Monday paper: Short-term changes in soil Munsell colour value, organic matter content and soil water repellency after a spring grassland fire in Lithuania


Pereira P, Úbeda X, Mataix-Solera J, Oliva M, Novara A: Short-term changes in soil Munsell colour value, organic matter content and soil water repellency after a spring grassland fire in Lithuania. Solid Earth, 5, 209-225. DOI: 10.5194/se-5-209-2014.

Evidence of earthworm activity (indicated with a red circle) in the burned plot 17 days after the fire.
Evidence of earthworm activity in the burned plot 17 days after the fire.

Abstract

Fire is a natural phenomenon with important implications on soil properties. The degree of this impact depends upon fire severity, the ecosystem affected, topography of the burned area and post-fire meteorological conditions. The study of fire effects on soil properties is fundamental to understand the impacts of this disturbance on ecosystems. The aim of this work was to study the short-term effects immediately after the fire (IAF), 2, 5, 7 and 9 months after a low-severity spring boreal grassland fire on soil colour value (assessed with the Munsell colour chart), soil organic matter content (SOM) and soil water repellency (SWR) in Lithuania. Four days after the fire a 400 m2 plot was delineated in an unburned and burned area with the same topographical characteristics. Soil samples were collected at 0–5 cm depth in a 20 m × 20 m grid, with 5 m space between sampling points. In each plot 25 samples were collected (50 each sampling date) for a total of 250 samples for the whole study. SWR was assessed in fine earth (< 2 mm) and sieve fractions of 2–1, 1–0.5, 0.5–0.25 and < 0.25 mm from the 250 soil samples using the water drop penetration time (WDPT) method. The results showed that significant differences were only identified in the burned area. Fire darkened the soil significantly during the entire study period due to the incorporation of ash/charcoal into the topsoil (significant differences were found among plots for all sampling dates). SOM was only significantly different among samples from the unburned area. The comparison between plots revealed that SOM was significantly higher in the first 2 months after the fire in the burned plot, compared to the unburned plot. SWR of the fine earth was significantly different in the burned and unburned plot among all sampling dates. SWR was significantly more severe only IAF and 2 months after the fire. In the unburned area SWR was significantly higher IAF, 2, 5 and 7 months later after than 9 months later. The comparison between plots showed that SWR was more severe in the burned plot during the first 2 months after the fire in relation to the unburned plot. Considering the different sieve fractions studied, in the burned plot SWR was significantly more severe in the first 7 months after the fire in the coarser fractions (2–1 and 1–0.5 mm) and 9 months after in the finer fractions (0.5–0.25 and < 0.25 mm). In relation to the unburned plot, SWR was significantly more severe in the size fractions 2–1 and < 0.25 mm, IAF, 5 and 7 months after the fire than 2 and 9 months later. In the 1–0.5- and 0.5–0.25 mm-size fractions, SWR was significantly higher IAF, 2, 5 and 7 months after the fire than in the last sampling date. Significant differences in SWR were observed among the different sieve fractions in each plot, with exception of 2 and 9 months after the fire in the unburned plot. In most cases the finer fraction (< 0.25 mm) was more water repellent than the others. The comparison between plots for each sieve fraction showed significant differences in all cases IAF, 2 and 5 months after the fire. Seven months after the fire significant differences were only observed in the finer fractions (0.5–0.25 and < 0.25 mm) and after 9 months no significant differences were identified. The correlations between soil Munsell colour value and SOM were negatively significant in the burned and unburned areas. The correlations between Munsell colour value and SWR were only significant in the burned plot IAF, 2 and 7 months after the fire. In the case of the correlations between SOM and SWR, significant differences were only identified IAF and 2 months after the fire. The partial correlations (controlling for the effect of SOM) revealed that SOM had an important influence on the correlation between soil Munsell colour value and SWR in the burned plot IAF, 2 and 7 months after the fire.

Solid Earth

Solid Earth (SE) is an international scientific journal dedicated to the publication and discussion of multidisciplinary research on the composition, structure and dynamics of the Earth from the surface to the deep interior at all spatial and temporal scales. More at Solid Earth homepage.

Soil color never lies


Soil balls made by students in the laboratory showing different colors. Credit: Antonio Jordán. Click to see the original picture at Imaggeo.

