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HYPOTHESIS AND THEORY article

Front. Plant Sci.
Sec. Functional Plant Ecology
Volume 15 - 2024 | doi: 10.3389/fpls.2024.1516251

Prediction of the potentially suitable areas of Paeonia lactiflora in China based on Maxent and Marxan models

Provisionally accepted
Yongji Wang Yongji Wang 1Wentao Huo Wentao Huo 1Kefan Wu Kefan Wu 1Jiaying Cao Jiaying Cao 1Guanghua Zhao Guanghua Zhao 2Fen-Guo Zhang Fen-Guo Zhang 1*
  • 1 School of Life Science, Shanxi Normal University, Shanxi, China
  • 2 School of Life Science, South China Normal University, Tianhe, China

The final, formatted version of the article will be published soon.

    Paeonia lactiflora Pall. (P. lactiflora) is an important medicinal plant in China with high ornamental value. Predicting the potential habitat of P. lactiflora is crucial for identifying its geographic distribution characteristics and ensuring its ecological and economic importance. Therefore, we aimed to predict the potential geographic distribution of P. lactiflora in China under future climate change scenarios. To this end, we used an optimized Maxent model and ArcGIS software to analyze the influence of 12 environmental variables on P. lactiflora potential distribution in China based on 291 effective distribution records. The key factors limiting the potential geographic distribution of P. lactiflora were evaluated by combining the contribution rates of the environmental variables with the significance of their replacement. The jackknife method was employed to assess the importance of these factors. Response curves were used to determine the appropriate intervals for the environmental factor variables and to analyze the changes in spatial patterns. The Maxent model exhibited a low degree of overfitting and good prediction accuracy. The main variables influencing P. lactiflora distribution were precipitation in the wettest month and hottest quarter, lowest temperature in the coldest month, and highest temperature in the warmest month. Under current climatic conditions, P. lactiflora could theoretically grow across and area of 231.1 × 10 4 km 2 in China. Under the six future climate change scenarios, the potential geographic distribution area was reduced compared with the current distribution area, and the potentially suitable areas shifted southwestward. The majority of priority conservation sites for P. lactiflora are located in northern and northeastern China, which align with the highly favorable areas predicted by the Maxent model. The findings of this investigation can guide the selection of future introductions as well as artificial cultivation and preservation of P. lactiflora resources.

    Keywords: Paeonia lactiflora, Climate Change, Maxent, Marxan, Prediction of suitable area

    Received: 25 Oct 2024; Accepted: 18 Dec 2024.

    Copyright: © 2024 Wang, Huo, Wu, Cao, Zhao and Zhang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Fen-Guo Zhang, School of Life Science, Shanxi Normal University, Shanxi, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.