Dehydration-induced changes in spectral reflectance indices and chlorophyll fluorescence of Antarctic lichens with different thallus color, and intrathalline photobiont

Barták, Miloš; Hájek, Josef; Morkusová, Jana; Skácelová, Kateřina; Alica, Košuthová

doi:10.1007/s11738-018-2751-3

Cited by 27 publications

(12 citation statements)

References 88 publications

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“…Intra-and inter-annual variability in spectral signatures might be attributed to short-term variations in their distribution (biological mats especially), their hydration status and photosynthetic activity in response to hydration. Numeric value of particular spectral reflectance indices in poikilohydric mosses and lichens are dependent on their hydration status as shown earlier in laboratory studies (Barták et al 2018). In the field Antarctic studies, the measurements of lichen thallus and/or moss cushion hydration status, however, meet some difficulties due to technical problems with installations of sensors into a moss and/or lichen thalli.…”

Section: Resultsmentioning

confidence: 56%

“…Field measure-ments of reflectance indices were done in spots dominated by differently coloured lichen species for these boulders. Even though for lichens, numeric values are hydration status-dependent (Singh et al 2013, Barták et al 2018, indices showed lichen species specificity according to thallus colour (Table 3).…”

Section: Ndvi Msr CI Greenmentioning

confidence: 99%

“…Among them, the Normalized Difference Vegetation Index (NDVI) has been applied to characterize different types of vegetation types forming vegetation cover and their vigour. However, in the ecosystems with partial or full absence of vascular plants, NDVI evaluation is rather complicated because of species-specific optical properties and spectral signature of mosses, lichens (Barták et al 2018) and cyanobacteria. However, Casanovas et al (2015) compared NDVI and matched filtering approaches for mapping lichens in Antarctica.…”

Section: Introductionmentioning

confidence: 99%

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Spectral properties of Antarctic and Alpine vegetation monitored by multispectral camera: Case studies from James Ross Island and Jeseníky Mts.

Váczi¹,

Barták²,

Bednaříková³

et al. 2020

Czech Polar Rep.

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In this study, we investigated the utility of spectral remote sensing data gathered by a multispectral camera for estimating of vegetation cover in Antarctic vegetation oasis and Arcto-Alpine tundra. The surveys exploiting unmanned aerial vehicles (UAV) and multispectral camera were done in an Antarctic vegetation oasis located at the Northern shore of James Ross Island (Antarctica), and arcto-alpine tundra located in the Jeseníky Mts. (NE Czech Republic, 1 420 m a.s.l.). For the two locations, false colour images of spectral indices (VARI, NGRDI, GLI, RGVI, ExG, NDVI, PRI) were taken and analysis of vegetation types and components of vegetation cover done. Additionally, field research was performed by handheld instruments measuring NDVI, PRI and of selected vegetation components: Bryum pseudotriquetrum, Nostoc commune colonies (Antarctica), lichens grown on flat stones and boulders (the Jeseníky Mts.). The results show UAV photo surveys and imaging of spectral reflectance indices can be used to monitor vegetation types forming Antarctic vegetation oases and arcto-alpine tundra.

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Section: Resultsmentioning

confidence: 56%

Section: Ndvi Msr CI Greenmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Spectral properties of Antarctic and Alpine vegetation monitored by multispectral camera: Case studies from James Ross Island and Jeseníky Mts.

Váczi¹,

Barták²,

Bednaříková³

et al. 2020

Czech Polar Rep.

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“…& Forssell. According to Miloš et al (2018), NDVI variation related to thallus water content is speciesspecific, such as the positive correlation noticeable in Physconia muscigena (Ach.) Poelt, while in R. elegans, the NDVI showed constant values for different thallus water contents.…”

Section: Discussionmentioning

confidence: 99%

“…These differences were used to calculate the NDVI as follows: NDVI = ((NIR 740 -VIS 660 )/(NIR 740 + VIS 660 )). VIS and NIR are the spectral reflectance measurements acquired respectively in the visible and near-infrared regions (Miloš et al, 2018).…”

Section: Photosynthetic Efficiencymentioning

confidence: 99%

Survival of Xanthoria parietina in simulated space conditions: vitality assessment and spectroscopic analysis

Lorenz

Bianchi

Benesperi

et al. 2022

International Journal of Astrobiology

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Xanthoria parietina is a widespread foliose lichen growing on barks and rocks showing a broad spectrum of tolerance to air pollutants such as NOX and heavy metals, and resistance to UV-radiation because of the screening properties provided by the secondary metabolite parietin. The aim of this study was to evaluate the ability of this lichen species to survive in the following simulated space conditions, UV-radiation in N2 atmosphere and UV-radiation in vacuum. The efficiency of the photosynthetic apparatus was used as an indicator of vitality, and was expressed in terms of chlorophyll a fluorescence (FV/FM) and Normalized Difference Vegetation Index (NDVI), which were measured within 72 h from the exposure. Additionally, during the irradiation, the IR reflectance spectrum of the lichen was monitored in situ to assess changes in spectral bands. The results showed significant differences in physiological recovery trends between the treatments, highlighting that UV-radiation in vacuum causes stronger effects on FV/FM values. The IR analysis revealed several spectral band changes in the fingerprint region. The most visible variation was the 5200 cm−1 water band that disappeared in the overtone region. Nevertheless, X. parietina was able to survive UV-radiation in N2 atmosphere and in vacuum, and for this reason it may be considered a candidate for further evaluations on its survival capacity in extreme conditions.

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Remote sensing and spectroscopy of lichens

Rautiainen,

Kuusinen,

Majasalmi

2024

Ecology and Evolution

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Lichens are combinations of two symbiotic organisms, a green alga or cyanobacterium and a fungus. They grow in nearly all terrestrial ecosystems and survive in habitats, which are very dry or cold, or too poor in nutrients to maintain vegetation growth. Because lichens grow on visible surfaces and exhibit spectral properties, which are clearly different from, for example, vegetation, it is possible to distinguish them in remote sensing data. In this first systematic review article on remote sensing of lichens, we analyze and summarize which lichen species or genera, and in which habitats and geographical regions, have been remotely sensed, and which remote sensing or spectroscopic technologies have been used. We found that laboratory or in situ measured spectra of over 70 lichen species have been reported to date. We show that studies on remote sensing of lichens fall under seven broad themes: (1) collection of lichen spectra for quantification of lichen species or characteristics, (2) pollution monitoring with lichens as ecological indicators, (3) geological and lithological mapping, (4) desert and dryland monitoring, (5) animal habitat monitoring, (6) land cover or vegetation mapping, and (7) surface energy budget modeling.

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Dehydration-induced changes in spectral reflectance indices and chlorophyll fluorescence of Antarctic lichens with different thallus color, and intrathalline photobiont

Cited by 27 publications

References 88 publications

Spectral properties of Antarctic and Alpine vegetation monitored by multispectral camera: Case studies from James Ross Island and Jeseníky Mts.

Spectral properties of Antarctic and Alpine vegetation monitored by multispectral camera: Case studies from James Ross Island and Jeseníky Mts.

Survival of Xanthoria parietina in simulated space conditions: vitality assessment and spectroscopic analysis

Remote sensing and spectroscopy of lichens

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