Transcript PPT 2.1 MB - START - SysTem for Analysis Research and Training

CLIMATE CHANGE SCENARIOS AND IMPACTS ON THE
BIOMES OF SOUTH AMERICA
Carlos A. Nobre
CPTEC/INPE, Cachoeira Paulista, SP- Brazil
What are the likely biome changes in
Tropical South America due to Global
Warming?
Vegetation-Climate Interactions
Climate
Vegetation
Balanço Hídrico
P=E+C
P = Precipitação
E = Evapotranspiração
C = Convergência de Umidade
P
E
C
-20
-10
lat
0
10
Holdridge Life Zones and potential vegetation: the way most models deal with
climatic effects on vegetation cover.
Data courtesy of D. Skole
-80
-70
-60
-50
-40
lon
drying
Holdridge life zones (Holdridge 1967)
Savanna?
The Holdridge Life-Zone Classification System (Holdridge, 1947; 1967)
Climatic Conditions for
Savannas
Annual
precipitation
Growing season
Mean
climatic
equator
Arid
Savanna
South
Rainforest
Equator
Latitude
Savanna
Growing season length in months
Mean annual precipitation in mm
Tmean > 24 C
13 C < Tcoldest month < 18 C
P (3 driest months) < 50 mm
P (6 wettest months) > 600 mm
1000 mm < Pannual < 1500 mm
Arid
North
A scheme of the relationship between mean annual precipitation and growing
season length in tropical climates (from Newman, 1977)
Map of dry season
length (DSL) (data
after Sombroek,
2001), expressed
as the number of
months with <100
mm of rain.
Steege et al., Biodiversity and Conservation 12 (in press), © 2003 Kluwer Academic Publishers
Modeling Approach to Geographical
Distribution of Species
Temperature
Ecology
Ecological Niche Model
Geography
Algorithm
Geographical
Occurrences
Precipitation
Geographic
Prediction
of Species
Distribution
Geography
Algorithm
Area of
occurrence
Enviromental Variable B
Ecology
Modeling the Geographical Distribution
of Biomes
Biome Model
Environmental Variable A
Prediction
of Biome
Geographic
Distribution
The Algorithm
A Potential Biome Model that uses 5
climate parameters to represent the
(SiB)
biome
classification
was
developed (CPTEC-PBM).
Simple Land Surface Model
Pr: rain
Ps: snow
T: sfc air temperature
Ts: soil temperature
S: soil water storage
N: overland snow storage
E: evapotranspiration
R: runoff
M: snowmelt
Oyama and Nobre, 2002
Five climate parameters drive the
potential vegetation model
Monthly values of precipitation and temperature
Water Balance Model
Potential Vegetation Model
SSiB Biomes
Oyama and Nobre, 2002
growing degree-days on 0oC base
growing degree-days on 5oC base
Figure 6. Environmental variables used in CPTEC
PVM: growing degree-days on 0oC base (a), growing
degree-days on 5oC base (b), mean temperature of the
coldest month (c), wetness index (d), seasonality index
(e). Growing degree-days in oC day month-1, and
temperature in oC.
Oyama and Nobre, 2002
mean temperature of the coldest month
Wetness index
Oyama and Nobre, 2002
seasonality index
Oyama and Nobre, 2002
Tropical Forest
The potential
vegetation model
algorithm
Oyama and Nobre, 2002
Visual Comparison of CPTEC-PBM
versus Natural Vegetation Map
CPTEC-PBM
SiB Biome
Classification
62% agreement on a global 2 deg x 2 deg grid
Oyama and Nobre, 2002
Visual Comparison of CPTEC-PBM
versus Natural Vegetation Map
NATURAL VEGETATION
POTENTIAL VEGETATION
SiB Biome
Classification
Oyama and Nobre, 2002
What are the likely biome changes in
Tropical South America due to Global
Warming?
Change in Amazon Climate and
Hydrology in HadCM3LC
Lat: 15oS - 0oN
Lon: 70oW - 50oW
Amazon forest die-back!
Change in Amazon Carbon Balance
in HadCM3LC
Lat: 15oS - 0oN
Lon: 70oW - 50oW
Amazon forest die-back!
Change in Global Climate in HadCM3LC
Interactive CO2 and Dynamic Vegetation
2090s - 1990s
Temperature Anomalies (deg C) for 2091-2100
A2 High GHG Emissions Scenario
B2 Low GHG Emissions Scenario
Nobre et al., 2004
Precipitation Anomalies (mm/day) for 2091-2100
A2 High GHG Emissions Scenario
B2 Low GHG Emissions Scenario
Nobre et al., 2004
Ecology
Environmental Variable B
Analysis of Biome Redistribution as a
response do Climate Change
Geography
Algorithm
Area of
occurrence
Biome Model
Environmental Variable A
Prediction of
Biome
Geographic
Distribution
Projections
taking into
account climat
chage
Projection of Biome
Geographic
Distribution due to
Climate Change
Projected Biome Distributions for South America for 2091-2100
A2 High GHG Emissions Scenario
Natural Vegetation
B2 Low GHG Emissions Scenario
Natural Vegetation
Nobre et al., 2004
Multiple equilibria: coupled climate
and vegetation (Oyama & Nobre 2003)
Forest
Savanna
Desert
Amazon soils map and
potential flammability
(Nepstad et al. 2004)
Before deforestation
After deforestation
Potential Vegetation
Does climate variability play the
key role linking together climate
change, edaphic factors, and human
use factors?
Possible stability landscape for Tropical South America. Valleys (X1, X2
and Y) and hills correspond to stable and unstable equilibrium states,
respectively. Arrows represent climate state (depicted as a black circle)
perturbations. State X1 refers to present-day stable equilibrium. For
small (large) excursions from X1, state X2 (Y) can be found. It is
suggested that the new alternative stable equilibrium state found in this
work corresponds to X2. Notice that it is necessary to reach X2 before
reaching state Y.
Resilience
Stochastic Perturbations
Gradual Perturbations affect Resilience
(e.g., deforestation, fire, fragmentation, etc.)
Amazonian Vegetation: Multiple Equilibria, Persistence &
Climate
After Wang & Eltahir 2000
A
A complication: How
does the system get
to one or the other?
B
Another complication
C
Climate change shifts equilibria
Vegetation, like climate, can have more than one state that is persistent and resilient, in
analogy with movement of a ball on a landscape. Small disturbances lead to
adjustments and return to the initial state. Large disturbances may cause the system
to change to a new stable state, possibly to revert at a later time (cf. C. Nobre).
A shift in climate, due to natural or anthropogenic causes, can change the landscape, as
well as the frequency and magnitude of disturbance. The change in relative system
stability might make a vegetation change irreversible (e.g. Cox et al, 2001), but it might
take a disturbance for the shift to occur. Leads to the concept of instability.
Conclusions
The future of biome distribution in South
America in face of climate changes
• “Savannization” of Amazonia and tendency of even drier biomes of
Northeast Brazil
•
Some tendency for southward displacement of the Atlantic forest.
• Results do depend strongly on climate model used and less so on
emissions scenarios.
• The synergistic combination of regional climate changes caused by
global warming and by land cover change over the next several
decades could tip the biome-climate state to a new stable
equilibrium with ‘savannization’ of parts of Amazonia (and
‘desertification’ in Northeast Brazil).