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MRV approaches in the BMU Belarus peatland project

MRV approaches in the BMU Belarus peatland project. Hans Joosten Greifswald University, Germany. Eastern Europe: famous for its vast and largely undisturbed peatlands. Rospuda Valley, Poland. Belarus has high proportion of peatlands...

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MRV approaches in the BMU Belarus peatland project

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  1. MRV approaches in the BMU Belarus peatland project Hans Joosten Greifswald University, Germany

  2. Eastern Europe: famous for its vast and largely undisturbed peatlands... Rospuda Valley, Poland

  3. Belarus has high proportion of peatlands... fens (green), bogs (red), transitional peatlands (purple): former extent ~15% of the area

  4. Present area of natural peatlands: 1.5 mio ha

  5. Present area of drained peatlands: 1.5 mio ha (agriculture 72%, forestry 25%, peat extraction 3%)

  6. Drained peatlands are huge emittors of CO2 + N2O

  7. CO2 emission Central Europe is peatland emission hot spot

  8. Does rewetting reduce greenhouse gas emissions?

  9. How much less emissions after rewetting?

  10. 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!)…

  11. BMU funded rewetting project (2008-2011) Deliverables: • methodology for GHG assessment • standard for voluntary trade • 15,000 ha rewetted and sustainably managed • local capacity

  12. Measuring directly is complicated, time consuming, expensive ( € 10,000 /ha/yr)  proxy indicators

  13. Mean water level is best predictor of emissions (meta-analysis of 25 site parameters in W-Europe)

  14. CO2 emissions clearly correlate with water levels: they become less with higher water levels

  15. CH4 emissions clearly correlate with water levels: they increase when higher than 20 cm - surface

  16. N2O emissions clearly correlate with water levels: they do not occur when higher than 15 cm - surface

  17. N2O erratic, but lower with higher water levels Leave N2O emissions out  conservative estimate

  18. By rewetting, greenhouse gas emissions decrease, but less between – 20 cm and 0 cm

  19. Emissions strongly related to water level Vegetation strongly related to water level  Use vegetation as indicator for emissions!

  20. site factor gradient species groups site factor classes 1 2 3 4 5 subunits 1 2 1 2 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”.

  21. Vegetation types calibrated for GHG emissions: GESTs: Greenhouse gas Emission Site Types Some examples: Water level Vegetation CH4 CO2 GWP

  22. GESTs with indicator species groups Each GEST with typical species Each GEST with typical GHG emissions

  23. 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!

  24. 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

  25. Vegetation forms: developed for NE Germany  test of correlations in Belarusian peatlands

  26. 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)

  27. Major gap: abandoned peat extraction sites

  28. 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…

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

  30. GESTs! info: joosten@uni-greifswald.de

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