Journal of Environment and Waste Management
JEWM
Vol. 2(4), pp. 102-107, October, 2015. © www.premierpublishers.org, ISSN: XXXX-XXXX
Research article
Estimation of carbon stored in selected tree species in
Gedo forest: Implications to forest management for
climate change mitigation
Hamere Yohannes1*, Teshome Soromessa2, Mekuria Argaw3
1*Department
of Natural Resource Management, College of Agriculture and Natural Resource Science, Debre Berhan
University, Post Box No: 445, DebreBerhan, Ethiopia.
2,3 Center for Environmental Science, College of Natural Science, Addis Ababa University, Post Box No: 1176, Addis
Ababa, Ethiopia.
Global forests are extremely diverse and provide a variety of ecosystem services including
carbon sequestration. Large trees are the most effective organisms to stock atmospheric
carbon. Ethiopia has substantial forest resource cover. But there is still limitation of scientific
studies that magnify the role of forests for climate change mitigation. This study focus on the
estimation of selected tree species carbon stock and their variation across different diameter at
breast height, tree height and stem density in Gedo forest. The data collected from 200m2
sample plots by using systematically stratified sampling method. The main finding of this study
was dominant trees in the forest contribute large amount of total carbon density stock by
storing 74.59% of total carbon. The amount of carbon stocked in selected trees significantly
varies within different diameter and height classes. Trees which have large height and diameter
but smaller in number store large amount of aboveground and belowground biomass carbon
with maximum 589.24ton ha-1 carbon at higher diameter class. These findings demonstrate that
tree biomass carbon determined by tree stand structure (density, diameter and height).
Keywords: Climate change mitigation, tree diameter, forest carbon stock, tree height, stem density.
INTRODUCTION
Climate change is a major global threat. Over the last
century, global temperatures have risen by 0.7°C
(Eliasch, 2008). Global climate change is predicted to
lead to rising temperatures, sea-level rise, changing
weather patterns, and more unpredictable and severe
weather events. It is likely to cause changes in rainfall
patterns, flooding, drought periods, forest fire frequency,
and fluctuating water availability. The combined effect will
decrease agricultural production and increase food
insecurity (Malla and Blaser, 2010).
Globally, forests cover about 4 billion hectares (ha) of
land, or 30% of the Earth’s land surface (FAO, 2008).
Tackling climate change is one of the most important
roles of forest by storing and sequestering carbon.FAO
(2010) Estimated that the world’s forests store 289 Gt of
carbon in their biomass alone. Deforestation and forest
degradation are major contributors to rising levels of CO 2
in the atmosphere and the associated changes in the
Earth’s climate. Tropical forests are being degraded and
deforested at the average rate of 8-15 million hectares
per year.
*Corresponding
author:
Hamere
Yohannes,
Department of Natural Resource Management, College
of Agriculture and Natural Resource Science, Debre
Berhan University, Post Box No: 445, Debre Berhan,
Ethiopia.
E-mail:
[email protected],
[email protected]
Estimation of carbon stored in selected tree species in Gedo forest: implications to forest management for climate change mitigation
Yohannes et al.
102
Figure 1. location map of the study area
Ethiopia is one of the countries that have significant
amount of forest resources. According to (FAO, 2010),
Ethiopia’s forest cover is 12.2 million ha (11%).The forest
and woody vegetation of Ethiopia play an important
environmental role in storing anthropogenic atmospheric
carbon. The largest carbon store is found in the
woodlands (45.7%) and the shrub lands (34.4%) (Yitebtu
et al., 2010).
Sustainable forest management provides an effective
framework for forest-based climate change mitigation
because vegetation characteristics like DBH, tree height,
leaf area index, stem density/volume and above ground
biomass can have influence the forest productivity (Lal,
2005;Offiong and Iwara, 2012). Since carbon
sequestration depends on productivity, all factors that
affect productivity will also affect carbon sequestration
(FAO, 2012).
The trees and forests of Ethiopia are under tremendous
pressure because of the radical decline in mature forest
cover and the continual pressures of population increase,
Inappropriate farming techniques, land use competition,
land tenure, and forest modification or change and
conversion. (Yitebtu et al., 2010) Forest change
accounting for an estimated 35% of total GHG emissions,
the status of the forest resources should be considered at
risk. However, the attention given to conservation and
sustainable use of these biological resources is
inadequate due to low level awareness about the wide
and vital role of the forests (Dereje, 2007). In summary,
Forest resources in the country have undergone
substantial changes over the years due to competing
land uses and unbalanced forest utilization. This is true in
the Gedo forest, as reported by (Berhanu et al.,
2014).This paper intended to explain the role of large
dominant trees for climate change mitigation by stocking
substantial amount of carbon in their biomass.
