SlideShare uma empresa Scribd logo
1 de 7
Baixar para ler offline
Estimation of carbon stored in selected tree species in Gedo forest: implications to forest management for climate change mitigation
JEWM
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 200m
2
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 CO2
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: hamerenew@gmail.com,
hamerey@gmail.com
Journal of Environment and Waste Management
Vol. 2(4), pp. 102-107, October, 2015. © www.premierpublishers.org, ISSN: 1936-8798x
Research article
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. 103
AGB = 34.4703 - 8.0671 (DBH) + 0.6589 (DBH
2
)
……………………………………. (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-to-
shoot 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 =
𝑇𝑕𝑒 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑎𝑏𝑜𝑣𝑒 𝑔𝑟𝑜𝑢𝑛𝑑 𝑠𝑡𝑒𝑚𝑠 𝑜𝑓 𝑎 𝑠𝑝𝑒𝑐𝑖𝑒𝑠 𝑐𝑜𝑢𝑛𝑡𝑒𝑑
𝑆𝑎𝑚𝑝𝑙𝑒𝑑 𝑎𝑟𝑒𝑎 𝑖𝑛 𝑕𝑒𝑐𝑡𝑎𝑟𝑒
… . . (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 𝑡𝑕𝑒 𝑠𝑎𝑚𝑝𝑙𝑒 𝑎𝑟𝑒𝑎
× 100. . (𝑒𝑞. 5)
Frelative =
Frequency of a species
Totalfrequency 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
(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
-1
CO2
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
-1
CO2equivalents, 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
M.
DBH
(cm)
AGB
(ton/ha)
BGB
(ton/ha)
AGBC.
(ton/ha)
BGBC.
(ton/ha)
T.C
(ton/ha)
CO2equ.
(ton/ha)
Podocarpus falcatus Podocarpaceae 61.9 102.98 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
Oleaceae 31 20.87 4.17 9.81 1.96 11.77 43.21
Schrebera alata 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
Myrtaceae 22 8.79 1.75 4.13 0.82 4.96 18.2
Olea welwitschii 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
Erythrina brucei Fabaceae 19.8 6.65 1.33 3.12 0.62 3.75 13.77
Average
30.68 24.18 4.83 11.36 2.26 13.63 50.05
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
-1
CO2 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 Stem
density
(stems/ha)
AGB.C
(ton/ha)
BGB.C
(ton/ha)
T. C. density
(ton/ha)
T. CO2
equivalent
Percentage
of C. stored
Class 1 1610 0.3 0.06 0.36 1.32 0.02
Class 2 2860 3.21 0.64 3.85 14.12 0.25
Class 3 2460 16.85 3.37 20.22 74.2 1.34
Class 4 805 46.5 9.3 55.8 204.78 3.71
Class 5 350 79.78 15.95 95.74 351.36 6.37
Class 6 290 137.1 27.42 164.52 603.78 10.95
Class 7 85 199.62 39.92 239.54 879.11 15.95
Class 8 60 276.68 55.33 332.01 1218.47 22.11
Class 9 50 491.04 98.2 589.24 2162.51 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
Stem
density
(stems/ha)
AGB.C
(ton/ha)
BGB.C
(ton/ha)
T. C.
density
(ton/ha)
T.CO2
Equivalent
(ton/ha)
Percentage
of C. stored
Class 1 1390 2.51 0.5 3.01 11.05 0.43
Class 2 2625 3.67 0.73 4.4 16.16 0.62
Class 3 2750 20.23 4.04 24.27 89.09 3.46
Class 4 1210 50.87 10.17 61.04 224.03 8.71
Class 5 470 120.8 24.16 144.96 532 20.7
Class 6 105 335 67 402 1475.34 57.41
Class 7 15 50.39 10.07 60.46 221.91 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.
REFERENCES
Birhanu K, Teshome S, Ensermu K (2014).Structure and
Regeneration Status of Gedo Dry Evergreen Montane
Forest, West Shewa Zone of Oromia National Regional
State, Central Ethiopia. Sci. Technol. Arts Res. J.,
April-June 2014, 3(2): 119-131.
Chave J, Andalo C, Brown S, Cairns MA, Chambers JQ,
Eamus D, Folster H, Fromard F, Higuchi N, Kira T,
Lescure JP, Nelson BW, Ogawa H, Puig H, Rie´ra B,
Yamakura T (2005). Tree allometry and improved
estimation of carbon stocks and balance in tropical
forests. J. Springer-Verlag. 145: 87–99.
De Castilho CV, Magnusson WE, de Araújo RNO, Luizão
RCC, Luizão FJ, Albertina P, Higuchi N (2006).
Variation in aboveground tree live biomass in a central
Amazonian Forest: effects of soil and topography. J.
Forest Ecology Management. 234: 85–96.
Dereje D (2007). Floristic composition and Ecological
Study of Bibita Forest (GuraFerda), Southwest
Ethiopia. Unpublished M.Sc. Thesis, Addis Ababa
University: Addis Ababa, Ethiopia.
Eliasch J (2008). Climate Change: Financing Global
Forests, review paper. ISBN and Crown. United
Kingdom.
Endalew A (2007). Use and management of medicinal
plants by indigenous people of Ejaji area (Cheliya
Woreda) West Shoa, Ethiopia: an ethnobotanical
approach. Unpublished M.Sc. Thesis, Addis Ababa
University, Addis Ababa, Ethiopia.
FAO (Food and Agriculture Organization)(2008). Climate
change adaptation and mitigation in the food and
agriculture sector.HLC/08/BAK/1.technical background
document from the expert consultation.
FAO (2010). Global Forest Resources Assessment Main
report 163, FAO forestry paper, ISBN 978-92-5-
106654-6, Rome. Italy.
FAO (2012). Forest Management and Climate Change: a
literature review Forests and Climate Change Working
Paper 10: Rome.
Yohannes H, Soromessa T, Argaw M (2015). Carbon
Stock Analysis Along Altitudinal Gradient in Gedo
Forest: Implications for Forest Management and
Climate Change Mitigation. American Journal of
Environmental Protection. Vol. 4, No. 5, 2015, pp. 237-
244. doi: 10.11648/j.ajep.20150405.14.
Kauppi PE, Birdsey RA, Pan Y, Ihalainen A, Nöjd P,
Lehtonen A (2015). Effects of land management on
large trees and carbon stocks. J. Biogeosciences, 12,
855–862.
Kent M, Coker P (1992). Vegetation Description and
Analysis. A practical approach. John Wiley and Sons,
New York, pp.363.
Khanal Y, Sharma RP, Upadhyaya CP (2010). Soil and
vegetation carbon pools in two community forests
of Palpa district, Nepal. J. Banko Janakari. 20(2):34-
40.
Lal R (2005). Forest Soils and Carbon Sequestration.
Journal of Forest Ecology and Management. 220: 242–
258.
MacDicken KG (1997). A Guide to Monitoring Carbon
Storage in Forestry and Agro-forestry Projects.In Forest
Carbon Monitoring Program. Winrock International
Institute for Agricultural Development, Arlington,
Virginia.
Malla Y, Blaser J (2010). The Role of Social Forestry in
Climate Change Mitigation and Adaptation in the Asean
Region, assessment paper. RECOFTC, ASFN, and
SDC: Thailand.
Muluken NB, Teshome S, Eyale B (2015). Above- and
Below-Ground Reserved Carbon in Danaba
Community Forest of Oromia Region, Ethiopia:
Implications for CO2Emission Balance. American
Journal of Environmental Protection. Vol. 4, No.2, pp.
75-82. doi: 10.11648/j.ajep.20150402.11.
Nakai Y, Hosoi F, Omasa K (2009). Estimating carbon
stocks of coniferous woody canopy trees using airborne
lidar and passive optical senser.iaprs, Vol. XXXVIII,
Part 3/W8 – Paris, France.
Neupane B, Sharma RP (2014). An assessment of the
effect of vegetation size and type, and altitude on
above ground plant biomass and carbon. Journal of
Agricultural and Crop Research . Vol. 2(3), pp. 44-50,
ISSN: 2384-731X.
Offiong RA, Iwara AI (2012). Quantifying the stock of soil
organic carbon using multiple regression models in
fallow vegetation, Southern Nigeria. Ethiopian. Journal
of Environmental Studies and Management EJESM
.5(2): 1-20.
Pearson TR, Walker S, Brown S(2005). Sourcebook for
land-use, land-use change and forestry projects.
Winrock International and the Bio-carbon fund of the
World Bank. Arlington, USA, pp. 19-35.
Ruiz-Jaen MC, Potvin C(2010). Can we predict carbon
stocks in tropical ecosystems from tree diversity?
Comparing species and functional diversity in a
plantation and a natural forest, McGill University:
Canada.
Scaranello MAD, Alves LF, Vieira SA, De Camargo PB,
Joly CA, Martinelli LA (2012). Height-diameter
relationships of tropical Atlantic moist forest trees in
southeastern Brazil. Sci. Agric. v.69, n.1, p.26-37.
Shrestha BP (2009). Carbon sequestration in broad
leaved forests of mid-hills of Nepal: A case study from
Palpa district. J. The initiation. 3:20-29.
Yanqiu Hu, Zhiyao Su, Wenbin Li, Jingpeng Li, Xiandong
Ke (2015). Influence of Tree Species Composition and
Community Structure on Carbon Density in a
Subtropical Forest. J. PLOS.
Yitebitu M, Zewdu E, Sisay N (2010). A review on Ethiopian
Estimation of carbon stored in selected tree species in Gedo forest: implications to forest management for climate change mitigation
J. Environ. Waste Manag. 107
Forest Resources: current status and future
management options in view of access to carbon
finances. Prepared for the Ethiopian climate research
and networking and the United Nations development
programme (UNDP).Addis Ababa, Ethiopia.
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 open-
access 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.

