Knowledge Management System Of Institute Of Botany,CAS
Hyperspectral retrieval of leaf physiological traits and their links to ecosystem productivity in grassland monocultures | |
Zhao, Yujin; Sun, Yihan1; Lu, Xiaoming; Zhao, Xuezhen1; Yang, Long2; Sun, Zhongyu2; Bai, Yongfei1 | |
2021 | |
发表期刊 | ECOLOGICAL INDICATORS |
ISSN | 1470-160X |
卷号 | 122 |
摘要 | Plant functional traits are closely associated with key ecological processes and ecosystem functions. Recent studies have demonstrated that plant functional traits, especially physiological traits, can be successfully derived from hyperspectral images. Plant physiological traits are frequently quantified either as area-based content [mu g cm(-2)] or mass-based concentration [mg g(-1) or %]. However, it remains unclear whether the two metrics of traits can be quantified using remote sensing approaches. We quantified area- and mass-based foliar physiological traits to compare the prediction accuracy of the two metrics based on leaf spectra using partial least squares regression (PLSR) at a grassland monoculture experiment. These two metrics were then scaled up to canopy traits, respectively, based on leaf area index (LAI) and biomass to test their performance at the canopy level. The canopy physiological traits with high prediction accuracy (R-2 = 0.60) were selected for mapping using the unmanned aerial vehicle (UAV)-based UHD185 spectrometer. Biomass and LAI were also estimated and mapped using the PLSR method. The mapped leaf traits (canopy traits divided by the corresponding LAI), were used to explore the relationships between the interspecific and intraspecific variations in leaf physiological traits and ecosystem productivity (i.e., aboveground biomass). The results showed that the retrieval of leaf physiological traits using leaf spectra and canopy spectra or remote sensing was better performed on an area basis rather than a mass basis, especially for the physiological traits related to photosynthesis. Model selection results also indicted that remotely sensed physiological traits (chlorophyll a, chlorophyll b, carotenoid, carbon, nitrogen, and leaf mass per area (LMA)) and their intraspecific variations (coefficient variation (CV) for a single trait and functional richness (FRic) for multiple traits) were significant predictors of community aboveground biomass across grassland monocultures. Our study highlights the potential of hyperspectral images for trait mapping and estimating ecosystem productivity at large scales. Our findings also provide a vital insight for disentangling the links of functional traits and intra- and interspecific trait variations to key ecological processes and functions. |
关键词 | Functional trait Partial least squares regression (PLSR) Hyperspectral image Ecosystem function Unmanned aerial vehicle (UAV) Aboveground biomass |
学科领域 | Biodiversity Conservation ; Environmental Sciences |
DOI | 10.1016/j.ecolind.2020.107267 |
收录类别 | SCI |
语种 | 英语 |
WOS关键词 | FUNCTIONAL DIVERSITY ; INNER-MONGOLIA ; IMAGING SPECTROSCOPY ; CHLOROPHYLL CONTENT ; OPTICAL-PROPERTIES ; PLANT TRAITS ; AREA INDEX ; NITROGEN ; VEGETATION ; IMAGERY |
WOS研究方向 | Science Citation Index Expanded (SCI-EXPANDED) |
WOS记录号 | WOS:000613238900003 |
出版者 | ELSEVIER |
文献子类 | Article |
出版地 | AMSTERDAM |
EISSN | 1872-7034 |
资助机构 | National Key R&D Program of China [2017YFA0604702] ; National Natural Science Foundation of China [41801230, 31630010] |
作者邮箱 | yfbai@ibcas.ac.cn |
作品OA属性 | gold |
引用统计 | |
文献类型 | 期刊论文 |
条目标识符 | http://ir.ibcas.ac.cn/handle/2S10CLM1/26716 |
专题 | 植被与环境变化国家重点实验室 |
作者单位 | 1.Chinese Acad Sci, Inst Bot, State Key Lab Vegetat & Environm Change, 20 Nanxincun, Beijing 100093, Peoples R China 2.Univ Chinese Acad Sci, Coll Resources & Environm, Beijing 100049, Peoples R China 3.Guangzhou Inst Geog, Guangdong Open Lab Geospatial Informat Technol &, Guangzhou 510070, Peoples R China |
推荐引用方式 GB/T 7714 | Zhao, Yujin,Sun, Yihan,Lu, Xiaoming,et al. Hyperspectral retrieval of leaf physiological traits and their links to ecosystem productivity in grassland monocultures[J]. ECOLOGICAL INDICATORS,2021,122. |
APA | Zhao, Yujin.,Sun, Yihan.,Lu, Xiaoming.,Zhao, Xuezhen.,Yang, Long.,...&Bai, Yongfei.(2021).Hyperspectral retrieval of leaf physiological traits and their links to ecosystem productivity in grassland monocultures.ECOLOGICAL INDICATORS,122. |
MLA | Zhao, Yujin,et al."Hyperspectral retrieval of leaf physiological traits and their links to ecosystem productivity in grassland monocultures".ECOLOGICAL INDICATORS 122(2021). |
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Hyperspectral_retrie(9433KB) | 期刊论文 | 出版稿 | 开放获取 | CC BY-NC-SA | 浏览 请求全文 |
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