IJERD – International Journal of Environmental and Rural Development (2015) 6-2

Research article
erd

Rapid Carbon Stock Appraisal (RACSA) Implementation in
Wahig-Inabanga Watershed, Bohol, Philippines
TOMAS D. REYES, JR.*
Bohol Island State University, Bohol, Philippines
Email: tomseyer@yahoo.com, tomseyer@gmail.com

ERWIN G. LUDEVESE
Bohol Island State University, Bohol, Philippines
Received 3 March 2015

Accepted 27 August 2015(*Corresponding Author)

Abstract. The study aimed at assessing the biomass and carbon stocks of all major land uses in
Wahig-Inabanga Watershed, Bohol, Philippines and to estimate its total carbon budget. The “Apriori stratification cum purposive sampling” was used. Field measurements were conductedfollowing the destructive and non-destructive methods. The total C stored in the different land
uses surveyed in the watershed was estimated at 3.89 Megatons, 83.23% of which was held in
the cultivated perennial crops. Among the land uses assessed, it was only mangrove which had
lower carbon density estimate relative to previously reported values indicating substantial
degradation of mangroves vegetation over the years. The possibility of increasing its potential
to store more carbon could only be improved if appropriate management and alternative
livelihood interventions, coupled with conservation and protection measures are properly
implemented.
Keywords RACSA, carbon stock, carbon budget, Wahig-Inabanga Watershed

INTRODUCTION
Carbon stock assessment is not new to science. Many researchers have attempted to document andquantify carbon stocks of almost every land use in the Philippines since the late 1990s, and even earlier
in other countries. Lasco and Pulhin (2003) provided a list of several studies which have investigatedthe carbon stocks of forest ecosystems and other land cover types in the Philippines. Most of the
carbon stock assessments were conducted in plantations where dynamics were only affected by the
choice of species, management styles and decisions, silvicultural operations and environmental factors.
Few have even designs species-plantation/stand-based allometric equations (Codilan et al., 2009).
These were all triggered by the increasing importance of carbon stock assessment in policy and thepossible consequences for economic incentives (C markets) (Hairiah et al., 2001 and Hairiah et al.,2011). In Bohol, carbon stock studies were implemented in a 2-hectare rubber plantation at Magsaysay,
Talibon (Reyes et al., 2011) and oil palm plantations in Carmen, Sierra Bullones, and Pilar (Pulhin,
personal communication).
The RACSA appraisal tool, which was used in this study, was designed to provide a basic level
understanding of carbon appraisal and it introduced a scientifically sound methodological frameworkof accounting carbon sinks; while focusing on activities that could improve local livelihoods andalleviated rural poverty (Hairiah et al., 2011). Its application in the Wahig-Inabanga Watershed
provided an idea of how much carbon was stored in the watershed and its potential in sequestering
more carbon dioxide from the atmosphere.
This report focused only on the rapid carbon stock estimation of Wahig-Inabanga Watershed in
Bohol, Philippines based on the current scenario. It assessed the biomass and carbon stocks of all majorⒸISERD102

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land uses in Wahig-Inabanga Watershed, Bohol, Philippines and determined the watershed’s total
carbon budget.
METHODOLOGY
Study Site
The study was conducted in Wahig-Inabanga Watershed, Bohol, Philippines. This watershed is thebiggest in Bohol Province embracing a total land area more than 610 km2 or over 15 % of the total landarea of the Province. It is geographically located between 124º 3’ 36” and 124º 23’ 24” East longitude,
and between 9º 43’ 48” to 10º 4’ 48” North latitude. It has two headwaters namely the Wahig andPamacsalan Rivers and its outlet is geographically located at 10º 4’12” North latitude and 124º 4’12”
East longitudes (Fig. 1). It traverses the municipalities of Garcia Hernandez, Jagna, Duero, Sierra
Bullones, Pilar, Alicia, Carmen, Dagohoy, San Miguel, Sagbayan, Trinidad, Talibon, Jetafe,
Buenavista, Danao, and Inabanga.