Mais conteúdo relacionado

Destaque

2011-2012 Semana Cultural CEIP CERVANTES Ejea de los Caballeros "SUPERANDO BA...
2011-2012 Semana Cultural CEIP CERVANTES Ejea de los Caballeros "SUPERANDO BA...2011-2012 Semana Cultural CEIP CERVANTES Ejea de los Caballeros "SUPERANDO BA...
2011-2012 Semana Cultural CEIP CERVANTES Ejea de los Caballeros "SUPERANDO BA...efcervantes
 
un adios
un adiosun adios
un adiosshura14
 
Seminario Edgar Gómez
Seminario Edgar GómezSeminario Edgar Gómez
Seminario Edgar Gómez@cristobalcobo
 
Trabajo normas de cortesía y situaciones (1)
Trabajo normas de cortesía y situaciones (1)Trabajo normas de cortesía y situaciones (1)
Trabajo normas de cortesía y situaciones (1)Anabel Cornago
 

Destaque (7)

2011-2012 Semana Cultural CEIP CERVANTES Ejea de los Caballeros "SUPERANDO BA...
2011-2012 Semana Cultural CEIP CERVANTES Ejea de los Caballeros "SUPERANDO BA...2011-2012 Semana Cultural CEIP CERVANTES Ejea de los Caballeros "SUPERANDO BA...
2011-2012 Semana Cultural CEIP CERVANTES Ejea de los Caballeros "SUPERANDO BA...
 
Via sacra 2
Via sacra 2Via sacra 2
Via sacra 2
 
Via sacra 2016
Via sacra 2016 Via sacra 2016
Via sacra 2016
 
Via sacra do amor
Via sacra do amorVia sacra do amor
Via sacra do amor
 
un adios
un adiosun adios
un adios
 
Seminario Edgar Gómez
Seminario Edgar GómezSeminario Edgar Gómez
Seminario Edgar Gómez
 
Trabajo normas de cortesía y situaciones (1)
Trabajo normas de cortesía y situaciones (1)Trabajo normas de cortesía y situaciones (1)
Trabajo normas de cortesía y situaciones (1)
 

Mais de Premier Publishers

Evaluation of Agro-morphological Performances of Hybrid Varieties of Chili Pe...
Evaluation of Agro-morphological Performances of Hybrid Varieties of Chili Pe...Evaluation of Agro-morphological Performances of Hybrid Varieties of Chili Pe...
Evaluation of Agro-morphological Performances of Hybrid Varieties of Chili Pe...Premier Publishers
 
An Empirical Approach for the Variation in Capital Market Price Changes
An Empirical Approach for the Variation in Capital Market Price Changes An Empirical Approach for the Variation in Capital Market Price Changes
An Empirical Approach for the Variation in Capital Market Price Changes Premier Publishers
 
Influence of Nitrogen and Spacing on Growth and Yield of Chia (Salvia hispani...
Influence of Nitrogen and Spacing on Growth and Yield of Chia (Salvia hispani...Influence of Nitrogen and Spacing on Growth and Yield of Chia (Salvia hispani...
Influence of Nitrogen and Spacing on Growth and Yield of Chia (Salvia hispani...Premier Publishers
 
