Quantifying Plant Species alpha-Diversity Using Normalized Difference Vegetation Index and Climate Data in Alpine Grasslands
文献类型：期刊论文
| 作者 | Tian, Yuan; Fu, Gang |
| 刊名 | REMOTE SENSING
 |
| 出版日期 | 2022-10-01 |
| 卷号 | 14期号:19页码:14 |
| 关键词 | biodiversity alpine ecosystem global change random forest alpine region 'Third Pole' Tibetan Plateau |
| DOI | 10.3390/rs14195007 |
| 通讯作者 | Fu, Gang(fugang@igsnrr.ac.cn) |
| 英文摘要 | Quantitative plant species alpha-diversity of grasslands at multiple spatial and temporal scales is important for investigating the responses of biodiversity to global change and protecting biodiversity under global change. Potential plant species alpha-diversity (i.e., SRp, Shannon(p), Simpson(p) and Pielou(p): potential species richness, Shannon index, Simpson index and Pielou index, respectively) were quantified by climate data (i.e., annual temperature, precipitation and radiation) and actual plant species alpha-diversity (i.e., SRa, Shannon(a), Simpson(a) and Pielou(a): actual species richness, Shannon index, Simpson index and Pielou index, respectively) were quantified by normalized difference vegetation index and climate data. Six methods (i.e., random forest, generalized boosted regression, artificial neural network, multiple linear regression, support vector machine and recursive regression trees) were used in this study. Overall, the constructed random forest models performed the best among the six algorithms. The simulated plant species alpha-diversity based on the constructed random forest models can explain no less than 96% variation of the observed plant species alpha-diversity. The RMSE and relative biases between simulated alpha-diversity based on the constructed random forest models and observed alpha-diversity were <= 1.58 and within +/- 4.49%, respectively. Accordingly, plant species alpha-diversity can be quantified from the normalized difference vegetation index and climate data using random forest models. The random forest models of plant alpha-diversity build by this study had enough predicting accuracies, at least for alpine grassland ecosystems, Tibet. The proposed random forest models of plant alpha-diversity by this current study can help researchers to save time by abandoning plant community field surveys, and facilitate researchers to conduct studies on plant alpha-diversity over a long-term temporal scale and larger spatial scale under global change. |
| WOS关键词 | GRAZING EXCLUSION ; TIBETAN PLATEAU ; PRECIPITATION ; FPAR/LAI ; MEADOW |
| 资助项目 | Youth Innovation Promotion Association of Chinese Academy of Sciences[2020054] ; National Natural Science Foundation of China[31600432] ; Bingwei Outstanding Young Talents Program of Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences[2018RC202] ; Science and Technology Project of Tibet Autonomous Region[XZ202101ZD0003N] ; Science and Technology Project of Tibet Autonomous Region[XZ202101ZD0007G] ; Science and Technology Project of Tibet Autonomous Region[XZ202201ZY0003N] ; STS Project of Chinese Academy of Sciences[KFJ-STS-QYZD-2021-22-003] ; Construction of Fixed Observation and Experimental Station of First and Try Support System for Agricultural Green Development in Zhongba County ; Central Government Guides Local Science and Technology Development Program[XZ202202YD0009C] |
| WOS研究方向 | Environmental Sciences & Ecology ; Geology ; Remote Sensing ; Imaging Science & Photographic Technology |
| 语种 | 英语 |
| WOS记录号 | WOS:000867130900001 |
| 出版者 | MDPI |
| 资助机构 | Youth Innovation Promotion Association of Chinese Academy of Sciences ; National Natural Science Foundation of China ; Bingwei Outstanding Young Talents Program of Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences ; Science and Technology Project of Tibet Autonomous Region ; STS Project of Chinese Academy of Sciences ; Construction of Fixed Observation and Experimental Station of First and Try Support System for Agricultural Green Development in Zhongba County ; Central Government Guides Local Science and Technology Development Program |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/185449]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | Fu, Gang |
| 作者单位 | Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Ecosyst Network Observat & Modeling, Lhasa Plateau Ecosyst Res Stn, Beijing 100101, Peoples R China |
| 推荐引用方式 GB/T 7714 | Tian, Yuan,Fu, Gang. Quantifying Plant Species alpha-Diversity Using Normalized Difference Vegetation Index and Climate Data in Alpine Grasslands[J]. REMOTE SENSING,2022,14(19):14. |
| APA | Tian, Yuan,&Fu, Gang.(2022).Quantifying Plant Species alpha-Diversity Using Normalized Difference Vegetation Index and Climate Data in Alpine Grasslands.REMOTE SENSING,14(19),14. |
| MLA | Tian, Yuan,et al."Quantifying Plant Species alpha-Diversity Using Normalized Difference Vegetation Index and Climate Data in Alpine Grasslands".REMOTE SENSING 14.19(2022):14. |
入库方式： OAI收割
来源：地理科学与资源研究所
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