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Climate change, land use and forests in India: research and institutional framework in the context of the Indo-US flux p

Climate change, land use and forests in India: research and institutional framework in the context of the Indo-US flux programme. R. Sukumar & N.H.Ravindranath Centre for Ecological Sciences Indian Institute of Science Bangalore. Obligations under UNFCCC.

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Climate change, land use and forests in India: research and institutional framework in the context of the Indo-US flux p

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  1. Climate change, land use and forests in India: research and institutional framework in the context of the Indo-US flux programme R. Sukumar & N.H.Ravindranath Centre for Ecological Sciences Indian Institute of Science Bangalore

  2. 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)

  3. 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

  4. 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

  5. ESTIMATES OF STOCKS AND FLUXES FROM INDIAN FORESTS Fig 1: Estimates of C-stock from Indian forests Fig 2: C-flux estimates 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)

  6. 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

  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.

  8. MITIGATION POTENTIAL OF LULUCF SECTOR 60 – 87 Gt C (cumulative) 1.09 – 1.58 Gt C (annual) Projections for mitigation potential for the period 1995 to 2050 Brown et al. 1996, 1999; IPCC 2001

  9. 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

  10. Impact of Climate Change on Forest Ecosystems

  11. SELECTION OF VEGETATION MODEL • Equilibrium models: BIOME 3 • Dynamic model: HYBRID 4.2 • BIOME3 used due to input data limitations for the HYBRID Model

  12. 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)

  13. Projections of seasonal surface air temperature for the period 2041-60, based on the regional climate model HadRM2. Source: IITM Pune Natcom

  14. Projections of seasonal precipitation for the period 2041-60, based on the regional climate model HadRM2. Source: IITM Pune Natcom

  15. Potential impact on forest biomes (B-2 scenario)

  16. Percentage of grids under different forest types undergoing change in A2 and B2 GHG scenarios

  17. Climate impacts on NPP; % Forest biome-RCM grids subjected to change in NPP under GHG scenario over the current scenario under B2 Scenario

  18. 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)

  19. 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

  20. Location of the Mudumalai 50 ha Forest Dynamics Plot Location of Mudumalai WLS

  21. Detailed studies on the forest community Over 50000 individuals from 250+ species monitored

  22. Topography of the Mudumalai plot

  23. Recruitment and Mortality in the 50 ha plot

  24. Dry season fire

  25. Mortality due to various causes

  26. Canopy trees: Average growth rates per size class during 3 intervals

  27. 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

  28. SCIENTIFIC DATA NEEDS FOR CLIMATE CHANGE AND LANDUSE AND LANDUSE CHANGE RESEARCH • 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

  29. 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,

  30. 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

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