Enhancing Social Capital During the Pandemic: A Case of the Rural Women in Bu...
Enhancing Social Capital During the Pandemic: A Case of the Rural Women in Bu...Enhancing Social Capital During the Pandemic: A Case of the Rural Women in Bu...
Enhancing Social Capital During the Pandemic: A Case of the Rural Women in Bu...Premier Publishers
 
Impact of Provision of Litigation Supports through Forensic Investigations on...
Impact of Provision of Litigation Supports through Forensic Investigations on...Impact of Provision of Litigation Supports through Forensic Investigations on...
Impact of Provision of Litigation Supports through Forensic Investigations on...Premier Publishers
 
Improving the Efficiency of Ratio Estimators by Calibration Weightings
Improving the Efficiency of Ratio Estimators by Calibration WeightingsImproving the Efficiency of Ratio Estimators by Calibration Weightings
Improving the Efficiency of Ratio Estimators by Calibration WeightingsPremier Publishers
 
Urban Liveability in the Context of Sustainable Development: A Perspective fr...
Urban Liveability in the Context of Sustainable Development: A Perspective fr...Urban Liveability in the Context of Sustainable Development: A Perspective fr...
Urban Liveability in the Context of Sustainable Development: A Perspective fr...Premier Publishers
 
Transcript Level of Genes Involved in “Rebaudioside A” Biosynthesis Pathway u...
Transcript Level of Genes Involved in “Rebaudioside A” Biosynthesis Pathway u...Transcript Level of Genes Involved in “Rebaudioside A” Biosynthesis Pathway u...
Transcript Level of Genes Involved in “Rebaudioside A” Biosynthesis Pathway u...Premier Publishers
 
Multivariate Analysis of Tea (Camellia sinensis (L.) O. Kuntze) Clones on Mor...
Multivariate Analysis of Tea (Camellia sinensis (L.) O. Kuntze) Clones on Mor...Multivariate Analysis of Tea (Camellia sinensis (L.) O. Kuntze) Clones on Mor...
Multivariate Analysis of Tea (Camellia sinensis (L.) O. Kuntze) Clones on Mor...Premier Publishers
 
Causes, Consequences and Remedies of Juvenile Delinquency in the Context of S...
Causes, Consequences and Remedies of Juvenile Delinquency in the Context of S...Causes, Consequences and Remedies of Juvenile Delinquency in the Context of S...
Causes, Consequences and Remedies of Juvenile Delinquency in the Context of S...Premier Publishers
 
The Knowledge of and Attitude to and Beliefs about Causes and Treatments of M...
The Knowledge of and Attitude to and Beliefs about Causes and Treatments of M...The Knowledge of and Attitude to and Beliefs about Causes and Treatments of M...
The Knowledge of and Attitude to and Beliefs about Causes and Treatments of M...Premier Publishers
 
Effect of Phosphorus and Zinc on the Growth, Nodulation and Yield of Soybean ...
Effect of Phosphorus and Zinc on the Growth, Nodulation and Yield of Soybean ...Effect of Phosphorus and Zinc on the Growth, Nodulation and Yield of Soybean ...
Effect of Phosphorus and Zinc on the Growth, Nodulation and Yield of Soybean ...Premier Publishers
 
Influence of Harvest Stage on Yield and Yield Components of Orange Fleshed Sw...
Influence of Harvest Stage on Yield and Yield Components of Orange Fleshed Sw...Influence of Harvest Stage on Yield and Yield Components of Orange Fleshed Sw...
Influence of Harvest Stage on Yield and Yield Components of Orange Fleshed Sw...Premier Publishers
 
Performance evaluation of upland rice (Oryza sativa L.) and variability study...
Performance evaluation of upland rice (Oryza sativa L.) and variability study...Performance evaluation of upland rice (Oryza sativa L.) and variability study...
Performance evaluation of upland rice (Oryza sativa L.) and variability study...Premier Publishers
 
Response of Hot Pepper (Capsicum Annuum L.) to Deficit Irrigation in Bennatse...
Response of Hot Pepper (Capsicum Annuum L.) to Deficit Irrigation in Bennatse...Response of Hot Pepper (Capsicum Annuum L.) to Deficit Irrigation in Bennatse...
Response of Hot Pepper (Capsicum Annuum L.) to Deficit Irrigation in Bennatse...Premier Publishers
 
Harnessing the Power of Agricultural Waste: A Study of Sabo Market, Ikorodu, ...
Harnessing the Power of Agricultural Waste: A Study of Sabo Market, Ikorodu, ...Harnessing the Power of Agricultural Waste: A Study of Sabo Market, Ikorodu, ...
Harnessing the Power of Agricultural Waste: A Study of Sabo Market, Ikorodu, ...Premier Publishers
 
Influence of Conferences and Job Rotation on Job Productivity of Library Staf...
Influence of Conferences and Job Rotation on Job Productivity of Library Staf...Influence of Conferences and Job Rotation on Job Productivity of Library Staf...
Influence of Conferences and Job Rotation on Job Productivity of Library Staf...Premier Publishers
 
Scanning Electron Microscopic Structure and Composition of Urinary Calculi of...
Scanning Electron Microscopic Structure and Composition of Urinary Calculi of...Scanning Electron Microscopic Structure and Composition of Urinary Calculi of...
Scanning Electron Microscopic Structure and Composition of Urinary Calculi of...Premier Publishers
 
Gentrification and its Effects on Minority Communities – A Comparative Case S...
Gentrification and its Effects on Minority Communities – A Comparative Case S...Gentrification and its Effects on Minority Communities – A Comparative Case S...
Gentrification and its Effects on Minority Communities – A Comparative Case S...Premier Publishers
 
Oil and Fatty Acid Composition Analysis of Ethiopian Mustard (Brasicacarinata...
Oil and Fatty Acid Composition Analysis of Ethiopian Mustard (Brasicacarinata...Oil and Fatty Acid Composition Analysis of Ethiopian Mustard (Brasicacarinata...
Oil and Fatty Acid Composition Analysis of Ethiopian Mustard (Brasicacarinata...Premier Publishers
 

Mais de Premier Publishers (20)

Evaluation of Agro-morphological Performances of Hybrid Varieties of Chili Pe...
Evaluation of Agro-morphological Performances of Hybrid Varieties of Chili Pe...Evaluation of Agro-morphological Performances of Hybrid Varieties of Chili Pe...
Evaluation of Agro-morphological Performances of Hybrid Varieties of Chili Pe...
 
