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Impact of climate Change on forest ecosystems in India

Impact of climate Change on forest ecosystems in India. Rajiv Kumar Chaturvedi National Environmental Sciences Fellow Indian Institute of Science Bangalore. CLIMATE CHANGE AND FOREST SECTOR. Forests are a critical sector for climate change science and policy.

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Impact of climate Change on forest ecosystems in India

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  1. Impact of climate Change on forest ecosystems in India Rajiv Kumar Chaturvedi National Environmental Sciences Fellow Indian Institute of Science Bangalore

  2. CLIMATE CHANGE AND FOREST SECTOR Forests are a critical sector for climate change science and policy. 1. Source to CO2 emissions contributing to Global warming and Climate Change - In 2008 forests contributed to 12% of the global GHG emissions (Le Quere et al. 2009) 2. A sink to CO2,leading to mitigation of Climate Change - Globally LULUCF sector is estimated to have a mitigation potential of 13.8 GtCO2e/yr by 2030 at carbon prices less than or equal to US$/tCO2e (Nabuurs et al. 2007) 3. Vulnerable to the impacts of Climate Change - Most DGVMs (dynamic global vegetation models) show significant forest dieback towards the end of this century in tropical, boreal and mountain areas (Fischlin et al. (2007)

  3. STATE OF INDIAN FORESTS Source: Forest survey of India Source: Champion & Seth, 1960

  4. MAN-MADE DISTURBANCE AND FOREST FRAGMENTATION

  5. How does the projected climate change impact Indian forests? • Changes Net Primary productivity • Changes biomass and soil carbon, and • Changes vegetation distribution patterns

  6. INPUT REQUIREMENTS FOR IBIS IBIS is forced with SRES – HadRM3 data for A2 and B2 scenarios

  7. MODEL VALIDATION – VEG TYPE CHANGE 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 1.Tropical wet evergreen forests,2.Tropical semi evergreen forests, 3.Tropical moist decidious forest, 4.Tropical dry decidious 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 Chaturvedi et al. 2011

  8. MODEL VALIDATION - NPP R2= 0.63 Chaturvedi et al. 2011 Model generated current NPP (kgC/m2) compared with the remote-sensing-derived mean NPP data from 1982 to 2006

  9. MODEL VALIDATION - SOC We find that mean from both the sources is approximately 5 kg/m2 over all of India (mean of IBIS = 4.98 Kg/m2 & mean of IGBP = 4.7 Kg/m2). However, interestingly enough we find IBIS simulated outputs to be more divergent (standard deviation = 4.27; Max = 20.83; Min = 0.13) than IGBP estimates (Standard deviation = 1.33; Max = 11; Min = 1.8). Chaturvedi et al. 2011

  10. MODEL VALIDATION - SOC Forested sites were found to have higher soil organic carbon with an average of 97 tonnes /ha compared (with a standard deviation of 19.8 tC/ha) to Non-forested patches with an average of 64 tonnes/ ha (with a standard deviation of 27.2 tC/ha). The average Soil Organic Carbon in the region was found to be 78.15 tonnes C/ha (S.D =29.2) as compared to 89.13 tonnes C/ha as predicted IBIS for that particular grid. Chaturvedi et al. 2011

  11. IMPACT OF CLIMATE CHANGE ON NPP Chaturvedi et al., 2011 The effect of climate change on the NPP of forested grids, by 2085 under A2 scenario. The values shown are the percentage change of NPP, compared to the baseline year.

  12. IMPACT OF CC ON SOIL ORGANIC CARBON Chaturvedi et al., 2011 The effect of climate change on the SOC of forested grids, by 2085 under A2 scenario. The values shown are the percentage change of SOC, compared to the baseline year

  13. LIMITATIONS OF THIS ASSESSMENT Single DGVM Single Climate Model and Single Scenario Climate Projections based on SRES scenarios Lack of species Level Assessment Forests, agriculture, and water resources are intrinsically linked at the landscape level, there is a lack of integrated assessment Lack of landscape/district/watershed level vulnerability Assessment In sufficient representation of Nitrogen Cycle, Fire/ Pest dynamics in the DGVMs

  14. Validation of LPJ model for India

  15. TrBE- Tropical broadleaved evergreen TeNE- Temperate needleleaved evergreen TrBR- Tropical broadleaved raingreen TeBE- Temperate broadleaved evergreen TeBS- Temperate broadleaved summergreen Kappa (3) 0.4261

  16. MULTI-MODEL CLIMATE CHANGE PROJECTIONS FOR INDIA Baseline = 1961-1990 Current Science, 2012

  17. NPP PROJECTIONS AS SIMULATED BY LPJ AND AS PROVIDED BY CMIP5 ESMS

  18. HETEROTROPHIC RESPIRATION AS SIMULATED BY LPJ AND AS PROVIDED BY CMIP5 ESMS

  19. NEP AS SIMULATED BY LPJ AND AS PROVIDED BY CMIP5 ESMS GPP- autotrophic respiration = NPP NPP- Heterotrophic respiration = NEP

  20. OBSERVATIONS: INCREASING ‘NET PRIMARY PRODUCTIVITY’ OVER THE INDIAN REGION? Journal ‘Remote Sensing’, 2013

  21. IMPACT OF CLIMATE CHANGE ON VEGETATION DISTRIBUTION IN INDIA

  22. 1 = stable grids 2=forest grids undergoing change Chaturvedi et al., 2011

  23. MAN-MADE DISTURBANCE AND FOREST FRAGMENTATION

  24. FOREST VULNERABILITY TO CLIMATE CHANGE, ARISES DUE TO HUMAN FACTORS OF DEFORESTATION, FOREST DEGRADATION AND FOREST FRAGMENTATION – WHICH INHIBITS THE VEGETATION'S ABILITY TO DISPERSE, POLLINATE AND MIGRATE

  25. Forested grids are vulnerable to multiple stresses including CC FOREST VULNERABILITY INDEX Chaturvedi et al., 2011

  26. LIMITATIONS OF IMPACT ASSESSMENT STUDIES IN INDIA • Lack of observational data, also observed impacts of CC not well quantified for different natural and production systems • Lack of climate data downscaling for local level applications • Uncertainty in the precipitation projections remains largely unaddressed • Overall uncertainty in the climate change impact projections are NOT quantified due to use of a single climate model, single scenario and single impact assessment model • Most of the impact assessment is based on mean climate, whereas it is the extreme climate that causes the maximum damage • Modelling and projections of extreme precipitation events remains a challenge • Most of our impact assessment models are coming from either Europe/US and these are tailor-made for these regions, and NOT for India

  27. Thanks

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