Estimation of Biomass and Carbon Stocks: the Case of the Atlantic Forest Simone Vieira Cena/USP.
Transcript of Estimation of Biomass and Carbon Stocks: the Case of the Atlantic Forest Simone Vieira Cena/USP.
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Estimation of Biomass and Carbon Stocks: the Case of
the Atlantic Forest
Simone VieiraCena/USP
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Estimation of Biomass and Carbon Stocks: the Case of The
Atlantic Forest
Simone A. Vieira, Luciana F. Alves, Marcos Aidar, Luciana Spinelli Araújo, Tim Baker, João Luís F. Batista, Mariana Cruz Campos, Plinio B. Camargo, Jerome Chave, Welington B. Delitti, Niro Higuchi, Euridice Honorio, Carlos A. Joly, Michael Keller, Luiz A. Martinelli, Eduardo Arcoverde de Mattos, Thiago Metzker, Oliver Phillips, Flavio A. M. Santos, Mônica Takako Shimabukuro, Marcos Silveira, Susan E. Trumbore
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Tropical forests are obviously a source of carbon dioxide to the atmosphere through land use
change
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But what are the dynamics of C in intact forests and what is their potential to respond to global environmental change such as - increased CO2
- climate change - anthropogenic pressure ?
and why Atlantic Forest???????
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The Atlantic Forest 500 years ago
(1.36 million km2)
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The Atlantic Forest today
(92 thousand km2)
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How much C was emitted to the atmosphere due to the land use
change in Atlantic forest?
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http://www.ib.unicamp.br/destaques/biota/gradiente_funcional/index.html
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0 m
1,000 m
How does the structure and the function of the
forest change along this altitudinal gradient?
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Our questions –
What is the capacity for these forests to store C?Where could it be stored and for how long?
Our approach –
First - Look at components of C stocks: Above and below ground and the environmental variables that control them.
Use radiocarbon to determine the residence time of carbon in trees and soils
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10m100m
300m
1000m
Floristic composition, structure and forest dynamics
Coastal flooded fo
rest
(restinga)
Lowland dense forest
Submontane dense
forestMontane dense forest
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RJSP
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X
Y
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Sed
e N
úcle
o S
anta
Vir
gíni
a
Fazenda Capricórnio
Casa da Farinha
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Restinga
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C
B
D
E
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G
H
IJ
F
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Stem information
-Number
-Location (X and Y)
-Identification(Floristic)
-Measurement
-DBH (1,30m)
-HDBH
-Total Height
-Trunk quality
-Illumination of canopy
-Vertical trunk position
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trees, palms and tree ferns
Mininum size:
4.8cm DBH
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Propagation of error
Data quality
Allometric model quality
Size of the sampled area
How well the plots represent
the forest
DBH of one tree
AGB of one tree
AGB of one plot
AGB of the forest
measurement
Allometric model
Sum of trees
Mean of plots
Chave et al. (2004)
Propagation of error in estimating the biomass of Tropical Forest
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Selection and validation of models
• Diameter (DBH, cm)• Height (m)• Wood density – specific gravity of wood (g/cm3, 15%
humidity)
Fonte: http://www.edb.ups-tlse.fr/equipe1/chave/ctfswd.htm
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Atlantic ForestAbove ground biomass
• Tiepolo et al. (2002) – Guaraqueçaba (PR)
• Burguer (2005) – Santos (SP)
• Rolim et al. (2005) – Linhares (ES)
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Allometric model – trees Dry biomass above ground (kg ha-1)
Reference Allometric model
(AGB) R2
DBH range
(cm)
Allometric Model with 1 variables – DBH
Chambers et al.
(2001)
exp(+1 ln(DBH)+2 (ln(DBH))2-3
(ln(DBH))3) -0.37 0.333 0.933 -0.122 0.973 5-130
Burger (2005) = exp(+1ln(DBase)) -
6.80067 3.77738 - - -0.915 12.5-27.9*
Tiepolo et al.
(2002) +1 (DBH)+2 (DBH)2 21.297 -6.953 0.74 - 0.91 4-116
Allometric Model with 2 variables – DBH and wood density or DBH and Height
Chave et al.,
(2005)a**
X exp(+1ln(DBH)+2ln(DBH))2 -
3 ln(DBH))3) -1.499 2.1481 0.207 -0.0281 0.996 5-156
Scatena et al.