Often, soil color is described using general terms such as “brown”, “red”, “dark”, etc. When I talk about this issue for the first time with my students of Soil Science, I use to ask them how to describe the color of a soil sample. Normally, in a few seconds, I get a list of color names ranging from dark brown to bright red, including “chocolate”, “coffee” and “dog belly”. Sometimes, we come to some consensus (for example, brown to yellowish brown), but in many cases I find very opposing positions. Then I show another soil sample with a very similar color, and ask them to say which one is more yellowish, green, brown or dark. Here now, discussions can be strong.

Why soil scientists describe soil color?

One of the properties most commonly used by soil scientists to describe and classify soil horizons is color. Color is a physical property of soils that allows us to know some of its most important characteristics, such as mineral composition, age and soil processes (chemical alteration, carbonate accumulation, the presence of humified organic matter, etc.). The presence of water in the soil profile during long periods of time also affects soil color as a result of changes in the oxidation rate. Similarly, together with other physical properties, color helps us to differentiate between types of horizons of the same profile or different soil profiles.

Red to greysh green colors in a soil profile as a consequence of redox processes. Credit: Antonio Jordán. Click to see the original picture at Imaggeo.

What does soil color tell?

The substances resulting from decomposition of the organic matter are oxidized and acquire a dark coloration. On the other hand, some of these substances can be combined with mineral substances present in the soil as a consequence of mineralization of organic materials or chemical alteration of clays (such as iron oxides). After physical and chemical alterations, organic and inorganic materials contribute to soil color in different ways and proportions and, as a result, color is a product of co-working soil processes and environmental conditions. Soil color is related to soil processes, and is used as a diagnostic criteria for soil classification. In the WRB, for example, soil color is used as a criteria for classifying diagnostic horizons (albic, anthric, fulvic, hortic, hydragric, melanic, mollic, plaggic, sombric, spodic, terric, umbric and voronic horizons must meet certain color parameters), diagnostic properties (albeluvic tonguing, aridic properties, gleyic and stagnic color patterns), and diagnostic materials (limnic and sulphidic materials), and is used for supporting field indentification in many cases.

Soil scientist (Dr. David Badía, University of Zaragoza, Spain), trying to find the dark colored surface horizon in a melon-cropped soil in Mallorca (Spain).

Agricultural soils, for example, often have a color slightly influenced by organic matter, since the contribution of organic residues is much lower than in the case of forest soils. Thus, in this case, the distinction between organic and mineral horizons is much weaker, having to rely on other properties such as texture or structure.

Dark and grey colors in a peaty soil in the Andean highland (Ecuador). Credit: Matin Mergili. Click to see the original picture at Imaggeo.

Among the most frequent soil colors, we can find the following :

  • Dark or black. Dark colors are usually due to the presence of organic matter, so that the darker the surface horizon more organic matter content is assumed (this is not an exact and one-to-one correspondence). It is characteristic of the surface horizon, but can be found in other exceptional cases (in Podzols, under acid conditions, transformed organic residues accumulate in the spodic horizon). The dark color is characteristic of soils as Chernozems, Russian word for “black earth”. Chernozems are mainly in a band that includes Croatia, northern Serbia, northern Bulgaria, southern Romania, Ukraine and Russia (Europe and Asia) and Canada (America), where climatic conditions favor the accumulation of humus. At other times, the dark color is due to the presence of compounds of reduced iron and manganese (as in Vertisols, black poorly drained soils), the presence of charcoal in soils from the Brazilian Amazon, Ecuador, Peru and some areas Africa (these soils are known as “Terra preta”, dark soil in Portuguese).

Dark surface horizon (mollic horizon) in eastern Spain. Credit: Jorge Mataix-Solera. Click to see the original picture at Imaggeo.
  • Clear or white. Usually due to the presence of calcium and magnesium carbonates, gypsum or other more soluble salts. Carbonates may show continuous or discontinuous patterns: nodules, fine powder or films on soil aggregates (pseudomycelia). Soluble salts such as NaCl, may form a surface white crust or be present in the soil matrix in a diffuse form. Carbonates and soluble salts may be present in the parent material or accumulate in soil due to the arid climate or other processes. In other cases, light color is due to a relatively high proportion of sand (quartz crystals), either in the whole soil or in profile horizons that have suffered extensive washing under very humid climate.

