scholarly journals Coverage and Rainfall Response of Biological Soil Crusts Using Multi-Temporal Sentinel-2 Data in a Central European Temperate Dry Acid Grassland

2021 ◽  
Vol 13 (16) ◽  
pp. 3093
Author(s):  
Jakob Rieser ◽  
Maik Veste ◽  
Michael Thiel ◽  
Sarah Schönbrodt-Stitt
Keyword(s):  
Biological Soil Crusts ◽  
Classification Model ◽  
Ecosystem Functions ◽  
Temperate Climate ◽  
Higher Plant ◽  
Detection Analysis ◽  
Soil Crusts ◽  
Daily Precipitation Data ◽  
Northeastern Germany ◽  
Sentinel 2

Biological soil crusts (BSCs) are thin microbiological vegetation layers that naturally develop in unfavorable higher plant conditions (i.e., low precipitation rates and high temperatures) in global drylands. They consist of poikilohydric organisms capable of adjusting their metabolic activities depending on the water availability. However, they, and with them, their ecosystem functions, are endangered by climate change and land-use intensification. Remote sensing (RS)-based studies estimated the BSC cover in global drylands through various multispectral indices, and few of them correlated the BSCs’ activity response to rainfall. However, the allocation of BSCs is not limited to drylands only as there are areas beyond where smaller patches have developed under intense human impact and frequent disturbance. Yet, those areas were not addressed in RS-based studies, raising the question of whether the methods developed in extensive drylands can be transferred easily. Our temperate climate study area, the ‘Lieberoser Heide’ in northeastern Germany, is home to the country’s largest BSC-covered area. We applied a Random Forest (RF) classification model incorporating multispectral Sentinel-2 (S2) data, indices derived from them, and topographic information to spatiotemporally map the BSC cover for the first time in Central Europe. We further monitored the BSC response to rainfall events over a period of around five years (June 2015 to end of December 2020). Therefore, we combined datasets of gridded NDVI as a measure of photosynthetic activity with daily precipitation data and conducted a change detection analysis. With an overall accuracy of 98.9%, our classification proved satisfactory. Detected changes in BSC activity between dry and wet conditions were found to be significant. Our study emphasizes a high transferability of established methods from extensive drylands to BSC-covered areas in the temperate climate. Therefore, we consider our study to provide essential impulses so that RS-based biocrust mapping in the future will be applied beyond the global drylands.

scholarly journals Biological soil crusts on initial soils: organic carbon dynamics and chemistry under temperate climatic conditions

2013 ◽  
Vol 10 (1) ◽  
pp. 851-894 ◽  
Author(s):  
A. Dümig ◽  
M. Veste ◽  
F. Hagedorn ◽  
T. Fischer ◽  
P. Lange ◽  
...  
Keyword(s):  
Chemical Composition ◽  
Organic Carbon ◽  
Sand Dune ◽  
Extracellular Polymeric Substances ◽  
Water Solubility ◽  
Biological Soil Crusts ◽  
Temperate Climate ◽  
Natural Sand ◽  
Soil Crusts ◽  
Northeastern Germany

Abstract. Numerous studies have been carried out on the community structure and diversity of biological soil crusts (BSCs) as well as their important functions on ecosystem processes. However, the amount of BSC-derived organic carbon (OC) input into soils and its chemical composition under natural conditions has rarely been investigated. In this study, different development stages of algae- and moss-dominated BSCs were investigated on a~natural (<17 yr old BSCs) and experimental sand dune (<4 yr old BSCs) in northeastern Germany. We determined the OC accumulation in BSC-layers and the BSC-derived OC input into the underlying substrates for bulk materials and fractions <63 μm. The chemical composition of OC was characterized by applying solid-state 13C NMR spectroscopy and analysis of the carbohydrate-C signature.14C contents were used to assess the origin and dynamic of OC in BSCs and underlying substrates. Our results indicated a rapid BSC establishment and development from algae- to moss-dominated BSCs within only 4 yr under this temperate climate. The distribution of BSC types was presumably controlled by the surface stability according to the position in the slope. We found no evidence that soil properties influenced the BSC distribution on both sand dunes. 14C contents clearly indicated the existence of two OC pools in BSCs and substrates, recent BSC-derived OC and lignite-derived "old" OC (biologically refractory). The input of recent BSC-derived OC strongly decreased the mean residence time of total OC. The downward translocation of OC into the underlying substrates was only found for moss-dominated BSCs at the natural sand dune which may accelerate soil formation at these spots. BSC-derived OC mainly comprised O-alkyl C (carbohydrate-C) and to a lesser extent also alkyl C and N-alkyl C in varying compositions. Accumulation of alkyl C was only detected in BSCs at the experimental dune which may induce a~lower water solubility of BSC-derived extracellular polymeric substances when compared to BSCs at the natural sand dune indicating that hydrological effects of BSCs on soils depend on the chemical composition of the extracellular polymeric substances.

