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Method

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

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  • 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 date: 2024-08-21

  Accepted date: 2024-09-29

  Online published: 2024-10-15

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).

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.

Cite this article

Jinshui Qiu, Jianwen Zhang, Yanan Wang, Huifu Zhuang . PPDC: an online platform for the prediction of plant distributions in China[J]. Journal of Plant Ecology, 2024 , 17(6) : 1 -11 . DOI: 10.1093/jpe/rtae094

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