MATERIALS AND METHODS
Description of study area
This study conducted in Gedo Forest which is located in
Cheliya District, West Shewa Zone of Oromia National
Regional State. The district has 3060m a.s.l highest pick
and 1300m lowest altitude (Endalew, 2007). The exact
geographical location of the study area map defines in
Figure 1. The natural forest area is estimated about 5,000
ha. According to (Berhanu et al., 2014) study, in Gedo
forest dominated by Olinia rochetiana, Olea europaea
subsp. cuspidata, Prunus Africana, Ekebergia capensis,
Allophylus abyssinicus, Syzygium guineese sub sp.
Afromontanum, Ficussur, Podocarpus falcatus species.
Methodology
Delineation of the study boundaries was done by using
GPS tracking. Systematic sampling method was used to
take samples from 10m x 20m plot. To reveal the tree
biomass, all live trees with a diameter ≥ 5cm within
the plot were measured by using diameter tape. Then
DBH (at 1.3m) and tree height were measured. After field
measurement aboveground, belowground, stem density
and important value index were calculated by the
following formulas:
According to (Pearson et al., 2005), field carbon stock
measurement guideline, the equation developed for
tropical county forests used to calculate the above
ground biomass is given below:
Estimation of carbon stored in selected tree species in Gedo forest: implications to forest management for climate change mitigation
J. Environ. Waste Manag.
AGB = 34.4703 - 8.0671 (DBH) + 0.6589 (DBH2)
……………………………………. (equ.1)
Where, AGB (above ground biomass) in kg., DBH is
diameter at breast height in cm. The carbon content in
the biomass were estimated by multiplying 0.47 while
multiplication factor 3.67 needs to be used to estimate
CO2 equivalent
To estimate below ground biomass, It was used root-toshoot ratio, which has become the standard method for
estimating root biomass from the more easily measured
shoot biomass. The equation developed by (MacDicken,
1997).
The equation is given below:
BGB
=
AGB
×
0.2
…………………………………………………………………
(equ. 2)
Where, BGB is below ground biomass, AGB is
above ground biomass, 0.2 is conversion factor (or
20% of AGB). Then the carbon content converts
accordingly.
According to (Kent and Coker, 1992)the stem density
was calculated by the following formula:
𝐷=
𝑇ℎ𝑒 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑎𝑏𝑜𝑣𝑒 𝑔𝑟𝑜𝑢𝑛𝑑 𝑠𝑡𝑒𝑚𝑠 𝑜𝑓 𝑎 𝑠𝑝𝑒𝑐𝑖𝑒𝑠 𝑐𝑜𝑢𝑛𝑡𝑒𝑑
𝑆𝑎𝑚𝑝𝑙𝑒𝑑 𝑎𝑟𝑒𝑎 𝑖𝑛 ℎ𝑒𝑐𝑡𝑎𝑟𝑒
… . . (equ.3)
Where D is stem density.
Importance Value Index (IVI)
According to (Kent and Coker, 1992), it often reflects the
extent of the dominance, occurrence and abundance of a
given species in relation to other associated species in an
area. It combines data for three parameters (relative
frequency, relative density and relative abundance)
Importance value index (IVI) = RD + RF +
RDO……………............... (eq. 4)
Where, RD is Relative Density, RF is Relative Frequency,
and RDO is Relative Dominance.
