Terra Rossa catenas in Wisconsin, USA

Evans, D.M.; Hartemink, Alfred E.

doi:10.1016/j.catena.2014.07.007

Cited by 12 publications

(7 citation statements)

References 25 publications

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“…The variability in SOC distribution was mostly shortranged (<145 m). This distance also corresponded to the length of few catenas sampled from the same study area (Evans and Hartemink, 2014b). For the predicted maps, as expected the results showed that soils under forest contained more C than soils under pasture and crop lands, which is common (Arrouays et al, 2001;Arrouays and Pelissier, 1994;Grigal and Ohmann, 1992;Minasny et al, 2006).…”

Section: Discussionsupporting

confidence: 66%

Digital Mapping of Topsoil Carbon Content and Changes in the Driftless Area of Wisconsin, USA

Adhikari

Hartemink

2015

Soil Science Society of America Journal

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We mapped topsoil (0-20 cm) soil organic C (SOC) content in a 5200-ha site and identified key variables affecting SOC distribution in the Driftless area where Alfisols and Mollisols are common. About 47% of the area was under arable crops, 22% under pasture, 21% under forest, and the remaining 10% under roads, constructions, and others. Condition-based regression rules were used to predict SOC using 13 environmental variables. The average C content of the soils was 23 g kg -1 and topsoils under forest had the highest levels of SOC (28 g kg -1 ). There was little difference in SOC contents of the different soil orders, but Inceptisols contained more SOC than Alfisols and Mollisols. Land use, soil order, and terrain parameters, such as elevation, insolation, wetness index were the key variables affecting SOC distribution. The highest prediction error was observed in the soils from the forest followed by pasture and crop lands. We also estimated SOC changes using the Projected Natural Vegetation Soil Carbon (PNVSC) approach as a reference to which the present day SOC predicted map was compared. The PNVSC represents a SOC map that would be observed in the landscape today if the area had remained under natural vegetation. Based on this approach, soils under forest had accumulated on average >2 g kg -1 , whereas crop land and pasture had lost 1.8 to 2.0 g kg -1 SOC in about 10 yr. There was a relation between soil orders, land use, and SOC levels; and we have spatially quantified this relationship including an estimate of the uncertainty.Abbreviations: AIC, Akaike information criteria; CV, coefficient of variation; DEM, digital elevation model; DSM, digital soil mapping; EBK, empirical bayesian kriging; LSP, land surface parameter; ME, mean error; NSR, nugget-to-sill ratio; PNVSC, projected natural vegetation soil carbon; RI, relative importance; SOC, soil organic carbon.

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Section: Discussionsupporting

confidence: 66%

Digital Mapping of Topsoil Carbon Content and Changes in the Driftless Area of Wisconsin, USA

Adhikari

Hartemink

2015

Soil Science Society of America Journal

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“…A total of 14 data sets (Alexandrovskiy, ; Bockheim & Tarnocai, ; Borman et al, ; Colman & Pierce, ; Evans & Hartemink, ; Goodman et al, ; Heimsath, Chappell, Dietrich, et al, ; Jacobson et al, ; McFadden & Weldon, ; Pillans, ; Schüli‐Maurer et al, ; Stevens, ; Vanden Bygaart and Protz, ; White et al, ) were accessed (Hunt, ) for comparison. They were selected for a wide range of conditions and locations, including alpine, semiarid alluvium, tropical, terra cotta loess, humid temperate lowland, and Antarctic dry valleys.…”

Section: Solute Transport and Hydrodynamic Dispersionmentioning

confidence: 99%

Flow, Transport, and Reaction in Porous Media: Percolation Scaling, Critical‐Path Analysis, and Effective Medium Approximation

