Articles | Volume 4, issue 2
https://doi.org/10.5194/soil-4-123-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/soil-4-123-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Original research article
| 
29 May 2018
Original research article |
| 29 May 2018
| 29 May 2018
Uncertainty indication in soil function maps – transparent and easy-to-use information to support sustainable use of soil resources
Lucie Greiner
CORRESPONDING AUTHOR
Swiss Soil Monitoring Network (NABO), Agroscope, 8046 Zurich,
Switzerland
Madlene Nussbaum
School of Agricultural, Forest and Food Science (HAFL), Bern
University of Applied Sciences (BFH), 3052 Zollikofen, Switzerland
Andreas Papritz
Institute of Biogeochemistry and Pollutant Dynamics, Swiss Federal
Institute of Technology (ETH), 8092 Zurich, Switzerland
Stephan Zimmermann
Forest Soils and Biogeochemistry, Soil Functions and Soil Protection,
Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), 8903
Birmensdorf, Switzerland
Andreas Gubler
Swiss Soil Monitoring Network (NABO), Agroscope, 8046 Zurich,
Switzerland
Adrienne Grêt-Regamey
Planning of Landscape and Urban Systems, Swiss Federal Institute of
Technology (ETH), 8093 Zurich, Switzerland
Armin Keller
Swiss Soil Monitoring Network (NABO), Agroscope, 8046 Zurich,
Switzerland
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Digital soil mapping (DSM) relates soil property data to environmental data that describe soil-forming factors. With imagery sampled from satellites or terrain analysed at multiple scales, large sets of possible input to DSM are available. We propose a new statistical framework (geoGAM) that selects parsimonious models for DSM and illustrate the application of geoGAM to two study regions. Straightforward interpretation of the modelled effects likely improves end-user acceptance of DSM products.
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We developed the Swiss mid-infrared spectral library and a statistical model collection across 4374 soil samples with reference measurements of 16 properties. Our library incorporates soil from 1094 grid locations and 71 long-term monitoring sites. This work confirms once again that nationwide spectral libraries with diverse soils can reliably feed information to a fast chemical diagnosis. Our data-driven reduction of the library has the potential to accurately monitor carbon at the plot scale.
Anatol Helfenstein, Philipp Baumann, Raphael Viscarra Rossel, Andreas Gubler, Stefan Oechslin, and Johan Six
SOIL, 7, 193–215, https://doi.org/10.5194/soil-7-193-2021, https://doi.org/10.5194/soil-7-193-2021, 2021
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Emily F. Solly, Valentino Weber, Stephan Zimmermann, Lorenz Walthert, Frank Hagedorn, and Michael W. I. Schmidt
Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-33, https://doi.org/10.5194/bg-2019-33, 2019
Revised manuscript not accepted
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Soils are the largest reservoir of carbon on land. In the context of global change, it is important to assess which environmental variables are needed to describe changes in the content of soil organic carbon. We assessed how climatic, vegetation and edaphic variables explain the variance of soil organic carbon content in Swiss forests. Our results provide a first indication that considering the effective cation exchange capacity of soils in future biogeochemical simulations could be beneficial.
Madlene Nussbaum, Kay Spiess, Andri Baltensweiler, Urs Grob, Armin Keller, Lucie Greiner, Michael E. Schaepman, and Andreas Papritz
SOIL, 4, 1–22, https://doi.org/10.5194/soil-4-1-2018, https://doi.org/10.5194/soil-4-1-2018, 2018
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This paper presents an extensive evaluation of digital soil mapping (DSM) tools. Recently, large sets of environmental covariates (e.g. from analysis of terrain on multiple scales) have become more common for DSM. Many DSM studies, however, only compared DSM methods using less than 30 covariates or tested approaches on few responses. We built DSM models from 300–500 covariates using six approaches that are either popular in DSM or promising for large covariate sets.
