Abstract. Various studies have been performed to quantify silicon (Si) stocks in plant biomass and related Si fluxes in terrestrial biogeosystems. Most of these studies were performed at relatively small plots with an intended low heterogeneity in soils and plant canopy composition, and results were extrapolated to larger spatial units up to global scale implicitly assuming similar environmental conditions. However, the emergence of new technical features and increasing knowledge on details in Si cycling leads to a more complex picture at landscape or catchment scales. Dynamic and static soil properties change along the soil continuum and might influence not only the species composition of natural vegetation, but its biomass distribution and related Si stocks. Maximum Likelihood (ML) classification was applied to multispectral imagery captured by an Unmanned Aerial System (UAS) aiming the identification of land cover classes (LCC). 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 (Calamagrostis epigejos and Phragmites australis) in a heterogeneous catchment and related corresponding spatial patterns of these stocks to soil properties. We found aboveground Si stocks of C. epigejos and P. australis to be surprisingly high (maxima of Si stocks reach values up to 98 g Si m⁻²), 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.

中文翻译：

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以草为主的流域地上植物源性硅储量的空间格局–基于UAS的高分辨率遥感的结果

摘要。已经进行了各种研究来量化植物生物量中的硅（Si）储量和陆地生物地球系统中的相关硅通量。这些研究大多数是在相对较小的样地上进行的，预期在土壤和植物冠层成分中具有较低的异质性，并且在假定相似的环境条件下，将结果外推至更大的空间单位，直至全球范围。但是，随着新技术的出现和Si骑行细节知识的增加，导致景观或集水区尺度的情况更加复杂。土壤的动态和静态特性沿土壤连续性变化，不仅会影响自然植被的物种组成，而且会影响其生物量分布和相关的硅储量。最大似然（ML）分类应用于无人航空系统（UAS）捕获的多光谱图像，旨在识别土地覆被类别（LCC）。随后，使用归一化植被指数（NDVI）和基于地面的生物量测量法来量化两个硅富集植物中地上硅的储量（异质集水区中的Calamagrostis epigejos和Phragmites australis）以及这些种群与土壤特性相关的相应空间格局。我们发现C. epigejos和P. australis的地上硅储量惊人地高（硅储量的最大值达到了高达98 g Si m ^-2的值），即与各种陆地生态系统的地上植被中的Si储量可比或显着超过报告的值。我们进一步发现了地上植物硅储量的空间格局，以反映土壤特性的空间异质性。根据我们的结果，我们得出以下结论：（i）植物的地上生物量似乎是相应植物硅储量的主要因素，并且（ii）通过基于UAS的遥感检测生物量异质性代表了一种有生命力的植物化定量分析的有前途的工具硅池在景观尺度上。