Effects of climate change and deforestation on carbon sequestration potential in Ethiopian forests

Effects of climate change and deforestation on
potential carbon sequestration and its implication in
forest landscape restoration
World Agroforestry Centre (ICRAF)
Nairobi, March 14, 2016
aWorld Agroforestry Centre (ICRAF), United Nations Avenue, P.O. Box 30677-00100, Nairobi, Kenya
bInstitute of Geography, Friedrich-Alexander-University Erlangen-Nuremberg, Wetterkreuz 15, 91058
Erlangen, Germany
Mulugeta Mokriaa,b, Dr. Aster Gebrekirstosa , Dr. Ermias Aynekulua, Prof. Dr.
Achim Bräuningb

• Brief introduction (forests, drivers of deforestation and
tree mortality)
• Methodology (site description, field, laboratory and
modeling analysis)
• Results (carbon stock, sequestration, growth rate,
impact, resilience and range of ecotone shift)
• Management and restoration implications
Outline

• Tropical forests and agroforests: an important biome,
to stabilize atmospheric carbon cycle and to minimize
climate change impact
• Continued to be degrade due to livelihood related
issues and climate change
• Become major carbon sources and accelerating global
climate change
• There is a need to understand the drivers, processes
and impacts to suggest possible policy and
management options
Introduction

Drivers of deforestation
Picture source: https://www.google.de/search?q=forest+clear+cutting+in+africa&biw=1600&bih=1089&tbm=isch&tbo=u&source=univ&sa=X&ei=6lxXVZ2JMoHaUsq_gbgL&sqi=2&ved=0CDcQ7Ak,
https://www.google.de/search?q=drought+induced+tree+mortality+pictures&biw=1600&bih=1089&tbm=isch&tbo=u&source=univ&sa=X&ei=Ll5XVayOOqahyAP2tIDABw&ved=0CE4Q7Ak
anthropogenic
..since deforestation is the permanent destruction of trees and
forests, it is considered to be one of the contributing factors to
global climate change. (Adams et al. 2010).

climate (drought /temperature)
https://www.google.com/search?q=drought+induced+tree+mortality+picture

 drought induced tree/forest mortality: Across the globe
Australia Europe
Africa
Asia
America

 drought induced forest mortality is projected to increase
Allen et al., 2010,2015

Ethiopia
ALLEN et al., 2015
Since 1970
Before 2010
Between 2010-2015

…forms a climatic buffer
zone between……
Study area

 disaggregate anthropogenic and climate related effects
 estimate the extent of the impact of tree dieback on
ecosystem services (C-sequestration potential)
 assess resilience/adaptation of foundation species in
their natural environment
 recommend policy and restoration options

https://www.google.com/search
Dendrochronology: "reading history books of trees"
Methodology

- Greenhouse effect
- Heavy metals
- Air pollution
- Forest diseases
GLACIO-
LOGY
ENVIRONMENTAL
RESEARCH
CLIMATOLOGY GEOMORPHOLOGY
HYDROLOGY
TEKTONICS/
VOLCANISM
DENDRO-
ECOLOGY
- Ground water-
fluctuations
- Peat bog growth
- Flood reconstruction
- River history
- Dating
of moraines
- glacier-
fluctuations
- Climate and
wood formation
- climate
reconstruction
- wind-/ fire-/
snow impact
- Erosion rates
- Debris flow frequency
- Slope movement
- Permafrost
dynamics
- Volcanic eruptions
- earthquakes
© Bräuning, Insitut für Geographie, Univ. Stuttgart, 24.04.2002

Interview with local people and experts in the area:
 Their local knowledge about the forest and their
perception
 Drivers of deforestation
 Change in climate and its impacts
 When the tree dieback started and its trend
Method- field data collection

Biometric data
• Five transects (1km)
• 57 plots
• 50m X 50m size
• Tree height and DBH>
5cm were measured

Sample collection for tree-ring analysis
 20 disks (dead and living)
 DBH range 20- 48 cm

Wood characteristics and growth ring identification
Bark
 J. procera forms distnict growth-rings
DRP
DRP
Methods- laboratory analysis
double staining with
Safranin-Astra blue

Radioactive carbon analysis
Methods- laboratory analysis
Year
1950
1955
1960
1965
1970
1975
1980
1985
1990
1995
2000
2005
2010
F
14
C_NH_zone3
1.0
1.2
1.4
1.6
1.8
F14C-NH zone 3
Tree ring (14C)
Ethiopia
Hua et al., 2013. Atmospheric
radiocarbon for the period
1950–2010. RADIOCARBON ,
Vol 55, Nr 4, 2013, p 2059–
2072Mokria et al., in preparation

GRB
Wider
rings
Narrow ring Wider
rings
Tree ring width measurement
r1
r2
r3
r4
pith