Light color in a cacium carbonate-rich soil (southeastern Spain). Credit: Jorge Mataix-Solera. Click to see the original picture at Imaggeo.
White salt crust (Mexico). Credit: Antonio Jordán. Click to see the original picture at Imaggeo.
  • Red. The red color is usually a result of alteration of clay minerals, so it usually occurs in the argillic horizons. Weathered clay minerals release aluminium and iron oxides such as hematite (Fe2O3). This process is favored in hot climates with a long and intense dry season, as the Mediterranean climate. Reddish colors indicate good drainage and aeration of the soil, allowing the existence of oxidizing conditions to form oxides. In the Mediterranean basin, red soils are known as “Terra rossa” (Italian expression for red soil).

Olive-cropped red soil (Andalusia, Spain). Credit: Artemi Cerdà. Click to see the original picture at Imaggeo.
  • Yellowish brown/orange. Yellowish or orange colors may be due to the presence of goethite, FeO(OH), and bound to the clay and organic matter. Therefore, although composition is similar to some red soils, we know that these soils were formed under conditions of increased moisture availability red soil.

  • Gleyic color pattern. The Russian word “gley” is used for mucky soil mass or clay. This color pattern is due to the presence of ferrous and ferric compounds. These colors are characteristic of Gleysols, developed under alternating reducing and oxidizing conditions. The mottled or marbled is presented as groups of spots of red, yellow and gray colors. This property appears in soils or horizons that are waterlogged for at least one part of the year. Sometimes it may be due to the activity of plant roots living in ponding. Usually, soils presenting this color pattern show reddish/brownish/yellowish colors in the surface of aggregates, pore surfaces or in the upper soil horizons (due to oxidized Fe3+ and Mn4+), and greyish/blueish colors inside the aggregates or in the deeper soil horizons (due to insoluble Fe2+ and Mn2+ compounds).

Wet soil (Egypt). Credit: Sameh Abd-Elmabod. Click to see the original picture at Imaggeo.
  • Green. The green color in the soil may be due to the presence of minerals such as glauconite, an iron potassium phyllosilicate mineral (mica group) or melanterite, a hydrated iron sulphate mineral.

How do soil scientists describe soil color?

The first thing to keep in mind (and a very common mistake among students) is that it is not describing soil color, but the color of the soil horizons. Normally, in a soil profile we find a variable number of horizons, each with a specific color as a result of its composition.

The second one is that even with the most objective method, two soil scientists may come to discrepancies or argue heatedly. Expertise, subjectivity, light conditions or irregular ped surfaces may not help (even sunglasses or daltonism!). For this reason, many teams designate one person responsible for the determination of color (usually the strongest person).

Soil color determination in the laboratory. Credit: Antonio Jordán. Click to see the original picture at Imaggeo.

Finally, the third one is: what are you describing the color of? Even when describing a soil horizon, color may not be homogeneously distributed. Often, mottles or nodules different in color, abundance, contrast and size may be present. Coatings do not help. So, soil scientists may pay attention to these features (and describe!).

Red colour (due to the massive release of dehydrated iron oxides, hematite), dark spots (manganese oxides) and a yellowish colour surrounding cracks and macropores were water flows (hydration and reduction of iron minerals). Credit: Antonio Jordán. Click to see the original picture at Imaggeo.

Soil colors may be technically described by the Munsell charts, separating the color shade components (relative to red, yellow and blue), value (lightness or darkness) and chroma (intensity or strength). For this, the color of a soil sample is compared to standard color samples, so that three parameters can be identified: hue, value and chroma. Optimum conditions for the assessment of soil color include direct sunlight, with light at right angle to the charts and soil moist.

  • Hue. The hue indicates its relative position on a scale of 100 different grades of color. Hue depends on the wavelength (in short: the real color). The notation is based in 10 major classes: red (R), yellowish red (YR), yellow (Y), greenish yellow (GY), green (G), blueish green (BG), blue (B), purplish blue (PB), purple (P), reddish purple (RP). Grayish, blueish and greenish hues may be grouped as gley. Most common soil hues are gley, R, YR and Y. Gradation of each hue may be expressed as 2.5, 5, 7.5 and 10. The purest hue is 5, and lower and higher grades indicate mixtures ot other hues.
  • Value. The value indicates the lightness or darkness of a color in relation to a neutral gray scale, ranging from absolute black (0/, absolute black, no light reflected) to absolute white (10/, absolute white, all light reflected).
  • Chroma. Chroma indicates the degree of concentration of hue from a neutral gray with the same brightness. The chroma scale ranges from /0 to /10, /12, /14, or more, depending on the sample being examined, with lower chromas indicating increasing grayness.