Madlene Nussbaum, Lorenz Walthert, Marielle Fraefel, Lucie Greiner, and Andreas Papritz
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Digital soil mapping (DSM) relates soil property data to environmental data that describe soil-forming factors. With imagery sampled from satellites or terrain analysed at multiple scales, large sets of possible input to DSM are available. We propose a new statistical framework (geoGAM) that selects parsimonious models for DSM and illustrate the application of geoGAM to two study regions. Straightforward interpretation of the modelled effects likely improves end-user acceptance of DSM products.
M. Teich, J.-T. Fischer, T. Feistl, P. Bebi, M. Christen, and A. Grêt-Regamey
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M. Nussbaum, A. Papritz, A. Baltensweiler, and L. Walthert
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Soil as a resource
Long-term field experiments in Germany: classification and spatial representation
Adsorption to soils and biochemical characterization of commercial phytases
Development of a harmonised soil profile analytical database for Europe: a resource for supporting regional soil management
Arable soil formation and erosion: a hillslope-based cosmogenic nuclide study in the United Kingdom
Assessment and quantification of marginal lands for biomass production in Europe using soil-quality indicators
Physical, chemical, and mineralogical attributes of a representative group of soils from the eastern Amazon region in Brazil
A systemic approach for modeling soil functions
Soil conservation in the 21st century: why we need smart agricultural intensification
World's soils are under threat
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Meike Grosse, Wilfried Hierold, Marlen C. Ahlborn, Hans-Peter Piepho, and Katharina Helming
SOIL, 6, 579–596, https://doi.org/10.5194/soil-6-579-2020, https://doi.org/10.5194/soil-6-579-2020, 2020
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Agricultural long-term field experiments (LTFEs) are an important basis for soil and agricultural sciences. A compilation of metadata and research data from LTFEs in Germany shall enhance networking and simplify the access to this most valuable research infrastructure. The common analyses of similar LTFEs on different sites can broaden the results. Therefore, LTFEs were classified and their distribution in Germany was compared to three site classifications.
María Marta Caffaro, Karina Beatriz Balestrasse, and Gerardo Rubio
SOIL, 6, 153–162, https://doi.org/10.5194/soil-6-153-2020, https://doi.org/10.5194/soil-6-153-2020, 2020
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Four commercial phytases were evaluated as candidates to be used as biological fertilizer to release inorganic phosphorus (P) from phytates and other soil P organic forms. All phytases were able to release inorganic P throughout the pH and temperature ranges for optimum crop production and had a low affinity for the solid phase, with some differences between them. These results indicate that the use of phytases to complement P fertilization may be a feasible tool to enhance soil P availability.
Jeppe Aagaard Kristensen, Thomas Balstrøm, Robert J. A. Jones, Arwyn Jones, Luca Montanarella, Panos Panagos, and Henrik Breuning-Madsen
SOIL, 5, 289–301, https://doi.org/10.5194/soil-5-289-2019, https://doi.org/10.5194/soil-5-289-2019, 2019
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In a world of increasing pressure on our environment, large-scale knowledge about our soil resources is in high demand. We show how five decades of collaboration between EU member states resulted in a full-coverage soil profile analytical database for Europe (SPADE), with soil data provided by soil experts from each country. We show how the dataset can be applied to estimate soil organic carbon in Europe and suggest further improvement to this critical support tool in continental-scale policies.
Daniel L. Evans, John N. Quinton, Andrew M. Tye, Ángel Rodés, Jessica A. C. Davies, Simon M. Mudd, and Timothy A. Quine
SOIL, 5, 253–263, https://doi.org/10.5194/soil-5-253-2019, https://doi.org/10.5194/soil-5-253-2019, 2019
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Policy to conserve thinning arable soils relies on a balance between the rates of soil erosion and soil formation. Our knowledge of the latter is meagre. Here, we present soil formation rates for an arable hillslope, the first of their kind globally, and a woodland hillslope, the first of their kind in Europe. Rates range between 26 and 96 mm kyr−1. On the arable site, erosion rates are 2 orders of magnitude greater, and in a worst-case scenario, bedrock exposure could occur in 212 years.