Fig. 1 Location of the study area: (a) map of the Philippines showing the Central Visayas; (b)map of the Central Visayas showing Bohol; and (c) map of Bohol showing the WahigInabanga Watershed
Site Selection and Sampling Procedure
The rapid carbon stock appraisal was carried out only in four identified municipalities of WahigInabanga Watershed. Among the 16 municipalities within the watershed, Pilar, Sierra Bullones, Danao,
and Inabanga were selected for this study. These are municipalities which cover large areas in thewatershed. Selection criteria considered were the variability of land cover and land uses, elevationdifferences, and geological features which would represent the characteristics of the whole watershed.
The strategy used in this research was the “Apriori Stratification cum Purposive Sampling”(Hairiah et al., 2001) commonly known as preferential sampling patterned from the methodology
suggested by Hairiah et al., (2011). This means that the sampling locations and plots are identified
prior to successive field surveys. This approach was employed for the reason that it would be more
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expensive and very time consuming if one of the regular field survey methods, such as random
sampling, systematic sampling, and stratified random sampling, is to be applied following a definite
sampling intensity.
In this study, plots were laid in secondary forests; shrub/scrublands; cultivated perennial crops
also referred in this paper as agroforestry areas; rice and cornfields; grasslands; mangroves; andexisting tree plantations (i.e. Swietenia, Gmelina, Tectona, Elaeis, and Acacias).
Sampling Layout and Plot Sizes
In this study, rectangular-shaped plots were chosen since these tended to include more of the withinplot heterogeneity, and thus, represented more heterogenic species than square or circular plots of thesame area. Three different plots sizes were employed in the study based on Hairiah et al. (2001) andHairiah et al. (2011). The 20m x 100m plot for trees with diameter at breast height (DBH) >30 cm andwas used mainly in secondary forests, shrubs, and apitong (Dipterocarpus grandiflorus) natural stand.
The 5m x 40m plot was established for trees in plantations, agroforestry farms (perennial crops), andmangrove sites. The same size of plot was also nested in the middle of the 20m x 100m plot to measuretrees with DBH < 30 cm. On the other hand, plot with a dimension of 1m x 1m was employed toappraise undergrowths, agricultural crops (rice and corn), low stature weeds, and grasses.
Biomass Measurement of Aboveground Carbon Pools
Trees and other woody plants: Non-destructive measurement of trees, shrubs, and other woody
plants as suggested by Hairiah et al. (2001) was adopted in this study. Diameter at breast height (DBH),
merchantable height (MH), and total height (TH) were among the biometrics measured.
Understorey vegetation: Destructive or harvest method was used to determine the biomass ofunderstorey vegetation. Total fresh samples were weighed and recorded, however only approximately
50-500 g of samples were collected for oven-drying. Oven-dried weight was again recorded in eachsample after 3 days of drying.
Floor litter: Similar with the understorey vegetation, destructive or harvest method was also employed
for floor litter. Total fresh samples were weighed and recorded, and only approximately 50-200g ofsamples were kept for subsequent oven-drying.
Cereals and weeds: The method applied to determine the biomass of the understorey vegetation was
also used for land uses such as rice, corn, and grassland.
Estimation of Belowground Carbon Pool
Belowground biomass (root biomass): This is a fraction of aboveground biomass. An equation in
Table 1 was used for this purpose.
Soil Stock Pool: Percent soil organic carbon and bulk density are important variables in the calculationof soil carbon. These values were derived from the ACIAR-BSWM project report (ACIAR, 2006) andresults of BSWM soil chemical analysis on soils collected during the series of soil surveys done by the
CSIRO-BSWM team.
Parameter values for percent soil organic carbon in each survey location were obtained using the
Kriging interpolation function in ArcGIS. The values were derived employing the extract by sample
function in the spatial analysis tool. On the other hand, bulk density values were directly taken fromthe BSWM soil survey report.
Data AnalysisⒸISERD104

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Quantifying biomass and carbon stock: Allometric equations for trees and other plants suggested by
Hairiah et al., (2011) for estimating above-ground and root biomass were used (Table 1). Biomass andcarbon content were calculated in kilograms and then finally converted in tons (=mega grams [Mg])
per hectare.
Table 1 Allometric equations used to compute for the above-ground (AGB) and below-groundbiomass (BGB)
Plant Type / Species
Tree/shrub
Mangrove
Rhizophora
Sonneratia
Avicennia
BananaAllometric Equation
AGB= ρ* EXP(-1.499 + 2.148 LN(DBH) + 0.207(LN[DBH])2 - 0.0281*(LN[DBH])3)

