Mapping functional diversity using individual tree-based morphological and physiological traits in a subtropical forest
文献类型：期刊论文
| 作者 | Zheng, Zhaoju1; Zeng, Yuan1,4; Schneider, Fabian D.; Zhao, Yujin3; Zhao, Dan1; Schmid, Bernhard; Schaepman, Michael E.; Morsdorf, Felix |
| 刊名 | REMOTE SENSING OF ENVIRONMENT
 |
| 出版日期 | 2021 |
| 卷号 | 252 |
| 关键词 | LiDAR Imaging spectroscopy Forest diversity Functional traits Individual tree-based approach Scaling |
| ISSN号 | 0034-4257 |
| DOI | 10.1016/j.rse.2020.112170 |
| 文献子类 | Article |
| 英文摘要 | Functional diversity (FD) provides a link between biodiversity and ecosystem functioning, summarizing inter and intra-specific variation of functional traits. However, quantifying plant traits and FD consistently and costeffectively across large and heterogeneous forest areas is challenging with traditional field sampling. Airborne light detection and ranging (LiDAR) and imaging spectroscopy provide spatially explicit data, which allow mapping of selected forest traits and FD at different spatial scales. We develop an individual tree-based method to measure forest FD from tree neighborhoods to whole forests, and demonstrate the approach by mapping functional traits of over one million trees in a subtropical forest in China. We retrieved canopy morphological traits (95th quantile height, leaf area index and foliage height diversity) and physiological traits (proxies of nitrogen, carotenoids and specific leaf area) for each individual canopy tree crown from LiDAR and imaging spectroscopy data, respectively. Based on the multivariate trait space spanned by the six trait axes and filled by measured tree individuals, we mapped forest FD as richness, divergence and evenness, and explored spatial patterns of FD as well as FD-area and FD-tree number relationships. The results show that LiDAR-derived morphological traits and spectral indices of physiological traits are consistent with field measurements and show weak correlations between each other at individual tree level. Morphological functional richness follows a hump-shaped pattern along the elevational gradient of 984-1805 m, with maximum values at elevations around 1450 m, while high physiological functional richness occurs at medium and high elevations. At an ecosystem scale of 30 x 30 m, morphological richness increases continuously with tree density, but physiological richness decreases again at very high densities. Moreover, functional richness shows a logarithmic relationship with increasing area or number of individual trees, and local trait convergence is predominant in our study area. We demonstrate the ability to quantify FD using morphological and physiological traits by remote sensing, which provides a pathway to conduct individual-level trait-based ecology with wall-to-wall data. |
| 学科主题 | Environmental Sciences ; Remote Sensing ; Imaging Science & Photographic Technology |
| 出版地 | NEW YORK |
| 电子版国际标准刊号 | 1879-0704 |
| WOS关键词 | SPECIES-AREA RELATIONSHIPS ; GEOMETRIC-OPTICAL MODEL ; IMAGING SPECTROSCOPY ; CANOPY TRAITS ; CHEMICAL-PROPERTIES ; CHLOROPHYLL CONTENT ; TROPICAL FOREST ; PLANT TRAITS ; LEAF ; LIDAR |
| WOS研究方向 | Science Citation Index Expanded (SCI-EXPANDED) |
| 语种 | 英语 |
| WOS记录号 | WOS:000595881100004 |
| 出版者 | ELSEVIER SCIENCE INC |
| 资助机构 | National Key Research and Development Program of China [2016YFC0500201] ; National Natural Science Foundation of China [42071344, 41771464] ; University of Zurich Research Priority Program on Global Change and Biodiversity (URPP GCB) ; National Aeronautics and Space Administration [80NM0018D0004] ; U.S. Government sponsorship ; Shanghai Hangyao Information Technology Cooperation ; China Scholarship Council [201704910941] |
| 源URL | [http://ir.ibcas.ac.cn/handle/2S10CLM1/26674]  |
| 专题 | 植被与环境变化国家重点实验室 |
| 作者单位 | 1.Univ Zurich, Dept Geog, Remote Sensing Labs, CH-8057 Zurich, Switzerland 2.Chinese Acad Sci, Inst Bot, State Key Lab Vegetat & Environm Change, Beijing 100093, Peoples R China 3.Schneider, Fabian D.] CALTECH, Jet Prop Lab, Pasadena, CA 91109 USA 4.Chinese Acad Sci, Aerosp Informat Res Inst, State Key Lab Remote Sensing Sci, Beijing 100101, Peoples R China 5.Univ Chinese Acad Sci, Beijing 100049, Peoples R China |
| 推荐引用方式 GB/T 7714 | Zheng, Zhaoju,Zeng, Yuan,Schneider, Fabian D.,et al. Mapping functional diversity using individual tree-based morphological and physiological traits in a subtropical forest[J]. REMOTE SENSING OF ENVIRONMENT,2021,252. |
| APA | Zheng, Zhaoju.,Zeng, Yuan.,Schneider, Fabian D..,Zhao, Yujin.,Zhao, Dan.,...&Morsdorf, Felix.(2021).Mapping functional diversity using individual tree-based morphological and physiological traits in a subtropical forest.REMOTE SENSING OF ENVIRONMENT,252. |
| MLA | Zheng, Zhaoju,et al."Mapping functional diversity using individual tree-based morphological and physiological traits in a subtropical forest".REMOTE SENSING OF ENVIRONMENT 252(2021). |
入库方式： OAI收割
来源：植物研究所
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