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

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.

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Institutions

Publication Details

Journal
Journal of Plant Ecology
Published
2024-10-14
DOI
https://doi.org/10.1093/jpe/rtae094
Citations
6
Primary Topic
Advanced Algorithms and Applications
Type
article
Field-Weighted Citation Impact
1.97
Controls
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article

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

Jinshui Qiu, Yanan Wang, Jianwen Zhang, Huifu Zhuang
6 citations
Journal of Plant Ecology
Advanced Algorithms and Applications
1.97
article

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

Jinshui Qiu, Yanan Wang, Jianwen Zhang, Huifu Zhuang
article en
6 citations

Abstract

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.

Journal of Plant EcologyVol. 17(6)
Kunming Institute of Botany (CN), Kunming Institute of Zoology (CN), Chinese Academy of Sciences (CN), Wildlife Information Liaison Development (IN), University of Chinese Academy of Sciences (CN)
Life in Land
Openalex Percentile: Top 13%
Advanced Algorithms and Applications
1.97
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