𝑅𝑒𝑙𝑎𝑡𝑖𝑣𝑒 𝑑𝑒𝑛𝑠𝑖𝑡𝑦
𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑔𝑟𝑜𝑢𝑛𝑑 𝑠𝑡𝑒𝑚𝑠 𝑜𝑓 𝑎 𝑠𝑝𝑒𝑐𝑖𝑒𝑠
=
𝑇𝑜𝑡𝑎𝑙 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑎𝑏𝑜𝑣𝑒 𝑔𝑟𝑜𝑢𝑛𝑑 𝑠𝑡𝑒𝑚𝑠 𝑖𝑛 𝑡ℎ𝑒 𝑠𝑎𝑚𝑝𝑙𝑒 𝑎𝑟𝑒𝑎
× 100. . (𝑒𝑞. 5)
Frequency of a species
Frelative =
Total frequency of all tree species
× 100 … … … … … … … … … … … … … (eq. 6)
𝑅𝑒𝑙𝑎𝑡𝑖𝑣𝑒 𝐷𝑜𝑚𝑖𝑛𝑎𝑛𝑐𝑒 (𝑅𝐷𝑂)
𝑇𝑜𝑡𝑎𝑙 𝐵𝐴 𝑜𝑓 𝑎 𝑠𝑝𝑒𝑐𝑖𝑒𝑠
=
𝑆𝑢𝑚 𝑜𝑓 𝐵𝐴 𝑜𝑓 𝑎𝑙𝑙 𝑠𝑝𝑒𝑐𝑖𝑒𝑠
× 100 … . . (𝑒𝑞. 7)
Data Analysis
The data analysis for estimation of above ground and
below ground biomass carbon for each tree species was
done by using Statistical package for Social Science
103
(SPSS) software version 20.The differences in mean
DBH and tree height across selected tree species were
evaluated using a one-way analysis of variance
(ANOVA), followed by the least significant difference
(LSD) test for multiple comparison among groups if the
ANOVA revealed an overall significant difference among
the group.
RESULTS AND DISCUSSION
Carbon stock amount within selected tree species
The average total carbon storage in selected tree species
calculated as 13.63 tonha-1 and 50.05 ton ha-1CO2
equivalents. The highest carbon stock was found in
Podocarpus falcatus, Schefflera abyssinica and Prunus
Africana andwith58.08, 42.51 and 20.48 ton ha-1,
respectively. These dominant species also store 213.17,
156.02 and 75.17 ton ha-1CO2equivalents, respectively
(table 1). These species were among the dominant tree
species included with Olinia rochetiana, Olea europaea
subsp.
Cuspidata,
Syzygium
guineese
subsp.
afromontanum,
Myrica
salicifolia,
Chionanthus
mildbraedii and Rhus glutinosa. These dominant species
have more DBH and height mean value. These species
contribute about 74.59% of total carbon density.
According to (Ruiz-Jaen and Potvin, 2010),the dominant
species can determine carbon storage in the forest. In
addition, (Neupane and Sharma, 2014)reported that the
highest carbon stored in species as 48.03 t ha-1 which is
lower than the current study result. This may be due to
better stem density. The least carbon storage observed in
Osyris quadripartite, Rhamnus staddo and Cordia
Africana species with average carbon stock calculated as
0.37 ton ha-1. These species were found in few numbers
in lower DBH and height classes. This is might be due to
they were selectively removed.
The average DBH value for individual tree was 25cm and
30.68cm for species. In other studies it reported
as11.11cm (Shrestha, 2009) and 16.22cm (Khanal et al.,
2010).The result revealed that the current study area has
better mean diameter which is an indication of
productivity status of the forest.
The average carbon stock per plot for aboveground
carbon pool was 281±23.34 ton ha-1 with CO2 equivalent
of 1031.2 ± 85.68 ton ha-1. The average belowground
carbon stock was calculated as 56.19±4.66 ton ha-1 with
CO2 equivalent of 206.24± 17.13 ton ha-1 (Hamere et al.,
2015). Significant variations were found in aboveground
and belowground biomass carbon density across the plot
(P>0:05). The study of (Yangiu et al., 2015) reported that
the average biomass carbon density of the trees in the
sample plot is 136.34 ton ha-1. Similarly, (DeCastilho et
al., 2006) found that the mean tree biomass per plot was
325.6 Mgha-1. The large biomass carbon density can be
related with the presence of higher density of trees which
are more productive and species diversity.
Estimation of carbon stored in selected tree species in Gedo forest: implications to forest management for climate change mitigation
Yohannes et al.
104
Table 1. Estimated Above and below ground biomass carbon amount for selected trees
Scientific Name
Family
Name
AGB
(ton/ha)
BGB
(ton/ha)
AGBC.
(ton/ha)
BGBC.
(ton/ha)
T.C
(ton/ha)
CO2equ.
(ton/ha)
Podocarpaceae
M.
