Beyond clay Rasmussen, Craig; Heckman, Katherine; Wieder, William R. ...
Biogeochemistry,
02/2018, Letnik:
137, Številka:
3
Journal Article
Recenzirano
Odprti dostop
Improved quantification of the factors controlling soil organic matter (SOM) stabilization at continental to global scales is needed to inform projections of the largest actively cycling terrestrial ...carbon pool on Earth, and its response to environmental change. Biogeochemical models rely almost exclusively on clay content to modify rates of SOM turnover and fluxes of climate-active CO₂ to the atmosphere. Emerging conceptual understanding, however, suggests other soil physicochemical properties may predict SOM stabilization better than clay content. We addressed this discrepancy by synthesizing data from over 5,500 soil profiles spanning continental scale environmental gradients. Here, we demonstrate that other physicochemical parameters are much stronger predictors of SOM content, with clay content having relatively little explanatory power. We show that exchangeable calcium strongly predicted SOM content in water-limited, alkaline soils, whereas with increasing moisture availability and acidity, iron- and aluminum-oxyhydroxides emerged as better predictors, demonstrating that the relative importance of SOM stabilization mechanisms scales with climate and acidity. These results highlight the urgent need to modify biogeochemical models to better reflect the role of soil physicochemical properties in SOM cycling.
Understanding the controls on the amount and persistence of soil organic carbon (C) is essential for predicting its sensitivity to global change. The response may depend on whether C is unprotected, ...isolated within aggregates, or protected from decomposition by mineral associations. Here, we present a global synthesis of the relative influence of environmental factors on soil organic C partitioning among pools, abundance in each pool (mg C g−1 soil), and persistence (as approximated by radiocarbon abundance) in relatively unprotected particulate and protected mineral‐bound pools. We show that C within particulate and mineral‐associated pools consistently differed from one another in degree of persistence and relationship to environmental factors. Soil depth was the best predictor of C abundance and persistence, though it accounted for more variance in persistence. Persistence of all C pools decreased with increasing mean annual temperature (MAT) throughout the soil profile, whereas persistence increased with increasing wetness index (MAP/PET) in subsurface soils (30–176 cm). The relationship of C abundance (mg C g−1 soil) to climate varied among pools and with depth. Mineral‐associated C in surface soils (<30 cm) increased more strongly with increasing wetness index than the free particulate C, but both pools showed attenuated responses to the wetness index at depth. Overall, these relationships suggest a strong influence of climate on soil C properties, and a potential loss of soil C from protected pools in areas with decreasing wetness. Relative persistence and abundance of C pools varied significantly among land cover types and soil parent material lithologies. This variability in each pool's relationship to environmental factors suggests that not all soil organic C is equally vulnerable to global change. Therefore, projections of future soil organic C based on patterns and responses of bulk soil organic C may be misleading.
In the first global meta‐analysis to examine both radiocarbon and C concentrations among different soil C pools, we found that three critical carbon pools (free particulate, occluded particulate, and mineral associated) respond differently to climate. Moisture had an almost equal influence as temperature on C persistence and abundance, highlighting the need for climate change studies focused on moisture manipulations. The strong variation in pool characteristics and their relationship to environmental factors indicates that we need to go beyond bulk soil carbon measurements to understand and model the responses of soil organic carbon to global change; it is critical to evaluate distinct pools as response variables.
The hydrologic response of upland watersheds is strongly controlled by soil (regolith) thickness. Despite the need to quantify soil thickness for input into hydrologic models, there is currently no ...widely used, geomorphically based method for doing so. In this paper we describe and illustrate a new method for predictive mapping of soil thicknesses using high-resolution topographic data, numerical modeling, and field-based calibration. The model framework works directly with input digital elevation model data to predict soil thicknesses assuming a long-term balance between soil production and erosion. Erosion rates in the model are quantified using one of three geomorphically based sediment transport models: nonlinear slope-dependent transport, nonlinear area- and slope-dependent transport, and nonlinear depth- and slope-dependent transport. The model balances soil production and erosion locally to predict a family of solutions corresponding to a range of values of two unconstrained model parameters. A small number of field-based soil thickness measurements can then be used to calibrate the local value of those unconstrained parameters, thereby constraining which solution is applicable at a particular study site. As an illustration, the model is used to predictively map soil thicknesses in two small, ∼0.1 km2, drainage basins in the Marshall Gulch watershed, a semiarid drainage basin in the Santa Catalina Mountains of Pima County, Arizona. Field observations and calibration data indicate that the nonlinear depth- and slope-dependent sediment transport model is the most appropriate transport model for this site. The resulting framework provides a generally applicable, geomorphically based tool for predictive mapping of soil thickness using high-resolution topographic data sets.
