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 Periodic report of greenhouse gas emissions inventory from all sectors including land use sectors such as forests, grassland, wetlands, etc 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 Assess the vulnerability of natural ecosystems and socioeconomic systems to projected climate change Report the steps taken to address climate change (mitigation, adaptation) Report the steps taken to address climate change (mitigation, adaptation)
Forests & Climate Change Forests play a critical role in global carbon cycle Forests play a critical role in global carbon cycle Forests contribute about 20% of global CO 2 emissions Forests contribute about 20% of global CO 2 emissions Forest ecosystems are vulnerable to projected climate change 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 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 Mitigation through forest sector has been a contentious issue in climate negotiations
GHG Emissions from forest sector Global emissions of carbon = 7 GtC Global emissions of carbon = 7 GtC Emissions from LUCF = 1.6 to 1.7 GtC 1 Emissions from LUCF = 1.6 to 1.7 GtC 1 Tropical deforestation = 13 to 15 Mha annually Tropical deforestation = 13 to 15 Mha annually Land use change is the dominant factor in tropical countries Land use change is the dominant factor in tropical countries
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 forestsFig 2: C-flux estimates from Indian forests
GAPS IN C FLUX ESTIMATES GAPS IN C FLUX ESTIMATES 1. Estimation of CO 2 emissions are based on Different methods Different sources of data Different C –pools Different years Thus the estimates are not comparable Thus the estimates are not comparable Uncertainties are high Periodic spatial data, forest-type wise, lacking for flux estimates
1. 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. 2. C stock dynamics under different land use change systems is poorly understood.
MITIGATION POTENTIAL OF LULUCF SECTOR Projections for mitigation potential for the period 1995 to 2050 Brown et al. 1996, 1999; IPCC – 87 Gt C (cumulative) 1.09 – 1.58 Gt C (annual)
Climate change impact studies at IISc Evaluate and select models to assess climate impacts on forests Evaluate and select models to assess climate impacts on forests Regional Climate Model; Regional Climate Model; Vegetation Response Model; Vegetation Response Model; Assess impacts of climate change on forest ecosystems at national level Assess impacts of climate change on forest ecosystems at national level Assess impacts on biodiversity and socio- economic systems through case studies Assess impacts on biodiversity and socio- economic systems through case studies Analyze policy implications of climate impacts Analyze policy implications of climate impacts Strategies for future Strategies for future Research; modeling and database Research; modeling and database Adaptation strategies Adaptation strategies
Impact of Climate Change on Forest Ecosystems
SELECTION OF VEGETATION MODEL Equilibrium models: BIOME 3 Equilibrium models: BIOME 3 Dynamic model: HYBRID 4.2 Dynamic model: HYBRID 4.2 BIOME3 used due to input data limitations for the HYBRID Model BIOME3 used due to input data limitations for the HYBRID Model
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: mid period: 2085 Observed Climate data: CRU data set for from East Anglia (0.5x0.5 degree grid)
Projections of seasonal surface air temperature for the period , based on the regional climate model HadRM2. Source: IITM Pune Natcom
Projections of seasonal precipitation for the period , based on the regional climate model HadRM2. Projections of seasonal precipitation for the period , based on the regional climate model HadRM2. Source: IITM Pune Natcom
Potential impact on forest biomes (B-2 scenario)
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
SUMMARY OF IMPACTS Had RM3 Model outputs using SRES: A2 and B2 scenarios & BIOME3 show; 1. Over 85% of forest grids will undergo changes in forest type (similar trend using Had RM2) 2. 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 3. Large (potential) increase in Net primary productivity -70% (B2) to 100% (A2)
GAPS IN UNDERSTANDING CURRENT STATUS Large uncertainty in climate and vegetation response models; Large uncertainty in climate and vegetation response models; regional climate level regional climate level equilibrium vegetation model equilibrium vegetation model Inadequate or lack of data for the models Inadequate or lack of data for the models Adaptation not incorporated in impact models Adaptation not incorporated in impact models
Location of Mudumalai WLS Location of the Mudumalai 50 ha Forest Dynamics Plot
Detailed studies on the forest community Over individuals from 250+ species monitored
Topography of the Mudumalai plot
Recruitment and Mortality in the 50 ha plot
Dry season fire
Mortality due to various causes
Canopy trees: Average growth rates per size class during 3 intervals
Basal area changes (m 2 /ha) 1988 = = = = = 25.5 Basal area changes (m 2 /ha) 1988 = = = = = 25.5 Carbon stocks probably increased to a greater degree because of shift from lower wood density to higher wood density species
Flux programme should ideally complement “on the ground” studies on soils and vegetation Flux programme should ideally complement “on the ground” studies on soils and vegetation Spatial data on land use, landuse changes & forests (partly available) 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) 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) 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 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 Land use systems – NRSA, IRS, ISRO, SAC & FSI Land use systems – NRSA, IRS, ISRO, SAC & FSI Vegetation carbon flux - IISc, KFRI, ICFRE, NHU, BHU, etc Vegetation carbon flux - IISc, KFRI, ICFRE, NHU, BHU, etc Soil carbon flux – NBSSLUP, ICAR institutes, Agric. Univ Soil carbon flux – NBSSLUP, ICAR institutes, Agric. Univ Climate data – IITM, IISc, IMD Climate data – IITM, IISc, IMD Modeling of fluxes – IISc, IITM, IIT, Modeling of fluxes – IISc, IITM, IIT,
National Coordination National Coordination DST DST Dedicated institution?? Dedicated institution?? Regional lead institutions – Research area Regional lead institutions – Research area Networking of all institutions Networking of all institutions Funding Funding DST, MoEF, ICAR, ICFRE DST, MoEF, ICAR, ICFRE External funding External funding Linking with endusers such as – MoEF, ICAR, research institutions