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Problems and Countermeasures in Prediction Model of Potential Distribution of Plant Species with Extremely Small Populations

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DOI: 10.23977/erej.2022.060501 | Downloads: 8 | Views: 450

Author(s)

Wei Hu 1, Xin Liang 1, Yaqi Zhang 1, Xiansheng Tan 1, Renyan Duan 1

Affiliation(s)

1 College of Agriculture and Biology Technology, Hunan University of Humanities Science and Technology, Loudi, Hunan, 417000, China

Corresponding Author

Renyan Duan

ABSTRACT

The plant species with extremely small populations (PSESP) is a kind of wild plant population that is on the verge of extinction. It is important to reasonably predict the suitable distribution area of the PSESP for its protection. However, the lack of suitable prediction models, low quality of distribution data and high sensitivity of simulation process can limit the application of species distribution models in the protection of PSESP. It is suggested that a small model niche factor model set should be constructed and optimized according to the different distribution characteristics of PSESP. In order to improve the quality of distribution data, the method of combining real species with virtual species is used to conduct field iterative stratified sampling. Based on the distribution data of iterative stratified sampling lifting and the optimized small model niche factor model, the key factors in the simulation process are optimized to reasonably predict the suitable distribution area of PSESP. Based on the distribution of nature reserves and the potential distribution of PSESP, field investigation and verification, the appropriate in situ or ex situ protection strategies for PSESP can be proposed.

KEYWORDS

Plant species with extremely small populations, Suitable habitat, Species distribution model, Prediction model

CITE THIS PAPER

Wei Hu, Xin Liang, Yaqi Zhang, Xiansheng Tan, Renyan Duan, Problems and Countermeasures in Prediction Model of Potential Distribution of Plant Species with Extremely Small Populations. Environment, Resource and Ecology Journal (2022) Vol. 6: 1-4. DOI: http://dx.doi.org/10.23977/erej.2022.060501.

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