Variation of albedo to soil moisture for sand dunes and biological soil crusts in arid desert ecosystems

The species composition of algae from biological soil crusts (biocrusts) on the surface of sand dunes (Black Sea coast, Primorske, Izmail District, Odesa Region, Ukraine) was investigated. Samples were collected from three coastal localities: Katranivska Spit, Zhebryianska Bay and Zhebryianska Ridge. The latter two localities are in the territory of the Danube Delta Biosphere Reserve. The samples were investigated by direct microscopy, followed by a culture approach. 60 species from Chlorophyta (32), Cyanobacteria (16), Streptophyta (7) and Ochrophyta (5) were identified. Representatives of the cyanobacterial genera Microcoleus Desmazières ex Gomont, Coleofasciculus M.Siegesmund, J.R.Johansen & T.Friedl, Nostoc Vaucher ex Bornet & Flahault, Hassallia Berkeley ex Bornet & Flahault, and streptophytes from the genus Klebsormidium P.C.Silva, Mattox & W.H.Blackwell dominated in the studied biocrusts. Phylogenetic analyses based on 16S/18S rRNA as well as 16S-23S ITS/ITS-1,2 regions were undertaken for some strains of cyanobacteria and eukaryotic algae. As a result, species identification and their position in respective phylogeny was refined, as well as aiding the discovery of some interesting and rare species. New genera and species were described (Streptosarcina arenaria Mikhailyuk & Lukešová and Tetradesmus arenicola Mikhailyuk & P.Tsarenko); with two genera (Nodosilinea R.B.Perkerson & D.A.Casamatta and Pleurastrosarcina H.J.Sluiman & P.C.J.Blommers) and four species reported for the first time for the flora of Ukraine (Nodosilinea epilithica Perkerson & Casamatta, Pseudomuriella aurantiaca (W.Vischer) N.Hanagata, Pleurochloris meiringensis Vischer, Pleurastrosarcina terriformae Darienko, W.J.Kang, Orzechowski & Pröschold). Comparison of the results from this study with similar investigations at Cape Kazantip (Sea of Azov, Ukraine) and at two islands of the Baltic Sea (Rügen, Usedom, Germany) revealed that sand composition and texture, as well as climate type of the respective region, are the main factors determining species composition of algae and cyanobacteria in biocrusts of maritime dunes.

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Biological soil crusts enhance the recovery of nutrient levels of surface dune soil in arid desert regions

Ecological Indicators ◽

10.1016/j.ecolind.2019.105497 ◽

2019 ◽

Vol 106 ◽

pp. 105497 ◽

Cited By ~ 4

Author(s):

Mingzhu He ◽

Rui Hu ◽

Rongliang Jia

Keyword(s):

Biological Soil Crusts ◽

Nutrient Levels ◽

Soil Crusts ◽

Desert Regions ◽

Arid Desert ◽

Dune Soil

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Desert shrub stemflow and its significance in soil moisture replenishment

Hydrology and Earth System Sciences ◽

10.5194/hess-15-561-2011 ◽

2011 ◽

Vol 15 (2) ◽

pp. 561-567 ◽

Cited By ~ 49

Author(s):

X.-P. Wang ◽

Z.-N. Wang ◽

R. Berndtsson ◽

Y.-F. Zhang ◽

Y.-X. Pan

Keyword(s):

Soil Moisture ◽

Soil Profile ◽

Root Zone ◽

Sand Dunes ◽

Aluminum Foil ◽

Time Domain Reflectometry ◽

Desert Ecosystem ◽

Desert Ecosystems ◽

Caragana Korshinskii ◽

Moisture Variation

Abstract. Stemflow of xerophytic shrubs represents a significant component of water replenishment to the soil-root system influencing water utilization of plant roots at the stand scale, especially in water scarce desert ecosystems. In this study, stemflow of Caragana korshinskii was quantified by an aluminum foil collar collection method on re-vegetated sand dunes of the Shapotou restored desert ecosystem in northwestern China. Time domain reflectometry probes were inserted horizontally at 20 different soil profile depths under the C. korshinskii shrub to monitor soil moisture variation at hourly intervals. Results indicated that 2.2 mm precipitation was necessary for the generation of stemflow for C. korshinskii. Stemflow averaged 8% of the gross precipitation and the average funnelling ratio was as high as 90. The soil moisture in the uppermost soil profile was strongly correlated with individual rainfall and the stemflow strengthened this relationship. Therefore, it is favourable for the infiltrated water redistribution in the deeper soil profile of the root zone. Consequently, stemflow contributes significantly to a positive soil moisture balance in the root zone and the replenishment of soil moisture at deeper soil layers. This plays an important role in plant survival and the general ecology of arid desert environments.

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

Remote Sensing ◽

10.3390/rs11111286 ◽

2019 ◽

Vol 11 (11) ◽

pp. 1286 ◽

Cited By ~ 3

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.

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