Magnitude and Spatial Distribution of Uncertainty in Ecosystem Production and Biomass of Amazonia

Caused by Vegetation Characteristics

Christopher Potter and Sassan SaatchiNASA Ames Research Center, Moffett Field, California, USA

Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109

Steven Klooster and Vanessa GenoveseCalifornia State University Monterey Bay

LBA-ECO Science ThemeLC - Carbon Dynamics

Existing Vegetation Maps for Model InputExisting Vegetation Maps for Model Input

1.1. JPL Amazon Basin Map Based on SPOT VGT 98-01, JERS-1 95-JPL Amazon Basin Map Based on SPOT VGT 98-01, JERS-1 95-96, (Saatchi, et al., 2003)96, (Saatchi, et al., 2003)

2.2. UMD global classification Based on AVHRR 92-93 data, (Hansen et UMD global classification Based on AVHRR 92-93 data, (Hansen et al., 2000)al., 2000)

3.3. TREES Vegetation Map of South America Based on SPOT VGT, TREES Vegetation Map of South America Based on SPOT VGT, JERS-1, ATSR-1, AVHRR, GTOPO30 (Eva et al., 2002)JERS-1, ATSR-1, AVHRR, GTOPO30 (Eva et al., 2002)

4.4. USGS Global Vegetation Map Based on AVHRR 92-93 (Loveland USGS Global Vegetation Map Based on AVHRR 92-93 (Loveland et al., 2000)et al., 2000)

5. Woods Hole Research Center Vegetation Map of South America 5. Woods Hole Research Center Vegetation Map of South America Based on AVHRR 88-91 LAC, GVI (Stone et al., 1994)Based on AVHRR 88-91 LAC, GVI (Stone et al., 1994)

Evergreen Forest

Deciduous Forest

Woody Savanna

Savanna

Flooded Forest

Flooded Nonforest

Secondary Forest

Pasture/Crops

Vegetation Map of Amazon Basin Data Fusion (Saatchi et al., 2003)

Vegetation Map of Amazon Basin Data Fusion SPOT VGT, JERS-1(Saatchi et al., 2003)

Deforestation Pattern in Rondonia, Brazil

Santarem

Deforestation along Transamazonian Highway BR230

Deforestation Pattern in Rondonia, Brazil

Santarem

Deforestation along Transamazonian Highway BR230

UMD Global Vegetation MapDecision Rule, AVHRR 92-93Hansen et al., 2000

Santarem

Deforestation Pattern in Rondonia, Brazil

Deforestation along Transamazonian Highway BR230

TREES Vegetation Map of South AmericaMulti-Resolution, SPOT VGT, JERS-1,ATSR-1, AVHRR, GTOPO30 Eva et al., 2002

Santarem

Deforestation Pattern in Rondonia, Brazil

Deforestation along Transamazonian Highway BR230

USGS Global Vegetation MapStandard Supervised, AVHRR 92-93 Loveland et al., 2000

Santarem

Deforestation Pattern in Rondonia, Brazil

Deforestation along Transamazonian Highway BR230

Woods Hole Research Lab.Vegetation Map of South AmericaClustering Approach AVHRR 88-91, LAC, GVI Stone et al., 1994

Santarem

Percent Cover of Land Cover Types in the Amazon Basin Percent Cover of Land Cover Types in the Amazon Basin

Class Type JPL % cover UMD% cover TREES %cover

USGS % cover WHRC % cover

Evergreen Forest 69.16 79.12 80.53 79.78 77.72Deciduous Forest 1.74 1.81 -- --- 1.56Woodland Savanna 5.67 5.32 4.86 4.61 7.76Savanna 4.55 11.24 3.27 7.03 3.49Flooded Forest 7.65 -- 2.73 -- 1.39Flooded Nonforest 2.43 -- 0.61 0.62 0.23Secondary Forest 1.88 -- 2.12 -- 0.28Pasture/Crops 4.99 0.60 4.59 6.26 4.23Water 1.57 1.79 1.27 -- 0.73

Percent Pixel-to-Pixel Agreement Between Land Cover Types

Maps JPL UMD TREES USGS WHRCJPL 100

UMD 60.6 100

TREES 63.5 76.0 100

USGS 68.7 77.2 76.2 100

WHRC 78.7 74.2 74.7 75.2 100

Maps JPL UMD TREES USGS WHRCJPL 100

UMD 84.3 100

TREES 91.6 96.3 100

USGS 88.9 95.2 96.3 100

WHRC 91.0 93.5 94.7 55.2 100

Percent Pixel-to-Pixel Agreement of Forest Type Between Maps

Maps JPL UMD TREES USGS WHRCJPL 100

UMD 32.2 100

TREES 41.2 38.8 100

USGS 37.1 53.6 44.7 100

WHRC 43.2 40.9 36.2 41.4 100

Percent Pixel-to-Pixel Agreement of Nonforest Type Between Maps

Results From Map ComparisonResults From Map Comparison

1.1. Agreement between maps range from 60-75% averaged over Agreement between maps range from 60-75% averaged over all class typesall class types

2.2. Approximately 80% of the basin is covered by forest and Approximately 80% of the basin is covered by forest and the agreements among maps for forest class are above 90%the agreements among maps for forest class are above 90%

3.3. Major disagreement between maps are in nonforested areas.Major disagreement between maps are in nonforested areas.On the average the maps are only 30-50% in agreement. On the average the maps are only 30-50% in agreement.

4. Differences are due to the prediction of deforested and regrowth 4. Differences are due to the prediction of deforested and regrowth areas in 1-km resolution maps. Savanna pixels with differentareas in 1-km resolution maps. Savanna pixels with differentdegrees of woody vegetation are misclassified as forest ordegrees of woody vegetation are misclassified as forest ornonforest in different maps.nonforest in different maps.

