changes of land use and land cover and biogeochemistry in ... · changes of land use and land cover...
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Department of Earth & Atmospheric Sciences and Department of Agronomy
Changes of Land Use and Land Cover and Biogeochemistry in Northern Eurasia
Qianlai Zhuang, Min Chen, Xudong Zhu, and Yaling LiuPurdue University
Jerry Melillo and Dave KicklighterEcosystems Center, Marine Biological Laboratory at Woods Hole
John Reilly, Andrei Sokolov, Sergey Paltsev, and Yongxia CaiMassachusetts Institute of Technology
Nadja Tchebakova, Anna Peregon, and Andrey SirinRussian Academy of Sciences
Anatoly ShvidenkoInternational Institute of Applied System Analysis
Guangsheng ZhouChinese Academy of Sciences
Shamil MaksyutovNational Institute for Environmental Studies, Tsukuba, Japan
Serreze et al., 2000, Climatic Change
Research Questions
How the land use and land cover in the region will be affected by natural and anthropogenic changes in this century?
How the biogeochemical cycles of carbon and water will be affected by changes of land use and land cover and climate?
Fertilizer N2O
Emissions
Natural
Transitions E
B
Future
Climate
Economic Model
(EPPA)
Biogeochemistry Model
(TEM)
Land-use
Change
Net Land
C Flux
A
Atmospheric
Chemistry and
Climate Model
Climate
Climate,
CO2, O3
Anthropogenic
Emissions
Updated
Land Cover
NPP
Biogeography
Model
(SiBCliM)
Land-cover
Change
Climate
Update
Land
Cover
MIT Integrated Global System Model
Major Features of EPPA and TEM
EPPA
• Multiple regions - Globe divided into 16 economic regions
• Multiple fuels - Fossil, Nuclear, Wind, Solar, Biomass, Biofuels
• Multiple sectors – Industry, Transportation, Households, Agriculture, Forestry
• International trade
TEM• Cycling of carbon, nitrogen,
and water
• Spatial information on soils, vegetation, climate, elevation, atmospheric chemistry (carbon dioxide, tropospheric ozone)
• Coupled with permafrost and fire dynamics
Major Features of SiBCliM
• A static envelope-type large-scale bioclimatic model based on the vegetation classification of Shumilova (1962)
• SiBCliM uses three bioclimatic indices: (1) growing degree-days above 50C; (2) negative degree-days below 00C; and (3) an annual moisture index (ratio of growing degree days above 5oC to annual precipitation)
• SiBCliM has been updated to include permafrost (the active layer depth)
Land Cover and Land Use Modeling
(Melillo et al., 2010)
Climate Policy
• An aggressive climate policy – CO2-eq. of 650 ppmv
• Free trade in biofuels
• Global participation in carbon constraint from 2015
• Cumulative emissions 2.3 Tt CO2-eq over 2001-2100, about 29% of no-policy scenario
• Target 2.4 w/m2 increase in radiative forcing by 2100 relative to 2000
a) Atmospheric CO2 concentrations b) AOT40 ozone index
c) Global mean air temperature d) Global mean precipitation
Atmospheric Climate and Chemistry during the 21st century
Year
2000 2010 2020 2030 2040 2050m
illio
n k
m2
0
5
10
15
20
25
30
Food Crop
Pasture
Managed Forests
Biofuels
Grasslands
Shrublands
Natural Forests
Other
Migration
Land-use Change in the Northern Eurasia over the first-half of the 21st Century
(No Policy)
Year
2000 2010 2020 2030 2040 2050
mill
ion k
m2
0
5
10
15
20
25
30No Migration
Food Crop
Pasture
Managed Forests
Biofuels
Grasslands
Shrublands
Natural Forests
Other
Global Land-use Change over the first-half the 21st Century(No Policy)
Year
2000 2010 2020 2030 2040 2050
mill
ion k
m2
0
15
30
45
60
75
90
105
120
135
Migration in Northern Eurasia
Year
2000 2010 2020 2030 2040 2050
mill
ion k
m2
0
15
30
45
60
75
90
105
120
135
No Migration in Northern Eurasia
