Literature DB >> 27082446

Assessment of soil organic carbon stocks under future climate and land cover changes in Europe.

Yusuf Yigini1, Panos Panagos2.   

Abstract

Soil organic carbon plays an important role in the carbon cycling of terrestrial ecosystems, variations in soil organic carbon stocks are very important for the ecosystem. In this study, a geostatistical model was used for predicting current and future soil organic carbon (SOC) stocks in Europe. The first phase of the study predicts current soil organic carbon content by using stepwise multiple linear regression and ordinary kriging and the second phase of the study projects the soil organic carbon to the near future (2050) by using a set of environmental predictors. We demonstrate here an approach to predict present and future soil organic carbon stocks by using climate, land cover, terrain and soil data and their projections. The covariates were selected for their role in the carbon cycle and their availability for the future model. The regression-kriging as a base model is predicting current SOC stocks in Europe by using a set of covariates and dense SOC measurements coming from LUCAS Soil Database. The base model delivers coefficients for each of the covariates to the future model. The overall model produced soil organic carbon maps which reflect the present and the future predictions (2050) based on climate and land cover projections. The data of the present climate conditions (long-term average (1950-2000)) and the future projections for 2050 were obtained from WorldClim data portal. The future climate projections are the recent climate projections mentioned in the Fifth Assessment IPCC report. These projections were extracted from the global climate models (GCMs) for four representative concentration pathways (RCPs). The results suggest an overall increase in SOC stocks by 2050 in Europe (EU26) under all climate and land cover scenarios, but the extent of the increase varies between the climate model and emissions scenarios.
Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Climate change; Climate scenarios; LUCAS Soil Survey; Land cover change; Regression-kriging; Soil organic carbon

Year:  2016        PMID: 27082446     DOI: 10.1016/j.scitotenv.2016.03.085

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


  5 in total

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Journal:  Sci Data       Date:  2018-11-13       Impact factor: 6.444

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Journal:  Front Microbiol       Date:  2022-09-15       Impact factor: 6.064

5.  Mapping LUCAS topsoil chemical properties at European scale using Gaussian process regression.

Authors:  Cristiano Ballabio; Emanuele Lugato; Oihane Fernández-Ugalde; Alberto Orgiazzi; Arwyn Jones; Pasquale Borrelli; Luca Montanarella; Panos Panagos
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  5 in total

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