Arid systems represent an important component of the global soil C budget in that they cover 12% of the global land area and contain nearly 20% of global soil C stocks, both organic (SOC) and ...inorganic (SIC). The objectives of this study were to quantify SOC and SIC stocks in Arizona biomes, using Arizona as a model system for arid lands. Biome distribution was extracted from the Arizona Gap Analysis Project spatial vegetation dataset (GAP), while soil C data were extracted from the Arizona State Soil Geographic Dataset (STATSGO) at a scale of 1:250 000, and the western Yavapai County Soil Survey Geographic Dataset (SSURGO) at a scale of 1:24 000. Soil data were converted from a polygonal vector format to a raster format, and a raster‐based method used to estimate SOC and SIC stocks by biome. Statewide, STATSGO soil C stocks indicate Arizona contains 0.5 and 1.5 Pg of SOC and SIC, respectively, with 27% of the SOC in pinyon‐juniper biomes (PJ), and 34% of SIC in creosotebush‐bursage biomes (CB). A comparison of soil C estimates between datasets indicates significantly greater estimates of biome SOC and SIC using SSURGO data relative to the STATSGO data. SSURGO soil C estimates varied considerably between the raster‐based and soil taxa based method of data aggregation. Soil taxa data exhibited large intra‐unit variation in each biome. In addition, soil C differed substantially between biomes by soil taxa (e.g., Haplargid SOC of 4.0 and 13.5 kg m−2 in the paloverde‐cacti (PC) and montane pine (MP) forest biomes, respectively). Raster based soil C estimations incorporate the spatial distribution and areal land cover of each soil type within a biome, providing a more accurate representation of soil C stocks.
Soil thickness determines the soil productivity in the black soil region of northeast China, which is important for national food security. Existing information on the spatial variation of black soil ...thickness is inadequate. In this paper, we propose a model framework for spatial estimation of the black soil thickness at the watershed scale by integrating field observations, unmanned aerial vehicle variations of topography, and satellite variations of vegetation with the aid of random forest. We sampled 141 sample profiles over a watershed and identified the black soil thickness based on indices of the mollic epipedon. Topographic variables were derived from a digital elevation model and vegetation variables were derived from Landsat 8 imagery. Random forest was used to determine the relationship between black soil thickness and environmental variables. The resulting model explained 61% of the black soil thickness spatial variation, which was more than twice that of traditional interpolation methods (ordinary kriging, universal kriging and inverse distance weighting). Topographic variables contributed the most toward explaining the thickness, followed by vegetation indices. The black soil thickness over the watershed had a clear catenary soil pattern, with thickest black soil in the low depositional areas and thinnest at the higher elevations that drain into the low areas. The proposed model framework will improve estimates of soil thickness in the region of our study.
Soil organic matter (SOM) turnover increasingly is conceptualized as a tension between accessibility to microorganisms and protection from decomposition via physical and chemical association with ...minerals in emerging soil biogeochemical theory. Yet, these components are missing from the original mathematical models of belowground carbon dynamics and remain underrepresented in more recent compartmental models that separate SOM into discrete pools with differing turnover times. Thus, a gap currently exists between the emergent understanding of SOM dynamics and our ability to improve terrestrial biogeochemical projections that rely on the existing models. In this opinion paper, we portray the SOM paradigm as a triangle composed of three nodes: conceptual theory, analytical measurement, and numerical models. In successful approaches, we contend that the nodes are connected—models capture the essential features of dominant theories while measurement tools generate data adequate to parameterize and evaluate the models—and balanced— models can inspire new theories via emergent behaviors, pushing empiricists to devise new measurements. Many exciting advances recently pushed the boundaries on one or more nodes. However, newly integrated triangles have yet to coalesce. We conclude that our ability to incorporate mechanisms of microbial decomposition and physicochemical protection into predictions of SOM change is limited by current disconnections and imbalances among theory, measurement, and modeling. Opportunities to reintegrate the three components of the SOM paradigm exist by carefully considering their linkages and feedbacks at specific scales of observation.