Land-use Change in Northern Eurasia over the first-half of the 21st Century
(Policy)
Year
2000 2010 2020 2030 2040 2050
mill
ion k
m2
0
5
10
15
20
25
30
No Migration Migration
-77 -60 -40 -20 -1 1 20 40 60 80 90
Percent
Difference in Land Use due to Migration in Northern Eurasia in 2050
Food Crops
Pasture
Managed Forests
Policy
Northern Eurasia
No Migration in Northern Eurasia
Year
2000 2010 2020 2030 2040 2050
mill
ion k
m2
0
15
30
45
60
75
90
105
120
135
Migration in Northern Eurasia
Year
2000 2010 2020 2030 2040 2050m
illio
n k
m2
0
15
30
45
60
75
90
105
120
135
Global Land-use Change over the first-half of the 21st Century(Policy)
Net Land Carbon Flux (Pg C) in the Northern Eurasia(No Policy)
Year
2000 2010 2020 2030 2040 2050
Cu
mu
lative
Ch
an
ge
in
Ca
rbo
n (
Pg
C )
-160
-140
-120
-100
-80
-60
-40
-20
0
20
40
60
No Migration
Year
2000 2010 2020 2030 2040 2050
Cu
mu
lative
Ch
an
ge
in
Ca
rbo
n (
Pg
C )
-160
-140
-120
-100
-80
-60
-40
-20
0
20
40
60
Migration
Food Crops
Biofuel Crops
Pasture
C4 Grass
C3 Grass
C3 Grass Arctic
Broadleaved Decidous Shrub Boreal
Broadleaved Deciduous Tree Boreal
Needle-leaf Decidous Tree Boreal
Needle-leaf Evergreen Tree Boreal
Broadleaved Deciduous Tree Temperate
Needle-leaf Evergreen Tree Temperate
Net Accumulation of Land Carbon
Global Land Carbon Flux (Pg C)(No Policy)
Year
2000 2010 2020 2030 2040 2050
La
nd
Ca
rbo
n F
lux (
Pg
C)
-600
-500
-400
-300
-200
-100
0
100
200
No Migration in Northern Eurasia
Food Crop
Pasture
Managed Forests
Biofuel
Grasslands
Shrublands
Natural Forests
Other
Net Land Carbon Flux
Year
2000 2010 2020 2030 2040 2050
La
nd
Ca
rbo
n F
lux (
Pg
C)
-600
-500
-400
-300
-200
-100
0
100
200
Migration in Northern Eurasia
Year
2000 2010 2020 2030 2040 2050
La
nd
Ca
rbo
n F
lux (
Pg
C)
-150
-100
-50
0
50
100
No Migration
Year
2000 2010 2020 2030 2040 2050
La
nd
Ca
rbo
n F
lux (
Pg
C)
-150
-100
-50
0
50
100
Food Crop
Pasture
Managed Forests
Biofuel
Grasslands
Shrublands
Natural Forests
Other
Net Land Carbon Flux
Migration
Net Land Carbon Flux (Pg C) in the Northern Eurasia(Policy)
Year
2000 2010 2020 2030 2040 2050
La
nd
Ca
rbo
n F
lux (
Pg
C)
-600
-500
-400
-300
-200
-100
0
100
200
No Migration
Year
2000 2010 2020 2030 2040 2050
La
nd
Ca
rbo
n F
lux (
Pg
C)
-600
-500
-400
-300
-200
-100
0
100
200
Food Crop
Pasture
Managed Forests
Biofuel
Grasslands
Shrublands
Natural Forests
Other
Net Land Carbon Flux
Migration in Northern Eurasia
Global Land Carbon Flux (Pg C)(Policy)
Changes in land cover (million km2) of Northern Eurasia
during the first half of the 21st century
Changes in global land cover (million km2) during the first half
of the 21st century
Net land carbon flux (Pg C) from terrestrial ecosystems in
Northern Eurasia during the first half of the 21st century
Net land carbon flux (Pg C) from global terrestrial ecosystems during the
first half of the 21st century. Migration only occurs in Northern Eurasia
Progress Summary• Northern Eurasia: By year 2050, under policy and migration conditions, the food crops will
change from 5 to 6, pasture from 6 to 8, managed forests from 1 to 2, natural forests from 8
to 5, grasslands from 6 to 4 million km2, respectively. There is a similar land-use change
trend under no-policy and migration conditions, but with smaller magnitudes.
• Globe: By year 2050, under policy and migration conditions, the food crops will change from
22 to 24, managed forests from 3 to 3.4, natural forests from 31 to 26, grasslands from 11 to
9 million km2, respectively. Under no-policy and migration conditions, the food crops will
change from 22 to 29, pasture from 34 to 38, natural forests from 31 to 25, and grasslands
from 11 to 8 million km2, respectively.
