Optimization of the Fuzzy Matter Element Method for Predicting Species Suitability Distribution Based on Environmental Data

Sustainability

Wei Gu¹  Quanzhong Zhang²  Haiyan Wei²  Zefang Zhao²  Jing Liu²  Qiao Ran²  Junhong Yu³ 

[1] National Engineering Laboratory for Resource Development of Endangered Crude Drugs in Northwest of China, Shaanxi Normal University, Xi’an 710119, China;School of Geography and Tourism, Shaanxi Normal University, Xi’an 710119, China;School of Mathematics and Information Science, Shaanxi Normal University, Xi’an 710119, China;

关键词: species distribution modelling;    membership function;    suitability index;    climate change;    GIS;    Gynostemma pentaphyllum (Thunb.) Makino;   

DOI  :  10.3390/su10103444

来源: DOAJ

【 摘 要 】

Over the years, with the efforts of many researchers, the field of species distribution model (SDM) has been well explored. The model of fuzzy matter elements (FME), which, combined with GIS to predict species distribution, has received extensive attention since its emergence. Based on previous studies, this paper improved FME, extended the scope of the membership degree and habitat suitability index, and explored the unsuitable areas of species. We have enhanced the limitation effect of key variables on species habitats, making the operation of FME more consistent with biological laws. By optimizing the FME, it could avoid the accumulation of predicted errors with multi-variables, and make the predicted results more reasonable. In this study, Gynostemma pentaphyllum (Thunb.) Makino was used as an example. The experimental process used several major environmental variables (climate, soil, and terrain variables) to predict the habitat suitability distribution of G. pentaphyllum in China for its current and future period, which includes the period of 2050s (average for 2041–2060) and 2070s (average for 2061–2080) under representative concentration pathways 4.5 (RCP4.5). The results of the analysis showed that the model performed well with a high accuracy by reducing the redundancy of the environmental data. The study could relieve the reliance on a large database of environmental information and propose a new approach for protecting the G. pentaphyllum in unsuitable areas under climate change.

【 授权许可】

Unknown