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Climate Change & Forests;
Impacts & vulnerability
Prof. Ravindranath
Indian Institute of Science
Bangalore
Outline
1. Critical issues in the context of climate
change and forests
2. Status of forests in India
3. Impacts of climate change on forest
ecosystems
4. Greening India Mission and long term
monitoring
–
India’s response to climate change
Forests and climate change
1. Deforestation and land use change contribute to
CO2 emissions
– IPCC; 20% of CO2 emissions
2. Forests provide a large potential to mitigate
climate change
- IPCC; 15 – 20% of CO2 emissions
3. Forests will be impacted by climate change and
are highly vulnerable to climate impacts
-
Need for adaptation to enable forests to cope with
climate change
------------------------------------------------------------Forest sector is critical in addressing climate change
Forest sector is very contentious in global negotiations
Figure 1: Forest cover map of India of 2007 (FSI, 2009)
Trends in area under forest over
the period 1987 to 2009
(according to FSI reports)
Cumulative area afforested
during 1951 to 2005
Status of Forests
• India has reasonably succeeded in conserving
forests – though degradation continues
• India has effective forest conservation acts
• India is also implementing one of the largest
afforestation programmes
• India has launched a large Greening India
Mission- aimed at mitigation and adaptation
to climate change
Impacts of Climate Change – IPCC findings
• Populations of threatened species are expected to
become extinct
– 1/3 to 2/3rd of known biodiversity at risk of extinction
• Species composition and dominance will be
altered, resulting in ecosystem changes
• Shifts in forest types boundary
– Altitude & Latitude
• Forest die-back / mortality
– Climate change faster than capacity to migrate
• Increase and later decrease in biomass productivity
• Tipping point; Amazon could be turned to
savannah
Projected Climate Change
for India
a) Pre monsoon (March–June) Tmax for the baseline period (1961–1990).
b) projected future (2071–2100 minus 1961–1990 mean) change.
c) Projected future change in number of rainy days (days with rainfall [2.5
mm) during monsoon season and
d) the projected change in the intensity (mm/day) of rainfall on a rainy day
Projection of Impact of
Climate Change on Forests
Global Vegetation Model:
1. BIOME4: Equilibrium model
2. IBIS (Integrated Biosphere
Simulator): dynamic global
Vegetation Model
3. Working currently on LPJ & CLM
models
Climate Model: GCM and RCM data from
• Hadley HadRM3 data (50x50 km2)
• In future other GCMs will be used
1.Tropical wet evergreen forests,2.Tropical semi evergreen
forests, 3.Tropical moist deciduous forest, 4.Tropical dry
deciduous forest, 5.Tropical thorny/scrub forests, 6.Tropical
dry evergreen forest,7.Littoral and swampy forest,
8.Subtropical broad -leaved hill forests, 9.Subtropical pine
forests, 10.Sub-tropical dry evergreen forests, 11.Montane
wet temperate forests, 12.Himalayan wet/ moist temperate
forests, 13.Himalayan dry temperate forests, 14.Sub-alpine
forests, 15.Moist alpine, 16.Dry alpine
1: tropical evergreen forest / woodland, 2: tropical deciduous
forest / woodland, 3. temperate evergreen broadleaf forest /
woodland, 4: temperate evergreen conifer forest / woodland,
5: temperate deciduous forest / woodland, 6: boreal evergreen
forest / woodland, 7: boreal deciduous forest / woodland, 8:
mixed forest / woodland, 9: savanna, 10: grassland / steppe,
11: dense shrubland, 12: open shrubland, 13: tundra, 14:
desert, 15. polar desert / rock / ice
VALIDATION: Model simulated current vegetation
distribution (right) compared with observed vegetation
distribution - 70% of grids correctly simulated
Forest type distribution and extent
simulated by IBIS for the baseline case
and A1B (2035 and 2085) scenarios. (VT
– refers to Vegetation Types. The
numbers refer to the following
vegetation types
1: tropical evergreen forest / woodland,
2: tropical deciduous forest /
woodland,
3. temperate evergreen broadleaf
forest / woodland,
4: temperate evergreen conifer forest /
woodland,
5: temperate deciduous forest /
woodland,
6: boreal evergreen forest / woodland,
7: boreal deciduous forest / woodland,
8: mixed forest / woodland,
9: savanna, 10: grassland/ steppe, 11:
dense shrubland, 12: open shrubland,
13: tundra, 14: desert, 15. polar desert
/ rock / ice)
NPP distribution (kgC/m2/year) simulated by IBIS for baseline and A1B scenarios
Vulnerable grids (marked red) in the A1B scenario – for all
of India - 2035 (2035 and 2085)
Red indicates that a change in vegetation is projected at that grid in
the time-period of 2035 & 2085 - under A1B scenario
Green indicates that no change in vegetation is projected by that
period.
