The DOI matches its Crossref record; 32 of the 32 references it cites were found in a registry or an index.
Assessment of soil organic carbon stocks under future climate and land cover changes in Europe
Open accessAbstract
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.
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Cites
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A generic framework for spatial prediction of soil variables based on regression-kriging
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Self-citationSensitivity of soil organic carbon stocks and fractions to different land-use changes across Europe
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Towards New Scenarios for Analysis of Emissions, Climate Change, Impacts, and Response Strategies
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An overview of pedometric techniques for use in soil survey
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SoilGrids 2.0: producing soil information for the globe with quantified spatial uncertainty
Poggio, L., de Sousa, L. M., Batjes, N. H., Heuvelink, G. B. M., Kempen, B., Ribeiro, E., & Rossiter, D. (2021) · SOIL · doi:10.5194/soil-7-217-2021 · Cited by 2,333
LUCAS Soil, the largest expandable soil dataset for Europe: a review
Orgiazzi, A., Ballabio, C., Panagos, P., Jones, A., & Fernández‐Ugalde, O. (2018) · European Journal of Soil Science · doi:10.1111/ejss.12499 · Cited by 699
Self-citationSoil and environmental issues in sandy soils
Huang, J., & Hartemink, A. E. (2020) · Earth-Science Reviews · doi:10.1016/j.earscirev.2020.103295 · Cited by 420
Soil carbon is the blind spot of European national GHG inventories
Bellassen, V., Angers, D., Kowalczewski, T., & Olesen, A. (2022) · Nature Climate Change · doi:10.1038/s41558-022-01321-9 · Cited by 55
Lyu, H., Zhong, R., Kilasara, M., Hartono, A., Sun, Z., Funakawa, S., & Watanabe, T. (2024) · Environmental Science & Technology · doi:10.1021/acs.est.3c07000 · Cited by 20
Metadata
- Authors
- Yigini, Y., & Panagos, P.
- Venue
- Science of The Total Environment
- Publisher
- Elsevier BV
- Published
- 2016-07
- Volume
- 557-558
- Pages
- 838-850
- ISSN
- 0048-9697 (ISSN-L)
- OpenAlex
- W2339831229
- Cited by
- 285
- References
- 32
- FWCI
- 11.25
- Type
- journal article
- Language
- en
- Open access
- hybrid
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