Density measurement
Water displacement method
- Fresh volume
- Oven dry for 72h under 105 oC
- Density = dry weight/ fresh
volume (g/cm3)

Two biomass estimation allometric equations
 improved pan-tropical allometric model by Chave et al., 2014
• where, coefficient a = 0.0673 and b = 0.976 and parameter AGB (kg), ρ = specific wood density (g/cm3),
D (cm) and H (m).
 the flexible tropical mixed-species biomass estimation model by
Ketterings et al. (2001):
• where, with coefficients D in centimeter, ρ in gram per cubic centimeter, AGBest, in kilogram, ϒ is a
constant parameter over a range of sites calculated as ϒ = a/ρ(wood specific gravity), where a = 0.066,
is the constant parameter, b is a scaling exponent derived from species-specific height-diameter
allometry (this study).
b
HDaAGB )( 2
1  
b
DAGB 
 2
2 
Biomass estimation

….. Propagation of measurement errors in σD, σH , σρ and σr , to
estimated AGB:
(Chave 2004, Schöngart et al., 2011)
Eq.1
Eq.2
total uncertainty per plotuncertainty in each trees
… then, the mean AGB and new variance form Eq. (1) and (2) to
consider errors due to model selection
Wood Science Underpinning Tropical Forest Ecology and Management,
Tervuren, May 26-29, 2015
Mokria et al.; Tree dieback affects carbon sequestration potential of a dry afromontane forest
 
 2bH)(ρDσ1b)2(Dba
2b)2D(ρHσ1bHba
2
b)2D(Hpσ1bρba)AGB(
2
σ





 1
50
1
2
1
.
)(
)( ))( AGB
AGB  
     2
Dbr
2
Dr
2
D)AGB(
2
σ b
D
bb
r
1
2

  )( 
50
2
2
2
.
)()( ))( AGBAGB  
  2502
2
1
22
.)()()(  AGBAGBmeanAGB 

Species Status No. of
trees
Mean [SE]
DBH (cm)
Mean [±
SE] H (m)
Range of
DBH
(cm)
Range of
H (m)
Proportion of trees (%) under
diff. diameter class (cm)
5-15 15-30 30-50 >50
Juniperus alive 1069 16.5 [0.96] 6.1 [0.29] 5-88 2-17.5 60.6 33.8 4.8 0.8
snag 607 17.2 [1.17] 5.9 [0.29] 5-90 2-20 48.4 44.2 5.6 1.8
Olea alive 1313 18.5 [0.83] 5.5 [0.16] 5 - 90 2-17 39.2 52.7 7.0 1.1
snag 802 19.6 [1.23] 4.7 [0.16] 5-114 2-13.5 48.3 46.4 3.7 1.6
Co-occurring alive 1747 11.4 [0.43] 4.2 [0.09] 5-85 2-17 78.1 20.8 1.0 0.1
snag 120 10.5 [0.73] 3.6 [0.20] 5-27 2-8.4 74.2 22.5 0.0 3.3
Summary of plot inventory data: DBH, H, and SE, refer to diameter at
breast height, tree height, and standard error, respectively…..
 92.2% of snags are from foundation tree species (i.e. juniperus and olea)
Total= 5658
Results
From inventory
 25% were dead trees

Total estimated - aboveground C-stock
At landscape level, 34.5% C-stock is going to be a source of carbon…
Mean aboveground C-stock
(Kg C tree-1)
Total aboveground C-stock
(Mg C ha-1)
Species Living trees Snags Eq. 2 Eq. 3 Mean
Proportion of C-stock
estimated from snags
(%)
J. procera 41.0 (±7.7) 57.8 (±10.9) 8.3 (±1.5) 10.6 (±1.8) 9.4 (±1.6) 44.5 %
O. europaea 80.7 (±17.6) 72.9 (±15.9) 11.0 (±2.2) 13.9 (±2.6) 12.4 (±2.4) 35.6 %
Co-occurring 22.1 (±6.6) 12.2 (±3.6) 2.0 (±0.5) 2.4 (±0.7) 2.2 (±0.6) 3.7 %
All species 43.6 (±9.9) 62.0 (±14.1) 17.2 (±3.5) 21.4 (±4.3) 19.3 (±3.9) 34.5 %
Total above ground C-stock/ha -19.3 Mg C/ha ,

Diameter class (cm)
5-10
10-15
15-20
20-25
25-30
30-35
35-40
40-45
45-50
>50
Carbonstock(Mg)
0
2
4
6
8
10
12
Living trees
Snags
(a) J. procera
Diameter class (cm)
5-10
10-15
15-20
20-25
25-30
30-35
35-40
40-45
45-50
>50
Carbonstock(Mg)
0
4
8
12
16
20
24
28
Living trees
Snags
(b) O. europaea
Diameter class (cm)
5-10
10-15
15-20
20-25
25-30
30-35
35-40
40-45
45-50
>50
Carbonstock(Mg)
0
2
4
6
8
Living trees
Snags
(C) Other species
Total aboveground carbon-stock - under different
diameter classes
Note: C-stock in snags increase with increasing diameter class

