干旱区生态环境知识资源中心(Arid): A novel approach for long-term spectral monitoring of desert shrubs affected by an oil spill

Arid

DOI	10.1016/j.envpol.2021.117788
	A novel approach for long-term spectral monitoring of desert shrubs affected by an oil spill
	Ignat, Timea; De Falco, Natalie; Berger-Tal, Reut; Rachmilevitch, Shimon; Karnieli, Arnon
通讯作者	Karnieli, A (corresponding author), Ben Gurion Univ Negev, Jacob Blaustein Inst Desert Res, Sede Boker Campus, IL-84990 Negev, Israel.
来源期刊	ENVIRONMENTAL POLLUTION
ISSN	0269-7491
EISSN	1873-6424
出版年	2021
卷号	289
英文摘要	Crude oil pollution is a global environmental concern since it persists in the environment longer than most conventional carbon sources. In December 2014, the hyper-arid Evrona Nature Reserve, Israel, experienced large-scale contamination when crude oil spilled. The overarching goal of the study was to investigate the possible changes, caused by an accidental crude oil spill, in the leaf reflectance and biochemical composition of four natural habitat desert shrubs. The specific objectives were (1) to monitor the biochemical properties of dominant shrub species in the polluted and control areas; (2) to study the long-term consequences of the contamination; (3) to provide information that will assist in planning rehabilitation actions; and (4) to explore the feasibility of vegetation indices (VIs), along with the machine learning (ML) technique, for detecting stressed shrubs based on the full spectral range. Four measurement campaigns were conducted in 2018 and 2019. Along with the various stress indicators, field spectral measurements were performed in the range of 350-2500 nm. A regression analysis to examine the relation of leaf reflectance to biochemical contents was carried out, to reveal the relevant wavelengths in which polluted and control plants differ. Vegetation indices applied in previous studies were found to be less sensitive for indirect detection of long-term oil contamination. A novel spectral index, based on indicative spectral bands, named the normalized blue-green stress index (NBGSI), was established. The NBGSI distinguished significantly between shrubs located in the polluted and in the control areas. The NBGSI showed a strong linear correlation with pheophytin a. Machine learning classification algorithms obtained high overall prediction accuracy in distinguishing between shrubs located in the oil-polluted and the control sites, indicating internal component differences. The findings of this study demonstrate the efficacy of indirect and non-destructive spectral tools for detecting and monitoring oil pollution stress in shrubs.
英文关键词	Spectroscopy Vegetation stress Arid ecosystem Environmental pollution Machine learning
类型	Article
语种	英语
收录类别	SCI-E
WOS记录号	WOS:000696798500006
WOS关键词	MACHINE LEARNING ALGORITHMS ; NONDESTRUCTIVE ESTIMATION ; PHOTOSYNTHETIC CAPACITY ; PLANT STRESS ; HEAVY-METALS ; REFLECTANCE ; PHYTOREMEDIATION ; POLLUTION ; RESPONSES ; GROWTH
WOS类目	Environmental Sciences
WOS研究方向	Environmental Sciences & Ecology
来源机构	Ben-Gurion University of the Negev
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/363139
作者单位	[Ignat, Timea; De Falco, Natalie; Berger-Tal, Reut; Rachmilevitch, Shimon; Karnieli, Arnon] Ben Gurion Univ Negev, Jacob Blaustein Inst Desert Res, French Associates Inst Agr & Biotechnol Drylands, Negev, Israel
推荐引用方式 GB/T 7714	Ignat, Timea,De Falco, Natalie,Berger-Tal, Reut,et al. A novel approach for long-term spectral monitoring of desert shrubs affected by an oil spill[J]. Ben-Gurion University of the Negev,2021,289.
APA	Ignat, Timea,De Falco, Natalie,Berger-Tal, Reut,Rachmilevitch, Shimon,&Karnieli, Arnon.(2021).A novel approach for long-term spectral monitoring of desert shrubs affected by an oil spill.ENVIRONMENTAL POLLUTION,289.
MLA	Ignat, Timea,et al."A novel approach for long-term spectral monitoring of desert shrubs affected by an oil spill".ENVIRONMENTAL POLLUTION 289(2021).