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Resumen
Soils hold the largest pool of organic carbon (C) on Earth; yet, soil organic carbon (SOC) reservoirs are not well represented in climate change mitigation strategies because our database for ecosystems where human impacts are minimal is still fragmentary. Here, we provide a tool for generating a global baseline of SOC stocks. We used partial least square (PLS) regression and available geographic datasets that describe SOC, climate, organisms, relief, [ver mas...]
dc.contributor.authorDuarte Guardia, Sandra
dc.contributor.authorPeri, Pablo Luis
dc.contributor.authorAmelung, Wulf
dc.contributor.authorSheil, Douglas
dc.contributor.authorLaffan, Shawn W.
dc.contributor.authorBorchard, Nils
dc.contributor.authorBird, Michael I.
dc.contributor.authorDieleman, Wouter
dc.contributor.authorPepper, David A.
dc.contributor.authorZutta, Brian
dc.contributor.authorJobbagy Gampel, Esteban Gabriel
dc.contributor.authorSilva, Lucas C. R.
dc.contributor.authorBonser, Stephen P.
dc.contributor.authorBerhongaray, Gonzalo
dc.contributor.authorPiñeiro, Gervasio
dc.contributor.authorMartinez, Maria Jose
dc.contributor.authorCowie, Annette L.
dc.contributor.authorLadd, Brenton
dc.date.accessioned2018-07-31T12:18:13Z
dc.date.available2018-07-31T12:18:13Z
dc.date.issued2018-05
dc.identifier.issn1381-2386
dc.identifier.issn1573-1596
dc.identifier.otherhttps://doi.org/10.1007/s11027-018-9815-y
dc.identifier.urihttps://link.springer.com/article/10.1007/s11027-018-9815-y
dc.identifier.urihttp://hdl.handle.net/20.500.12123/2925
dc.description.abstractSoils hold the largest pool of organic carbon (C) on Earth; yet, soil organic carbon (SOC) reservoirs are not well represented in climate change mitigation strategies because our database for ecosystems where human impacts are minimal is still fragmentary. Here, we provide a tool for generating a global baseline of SOC stocks. We used partial least square (PLS) regression and available geographic datasets that describe SOC, climate, organisms, relief, parent material and time. The accuracy of the model was determined by the root mean square deviation (RMSD) of predicted SOC against 100 independent measurements. The best predictors were related to primary productivity, climate, topography, biome classification, and soil type. The largest C stocks for the top 1 m were found in boreal forests (254 ± 14.3 t ha−1) and tundra (310 ± 15.3 t ha−1). Deserts had the lowest C stocks (53.2 ± 6.3 t ha−1) and statistically similar C stocks were found for temperate and Mediterranean forests (142 - 221 t ha−1), tropical and subtropical forests (94 - 143 t ha−1) and grasslands (99-104 t ha−1). Solar radiation, evapotranspiration, and annual mean temperature were negatively correlated with SOC, whereas soil water content was positively correlated with SOC. Our model explained 49% of SOC variability, with RMSD (0.68) representing approximately 14% of observed C stock variance, overestimating extremely low and underestimating extremely high stocks, respectively. Our baseline PLS predictions of SOC stocks can be used for estimating the maximum amount of C that may be sequestered in soils across biomes.eng
dc.formatapplication/pdfes_AR
dc.language.isoenges_AR
dc.rightsinfo:eu-repo/semantics/restrictedAccesses_AR
dc.sourceMitigation and Adaptation Strategies for Global Change : 1–18 (May 2018)es_AR
dc.subjectClimaes_AR
dc.subjectClimateeng
dc.subjectCambio Climáticoes_AR
dc.subjectClimate Changeeng
dc.subjectSueloes_AR
dc.subjectSoileng
dc.subjectCarbonoes_AR
dc.subjectCarboneng
dc.subjectSistemas de Información Geográficaes_AR
dc.subjectGeographical Information Systemseng
dc.titleBetter estimates of soil carbon from geographical data: a revised global approaches_AR