An Empirical Approach for the Variation in Capital Market Price Changes
An Empirical Approach for the Variation in Capital Market Price Changes An Empirical Approach for the Variation in Capital Market Price Changes
An Empirical Approach for the Variation in Capital Market Price Changes
 
Influence of Nitrogen and Spacing on Growth and Yield of Chia (Salvia hispani...
Influence of Nitrogen and Spacing on Growth and Yield of Chia (Salvia hispani...Influence of Nitrogen and Spacing on Growth and Yield of Chia (Salvia hispani...
Influence of Nitrogen and Spacing on Growth and Yield of Chia (Salvia hispani...
 
Enhancing Social Capital During the Pandemic: A Case of the Rural Women in Bu...
Enhancing Social Capital During the Pandemic: A Case of the Rural Women in Bu...Enhancing Social Capital During the Pandemic: A Case of the Rural Women in Bu...
Enhancing Social Capital During the Pandemic: A Case of the Rural Women in Bu...
 
Impact of Provision of Litigation Supports through Forensic Investigations on...
Impact of Provision of Litigation Supports through Forensic Investigations on...Impact of Provision of Litigation Supports through Forensic Investigations on...
Impact of Provision of Litigation Supports through Forensic Investigations on...
 
Improving the Efficiency of Ratio Estimators by Calibration Weightings
Improving the Efficiency of Ratio Estimators by Calibration WeightingsImproving the Efficiency of Ratio Estimators by Calibration Weightings
Improving the Efficiency of Ratio Estimators by Calibration Weightings
 
Urban Liveability in the Context of Sustainable Development: A Perspective fr...
Urban Liveability in the Context of Sustainable Development: A Perspective fr...Urban Liveability in the Context of Sustainable Development: A Perspective fr...
Urban Liveability in the Context of Sustainable Development: A Perspective fr...
 
Transcript Level of Genes Involved in “Rebaudioside A” Biosynthesis Pathway u...
Transcript Level of Genes Involved in “Rebaudioside A” Biosynthesis Pathway u...Transcript Level of Genes Involved in “Rebaudioside A” Biosynthesis Pathway u...
Transcript Level of Genes Involved in “Rebaudioside A” Biosynthesis Pathway u...
 
Multivariate Analysis of Tea (Camellia sinensis (L.) O. Kuntze) Clones on Mor...
Multivariate Analysis of Tea (Camellia sinensis (L.) O. Kuntze) Clones on Mor...Multivariate Analysis of Tea (Camellia sinensis (L.) O. Kuntze) Clones on Mor...
Multivariate Analysis of Tea (Camellia sinensis (L.) O. Kuntze) Clones on Mor...
 
Causes, Consequences and Remedies of Juvenile Delinquency in the Context of S...
Causes, Consequences and Remedies of Juvenile Delinquency in the Context of S...Causes, Consequences and Remedies of Juvenile Delinquency in the Context of S...
Causes, Consequences and Remedies of Juvenile Delinquency in the Context of S...
 
The Knowledge of and Attitude to and Beliefs about Causes and Treatments of M...
The Knowledge of and Attitude to and Beliefs about Causes and Treatments of M...The Knowledge of and Attitude to and Beliefs about Causes and Treatments of M...
The Knowledge of and Attitude to and Beliefs about Causes and Treatments of M...
 
Effect of Phosphorus and Zinc on the Growth, Nodulation and Yield of Soybean ...
Effect of Phosphorus and Zinc on the Growth, Nodulation and Yield of Soybean ...Effect of Phosphorus and Zinc on the Growth, Nodulation and Yield of Soybean ...
Effect of Phosphorus and Zinc on the Growth, Nodulation and Yield of Soybean ...
 
Influence of Harvest Stage on Yield and Yield Components of Orange Fleshed Sw...
Influence of Harvest Stage on Yield and Yield Components of Orange Fleshed Sw...Influence of Harvest Stage on Yield and Yield Components of Orange Fleshed Sw...
Influence of Harvest Stage on Yield and Yield Components of Orange Fleshed Sw...
 
Performance evaluation of upland rice (Oryza sativa L.) and variability study...
Performance evaluation of upland rice (Oryza sativa L.) and variability study...Performance evaluation of upland rice (Oryza sativa L.) and variability study...
Performance evaluation of upland rice (Oryza sativa L.) and variability study...
 
Response of Hot Pepper (Capsicum Annuum L.) to Deficit Irrigation in Bennatse...
Response of Hot Pepper (Capsicum Annuum L.) to Deficit Irrigation in Bennatse...Response of Hot Pepper (Capsicum Annuum L.) to Deficit Irrigation in Bennatse...
Response of Hot Pepper (Capsicum Annuum L.) to Deficit Irrigation in Bennatse...
 
Harnessing the Power of Agricultural Waste: A Study of Sabo Market, Ikorodu, ...
Harnessing the Power of Agricultural Waste: A Study of Sabo Market, Ikorodu, ...Harnessing the Power of Agricultural Waste: A Study of Sabo Market, Ikorodu, ...
Harnessing the Power of Agricultural Waste: A Study of Sabo Market, Ikorodu, ...
 
Influence of Conferences and Job Rotation on Job Productivity of Library Staf...
Influence of Conferences and Job Rotation on Job Productivity of Library Staf...Influence of Conferences and Job Rotation on Job Productivity of Library Staf...
Influence of Conferences and Job Rotation on Job Productivity of Library Staf...
 
Scanning Electron Microscopic Structure and Composition of Urinary Calculi of...
Scanning Electron Microscopic Structure and Composition of Urinary Calculi of...Scanning Electron Microscopic Structure and Composition of Urinary Calculi of...
Scanning Electron Microscopic Structure and Composition of Urinary Calculi of...
 
Gentrification and its Effects on Minority Communities – A Comparative Case S...
Gentrification and its Effects on Minority Communities – A Comparative Case S...Gentrification and its Effects on Minority Communities – A Comparative Case S...
Gentrification and its Effects on Minority Communities – A Comparative Case S...
 
Oil and Fatty Acid Composition Analysis of Ethiopian Mustard (Brasicacarinata...
Oil and Fatty Acid Composition Analysis of Ethiopian Mustard (Brasicacarinata...Oil and Fatty Acid Composition Analysis of Ethiopian Mustard (Brasicacarinata...
Oil and Fatty Acid Composition Analysis of Ethiopian Mustard (Brasicacarinata...
 

