Peatland Diversity and Carbon Dynamics (September 2010)Presentation Transcript
PeatlandDiversity and Carbon Dynamics Mike Whitfield Nick Ostle, Richard Bardgett, Rebekka Artz firstname.lastname@example.org | www.mikewhitfield.co.uk
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
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
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? ?
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
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?
Field Site: Trout Beck, Moor House, north Pennines Area: 1146 ha Altitudinal range: 535 – 848m 90% blanket peat
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
Peat Bog Landforms
Large-scale vegetation survey (419 quadrats)
Species presence and percentage cover
Vegetation height at 3 in-plot locations
Topography: aspect, slope
Soil C and N PLFA T-RFLP
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
Below-ground: Peat Depths Deepest peat under open moorland Kruskal-Wallis test indicates significant differences between landform types (p < 0.001)
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)
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…
Below-ground: Microbial community Significant difference in vegetation cover between landforms (ANOVA, p <0.001) a a b
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
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
Greenhouse Gas Fluxes: Preliminary Results Photosynthesis Respiration (plant and soil) Respiration (soil only)
Upscaling Peatland Carbon Dynamics to the Ecosystem Scale
Conclusions so far…
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?
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.