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... fens (green), bogs (red), transitional peatlands

(purple): former extent ~15% of the area

Present area of natural peatlands: 1.5 mio ha

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

Drained peatlands are huge emittors of CO2 + N2O

CO2 emission

Central Europe is peatland emission hot spot

Does rewetting reduce greenhouse gas emissions?

How much less emissions after rewetting?

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!)…

BMU funded rewetting project (2008-2011)

Deliverables: methodology for

GHG assessment standard for

voluntary trade 15,000 ha rewetted

and sustainably managed

local capacity

Measuring directly is complicated, time consuming,

expensive ( € 10,000 /ha/yr) proxy indicators

Mean water level is best predictor of emissions

(meta-analysis of 25 site parameters in W-Europe)

-10

-5

0

5

10

15

20

25

30

-120 -100 -80 -60 -40 -20 0

mean water level [cm]

t C

O2-

eq∙h

a-1

∙a-1

bogs

fens

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

-100

0

100

200

300

400

500

600

-100 -80 -60 -40 -20 0 20 40 60

mean water level [cm]

kg C

H4∙

ha

-1∙a

-1

-2

0

2

4

6

8

10

12

t C

O2-

eq∙h

a-1

∙a-1

bogs

fens

other

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

-5

5

15

25

35

45

55

65

75

85

95

-100 -80 -60 -40 -20 0 20 40

mean water level [cm]

kg N

20∙h

a-1∙

a-1

-2

4

9

14

19

24

29

t C

O2-

eq∙h

a-1∙

a-1

bogs

fens - unfertilized

fens - fertilized

other

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

N2O erratic, but lower with higher water levels

Leave N2O emissions out conservative estimate

-15

-10

-5

0

5

10

15

20

25

30

-100 -80 -60 -40 -20 0

mean water level [cm]

GW

P [

t C

O2-

eq ∙

ha

-1∙a

-1]

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

Emissions strongly related to water level Vegetation strongly related to water level

Use vegetation as indicator for emissions!

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”.

site factor gradient

species groups

site factor classes

subunits 1

1 2

2

3 4 5

1 2

Vegetation types calibrated for GHG emissions:

GESTs: Greenhouse gas Emission Site Types

Some examples: 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

Water level

Vegetation

CH4

CO2

GWP

Vegetation type Typical/differentiating species WL class

CH4 CO2 GWP

Sphagnum-Carex limosa-marsh

Sphagnum recurvum agg., Carex limosa, Scheuchzeria

5+ 12.5<0

(±0)12.5

Sphagnum-Carex-Eriophorum-marsh

Sph. recurvum agg., Carex nigra, C. curta, Eriophorum angustifolium

Drepanocladus-Carex-marsh Drepanocladus div. spec., Carex diandra, Carex rostr., Carex limosa - Carex dominated

Scorpidium-Eleocharis-marsh Scorpidium, Eleocharis quinqueflora - Carex (shunt) dominated

Sphagnum-Juncus effusus-marsh

Juncus effusus, Sphagnum recurvum agg.

Equisetum-reeds Equisetum fluviatile

Scorpidium-Cladium-reeds Cladium, Scorpidium

Sphagnum-Phragmites-reeds Phragmites, Solanum dulcamara

5+ 10<0 / ±0

10

Solano-Phragmitetum Scorpidium, Eleocharis quinqueflora - Phragmites + Solanum without Urtica-gr.

Rorippa-Typha-Phragmites-reeds

Typha latifolia, Phragmites, Rorippa aquatica, Lemna minor

Bidens-Glyceria-reeds Glyceria maxima, Berula erecta, Bidens tripartita, B. cernua

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 <0 2

GESTs with indicator species groups

Each GEST with typical species

Each GEST with typical GHG emissions

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!

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

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

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)

Major gap: abandoned peat extraction sites

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…

Developed with

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

info: joosten@uni-greifswald.de

GESTs!