Weathering and pedogenesis of sediments and basaltic rocks on Vega Island, Antarctic Peninsula

Siqueira, Rafael Gomes; Schaefer, Carlos Ernesto Gonçalves Reynaud; Filho, Elpı́dio Inácio Fernandes; Corrêa, Guilherme Resende; Francelino, Márcio Rocha; Souza, José João Lelis Leal de; Rocha, Pablo de Azevedo

doi:10.1016/j.geoderma.2020.114707

Cited by 20 publications

(27 citation statements)

References 41 publications

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“…One single sulfate soil was described in Livingston Island (Byers Peninsula). In JRA, twenty-tree acid sulfate soils were reported in two islands: Vega Island (Cape Lamb), with ten pedons (Siqueira et al 2021), and Seymour Island (Fig. 1), totalizing 13 pedons (Delpupo et al 2014, Gjorup et al 2020).…”

Section: Soil Samplesmentioning

confidence: 99%

Acid sulfate soils from Antarctica: genesis and properties along a climatic gradient

Siqueira

Lopes

Souza

et al. 2022

An. Acad. Bras. Ciênc.

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Sulfurization is a pedogenic process that involves pyrite oxidation and strong soil acidifi cation, accounting for the formation of acid sulfate soils. In Antarctica, acid sulfate soils are related to specifi c parent materials, such as sulfi de-bearing andesites in Maritime Antarctica and pyritized sedimentary rocks in James Ross Archipelago. The hypothesis is that the acid sulfate soils of these regions vary according with a climate gradient. The reviewing of current data showed that the acid sulfate soils of warmer and wetter Maritime Antarctica have a greater weathering degree, higher acidity, leaching, phosphorus adsorption capacity, structural development, and well-crystallized iron oxides and kaolinite formation. On the other hand, the sulfurization at the drier region of James Ross Archipelago is counterbalanced by the semiaridity, resulting in lower acidity and higher base contents combined with little morphological and mineralogical evolution besides presence of weatherable minerals in the clay fraction. The sulfurization process interplays with other pedogenic processes, such as the phosphatization in Maritime Antarctica and salinization in James Ross Archipelago. Higher temperatures and soil moisture enhance the pedogenesis, showing that even the Antarctic sulfate soils, which originated from specifi c parent materials, have their development and characteristics controlled by a clear climatic gradient.

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Section: Soil Samplesmentioning

confidence: 99%

Acid sulfate soils from Antarctica: genesis and properties along a climatic gradient

Siqueira

Lopes

Souza

et al. 2022

An. Acad. Bras. Ciênc.

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“…Some parent materials tend to have higher P concentrations, which then translate into higher total soil P (Mage and Porder, 2013;Dieter et al, 2010;Kitayama et al, 2000). Additionally, parent material also affects soil total P indirectly via the influence of soil physiochemical properties such as soil texture, pH, and Al and Fe oxides (Siqueira et al, 2021;Mehmood et al, 2018). For example, the retention of P in soil can be influenced by the soil content of clay, soluble calcium, and Fe oxyhydroxides (Delgado-Baquerizo et al, 2020;Mehmood et al, 2018;Achat et al, 2016b).…”

Section: Soil Total P Concentration In Relation To Its Predictorsmentioning

confidence: 99%

Global patterns and drivers of soil total phosphorus concentration

Augusto

Goll

et al. 2021

Earth Syst. Sci. Data

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Abstract. Soil represents the largest phosphorus (P) stock in terrestrial ecosystems. Determining the amount of soil P is a critical first step in identifying sites where ecosystem functioning is potentially limited by soil P availability. However, global patterns and predictors of soil total P concentration remain poorly understood. To address this knowledge gap, we constructed a database of total P concentration of 5275 globally distributed (semi-)natural soils from 761 published studies. We quantified the relative importance of 13 soil-forming variables in predicting soil total P concentration and then made further predictions at the global scale using a random forest approach. Soil total P concentration varied significantly among parent material types, soil orders, biomes, and continents and ranged widely from 1.4 to 9630.0 (median 430.0 and mean 570.0) mg kg−1 across the globe. About two-thirds (65 %) of the global variation was accounted for by the 13 variables that we selected, among which soil organic carbon concentration, parent material, mean annual temperature, and soil sand content were the most important ones. While predicted soil total P concentrations increased significantly with latitude, they varied largely among regions with similar latitudes due to regional differences in parent material, topography, and/or climate conditions. Soil P stocks (excluding Antarctica) were estimated to be 26.8 ± 3.1 (mean ± standard deviation) Pg and 62.2 ± 8.9 Pg (1 Pg = 1 × 1015 g) in the topsoil (0–30 cm) and subsoil (30–100 cm), respectively. Our global map of soil total P concentration as well as the underlying drivers of soil total P concentration can be used to constraint Earth system models that represent the P cycle and to inform quantification of global soil P availability. Raw datasets and global maps generated in this study are available at https://doi.org/10.6084/m9.figshare.14583375 (He et al., 2021).

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“…According to Siqueira et al (2021), the landforms of Cape Lamb, Vega Island are encompassed within four geomorphological domains: glacial, glaciogenic, periglacial and paraglacial. The glaciers (glacial domain) of Vega are constituted by cirque, valley and tidewater glaciers, common in the Weddell Sea sector (Davies et al, 2013).…”

Section: Discussionmentioning

confidence: 99%

Evaluation of machine learning algorithms to classify and map landforms in Antarctica

Siqueira

Veloso

Filho

et al. 2021

Earth Surf Processes Landf

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The detailed geomorphology of ice‐free landscapes of Antarctica is key to understanding how their highly fragile environments respond to climate change, at different temporal and spatial scales. Despite the recent advances in geomorphological studies of ice‐free areas, machine learning applications to produce landform maps are still scarce on the Antarctic continent. In this study, we evaluated the predictive performance of different supervised machine learning algorithms to produce digital geomorphological maps in Vega Island—Antarctic Peninsula region. We tested six different models: average artificial neural networks, C5.0 decision tree, random forest, support vector machine, supervised self‐organizing map and weighted k‐nearest neighbours. We used an initial set of 54 geomorphometric and spectral predictors, from which redundant variables with Pearson correlation coefficient >|0.95| were removed, and only the most important predictors for each model were selected using recursive feature elimination. For training, we ran each model 100 times and predictions were assessed by the kappa and global accuracy values. The best predictors were the Red Edge 6 and SWIR 11 bands, roughness concentration index, elevation and drainage density. The decision trees C5.0 and random forest had the best performance, with average validation kappa of 0.85 ± 0.03 and 0.84 ± 0.03, respectively, evidencing excellent prediction. Despite the similar performance, random forest showed greater uncertainty degree and accuracy when classifying complex landforms, attesting to its great robustness. From sensitivity and specificity values, we observed that the glaciers and talus showed higher accuracy, whereas cryoplanated platforms and scree slopes had the worst classification. The presented methodology optimized the classification by selecting the most important predictors, assessing accuracy and evaluating uncertainty. The results indicated that machine learning methods have great potential to produce geomorphological mappings in the Antarctic ice‐free areas, as a promising tool to provide detailed information on remote, harsh polar environments.

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Weathering and pedogenesis of sediments and basaltic rocks on Vega Island, Antarctic Peninsula

Cited by 20 publications

References 41 publications

Acid sulfate soils from Antarctica: genesis and properties along a climatic gradient

Acid sulfate soils from Antarctica: genesis and properties along a climatic gradient

Global patterns and drivers of soil total phosphorus concentration

Evaluation of machine learning algorithms to classify and map landforms in Antarctica

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