DBH
(cm)
61.9
Podocarpus falcatus
102.98
20.59
48.4
9.68
58.08
213.17
Schefflera abyssinica
Araliaceae
53.8
75.38
15.07
35.42
7.08
42.51
156.02
Prunus Africana
Rosaceae
39.1
36.31
7.26
17.06
3.41
20.48
75.17
Flacourtiaindica
Flacourtiaceae
38
33.96
6.79
15.96
3.19
19.15
70.31
Albizia gummifera
Fabaceae
32.5
23.41
4.68
11
2.2
13.2
48.46
Apodytes dimidiata
Icacinaceae
31.6
21.87
4.37
10.28
2.05
12.33
45.27
Olea europaea subsp.
cuspidata
Schrebera alata
Oleaceae
31
20.87
4.17
9.81
1.96
11.77
43.21
Oleaceae
29.8
18.96
3.79
8.91
1.78
10.69
39.24
Ekebergia capensis
Meliaceae
29.3
18.18
3.63
8.54
1.7
10.25
37.64
Ricinus communis
Euphorbiaceae
28.2
16.54
3.3
7.77
1.55
9.33
34.25
Myrica salicifolia
Myricaceae
27
14.84
2.96
6.97
1.39
8.37
30.73
Acacia abyssinica
Fabaceae
25
12.23
2.44
5.74
1.14
6.89
25.31
Dombeya torrida
Sapindaceae
25
12.23
2.44
5.74
1.14
6.89
25.31
Pittosporum viridiflorum
Pittosporaceae
22.7
9.54
1.9
4.48
0.89
5.38
19.75
Allophylus abyssinca
Sapindaceae
22.3
9.11
1.82
4.28
0.85
5.13
18.86
Syzygium
guineese
subsp. afromontanum
Olea welwitschii
Myrtaceae
22
8.79
1.75
4.13
0.82
4.96
18.2
Oleaceae
21.7
8.48
1.69
3.98
0.79
4.78
17.56
Olinia rochetiana
Oliniaceae
21.1
7.88
1.57
3.7
0.74
4.44
16.31
Phoenix reclinata
Arecaceae
21.1
7.88
1.57
3.7
0.74
4.44
16.31
Fabaceae
19.8
6.65
1.33
3.12
0.62
3.75
13.77
30.68
24.18
4.83
11.36
2.26
13.63
50.05
Erythrina brucei
Average
M. DBH ((mean diameter at breast height); AGBC and BGBC (Above ground and belowground biomass carbon respectively); T.C. (Total
carbon).
Difference in carbon stored across DBH and Height
class of tree species
Biomass carbon stock significantly differed (P < 0.05)
among diameter of standing trees. the large diameter
class (328 individual trees out of total 1714 trees)
contributed 98.33% to the total biomass carbon stock
with total carbon amount 1476.85 ton ha-1 and 5420.01
ton ha-1 CO2 equivalent; the rest of 1386 individuals with
small-diameter class contributed only 1.67% of total
carbon with 24.43 ton ha-1 carbon of total biomass carbon
stock and 89.64 ton ha-1CO2 equivalent(table 2).This
might be possibly due to the relative predominance of
species with small-sized individuals, such as
Chionanthus mildbraedii, Bersama abyssinica and
Maytenus gracilipes in this group, because the DBH
distribution in the Gedo forest show approximately
inverted J shape. This indicates that the forest is
recovering from previous anthropogenic disturbances.
This result supported by (Berhanu et al., 2014). The
current large biomass carbon in larger diameter class
finding consistent with the following studies (Neupane
and Sharma, 2014, DeCastilho et al., 2006, Chave et al.,
2005, Muluken et al., 2015, Kuamppi et al., 2015).
The lowest stem density found that in DBH > 150cm
which is the largest class and the largest stem density
was found in DBH >10-30cm. This explains that the forest
is dominated by young trees; this could be an indication
for better biomass in the future as explained by
(DeCastilho et al., 2006, Muluken et al., 2015) studies
reported that DBH<10cm held the majority of the
individuals, but represented only 6% of the total tree
biomass.
The largest total carbon density (402 ton ha-1) was found
in highest height class (>40-50m) and the smallest total
carbon density (3.01 ton ha-1) was found in lower height
class (2-5m). This indicates that total carbon density
increases as height class increases even if it is not
smooth (table 3). This might be due to there are very few
Estimation of carbon stored in selected tree species in Gedo forest: implications to forest management for climate change mitigation
J. Environ. Waste Manag.
105
Table 2. Aboveground and belowground biomass carbon variation within different DBH classes
BH classes
Class 1
Class 2
Class 3
Class 4
Class 5
Class 6
Class 7
Class 8
Class 9
Stem
density
(stems/ha)
1610
2860
2460
805
350
290
85
60
50
AGB.C
(ton/ha)
BGB.C
(ton/ha)
T. C. density
(ton/ha)
T.