When determining soil color with the Munsell charts, the first step is selecting the correct hue. Each chart has a number of color chips arranged according to value and chroma. All chips from one chart have the same hue (this means: all chips in a page reflect the same wavelength). In each chart, color chips are arranged vertically from lighter (top) to darker value (bottom) and horizontally from lower (left) to higher chroma (right). Hue is designated by a symbol in the upper right hand-corner of each chart, and rows and columns are numbered according to the value and chroma. Usually, common soil names are given in the opposite chart (but this should be only orientative). For this step I recommend my students to hold the soil sample or aggregate in one hand and travel through the charts to find that they think matches the soil color.

Soil colour determination. Credit: Flickr user Soil Science @ NC State.
Soil color determination. Credit: Soil Science @ NC State (Flickr).

Then, the soil sample must be placed behind the apertures of the chart in order to find the most similar color chip. Black and grey masks provided with the charts can be used for dark and intermediate/light samples to avoid disturbing contrast. When the correct chip is found, it is time to describe the color.

Finding soil value and chroma.
Finding soil value and chroma. Credit: Center for American Archeology (Flickr).

Let’s assume that the soil color in the next picture is the same that the chip in the third row, third column. We must find hue (upper right corner), value (row number) and chroma (column number): 5YR 6/3. In the opposite page, we can find the color name: light reddish brown.

Munsell soil color chart.
Munsell soil color chart.

 Munsell color charts may be used for many other purposes, not only soil color. Munsell color system is used in arts, science (geology, archeology, pharmacy, medicine, etc.), education and industries (agronomy, food technologies, design, architecture, etc.). Even for fun!

You can easily munsell people and animals.

Know more

Barron, V., Torrent, J. 1986. Use of the Kubelka-Munk theory to study the influence of iron oxides on soil colour. European Journal of Soil Science 37, 499-510. DOI: 10.1111/j.1365-2389.1986.tb00382.x.

Bodí, M.B., Mataix-Solera, J., Doerr, S.H., Cerdà, A. 2011. The wettability of ash from burned vegetation and its relationship to Mediterranean plant species type, burn severity and total organic carbon content. Geoderma 160, 599-607. DOI: 10.1016/j.geoderma.2010.11.009.

Ben-Dor, E., Heller, D., Chudnovsky, A. 2008. A novel method for classifying soi profiles in the field using optical means. Soil Science Society of America Journal 72, 1113-1123. DOI: 10.2136/sssaj2006.0059.

Erskine, W.D. 2013. Soil colour as a tracer of sediment dispersion from erosion of forest roads in Chichester State Forest, NSW, Australia. Hydrological Processes 27, 933-942. DOI: 10.1002/hyp.9412.

He, X., Vepraskas, M.J., Lindbo, D.L., Skaggs, R.W. 2003. A method to predict soil saturation frequency and duration from soil color. Soil Science Society of America Journal 67, 961-969. DOI: 10.2136/sssaj2003.9610.

Gómez-Robledo, L-, López-Ruiz, N., Melgosa, M., Palma, A.J., Capitán-Vallvey, L.F., Sánchez-Marañón, M. 2013. Using the mobile phone as Munsell soil-colour sensor: An experiment under controlled illumination conditions. Computers and Electronics in Agriculture 99. 200-208. DOI: 10.1016/j.compag.2013.10.002.

Ketterings, Q.M., Bigham, J.M. 2000. Soil color as an indicator of slash-and-burn fire severity and soil fertility in Sumatra, Indonesia. Soil Science Society of America Journal 64, 1826-1833. DOI: 10.2136/sssaj2000.6451826x.

Sánchez-Marañón, M., García, P.A., Huertas, R., Hernández-Andrés, J., Melgosa, M. 2010. Influence of natural daylight on soil color description: assessment using a color-appearance model. Soil Science Society of America Journal 75, 984-993. DOI: 10.2136/sssaj2010.0336.

Sánchez-Marañón, M., Huertas, R., Melgosa, M. 2005. Colour variation in standard soil-colour charts. Soil Research 43, 827-837. DOI: 10.1071/SR04169.

