Prediction of global marginal land resources for Pistacia chinensis Bunge by a machine learning method
文献类型：期刊论文
| 作者 | Chen, Shuai1,2; Hao, Mengmeng1,2; Qian, Yushu1; Ding, Fangyu1; Xie, Xiaolan1,2; Ma, Tian1,2 |
| 刊名 | SCIENTIFIC REPORTS
 |
| 出版日期 | 2022-04-07 |
| 卷号 | 12期号:1页码:9 |
| ISSN号 | 2045-2322 |
| DOI | 10.1038/s41598-022-09830-5 |
| 通讯作者 | Ding, Fangyu(dingfy@igsnrr.ac.cn) ; Xie, Xiaolan(xiexl.20b@igsnrr.ac.cn) |
| 英文摘要 | Biofuel has attracted worldwide attention due to its potential to combat climate change and meet emission reduction targets. Pistacia chinensis Bunge (P. chinensis) is a prospective plant for producing biodiesel. Estimating the global potential marginal land resources for cultivating this species would be conducive to exploiting bioenergy yielded from it. In this study, we applied a machine learning method, boosted regression tree, to estimate the suitable marginal land for growing P. chinensis worldwide. The result indicated that most of the qualified marginal land is found in Southern Africa, the southern part of North America, the western part of South America, Southeast Asia, Southern Europe, and eastern and southwest coasts of Oceania, for a grand total of 1311.85 million hectares. Besides, we evaluated the relative importance of the environmental variables, revealing the major environmental factors that determine the suitability for growing P. chinensis, which include mean annual water vapor pressure, mean annual temperature, mean solar radiation, and annual cumulative precipitation. The potential global distribution of P. chinensis could provide a valuable basis to guide the formulation of P. chinensis-based biodiesel policies. |
| WOS关键词 | COMPLETE CHLOROPLAST GENOME ; SEED OIL ; BIOENERGY ; BIODIESEL |
| 资助项目 | National Key R&D Program of China[2019YFC0507805] |
| WOS研究方向 | Science & Technology - Other Topics |
| 语种 | 英语 |
| WOS记录号 | WOS:000779768200023 |
| 出版者 | NATURE PORTFOLIO |
| 资助机构 | National Key R&D Program of China |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/174631]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Ding, Fangyu; Xie, Xiaolan |
| 作者单位 | 1.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, 11A Datun Rd, Beijing 100101, Peoples R China 2.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China |
| 推荐引用方式 GB/T 7714 | Chen, Shuai,Hao, Mengmeng,Qian, Yushu,et al. Prediction of global marginal land resources for Pistacia chinensis Bunge by a machine learning method[J]. SCIENTIFIC REPORTS,2022,12(1):9. |
| APA | Chen, Shuai,Hao, Mengmeng,Qian, Yushu,Ding, Fangyu,Xie, Xiaolan,&Ma, Tian.(2022).Prediction of global marginal land resources for Pistacia chinensis Bunge by a machine learning method.SCIENTIFIC REPORTS,12(1),9. |
| MLA | Chen, Shuai,et al."Prediction of global marginal land resources for Pistacia chinensis Bunge by a machine learning method".SCIENTIFIC REPORTS 12.1(2022):9. |
入库方式： OAI收割
来源：地理科学与资源研究所
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