Werner Gerwin, Frank Repmann, Spyridon Galatsidas, Despoina Vlachaki, Nikos Gounaris, Wibke Baumgarten, Christiane Volkmann, Dimitrios Keramitzis, Fotis Kiourtsis, and Dirk Freese
SOIL, 4, 267–290, https://doi.org/10.5194/soil-4-267-2018, https://doi.org/10.5194/soil-4-267-2018, 2018
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The need for biomass for energetic or material use is increasing parallel to the need to extend the production of food for a growing world population. This results in conflicts between both land use strategies. Use of marginal lands could solve this conflict, however, the understanding of marginal lands and the knowledge of their potentials are still not fully developed. We present an approach to assess land marginality based on soil quality and an estimation of land potentials all over Europe.
Edna Santos de Souza, Antonio Rodrigues Fernandes, Anderson Martins De Souza Braz, Fábio Júnior de Oliveira, Luís Reynaldo Ferracciú Alleoni, and Milton César Costa Campos
SOIL, 4, 195–212, https://doi.org/10.5194/soil-4-195-2018, https://doi.org/10.5194/soil-4-195-2018, 2018
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The study refers to a survey of the attributes of the main soil classes of the state of Pará, an eastern Amazon region in Brazil. These soils have good potential for agricultural use under natural conditions. In this study we observed that the soils are predominantly kaolinitic, but have relatively low aluminum and organic matter contents, with huge textural variability. The results enable a better understanding of eastern Amazonian soils, whose area reaches more than 1.2 million km2.
Hans-Jörg Vogel, Stephan Bartke, Katrin Daedlow, Katharina Helming, Ingrid Kögel-Knabner, Birgit Lang, Eva Rabot, David Russell, Bastian Stößel, Ulrich Weller, Martin Wiesmeier, and Ute Wollschläger
SOIL, 4, 83–92, https://doi.org/10.5194/soil-4-83-2018, https://doi.org/10.5194/soil-4-83-2018, 2018
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This paper deals with the importance of soil for our terrestrial environment and the need to predict the impact of soil management on the multitude of functions that soil provides. We suggest to consider soil as a self-organized complex system and provide a concept of how this could be achieved. This includes how soil research, currently fragmented into a number of more or less disjunct disciplines, may be integrated to substantially contribute to a science-based evaluation of soil functions.
Gerard Govers, Roel Merckx, Bas van Wesemael, and Kristof Van Oost
SOIL, 3, 45–59, https://doi.org/10.5194/soil-3-45-2017, https://doi.org/10.5194/soil-3-45-2017, 2017
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We discuss pathways towards better soil protection in the 21st century. The efficacy of soil conservation technology is not a fundamental barrier for a more sustainable soil management. However, soil conservation is generally not directly beneficial to the farmer. We believe that the solution of this conundrum is a rapid, smart intensification of agriculture in the Global South. This will reduce the financial burden and will, at the same time, allow more effective conservation.
Luca Montanarella, Daniel Jon Pennock, Neil McKenzie, Mohamed Badraoui, Victor Chude, Isaurinda Baptista, Tekalign Mamo, Martin Yemefack, Mikha Singh Aulakh, Kazuyuki Yagi, Suk Young Hong, Pisoot Vijarnsorn, Gan-Lin Zhang, Dominique Arrouays, Helaina Black, Pavel Krasilnikov, Jaroslava Sobocká, Julio Alegre, Carlos Roberto Henriquez, Maria de Lourdes Mendonça-Santos, Miguel Taboada, David Espinosa-Victoria, Abdullah AlShankiti, Sayed Kazem AlaviPanah, Elsiddig Ahmed El Mustafa Elsheikh, Jon Hempel, Marta Camps Arbestain, Freddy Nachtergaele, and Ronald Vargas
SOIL, 2, 79–82, https://doi.org/10.5194/soil-2-79-2016, https://doi.org/10.5194/soil-2-79-2016, 2016
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The Intergovernmental Technical Panel on Soils has completed the first State of the World's Soil Resources Report. The gravest threats were identified for all the regions of the world. This assessment forms a basis for future soil monitoring. The quality of soil information available for policy formulation must be improved.