Sánchez-Marañón, M., Soriano, M., Melgosa, M., Delgado, G., Delgado, R. 2004. Quantifying the effects of aggregation, particle size and components on the colour of Mediterranean soils. European Journal of Soil Science 55, 551-565. DOI: 10.1111/j.1365-2389.2004.00624.x.

Terefe, T., Mariscal-Sancho, I., Peregrina, F., Espejo, R. 2008. Influence of heating on various properties of six Mediterranean soils. A laboratory study. Geoderma 143, 273-280. DOI: 10.1016/j.geoderma.2007.11.018.

Thompson, J.A., Bell, J.C. 1996. Color index for identifying hydric conditions for seasonally saturated mollisols in Minnesota. Soil Science Society of America Journal 60, 1979-1988. DOI: 10.2136/sssaj1996.03615995006000060051x.

Torrent, J., Schwertmann, U., Schulze, D.G. 1980. Iron oxide mineralogy of some soils of two river terrace sequences in Spain. Geoderma 23, 191-208. DOI: 10.1016/0016-7061(80)90002-6.

van der Waals, J.H. 2013. Soil colour variation between topsoil and subsoil horizons in a plinthic catena on the Mpumalanga Highveld, South Africa. South African Journal of Plant and Soil 30, 47-51. DOI: 10.1080/02571862.2013.777132.

Wills, S.A., Burras, C.L., Sandor, J.A. 2007. Prediction of soil organic carbon content using field and laboratory measurements of soil color. Soil Science Society of America Journal 71, 380-388. DOI: 10.2136/sssaj2005.0384.

Yang, S., Fang, X., Li, J., An, Z., Chen. S., Hitoshi, F. 2001. Transformation functions of soil color and climate. Science in China. Series D: Earth Sciences 44, 218-226. DOI: 10.1007/BF02911990.

 

This post was published simultaneously in the EGU Blog Network.

Monday paper: A dual isotope approach to isolate soil carbon pools of different turnover times


Torn, M. S., Kleber, M., Zavaleta, E. S., Zhu, B., Field, C. B., and Trumbore, S. E. 2013. A dual isotope approach to isolate soil carbon pools of different turnover times. Biogeosciences, 10, 8067-8081. DOI: 10.5194/bg-10-8067-2013.

Abstract

Soils are globally significant sources and sinks of atmospheric CO2. Increasing the resolution of soil carbon turnover estimates is important for predicting the response of soil carbon cycling to environmental change. We show that soil carbon turnover times can be more finely resolved using a dual isotope label like the one provided by elevated CO2 experiments that use fossil CO2. We modeled each soil physical fraction as two pools with different turnover times using the atmospheric 14C bomb spike in combination with the label in 14C and 13C provided by an elevated CO2 experiment in a California annual grassland. In sandstone and serpentine soils, the light fraction carbon was 21–54% fast cycling with 2–9 yr turnover, and 36–79% slow cycling with turnover slower than 100 yr. This validates model treatment of the light fraction as active and intermediate cycling carbon. The dense, mineral-associated fraction also had a very dynamic component, consisting of ∼7% fast-cycling carbon and ∼93% very slow cycling carbon. Similarly, half the microbial biomass carbon in the sandstone soil was more than 5 yr old, and 40% of the carbon respired by microbes had been fixed more than 5 yr ago. Resolving each density fraction into two pools revealed that only a small component of total soil carbon is responsible for most CO2 efflux from these soils. In the sandstone soil, 11% of soil carbon contributes more than 90% of the annual CO2 efflux. The fact that soil physical fractions, designed to isolate organic material of roughly homogeneous physico-chemical state, contain material of dramatically different turnover times is consistent with recent observations of rapid isotope incorporation into seemingly stable fractions and with emerging evidence for hot spots or micro-site variation of decomposition within the soil matrix. Predictions of soil carbon storage using a turnover time estimated with the assumption of a single pool per density fraction would greatly overestimate the near-term response to changes in productivity or decomposition rates. Therefore, these results suggest a slower initial change in soil carbon storage due to environmental change than has been assumed by simpler (one-pool) mass balance calculations.

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Biogeosciences (BG) is an international scientific journal dedicated to the publication and discussion of research articles, short communications and review papers on all aspects of the interactions between the biological, chemical and physical processes in terrestrial or extraterrestrial life with the geosphere, hydrosphere and atmosphere. The objective of the journal is to cut across the boundaries of established sciences and achieve an interdisciplinary view of these interactions. Experimental, conceptual and modelling approaches are welcome. More at Biogeosciences homepage.

