MRV approaches

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• MRV approaches
• in the BMU Belarus peatland project

Hans Joosten Greifswald University, Germany
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Eastern Europe famous for its vast and largely
undisturbed peatlands...
Rospuda Valley, Poland
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Belarus has high proportion of peatlands...
fens (green), bogs (red), transitional peatlands
(purple) former extent 15 of the area
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Present area of natural peatlands 1.5 mio ha
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Present area of drained peatlands 1.5 mio ha
(agriculture 72, forestry 25, peat extraction
3)
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Drained peatlands are huge emittors of CO2 N2O
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CO2 emission
Central Europe is peatland emission hot spot
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Does rewetting reduce greenhouse gas emissions?
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How much less emissions after rewetting?
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BMU funded rewetting project (2008-2011)

• builds on GEF funded rewetting project (42,000
  ha)
• strong support of Belarusian government
• carbon credits
• reduction of fires (radioactivity!)

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BMU funded rewetting project (2008-2011)

• Deliverables
• methodology for GHG assessment
• standard for voluntary trade
• 15,000 ha rewetted and sustainably managed
• local capacity

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Measuring directly is complicated, time
consuming, expensive ( 10,000 /ha/yr) ? proxy
indicators
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Mean water level is best predictor of emissions
(meta-analysis of 25 site parameters in W-Europe)
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CO2 emissions clearly correlate with water
levels they become less with higher water levels
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CH4 emissions clearly correlate with water
levels they increase when higher than 20 cm -
surface
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N2O emissions clearly correlate with water
levels they do not occur when higher than 15 cm
- surface
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N2O erratic, but lower with higher water
levels Leave N2O emissions out ? conservative
estimate
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By rewetting, greenhouse gas emissions decrease,
but less between 20 cm and 0 cm
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Emissions strongly related to water level
Vegetation strongly related to water level ?
Use vegetation as indicator for emissions!
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In an environmental gradient some plant species
occur together others exclude each
other. Species groups (and their absence!)
indicate site conditions much sharper than
individual plant species vegetation forms.
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Vegetation types calibrated for GHG
emissions GESTs Greenhouse gas Emission Site
Types Some examples
Water level Vegetation CH4 CO2 GWP
2-, 2, 2 (3/2) 3 4/3 4 5 6
MOD. MOIST FORBS MEADOWS MOIST FORBS MEADOWS VERY MOIST MEADOWS VERY MOIST MEADOWS, FORBS TALL REEDS WET TALL SEDGE MARSHES FLOODED TALL AND SHORT REEDS
0 1.5 (1.3 2) 3.5 (2.5 6) 3 7 (5.0 9.5) 1 (0.3 1.7)
24 15 13 (8.5 16.5) 8 0 0
24 16.5 16.5 11 7 1
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GESTs with indicator species groups
Vegetation type Typical/differentiating species WL class CH4 CO2 GWP
Sphagnum-Carex limosa-marsh Sphagnum recurvum agg., Carex limosa, Scheuchzeria 5 12.5 lt0 (0) 12.5
Sphagnum-Carex-Eriophorum-marsh Sph. recurvum agg., Carex nigra, C. curta, Eriophorum angustifolium 5 12.5 lt0 (0) 12.5
Drepanocladus-Carex-marsh Drepanocladus div. spec., Carex diandra, Carex rostr., Carex limosa - Carex dominated 5 12.5 lt0 (0) 12.5
Scorpidium-Eleocharis-marsh Scorpidium, Eleocharis quinqueflora - Carex (shunt) dominated 5 12.5 lt0 (0) 12.5
Sphagnum-Juncus effusus-marsh Juncus effusus, Sphagnum recurvum agg. 5 12.5 lt0 (0) 12.5
Equisetum-reeds Equisetum fluviatile 5 12.5 lt0 (0) 12.5
Scorpidium-Cladium-reeds Cladium, Scorpidium 5 12.5 lt0 (0) 12.5
Sphagnum-Phragmites-reeds Phragmites, Solanum dulcamara 5 10 lt0 / 0 10
Solano-Phragmitetum Scorpidium, Eleocharis quinqueflora - Phragmites Solanum without Urtica-gr. 5 10 lt0 / 0 10
Rorippa-Typha-Phragmites-reeds Typha latifolia, Phragmites, Rorippa aquatica, Lemna minor 5 10 lt0 / 0 10
Bidens-Glyceria-reeds Glyceria maxima, Berula erecta, Bidens tripartita, B. cernua 5 10 lt0 / 0 10
Red or green Sphagnum lawn (optimal) Sph. magellanicum, Sph. rubellum, Sph. fuscum, Sph. recurvum agg. 5 5 -2 3
Green Sphagnum hollow Sph. cuspidatum, Scheuchzeria 5 10 -2 8
Polytrichum-lawn Polytrichum commune 5 2 lt0 2
Each GEST with typical species
Each GEST with typical GHG emissions
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Benefits of vegetation as a GHG proxy

• reflects long-term water levels
• ? provides indication on GHG fluxes per yr
• is controlled by factors that control GHG
  emissions (water, nutrients, acidity, land use)
• is responsible for GHG emissions via its own
  organic matter (root exudates!)
• may provide bypasses for increased CH4 via
  aerenchyma (shunt species)
• allows rapid and fine-scaled mapping
• ? Vegetation is a more comprehensive proxy
  than water level!

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Disadvantages of vegetation as a proxy

• slow reaction on environmental changes
• 3 years before change in water level is
  reflected in vegetation (negative effect faster)
• needs to be calibrated for different climatic and
  phytogeographical conditions

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Vegetation forms developed for NE Germany
? test of correlations in Belarusian
peatlands
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BMU Belarus project

• Calibration of NE German model for Belarus
• relation vegetation ? water level (CIM position)
• relation water level ? GHG emissions (CIM
  position)
• Completion of model (gap filling)
• Consistency test with international literature
• Development of conservative approaches
• Selection of rewetting sites
• Mapping of vegetation before rewetting
  (assessment of emission baseline )
• Monitor water level and vegetation development
  (ex-post emission monitoring)

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Major gap abandoned peat extraction sites
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• Perspectives of GEST-approach
• Ex-ante baseline assessment with ex-post
  evaluation
• Fine-scaled mapping
• Remote sensing monitoring
• Continuous refinement with progressing GHG
  research
• Addition of new modules (forest, transient
  dynamics)
• Simple, cheap, reliable

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Developed with

• Jürgen Augustin (ZALF)
• John Couwenberg (DUENE)
• Dierk Michaelis (Uni Greifswald)
• Merten Minke (APB / CIM)
• Annett Thiele (APB/ CIM)
• And many more

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GESTs!
info joosten_at_uni-greifswald.de