peatland diversity and carbon dynamics

Peatland Diversity and Carbon Dynamics

Peatland Diversity and Carbon Dynamics

Mike WhitfieldNick Ostle, Richard Bardgett, Rebekka Artzmiit@ceh.ac.uk | www.mikewhitfield.co.uk

• Background:Peatlands and climate changeAbove- and below-ground links

• Research:– Plant and soil diversity– Peatland carbon stocks– Greenhouse gas emissions (CO2, CH4, N2O)

• Conclusions

• 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

Introduction: Peatlands

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

• 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

Introduction: Peatlands

• To a depth of 1m, UK peatlands contain 1357Mt C, nearly half of which is in Scotland

• A loss of 12% of the UK peatland area = total annual UK human GHG emissions

(Bradley et al. 2005; Smith et al. 2010)

• Estimates of global soil organic carbon stocks range between 700 – 2946 x 1012 kg

• 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: Climate-Carbon Feedback Uncertainty

• Growing evidence of feedbacks between the biosphere and global biogeochemical 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?

Introduction: Linking Plant and Soil Biodiversity

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?

• Area: 1146 ha

• Altitudinal range: 535 – 848m

• 90% blanket peat

Field Site: Trout Beck, Moor House, north Pennines

• 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

Upscaling Peatland Carbon Dynamics

Peat Bog Landforms

Peat Bog Landforms

Methodology: soil-sampling

•Soil C and N

•PLFA

•T-RFLP

•Large-scale vegetation survey (419 quadrats)

• Species presence and percentage cover

• Vegetation height at 3 in-plot locations

• Habitat context

• Topography: aspect, slope

• Peat depth

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

Landscape Survey Results

Open moorland: 52%

Eroded areas: 11%

Gullies: 12%

Landscape Survey Results

Open moorland: 52%

Eroded areas: 11%

Gullies: 12%

Above-ground: Vegetation Composition

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)

• 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

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

N2O

CH4

• 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

• May 2010 to June 2011

Greenhouse Gas Fluxes: Experimental Design

Image: Sue Ward

Greenhouse Gas Fluxes: Preliminary Results

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?o Differences in the composition of Plant Functional Types between landforms

are clearly visibleo Eroding areas have lower microbial biomass, which may be a reflection of

lower vegetation cover on bare peat

• Are there differences in below-ground carbon dynamics between landform types?o Gullies have a greater carbon content, and a lower CN ratio

• 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

Mike Whitfield is supported by a Natural Environment Research Council CASE studentship.