Transcript An introduction to palaeoecology

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)
30
25
t CO 2-eq∙ha -1 ∙a -1
20
15
10
5
bogs
fens
0
-120
-100
-80
-60
-40
-20
0
-5
-10
mean water level [cm]
CO2 emissions clearly correlate with water levels:
they become less with higher water levels
600
bogs
12
fens
500
other
kg CH 4∙ha -1∙a -1
400
8
300
6
200
4
100
0
-100
t CO 2-eq∙ha -1 ∙a -1
10
2
0
-80
-60
-40
-20
0
-100
20
40
60
-2
mean water level [cm]
CH4 emissions clearly correlate with water levels:
they increase when higher than 20 cm - surface
95
bogs
fens - unfertilized
85
29
fens - fertilized
other
24
kg N20∙ha-1∙a-1
65
19
55
45
14
35
t CO2-eq∙ha-1∙a-1
75
9
25
15
4
5
-5-100
-80
-60
-40
-20
0
20
40 -2
mean water level [cm]
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
30
25
GWP [t CO 2-eq ∙ha -1∙a -1]
20
15
10
5
0
-100
-5
-80
-60
-40
-20
0
-10
-15
mean water level [cm]
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
subunits
2
1
site factor classes
1
2
3
4
5
1
2
Vegetation types calibrated for GHG emissions:
GESTs: Greenhouse gas Emission Site Types
Some examples:
Water level
2-, 2+, 2~
(3+/2+) 3+
4+/3+
4+
5+
6+
Vegetation
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
CH4
CO2
GWP
GESTs with indicator species groups
Vegetation type
Typical/differentiating species
Sphagnum-Carex limosamarsh
Sphagnum recurvum agg., Carex limosa, Scheuchzeria
Sphagnum-CarexEriophorum-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
WL
class
CH4
CO2
GWP
5+
12.5
<0
(±0)
12.5
EachJuncus
GEST
withrecurvum
typical
species
effusus, Sphagnum
agg.
Sphagnum-Juncus effususmarsh
Equisetum fluviatile
Each GEST
with typical GHG emissions
Equisetum-reeds
Scorpidium-Cladium-reeds
Cladium, Scorpidium
Sphagnum-Phragmites-reeds
Phragmites, Solanum dulcamara
Solano-Phragmitetum
Scorpidium, Eleocharis quinqueflora - Phragmites + Solanum
without Urtica-gr.
5+
10
<0 /
±0
10
Rorippa-Typha-Phragmitesreeds
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
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…
GESTs!
info: [email protected]