M. Köchy, R. Hiederer, and A. Freibauer
SOIL, 1, 351–365, https://doi.org/10.5194/soil-1-351-2015, https://doi.org/10.5194/soil-1-351-2015, 2015
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Soils contain 1062Pg organic C (SOC) in 0-1m depth based on the adjusted Harmonized World Soil Database. Different estimates of bulk density of Histosols cause an uncertainty in the range of -56/+180Pg. We also report the frequency distribution of SOC stocks by continent, wetland type, and permafrost type. Using additional estimates for frozen and deeper soils, global soils are estimated to contain 1325Pg SOC in 0-1m and ca. 3000Pg, including deeper layers.
Cited articles
Adhikari, K. and Hartemink, A. E.: Linking soils to ecosystem services – A global review, Geoderma, 262, 101–111, https://doi.org/10.1016/j.geoderma.2015.08.009, 2016.
Bastin, L., Cornford, D., Jones, R., Heuvelink, G. B. M., Pebesma, E., Stasch, C., Nativi, S., Mazzetti, P., and Williams, M.: Managing uncertainty in integrated environmental modelling: The UncertWeb framework, Environ. Modell. Softw., 39, 116–134, https://doi.org/10.1016/j.envsoft.2012.02.008, 2013.
Bechler, K. and Toth, O.: Bewertung von Böden nach ihrer Leistungsfähigkeit, Leitfaden für Planungen und Gestattungsverfahren (LUBW), Karlsruhe, Germany, 36 pp., ISBN: 978-3-88251-349-3, 2010.
BFS: Arealstatistik (AS09_72), Bundesamt für Statistik (BFS), Bern, Switzerland, 2010.
BLW: Minimales Geodatenmodell: 77.1 Klimaeignungskarte für die Landwirtschaft, Bundesamt für Landwirtschaft/Federal Office of Agriculture, Bern, Switzerland, 2012.
Bouma, J.: Implications of the Knowledge Paradox for Soil Science, in: Advances in Agronomy, edited by: Sparks, D. L., Elsevier, San Diego, USA, 106, 143–171, 2010.
Bouma, J.: Soil science contributions towards Sustainable Development Goals and their implementation: linking soil functions with ecosystem services, J. Plant Nutr. Soil Sci., 177, 111–120, https://doi.org/10.1002/jpln.201300646, 2014.
Brown, J. D., Heuvelink, G., and Refsgaard, J.: An integrated methodology for recording uncertainties about environmental data, Water Sci. Technol., 52, 153–160, 2005.
Budescu, D. V.: Improving communication of uncertainty in the IPCC reports, in Advance paper submitted to the IPCC Expert Meeting on Communication, Oslo, Norway, 9–10 February 2016, p. 3., 2016.
Calzolari, C., Ungaro, F., Filippi, N., Guermandi, M., Malucelli, F., Marchi, N., Staffilani, F., and Tarocco, P.: A methodological framework to assess the multiple contributions of soils to ecosystem services delivery at regional scale, Geoderma, 261, 190–203, 2016.
Campbell, G. A., Lilly, A., Corstanje, R., Mayr, T. R., and Black, H. I. J.: Are existing soils data meeting the needs of stakeholders in Europe? An analysis of practical use from policy to field, Land Use Policy, 69, 211–223, https://doi.org/10.1016/j.landusepol.2017.09.016, 2017.
Chirico, G. B., Medina, H., and Romano, N.: Functional evaluation of PTF prediction uncertainty: An application at hillslope scale, Geoderma, 155, 193–202, https://doi.org/10.1016/J.GEODERMA.2009.06.008, 2010.
Danner, C., Henshold, C., Weidenhammer, S., Aussendorf, M., Kraft, M., Weidenbacher, A., and Kölling, C.: Das Schutzgut Boden in der Planung. Bewertung natürlicher Bodenfunktionen und Umsetzung in Planungs- und Genehmigungsverfahren, Bayerisches Geologisches Landesamt, Bayerisches Landesamt für Umweltschutz, 2003.
