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Abstract

 

This article in SSSAJ

  1. Vol. 80 No. 5, p. 1296-1307
    unlockOPEN ACCESS
     
    Received: Feb 14, 2016
    Accepted: July 01, 2016
    Published: September 29, 2016


    * Corresponding author(s): jonathan.gray@environment.nsw.gov.au
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doi:10.2136/sssaj2016.02.0038

Change in Soil Organic Carbon Stocks under 12 Climate Change Projections over New South Wales, Australia

  1. Jonathan M. Gray *a and
  2. Thomas F.A. Bishopb
  1. a Office of Environment and Heritage PO Box 644 Parramatta NSW 2124 Australia Faculty of Agriculture and Environment, Biomedical Building C81 Univ. of Sydney NSW, 2006 Australia
    b Faculty of Agriculture and Environment Biomedical Building C81 Univ. of Sydney NSW, 2006 Australia
Core Ideas:
  • Potential changes in soil organic C to 2070 mapped (100-m grid) and examined.
  • The direction and magnitude of change varied between the 12 climate projections.
  • Differing changes revealed for 36 current climate–parent material–land use regimes.
  • Digital soil mapping–space-for-time substitution is useful for climate change study

Abstract

Digital soil mapping (DSM) techniques combined with space-for-time substitution (SFTS) processes were used to map and examine soil organic carbon (SOC) changes caused by projected climate change over New South Wales, Australia until ∼2070. Twelve projections were derived from four global climate models downscaled with three regional climate models. A marked variation in the direction and magnitude of SOC change was demonstrated with the different projections. Mean state-wide predictions (0–30 cm depth) ranged between 2.9 Mg ha-1 gain and 8.7 Mg ha-1 SOC loss. Greater consistency among climate change projections is required before we can confidently predict SOC changes. By using averaged results from the 12 projections, broad trends were revealed for the change in SOC over two intervals (0–30 and 30–100 cm). A mean loss rate of 2.0 Mg ha-1 for the upper interval was demonstrated and a total loss of 737 Tg of CO2 equivalent for the entire depth to 100 cm but the 95% confidence interval was wide. Although changes are primarily controlled by the balance between changing temperatures and rainfall, the extent of change also depends on the environmental regime, with differing changes demonstrated over 36 current climate–parent material–land use combinations (e.g., projected mean SOC decline is <1 Mg ha-1 for dry–highly siliceous–cropping but >15 Mg ha-1 for wet–mafic–native vegetation). This DSM–SFTS technique offers a viable alternative to dynamic simulation techniques for predicting and identifying patterns in the change of soil properties caused by climate change.

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