Hunt

Sahimi

2017

Reviews of Geophysics

141

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We describe the most important developments in the application of three theoretical tools to modeling of the morphology of porous media and flow and transport processes in them. One tool is percolation theory. Although it was over 40 years ago that the possibility of using percolation theory to describe flow and transport processes in porous media was first raised, new models and concepts, as well as new variants of the original percolation model are still being developed for various applications to flow phenomena in porous media. The other two approaches, closely related to percolation theory, are the critical‐path analysis, which is applicable when porous media are highly heterogeneous, and the effective medium approximation—poor man's percolation—that provide a simple and, under certain conditions, quantitatively correct description of transport in porous media in which percolation‐type disorder is relevant. Applications to topics in geosciences include predictions of the hydraulic conductivity and air permeability, solute and gas diffusion that are particularly important in ecohydrological applications and land‐surface interactions, and multiphase flow in porous media, as well as non‐Gaussian solute transport, and flow morphologies associated with imbibition into unsaturated fractures. We describe new applications of percolation theory of solute transport to chemical weathering and soil formation, geomorphology, and elemental cycling through the terrestrial Earth surface. Wherever quantitatively accurate predictions of such quantities are relevant, so are the techniques presented here. Whenever possible, the theoretical predictions are compared with the relevant experimental data. In practically all the cases, the agreement between the theoretical predictions and the data is excellent. Also discussed are possible future directions in the application of such concepts to many other phenomena in geosciences.

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“…Data for the temporal evolution of the depths of 21 soils from around the world (the Baltic, Australia, Czech Republic, Wisconsin, the Himalayas, Peru, Norway, California, Canada, New Zealand, Antarctica, Idaho, China, Oregon, Washington, and others: Alexandrovskiy, 2007; Bockheim and Tarnocai, 1998; Bormann et al, 1995; Colman and Pierce, 1986; Evans and Hartemink, 2014; Goodman et al, 2001; Jacobson et al, 2002; McFadden and Weldon, 1987; Pillans, 1997; Schülli‐Maurer et al, 2007; Stevens, 1968; VandenBygaart and Protz, 1995; White et al, 1996; Heimsath et al, 2001a; Frouz et al, 2008; Li et al, 2007; Smale et al, 1997; Mavris et al, 2010; Trustrum and de Rose, 1988; Dethier, 1988; Almond et al, 2007) were accessed and transcribed or digitized. Of these soils, eight individual examples were compatible with the slope of the scaling relationship, and five of those also with the specific numerical value of the prefactor.…”

Section: Comparison With Datamentioning

confidence: 99%

Spatio‐temporal Scaling of Vegetation Growth and Soil Formation from Percolation Theory

Hunt

2015

Vadose Zone Journal

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Core Ideas Solute or nutrient transport limits soil formation and vegetation growth Limitations on solute transport can only be understood within non‐Gaussian theories Three scaling relationships have a common origin in space and time Nutrient transport constraints limit vascular plant growth Solute transport constraints limit soil development Critical path analysis (CPA) is suited to calculating the hydraulic conductivity, K, of heterogeneous porous media by quantifying the paths of least resistance. Whenever CPA can be used to calculate K, advective transport scaling relationships from percolation theory should describe solute transport. Two solute transport relationships were applied to predict soil development and edaphic constraints on natural vegetation growth. These results used known exponents from percolation theory and known subsurface flow velocities. The typical flow velocity itself constrains the optimal growth rates of cultivars. The percolation scaling relationship constraining vegetation growth was shown to be in accord with data across time scales from hours to 100,000 yr, including more than a dozen studies (and two models) of tree growth. The scaling function for soil development explains time scales for the formation of soils from years to hundreds of millions of years. Data on soil development came from 23 different studies. The key unification is the common origin of the time and space coordinates for all three relationships in the transport time through a single pore of roughly micrometer size at a typical subsurface pore‐scale flow velocity. The distinction in evolving time scales is primarily a result of the hierarchical nature of vascular plant root systems, which speed up nutrient access relative to physical transport rates in the soil. The results help explain reductions in forest productivity with age, diminishing soil production with time, and the temporal distinction between chemical and biological processes in soils and their relevance to the global C cycle.

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Terra Rossa catenas in Wisconsin, USA

Cited by 12 publications

References 25 publications

Digital Mapping of Topsoil Carbon Content and Changes in the Driftless Area of Wisconsin, USA

Digital Mapping of Topsoil Carbon Content and Changes in the Driftless Area of Wisconsin, USA

Flow, Transport, and Reaction in Porous Media: Percolation Scaling, Critical‐Path Analysis, and Effective Medium Approximation

Spatio‐temporal Scaling of Vegetation Growth and Soil Formation from Percolation Theory

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