Post-fire recovery of soil organic matter in a Cambisol from typical Mediterranean forest in Southwestern Spain

Jiménez-González, Marco A.; Rosa, José María De la; Morillo, N. T. Jiménez; Almendros, G.; González‐Pérez, José Antonío; Knicker, Heike

doi:10.1016/j.scitotenv.2016.02.134

Cited by 53 publications

(25 citation statements)

References 26 publications

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“…The results of solid-state carbon-13 nuclear magnetic resonance (13-C NMR) spectroscopy reported by Jiménez-González et al, 2016 were consistent with an increase of aromatic compounds in upper horizons of postfire soils because of the accumulation of charcoal in comparison with the deeper soil sections. Almendros, González-Vila, Martín, Fründ, and Lüdemann (1992) showed that NMR results suggested that humic acids (HAs) in a laboratory simulation of fire underwent decarboxylation, and selective transformation of aliphatic part and also the amount of aromatic carbons have been increased.…”

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confidence: 65%

Assessment of postfire soils degradation dynamics: Stability and molecular composition of humic acids with use of spectroscopy methods

2017

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The effect of wildfires on the soils of the south taiga and forest‐steppe environments of Central Russia (Histic Spodosols and Eutric Fluvic Arenosols) was investigated in terms of the content and quality of humic acids (HAs) using instrumental spectroscopic methods (solid‐state carbon‐13 nuclear magnetic resonance and electron spin resonance). The bulk elemental composition of HAs was not essentially altered in postfire soils; however, the organic matter of fire‐affected superficial soil layers was characterized by changes in the structural composition and biochemical activity levels. Solid‐state carbon‐13 nuclear magnetic resonance spectroscopy showed that there is an intensive increase in aromatic compounds in HA molecules in soil from both the south taiga and forest‐steppe environments. There is a pronounced and statistically significant decline of aliphatic chain content in response to exposure to fire. The free radicals content and the degree of molecular stabilization assessed with electron spin resonance showed an essential alteration of the HAs, expressed in the increase in the radical's portion, in postfire soils compared with that found in soils not exposed to fire. It was also shown that the accumulation of aromatic compounds indicates only apparent stabilization of HAs due to the loss of periphery alkylic carbon species, which was confirmed by destabilization of the molecules as illustrated by the increase of free radicals.

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confidence: 65%

Assessment of postfire soils degradation dynamics: Stability and molecular composition of humic acids with use of spectroscopy methods

2017

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“…41 The favorable conditions for microbial degradation under the warm and humid conditions in the experimental region ( Figure 2) could have enhanced the complete or partial degradation of pyrogenic organic matter, and the leaching of the pyrogenic compounds may have been favored due to the high precipitation rates after burning ( Figure 2) and to the sandy character of the soil (Table 1). Jimenez-Gonzalez et al 11 reported similar results when comparing aryl C contributions to C soil within 0.00-0.10 m depth in a Cambisol under unburnt Mediterranean Forest (18-19%) and two years after burning of the forest (24-20%).…”

Section: Chemical Composition Of Som Assessed By 13 C Nmrmentioning

confidence: 58%

“…7 The literature reports decrease as well as increase in SOM content after vegetation burning events. [8][9][10][11] Usually, loss of labile organic compounds (e.g. carbohydrates) and increase in aromatic and polyaromatic C compounds (pyrogenic C, PyC) are observed right after vegetation burning, shifting SOM composition towards a higher aromatic and hydrophobic character, specially within the first soil layers.…”

Section: Introductionmentioning

confidence: 99%

Carbon in Physical Fractions and Organic Matter Chemical Composition of an Acrisol after Amazon Forest Burning and Conversion into Pasture

Leal¹,

Dick²,

Costa³

et al. 2018

J. Braz. Chem. Soc.

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The aim of this study was to investigate impacts of Amazon Forest (AF) fire and conversion to pasture on carbon accumulation in particle size fractions and organic matter (OM) composition of an Acrisol. Soil samples were collected (0.00-2.00 m depth) in three sites: native AF (NAF); AF under natural regeneration for two years after burning (BAF); 23-years old Brachiaria pasture after AF burning (BRA). Assuming NAF area as reference, BAF and BRA areas showed negative carbon balance when carbon emitted to the atmosphere at AF burning is taken into account. Soil OM aromaticity and hydrophobicity, assessed via 13 C nuclear magnetic resonance, in BRA and BAF were similar to that in NAF. Fire and post-fire land use altered the carbon distribution in sand, silt and clay along the soil profile and seem to have affected organo-mineral and OM self-assemblage interactions, since the relation between total soil carbon and carbon in clay was asymptotic in BAF and linear in NAF and BRA.

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“…These values are higher than the average values registered in global (Brown, Shepherd, Walsh, Mays, & Reinsch, ) and European (Stevens et al, ) soil databases, which is rather surprising given that approximately one third of the samples is from the burned areas. However, the unusually high SOM content in samples of burned soils may be due to vigorous vegetation development in the burned areas, which may have contributed to accelerated recovery of organic material destroyed by the fire (Jiménez‐González et al, ; Vlassova & Pérez‐Cabello, ).…”

Section: Resultsmentioning

confidence: 99%

Soil organic matter and texture estimation from visible–near infrared–shortwave infrared spectra in areas of land cover changes using correlated component regression

et al. 2019

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Land use changes due to natural and human‐related factors, which include wildfires and crop abandonment, are among the most important drivers of soil degradation and demand regular monitoring. Proximal soil sensing in visible–near infrared–shortwave infrared spectral regions could offer a solution. However, to become operational, optimal combination of data and technique has to be defined. Thus, the purpose of this study was (a) to predict the soil organic matter (SOM) content and soil texture in areas of wildfire burns and crop abandonment in Aragón Province, Northern Spain, from their laboratory reflectance spectra using novel correlated components regression with a step‐down variable selection algorithm (CCR‐SD) and (b) to compare the CCR‐SD and the partial least squares regression (PLSR) methods. The results obtained by the tested methods were similar. CCR‐SD models showed high predictive capacity with coefficients of determination (R2) in the range of 0.80–0.86 and 0.70–0.87 for calibration and validation data sets, respectively, and the highest R2 value was attained in the SOM estimation. Moreover, the CCR‐SD models stand out for the superior accuracy–parsimony relationship: the number of predictors varied from 16 (silt models) to 49 (SOM models). On average, the CCR‐SD calibrations needed less than a half of the predictors employed in PLSR models. This research confirmed that CCR‐SD can be used for monitoring SOM content and texture of soils from visible–near infrared–shortwave infrared spectra in the study area and, probably, in other areas of land use/land cover change and that CCR‐SD can create highly parsimonious models that achieve results comparable with the commonly used PLSR method.

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Post-fire recovery of soil organic matter in a Cambisol from typical Mediterranean forest in Southwestern Spain

Cited by 53 publications

References 26 publications

Assessment of postfire soils degradation dynamics: Stability and molecular composition of humic acids with use of spectroscopy methods

Assessment of postfire soils degradation dynamics: Stability and molecular composition of humic acids with use of spectroscopy methods

Carbon in Physical Fractions and Organic Matter Chemical Composition of an Acrisol after Amazon Forest Burning and Conversion into Pasture

Soil organic matter and texture estimation from visible–near infrared–shortwave infrared spectra in areas of land cover changes using correlated component regression

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