Aboveground biomass calculations Carbon and biodiversity plots 1. Inventory design
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10 Manuri et al. 2014 and Komiyama et al. 2005 were used to estimate tree AGB for dryland forests,
peat swamp forests and other mangrove species i.e. Excoecaria agallocha and Sonneratia caseolaris, respectively.
Table 3: Allometric biomass models for estimating tree aboveground biomass AGB.
Tree species Allometric model
Statistics Location
Source Plantation forest
Acacia mangium W
ag
= 0.070D
2.580
D: 8–28 cm R
2
= 0.97 South Sumatra
Wicaksono 2004 cited in Krisnawati et al. 2012
Eucalyptus pellita
1
W
ag
= 0.0678D
2.790
D: 2–27 cm R
2
= 0.99 South Sumatra
Onrizal et al. 2009 cited in Krisnawati et al. 2012
Estate crop Hevea brasiliensis
W
ag
= 0.2661D
2.1430
Elias 2014 Elaeis guineensis
W
ag
= 0.0706 + 0.0976H Sumatra, Kalimantan
ICRAF 2009 cited in Hairiah et al. 2011
Dryland forest Tropical mixed species
W
ag
= 0.0673 pD
2
H
0.976
D: 2–212 cm Africa, America, Asia
Chave et al. 2014
Peat swamp forest Mixed species
W
ag
= 0.15 D
2.0.95
p
0.664
H
05526
D: 2–167 cm R
2
= 0.981 Riau, South Sumatra,
West Kalimantan Manuri et al. 2014
Mangrove forest Avicennia marina,
Avicennia alba
1
W
ag
= 0.1846D
2.352
D: 6–35 cm R
2
= 0.98 West Java
Darmawan Siregar 2008 cited in Krisnawati et al. 2012
Bruguiera gymnorrhiza W
ag
= 0.1858D
2.3055
D: 2–24 cm R
2
= 0.989 Australia
Clough Scott 1989 Bruguiera parviflora,
Bruguiera sexangula
1
W
ag
= 0.1799D
2.4167
D: 2–21 cm R
2
= 0.993 Australia
Clough Scott 1989 Ceriops tagal
W
ag
= 0.1884D
2.3379
D: 2–18 cm R
2
= 0.989 Australia
Clough Scott 1989 Rhizophora apiculate,
Rhizophora mucronata
1
W
ag
= 0.235D
2.42
D: 5–28 cm R
2
= 0.98 Malaysia
Ong et al. 2004 Xylocarpus granatum
W
ag
= 0.0823D
2.5883
D: 3–17 cm R
2
= 0.994 Australia
Clough Scott 1989 Other species
Excoecaria agallocha, Sonneratia caseolaris
W
ag
= 0.2512pD
2.46
D: 5–49 cm R
2
= 0.979 Indonesia, Thailand
Komiyama et al. 2005 W
ag
= aboveground biomass kg, D = Diameter at Breast Height DBH, cm, H = tree height m, p = wood density gramcm
3
, R
2
= coefficient of determination
1
The aboveground biomass of these tree species were estimated using the available allometric models for similar tree species.
The diameter at breast height D and tree height H data were obtained from the field measurements in each carbon inventory plot. But, the height data of some trees in Secondary Logged over Dryland
Forests at PT REKI and BKSDA Dangku and Primary Mangrove Forests at TN Sembilang were not available, so that diameter-height models Table 4, which were developed based on the available data,
were applied to estimate missing tree height measurements. Wood density p data was obtained from ICRAF’s database
http:db.worldagroforestry.org . When a species-specific wood density value for a
particular tree species was not available, then the genus or family level wood density value was used in the allometric models. For tree species that could not be identified by their scientific names only 0.8
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11 of the total tree species, the allometric models used average wood density values that were derived
from identified tree species in a particular stratum and location Table 5.
Table 4: Diameter-height models for estimating tree height in some surveyed areas.
Stratum
1
Location Model
Statistics
Secondary Logged over Dryland Forest Hutan Lahan Kering Sekunder Bekas Tebangan
PT REKI H = D0.7707+0.0195D
n = 168, D = 5–104 cm, AIC = 1032.21, RMSE = 5.58,
R
2 adj
= 0.624 BKSDA Dangku
H = exp0.7071+0.6556lnD n = 156, D = 6–69 cm,
AIC = 845.56, RMSE = 3.75, R
2 adj
= 0.690 Primary Mangrove Forest
Hutan Mangrove Primer TN Sembilang
H = 28.16131-exp-D27.0703 n = 221, D = 5-77 cm,
AIC = 1098.86, RMSE = 2.89, R
2 adj
= 0.750 D = Diameter at Breast Height DBH, cm, H = tree height m, n = number of samples, AIC = Akaike Information Criterion, RMSE =
root mean square error, R
2 adj
= coefficient of determination adjusted
1
in brackets Bahasa Indonesia
Table 5: Average wood density for unidentified tree species.