Dominati, E., Patterson, M., and Mackay, A.: A framework for classifying and quantifying the natural capital and ecosystem services of soils, Ecol. Econ., 69, 1858–1868, https://doi.org/10.1016/j.ecolecon.2010.05.002, 2010.
Dominati, E., Mackay, A., Green, S., and Patterson, M.: A soil change-based methodology for the quantification and valuation of ecosystem services from agro-ecosystems: A case study of pastoral agriculture in New Zealand, Ecol. Econ., 100, 119–129, https://doi.org/10.1016/j.ecolecon.2014.02.008, 2014.
DVWK (Deutscher Verband für Wasserwirtschaft und Kulturbau): Filtereigenschaften des Bodens gegenüber Schadstoffen. Teil I: Beurteilung der Fähigkeit von Böden, zugeführte Schwermetalle zu immobilisieren, Merkblätter zur Wasserwirtschaft, Verlag Paul Parey, Hamburg and Berlin, Germany, 1988.
EC: Thematic Strategy for Soil Protection, Commission of the European Communities, Brussels, Belgium, 12 pp., 2006.
FAO: Soil organic carbon mapping cookbook, Food and Agriculture Organization of the United Nations, Rome, Italy, available at: http://www.fao.org/3/a-bs901e.pdf (last access: 17 July 2018), 2017.
Franzen, J., Müller, M., and Keller, A.: Einsatz von Pflanzenschutzmitteln im Messnetz der Nationalen Bodenbeobachtung (NABO) von 1985 bis 2013, Agroscope, in preparation, 2017.
Gerber, C.: Funktionale Bodenbewertung Lyss. Die Erstellung von Bodenfunktionskarten für das Kartenblatt Lyss, University of Bern, Bern, Switzerland, 2014.
Greiner, L., Keller, A., Grêt-Regamey, A., and Papritz, A.: Soil function assessment: review of methods for quantifying the contributions of soils to ecosystem services, Land Use Policy, 69, 224–237, https://doi.org/10.1016/j.landusepol.2017.06.025, 2017.
Grêt-Regamey, A., Altwegg, J., Sirén, E. A., van Strien, M. J., and Weibel, B.: Integrating ecosystem services into spatial planning – A spatial decision support tool, Landscape Urban Plan., 165, 206–219, https://doi.org/10.1016/j.landurbplan.2016.05.003, 2017.
Gubler, A., Schwab, P., Wächter, D., Meuli, R., and Keller, A.: Ergebnisse der Nationalen Bodenbeobachtung (NABO) 1985–2009: Zustand und Veränderungen der anorganischen Schadstoffe und Bodenbegleitparameter, BAFU Umwelt-Zustand 1507, 1–81, 2015.
HADES: Hydrologischer Atlas der Schweiz, University of Bern, Bern, Switzerland, 15 May 2017, available at: https://hydromaps.ch/#de/8/46.830/8.193/bl_hds (last access: 7 May 2018), 2017.
Haslmayr, H.-P., Geitner, C., Sutor, G., Knoll, A., and Baumgarten, A.: Soil function evaluation in Austria – Development, concepts and examples, Geoderma, 264, 379–387, https://doi.org/10.1016/j.geoderma.2015.09.023, 2016.
Haygarth, P. M. and Ritz, K.: The future of soils and land use in the UK: Soil systems for the provision of land-based ecosystem services, Land Use Policy, 26, Supplement S187–S197, https://doi.org/10.1016/j.landusepol.2009.09.016, 2009.
Heuvelink, G. B. M., Brown, J. D., and van Loon, E. E.: A probabilistic framework for representing and simulating uncertain environmental variables, Int. J. Geogr. Inf. Sci., 21, 497–513, https://doi.org/10.1080/13658810601063951, 2007.