Basalt rocks occupy substantial land area and play a significant role in global weathering patterns and biogeochemical cycling. The objective of this research was to quantify climatic controls of ...weathering and pedogenic processes on basalt-derived soils across an environmental gradient on the western slope of the Casacade Range of California, USA. We hypothesized that climate controls mineral neogenesis, with cool, moist conditions favoring formation of short-range-order (SRO) materials and warm, dry conditions favoring smectite, crystalline Fe-oxyhydroxides and kaolins. Four pedons were sampled across an elevation gradient (250–2500 m) having large variation in mean annual soil temperature (5–17 °C) and mean annual precipitation (750–1350 mm). The soil mineral assemblage was characterized by X-ray diffraction, selective dissolution, total elemental analysis and light microscopy. The degree of weathering and mineral assemblage exhibited a clear threshold at the permanent winter snowline (~
1200 m). Maximum soil development was noted just below the snowline with soils dominated by kaolinite and dehydrated halloysite, crystalline Fe-oxyhydroxides (48 kg m
−
2
), extensive loss of cations (chemical index of alteration, CIA >
95%) and clay accumulation (447 kg m
−
2
). In contrast, the high elevation snow-dominated pedons displayed less intense weathering (e.g., CIA <
75% and clay <
25 kg m
−
2
) and a mineral assemblage dominated by primary minerals and SRO materials. The cool, moist conditions of mid-altitude (~
1600 m) soils appear optimum for the formation and preservation of SRO materials (allophane
=
30 kg m
−
2
). All pedons contained hydroxy-Al interlayered smectite that was either neogenic or derived from eolian minerals. With increasing elevation soil development followed Alfisols
→
Ultisols
→
Andisols
→
Entisols, in agreement with similar gradients in the California Sierra Nevada. Weathering, mineralogical transformations and soil development are limited by water availability at low elevations, whereas low soil temperature is the major limitation at high elevations.
The green fraction of humic acid (Pg) and the chloroform-extractable green fraction (CEGF) are characteristic soil organic matter (SOM) components. These alkaline solutions are green-colored due to ...the presence of 4,9-dihydroxyperylene-3,10-quinone (DHPQ) chromophore. While both of which are potential indicators for the effect of land use and paleoclimatic environment in the fields of soil science as well as geochemistry, CEGF as well as its relationship with Pg in soils are not yet fully documented. In this study, we firstly investigated the chemical properties of soil CEGF fractions by ultraviolet-visible (UV-Vis) and infrared (IR) method. Two CEGF components were separated by sequential liquid-liquid extraction using aqueous ammonium hydroxide (NH
4
OH) followed by aqueous sodium hydroxide (NaOH). Results showed that the UV-Vis spectral shape of NH
4
OH-extractable component is very similar to that of DHPQ, except that it is red-shifted. The solubility and UV-Vis spectrum of the NaOH-extractable fraction were completely identical with those of synthesized DHPQ. Their IR spectral shapes were also almost the same. Subsequently, the distribution of CEGF in humic acid (HA), fulvic acid (FA) and humin (HN) from Japanese Andosols and Cambisol was quantitatively evaluated by sequential extraction. Most of CEGF was detected in the HA (60-78%) and HN (22-40%), but not in the FA. While the UV-Vis spectral shape of CEGF extracted from Andosols HAs showed a relatively higher proportion of DHPQ than its derivative, the opposite was observed in Cambisol HA, whose CEGF is similar to that of sclerotium grain (one of the possible origin of CEGF). These results suggest the diversity of CEGF-producing soil fungi. Quantitative data also indicated that 35-49% of Pg consisted of a chloroform-soluble fraction (i.e., CEGF) and the remaining 51-65% of Pg was chloroform-insoluble. Based on these results, we propose that CEGF is composed of DHPQ and DHPQ-derivatives and that CEGF is one of the major fractions of Pg.
Conceptual energy-based pedogenic models present a framework for quantitatively linking pedon energy throughflow to soil development. In this study, we utilized a quantitative pedogenic energy model ...(QPEM) based on rates of effective energy and mass transfer (EEMT, kJ m-2 yr-1) to the soil system to predict pedogenesis across a wide range of pedogenic environments. Our objectives were to: (i) derive a global equation for estimating EEMT; (ii) test the QPEM framework at the pedon scale across a series of environmental gradients on igneous rock residuum; and (iii) develop quantitative transfer functions between pedogenic indices and EEMT. We derived a simplified two-dimensional Gaussian expression for estimating EEMT from mean annual temperature (MAT) and mean annual precipitation (MAP) (R2 = 0.96, significant at P <or= 0.001) using a global climate data set. Environmental gradient data indicated significant differences in EEMT between soil orders (i.e., Entisol = 14,586 vs. Ultisol = 36,521 kJ m-2 yr-1), whereas neither MAT nor MAP demonstrated significant differences among soil orders. Pedon data from the gradients were used to derive quantitative transfer functions between EEMT and pedogenic indices, including pedon depth, clay content, subsurface chemical index of alteration minus potassium (CIA-K), and the ratio of free Fe oxides to total Fe (Fe(d)/Fe(T)). Significant linear and nonlinear functions were derived between EEMT and all of the pedogenic indices, whereas no significant functions could be fit between pedogenic indices, MAT, or MAP. The favorable results from this study suggest that the QPEM framework and EEMT may provide a basis for quantitative pedogenic modeling and prediction of soil properties.
PDF
