We evaluated the fungal diversity associated with carbonate veins and two types of salt encrustation in rocks in a polar desert region of continental Antarctica using DNA a metabarcoding approach. We ...detected 262,268 reads grouped into 517 amplicon sequence variants (ASVs) assigned to the phyla
Ascomycota
,
Basidiomycota
,
Mortierellomycota
and
Mucoromycota
. Fourteen ASVs belonging to the genera
Trichosporon
,
Mortierella
,
Penicillium
,
Aspergillus
,
Cladosporium
,
Coprinellus
,
Pleurotus
and
Pseudogymnoascus
were assessed to be dominant taxa. The fungal communities of the three habitats sampled displayed high diversity indices when compared with other habitats of Antarctica, although differing in detail, with the highest diversity indices in the gypsum crust type 2. Only 48 of the 517 ASVs (9.28%) were detected in all three habitats, including dominant, intermediate and minor components. In contrast with previous studies of fungal communities living in the ultra-extreme conditions of continental Antarctica, application of metabarcoding revealed the DNA of a rich and complex resident fungal community. The ASVs detected included fungi with different ecological roles, with xerophilic, human- and animal-associated, phytopathogenic, saprotrophic, mutualistic, psychrotolerant and cosmopolitan taxa. This sequence diversity may be the result of deposition of fungal propagules over time driven by air currents, precipitation or human activities in the region.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
2.
Ornithogenic Gelisols (Cryosols) from Maritime Antarctica Michel, Roberto Ferreira Machado; Schaefer, Carlos Ernesto G. Reynaud; Dias, Luis Eduardo ...
Soil Science Society of America journal,
07/2006, Volume:
70, Issue:
4
Journal Article
Peer reviewed
In terrestrial ecosystems of Maritime Antarctica (King George Island), the transference of primary marine production to the land promoted by penguins (
Pygoscelis adeliae)
and other birds, appears to ...influence soil formation and chemical weathering to a greater extent than formerly predicted. This paper summarizes the results of pedological investigations on the vicinity of the American Pieter J. Lenie Field Station (62°10′ S, 58°28′ W), discussing soil formation processes related to vegetation succession in the studied area. Soil organic matter (SOM) accumulation and associated phosphatization are marked soil‐forming processes in ice‐free areas once colonized by penguins. Also there is a high correlation between soil development and vegetation patterns. Nutrient supply in these cryogenic soils is affected by low pH following nitrification and high contents of P, K, Ca, and Mg due to seabirds' inputs. Lithic Umbriturbels and Glacic Haploturbels are the most common ornithogenic soils, followed by Lithic Fibristels and Psammentic Aquiturbels. In all soils phosphatization and ornithogenesis occurs in varying degrees. However, the recent Gelisols order of Soil Taxonomy does not consider the influence of ornithogenesis or phosphatization in its framework, so that a more detailed classification of such soils is not possible.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Antarctic soils occur in restricted areas, but few integrated studies on soils and landforms have focused in the Antarctic Peninsula. We studied the representative soils of Hope Bay, emphasizing the ...processes of quaternary sedimentation, landforms, soil classification, and distribution. Results show that landforms and soils are closely associated in Hope Bay. Ornithogenic soils are associated with Late Pleistocene to Holocene stable ground moraines; these are currently being destroyed by thermokarst erosion around Lake Boekella. Lithic Haploturbels occur chiefly on shallow rocky terrains whereas Typic Haploturbels are found on patterned ground. In Hope Bay, a much colder climate prevails compared with the South Shetlands, and the widespread permafrost close to the surface warrants strong cryoclastic weathering with active and general gelifraction across different lithologies. The shallow occurrence of permafrost in Hope Bay has a strong regulating effect on soils, retarding leaching and soil development processes. Local soils are, in general, shallow and cryoturbic, and the current pedoenvironment on lowland stable areas was subjected to varying phosphatization on previously weathered sedimentary material. The evidence of phosphatization of a formerly larger area appears to be the main driver of pedogenesis at Hope Bay, and nesting activity by penguins on stable surfaces is capable of enhancing weathering and soil formation.
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FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
Distribution ranges of plant species are related to physical variables of ecosystems that limit plant growth. Therefore, each plant species response to physical factors builds up the functional ...diversity of an ecosystem. The higher the species richness of an ecosystem, the larger the probability of maintaining functions and the higher the potential number of plant functional groups (FGs). Thus, the richness potentially increases the number of functions of the highly diverse Atlantic Rainforest domain in Brazil. Severe plant growth limitations caused by stress, however, decrease species richness. In the Spodosols of the Mussununga, an associated ecosystem of Atlantic Rainforest, the percentage of fine sand is directly related to water retention. Moreover, the depth of the cementation layer in the Mussununga's sandy soil is a physical factor that can affect the plants' stress gradients. When a shallow cementation layer depth is combined with low water retention in soils and with low fine sand percentage, the double stresses of flooding in the rainy season and water scarcity in the dry season result. This study aimed to identify FGs among Mussununga plant species responding to water stress gradients of soil and to verify the effects of the gradients on plant species richness of the Mussununga. A canonical correspondence analysis (CCA) of species abundance and soil texture variables was performed on 18 plots in six physiognomies of the Mussununga. Species richness rarefactions were calculated for each vegetation form to compare diversity. The two main axes of the CCA showed two FGs responding to soil texture and cementation layer depth: stress tolerator species and mesic species. Physical variables affect plant diversity, with species richness rising as the fine sand proportion also rises in the Mussununga. The effect of the cementation layer is not significantly related to species richness variation.