Heuvelink, G. B. M., Burgers, S. L. G. E., Tiktak, A., and Den Berg, F. Van: Uncertainty and stochastic sensitivity analysis of the GeoPEARL pesticide leaching model, Geoderma, 155, 186–192, https://doi.org/10.1016/j.geoderma.2009.07.004, 2010.
Höllermann, B. and Evers, M.: Perception and handling of uncertainties in water management – A study of practitioners' and scientists' perspectives on uncertainty in their daily decision-making, Environ. Sci. Policy, 71, 9–18, https://doi.org/10.1016/j.envsci.2017.02.003, 2017.
IOM: Environmental Decisions in the Face of Uncertainty, The National Academies Press, Washington D.C., USA, 2013.
Jäggli, F., Peyer, K., Pazeller, A., and Schwab, P.: Grundlagenbericht zur Bodenkartierung des Kantons Zürich, Landwirtschaftsareal, Eidgenössische Forschungsanstalt für Agrarökologie und Landbau (FAL), Zurich-Reckenholz, Switzerland, 1998.
Jensen, J., Larsen, M. M., and Bak, J.: National monitoring study in Denmark finds increased and critical levels of copper and zinc in arable soils fertilized with pig slurry, Environ. Pollut., 214, 334–340, https://doi.org/10.1016/j.envpol.2016.03.034, 2016.
KA5: Bodenkundliche Kartieranleitung, 5. Auflage, Bundesanstalt für Geowissenschaften und Rohstoffe (BGR), Staatliche Geologische Dienste der Bundesrepublik Deutschland, Hannover, Germany, 2005.
Keller, A. and Schulin, R.: Modelling regional-scale mass balances of phosphorus, cadmium and zinc fluxes on arable and dairy farms, Eur. J. Agron., 20, 181–198, https://doi.org/10.1016/S1161-0301(03)00075-3, 2003.
Keller, A., Abbaspour, K., and Schulin, R.: Assessment of Uncertainty and Risk in Modeling Regional Heavy-Metal Accumulation in Agricultural Soils, J. Environ. Qual., 31, 175–187, 2002.
Krayer von Krauss, M., van Asselt, M. B. A., Henze, M., Ravetz, J., and Beck, M. B.: Uncertainty and precaution in environmental management, Water Sci. Technol., 52, 1–9, available at: http://wst.iwaponline.com/content/52/6/1.abstract (last access: 7 May 2018), 2005.
Lehmann, A. and Stahr, K.: The potential of soil functions and planner-oriented soil evaluation to achieve sustainable land use, J. Soils Sediments, 10, 1092–1102, https://doi.org/10.1007/s11368-010-0207-5, 2010.
Lehmann, A., David, S., and Stahr, K.: Technique for soil evaluation and categorization for natural and anthropogenic soils, Hohenheimer Bodenkundliche Hefte, 86, 232 pp., University of Hohenheim, Stuttgart, Germany (2. Auflage), 2013.
Lesschen, J. P., Stoorvogel, J. J., Smaling, E. M. A., Heuvelink, G. B. M., and Veldkamp, A.: A spatially explicit methodology to quantify soil nutrient balances and their uncertainties at the national level, Nutr. Cycl. Agroecosys., 78, 111–131, https://doi.org/10.1007/s10705-006-9078-y, 2007.
Litz, N.: Schutz vor Organika, in: Handbuch der Bodenkunde, vol. 3, edited by: Blume, H.-P., 28 pp., Landsberg, Germany, 1998.
Makó, A., Kocsis, M., Barna, G., and Tóth, G.: Mapping the storing and filtering capacity of European soils, JRC Technical Reports, European Commission, https://doi.org/10.2788/49218, EUR 28392 EN, 62 pp., 2017.
Maxim, L. and van der Sluijs, J. P.: Quality in environmental science for policy: Assessing uncertainty as a component of policy analysis, Environ. Sci. Policy, 14, 482–492, https://doi.org/10.1016/j.envsci.2011.01.003, 2011.