Último

Kondhwa ( Call Girls ) Pune 6297143586 Hot Model With Sexy Bhabi Ready For ...
Kondhwa ( Call Girls ) Pune  6297143586  Hot Model With Sexy Bhabi Ready For ...Kondhwa ( Call Girls ) Pune  6297143586  Hot Model With Sexy Bhabi Ready For ...
Kondhwa ( Call Girls ) Pune 6297143586 Hot Model With Sexy Bhabi Ready For ...tanu pandey
 
GENUINE Babe,Call Girls IN Chhatarpur Delhi | +91-8377877756
GENUINE Babe,Call Girls IN Chhatarpur Delhi | +91-8377877756GENUINE Babe,Call Girls IN Chhatarpur Delhi | +91-8377877756
GENUINE Babe,Call Girls IN Chhatarpur Delhi | +91-8377877756dollysharma2066
 
VVIP Pune Call Girls Koregaon Park (7001035870) Pune Escorts Nearby with Comp...
VVIP Pune Call Girls Koregaon Park (7001035870) Pune Escorts Nearby with Comp...VVIP Pune Call Girls Koregaon Park (7001035870) Pune Escorts Nearby with Comp...
VVIP Pune Call Girls Koregaon Park (7001035870) Pune Escorts Nearby with Comp...Call Girls in Nagpur High Profile
 
RATING SYSTEMS- IGBC, GRIHA, LEED--.pptx
RATING  SYSTEMS- IGBC, GRIHA, LEED--.pptxRATING  SYSTEMS- IGBC, GRIHA, LEED--.pptx
RATING SYSTEMS- IGBC, GRIHA, LEED--.pptxJIT KUMAR GUPTA
 
Call Girls in Sakinaka Agency, { 9892124323 } Mumbai Vashi Call Girls Serivce...
Call Girls in Sakinaka Agency, { 9892124323 } Mumbai Vashi Call Girls Serivce...Call Girls in Sakinaka Agency, { 9892124323 } Mumbai Vashi Call Girls Serivce...
Call Girls in Sakinaka Agency, { 9892124323 } Mumbai Vashi Call Girls Serivce...Pooja Nehwal
 
Verified Trusted Kalyani Nagar Call Girls 8005736733 𝐈𝐍𝐃𝐄𝐏𝐄𝐍𝐃𝐄𝐍𝐓 Call 𝐆𝐈𝐑𝐋 𝐕...
Verified Trusted Kalyani Nagar Call Girls  8005736733 𝐈𝐍𝐃𝐄𝐏𝐄𝐍𝐃𝐄𝐍𝐓 Call 𝐆𝐈𝐑𝐋 𝐕...Verified Trusted Kalyani Nagar Call Girls  8005736733 𝐈𝐍𝐃𝐄𝐏𝐄𝐍𝐃𝐄𝐍𝐓 Call 𝐆𝐈𝐑𝐋 𝐕...
Verified Trusted Kalyani Nagar Call Girls 8005736733 𝐈𝐍𝐃𝐄𝐏𝐄𝐍𝐃𝐄𝐍𝐓 Call 𝐆𝐈𝐑𝐋 𝐕...tanu pandey
 
VVIP Pune Call Girls Vishal Nagar WhatSapp Number 8005736733 With Elite Staff...
VVIP Pune Call Girls Vishal Nagar WhatSapp Number 8005736733 With Elite Staff...VVIP Pune Call Girls Vishal Nagar WhatSapp Number 8005736733 With Elite Staff...
VVIP Pune Call Girls Vishal Nagar WhatSapp Number 8005736733 With Elite Staff...SUHANI PANDEY
 
VIP Model Call Girls Chakan ( Pune ) Call ON 8005736733 Starting From 5K to 2...
VIP Model Call Girls Chakan ( Pune ) Call ON 8005736733 Starting From 5K to 2...VIP Model Call Girls Chakan ( Pune ) Call ON 8005736733 Starting From 5K to 2...
VIP Model Call Girls Chakan ( Pune ) Call ON 8005736733 Starting From 5K to 2...SUHANI PANDEY
 
Call Girls Moshi Call Me 7737669865 Budget Friendly No Advance Booking
Call Girls Moshi Call Me 7737669865 Budget Friendly No Advance BookingCall Girls Moshi Call Me 7737669865 Budget Friendly No Advance Booking
Call Girls Moshi Call Me 7737669865 Budget Friendly No Advance Bookingroncy bisnoi
 
Booking open Available Pune Call Girls Budhwar Peth 6297143586 Call Hot Indi...
Booking open Available Pune Call Girls Budhwar Peth  6297143586 Call Hot Indi...Booking open Available Pune Call Girls Budhwar Peth  6297143586 Call Hot Indi...
Booking open Available Pune Call Girls Budhwar Peth 6297143586 Call Hot Indi...Call Girls in Nagpur High Profile
 
Proposed Amendments to Chapter 15, Article X: Wetland Conservation Areas
Proposed Amendments to Chapter 15, Article X: Wetland Conservation AreasProposed Amendments to Chapter 15, Article X: Wetland Conservation Areas
Proposed Amendments to Chapter 15, Article X: Wetland Conservation Areas💥Victoria K. Colangelo
 
Call Girls Service Pune ₹7.5k Pick Up & Drop With Cash Payment 8005736733 Cal...
Call Girls Service Pune ₹7.5k Pick Up & Drop With Cash Payment 8005736733 Cal...Call Girls Service Pune ₹7.5k Pick Up & Drop With Cash Payment 8005736733 Cal...
Call Girls Service Pune ₹7.5k Pick Up & Drop With Cash Payment 8005736733 Cal...SUHANI PANDEY
 
VIP Model Call Girls Viman Nagar ( Pune ) Call ON 8005736733 Starting From 5K...
VIP Model Call Girls Viman Nagar ( Pune ) Call ON 8005736733 Starting From 5K...VIP Model Call Girls Viman Nagar ( Pune ) Call ON 8005736733 Starting From 5K...
VIP Model Call Girls Viman Nagar ( Pune ) Call ON 8005736733 Starting From 5K...SUHANI PANDEY
 
Booking open Available Pune Call Girls Parvati Darshan 6297143586 Call Hot I...
Booking open Available Pune Call Girls Parvati Darshan  6297143586 Call Hot I...Booking open Available Pune Call Girls Parvati Darshan  6297143586 Call Hot I...
Booking open Available Pune Call Girls Parvati Darshan 6297143586 Call Hot I...Call Girls in Nagpur High Profile
 
Book Sex Workers Available Pune Call Girls Kondhwa 6297143586 Call Hot India...
Book Sex Workers Available Pune Call Girls Kondhwa  6297143586 Call Hot India...Book Sex Workers Available Pune Call Girls Kondhwa  6297143586 Call Hot India...
Book Sex Workers Available Pune Call Girls Kondhwa 6297143586 Call Hot India...Call Girls in Nagpur High Profile
 
