Climate change, land use and forests in India: research and institutional framework in the context of the Indo-US flux programme : Climate change, land use and forests in India: research and institutional framework in the context of the Indo-US flux programme Extracted from the government of India source
Obligations under UNFCCC : Obligations under UNFCCC Periodic report of greenhouse gas emissions inventory from all sectors including land use sectors such as forests, grassland, wetlands, etc
Assess the vulnerability of natural ecosystems and socioeconomic systems to projected climate change
Report the steps taken to address climate change (mitigation, adaptation)
Forests & Climate Change : Forests & Climate Change Forests play a critical role in global carbon cycle
Forests contribute about 20% of global CO2 emissions
Forest ecosystems are vulnerable to projected climate change
Likely to have adverse impacts on forest biodiversity and biomass production
Thus need to assess impacts and develop adaptation strategies
Forests provide mitigation opportunity to stabilize GHG concentration in the atmosphere, along with significant co-benefits
Mitigation through forest sector has been a contentious issue in climate negotiations
GHG Emissions from forest sector : GHG Emissions from forest sector Global emissions of carbon = 7 GtC
Emissions from LUCF = 1.6 to 1.7 GtC 1
Tropical deforestation = 13 to 15 Mha annually
Land use change is the dominant factor in tropical countries
ESTIMATES OF STOCKS AND FLUXES FROM INDIAN FORESTS : ESTIMATES OF STOCKS AND FLUXES FROM INDIAN FORESTS (Sources:
1880: Richard and Flint, 1994;
1980-Richard and Flint, 1994;
1986:Ravindranath et al., 1997;
1986:Chhabra and Dadhwal, 2004;
1994:Haripriya, 2003; 2005:FAO, 2005) (Sources:
1986-Ravindranath et al., 1997;
1986:Chhabra and Dadhwal, 2004;
1990 – ALGAS (ADB)., 1999;
1994:Haripriya, 2003;
1994: NATCOM, 2004) Fig 1: Estimates of C-stock from Indian forests Fig 2: C-flux estimates from Indian forests
GAPS IN C FLUX ESTIMATES : GAPS IN C FLUX ESTIMATES Estimation of CO2 emissions are based on
Different methods
Different sources of data
Different C –pools
Different years
Thus the estimates are not comparable
Uncertainties are high
Periodic spatial data, forest-type wise, lacking for flux estimates
Slide 7 : C - Inventory process requires information pertaining to activity data (i.e. land area change statistics) and impact of land use change on the C stock dynamics.
C stock dynamics under different land use change systems is poorly understood.
MITIGATION POTENTIAL OF LULUCF SECTOR : MITIGATION POTENTIAL OF LULUCF SECTOR Projections for mitigation potential for the period 1995 to 2050 Brown et al. 1996, 1999; IPCC 2001 60 – 87 Gt C (cumulative) 1.09 – 1.58 Gt C (annual)
Climate change impact studies at IISc : Climate change impact studies at IISc Evaluate and select models to assess climate impacts on forests
Regional Climate Model;
Vegetation Response Model;
Assess impacts of climate change on forest ecosystems at national level
Assess impacts on biodiversity and socio-economic systems through case studies
Analyze policy implications of climate impacts
Strategies for future
Research; modeling and database
Adaptation strategies
Impact of Climate Change on Forest Ecosystems : Impact of Climate Change on Forest Ecosystems
SELECTION OF VEGETATION MODEL : SELECTION OF VEGETATION MODEL Equilibrium models: BIOME 3
Dynamic model: HYBRID 4.2
BIOME3 used due to input data limitations for the HYBRID Model
CLIMATE DATA FOR BIOMES : CLIMATE DATA FOR BIOMES Model used: Hadley Centre Regional Model; Had RM3
Mean monthly temp. & rainfall, cloud cover
Scale: 0.44 x 0.44 degree RCM grid
Scenarios: SRES; A2 and B2
Period: 2071-2100 mid period: 2085
Observed Climate data: CRU data set for 1901-1995 from East Anglia (0.5x0.5 degree grid)