Miller, R.: Bodenfunktionsbewertung für die Raum- und Bauleitplanung in Hessen und Rheinland-Pfalz, Hessisches Landesamt für Umwelt und Geologie, Landesamt für Geologie und Bergbau, Rheinland-Pfalz, Germany, 2012.
Nussbaum, M. and Papritz, A.: Transferfunktion Dichte. Einfache PTF für PMSoil, Dokumentation Analyse, Soil and Terrestrial Environmental Physics, ETH Zurich, Zurich, Switzerland, 2015.
Nussbaum, M., Walthert, L., Fraefel, M., Greiner, L., and Papritz, A.: Mapping of soil properties at high resolution in Switzerland using boosted geoadditive models, SOIL, 3, 191–210, https://doi.org/10.5194/soil-3-191-2017, 2017.
Nussbaum, M., Spiess, K., Baltensweiler, A., Grob, U., Keller, A., Greiner, L., Schaepman, M. E. and Papritz, A.: Evaluation of digital soil mapping approaches with large sets of environmental covariates, SOIL, 4, 1–22, https://doi.org/10.5194/soil-4-1-2018, 2018.
Oberholzer, H.-R. and Scheid, S.: Bodenmikrobiologische Kennwerte, Erfassung des Zustands landwirtschaftlicher Böden im NABO-Referenzmessnet anhang biologischer Parameter (NABObio), Umwelt-Wissen, 723, 78 pp., Bundesamt für Umwelt/Federal Office of the Environment, Bern, Switzerland, 2007.
PPDB: Pesticide Properties DataBase, University of Hertfordshire, Hertfordshire, UK, 22 May 2017, available at: http://sitem.herts.ac.uk/aeru/ppdb/ (last access: 7 May 2018), 2017.
Sanchez, P. A., Ahamed, S., Carre, F., Hartemink, A. E., Hempel, J., Huising, J., Lagacherie, P., McBratney, A. B., McKenzie, N. J., Mendonca-Santos, M. d. L., Minasny, B., Montanarella, L., Okoth, P., Palm, C. A., Sachs, J. D., Shepherd, K. D., Vagen, T.-G., Vanlauwe, B., Walsh, M. G., Winowiecki, L. A., and Zhang, G.-L.: Digital Soil Map of the World, Science, 325, 680–681, https://doi.org/10.1126/science.1175084, 2009.
Schaap, M. G.: Accuracy and uncertainty in PTF predictions, Dev. Soil Sci., 30, 33–43, https://doi.org/10.1016/S0166-2481(04)30003-6, 2004.
Schulte, R. P. O., Creamer, R. E., Donnellan, T., Farrelly, N., Fealy, R., O'Donoghue, C., and O'hUallachain, D.: Functional land management: A framework for managing soil-based ecosystem services for the sustainable intensification of agriculture, Environ. Sci. Policy, 38, 45–58, https://doi.org/10.1016/j.envsci.2013.10.002, 2014.
Schwilch, G., Bernet, L., Fleskens, L., Giannakis, E., Leventon, J., Marañón, T., Mills, J., Short, C., Stolte, J., van Delden, H., and Verzandvoort, S.: Operationalizing ecosystem services for the mitigation of soil threats: A proposed framework, Ecol. Indic., 67, 586–597, https://doi.org/10.1016/j.ecolind.2016.03.016, 2016.
Siemer, B., Hinrichs, U., Penndorf, O., Pohl, M., Schürer, S., Schulze, P., and Seiffert, S.: Bodenbewertungsinstrument Sachsen, Sächsiches Landesamt für Umwelt, Landwirtschaft und Geologie, Dresden, Germany, 66 pp., available at: http://www.umwelt.sachsen.de/umwelt/download/boden/Bodenbewertungsinstrument_Sachsen_092014(1).pdf (last access: 7 May 2018), 2014.
Six, L. and Smolders, E.: Future trends in soil cadmium concentration under current cadmium fluxes to European agricultural soils, Sci. Total Environ., 485–486, 319–328, https://doi.org/10.1016/j.scitotenv.2014.03.109, 2014.