scholarly journals Infiltration and water retention of biological soil crusts on reclaimed soils of former open-cast lignite mining sites in Brandenburg, north-east Germany

2016 ◽  
Vol 64 (1) ◽  
pp. 1-11 ◽  
Author(s):  
Stella Gypser ◽  
Maik Veste ◽  
Thomas Fischer ◽  
Philipp Lange
Keyword(s):  
Green Algae ◽  
Water Retention ◽  
Biological Soil Crusts ◽  
Water Holding Capacity ◽  
Temperate Climate ◽  
Lignite Mining ◽  
Mining Sites ◽  
Soil Crusts ◽  
Water Holding ◽  
Open Cast

AbstractInvestigations were done on two former open-cast lignite mining sites under reclamation, an artificial sand dune in Welzow Süd, and a forest plantation in Schlabendorf Süd (Brandenburg, Germany). The aim was to associate the topsoil hydrological characteristics of green algae dominated as well as moss and soil lichen dominated biological soil crusts during crustal succession with their water retention and the repellency index on sandy soils under temperate climate and different reliefs.The investigation of the repellency index showed on the one hand an increase due to the cross-linking of sand particles by green algae which resulted in clogging of pores. On the other hand, the occurrence of moss plants led to a decrease of the repellency index due to absorption caused by bryophytes. The determination of the water retention curves showed an increase of the water holding capacity, especially in conjunction with the growth of green algae layer. The pore-related van Genuchten parameter indicate a clay-like behaviour of the developed soil crusts. Because of the inhomogeneous distribution of lichens and mosses as well as the varying thickness of green algae layers, the water retention differed between the study sites and between samples of similar developmental stages. However, similar tendencies of water retention and water repellency related to the soil crust formation were observed.Biological soil crusts should be considered after disturbances in the context of reclamation measures, because the initial development of green algae biocrusts lead to an increasing repellency index, while the occurrence of mosses and a gain in organic matter enhance the water holding capacity. Thus, the succession of biocrusts and their small-scale succession promote the development of soil and ecosystem.

scholarly journals Rapidly restoring biological soil crusts and ecosystem functions in a severely disturbed desert ecosystem

2016 ◽  
Vol 26 (4) ◽  
pp. 1260-1272 ◽  
Author(s):  
Lindsay P. Chiquoine ◽  
Scott R. Abella ◽  
Matthew A. Bowker
Keyword(s):  
Biological Soil Crusts ◽  
Desert Ecosystem ◽  
Ecosystem Functions ◽  
Soil Crusts

scholarly journals A New Application of Random Forest Algorithm to Estimate Coverage of Moss-Dominated Biological Soil Crusts in Semi-Arid Mu Us Sandy Land, China

2019 ◽  
Vol 11 (11) ◽  
pp. 1286 ◽  
Author(s):  
Xiang Chen ◽  
Tao Wang ◽  
Shulin Liu ◽  
Fei Peng ◽  
Atsushi Tsunekawa ◽  
...  
Keyword(s):  
Random Forest ◽  
Biological Soil Crusts ◽  
Data Availability ◽  
Sandy Land ◽  
Desert Ecosystems ◽  
Mu Us Sandy Land ◽  
Soil Crusts ◽  
Band Combinations ◽  
Semi Arid ◽  
Sentinel 2

Biological soil crusts (BSCs) play an essential role in desert ecosystems. Knowledge of the distribution and disappearance of BSCs is vital for the management of ecosystems and for desertification researches. However, the major remote sensing approaches used to extract BSCs are multispectral indices, which lack accuracy, and hyperspectral indices, which have lower data availability and require a higher computational effort. This study employs random forest (RF) models to optimize the extraction of BSCs using band combinations similar to the two multispectral BSC indices (Crust Index-CI; Biological Soil Crust Index-BSCI), but covering all possible band combinations. Simulated multispectral datasets resampled from in-situ hyperspectral data were used to extract BSC information. Multispectral datasets (Landsat-8 and Sentinel-2 datasets) were then used to detect BSC coverage in Mu Us Sandy Land, located in northern China, where BSCs dominated by moss are widely distributed. The results show that (i) the spectral curves of moss-dominated BSCs are different from those of other typical land surfaces, (ii) the BSC coverage can be predicted using the simulated multispectral data (mean square error (MSE) < 0.01), (iii) Sentinel-2 satellite datasets with CI-based band combinations provided a reliable RF model for detecting moss-dominated BSCs (10-fold validation, R2 = 0.947; ground validation, R2 = 0.906). In conclusion, application of the RF algorithm to the Sentinel-2 dataset can precisely and effectively map BSCs dominated by moss. This new application can be used as a theoretical basis for detecting BSCs in other arid and semi-arid lands within desert ecosystems.