Total aboveground carbon-stock - along an elevation
gradient
Elevation (m.a.s.l)
1400
1500
1600
1700
1800
1900
2000
2100
2200
2300
2400
2500
2600
2700
2800
Carbonstock(Mg)
0
5
10
15
20
Living trees
Snags
(b) O. europaea
Elevation (m.a.s.l)
1400
1500
1600
1700
1800
1900
2000
2100
2200
2300
2400
2500
2600
2700
2800
Carbonstock(Mg)
0
2
4
6
8
10
12
14
16
Living trees
Snags
(a) J. procera
Elevation (m.a.s.l)
1400
1500
1600
1700
1800
1900
2000
2100
2200
2300
2400
2500
2600
2700
2800
Carbonstock(Mg)
0
2
4
6
Living trees
Snags
(C) Other species
 the trees at lower elevation are vulnerable due to increase in temperature
and heat wave from Dallol
 shifting ecotone by 500m
what is the implication of this change when we consider restoration of
degraded landscapes?

Tree age and diameter increment
 tree age ranges from 106 to 248 years
 the radial increment range: 0.25 to 2.1 mm year-1
 the overall mean of 0.91 (± 0.02) mm year-1
C-sequestration determination
Year (Age)
50 100 150 200 250
Cumulativediameter(cm)
0
10
20
30
40
50

Age and C-stock in AGB relationship
• From the above model we drive the annual carbon sequestration (kg
year-1 tree-1): C-sequestration = CC-stock (t + 1) – CC-stock (t), where
CC–stock is cumulative carbon stock over the entire life span of tree
growth
Year(Age)
100 125 150 175 200 225 250
C-stockinAGB(KgC)
0
100
200
300
400
500
Eq. 2
Eq. 3
Sigmoidal (Eq.2)
Sigmoidal (Eq. 3)
Eq.2
a = 577.8
b = 40.3
c =207.4
r2 = 0.81, p < 0.001
n = 20 Eq.3
a = 479.4
b = 36.4
c = 186.9
r2 = 0.8, P < 0.001
n = 20

Mean annual C-sequestration rate per tree
 The mean annual C-sequestration rate: 1.12 (± 0.05) kg C tree-1 yr-1.
Years(age)
0 25 50 75 100 125 150 175 200 225 250
C-sequestrationinAGB(KgCyr-1)
0.0
0.5
1.0
1.5
2.0
2.5
3.0
C-sequestration[M2]
C-sequestration[M3]
Mean C-sequestration

Carbon-sequestration potential- at landscape level
Mean annual C-sequestration potential (Mg C ha-1 year-1)
Species Pre-tree-dieback Post-tree dieback
Lost CS-potential
(%)
J. procera 0.22 (± 0.03) 0.14 (± 0.03) 36.4
O. europaea 0.18 (± 0.02) 0.11 (± 0.02) 39.0
Co-occurring species 0.15 (± 0.01) 0.14 (± 0.01) 6.7
All species 0.45 (± 0.03) 0.33 (± 0.03) 27.0
• Pre and Post-tree dieback carbon-sequestration
• Lost carbon-sequestration potential due to dieback
Note: Annual C-sequestration per hectare
= 1.12 (± 0.05) kg C tree-1 year-1 X stem density per ha

It is an indication of required period of time to reach
optimum harvestable size under natural condition
Other ecological implications
Years (Age)
0 50 100 150 200 250
CGW(cm)
0
10
20
30
40
50
MAI(cm)
0.06
0.12
0.18
0.24
CGW
MAI
J. procera require more than 100 years to
reach… the impact is long lasting impact

What is the implication if we consider to restore this degraded landscapes?

 trees at lower elevation are more vulnerable due to increase
in temperature and heat wave from Dallol
 dieback caused upward ecotone shift by about 500m,
 ecotone shift Indicates changing environmental conditions
 the impact of tree dieback on the ecosystem is long-lasting
 It is costly to curb the situation after major vegetation loss
 conservation is cheaper than restoration
 restoration should consider a micros site conditions and
climate resilient species
 Dendrochronology is very useful tool to determine annual
carbon sequestration (temporal and spatial), to asses
resilience of species , understand landscape history and
population dynamics
Conclusion and recommendation

Thank you!
Acknowledgement
CRP 6.4 for co-funding
Mekele University for support during field work
Edith Anyango for assisting laboratory work

Effects of climate change and deforestation on carbon sequestration potential in Ethiopian forests

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Effects of climate change and deforestation on carbon sequestration potential in Ethiopian forests