Swisstopo: Geologische Karte der Schweiz 1 : 500 000, 18 May 2017, available at: https://shop.swisstopo.admin.ch/de/products/maps/geology/GK500/GK500_DIGITAL (last access: 7 May 2018), 2008.
Swisstopo: SwissAlti3d, Federal Office of Topography, Wabern bei Bern, Switzerland, 2014.
Taylor, A. L., Dessai, S., and de Bruin, W. B.: Communicating uncertainty in seasonal and interannual climate forecasts in Europe, Philos. T. R. Soc. A, 373, 16 pp., https://doi.org/10.1098/rsta.2014.0454, 2015.
Tóth, G., Gardi, C., Bódis, K., Ivits, E., Aksoy, E., Jones, A., Jeffery, S., Petursdottir, T., and Montanarella, L.: Continental-scale assessment of provisioning soil functions in Europe, Ecol. Process., 2, 18 pp., https://doi.org/10.1186/2192-1709-2-32, 2013.
Valujeva, K., O'Sullivan, L., Gutzler, C., Fealy, R., and Schulte, R. P. O.: The challenge of managing soil functions at multiple scales: An optimisation study of the synergistic and antagonistic trade-offs between soil functions in Ireland, Land Use Policy, 58, 335–347, https://doi.org/10.1016/j.landusepol.2016.07.028, 2016.
Vatn, A.: An institutional analysis of methods for environmental appraisal, Ecol. Econ., 8, 2207–2215, https://doi.org/10.1016/j.ecolecon.2009.04.005, 2009.
Vaysse, K. and Lagacherie, P.: Evaluating Digital Soil Mapping approaches for mapping GlobalSoilMap soil properties from legacy data in Languedoc-Roussillon (France), Geoderma Reg., 4, 20–30, https://doi.org/10.1016/J.GEODRS.2014.11.003, 2015.
Vereecken, H., Schnepf, A., Hopmans, J. W., Javaux, M., Or, D., Roose, T., Vanderborght, J., Young, M. H., Amelung, W., Aitkenhead, M., Allison, S. D., Assouline, S., Baveye, P., Berli, M., Brüggemann, N., Finke, P., Flury, M., Gaiser, T., Govers, G., Ghezzehei, T., Hallett, P., Hendricks Franssen, H. J., Heppell, J., Horn, R., Huisman, J. A., Jacques, D., Jonard, F., Kollet, S., Lafolie, F., Lamorski, K., Leitner, D., McBratney, A., Minasny, B., Montzka, C., Nowak, W., Pachepsky, Y., Padarian, J., Romano, N., Roth, K., Rothfuss, Y., Rowe, E. C., Schwen, A., Šimůnek, J., Tiktak, A., Van Dam, J., van der Zee, S. E. A. T. M., Vogel, H. J., Vrugt, J. A., Wöhling, T., and Young, I. M.: Modeling Soil Processes: Review, Key Challenges, and New Perspectives, Vadose Zone J., 15, 57 pp., https://doi.org/10.2136/vzj2015.09.0131, 2016.
Walthert, L., Bridler, L., Keller, A., Lussi, M., and Grob, U.: Harmonisierung von Bodendaten. Anhang zum Schlussbericht von PMSoil (“Predictive mapping of soil properties for the evaluation of soil functions at regional scale”, NRP 68), Eidgenössische Forschungsanstalt WSL und Agroscope Reckenholz, ETH Zurich Research Collection, 58 pp., https://doi.org/10.3929/ethz-a-010801994, 2016.
Short summary
To maintain the soil resource, spatial information on soil multi-functionality is key. Soil function (SF) maps rate soils potentials to fulfill a certain function, e.g., nutrient regulation. We show how uncertainties in predictions of soil properties generated by digital soil mapping propagate into soil function maps, present possibilities to display this uncertainty information and show that otherwise comparable SF assessment methods differ in their behaviour in view of uncertainty propagation.
To maintain the soil resource, spatial information on soil multi-functionality is key. Soil...