Biological soil crusts in continental Antarctica: Garwood Valley, southern Victoria Land, and Diamond Hill, Darwin Mountains region

2013 ◽  
Vol 26 (2) ◽  
pp. 115-123 ◽  
Author(s):  
Claudia Colesie ◽  
Maxime Gommeaux ◽  
T.G. Allan Green ◽  
Burkhard Büdel
Keyword(s):  
Soil Stabilization ◽  
Higher Plants ◽  
Biological Soil Crusts ◽  
Ecosystem Functions ◽  
Dry Valleys ◽  
Cold Desert ◽  
Chlorophyll Contents ◽  
Green Algal ◽  
Soil Crusts ◽  
Continental Antarctica

AbstractBiological soil crusts are associations of lichens, mosses, algae, cyanobacteria, microfungi and bacteria in different proportions forming a thin veneer within the top centimetres of soil surfaces. They occur in all biomes, but particularly in arid and semi-arid regions, even in the most extreme climates. They carry out crucial ecosystem functions, such as soil stabilization, influencing water and nutrient cycles, and contribute to the formation of microniches for heterotrophic life. In continental Antarctica especially, these roles are essential because no higher plants provide such ecosystem services. We provide a detailed description of biological soil crusts from Garwood Valley, McMurdo Dry Valleys region (78°S) and Diamond Hill (80°S) in the Darwin Mountains region. The coverage was low at 3.3% and 0.8% of the soil surface. At Garwood Valley the crusts were composed of green algal lichens, cyanobacteria, several species of green algae and the mossHennediella heimii(Hedw.) R.H. Zander. Diamond Hill crusts appear to be unique in not having any species of cyanobacteria. Major parts are embedded in the soil, and their thickness correlates with higher chlorophyll contents, higher soil organic carbon and nitrogen, which are fundamental components of this species poor cold desert zone.

Proglacial succession of biological soil crusts and vascular plants: biotic interactions in the High Arctic

2006 ◽  
Vol 84 (11) ◽  
pp. 1714-1731 ◽  
Author(s):  
Katie Breen ◽  
Esther Lévesque
Keyword(s):  
Vascular Plants ◽  
Biotic Interactions ◽  
Distribution Patterns ◽  
High Arctic ◽  
Biological Soil Crusts ◽  
Vegetation Density ◽  
Higher Plant ◽  
Soil Crusts ◽  
Glacier Foreland ◽  
Plant Densities

To evaluate the hypothesis that biological soil crusts facilitate the establishment and maintenance of vascular plants during succession, we studied the distribution patterns of crusts and vascular plants along a High Arctic glacier foreland and compared the success of plants growing in and out of crusted substrate. Multivariate analyses determined that distance from the glacier and crust cover were the most important variables, explaining 11% and 9% of the variance in the vegetation data, respectively. Surfaces colonized by biological soil crusts generally supported higher plant densities and showed positive associations with the most dominant, long-lived plant species such as Saxifraga oppositifolia L., Salix arctica Pall., and Dryas integrifolia Vahl. Crusts facilitate plant establishment and growth in early and midsuccession but may compete for available resources further along the chronosequence. This study recognizes subtle direct influences of crust on vegetation density but also draws attention to a much larger overall positive effect on community structure. Succession on this foreland proceeds via a “directional-replacement” model and supports a well-developed community of biological soil crusts and vascular plants with greater species richness, cover, and density compared with other glacier foreland vegetation communities previously investigated on Ellesmere Island, Nunavut.