VIP Model Call Girls Wagholi ( Pune ) Call ON 8005736733 Starting From 5K to ...
VIP Model Call Girls Wagholi ( Pune ) Call ON 8005736733 Starting From 5K to ...VIP Model Call Girls Wagholi ( Pune ) Call ON 8005736733 Starting From 5K to ...
VIP Model Call Girls Wagholi ( Pune ) Call ON 8005736733 Starting From 5K to ...SUHANI PANDEY
 
Cyclone Case Study Odisha 1999 Super Cyclone in India.
Cyclone Case Study Odisha 1999 Super Cyclone in India.Cyclone Case Study Odisha 1999 Super Cyclone in India.
Cyclone Case Study Odisha 1999 Super Cyclone in India.cojitesh
 
VVIP Pune Call Girls Moshi WhatSapp Number 8005736733 With Elite Staff And Re...
VVIP Pune Call Girls Moshi WhatSapp Number 8005736733 With Elite Staff And Re...VVIP Pune Call Girls Moshi WhatSapp Number 8005736733 With Elite Staff And Re...
VVIP Pune Call Girls Moshi WhatSapp Number 8005736733 With Elite Staff And Re...SUHANI PANDEY
 

Último (20)

(NEHA) Call Girls Navi Mumbai Call Now 8250077686 Navi Mumbai Escorts 24x7
(NEHA) Call Girls Navi Mumbai Call Now 8250077686 Navi Mumbai Escorts 24x7(NEHA) Call Girls Navi Mumbai Call Now 8250077686 Navi Mumbai Escorts 24x7
(NEHA) Call Girls Navi Mumbai Call Now 8250077686 Navi Mumbai Escorts 24x7
 
Kondhwa ( Call Girls ) Pune 6297143586 Hot Model With Sexy Bhabi Ready For ...
Kondhwa ( Call Girls ) Pune  6297143586  Hot Model With Sexy Bhabi Ready For ...Kondhwa ( Call Girls ) Pune  6297143586  Hot Model With Sexy Bhabi Ready For ...
Kondhwa ( Call Girls ) Pune 6297143586 Hot Model With Sexy Bhabi Ready For ...
 
GENUINE Babe,Call Girls IN Chhatarpur Delhi | +91-8377877756
GENUINE Babe,Call Girls IN Chhatarpur Delhi | +91-8377877756GENUINE Babe,Call Girls IN Chhatarpur Delhi | +91-8377877756
GENUINE Babe,Call Girls IN Chhatarpur Delhi | +91-8377877756
 
VVIP Pune Call Girls Koregaon Park (7001035870) Pune Escorts Nearby with Comp...
VVIP Pune Call Girls Koregaon Park (7001035870) Pune Escorts Nearby with Comp...VVIP Pune Call Girls Koregaon Park (7001035870) Pune Escorts Nearby with Comp...
VVIP Pune Call Girls Koregaon Park (7001035870) Pune Escorts Nearby with Comp...
 
(INDIRA) Call Girl Katra Call Now 8617697112 Katra Escorts 24x7
(INDIRA) Call Girl Katra Call Now 8617697112 Katra Escorts 24x7(INDIRA) Call Girl Katra Call Now 8617697112 Katra Escorts 24x7
(INDIRA) Call Girl Katra Call Now 8617697112 Katra Escorts 24x7
 
RATING SYSTEMS- IGBC, GRIHA, LEED--.pptx
RATING  SYSTEMS- IGBC, GRIHA, LEED--.pptxRATING  SYSTEMS- IGBC, GRIHA, LEED--.pptx
RATING SYSTEMS- IGBC, GRIHA, LEED--.pptx
 
Call Girls in Sakinaka Agency, { 9892124323 } Mumbai Vashi Call Girls Serivce...
Call Girls in Sakinaka Agency, { 9892124323 } Mumbai Vashi Call Girls Serivce...Call Girls in Sakinaka Agency, { 9892124323 } Mumbai Vashi Call Girls Serivce...
Call Girls in Sakinaka Agency, { 9892124323 } Mumbai Vashi Call Girls Serivce...
 
Verified Trusted Kalyani Nagar Call Girls 8005736733 𝐈𝐍𝐃𝐄𝐏𝐄𝐍𝐃𝐄𝐍𝐓 Call 𝐆𝐈𝐑𝐋 𝐕...
Verified Trusted Kalyani Nagar Call Girls  8005736733 𝐈𝐍𝐃𝐄𝐏𝐄𝐍𝐃𝐄𝐍𝐓 Call 𝐆𝐈𝐑𝐋 𝐕...Verified Trusted Kalyani Nagar Call Girls  8005736733 𝐈𝐍𝐃𝐄𝐏𝐄𝐍𝐃𝐄𝐍𝐓 Call 𝐆𝐈𝐑𝐋 𝐕...
Verified Trusted Kalyani Nagar Call Girls 8005736733 𝐈𝐍𝐃𝐄𝐏𝐄𝐍𝐃𝐄𝐍𝐓 Call 𝐆𝐈𝐑𝐋 𝐕...
 
VVIP Pune Call Girls Vishal Nagar WhatSapp Number 8005736733 With Elite Staff...
VVIP Pune Call Girls Vishal Nagar WhatSapp Number 8005736733 With Elite Staff...VVIP Pune Call Girls Vishal Nagar WhatSapp Number 8005736733 With Elite Staff...
VVIP Pune Call Girls Vishal Nagar WhatSapp Number 8005736733 With Elite Staff...
 
VIP Model Call Girls Chakan ( Pune ) Call ON 8005736733 Starting From 5K to 2...
VIP Model Call Girls Chakan ( Pune ) Call ON 8005736733 Starting From 5K to 2...VIP Model Call Girls Chakan ( Pune ) Call ON 8005736733 Starting From 5K to 2...
VIP Model Call Girls Chakan ( Pune ) Call ON 8005736733 Starting From 5K to 2...
 
Call Girls Moshi Call Me 7737669865 Budget Friendly No Advance Booking
Call Girls Moshi Call Me 7737669865 Budget Friendly No Advance BookingCall Girls Moshi Call Me 7737669865 Budget Friendly No Advance Booking
Call Girls Moshi Call Me 7737669865 Budget Friendly No Advance Booking
 
Booking open Available Pune Call Girls Budhwar Peth 6297143586 Call Hot Indi...
Booking open Available Pune Call Girls Budhwar Peth  6297143586 Call Hot Indi...Booking open Available Pune Call Girls Budhwar Peth  6297143586 Call Hot Indi...
Booking open Available Pune Call Girls Budhwar Peth 6297143586 Call Hot Indi...
 