Impact of fires on soil properties, runoff generation and sediment transport


Notes on session Session SSS 9.6/GM 6.7/HS 12.6 (EGU2013)

Conveners: Lee MacDonald; Jonay Neris; Stefan Doerr; Artemi Cerdà; J. Jacob Keizer

Wildfires are increasingly recognized as the primary cause of geomorphic change in forests and brush lands, and climate change is expected to further increase both the amount and severity of wildfires. Recent studies have provided an increasing amount of data on how fires can affect runoff and erosion rates, but there is still much to be done on the underlying causes of the observed increases, and how fire affects vary across vegetation types, climates, and spatial scale.

Post-wildfire landscape.
Post-wildfire landscape.

Dr. Scott Woods at the University of Montana was taking a leading role in this process-based research until his career was tragically ended by lung cancer. The Soil System Science sponsored a session in his honor during the 2013 EGU meeting, and this was entitled Impact of fires on soil properties, runoff generation and sediment transport.  The main aim of this session was to discuss the recent studies on the effects of fires on soil properties, the resultant changes in runoff and erosion rates, and the effectiveness of different post-fire treatments to mitigate these effects.

Impact of fires on soil properties, runoff generation and sediment transport oral session.
Impact of fires on soil properties, runoff generation and sediment transport oral session.

Twenty-four papers were submitted to this session.  The morning oral session in the morning began with a brief summary of Scott’s career, and this was followed by eight talks.  The session then shifted to a different room where a series of short presentations summarized many of the 16 poster papers.    The afternoon poster session then provided a lively venue for further discussions, and in the evening many of the presenters attended the special dinner for all those working on topics related to soil erosion.  Discussions are being held regarding the possible publication of the papers in a special issue of a peer-reviewed journal.

Biogeosciences: Modeling the vertical soil organic matter profile using Bayesian parameter estimation


Modeling the vertical soil organic matter profile using Bayesian parameter estimation. M. C. Braakhekke, T. Wutzler, C. Beer, J. Kattge, M. Schrumpf, B. Ahrens, I. Schöning, M. R. Hoosbeek, B. Kruijt, P. Kabat, and M. Reichstein. Biogeosciences, 10, 399-420, 2013

Abstract

The vertical distribution of soil organic matter (SOM) in the profile may constitute an important factor for soil carbon cycling. However, the formation of the SOM profile is currently poorly understood due to equifinality, caused by the entanglement of several processes: input from roots, mixing due to bioturbation, and organic matter leaching. In this study we quantified the contribution of these three processes using Bayesian parameter estimation for the mechanistic SOM profile model SOMPROF. Based on organic carbon measurements, 13 parameters related to decomposition and transport of organic matter were estimated for two temperate forest soils: an Arenosol with a mor humus form (Loobos, the Netherlands), and a Cambisol with mull-type humus (Hainich, Germany). Furthermore, the use of the radioisotope 210Pbex as tracer for vertical SOM transport was studied. For Loobos, the calibration results demonstrate the importance of organic matter transport with the liquid phase for shaping the vertical SOM profile, while the effects of bioturbation are generally negligible. These results are in good agreement with expectations given in situ conditions. For Hainich, the calibration offered three distinct explanations for the observations (three modes in the posterior distribution). With the addition of 210Pbex data and prior knowledge, as well as additional information about in situ conditions, we were able to identify the most likely explanation, which indicated that root litter input is a dominant process for the SOM profile. For both sites the organic matter appears to comprise mainly adsorbed but potentially leachable material, pointing to the importance of organo-mineral interactions. Furthermore, organic matter in the mineral soil appears to be mainly derived from root litter, supporting previous studies that highlighted the importance of root input for soil carbon sequestration. The 210Pbex measurements added only slight additional constraint on the estimated parameters. However, with sufficient replicate measurements and possibly in combination with other tracers, this isotope may still hold value as tracer for SOM transport.

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Biogeosciences (BG) is an international scientific journal dedicated to the publication and discussion of research articles, short communications and review papers on all aspects of the interactions between the biological, chemical and physical processes in terrestrial or extraterrestrial life with the geosphere, hydrosphere and atmosphere. The objective of the journal is to cut across the boundaries of established sciences and achieve an interdisciplinary view of these interactions. Experimental, conceptual and modelling approaches are welcome. More at Biogeosciences homepage.