Discussion on wind factor influencing the distribution of biological soil crusts on surface of sand dunes

2013 ◽  
Vol 5 (6) ◽  
pp. 739
Author(s):  
Wu YongSheng ◽  
Erdun Hasi ◽  
Yin RuiPing ◽  
Zhang Xin ◽  
Ren Jie ◽  
...  
Keyword(s):  
Sand Dunes ◽  
Biological Soil Crusts ◽  
Soil Crusts

scholarly journals Evaluating the Potentiality of Sentinel-2 for Change Detection Analysis Associated to LULUCF in Wallonia, Belgium

Land ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 55
Author(s):  
Odile Close ◽  
Sophie Petit ◽  
Benjamin Beaumont ◽  
Eric Hallot
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Change Detection ◽  
Signal To Noise Ratio ◽  
Land Conversion ◽  
Sustainable Resources ◽  
Detection Techniques ◽  
Detection Analysis ◽  
Conversion Rates ◽  
Sentinel 2

Land Use/Cover changes are crucial for the use of sustainable resources and the delivery of ecosystem services. They play an important contribution in the climate change mitigation due to their ability to emit and remove greenhouse gas from the atmosphere. These emissions/removals are subject to an inventory which must be reported annually under the United Nations Framework Convention on Climate Change. This study investigates the use of Sentinel-2 data for analysing lands conversion associated to Land Use, Land Use Change and Forestry sector in the Wallonia region (southern Belgium). This region is characterized by one of the lowest conversion rates across European countries, which constitutes a particular challenge in identifying land changes. The proposed research tests the most commonly used change detection techniques on a bi-temporal and multi-temporal set of mosaics of Sentinel-2 data from the years 2016 and 2018. Our results reveal that land conversion is a very rare phenomenon in Wallonia. All the change detection techniques tested have been found to substantially overestimate the changes. In spite of this moderate results our study has demonstrated the potential of Sentinel-2 regarding land conversion. However, in this specific context of very low magnitude of land conversion in Wallonia, change detection techniques appear to be not sufficient to exceed the signal to noise ratio.

scholarly journals Continental-Scale Land Cover Mapping at 10 m Resolution Over Europe (ELC10)

2021 ◽  
Vol 13 (12) ◽  
pp. 2301
Author(s):  
Zander Venter ◽  
Markus Sydenham
Keyword(s):  
Land Cover ◽  
Atmospheric Correction ◽  
Google Earth ◽  
Tree Planting ◽  
Training Data ◽  
Classification Model ◽  
Night Time ◽  
Continental Scale ◽  
Land Cover Maps ◽  
Sentinel 2

Land cover maps are important tools for quantifying the human footprint on the environment and facilitate reporting and accounting to international agreements addressing the Sustainable Development Goals. Widely used European land cover maps such as CORINE (Coordination of Information on the Environment) are produced at medium spatial resolutions (100 m) and rely on diverse data with complex workflows requiring significant institutional capacity. We present a 10 m resolution land cover map (ELC10) of Europe based on a satellite-driven machine learning workflow that is annually updatable. A random forest classification model was trained on 70K ground-truth points from the LUCAS (Land Use/Cover Area Frame Survey) dataset. Within the Google Earth Engine cloud computing environment, the ELC10 map can be generated from approx. 700 TB of Sentinel imagery within approx. 4 days from a single research user account. The map achieved an overall accuracy of 90% across eight land cover classes and could account for statistical unit land cover proportions within 3.9% (R2 = 0.83) of the actual value. These accuracies are higher than that of CORINE (100 m) and other 10 m land cover maps including S2GLC and FROM-GLC10. Spectro-temporal metrics that capture the phenology of land cover classes were most important in producing high mapping accuracies. We found that the atmospheric correction of Sentinel-2 and the speckle filtering of Sentinel-1 imagery had a minimal effect on enhancing the classification accuracy (< 1%). However, combining optical and radar imagery increased accuracy by 3% compared to Sentinel-2 alone and by 10% compared to Sentinel-1 alone. The addition of auxiliary data (terrain, climate and night-time lights) increased accuracy by an additional 2%. By using the centroid pixels from the LUCAS Copernicus module polygons we increased accuracy by <1%, revealing that random forests are robust against contaminated training data. Furthermore, the model requires very little training data to achieve moderate accuracies—the difference between 5K and 50K LUCAS points is only 3% (86 vs. 89%). This implies that significantly less resources are necessary for making in situ survey data (such as LUCAS) suitable for satellite-based land cover classification. At 10 m resolution, the ELC10 map can distinguish detailed landscape features like hedgerows and gardens, and therefore holds potential for aerial statistics at the city borough level and monitoring property-level environmental interventions (e.g., tree planting). Due to the reliance on purely satellite-based input data, the ELC10 map can be continuously updated independent of any country-specific geographic datasets.

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