• Northern Eurasia: During the first 50 years of this century, the cumulative net carbon
exchange is -13 and -93 Pg C under no-policy and no-migration and migration conditions,
respectively. With policy, the region will act as a sink of 0.8 and a source of -94 Pg C under
no-migration and migration conditions, respectively.
• Globe: Under the no-policy condition, the cumulative net carbon exchange is -46 and -428 Pg
C over the globe under no-migration and migration in northern Eurasia by year 2050. Under
the policy condition, the global cumulative source of carbon is smaller with -8 and -409 under
no-migration and migration, respectively.
Vegetation Distribution in NE Simulated with SiBCliM
Vegetation distribution in Siberia for the current (top right) and in 2080 mapped by coupling our SiBCliM with bioclimatic indices and the permafrost for HadCM3 B1 (top left) and HadCM3 A2 (bottom) with no albedo feedbacks
Vegetation class key: 0- Water,;Boreal: 1 –Tundra; 2 – Forest-Tundra; Northern Taiga: 3 – dark, 4 – light; Middle taiga: 5 – dark, 6 – light; Southern Taiga: 7 – dark, 8 – light; 9 – Subtaiga, Forest-Steppe; 10– Steppe; 11 –Semidesert
Tundra Needle-leaf Evergreen
Forest-Tundra
Needle-leaf Deciduous
Forest-Tundra
Needle-leaf
Evergreen Taiga
Needle-leaf
Deciduous Taiga
Boreal Birch Subtaiga/
Temperate Broadleaf
Temperate
Mixed Forest
Forest-Steppe
Boreal
Forest-Steppe
Temperate
Tundra No Change Fire Fire Fire Fire Fire Fire Fire Fire
Needle-leaf Evergreen Forest-
Tundra Succession No Change Fire Fire Fire Fire Fire Partial Fire Fire
Needle-leaf Deciduous Forest-
Tundra Succession Fire No Change Fire Fire Fire Fire Fire Fire
Needle-leaf Evergreen Taiga Succession Succession Fire No Change Fire Fire Fire Succession Fire
Needle-leaf Deciduous Taiga Succession Fire Succession Fire No Change Fire Fire Fire Fire
Boreal Birch Subtaiga/
Temperate Broadleaf Succession Succession Succession Fire Fire No Change Succession Fire Succession
Temperate Mixed Forest Succession Succession Succession Fire Fire Succession No Change Fire Succession
Forest-Steppe Boreal Fire Partial Fire Fire Fire Fire Fire Fire No Change Fire
Forest-Steppe Temperate Fire Fire Fire Fire Fire Partial Fire Partial Fire Fire No Change
Steppe Boreal, Temperate Fire Fire Fire Fire Fire Fire Fire Fire Fire
Semi-Desert/Desert Fire Fire Fire Fire Fire Fire Fire Fire Fire
Succession - no loss of carbon due to disturbance; Fire - loss of carbon associated with fire disturbance event; Partial Fire - fire disturbance results in loss of carbon from only grasses, forbs, shrubs and perhaps some trees - some vegetation survive fire
New Vegetation Type Old Vegetation Type
Mechanisms of Vegetation Transitions
Interannual Variability in Area Burned
No Policy Policy
Distribution of Fire Events in the No Policy Scenario
Year 2091
Year 2092
EPPA Model * The MIT Emissions Prediction and Policy Analysis (EPPA) model is a recursive dynamic multi-regional computable general equilibrium (CGE) model of the world economy
* The model is based on the Global Trade Analysis Project (GTAP) data base with the data aggregated into 16 regions and 25 sectors
* In the version of the model used here (EPPA4), five of these sectors require land inputs that have been stratified into five land classes— cropland, pastureland, managed forest land, unmanaged grasslands, and unmanaged forest.
•The EPPA model also incorporates United States EPA inventory data and projections on greenhouse gas (CO2, CH4, N2O, HFCs, PFCs, and SF6) and air pollutant emissions (SO2, NOx, black carbon, organic carbon, NH3, CO, VOC) to estimate anthropogenic emissions of these compounds.
* The EPPA model projects the global economy, land use, and associated anthropogenic emissions into the future using a 5-year time step.