5.5. Deforested areas covered with pasture and crops are betterDeforested areas covered with pasture and crops are better estimated by JPL and TREES maps because of the use ofestimated by JPL and TREES maps because of the use of

high resolution imagery.high resolution imagery.

NASA-CASA ModelNASA-CASA Model

f(TEMP)f(WFPS) f(Lit q)

(a) Soil Moisture Balance and Plant Functional Types

(b) Ecosystem Production Nutrient Mineralization

(c) Biogenic Trace Gas Flux

Leaf Litter

Root Litter

Microbes

Soil OrganicMatter

CO2

Mineral Nf(Lit q)

SoilProfile Layers

Heat &WaterFlux

PPT

N2O NO

f(WFPS)

CH4

Grass/Crop Shrub Tree

PET

FPAR

NPP

M 0

M 1

M 2

M 3

M 0

M 1

M 2

M 3

M 0

M 1

M 2

M 3

Soil Surface

Biomass

CO2NEP

Rh

f(TEMP)f(WFPS) f(SOLAR)

NASA-CASA Model SimulationsOver Legal Amazon

1. Five land cover types are used as input layers in the model and allother variables are considered constant for each run

2. Land cover maps are resampled to 8 km x 8 km grid cells using a majority filter. Cover types are combined to four general

classes of evergreen forests, wooded grassland and savanna,pasture and cultivated land, and other classes. Wetland classes are integrated into forest and savanna types.

3. Annual Net Ecosystem Production (NEP) are simulated for twoextreme years: 1983 (dry condition) and 1990 (wet condition).

4. Total above ground wood biomass carbon is simulated for 1990.

NEP Simulations Over Legal AmazonBased on JPL Map (g C m-2 yr-1)

19831990

-500 -250 0 250 500 g C m-1 yr-1

Changes in NEP Simulations1983

JPL-UMD JPL-TREES

JPL-USGS JPL-WHRC

No Change

> 0

< 0

Changes in NEP Simulations1990

JPL-UMD JPL-TREES

JPL-USGS JPL-WHRC

No Change

> 0

< 0

NEP Profile Across Basin, 1983

NEP Profile Across Basin, 1990

NEP83 JPL UMD TREES USGS WHRCJPL 100

UMD 82.0 100

TREES 82.3 83.5 100

USGS 81.7 80.3 81.2 100

WHRC 81.9 82.4 84.6 80.3 100

Percent Pixel-to-Pixel Agreement of Between NEP-83 Simulations

-3.54

-3.53

-3.52

-3.51

-3.5

-3.49

-3.48

-3.47

-3.46

0.08 0.1 0.12 0.14 0.16 0.18

Total NEP (pg C yr

-1)

Ratio of Area Non Forest/ Forest

JPL

UMD

WHRC

TREES

USGSFloodplain Areas are Excluded

NEP90 JPL UMD TREES USGS WHRCJPL 100

UMD 82.2 100

TREES 82.6 83.6 100

USGS 81.9 80.5 81.5 100

WHRC 82.2 82.6 84.5 80.7 100

Percent Pixel-to-Pixel Agreement of Between NEP-90 Simulations

3.21

3.22

3.23

3.24

3.25

3.26

3.27

3.28

0.08 0.1 0.12 0.14 0.16 0.18

Total NEP (pg C yr

-1)

Ratio of Area Non Forest/ Forest

JPL

UMDWHRC

TREES

USGS

Floodplain Areas are Excluded

Summary

1. Differences in land cover maps cause 0.1-0.4 pg C yr-1 uncertainty in total Net Ecosystem Production over the Legal Amazon

2. The impact of land cover uncertainties are higher during wet year (carbon sink flux) over the region.

3. Ratio of nonforest area over forest area explains the changes of total annual NEP. Relationship is significant in wet years and insignificant during the dry years (regional source flux).

4. The impacts of uncertainty in land cover types (e.g. deforested, pasture, crops) are the same magnitude of the NEP interannual variability.

5. During dry years other variables such as fire rainfall distribution anomalies dominate the impact of land cover differences

Above Ground Woody Biomass CarbonDerived from NASA_CASA Model

Early 1990s

0 5,000 10,000 18,000 g C m-2

Changes in Biomass Carbon1990

JPL-UMD JPL-TREES

JPL-USGS JPL-WHRC

No Change

> 0

< 0

BIOMASS90 JPL UMD TREES USGS WHRCJPL 100

UMD 96.1 100

TREES 96.2 96.5 100

USGS 96.0 95.7 96.0 100

WHRC 96.2 96.2 96.6 96.1 100

-2

-1

0

1

2

3

0 5 10 15 20

Wood Biomass Difference (pg C)

Normalized Ratio of Nonforest

JPL-UMD

JPL-USGSJPL-TREES

JPL-WHRC

54

55

56

57

58

59

0 0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08

Total Wood Biomass (pg C)

Ratio Nonforest/Forest

UMD

JPL

WHRC

TREES USGS

Percent Pixel-to-Pixel Agreement of Between Biomass Simulations

Summary1. NASA-CASA model predicts 54-58 pg C of above ground woody

biomass across legal Amazon for the early 1990s

2. The impact of land cover differences are on the order of 1-3 pg Cthat are primarily due to misclassification of areas of nonforest types in land cover maps.

3. Total forest cover defines the above ground woody biomass

carbon. All five maps show above 95% agreement on forest cover. Differences in normalized ratio of nonforest/forest explain changes of above ground woody biomass across the region.

4. Coarse resolution maps do not allow accurate classification of areas of disturbance on annual basis.