GEST Greenhouse Emissions Site Types
• The ‘emissions avoided’ model developed by John Couwenberg et al. at University of Greifswald.
• Couwenberg et al., 2011, Hydrobiologia.
Using a Proxy for GHG fluxes
• Direct methods
– chamber measurements –
– Micro-meteorology measurements–
• Indirect method
– Use a proxy that indicates ghg fluxes
Three parameters currently emerge as suitable proxies for GHG
fluxes from peat soils:
• Subsidence
• Water level
• Vegetation
Possible Proxies
Subsidence
Su
bis
den
ce (
cma-1
)
Drainage depth (cm)
CONS:
1. hardly covertable into CO2 emission, due
to shrinkage and compaction
2. not an indicator for N2O and CH4
3. only for drained situations
Water table depth
Carbon dioxide O - flooded site & lysimeter experiments of Mundel (1976)
• - based on long term
subsidence measurements (van den Akker et al., 2008;
Verhagen et al., 2009) • -
representing NEP measurements corr. for harvest export (Augustin unpubl., Bortoluzzi et al. 2006, Drösler 2005, Flessa et al. 1998, Jacobs et al. 2003, Meyer 1999, Müller et al. 1997, Mundel 1976, Nieveen et al. 1998, Veenendaal et al. 2007.
Methane
n = 99 - collated from Augustin (2003, unpubl.), Augustin & Merbach (1998), Augustin et al. (1996), Bortoluzzi et al. (2006), Drösler (2005), Hendriks et al. (2007), Jacobs et al. (2003), Meyer (1999), Müller (1999), Sommer et al. (2003), Tauchnitz et al. (2008), Van den Bos (2003), Van den Pol-Van Dasselaar et al. (1999), Van Huissteden et al. (2006), Von Arnold (2004), Wild et al. (2001).
CONS:
1. mapping of water level via remote sensing
is so far impossible
2. direct monitoring is very labour-intensive
Vegetation Emissions strongly related to water level
and
Vegetation can be strongly related to water level –e.g. Ellenberg moisture
values
- Species groups presence/absence as indicator for mean water levels
- Initially NE German metadata, country-specific refinement in Belarus &
Ukraine peatlands
site factor gradient - moisture
species groups
Moisture classes
subunits 1
1 2
2
3 4 5
1 2
A simpe GEST example
Re-wetting Bog
green Sphagnum
lawn (optimal)
Sphagnum
Eriophorum lawn
acidophilous
Molinia-meadow
Vegetation
+10 … -10+10 … -20-15 … -45water level*
GWP
CO2
CH4
GEST
3-1.516.5
-2-215
50.51.5
wet peatmoss
lawn
very moist
peatmoss lawn
moist forbs &
meadows
green Sphagnum
lawn (optimal)
Sphagnum
Eriophorum lawn
acidophilous
Molinia-meadow
Vegetation
+10 … -10+10 … -20-15 … -45water level*
GWP
CO2
CH4
GEST
3-1.516.5
-2-215
50.51.5
wet peatmoss
lawn
very moist
peatmoss lawn
moist forbs &
meadows
-13.5t CO2-eq.·ha-1·a-1
*median of the dry and wet season relative to the surface, cm
Moderately dry
cultivated
peatland
24
Very moist
reeds and Wet
reed/sedge fens
Very moist
reeds and Wet
reeds/sedge
fens
Rewetting open fen Future emissions avoided
Year 0 Year 10 Year 20
Moderately dry
cultivated
peatland
24
Moderately dry
cultivated peatland
24
Very moist reeds/
Wet reeds & sedge
fens
15.5/8.5
Moderately dry
cultivated
peatland
24
Bas
elin
e S
cen
ario
R
ewet
tin
g Sc
en
ario
Very moist reeds/
Wet reeds & sedge
fens
15.5/8.5
Moderately dry
cultivated
peatland
24
8.5/-15,5 -8.5/-15.5
Metadata Indicator
species/communities with water table depth
Initial values for avoided emissions
= Baseline - Project
Local refinement Measuring
Species/communities Water depth
Final value for avoided emissions
Emissions accounting mechanisms, auditing
etc
