Literature DB >> 24636454

Landscape scale estimation of soil carbon stock using 3D modelling.

F Veronesi1, R Corstanje1, T Mayr1.   

Abstract

Soil C is the largest pool of carbon in the terrestrial biosphere, and yet the processes of C accumulation, transformation and loss are poorly accounted for. This, in part, is due to the fact that soil C is not uniformly distributed through the soil depth profile and most current landscape level predictions of C do not adequately account the vertical distribution of soil C. In this study, we apply a method based on simple soil specific depth functions to map the soil C stock in three-dimensions at landscape scale. We used soil C and bulk density data from the Soil Survey for England and Wales to map an area in the West Midlands region of approximately 13,948 km(2). We applied a method which describes the variation through the soil profile and interpolates this across the landscape using well established soil drivers such as relief, land cover and geology. The results indicate that this mapping method can effectively reproduce the observed variation in the soil profiles samples. The mapping results were validated using cross validation and an independent validation. The cross-validation resulted in an R(2) of 36% for soil C and 44% for BULKD. These results are generally in line with previous validated studies. In addition, an independent validation was undertaken, comparing the predictions against the National Soil Inventory (NSI) dataset. The majority of the residuals of this validation are between ± 5% of soil C. This indicates high level of accuracy in replicating topsoil values. In addition, the results were compared to a previous study estimating the carbon stock of the UK. We discuss the implications of our results within the context of soil C loss factors such as erosion and the impact on regional C process models.
Copyright © 2014 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  3 Dimensional maps; Carbon stock estimates; Soil C landscapes; Soil carbon

Mesh:

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Year:  2014        PMID: 24636454     DOI: 10.1016/j.scitotenv.2014.02.061

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  3 in total

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Authors:  Tobias Rentschler; Philipp Gries; Thorsten Behrens; Helge Bruelheide; Peter Kühn; Steffen Seitz; Xuezheng Shi; Stefan Trogisch; Thomas Scholten; Karsten Schmidt
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  3 in total

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