dc.typeinfo:ar-repo/semantics/artículoes_AR
dc.typeinfo:eu-repo/semantics/articlees_AR
dc.typeinfo:eu-repo/semantics/publishedVersiones_AR
dc.description.origenEEA Santa Cruzes_AR
dc.description.filFil: Duarte Guardia, Sandra. Universidad Nacional de la Patagonia Austral; Argentinaes_AR
dc.description.filFil: Peri, Pablo Luis. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santa Cruz; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentinaes_AR
dc.description.filFil: Amelung, Wulf. University of Bonn. Soil Science and Soil Ecology. Institute of Crop Science and Resource Conservation (INRES); Alemaniaes_AR
dc.description.filFil: Sheil, Douglas. Norwegian University of Life Sciences. Faculty of Environmental Sciences and Natural Resource Management; Noruega. Jalan Cifor Rawajaha. Center for International Forestry Research (CIFOR); Indonesiaes_AR
dc.description.filFil: Borchard, Nils. Forschungszentrum Jülich GmbH. Agrosphere Institute (IBG-3); Alemania. Jalan Cifor Rawajaha. Center for International Forestry Research (CIFOR); Indonesia. Ruhr-University Bochum, Institute of Geography, Soil Science/Soil Ecology; Alemania. Plant Production Natural Resources Institute Finland (Luke); Finlandiaes_AR
dc.description.filFil: Laffan, Shawn W. University of New South Wales. School of Biological, Earth and Environmental Sciences; Australiaes_AR
dc.description.filFil: Bird, Michael I. James Cook University. College of Science, Technology and Engineering and Centre for Tropical Environmental and Sustainability Science; Australiaes_AR
dc.description.filFil: Dieleman, Wouter. James Cook University. College of Science, Technology and Engineering and Centre for Tropical Environmental and Sustainability Science; Australiaes_AR
dc.description.filFil: Pepper, David A. University of New South Wales. School of Biological, Earth and Environmental Sciences; Australia. University of Canberra. Institute for Applied Ecology; Australiaes_AR
dc.description.filFil: Zutta, Brian. Perú. Ministerio del Ambiente. Programa Nacional de Conservación de Bosques; Perúes_AR
dc.description.filFil: Jobbagy Gampel, Esteban Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Instituto de Matemática Aplicada de San Luis "Prof. Ezio Marchi". Universidad Nacional de San Luis. Facultad de Ciencias Físico, Matemáticas y Naturales. Instituto de Matemática Aplicada de San Luis; Argentinaes_AR
dc.description.filFil: Silva, Lucas C. R. University of Oregon. Institute of Ecology & Evolution. Department of Geography. Environmental Studies Program; Estados Unidoses_AR
dc.description.filFil: Bonser, Stephen P. University of New South Wales. School of Biological, Earth and Environmental Sciences. Evolution and Ecology Research Centre; Australiaes_AR
dc.description.filFil: Berhongaray, Gonzalo. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad Nacional del Litoral.Facultad de Ciencias Agrarias; Argentinaes_AR
dc.description.filFil: Piñeiro, Gervasio. Universidad de Buenos Aires. Facultad de Agronomía. Cátedra de Ecología. Laboratorio de Análisis Regional y Teledetección; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de la República. Facultad de Agronomia; Uruguayes_AR
dc.description.filFil: Martinez, Maria Jose. Universidad Científica del Sur. Escuela de Agroforestería; Perúes_AR
dc.description.filFil: Cowie, Annette L. NSW Department of Primary Industries; Australia. University of New England. School of Environmental and Rural Science; Australiaes_AR
dc.description.filFil: Ladd, Brenton. Universidad Científica del Sur. Escuela de Agroforestería; Peru. UNSW Australia. School of Biological. Earth and Environmental Sciences, Evolution and Ecology Research Centre; Australiaes_AR
dc.subtypecientifico


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