distributions can effectively guide the protection of endangered plants, prevention and control of invasive plants, and plant introduction and ex-situ conservation. However, traditional methods and processes for predicting potential distributions of plants are tedious and complex, requiring the collection and processing of large amounts of data and the manual operation of multiple tools. Therefore, it is difficult to achieve large-scale prediction of the potential distributions of plants. To address these limitations, by collecting and organizing a large amount of basic data, occurrence records, and environmental data and integrating species distribution models and mapping techniques, a workflow to automatically predict the potential distributions of Chinese plants was established, thus the innovative work of predicting the potential distributions of 32 000 species of plants in China was completed. Furthermore, an online platform for predicting plant distributions in China based on visualization technology was developed, providing a basis for sharing the prediction results across a wide range of scientists and technologists. Users can quickly access information about the potential distributions of plants in China, providing a reference for the collection, preservation, and protection of plant resources. In addition, users can quickly predict the potential distribution of a certain plant in a certain region across China according to specific needs, thus providing technical support for biodiversity conservation.

Key words: plants in China, plant distribution prediction, potential distribution, species distribution model, distribution prediction service