Proposed Amendments to Chapter 15, Article X: Wetland Conservation Areas
Proposed Amendments to Chapter 15, Article X: Wetland Conservation AreasProposed Amendments to Chapter 15, Article X: Wetland Conservation Areas
Proposed Amendments to Chapter 15, Article X: Wetland Conservation Areas
 
Call Girls Service Pune ₹7.5k Pick Up & Drop With Cash Payment 8005736733 Cal...
Call Girls Service Pune ₹7.5k Pick Up & Drop With Cash Payment 8005736733 Cal...Call Girls Service Pune ₹7.5k Pick Up & Drop With Cash Payment 8005736733 Cal...
Call Girls Service Pune ₹7.5k Pick Up & Drop With Cash Payment 8005736733 Cal...
 
VIP Model Call Girls Viman Nagar ( Pune ) Call ON 8005736733 Starting From 5K...
VIP Model Call Girls Viman Nagar ( Pune ) Call ON 8005736733 Starting From 5K...VIP Model Call Girls Viman Nagar ( Pune ) Call ON 8005736733 Starting From 5K...
VIP Model Call Girls Viman Nagar ( Pune ) Call ON 8005736733 Starting From 5K...
 
Booking open Available Pune Call Girls Parvati Darshan 6297143586 Call Hot I...
Booking open Available Pune Call Girls Parvati Darshan  6297143586 Call Hot I...Booking open Available Pune Call Girls Parvati Darshan  6297143586 Call Hot I...
Booking open Available Pune Call Girls Parvati Darshan 6297143586 Call Hot I...
 
Book Sex Workers Available Pune Call Girls Kondhwa 6297143586 Call Hot India...
Book Sex Workers Available Pune Call Girls Kondhwa  6297143586 Call Hot India...Book Sex Workers Available Pune Call Girls Kondhwa  6297143586 Call Hot India...
Book Sex Workers Available Pune Call Girls Kondhwa 6297143586 Call Hot India...
 
VIP Model Call Girls Wagholi ( Pune ) Call ON 8005736733 Starting From 5K to ...
VIP Model Call Girls Wagholi ( Pune ) Call ON 8005736733 Starting From 5K to ...VIP Model Call Girls Wagholi ( Pune ) Call ON 8005736733 Starting From 5K to ...
VIP Model Call Girls Wagholi ( Pune ) Call ON 8005736733 Starting From 5K to ...
 
Cyclone Case Study Odisha 1999 Super Cyclone in India.
Cyclone Case Study Odisha 1999 Super Cyclone in India.Cyclone Case Study Odisha 1999 Super Cyclone in India.
Cyclone Case Study Odisha 1999 Super Cyclone in India.
 
VVIP Pune Call Girls Moshi WhatSapp Number 8005736733 With Elite Staff And Re...
VVIP Pune Call Girls Moshi WhatSapp Number 8005736733 With Elite Staff And Re...VVIP Pune Call Girls Moshi WhatSapp Number 8005736733 With Elite Staff And Re...
VVIP Pune Call Girls Moshi WhatSapp Number 8005736733 With Elite Staff And Re...
 

Estimation of carbon stored in selected tree species in Gedo forest: Implications to forest management for climate change mitigation

