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Peatland Diversity and Carbon Dynamics (September 2010)

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  • Good background data, long-term measurements
  • Driven by hydrology
  • More productive! Gullies!
  • Measuring ecosystem function: GHG fluxes
  • Significant differences in methane flux between all landforms (ANOVA, p < 0.001)
  • Transcript

    • 1. PeatlandDiversity and Carbon Dynamics
      Mike Whitfield
      Nick Ostle, Richard Bardgett, Rebekka Artz
      miit@ceh.ac.uk | www.mikewhitfield.co.uk
    • 2. Background:
      Peatlands and climate change
      Above- and below-ground links
      Research:
      Plant and soil diversity
      Peatland carbon stocks
      Greenhouse gas emissions (CO2, CH4, N2O)
      Conclusions
    • 3. Introduction: Peatlands
      Globally, peatlands constitute 25 – 30% of the soil carbon pool
      Climate warming is projected to be greatest over high northern latitudes, coincidental with a high proportion of the world’s peatlands
      Roughly 8% of UK is covered with blanket peat moorland
      Map data: Jones et al. 2005: Estimating organic carbon in the soils of Europe for policy support. DOI: 10.1111/j.1365-2389.2005.00728.x
    • 4. Introduction: Climate-Carbon Feedback Uncertainty
      Estimates of global soil organic carbon stocks range between 700 – 2946 x 1012kg
      Need reliable estimates based on upscaling processes from small to larger scales to resolve uncertainty.
      ‘Bucket and slab’ peatland models
      What about the biological functioning?
      ?
    • 5. Introduction: Linking Plant and Soil Biodiversity
      Growing evidence of feedbacks between the biosphere and global biogeochamical cycles.
      Plant-soil interactions lie at the heart of these feedbacks.
      Climate change and land use are powerful drivers of change in plant diversity.
      What will the implications be?
      Pendall et al. 2008
    • 6. Main Questions
      Are there any relationships between plant diversity-abundance and microbial community structure at the landscape scale?
      Can these relationships be used to predict ecosystem scale greenhouse gas emissions?
      How little do I need to know about biodiversity to predict ecosystem C cycling and GHG emissions?
    • 7. Field Site: Trout Beck, Moor House, north Pennines
      Area: 1146 ha
      Altitudinal range: 535 – 848m
      90% blanket peat
    • 8. Upscaling Peatland Carbon Dynamics
      Survey of peatland condition (plant-soil diversity and carbon stocks)
      Measurement of peatland GHG function
      Statistical analyses and spatial modelling of both (LiDAR, image classification and geostatistics (e.g. regression kriging)
      …to predict carbon dynamics and greenhouse gas fluxes at the ecosystem scale
    • 9. Peat Bog Landforms
    • 10. Methodology: soil-sampling
      • Large-scale vegetation survey (419 quadrats)
      • 11. Species presence and percentage cover
      • 12. Vegetation height at 3 in-plot locations
      • 13. Habitat context
      • 14. Topography: aspect, slope
      • 15. Peat depth
      Soil C and N
      PLFA
      T-RFLP
    • 16. Methodology: soil-sampling
      Spatial distribution of soil sampling
      Coring locations randomly selected based on membership of landform (OM, EA, GU) and depth (0-100, 100-200, 200-300cm) categories
      Microbial community sampling:
      Three depths within each core
      Based on mean water table conditions derived from published and unpublished data
      0-5cm: Acrotelm
      15-20cm: Mesotelm
      75-80cm: Catotelm
    • 17. Landscape Survey Results
      Open moorland: 52%
      Eroded areas: 11%
      Gullies: 12%
    • 18. Above-ground: Vegetation Composition
    • 19. Below-ground: Peat Depths
      Deepest peat under open moorland
      Kruskal-Wallis test indicates significant differences between landform types (p < 0.001)
    • 20. Below-ground: Carbon Stocks
      Significantly lower CN ratio in gullies(ANOVA, f =34.6, p <0.001)
      Higher C content in gullies
      (Kruskal-Wallis, p <0.001)
    • 21. Below-ground: Microbial community
      Significant differences between landforms for Actinobacterial and Total PLFA (Kruskal-Wallis tests: p <0.001 and p = 0.005 respectively)
      Perhaps reflecting lack of plant inputs on bare peat in eroding areas…
    • 22. Below-ground: Microbial community
      Significant difference in vegetation cover between landforms (ANOVA, p <0.001)
      a
      a
      b
    • 23. Greenhouse Gas Fluxes: Experimental Design
      What are the differences in greenhouse gas fluxes between landforms?
      36 chambers on fixed plots
      3 landforms
      3 depth classes
      4 replicates
      CO2
      CH4
      N2O
    • 24. Greenhouse Gas Fluxes: Experimental Design
      Monthly sampling using static dome chambers, Infra-Red Gas Analysers (IRGAs) and gas chromatography
      Continuous landform hydrology and temperature measured using automated dip wells
      Seasonal sampling for C and N, microbial PLFA and T-RFLP
      4 months in, 8 to go!
      Image: Sue Ward
    • 25. Greenhouse Gas Fluxes: Preliminary Results
      Photosynthesis
      Respiration (plant and soil)
      Respiration (soil only)
    • 26. Upscaling Peatland Carbon Dynamics to the Ecosystem Scale
    • 27. Conclusions so far…
      • Are there any relationships between plant diversity-abundance and microbial community structure at the landscape scale?
      • 28. Can these relationships be used to predict ecosystem scale greenhouse gas emissions?
      • 29. How little do I need to know about biodiversity to predict ecosystem C cycling and GHG emissions?
    • Acknowledgements
      This talk can be downloaded from www.mikewhitfield.co.uk
      Many thanks to:
      Catherine Turner, Sean Case, Simon Oakley, Susan Ward, Sergio Menendez Villanueva, Harriett Rea, Paula Reimer, David Beilman and Nicola Thompson
      This presentation was part-funded by the British Society for Soil Science. Mike Whitfield is supported by a Natural Environment Research Council CASE studentship.