SourceChave et al., 2005

AGB = 0.2453 – 0.2165*(DBH) + 0.0658*(DBH2) +0.0270*(DBH2*TH)
AGB = 0.2301 – 0.5382*(DBH) + 0.3370*(DBH2) +0.0474*(DBH2*MH)
AGB = 0.0198 – 0.0013*(DBH) + 0.0097*(DBH2) +0.0155*(DBH2*MH)
AGB = 0.030*(DBH2.13)

Codilan et al., 2009
Codilan et al., 2009
Codilan et al., 2009
Arifin, 2001; Noordwijk
et al., 2002
Priyadarsini, 2000
ICRAF, 2009
Frangi and Lugo, 1985
Modified from Teopolo
et al., 2002

AGB = 0.131*(BDC2.28)
AGB = 0.0976 *(TH) + 0.0706
AGB = 4.5 + 7.7*(TH)AGB = 0.3999 + (7.907*TH)*0.2
Note:
0.2 added in the equation since nipa does not have
aboveground stem
Coffee
AGB = 0.281 D 2.06
Arifin, 2001
Root Biomass
RB = EXP(-1.0587 + 0.8836*LN[AGB])
Cairns et al., 1997
Note: AGB = estimated aboveground biomass (kg/tree); RB = estimated root biomass; DBH = diameter at breast
height (cm); BDC = basal diameter of cluster (cm); TH = total height (m); ρ = wood specific gravity (Mg/m 3); EXP =exponent; LN = natural logarithm
BambooOil palm
Palm
Nipa

For this study, a conservative estimate of 45% tons of C per 100% tons of oven-dried biomass was
adopted since the carbon content of biomass dry weight based on the studies conducted in and out of
the country ranges from 40% to 55% (Lasco and Pulhin, 2000 as cited by Lasco et al., 2005).
Conversely, a simple formula on oven dried weight was used to compute for the biomass ofunderstorey plants, weeds, rice, corn, and floor litter.
ODW = TFW- (TFW*(SFW-SODW))/SFW
Where ODW is total oven dry weight, TFW total fresh weight, SFW sample fresh weight and SODW
sample oven dry weight
The carbon content of each pool was calculated by getting the 45% of the total biomass, except
for soil carbon which was computed by obtaining the product of soil weight and % organic carbon. The
total carbon was calculated as the summation of all carbon content in all pools.
RESULTS AND DISCUSSION
Biomass and Carbon Stock Assessment
Plantation: Among the major land uses considered in the study, plantation had the largest above- andbelowground biomass which was estimated to be 630.64 tons ha-1 and 102.45 tons ha-1, respectively. Its
soil carbon was also computed at 3.64 tons ha-1. Forty five percent of its combined biomass inclusiveof soil carbon amounted to 333.53 tons of carbon per hectare (Table 2). Such quantity of carbon isⒸISERD105