Biogeosciences: Black carbon contributes to organic matter in young soils in the Morteratsch proglacial area (Switzerland)


Eckmeier, E., Mavris, C., Krebs, R., Pichler, B., and Egli, M.: Black carbon contributes to organic matter in young soils in the Morteratsch proglacial area (Switzerland), Biogeosciences, 10, 1265-1274, doi:10.5194/bg-10-1265-2013, 2013.

Abstract

Most glacier forefields of the European Alps are being progressively exposed since the glaciers reached their maximum expansion in the 1850s. Global warming and climate changes additionally promote the exposure of sediments in previously glaciated areas. In these proglacial areas, initial soils have started to develop so that they may offer a continuous chronosequence from 0 to 150-yr-old soils.

The build-up of organic matter is an important factor of soil formation, and not only autochthonous but also distant sources might contribute to its accumulation in young soils and surfaces of glacier forefields. Only little is known about black carbon in soils that develop in glacier forefields, although charred organic matter could be an important component of organic carbon in Alpine soils.

The aim of our study was to examine whether black carbon (BC) is present in the initial soils of a proglacial area, and to estimate its relative contribution to soil organic matter. We investigated soil samples from 35 sites distributed over the whole proglacial area of Morteratsch (Upper Engadine, Switzerland), covering a chronosequence from 0 to 150 yr. BC concentrations were determined in fine earth using the benzene polycarboxylic acid (BPCA) marker method. We found that charred organic matter occurred in the whole area, and that it was a main compound of soil organic matter in the youngest soils, where total Corgconcentrations were very low. The absolute concentrations of BC in fine earth were generally low but increased in soils that had been exposed for more than 40 yr. Specific initial microbial communities may profit from this additional C source during the first years of soil evolution and potentially promote soil development in its early stage.

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Biogeosciences (BG) is an international scientific journal dedicated to the publication and discussion of research articles, short communications and review papers on all aspects of the interactions between the biological, chemical and physical processes in terrestrial or extraterrestrial life with the geosphere, hydrosphere and atmosphere. The objective of the journal is to cut across the boundaries of established sciences and achieve an interdisciplinary view of these interactions. Experimental, conceptual and modelling approaches are welcome. More at Biogeosciences homepage.

Biogeosciences: The impact of four decades of annual nitrogen addition on dissolved organic matter in a boreal forest soil


Rappe-George, M. O., Gärdenäs, A. I., and Kleja, D. B.: The impact of four decades of annual nitrogen addition on dissolved organic matter in a boreal forest soil, Biogeosciences, 10, 1365-1377, doi:10.5194/bg-10-1365-2013, 2013

Abstract

Addition of mineral nitrogen (N) can alter the concentration and quality of dissolved organic matter (DOM) in forest soils. The aim of this study was to assess the effect of long-term mineral N addition on soil solution concentration of dissolved organic carbon (DOC) and dissolved organic nitrogen (DON) in Stråsan experimental forest (Norway spruce) in central Sweden. N was added yearly at two levels of intensity and duration: the N1 treatment represented a lower intensity but a longer duration (43 yr) of N addition than the shorter N2 treatment (24 yr). N additions were terminated in the N2 treatment in 1991. The N treatments began in 1967 when the spruce stands were 9 yr old. Soil solution in the forest floor O, and soil mineral B, horizons were sampled during the growing seasons of 1995 and 2009. Tension and non-tension lysimeters were installed in the O horizon (n = 6), and tension lysimeters were installed in the underlying B horizon (n = 4): soil solution was sampled at two-week intervals. Although tree growth and O horizon carbon (C) and N stock increased in treatments N1 and N2, the concentration of DOC in O horizon leachates was similar in both N treatments and control. This suggests an inhibitory direct effect of N addition on O horizon DOC. Elevated DON and nitrate in O horizon leachates in the ongoing N1 treatment indicated a move towards N saturation. In B horizon leachates, the N1 treatment approximately doubled leachate concentrations of DOC and DON. DON returned to control levels, but DOC remained elevated in B horizon leachates in N2 plots nineteen years after termination of N addition. We propose three possible explanations for the increased DOC in mineral soil: (i) the result of decomposition of a larger amount of root litter, either directly producing DOC or (ii) indirectly via priming of old SOM, and/or (iii) a suppression of extracellular oxidative enzymes.

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