improvements to the representation of forest land in the...
TRANSCRIPT
Improvements to the representation of forest land in the UK GHG inventory and implications for KP accounting
Paul Henshall, Robert Matthews (and Gwen Buys, CEH)
Forest Mensuration, Modelling and Forecasting
Centre for Sustainable Forestry and Climate Change
JRC LULUCF Workshop, Arona, 6th May 2014
12/05/2014 2
• Input data on forests
• Modelling
• Representation of management
• How the results have changed
• Implications for KP accounting (CP1 and CP2).
A description of improvements
to the GHG calculations for forest land
What we will aim to cover
12/05/2014 3
Input data: forest area and species
0.0
100.0
200.0
300.0
400.0
500.0
600.0
700.0
800.0
900.0
Norw
ay sp
ruce
Sitk
a sp
ruce
Cors
ican
pine
Sco
ts pin
e
Lodg
epole
pine
Eur
opean
larc
h
Japa
nese la
rch
Doug
las fir
Gra
nd fir
Nobl
e fir
West
ern
red
cedar
West
ern
hemlo
ckOak
Bee
ch
Syc
amor
e, ash
, birc
h
Noth
ofagu
s
Pop
lar
Are
a (
kh
a)
Post-1920 planting Area
Pre-1921 planting Area
Previously:
• Post-1920 forest areas (pre-1921 areas assumed to be ‘in balance’)
• All conifer area represented by Sitka spruce
• All broadleaf area represented by beech.
Updated:
(based on NFI from 1990s)
12/05/2014 4
Input data: growth rates
Previously:
• Sitka spruce all with average potential growth rate of 12 m3 ha-1 yr-1 apart from Northern Ireland (14)
• Beech all with average potential growth rate of 6 m3 ha-1 yr-1.
0
50
100
150
200
250
2 4 6 8 10 12 14 16 18 20 22 24
Yield class (m3 ha-1 yr-1)
Are
a (
kh
a)
Western hemlock
Western red cedar
Noble fir
Grand fir
Douglas fir
Japanese larch
European larch
Lodgepole pine
Scots pine
Corsican pine
Sitka spruce
Norway spruce
0
50
100
150
200
250
300
350
400
450
500
2 4 6 8 10 12 14 16 18 20 22 24
Yield class (m3 ha-1 yr-1)
Are
a (
kh
a)
Poplar
Nothofagus
Sycamore, ash, birch
Beech
Oak
Updated:
(based on records for Public Forest Estate)
12/05/2014 5
Input data: age distribution
Previously:
• Effectively the new planting projected forward (no independent data, example shown for Wales)
0
1
2
3
4
5
6
1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010 2020
Year of planting
Are
a (
kh
a)
Conifer
Broadleaf
12/05/2014 6
Analysis of forest age distribution
0
5
10
15
20
25
30
35
40
45
50
55
60
65
0 50 100 150 200
Age class
Are
a (
kh
a)
0
5
10
15
20
25
30
35
40
45
50
55
60
65
0 50 100 150 200
Age class
Are
a (
kh
a)
Updated: Reconciling new planting with NFI age distributions
Conifer Broadleaf
0
1
2
3
4
5
6
1910 1920 1930 1940 1950 1960 1970 1980 1990 2000 2010 2020
Year of planting
Are
a (
kh
a)
Conifer
BroadleafFC data on
“new planting”
12/05/2014 7
Which gives this profile for new planting …
0
5
10
15
20
25
30
35
401
50
0
15
11
15
22
15
33
15
44
15
55
15
66
15
77
15
88
15
99
16
10
16
21
16
32
16
43
16
54
16
65
16
76
16
87
16
98
17
09
17
20
17
31
17
42
17
53
17
64
17
75
17
86
17
97
18
08
18
19
18
30
18
41
18
52
18
63
18
74
18
85
18
96
19
07
19
18
19
29
19
40
19
51
19
62
19
73
19
84
19
95
20
06
Are
a k
ha
Year
UK - CFlow Planting InputsBroadleaf
Conifer - org soil
Conifer - min soil
0
5
10
15
20
25
30
35
40
15
00
15
11
15
22
15
33
15
44
15
55
15
66
15
77
15
88
15
99
16
10
16
21
16
32
16
43
16
54
16
65
16
76
16
87
16
98
17
09
17
20
17
31
17
42
17
53
17
64
17
75
17
86
17
97
18
08
18
19
18
30
18
41
18
52
18
63
18
74
18
85
18
96
19
07
19
18
19
29
19
40
19
51
19
62
19
73
19
84
19
95
20
06
Are
a k
ha
Year
UK - CARBINE Planting InputsBroadleaf
Conifer - org soil
Conifer - min soil
Updated:
Previously:
12/05/2014 8
Input data: rotations
Previously:
• Sitka spruce all age 59 years (minor variations), all beech 91 years.