Startum
1
Location Mean
gcm
3
St.dev. gcm
3 2
Primary Dryland Forest Hutan Lahan Kering Primer
TN Kerinci Seblat 0.615
0.142 Secondary Logged over Dryland Forest
Hutan Lahan Kering Sekunder Bekas Tebangan PT REKI
0.594 0.143
Primary Mangrove Forest Hutan Mangrove Primer
Banyuasin 0.702
0.077 Secondary Logged over Swamp Forest
Hutan Rawa Sekunder Bekas Tebangan TN Sembilang
0.643 0.115
1
in brackets Bahasa Indonesia
2
standard deviation
Some carbon inventory plots i.e. 7 plots or 4.9 of the total sample plots also contained non-woody vegetation i.e. bamboo, palm or rattan. The quantity of such non-woody vegetation, however, was
very low with incomplete measurements of diameter or height, which resulted in difficulties when estimating their biomass. Therefore, the quantification of this insignificant non-woody biomass for
these 7 sample plots was ignored. The biomass of understory vegetation in each carbon inventory plot was estimated based on the field
measurements and a laboratory analysis of the understory vegetation samples. The field measurements provided data on the sample’s fresh weight and total fresh weight of the understory
vegetation, while the laboratory analysis provided data on the sample’s dry weight of the understory vegetation. The aboveground biomass of the understory vegetation was then calculated on the ratio of
dry and fresh weights of the sample, which was then multiplied with the total fresh weight of the understory vegetation within a sample plot.
Total biomass of saplings, poles, small trees, large trees und understory vegetation in each subplot were converted into a common unit i.e. tonha and then were added to derive total aboveground
biomass for each sample plot. Aboveground biomass estimates per plot in tons per hectare tha for the carbon plots are shown in Appendix A. Table 6 summarizes the aboveground biomass estimates
for the different strata. An in-depth explanation of the results and methods applied in the field
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12 inventory is provided in the BIOCLIME GIZ Final Report: Cadangan Karbon Hutan dan Keanekaragaman
Flora di Sumatera Selatan Tiryana et al. 2015.
Table 6: Statistical results for the aboveground biomass AGB estimates for the different strata.
Stratum
1
Number of carbon inventory plots
Min AGB tha
2
Max AGB tha
3
Mean AGB tha
4
Primary Dryland Forest Hutan Lahan Kering Primer
8 196.1
637.0 335.6 ±153.8
Secondary Logged over Dryland Forest Hutan Lahan Kering Sekunder
33 69.1
560.7 259.0 ±129.0
Primary Mangrove Forest Hutan Mangrove Primer
13 159.8
531.3 304.7 ±98.8
Secondary Logged over Mangrove Forest Hutan Mangrove Sekunder
7 44.9
342.5 174.0 ±114.1
Primary Peat Swamp Forest Hutan Rawa Gambut Primer
5 442.4
616.0 538.1 ±64.9
Secondary Logged over Peat Swamp Forest
Hutan Rawa Gambut Sekunder 9
114.9 414.0
207.1 ±89.9 Plantation Forest
Hutan Tanaman 8
5.4 133.8
59.9 ±43.7 Tree Crop Plantation
Perkebunan 15
3.4 211.6
62.2 ±55.4 Shrubs
Semak Belukar 6
8.7 127.2
59.6 ±54.0 Swamp Shrubs
Semak Belukar Rawa 8
1.3 105.5
55.5 ±41.5
Sum 112
1
in brackets Bahasa Indonesia
2
Minimum aboveground biomass AGB in tons per hectare for the stratum
3
Maximum aboveground biomass AGB in tons per hectare for the stratum
4
Mean aboveground biomass AGB in tons per hectare for the Stratum class ± = standard deviation
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13
3. LiDAR data and aerial photos 3.1. LiDAR and aerial photo survey
In October 2014 15 transects of LiDAR data and aerial photos were captured for an area of approximately 43,300 ha. LiDAR data was acquired in two modes a LiDAR full waveform mode +
aerial photos with an overlap of 60 and b LiDAR discrete return mode + aerial photo overlap 80. Table 7 displays the technical specification of this LiDAR and aerial photo survey. A more detailed
description of the survey can be found in the report of the surveying company PT Asi Pudjiastuti Geosurvey PT Asi Pudjiastuti Geosurvey 2014.
Table 7: Technical specifications of the LiDAR and aerial photo survey PT Asi Pudjiastuti Geosurvey 2014.
Parameter Flight plan
Remark
LiDAR acquisition mode Full Waveform FWF Unlimited returns of laser reflectance
Discrete Return 4 returns of laser reflectance Flying height
800 m The survey was conducted at 800 m above
ground level to get the accurate laser reflectance and minimize cloud cover.
Laser pulse frequency 500 KHz
Product specification in ALS70 Leica used for the project.
LiDAR point density Full Waveform FWF 8-15 pointsm
2
Discrete Return 6-8 pointsm
2
Aircraft speed 110 knots
Half scan angle 28 degrees
Field of view FOV 56 degrees. With this FOV LiDAR coverage will be embedded
with aerial photo coverage.
Swath width 851 m
A scan angle FOV of 56 degrees and a flying height of 800 m will provide 851 m
area coverage
Ground Sample Distance GSD 10-12.5 m
Forward overlap Full Waveform FWF 60 overlap
Discrete Return 80 overlap
Aerial photo coverage 86 m x 644 m
Acquisition of aerial photos using a digital camera: Leica RCD 30 with 6 µm pixel
resolution, with a GSD of 10 cm per pixel will results in a coverage of 860 m x
644 m.
Figure 6 shows the location of the LiDAR transects within the BIOCLIME study area.
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14 Figure 6: Location of the approximately 43,300 ha of LiDAR transects captured within the BIOCLIME
study area.