Spatial patterns of aboveground phytogenic Si stocks in a grass-dominated catchment – results from UAS-based high-resolution remote sensing

<p>Various studies have been performed to quantify silicon (Si) stocks in plant biomass and related Si fluxes in terrestrial biogeosystems. Most studies are deliberately designed on the plot scale to ensure low heterogeneity in soils and plant composition, hence similar environmental condition...

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Main Authors: M. Wehrhan, D. Puppe, D. Kaczorek, M. Sommer
Format: Article
Language:English
Published: Copernicus Publications 2021-09-01
Series:Biogeosciences
Online Access:https://bg.copernicus.org/articles/18/5163/2021/bg-18-5163-2021.pdf
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spelling doaj-def726d7fba346cbbb9921b98ff2505a2021-09-22T06:02:23ZengCopernicus PublicationsBiogeosciences1726-41701726-41892021-09-01185163518310.5194/bg-18-5163-2021Spatial patterns of aboveground phytogenic Si stocks in a grass-dominated catchment – results from UAS-based high-resolution remote sensingM. Wehrhan0D. Puppe1D. Kaczorek2D. Kaczorek3M. Sommer4M. Sommer5M. Sommer6Leibniz Centre for Agricultural Landscape Research (ZALF), “Landscape Pedology” Working Group, 15374 Müncheberg, GermanyLeibniz Centre for Agricultural Landscape Research (ZALF), “Silicon Biogeochemistry” Working Group, 15374 Müncheberg, GermanyLeibniz Centre for Agricultural Landscape Research (ZALF), “Landscape Pedology” Working Group, 15374 Müncheberg, GermanyDepartment of Soil Environment Sciences, Warsaw University of Life Sciences (SGGW), 02-776 Warsaw, PolandLeibniz Centre for Agricultural Landscape Research (ZALF), “Landscape Pedology” Working Group, 15374 Müncheberg, GermanyLeibniz Centre for Agricultural Landscape Research (ZALF), “Silicon Biogeochemistry” Working Group, 15374 Müncheberg, GermanyInstitute of Geography and Environmental Science, University of Potsdam, 14476 Potsdam, Germany<p>Various studies have been performed to quantify silicon (Si) stocks in plant biomass and related Si fluxes in terrestrial biogeosystems. Most studies are deliberately designed on the plot scale to ensure low heterogeneity in soils and plant composition, hence similar environmental conditions. Due to the immanent spatial soil variability, the transferability of results to larger areas, such as catchments, is therefore limited. However, the emergence of new technical features and increasing knowledge on details in Si cycling lead to a more complex picture at landscape and catchment scales. Dynamic and static soil properties change along the soil continuum and might influence not only the species composition of natural vegetation but also its biomass distribution and related Si stocks. Maximum likelihood (ML) classification was applied to multispectral imagery captured by an unmanned aerial system (UAS) aiming at the identification of land cover classes (LCCs). Subsequently, the normalized difference vegetation index (NDVI) and ground-based measurements of biomass were used to quantify aboveground Si stocks in two Si-accumulating plants (<i>Calamagrostis epigejos</i> and <i>Phragmites australis</i>) in a heterogeneous catchment and related corresponding spatial patterns of these stocks to soil properties. We found aboveground Si stocks of <i>C. epigejos</i> and <i>P. australis</i> to be surprisingly high (maxima of Si stocks reach values up to 98 <span class="inline-formula">g Si m<sup>−2</sup></span>), i.e. comparable to or markedly exceeding reported values for the Si storage in aboveground vegetation of various terrestrial ecosystems. We further found spatial patterns of plant aboveground Si stocks to reflect spatial heterogeneities in soil properties. From our results, we concluded that (i) aboveground biomass of plants seems to be the main factor of corresponding phytogenic Si stock quantities, and (ii) a detection of biomass heterogeneities via UAS-based remote sensing represents a promising tool for the quantification of lifelike phytogenic Si pools at landscape scales.</p>https://bg.copernicus.org/articles/18/5163/2021/bg-18-5163-2021.pdf
collection DOAJ
language English
format Article
sources DOAJ
author M. Wehrhan
D. Puppe
D. Kaczorek
D. Kaczorek
M. Sommer
M. Sommer
M. Sommer
spellingShingle M. Wehrhan
D. Puppe
D. Kaczorek
D. Kaczorek
M. Sommer
M. Sommer
M. Sommer
Spatial patterns of aboveground phytogenic Si stocks in a grass-dominated catchment – results from UAS-based high-resolution remote sensing
Biogeosciences
author_facet M. Wehrhan
D. Puppe
D. Kaczorek
D. Kaczorek
M. Sommer
M. Sommer
M. Sommer
author_sort M. Wehrhan
title Spatial patterns of aboveground phytogenic Si stocks in a grass-dominated catchment – results from UAS-based high-resolution remote sensing
title_short Spatial patterns of aboveground phytogenic Si stocks in a grass-dominated catchment – results from UAS-based high-resolution remote sensing
title_full Spatial patterns of aboveground phytogenic Si stocks in a grass-dominated catchment – results from UAS-based high-resolution remote sensing
title_fullStr Spatial patterns of aboveground phytogenic Si stocks in a grass-dominated catchment – results from UAS-based high-resolution remote sensing
title_full_unstemmed Spatial patterns of aboveground phytogenic Si stocks in a grass-dominated catchment – results from UAS-based high-resolution remote sensing
title_sort spatial patterns of aboveground phytogenic si stocks in a grass-dominated catchment – results from uas-based high-resolution remote sensing
publisher Copernicus Publications
series Biogeosciences
issn 1726-4170
1726-4189
publishDate 2021-09-01
description <p>Various studies have been performed to quantify silicon (Si) stocks in plant biomass and related Si fluxes in terrestrial biogeosystems. Most studies are deliberately designed on the plot scale to ensure low heterogeneity in soils and plant composition, hence similar environmental conditions. Due to the immanent spatial soil variability, the transferability of results to larger areas, such as catchments, is therefore limited. However, the emergence of new technical features and increasing knowledge on details in Si cycling lead to a more complex picture at landscape and catchment scales. Dynamic and static soil properties change along the soil continuum and might influence not only the species composition of natural vegetation but also its biomass distribution and related Si stocks. Maximum likelihood (ML) classification was applied to multispectral imagery captured by an unmanned aerial system (UAS) aiming at the identification of land cover classes (LCCs). Subsequently, the normalized difference vegetation index (NDVI) and ground-based measurements of biomass were used to quantify aboveground Si stocks in two Si-accumulating plants (<i>Calamagrostis epigejos</i> and <i>Phragmites australis</i>) in a heterogeneous catchment and related corresponding spatial patterns of these stocks to soil properties. We found aboveground Si stocks of <i>C. epigejos</i> and <i>P. australis</i> to be surprisingly high (maxima of Si stocks reach values up to 98 <span class="inline-formula">g Si m<sup>−2</sup></span>), i.e. comparable to or markedly exceeding reported values for the Si storage in aboveground vegetation of various terrestrial ecosystems. We further found spatial patterns of plant aboveground Si stocks to reflect spatial heterogeneities in soil properties. From our results, we concluded that (i) aboveground biomass of plants seems to be the main factor of corresponding phytogenic Si stock quantities, and (ii) a detection of biomass heterogeneities via UAS-based remote sensing represents a promising tool for the quantification of lifelike phytogenic Si pools at landscape scales.</p>
url https://bg.copernicus.org/articles/18/5163/2021/bg-18-5163-2021.pdf
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