0
50
100
150
200
250
300
350
400
450
500
Less than
30
30-39 40-49 50-59 60-69 70-99 100-119 120-149 150+
Rotation (years)
Are
a (
kh
a)
Poplar
Nothofagus
Sycamore, ash, birch
Beech
Oak
Western hemlock
Western red cedar
Noble fir
Grand fir
Douglas fir
Japanese larch
European larch
Lodgepole pine
Scots pine
Corsican pine
Sitka spruce
Norway spruce
Updated:
• Based on growth rates and reconciliation of ages with new planting.
12/05/2014 9
• Species-specific:
• Forest growth functions (published FC models)
• Wood density estimates (published source)
• Biomass expansion factors for branches, foliage and roots (new analysis of available data)
• Allocation factors for harvested wood.
Refined modelling: CARBINE
Some examples …
12/05/2014 10
Assumptions about management
Previously:
• All in management, thinned and clearfell.
Updated:
(based on records for Public Forest Estate and Woodland Grant Scheme records provided by country representatives)
0
100
200
300
400
500
600
700
Norw
ay sp
ruce
Sitk
a sp
ruce
Cors
ican
pine
Sco
ts pin
e
Lodg
epole
pine
Eur
opean
larc
h
Japa
nese la
rch
Doug
las fir
Gra
nd fir
Nobl
e fir
West
ern
red
cedar
West
ern
hemlo
ckOak
Bee
ch
Syc
amor
e, ash
, birc
h
Noth
ofagu
s
Pop
lar
Are
a (
kh
a)
Not in management
Continuous
Thin/fell
No thin/fell
12/05/2014 11
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
1975 1980 1985 1990 1995 2000 2005 2010
Year
Vo
lum
e p
rod
uc
tio
n (
millio
n m
3)
Predicted
Reported
Management/production ‘reality check’
About „double‟ About +30%
Example for Wales
12/05/2014 12
• Gross:net area
• In production:not in production (private sector)
• Thin:no-thin (private sector, historical for all)
• Production ‘held back’ in private sector?
• Growth rate assumptions (private sector)
• New planting:pre-1920 forests (FC:private sector)
• Under-reporting in production statistics
Why is predicted production higher than reported?
Management/production ‘reality check’
12/05/2014 13
Input data (again): deforestation
Previously:
Updated:
Results
12/05/2014 15
Afforestation
-3.5
-3
-2.5
-2
-1.5
-1
-0.5
0
0.5
1985 1990 1995 2000 2005 2010 2015 2020
Year
Em
issio
n/r
em
oval
(+/-
) M
tCO
2
Previously
Updated
12/05/2014 16
Deforestation
0
0.2
0.4
0.6
0.8
1
1.2
1990 1995 2000 2005 2010 2015 2020
Year
Em
issio
n/r
em
oval
(+/-
) M
tCO
2 Previously
Updated
12/05/2014 17
Forest Management
-18
-16
-14
-12
-10
-8
-6
-4
-2
0
1990 1995 2000 2005 2010 2015 2020
Year
Em
issio
n/r
em
oval
(+/-
) M
tCO
2 Previously
Updated
Implications for KP accounting
12/05/2014 19
• FM removals now much bigger than previously reported
• However, FM removals are capped in CP1.
• The cap is related to the level of FM removals in the base year, but was fixed at that level at the time the details were negotiated, and doesn’t get changed now
• Therefore, removals accounted due to FM will not change in CP1
• Accounted removals due to afforestation lower than previously suggested (down by about 10% or 300 ktCO2, yr-1)
• Accounted emissions due to deforestation higher than previously suggested (up by about 85% or 500 k tCO2, yr-1).
First commitment period
12/05/2014 20
• At present, the main issue is the implication of the changed FM results for the FMRL.
• FM removals now much bigger than previously reported, and projected level now very likely to be significantly different to when the FMRL was originally set.
• It is likely that a Technical Correction to the FMRL will be required…
Second commitment period
12/05/2014 21
Forest Management
-18
-16
-14
-12
-10
-8
-6
-4
-2
0
1990 1995 2000 2005 2010 2015 2020
Year
Em
issio
n/r
em
oval
(+/-
) M
tCO
2 Previously
Updated
Original
projection
New
projection
Basis for calculating
Technical Correction?
12/05/2014 22
• Main challenge: There is a new National Forest Inventory (NFI) for GB
• The base year for the new NFI is ~2013
• This NFI includes directly and transparently-calculated estimates of tree carbon stocks
• We will need to decide whether to refer directly to these carbon stock estimates or use them for validation of model results
• There could be implications for back-calculation (i.e. for period 1990 to 2012)
• Several other challenges: Integrating calculations for non-CO2 GHGs; soil GHG emissions/removals related to AR and particularly D; better reconciliation with actual wood production?
Future challenges
Thank you