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Benchmark values for forest soil carbon stocks in Europe: results from a large scale forest soil survey

Onderzoeksoutput: Bijdrage aan tijdschriftA1: Web of Science-artikelOnderzoekpeer review

Auteurs

  • Hannu Ilvesniemi
  • Lars Vesterdal
  • Elena Vanguelova
  • Stefano Carnicelli

Externe Organisaties

  • Natural Resources Institute Finland
  • Department of Geosciences and Natural Resource Management, University of Copenhagen
  • Centre for Ecosystems, Society and Biosecurity
  • University of Florence

Details

Originele taal-2Engels
TijdschriftGeoderma
Volume251-252
Pagina's (van-tot)33-46
Aantal pagina's14
ISSN0016-7061
StatusGepubliceerd - 6-mrt-2015

Abstract

Soil organic carbon (SOC) stocks in forest floors and in mineral and peat forest soils were estimated at the European scale. The assessment was based on measured C concentration, bulk density, coarse fragments and effective soil depth data originating from 4914 plots in 22 EU countries belonging to the UN/ECE ICP Forests 16 × 16 km Level I network. Plots were sampled and analysed according to harmonized methods during the 2nd European Forest Soil Condition Survey. Using continuous carbon density depth functions, we estimated SOC stocks to 30-cm and 1-m depth, and stratified these stocks according to 22 WRB Reference Soil Groups (RSGs) and 8 humus forms to provide European scale benchmark values. Average SOC stocks amounted to 22.1 t C ha−1 in forest floors, 108 t C ha−1 in mineral soils and 578 t C ha−1 in peat soils, to 1 m depth. Relative to 1-m stocks, the vertical SOC distribution confirmed global patterns reported for forest soils: ~50% of SOC was stored in the upper 20 cm, and ~55–65% in the upper 30 cm of soil. Assuming 163 Mha of European forest cover and by using various scaling up procedures, we estimated total stocks at 3.50–3.94 Gt C in forest floors and 21.4–22.7 Gt C in mineral and peat soils down to 1-m,which is ~40% more than commonly published. The most useful predictors and stratifiers for C stockswere humus form and tree species for the forest floor, RSG for mineral soils and parent material for peat soils. This dataset will be further explored, predominantly for validation of soil C models, resampling and comparison with legacy and future forest SOC inventories.
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