Projections of seasonal surface air temperature for the period 2041-60, based on the regional climate model HadRM2. : Projections of seasonal surface air temperature for the period 2041-60, based on the regional climate model HadRM2. Source:
IITM Pune
Natcom
Projections of seasonal precipitation for the period 2041-60, based on the regional climate model HadRM2. : Projections of seasonal precipitation for the period 2041-60, based on the regional climate model HadRM2. Source:
IITM Pune
Natcom
Slide 15 : Potential impact on forest biomes
(B-2 scenario)
Percentage of grids under different forest types undergoing change in A2 and B2 GHG scenarios : Percentage of grids under different forest types undergoing change in A2 and B2 GHG scenarios
Climate impacts on NPP; % Forest biome-RCM grids subjected to change in NPP under GHG scenario over the current scenario under B2 Scenario : Climate impacts on NPP; % Forest biome-RCM grids subjected to change in NPP under GHG scenario over the current scenario under B2 Scenario
SUMMARY OF IMPACTS : SUMMARY OF IMPACTS Had RM3 Model outputs using SRES: A2 and B2 scenarios & BIOME3 show;
Over 85% of forest grids will undergo changes in forest type (similar trend using Had RM2)
Regional assessment shows;
Higher impact on Savanna biomes, Teak and Sal forests of central and east, temperate biomes of Himalayas
Lower impact on Western ghats and North-east; Evergreen biomes
Large (potential) increase in Net primary productivity
- 70% (B2) to 100% (A2)
GAPS IN UNDERSTANDING : GAPS IN UNDERSTANDING CURRENT STATUS
Large uncertainty in climate and vegetation response models;
regional climate level
equilibrium vegetation model
Inadequate or lack of data for the models
Adaptation not incorporated in impact models
Location of Mudumalai WLS : Location of Mudumalai WLS Location of the Mudumalai 50 ha Forest Dynamics Plot
Slide 21 : Detailed studies on the forest community
Over 50000 individuals from 250+ species monitored
Topography of the Mudumalai plot : Topography of the Mudumalai plot
Slide 23 :
Recruitment and Mortality in the 50 ha plot : Recruitment and Mortality in the 50 ha plot
Slide 25 : Dry season fire
Mortality due to various causes : Mortality due to various causes
Canopy trees: Average growth rates per size class during 3 intervals : Canopy trees: Average growth rates per size class during 3 intervals
Slide 28 : Basal area changes (m2 /ha)
1988 = 24.4
1992 = 24.8
1996 = 24.7
2000 = 25.9
2004 = 25.5 Carbon stocks probably
increased to a greater degree because
of shift from lower wood density to
higher wood density species
Slide 29 : Flux programme should ideally complement “on the ground” studies on soils and vegetation
Spatial data on land use, landuse changes & forests (partly available)
Data on carbon stocks and fluxes under different land use and landuse change systems (lacking)
Spatial data on soil, water and plant physiological functions (limited availability)
Flux programme should thus network with institutions in order to extract maximum scientific understanding of C dynamics from the soil, through vegetation to the atmosphere SCIENTIFIC DATA NEEDS FOR CLIMATE CHANGE
AND LANDUSE AND LANDUSE CHANGE RESEARCH
Networking on Institutions : Networking on Institutions Land use systems – NRSA, IRS, ISRO, SAC & FSI
Vegetation carbon flux - IISc, KFRI, ICFRE, NHU, BHU, etc
Soil carbon flux – NBSSLUP, ICAR institutes, Agric. Univ
Climate data – IITM, IISc, IMD
Modeling of fluxes – IISc, IITM, IIT,
Continued from the previous slide : Continued from the previous slide National Coordination
DST
Dedicated institution??
Regional lead institutions – Research area
Networking of all institutions
Funding
DST, MoEF, ICAR, ICFRE
External funding
Linking with endusers such as – MoEF, ICAR, research institutions