Identifying the habitat suitability of Pteris vittata in China and associated key drivers using machine learning models
文献类型：期刊论文
| 作者 | Chen, Shiqi3; Guo, Guanghui3; Lei, Mei3; Peng, Hao2; Ju, Tienan3 |
| 刊名 | SCIENCE OF THE TOTAL ENVIRONMENT
 |
| 出版日期 | 2024-12-01 |
| 卷号 | 954页码:176213 |
| 关键词 | Pteris vittata Machine learning Spatial correlation Prediction accuracy Arsenic |
| DOI | 10.1016/j.scitotenv.2024.176213 |
| 产权排序 | 1 |
| 文献子类 | Article |
| 英文摘要 | Pteris vittata (P. P. vittata) ) possesses significant potential in remediating arsenic (As) soil pollution. Understanding the habitat suitability of P. vittata in China and pinpointing the key drivers that influence its distribution can facilitate the identification of optimal areas for using P. vittata as a remediation tool for As-polluted soils. In this study, a comparative analysis was conducted using ten machine learning models to assess the habitat suitability of P. vittata based on 744 specimen records and 20 environmental factors. The key drivers affecting the distribution of P. vittata were also investigated based on the optimal model. The results indicate that the XGBOOST model was the most reliable and stable, achieving a coefficient of determination of 0.95. Approximately 24.47 % of China's land area was identified as suitable for P. vittata. . Particularly, it was predominantly found in Hainan (45.9 %), Guangxi (92.96 %), Guangdong (91.68 %), Hunan (91.26 %), Guizhou (90.83 %), Chongqing (88.17 %), Fujian (85.70 %), Yunnan (77.44 %), Jiangxi (73.99 %) and Zhejiang (57.05 %). Furthermore, this study pinpointed the lowest temperature, annual temperature range, and mining density as key drivers, contributing 45.9 %, 31.9 %, and 7.2 %, respectively. Spatial correlation analysis revealed a significant correlation between mining density and the habitat distribution of P. vittata (Moran' I = 0.519). This study confirmed that both natural factors and anthropogenic activities affect the distribution of P. vittata and provided valuable insights for optimizing the application of P. vittata in soil phytoremediation and reclamation. |
| WOS关键词 | DISTRIBUTIONS ; ACCUMULATION ; ZINC ; LEAD ; SOIL |
| WOS研究方向 | Environmental Sciences & Ecology |
| WOS记录号 | WOS:001321277000001 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/207972]  |
| 专题 | 资源利用与环境修复重点实验室_外文论文 |
| 通讯作者 | Guo, Guanghui |
| 作者单位 | 1.Chinese Acad Sci, Natl Sci Lib, Beijing 100086, Peoples R China 2.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 3.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China |
| 推荐引用方式 GB/T 7714 | Chen, Shiqi,Guo, Guanghui,Lei, Mei,et al. Identifying the habitat suitability of Pteris vittata in China and associated key drivers using machine learning models[J]. SCIENCE OF THE TOTAL ENVIRONMENT,2024,954:176213. |
| APA | Chen, Shiqi,Guo, Guanghui,Lei, Mei,Peng, Hao,&Ju, Tienan.(2024).Identifying the habitat suitability of Pteris vittata in China and associated key drivers using machine learning models.SCIENCE OF THE TOTAL ENVIRONMENT,954,176213. |
| MLA | Chen, Shiqi,et al."Identifying the habitat suitability of Pteris vittata in China and associated key drivers using machine learning models".SCIENCE OF THE TOTAL ENVIRONMENT 954(2024):176213. |
入库方式： OAI收割
来源：地理科学与资源研究所
浏览0
下载0
收藏0
其他版本
除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。