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almost 300 tons larger than the average of the total stored carbon in selected Philippine plantations
amounting to only 55.6 tons ha-1 (Lasco and Pulhin, 2000 as cited by Lasco et al., 2005). Though thetypical condition of most of the tree plantations in the watershed is not ideal (crooked, and mostly
thinner and shorter (stunted) relative to the trees age), their density (close spacing) has contributed
much to their current biomass.
Conversely, Lasco and Pulhin (2003) reported that carbon stocks of plantations in Mt. Makiling
ranged from 125.6 to 285.7 tons ha-1 and even way lower in other parts of the country. A separate study
conducted earlier by Racelis (2000), however conformed with the result of this study and revealed thatmahogany plantation in Mt. Makiling, due to its age, dense stocking and large girth, had a computed
carbon stock of 542.05 tons ha-1. These results also added that the dipterocarp stand in the same study
area, sharing similar features, had even higher stored carbon of about 639.81 tons ha-1.
Secondary forest including apitong stand: The second type of land use in Wahig-Inabanga
watershed having considerable quantity of biomass and, thus, carbon was the secondary forest. Its
above- and belowground biomass were 209.51 tons ha-1 and 38.13 tons ha-1, respectively. Its soil
carbon of 3.78 tons ha-1 was the largest among the computed soil carbon in all land uses. These gave a
total carbon stock of 115.22 tons ha-1 (Table 2). The computed total stored carbon of secondary forest
in Wahig-Inabanga watershed was comparable with that of the secondary forest in Kaliwa watershed.
The latter, according to Lasco et al. (2005), has a total carbon stock of 121.21 tons ha-1. Lasco andPulhin (2009) stated an average of 111.10 tons ha-1 of stored carbon for several surveyed secondary
forests in the country.
Agroforestry: Same with the first two land uses, agroforestry had an estimated total carbon stock ofmore than 100 tons ha-1. Its estimated total stored carbon was 104.05 tons ha-1 (Table 2). This value istwice as high as the estimate presented by Lasco and Pulhin (2000) as cited by Lasco et al. (2005)
disclosing an average of 50.3 tons ha-1 for agrorestry sites in the country. The bloated values in thepresent study were attributed to the dominance of coconuts and other tree crops in the surveyed areas.
However, such amount of carbon is still below the carbon stocks of Taungya agroforestry and mixed
multistorey systems in Bukidnon with 174 tons ha-1 and 162 tons ha-1, respectively (Labata et al., 2012).
Shrub/brushland: The computed above- and belowground biomass per hectare in shrub/brushlandamounting to 172.56 tons ha-1 and 32.77 tons ha-1, and a soil carbon of 3.50 tons ha-1 provided anequivalent carbon stock of 95.90 tons ha-1 (Table 2). This value is comparatively higher than theestimates of Lasco and Pulhin (2000) as cited by Lasco et al. (2005), in several watersheds in the
country which ranged from 29.0 tons ha-1 to 74.27 tons ha-1. This could be due to the presence of few
invasive timber species such as yemane (Gmelina arborea), mahogany (Swietenia macrophylla) and
ipi-ipil (Leucaena leucocephala) which have been naturally dispersed from adjacent plantations andhave grown with small-sized native shrubs and trees.
Mangrove: Among the major land uses, mangrove is generally noted as the most represented in termsof number of individuals. However, the density alone is not the only requisite for a particular land use
to acquire high biomass. The foremost requirement is the availability of considerable number of hugediameter trees which, unfortunately, is not a good trait of the surveyed mangrove areas. Based onrecords, more than half of the measured plants (mostly young Rhizophoras) had diameters of less than
5 cm. For this reason, the computed biomass densities were only 87.98 tons ha-1 for aboveground and17.72 tons ha-1 for belowground, with a corresponding carbon stock of not more than 50 tons ha -1(Table 2). These values are over 3 times smaller than the country’s average mangrove biomass andcarbon stock of about 401.8 and 176.8 tons ha-1, respectively (Lasco and Pulhin, 2000 as cited byGevana et al., 2008). Gevana et al., (2008) reported that mangroves’ biomass density may reach up to
more than 500 tons ha-1 especially if it is dominated by large-sized Rhizophoras. One good example isthe study of Fujimoto (2000) as cited by Gevana et al., (2008) in Matang, Malaysia which revealed thatabove-ground biomass alone was computed to reach 558 tons ha-1. Rhizophora-dominated mangroveⒸISERD106

