Climatic Change

, Volume 85, Issue 1–2, pp 139–158 | Cite as

Predicting the future carbon budget of an upland peat catchment

  • Fred WorrallEmail author
  • Tim Burt
  • John Adamson
  • Mark Reed
  • Jeff Warburton
  • Alona Armstrong
  • Martin Evans


Using data from a single upland peat catchment (North Pennines, UK), this study combines descriptions of the uptake of carbon by primary productivity and input from both wet and dry deposition with descriptions of carbon release pathways: soil CO2 respiration, CH4 flux, particulate organic carbon (POC), dissolved organic carbon (DOC), and excess dissolved CO2. Each pathway is projected 10 years into the future based upon extrapolated changes in rainfall and temperature. The study shows that the catchment is presently a net source of carbon and that over a period of 10 years the catchment goes from a net source of 11.2 to 20.9 gC/m2/year. The probability that the catchment is a net sink of carbon decreases from 35 to 26% over the study period, i.e. upland peats are predicted to become an increasing source of carbon. With respect to carbon gases (CO2 + CH4), the catchment remains a net sink but this decreases from 15.9 to 11.2 gC/m2/year, given current trends the catchment will become a net source of carbon gases by 2034. For most pathways the predicted increases or decreases are in line with increasing temperature predicted for the area, but DOC flux shows a larger percentage increase because of additional production caused by the increased frequency of severe droughts within the catchment. If this result is extended across the UK uplands, peats would be a net source of between 0.26 and 0.45 Mt C/year, but with respect to carbon gases alone the catchment is net sink of between 0.35 and 0.23 Mt C/year.


Soil Respiration Dissolve Inorganic Carbon Particulate Organic Carbon Dissolve Organic Carbon Concentration Suspended Sediment Concentration 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media B.V. 2007

Authors and Affiliations

  • Fred Worrall
    • 1
    Email author
  • Tim Burt
    • 2
  • John Adamson
    • 3
  • Mark Reed
    • 4
  • Jeff Warburton
    • 2
  • Alona Armstrong
    • 2
  • Martin Evans
    • 5
  1. 1.Department of Geological SciencesScience LaboratoriesDurhamUK
  2. 2.Department of GeographyScience LaboratoriesDurhamUK
  3. 3.Centre for Ecology & HydrologyEnvironmental Change NetworkCumbriaUK
  4. 4.Leeds Institute of Environmental Science & Management, School of the EnvironmentUniversity of LeedsLeedsUK
  5. 5.The School of GeographyUniversity of ManchesterManchesterUK

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