(1993) = exp(+1 (ln(DBH)2 X H)) -3.282 0.95 - - 0.947 2.5-57
Allometric Model with 3 variables– DBH, wood density, height
Chave et al.,
(2005)b* = X exp(+ln(X DBH2 * H) -2.977 - - - 0.989 5-156
* Base diameter ** These models refer to the moist tropical forests.
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Life-
form Reference
Allometric model
(AGB) R2
DBH (cm) and
H (m) range
Pal
ms
Allometric Model with 1 variable – DBH or Height
Tiepolo et al. (2002) = + 1*(Height) 0.3999 7.907 - 0.75 1-33
Brown et al. (2005) =+ (1(DBH0.5)*ln(DBH)) 6.6666 12.826 -
Hughes et al. (1999) = exp (((+1 ln(DBH2))*2 )/103 5.7236 0.9285 1.05001 0.82 -
Allometric Model with 2 variables – DBH and Height
Saldarriaga et al.
(1988) = exp (+1 ln(1/(DBH)2)+2ln(Height)) -6.3789 -0.877 2.151 0.89 -
Tre
e fe
rn Allometric Model with 1 variable – DBH
Tiepolo et al. (2002) = /(1-1exp-2 * Height) -4266348 2792284 0,313677 0.88 1-8
Lia
nas
Allometric Model with 1 variable – Diameter
Gehring et al. (2004) = exp (+1 (ln(D)) 7.114 2.276 0.945 0.1-13.8 (Db)
0.2-48(H)
Schnitzer et al. (2006) = exp (+1 (ln(D)) -1.484 2.657 0.694 1-23
Gerwing et al. (2000) = exp (+1 (ln(D)) 0.07 2.17 0.95 1-13.5
Allometric model – other life forms
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Amazon forest
Atlantic Forest
Tree total height x DBH in Amazon forest (western Amazon) and Atlantic forest (Picinguaba).
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DBH (cm)
0 20 40 60 80 100
Hs´
(m
)
0
5
10
15
20
25
30
35
Coastal F. forestLowland forestSubmontane forestMontane forest
Scaranello (2007)
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0
50
100
150
200
250
300
350
400
450
500
Submontane forest
Bio
mas
s (M
g h
a-1)
Scatena et a. (1993)
Chave et al. (2005)b
Tiepolo et al (2002)
Chave et al. (2005)a
Chambers et al. (2001)
Submontane dense forest
Abo
ve g
roun
d bi
omas
s (M
g/ha
)
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• ca.22,000 tree stems > 4.8 cm DBH
• Dens = 1477 180 ind ha-1 ( CI 95%)
• BA = 34.0 4.1 m2 ha-1
• > 10 cm DBH - change between altitudinal
density 25%
Basal area– 69%
biomass – 30%
Forest Structure
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AltitudeAltitude
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Total Above Ground BiomassTotal Above Ground Biomass
AltitudeAltitude
74%
47%
71%
69%
> 30 cm> 30 cm
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AB
C
D
E
F
G HI
J
N
-3
-3.5
-1 1 3
-2.5
-1.5
-0.5
0.5
Axis 1
Axi
s 2
FOD
Montana
FOD Terras Baixas Explorada
Restinga
FOD Terras
Baixas
FOD Submontana
FOD Submontana
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Forest Structureimplications to carbon stocks
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Disturbance
Forest structure and biomass
Carbon stock
Residence time and Residence time and forest dynamicforest dynamic
Edaphic factorsEdaphic factors
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Biomass distribution in DBH size class
Dry season
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Altitudinal Position
Biomass distribution in DBH size class
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Spatial patterns in carbon storage above and belowground in Brazilian Tropical Forest: Amazon and Atlantic Forest
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FinanciamentoFinanciamento
Este trabalho foi financiado pela Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) no âmbito do Projeto Temático Gradiente Funcional (Processo 03/12595-7), que faz parte do Programa BIOTA/FAPESP - O Instituto Virtual da Biodiversidade (www.biota.org.br). Autorização COTEC/IF 41.065/2005 e autorização IBAMA/CGEN 093/2005.
http://www.ib.unicamp.br/destaques/biota/gradiente_funcional/index.html