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stands are noted to have large biomass and carbon density (Tanouchi et al., 2000 as cited by Gevana etal., 2008). The presence of their unique physiognomic characteristics such as the presence of stilt roots,
dense stem and branches, and relatively large canopy contributes much to the total biomass.
Grass: The result of the above-ground biomass density computation for the surveyed grasslands,
together with its carbon stock, coincides with the estimates of Lasco and Pulhin (2000) as cited by
Lasco et al., (2005). The carbon stock of 5.48 tons ha-1 is comparable with the country’s averagecarbon stock for grasslands of about 5 tons ha-1 (Table 2).
Rice: Farms planted to rice are among the land uses with little amount of biomass and consequently
carbon content. This is due to seasonal harvests leaving almost no traces of biomass especially afterland preparation. The rice farms’ computed above-ground biomass density and total carbon stock were
4.11 tons ha-1 and 5.3 tons ha-1, respectively (Table 2). Same with grass, more than half of the total
carbon stock for rice came from the soil carbon.
Corn: Among the land uses assessed in this study, it was corn which had the least estimated biomass
and carbon stock. This was because of having only 3-4 individual plants which were harvested forbiomass calculation in a standard one square-meter plot. In addition, regular care and maintenance likeharrowing and weeding limit the growth of herbaceous weeds and grasses. For these reasons, thecomputed above-ground biomass was only 2.97 tons ha-1 and its carbon stock was 4.74 tons ha-1. It isalso noticeable that a big chunk, roughly 3.4 tons, of carbon per hectare was derived from soil carbon(Table 2).
Table 2 Computed above and belowground biomass and carbon in major land uses in WahigInabanga Watershed, Bohol, Philippines
Land Use
Plantation
Secondary forest with Apitong standAgroforestry
Shrub/Scrubland
Mangrove with nipa
Grassland
Rice
Corn

AGB
(ton ha-1)
630.64209.51
188.28172.56
87.98
4.52
4.11
2.97

BGB
(ton ha-1)
102.45
38.13
34.71
32.77
17.72
-

Soil Carbon(ton ha-1)
3.64
3.78
2.21
3.50
2.21
0.96
3.45
3.40

Total Carbon(ton ha-1)
333.53115.22104.05
95.90
49.77
5.48
5.30
4.74

Note: AGB = aboveground biomass; BGB = belowground biomass

Table 3 Carbon storage of different land uses in Wahig-Inabanga Watershed, Bohol,
Philippines
Land Use
Secondary forest
Shrubland
Cultivated perennials*
a. Coconut/tree-based
agroforestry farmb. Tree plantation
Mangrove with nipa
Rice
Corn
Grassland

Area of Coverage(ha)1,247.75
5,910.05
23,878.82
(90%)
(10%)
537.6314,146.65
9,401.21
4,073.16

Carbon Stock(tons ha-1)
113.2992.12

Total Carbon Stock(tons)
141,357.60
544,443.81

104.052,236,132.10

333.53
49.78
5.30
4.74
5.48
Total

796,430.28
26,763.22
74,977.25
44,561.74
22,320.92
3,886,976.90

Note: *“Cultivated perennials” is assumed composed of 90% coconut/tree-based agroforestry farms and 10% plantations.
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Total Carbon Budget
Table 3 provides a rough estimate of the carbon budget of the whole watershed. A total of
3,886,976.90 tons or 3.89 megatons of carbon was computed based on the land uses’ areas of coverageand computed carbon stocks. The biggest share comes from cultivated perennial crops which had thelargest area of coverage within the watershed and the highest estimated carbon stocks.
Shrub/brushland and secondary forest also had significant contributions on the watershed’s carbon
budget due to the substantial number of trees and shrubs which were appraised in these types of land
use compared to those with extensive area of coverage however dominated by low stature annual plants.
CONCLUSION AND RECOMMENDATION
The Wahig-Inabanga watershed’s estimated overall carbon stock of 3.89 megatons presents the finest
contribution of the watershed to the global carbon budget. Around 83.38% of these are presented incultivated perennial crops, while the rests are stored other land uses. The possibility of increasing its
potential to store more carbon could only be harnessed if appropriate management interventions were
implemented.
Open areas like grasslands, for instance, offer immense potential of sequestering carbon throughtree planting and agroforestry. If in case tree planting and agroforestry, as immediate interventions, areinappropriate, natural or artificial regeneration may be the best alternative option.
Among the land uses assessed in the watershed, it was only mangrove which had lower carbon
density estimate relative to previously reported values. This indicates substantial degradation ofmangroves vegetation through time. For this type of land use, provision of alternative livelihood,protection and conservation, apart from reforestation activities are the best options to undertake. Any
management intervention would only be wasted if alternative livelihood options are not available andconservation and protection measures are not properly enforced.
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