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BFBNIB, DOBA, EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, IZUM, KILJ, KISLJ, MFDPS, NLZOH, NMLJ, NUK, OILJ, PILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UILJ, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Here we describe fossil vertebrate remains from a new Solimões Formation (Eocene-Pliocene) locality, near the highway BR 364 at Sena Madureira municipality (Acre, Brazil). The findings comprise more ...than forty-four isolated fragments from which twenty-three specimens could be properly identified anatomically and systematically. The materials include at least three different Caimaninae genera (Caiman, Melanosuchus, and Mourasuchus), two distinct side-necked turtles (Chelus and Podocnemididae) and one mammal (Toxodontidae). The studied fossils could be systematized into two taphonomic classes based on their preservational status, indicating a sinuous fluvial meandering paleoenvironment. This new locality seems to be relevant regarding not only its fossil vertebrate diversity but also because of its geographic position: on a highway side, which allows access at any season of the year, as contrary to most common riverine outcrops from Solimões Formation, which are restricted to collections during the dry seasons.
•New outcrop is described with several fossil vertebrate remains.•Increase of knowledge regarding Solimões Formation in the interfluvial regions.•Rich fossil tetrapod assemblage, presenting turtles, notoungulates, and crocodiles.•Description of the first postcranial Melanosuchus fossil from Solimões Formation.•Fossils systematized in taphonomical classes according to preservational patterns.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Geophysical sensors combined with machine learning
algorithms were used to understand the pedosphere system and landscape
processes and to model soil attributes. In this research, we used parent
...material, terrain attributes, and data from geophysical sensors in different
combinations to test and compare different and novel machine learning
algorithms to model soil attributes. We also analyzed the importance of
pedoenvironmental variables in predictive models. For that, we collected
soil physicochemical and geophysical data (gamma-ray emission from uranium,
thorium, and potassium; magnetic susceptibility and apparent electric
conductivity) by three sensors (gamma-ray spectrometer, RS 230;
susceptibilimeter KT10, Terraplus; and conductivimeter, EM38 Geonics) at
75 points and analyzed the data. The models with the best performance
(R2 0.48, 0.36, 0.44, 0.36, 0.25, and 0.31) varied for clay, sand,
Fe2O3, TiO2, SiO2, and cation exchange capacity
prediction, respectively. Modeling with the selection of covariates at three
phases (variance close to zero, removal by correction, and removal by
importance) was adequate to increase the parsimony. The results were
validated using the method “nested leave-one-out cross-validation”. The
prediction of soil attributes by machine learning algorithms yielded
adequate values for field-collected data, without any sample preparation,
for most of the tested predictors (R2 values ranging from 0.20 to
0.50). Also, the use of four regression algorithms proved to be important
since at least one of the predictors used one of the tested algorithms. The
performance values of the best algorithms for each predictor were higher
than those obtained with the use of a mean value for the entire area
comparing the values of root mean square error (RMSE) and mean absolute
error (MAE). The best combination of sensors that reached the highest model
performance was that of the gamma-ray spectrometer and the
susceptibilimeter. The most important variables for most
predictions were parent material,
digital elevation, standardized height, and magnetic susceptibility. We concluded that soil attributes can be efficiently modeled
by geophysical data using machine learning techniques and geophysical sensor
combinations. This approach can facilitate future soil mapping in a more
time-efficient and environmentally friendly manner.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Ornithogenic Gelisols (Cryosols) from Maritime Antarctica Michel, Roberto Ferreira Machado; Schaefer, Carlos Ernesto G. Reynaud; Dias, Luis Eduardo ...
Soil Science Society of America journal,
July 2006, Volume:
70, Issue:
4
Journal Article
Peer reviewed
In terrestrial ecosystems of Maritime Antarctica (King George Island), the transference of primary marine production to the land promoted by penguins (Pygoscelis adeliae) and other birds, appears to ...influence soil formation and chemical weathering to a greater extent than formerly predicted. This paper summarizes the results of pedological investigations on the vicinity of the American Pieter J. Lenie Field Station (62°10′ S, 58°28′ W), discussing soil formation processes related to vegetation succession in the studied area. Soil organic matter (SOM) accumulation and associated phosphatization are marked soil‐forming processes in ice‐free areas once colonized by penguins. Also there is a high correlation between soil development and vegetation patterns. Nutrient supply in these cryogenic soils is affected by low pH following nitrification and high contents of P, K, Ca, and Mg due to seabirds' inputs. Lithic Umbriturbels and Glacic Haploturbels are the most common ornithogenic soils, followed by Lithic Fibristels and Psammentic Aquiturbels. In all soils phosphatization and ornithogenesis occurs in varying degrees. However, the recent Gelisols order of Soil Taxonomy does not consider the influence of ornithogenesis or phosphatization in its framework, so that a more detailed classification of such soils is not possible.
Full text
Available for:
FZAB, GIS, IJS, KILJ, NLZOH, NUK, OILJ, SBCE, SBMB, UL, UM, UPUK
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