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Carbon Consequences of China's Land Cover Changes -- Climate or Human Responsible?
Jiaguo Qi, DirectorCenter for Global Change and Earth Observations
Department of GeographyMichigan State University
Team: Dr. Jianjun Ge (Oklahoma State University); Dr. Haiyan Wei (USDA-ARS, Tucson, AZ);Dr. Phil Heilman (USDA-ARS, Tucson, AZ);Mr. Feng Zhang (Lanzhou University); Nathan Moore (MSU and ZJU)
Through my research and international
activities, I learned that the environmental
issues in Central Asia need to be addressed
urgently!
Why Central Asia?
K A Z A K H S T A N
R U S S I A
M O N G O L I A
C H I N A
1922 1999
5377
14951
1922 1999
4363
24232
1922 1999
965
6164
1940 1990
7502500
1952 2003
2581010650 1950 1996
23060
6600
1949 2002
36740
13170
1964 2000
26161251
1949 2000
19250
44331922 1999
4990
903
1922 1999
4730
883
1480
5180
1949 20001922 2002
23700
No data
1947 2002
1250032000
1949 1998
4090
1190
Population Changes in Central Asia (50s-80s)(Unit:1000)
Siberia-Mongolian High
(Aleutian Low)
North Pacif Low?
Subtropical High
Indian Low
westerlies
Indian Monsoon Asian Monsoon
Arctic-North Atlantic Low
Sensitive to climate change
8-19-2001(MODIStrueColor)
9-22-2004 (MODIS true color)
4-8-2005 (MODIS truecolor)
6-23-2003, (MODIS false color)
8-11-2007 (MODIS true color)
Agricultural Intensification
Desertification Salinization
Degradation
The National Research Council on March 12 released a report,Informing Decisions in a Changing Climate, that concludes we are “unprepared, both conceptually and practically” for climate change and that it is no longer valid to base decisions on the assumption of continued climatic conditions of the past.
Science Questions
• To what extent have human activities affected regional climate change?
• To what extent has the climate change affected ecosystems?
• How to discern the human impacts on China’s ecosystem dynamics from climate impacts?
EcosystemsHumanSystem
ClimateSystem
Approaches
Approach 1:Observational and Statistical Modeling• Remote sensing – temporal change
– GIMMS (1982-2006) and MODIS (2000-2007) time series
– In phenological and carbon/biomass
• Time series analysis with TIMESAT– Calculate the biomass
• Correlations analysis biomass – climate – Correlation coefficients: percentage of explanation– Examine residuals: percentage of explanation?
SI
Climate Downscaling
(RAMS)
HouseholdDynamics and Management
Practices
Land Use/Cover Change
Basic R S & GISLayers –
soil, property,Practice
Watersheds
EcosystemModels
(DNDC, TMDL)
EnvironmentalConsequences(N2O, CO2, CH4…)
SocioeconomicScenarios:
BMPs
Approach 2: System Modeling
738 meteorological stations across China
Climate data
To answer the question:
How to discern climate impact from human disturbance?
The SI over the growing season in 1982 across China
Example map of Small Integral (SI)
Slope of linear temporal trend of small integral across China from 1982 to 2006 (p<=0.05)
Correlation between SI and and climate factors
Correlation coefficient between SI and PJuly
Correlation between SI and and climate factors
Correlation coefficient between SI and TJuly
12 3
4
5
6
78
Taking the 8 counties as an example:
Results, residual trend
# CountyRelationship between small integral and selected
climate factors linear temporal trend
of residualEquation r2 Equation r2
1 Changji Sl = -7620.44 + 9.17 PJuly + 233.10 TJune + 201.21 TJuly 0.59 y=15.96x-31818 0.22
2 Dengkou SI = -1565.08 + 6.11 PJuly+ 46.56 TApril + 104.22 TJune 0.67 y = 6.96x - 13879 0.15
3 Qingshuihe SI = -114.95 + 5.21 PJuly -225.19 TMay + 243.94 TJuly 0.39 y = 30.06x - 59938 0.37
4 Aohan SI = -1289.97 + 6.81 PJune + 85.22 TFeb + 171.14 TJuly 0.34 y = 29.2x - 58225 0.24
5 Nantong SI = 16702.14 - 4.28 PJuly - 531.22TApril - 192.21 TJuly 0.52 y = -48.94x + 97576 0.31
6 Qianjiang SI = 14460.55 - 109.6 TFeb- 170.42TApril - 317.50 TJune 0.42 y = -31.33x + 62472 0.16
7 Guangning SI = 47614.52 - 7.11 PJuly - 222.17TApril - 1286.47 TJuly 0.38 y = -51.85x +103380 0.16
8 Mabian SI = 5623.69 + 4.15 PJuly - 157.61 TFeb - 166.95 TApril 0.44 y = -23.68x + 47222 0.08
Linear temporal trend of residual
-800
-600
-400
-200
0
200
400
600
800
1000
1982 1986 1990 1994 1998 2002 2006
Year
Resi
dual
1. Changji2. Dengkou3. Qingshuihe4. Aohan
-2500
-2000
-1500
-1000
-500
0
500
1000
1500
2000
1982 1986 1990 1994 1998 2002 2006
Year
Resi
dual
5. Nantong6. Qianjiang7. Guangning8. Mabian
Linear temporal trend of residual
To answer the question:
How has the climate change impacted the carbon sequestration of China
grassland?
Grassland above ground carbon change trend from 2000 to 2007
Grassland soil carbon storage change trend from 2000 to 2007
y = 1.5734x + 542.28R2 = 0.8973
0
5000
10000
15000
20000
25000
0 2000 4000 6000 8000 10000 12000 14000Estimated below ground vegetation carbon density(KgC/ha)
fan
belo
w g
roun
d ve
geta
tion
carb
onde
nsity
(KgC
/ha)
y = 1.4856x + 0.002R2 = 0.9971
0. 0
0. 5
1. 0
1. 5
2. 0
2. 5
3. 0
0. 0 0. 2 0. 4 0. 6 0. 8 1. 0 1. 2 1. 4 1. 6 1. 8 2. 0Estimated below ground vegetation carbon storage(PgC)
fan
belo
w g
roun
d ve
geta
tion
carb
onst
orag
e(Pg
C)
Below ground carbon results compare with Fan’s results
C density (PgC/ha)
C storage (PgC)
y = 0.3925x + 219.78R2 = 0.6194
0
200
400
600
800
1000
1200
1400
0 500 1000 1500 2000 2500 3000Estimated above ground carbon density (KgC/ha)
Ni f
orag
e ca
rbon
den
sity
(KgC
/ha)
y = 0.323x + 0.0026R2 = 0.7097
0.00
0.01
0.02
0.03
0.00 0.01 0.02 0.03 0.04 0.05 0.06
Estimated above ground carbon storage(PgC)
Ni f
orag
e ca
rbon
stor
age(
PgC
)
Above ground carbon result compare with Ni’s results
C density (PgC/ha)
C storage (PgC)
Conclusions
• Remote sensing, long term monitoring data can be very useful to study ecosystem changes
• Statistical approaches are useful in understanding the drivers of changes (discern climate cause from human impacts)
• Biogeochemical models (DNDC) incorporate human and climate into a system to quantitatively assess ecosystem responses to both climate and human drivers
• More research is needed to investigate the change patterns and their linkages to specific policy implementations (on going)
• On-going research focuses on fine resolution MODIS type data for other land cover types
Acknowledgment
• NASA and NSF funding
• Chinese MOST funding through CAS