This document discusses error and accuracy in estimating above ground biomass (AGB) in rainforests. It provides AGB estimates for various rainforest locations ranging from 55 to 552 Mg/ha. Estimating AGB is challenging due to high plant diversity, large numbers of small trees, and variability in wood density and tree architecture between species. The document examines how measurement error, algorithm suitability, plot size, and accounting for understory biomass can impact AGB estimation accuracy. It presents data from a 25ha rainforest plot in Robson Creek that found high variability between hectares and subplots in estimated AGB. Larger plot sizes were shown to improve AGB estimation accuracy.
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Matt Bradford_Error and precision in rainforest biomass estimations
1. Error and accuracy of rainforest
biomass estimation
Matt Bradford, Adam Mckeown, Anna Deffner
19th February 2013
SUSTAINABLE ECOSYSTEMS
2. Above ground biomass (AGB)
Location Approx AGB (Mg/ha) Source
Solomon Is. and New Caledonia 552 Keppel et al. (2007)
Congo (Gilbertiodendron forest) 535 Makana et al. (2011)
Wet Tropics, QLD (uplands) 500 CSIRO (unpublished)
Borneo, SE Asia 457 Slik et al. (2010)
Congo (mixed rainforest) 399 Makana et al. (2011)
Amazon basin 288 Malhi et al. (2006)
Amazon basin central and eastern 278 Baker et al. (2004)
Wet Tropics, QLD (lowlands) 270 Liddell et al. (2007)
Barro Colorado Is. Panama 270 Chave et al. (2004)
Amazon basin north west 221 Baker et al. (2004)
Amazon basin south west 207 Baker et al. (2004)
2 | Rainforest biomass Matt Bradford February 2013
3. Above ground biomass (AGB)
Approx AGB
Location Forest type (Mg/ha) Reference
Wet Tropics, QLD (uplands) Rainforest 500 CSIRO (unpublished)
Victoria Tall Eucalypt 476 Tajchman et al. (1996)
Batemans Bay, NSW Woodland 397 Ximenes et al. (2006)
Wombat SF, Vic Woodland 309 TERN supersite
Wet Tropics, QLD (lowlands) Rainforest 270 Liddell et al. (2007)
New England, NSW Woodland 250 Yoa et al. (2011)
SERF, Samford QLD Woodland 200 TERN supersite
South west WA Mallee woodlands 150 Jonson and Freudberger (2011)
South west WA Woodland 150 Jonson and Freudberger (2011)
Northern Territory Woodland 55 O'Grady et al. (2000)
3 | Rainforest biomass Matt Bradford February 2013
4. Above ground biomass (AGB) estimations
• Accuracy of AGB estimations is influenced by:
• measurement error
• algorithm suitability
– availability of wood density and height
– number of large trees
• Size of measurement unit
• Biomass held in understory and other life-forms
How do we best collect and use our data to calculate
an accurate AGB?
4 | Rainforest biomass Matt Bradford February 2013
5. AGB estimation in rainforest
• Large number of trees
• Large numbers of stems in understory
• Approx 9500 stems/ha, 4.9% of biomass
• High plant diversity
• Architecture
• wood density (0.2-1.1g/cm3)
5 | Rainforest biomass Matt Bradford February 2013
6. Robson Creek 25ha rainforest plot
6 |
Rainforest biomass Matt Bradford February 2013
7. Robson Creek 25ha rainforest plot
7 |
Rainforest biomass Matt Bradford February 2013
8. Robson Creek 25ha rainforest plot
ROBSON CREEK 25HA SUPERSITE. TREES
>=10CM DBH
Hectare Subplot Team
Date
Tag # DBH POM Species HT East North Codes
(cm) (m) (m) (m) (m)
8 | Rainforest biomass Matt Bradford February 2013
9. Robson Creek 25ha rainforest plot
• 23400 stems ≥10 cm DBH
•Mean of 936 stems per hectare
• 213 species from 50 families
•Mean of 98 species per hectare (81-120)
•Range of wood density from 0.2 – 1.0 g/cm3
9 | Rainforest biomass Matt Bradford February 2013
10. Robson Creek 25ha rainforest plot
10000
8000
Number of observations
6000
4000 2000
2000 1.2% of stems
1500
19% of biomass
Number of Observations
0
10 30 50 70 90 110 130 160
Diameter at breast height (cm)
1000
500
0
Species
10 | Rainforest biomass Matt Bradford February 2013
11. Variation in AGB Chave et al. (2005)
AGB = 0.0509*DBH2*HT*wood density
600
500
Above ground biomass (Mg/ha)
400
300
200
100
0
Hectare
11 | Rainforest biomass Matt Bradford February 2013
12. Variation in AGB
50
40
Above ground biomass (Mg)
30
20
10
0
20 x 20m subplot
12 | Rainforest biomass Matt Bradford February 2013
13. Variation in AGB
1200
1000
Above ground biomass (Mg/ha)
800
Mean = 402.0 ± 159.6 SD
600
400
Mean = 402.0 ± 56.9 SD
200
0
13 | Rainforest biomass Matt Bradford February 2013
14. Estimation error – plot size
0.25
20 x 20 m plot
0.20
Mean proportion error
0.15
0.10
0.05
0.00
0 5 10 15 20 25
Area (Ha)
14 | Rainforest biomass Matt Bradford February 2013
15. Estimation error – plot size
0.25
0.20
20*20
Mean proportion error
20*50
50*100
0.15
100*100
0.10
0.05
0.00
0 5 10 15 20 25
Area (Ha)
15 | Rainforest biomass Matt Bradford February 2013
16. Estimation accuracy – plot size
Probability of being within 5% of true value 1.0
0.8
20*20
0.6 20*50
50*100
100*100
0.4
0.2
0.0
0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25
Area (ha)
16 | Rainforest biomass Matt Bradford February 2013
19. Collaboration - LIDAR
73 cm DBH stem
LIDAR height = 43m
AGB = 8.83 Mg
CSIRO height = 44m
AGB = 9.03 Mg
Mean 11 stems/ha >70 cm DBH
AGB = 2.2 Mg/ha
19 | Rainforest biomass Matt Bradford February 2013
20. Accuracy of AGB estimation
• Measurement error – height and DBH
• Choice of algorithm – wood density
• Number of large trees
• Biomass held in understory and other life-forms
• Size of measurement unit
20 | Rainforest biomass Matt Bradford February 2013
21. Thank you
Ecosystem Sciences
Matt Bradford
Research Projects Officer
t +61 7 40918825
e matt.bradford@csiro.au
w www.csiro.au/
ECOSYSTEM SCIENCES
23. Collaboration
• Column plots of measured BA vs prism BA vs TLS BA
23 | Rainforest biomass Matt Bradford February 2013
24. Collaboration
• May have to use BA comparisons
2
p = 0.0000; r = 0.9246
500
400
Calculated AGB (Mg/ha)
300
200
100
0
0 10 20 30 40 50
Measured basal area (m2/ha)
24 | Rainforest biomass Matt Bradford February 2013