39% of the forest grids
likely change under A2
scenario by 2085
causing loss of C stock
and biodiversity
Source: Chaturvedi et al., 2011
1 = stable grids
2=forest grids
undergoing
change
PROJECTED IMPACT
OF CLIMATE
CHANGE ON
FORESTED GRIDS IN
INDIA A2 SCENARIO
Percentage of FSI grids projected to undergo change,
aggregated by the major forested states – A1B Scenario
State
Number of FSI
grids in the state
Rajasthan
802
Jammu & Kashmir
910
Chhattisgarh
Himachal Pradesh
3292
838
Andhra Pradesh
2288
Karnataka
1947
Tamil Nadu
776
Madhya Pradesh
4432
Maharashtra
2197
Uttaranchal
1203
Arunachal Pradesh
2666
Orissa
2564
Meghalaya
829
Assam
1261
Jharkhand
1148
% projected to
% projected to
change by 2035 change by 2085
61.22
78.18
57.03
88.35
48.00
75.85
47.49
65.39
39.20
51.57
38.37
62.20
27.45
47.04
22.59
48.17
21.21
45.33
19.04
31.92
12.27
6.90
9.71
13.53
7.96
0.00
5.23
1.11
0.00
24.30
Percentage of FSI grids projected to undergo change,
aggregated by Champion and Seth forest types – A!B
Forest type
(by Champion and Seth, 1968)
Tropical dry evergreen forest
Number of
FSI grids in
type
37
Subtropical dry evergreen forest
133
Himalayan dry temperate forest
106
Himalayan moist temperate forest
Subalpine and alpine forest
1144
400
Tropical thorn forest
1278
Tropical semi evergreen forest
1239
Littoral and swamp forest
Tropical dry deciduous forest
Tropical moist deciduous forest
Subtropical pine forest
Subtropical broad leaved hill forest
7
9663
11266
1662
192
Tropical wet evergreen forest
2862
Montane wet temperate forest
940
% projected to
change by 2035
70.27
54.14
52.83
52.62
49.75
41.39
30.67
28.57
25.62
22.63
20.64
15.10
14.61
5.64
% projected
to change by
2085
72.97
67.67
76.42
88.02
77.50
75.12
50.36
28.57
46.73
37.88
17.39
15.10
14.68
0.32
Vulnerability Index and Profile
Development
Vulnerability Assessment Indicators
1. Climate change impact
Indicators
2. Bio-physical Indicators
3. Socio-economic Indicators
Criteria & Indicators for Mitigation projects
• Disturbance index:
An indication of the human
disturbance for a particular forest patch. More the disturbance
index, higher the forest vulnerability.
• Fragmentation status: An indication of how fragmented
the forest patch is. More the fragmentation status, higher the
forest vulnerability.
• Biological richness: Indicates the species diversity of the
forest patch, a measure of the number of species of flora and
fauna, per unit area. Higher the biological richness, lower the
forest vulnerability
• Impact of climate change on carbon sinks of
forests: For estimating climate change impacts, IBIS, which is a
dynamic global vegetation model, was used.
Why Adaptation? When uncertainty in
Impact Assessment
• Impacts will be irreversible; e.g.,
– loss of biodiversity
• Inertia in response to changing climate
• Long gestation period in developing &
implementation of adaptation practices
• Waiting for full knowledge – high risk
• Large ecological, economic and social implications
Focus on “win – win” adaptation options
Greening India Mission (GIM)
The Mission aims at addressing climate change by
1. Enhancing carbon sinks in sustainably
managed forests and other ecosystems
2. Adaptation of vulnerable species /
ecosystems to changing climate
3. Enabling adaptation of forest-dependant
communities.
Key Issues in the context of Climate Change and
Forests
• Tropical deforestation continues at nearly 13 Mha annually
(2000-2010 – FAO)
• CO2 emissions are at 1.6 GtC with high uncertainty
• Cancun Agreement has included – REDD+; Need for
operation – complexity of measurement, reporting,
verification, financing, payment, role for local communities..
• CDM in forestry has failed due to methodological
complexities and risks of carbon loss
• Climate change is projected to impact forests
• Climate change + Degradation + poor management of
forests; increases vulnerability
• Need for forest and biodiversity conservation & also meet
the food needs of poor – land for food is a driver of
deforestation
Conclusions
1. India has reasonably succeeded in reducing
deforestation, but degradation continues
2. There are biodiversity rich hot spots and
there is a large dependence of communities
on forest biodiversity
3. Climate change even in the short and
medium term is likely to adversely impact
forest ecosystems
4. Thus India has initiated a large Greening
Indian Mission – to promote Mitigation and
Adaptation
Limitations of IBIS model
• IBIS is known to have limitations in characterizing
nitrogen dynamics (Cramer et al. 2001).
• It is known to over-simulate grasslands (Bonan et al.
2003)
• IBIS tends to simulate a fairly strong CO2 fertilization
effect (Cramer et al. 2001; McGuire et al. 2001).
• IBIS model in its current form does not include a dynamic
fire module (Foley et al. 1996).
• It does not account for changes in pest attack profile
THUS overestimation of future NPP and SOC.
• There is uncertainty in climate projections, particularly in
precipitation at down-scaled regional levels. Land-use
change and other anthropogenic influences are not
factored in this study. Afforestation and regeneration
(e.g. on abandoned croplands or wastelands) are also not
considered.