CO2
equivalent
Percentage
of C. stored
0.3
3.21
16.85
46.5
79.78
137.1
199.62
276.68
491.04
0.06
0.64
3.37
9.3
15.95
27.42
39.92
55.33
98.2
0.36
3.85
20.22
55.8
95.74
164.52
239.54
332.01
589.24
1.32
14.12
74.2
204.78
351.36
603.78
879.11
1218.47
2162.51
0.02
0.25
1.34
3.71
6.37
10.95
15.95
22.11
39.24
Class 1 (5-10cm); Class 2 (>10-30cm); Class 3(>30-50cm) ; Class 4 (>50-70cm); Class 5 (>70-90cm); Class 6 (>90-110cm); Class
7 (>110-130cm); Class 8 (>130-150cm) and Class 9 (>150cm)
Table 3. Aboveground and belowground biomass carbon variation within different height classes
Height
classes
Class 1
Class 2
Class 3
Class 4
Class 5
Class 6
Class 7
Stem
density
(stems/ha)
1390
2625
2750
1210
470
105
15
AGB.C
(ton/ha)
BGB.C
(ton/ha)
2.51
3.67
20.23
50.87
120.8
335
50.39
0.5
0.73
4.04
10.17
24.16
67
10.07
T.
C.
density
(ton/ha)
3.01
4.4
24.27
61.04
144.96
402
60.46
T.CO2
Equivalent
(ton/ha)
11.05
16.16
89.09
224.03
532
1475.34
221.91
Percentage
of C. stored
0.43
0.62
3.46
8.71
20.7
57.41
8.63
Class 1 (2-5m); Class 2 (>5-10m); Class 3(>10-20m); Class 4 (>20-30m); Class 5 (>30-40m); Class 6 (>40-50m); Class 7 (>50m);
stems in the last class (>50m), this result in lower total
carbon density than height class of four, five and six.
Neupane and Sharma (2014) found that 97.86 t ha-1 total
carbon with maximum height of stand 30m. In present
study 61.04 t ha-1 carbon was found at similar height. The
largest height classes contribute about 95.45% of total
carbon density. Nakai et al. (2009) reported that an
increasing trend in total carbon density as tree height
increases. Aboveground and belowground biomass
carbon varies significantly among different height classes
(P < 0.05). This finding is consistent with Scaranello et al.
(2012) report as tree height has a strong influence on
the estimate of live aboveground biomass. The density
of trees revealed decreased with increasing height
classes with uneven pattern; maximum value in class
three (tree height >10-20m) and minimum value in the
last class (tree height >50m).This indicates that there are
higher numbers of individual in the lower and medium
height classes. Further, the findings of (Berhanu et al.,
2014, Muluken et al., 2015) show continues decreasing
of stem density as height class increases.
CONCLUSION
Large and dominant trees are important to store
substantial amount of carbon in their biomass. These
trees are very effective because they are more adaptable
for local climate and soil condition. Different diameter
size, tree height and stem density have significant impact
on the amount of carbon stored in the trees biomass.
There are a few numbers of trees which have large
height and diameter in the forest but they store large
amount of carbon in their biomass. Forest management
has significant role for climate change mitigation, since
when the forest managed properly, there will be more
large trees which can stock more carbon.
ACKNOWLEDGEMENT
The author acknowledged the contributions of Dr. Uzay
Karahalil, Indu K Murthy, Mykola Gusti, Ana Isabel
Cabral, Maarten Smies, Raine Isaksson, Dominique
Hervé and Prof. Kokou Kouami for donating their time,
Estimation of carbon stored in selected tree species in Gedo forest: implications to forest management for climate change mitigation
Yohannes et al.
106
critical evaluation, constructive comments, and invaluable
assistance toward the improvement of this very
manuscript.
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Accepted 11 October, 2015.
Citation: Yohannes H, Soromessa T, Argaw M (2015).
Estimation of carbon stored in selected tree species in
Gedo forest: Implications to forest management for
climate change mitigation. Journal of Environment and
Waste Management 2(4): 102-107.
Copyright: © 2015 Yohannes et al. This is an openaccess article distributed under the terms of the Creative
Commons Attribution License, which permits unrestricted
use, distribution, and reproduction in any medium,
provided the original author and source are cited.
Estimation of carbon stored in selected tree species in Gedo forest: implications to forest management for climate change mitigation
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