ALBERT

Description: Pavlu L, Drabek O, Stejskalova S, Tejnecky V, Hradilova M, Nikodem A, Boruvka L DISTRIBUTION OF ALUMINIUM FRACTIONS IN ACID FOREST SOILS: INFLUENCE OF VEGETATION CHANGES Abstract : This study examines aluminium as a potentially phytotoxic element in acidic forest soils. Concentrations of Al forms in soils are generally controlled by soil chemical conditions, such as pH, organic matter, base cation contents, etc. Moreover, soil conditions are influenced by the vegetation cover. This study analyzed the distribution of Al forms in soils after changes in vegetation. HPLC/IC was used for the separation of three Al fractions in two soil extracts according to their charge. An aqueous extract (AlH2O) simulated the natural soil conditions and bioavailable Al fractions. Potentially available Al form was represented by a 0.5 M KCl extract (AlKCl). We demonstrated that the vegetation type influences the concentrations of different Al fractions, mainly in the surface organic horizons. Differences were more common in the KCl extract. The trivalent fraction was less influenced by vegetation changes than the mono- and divalent fractions. Afforestation increased the concentrations of AlKCl and AlH2O. In contrast, grass expansion after deforestation led to significantly decreased concentrations of AlKCl and AlH2O. Concentrations of AlH2O in organic horizons were higher in spruce forest than in beech forest. A long-term effect of liming on soil pH and concentrations of potentially toxic Al fractions was not apparent. The results provide information on the variations of Al fractions distributions following vegetation type changes and indicate the existence of some natural mechanisms controlling Al toxicity. Furthermore, the results can be used in the management of forested areas endangered by soil acidification. Keywords : Aluminium Fractionation, Forest Soil, Afforestation, Deforestation, HPLC/IC iForest 11 (6): 721-727 (2018) - doi: 10.3832/ifor2498-011 http://iforest.sisef.org/contents/?id=ifor2498-011

Description: Any strategy to change Carbon (C) pool would have a substantial effect on functionality of numerous ecosystem functions, detachment of Soil Organic Carbon (SOC), atmospheric carbon dioxide (CO2) concentration, and climate change mitigation. As the largest amount of the world’s C is stored in forests soils, the importance of forest SOC management is highlighted. Total SOC in forest varies not only laterally but also vertically with depth; however, the SOC storage of lower soil horizons have not been investigated enough despite their potential to frame our understanding of soil functioning. Visible–Near Infrared (vis–NIR) reflectance spectroscopy enables rapid examinations of the horizontal distribution of forest SOC, overcoming limitations of traditional soil assessment. This study aims to evaluate the potential of vis–NIR spectroscopy for characterizing the SOC contents of organic and mineral horizons in forests. We investigated 1080 forested sites across the Czech Republic at five individual soil layers, representing the Litter (L), Fragmented (F), and Humus (H) organic horizons, and the A1 (depth of 2–10 cm) and A2 (depth of 10–40 cm) mineral horizons (total 5400 samples). We then used Support Vector Machine (SVM) to model the SOC contents of (i) the profile (all organic and mineral horizons together), (ii) the combined organic horizons, (iii) the combined mineral horizons, and (iv) each individual horizon separately. The models were validated using 10-repeated 10-fold cross validation. Results showed that there was at least more than seven times as much SOC in the combined organic horizons compared to the combined mineral horizons with more variation in deeper layers. All individual horizons’ SOC was successfully predicted with low error and R2 values higher than 0.63; however, the prediction accuracy of F and A1 was greater compared to others (R2 〉 0.70 and very low-biased spatial estimates). We have shown that modelling of SOC with vis–NIR spectra in different soil horizons of highly heterogeneous forests of the Czech Republic is practical.

Description: Soil Carbon (C) is central to the functioning of ecosystems and climate change mitigation. It represents the largest terrestrial pool and much of it, is stored in forest soils. Soil Organic Carbon (SOC) in a forest varies not only laterally, but also vertically (i.e., with depth). However, the SOC content of forest soil horizons has not been investigated over large scales, despite its importance for framing our understanding of soil function. Visible–Near Infrared (vis–NIR) reflectance spectroscopy enables rapid and cost-effective examination of forest SOC distribution, both laterally and vertically. This study aims to evaluate the potential of vis–NIR spectroscopy for classifying and predicting the SOC concentration of organic and mineral horizons in forests of the Czech Republic. We investigated 1080 forest sites across the country, each with five soil horizons, representing the Litter (L), Fragmented (F), and Humus (H) organic horizons, as well as the A1 (depth of 2–10 cm) and A2 (depth of 10–40 cm) mineral horizons. We, then, used Support Vector Machines (SVMs) to classify the soil horizons based on their spectra and also to model the SOC concentration of (i) the profile (organic and mineral horizons together), (ii) only the organic horizons, (iii) only the mineral horizons, and (iv) each individual horizon separately. The models were validated using 10-repeated 10-fold cross-validation. Results show that the SVM with radial basis kernel could accurately classify the soil horizons (Correct Classification Rate (CCR) of 70% and Kappa coefficient of 0.63). The SOC model developed for the soil profile performed well (R2 = 0.76 and RMSE = 1.63%). The model of the combined organic horizons was considerably more accurate than that of the combined mineral horizons (R2 = 0.78 and R2 = 0.53, respectively). Estimates of SOC in the individual soil horizons had R2 values greater than 0.63 but those of the F and A1 models were better with R2 〉 0.70. The study indicates that vis–NIR spectroscopy can effectively characterize the SOC concentration of the highly variable forest soil horizons in the Czech Republic.