1. Climate Change & Forests; Impacts & vulnerability Prof. Ravindranath Indian Institute of Science Bangalore

2. 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

3. Forests and climate change 1.Deforestation and land use change contribute to CO 2 emissions – IPCC; 20% of CO 2 emissions 2.Forests provide a large potential to mitigate climate change - IPCC; 15 – 20% of CO 2 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

4. Figure 1: Forest cover map of India of 2007 (FSI, 2009)

5. Trends in area under forest over the period 1987 to 2009 (according to FSI reports)

6. Cumulative area afforested during 1951 to 2005

7. 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

8. Impacts of Climate Change – IPCC findings Populations of threatened species are expected to become extinct – 1/3 to 2/3 rd 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

9. Projected Climate Change for India

10. 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

11. Projection of Impact of Climate Change on Forests

12. 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 km 2 ) In future other GCMs will be used

13. 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

14. 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)

15. NPP distribution (kgC/m 2 /year) simulated by IBIS for baseline and A1B scenarios

16. Vulnerable grids (marked red) in the A1B scenario – for all of India - 2035 (2035 and 2085)

17. 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.

18. PROJECTED IMPACT OF CLIMATE CHANGE ON FORESTED GRIDS IN INDIA A2 SCENARIO Source: Chaturvedi et al., 2011 39% of the forest grids likely change under A2 scenario by 2085 causing loss of C stock and biodiversity 1 = stable grids 2=forest grids undergoing change

19. State Number of FSI grids in the state % projected to change by 2035 % projected to change by 2085 Rajasthan802 61.22 78.18 Jammu & Kashmir910 57.03 88.35 Chhattisgarh3292 48.00 75.85 Himachal Pradesh838 47.49 65.39 Andhra Pradesh2288 39.20 51.57 Karnataka1947 38.37 62.20 Tamil Nadu776 27.45 47.04 Madhya Pradesh4432 22.59 48.17 Maharashtra2197 21.21 45.33 Uttaranchal1203 19.04 31.92 Arunachal Pradesh2666 12.27 6.90 Orissa2564 9.71 13.53 Meghalaya829 7.96 0.00 Assam1261 5.23 1.11 Jharkhand1148 0.00 24.30 Percentage of FSI grids projected to undergo change, aggregated by the major forested states – A1B Scenario

20. Forest type (by Champion and Seth, 1968) Number of FSI grids in type % projected to change by 2035 % projected to change by 2085 Tropical dry evergreen forest37 70.27 72.97 Subtropical dry evergreen forest133 54.14 67.67 Himalayan dry temperate forest106 52.83 76.42 Himalayan moist temperate forest1144 52.62 88.02 Subalpine and alpine forest400 49.75 77.50 Tropical thorn forest1278 41.39 75.12 Tropical semi evergreen forest1239 30.67 50.36 Littoral and swamp forest7 28.57 Tropical dry deciduous forest9663 25.62 46.73 Tropical moist deciduous forest11266 22.63 37.88 Subtropical pine forest1662 20.64 17.39 Subtropical broad leaved hill forest192 15.10 Tropical wet evergreen forest2862 14.61 14.68 Montane wet temperate forest940 5.64 0.32 Percentage of FSI grids projected to undergo change, aggregated by Champion and Seth forest types – A!B

21. Vulnerability Index and Profile Development

22. Vulnerability Assessment - Indicators 1.Climate change impact Indicators 2.Bio-physical Indicators 3.Socio-economic Indicators

23. 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.

24. 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

25. 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.

26. 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

27. 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

28. 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.