  • 1. Estimation of carbon stored in selected tree species in Gedo forest: implications to forest management for climate change mitigation JEWM 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 200m 2 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 CO2 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: hamerenew@gmail.com, hamerey@gmail.com Journal of Environment and Waste Management Vol. 2(4), pp. 102-107, October, 2015. © www.premierpublishers.org, ISSN: 1936-8798x Research article
  • 2. 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:
  • 3. Estimation of carbon stored in selected tree species in Gedo forest: implications to forest management for climate change mitigation J. Environ. Waste Manag. 103 AGB = 34.4703 - 8.0671 (DBH) + 0.6589 (DBH 2 ) ……………………………………. (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-to- shoot 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 = 𝑇𝑕𝑒 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑎𝑏𝑜𝑣𝑒 𝑔𝑟𝑜𝑢𝑛𝑑 𝑠𝑡𝑒𝑚𝑠 𝑜𝑓 𝑎 𝑠𝑝𝑒𝑐𝑖𝑒𝑠 𝑐𝑜𝑢𝑛𝑡𝑒𝑑 𝑆𝑎𝑚𝑝𝑙𝑒𝑑 𝑎𝑟𝑒𝑎 𝑖𝑛 𝑕𝑒𝑐𝑡𝑎𝑟𝑒 … . . (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 𝑡𝑕𝑒 𝑠𝑎𝑚𝑝𝑙𝑒 𝑎𝑟𝑒𝑎 × 100. . (𝑒𝑞. 5) Frelative = Frequency of a species Totalfrequency 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 (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 -1 CO2 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 -1 CO2equivalents, 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.
  • 4. 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 M. DBH (cm) AGB (ton/ha) BGB (ton/ha) AGBC. (ton/ha) BGBC. (ton/ha) T.C (ton/ha) CO2equ. (ton/ha) Podocarpus falcatus Podocarpaceae 61.9 102.98 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 Oleaceae 31 20.87 4.17 9.81 1.96 11.77 43.21 Schrebera alata 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 Myrtaceae 22 8.79 1.75 4.13 0.82 4.96 18.2 Olea welwitschii 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 Erythrina brucei Fabaceae 19.8 6.65 1.33 3.12 0.62 3.75 13.77 Average 30.68 24.18 4.83 11.36 2.26 13.63 50.05 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 -1 CO2 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
  • 5. 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 Stem density (stems/ha) AGB.C (ton/ha) BGB.C (ton/ha) T. C. density (ton/ha) T. CO2 equivalent Percentage of C. stored Class 1 1610 0.3 0.06 0.36 1.32 0.02 Class 2 2860 3.21 0.64 3.85 14.12 0.25 Class 3 2460 16.85 3.37 20.22 74.2 1.34 Class 4 805 46.5 9.3 55.8 204.78 3.71 Class 5 350 79.78 15.95 95.74 351.36 6.37 Class 6 290 137.1 27.42 164.52 603.78 10.95 Class 7 85 199.62 39.92 239.54 879.11 15.95 Class 8 60 276.68 55.33 332.01 1218.47 22.11 Class 9 50 491.04 98.2 589.24 2162.51 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 Stem density (stems/ha) AGB.C (ton/ha) BGB.C (ton/ha) T. C. density (ton/ha) T.CO2 Equivalent (ton/ha) Percentage of C. stored Class 1 1390 2.51 0.5 3.01 11.05 0.43 Class 2 2625 3.67 0.73 4.4 16.16 0.62 Class 3 2750 20.23 4.04 24.27 89.09 3.46 Class 4 1210 50.87 10.17 61.04 224.03 8.71 Class 5 470 120.8 24.16 144.96 532 20.7 Class 6 105 335 67 402 1475.34 57.41 Class 7 15 50.39 10.07 60.46 221.91 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,
  • 6. 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. REFERENCES Birhanu K, Teshome S, Ensermu K (2014).Structure and Regeneration Status of Gedo Dry Evergreen Montane Forest, West Shewa Zone of Oromia National Regional State, Central Ethiopia. Sci. Technol. Arts Res. J., April-June 2014, 3(2): 119-131. Chave J, Andalo C, Brown S, Cairns MA, Chambers JQ, Eamus D, Folster H, Fromard F, Higuchi N, Kira T, Lescure JP, Nelson BW, Ogawa H, Puig H, Rie´ra B, Yamakura T (2005). Tree allometry and improved estimation of carbon stocks and balance in tropical forests. J. Springer-Verlag. 145: 87–99. De Castilho CV, Magnusson WE, de Araújo RNO, Luizão RCC, Luizão FJ, Albertina P, Higuchi N (2006). Variation in aboveground tree live biomass in a central Amazonian Forest: effects of soil and topography. J. Forest Ecology Management. 234: 85–96. Dereje D (2007). Floristic composition and Ecological Study of Bibita Forest (GuraFerda), Southwest Ethiopia. Unpublished M.Sc. Thesis, Addis Ababa University: Addis Ababa, Ethiopia. Eliasch J (2008). Climate Change: Financing Global Forests, review paper. ISBN and Crown. United Kingdom. Endalew A (2007). Use and management of medicinal plants by indigenous people of Ejaji area (Cheliya Woreda) West Shoa, Ethiopia: an ethnobotanical approach. Unpublished M.Sc. Thesis, Addis Ababa University, Addis Ababa, Ethiopia. FAO (Food and Agriculture Organization)(2008). Climate change adaptation and mitigation in the food and agriculture sector.HLC/08/BAK/1.technical background document from the expert consultation. FAO (2010). Global Forest Resources Assessment Main report 163, FAO forestry paper, ISBN 978-92-5- 106654-6, Rome. Italy. FAO (2012). Forest Management and Climate Change: a literature review Forests and Climate Change Working Paper 10: Rome. Yohannes H, Soromessa T, Argaw M (2015). Carbon Stock Analysis Along Altitudinal Gradient in Gedo Forest: Implications for Forest Management and Climate Change Mitigation. American Journal of Environmental Protection. Vol. 4, No. 5, 2015, pp. 237- 244. doi: 10.11648/j.ajep.20150405.14. Kauppi PE, Birdsey RA, Pan Y, Ihalainen A, Nöjd P, Lehtonen A (2015). Effects of land management on large trees and carbon stocks. J. Biogeosciences, 12, 855–862. Kent M, Coker P (1992). Vegetation Description and Analysis. A practical approach. John Wiley and Sons, New York, pp.363. Khanal Y, Sharma RP, Upadhyaya CP (2010). Soil and vegetation carbon pools in two community forests of Palpa district, Nepal. J. Banko Janakari. 20(2):34- 40. Lal R (2005). Forest Soils and Carbon Sequestration. Journal of Forest Ecology and Management. 220: 242– 258. MacDicken KG (1997). A Guide to Monitoring Carbon Storage in Forestry and Agro-forestry Projects.In Forest Carbon Monitoring Program. Winrock International Institute for Agricultural Development, Arlington, Virginia. Malla Y, Blaser J (2010). The Role of Social Forestry in Climate Change Mitigation and Adaptation in the Asean Region, assessment paper. RECOFTC, ASFN, and SDC: Thailand. Muluken NB, Teshome S, Eyale B (2015). Above- and Below-Ground Reserved Carbon in Danaba Community Forest of Oromia Region, Ethiopia: Implications for CO2Emission Balance. American Journal of Environmental Protection. Vol. 4, No.2, pp. 75-82. doi: 10.11648/j.ajep.20150402.11. Nakai Y, Hosoi F, Omasa K (2009). Estimating carbon stocks of coniferous woody canopy trees using airborne lidar and passive optical senser.iaprs, Vol. XXXVIII, Part 3/W8 – Paris, France. Neupane B, Sharma RP (2014). An assessment of the effect of vegetation size and type, and altitude on above ground plant biomass and carbon. Journal of Agricultural and Crop Research . Vol. 2(3), pp. 44-50, ISSN: 2384-731X. Offiong RA, Iwara AI (2012). Quantifying the stock of soil organic carbon using multiple regression models in fallow vegetation, Southern Nigeria. Ethiopian. Journal of Environmental Studies and Management EJESM .5(2): 1-20. Pearson TR, Walker S, Brown S(2005). Sourcebook for land-use, land-use change and forestry projects. Winrock International and the Bio-carbon fund of the World Bank. Arlington, USA, pp. 19-35. Ruiz-Jaen MC, Potvin C(2010). Can we predict carbon stocks in tropical ecosystems from tree diversity? Comparing species and functional diversity in a plantation and a natural forest, McGill University: Canada. Scaranello MAD, Alves LF, Vieira SA, De Camargo PB, Joly CA, Martinelli LA (2012). Height-diameter relationships of tropical Atlantic moist forest trees in southeastern Brazil. Sci. Agric. v.69, n.1, p.26-37. Shrestha BP (2009). Carbon sequestration in broad leaved forests of mid-hills of Nepal: A case study from Palpa district. J. The initiation. 3:20-29. Yanqiu Hu, Zhiyao Su, Wenbin Li, Jingpeng Li, Xiandong Ke (2015). Influence of Tree Species Composition and Community Structure on Carbon Density in a Subtropical Forest. J. PLOS. Yitebitu M, Zewdu E, Sisay N (2010). A review on Ethiopian
  • 7. Estimation of carbon stored in selected tree species in Gedo forest: implications to forest management for climate change mitigation J. Environ. Waste Manag. 107 Forest Resources: current status and future management options in view of access to carbon finances. Prepared for the Ethiopian climate research and networking and the United Nations development programme (UNDP).Addis Ababa, Ethiopia. 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 open- access 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.