Climate change, land use and Climate change, land use and forests in India: research and forests in India: research and institutional framework in the institutional framework in the

context of the Indo-US flux context of the Indo-US flux programmeprogramme

R. Sukumar & N.H.RavindranathR. Sukumar & N.H.RavindranathCentre for Ecological SciencesCentre for Ecological Sciences

Indian Institute of ScienceIndian Institute of ScienceBangaloreBangalore

Obligations under UNFCCCObligations under UNFCCC

Periodic report of greenhouse gas Periodic report of greenhouse gas emissions inventory from all sectors emissions inventory from all sectors including land use sectors such as forests, including land use sectors such as forests, grassland, wetlands, etcgrassland, wetlands, etc

Assess the vulnerability of natural Assess the vulnerability of natural ecosystems and socioeconomic systems to ecosystems and socioeconomic systems to projected climate changeprojected climate change

Report the steps taken to address climate Report the steps taken to address climate change (mitigation, adaptation)change (mitigation, adaptation)

Forests & Climate ChangeForests & Climate Change Forests play a critical role in global carbon cycleForests play a critical role in global carbon cycle Forests contribute about 20% of global COForests contribute about 20% of global CO22 emissionsemissions Forest ecosystems are vulnerable to projected Forest ecosystems are vulnerable to projected

climate changeclimate change Likely to have adverse impacts on forest biodiversity Likely to have adverse impacts on forest biodiversity

and biomass productionand biomass production Thus need to assess impacts and develop adaptation Thus need to assess impacts and develop adaptation

strategiesstrategies Forests provide mitigation opportunity to Forests provide mitigation opportunity to

stabilize GHG concentration in the atmosphere, stabilize GHG concentration in the atmosphere, along with significant co-benefitsalong with significant co-benefits

Mitigation through forest sector has been a Mitigation through forest sector has been a contentious issue in climate negotiationscontentious issue in climate negotiations

GHG Emissions from forest GHG Emissions from forest sectorsector

Global emissions of carbon = 7 GtCGlobal emissions of carbon = 7 GtC Emissions from LUCF = 1.6 to 1.7 GtC Emissions from LUCF = 1.6 to 1.7 GtC 1 1 Tropical deforestation = 13 to 15 Mha Tropical deforestation = 13 to 15 Mha

annuallyannually Land use change is the dominant factor in Land use change is the dominant factor in

tropical countriestropical countries

ESTIMATES OF STOCKS AND FLUXES ESTIMATES OF STOCKS AND FLUXES FROM INDIAN FORESTSFROM INDIAN FORESTS

0

2000

4000

6000

8000

10000

12000

1880

1980

1986

1986

1994

2005

Carb

on s

tock

(MtC

)

Biomass carbon Soil carbon

(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)

Estimates of fluxes from Indian Forests

-20

-15

-10

-5

0

5

10

1986 1986 1990 1994 1994

Flux

es in

Mill

ion

tonn

esFig 1: Estimates of C-stock from Indian forests Fig 2: C-flux estimates from Indian forests

GAPS IN C FLUX ESTIMATESGAPS IN C FLUX ESTIMATES

1.1. Estimation of COEstimation of CO22 emissions are based on emissions are based on Different methods Different methods Different sources of dataDifferent sources of data Different C –poolsDifferent C –pools Different years Different years

Thus the estimates are not comparableThus the estimates are not comparableUncertainties are highUncertainties are highPeriodic spatial data, forest-type wise, Periodic spatial data, forest-type wise,

lacking for flux estimateslacking for flux estimates

1.1. C - Inventory process requires information C - Inventory process requires information pertaining to activity data (i.e. land area pertaining to activity data (i.e. land area change statistics) and impact of land use change statistics) and impact of land use change on the C stock dynamics.change on the C stock dynamics.

2.2. C stock dynamics under different land use C stock dynamics under different land use change systems is poorly understood.change systems is poorly understood.

MITIGATION POTENTIAL OF LULUCF MITIGATION POTENTIAL OF LULUCF SECTORSECTOR

17.0%

80.1%

BOREAL

TEMPERATE

TROPICAL

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 IIScClimate change impact studies at IISc Evaluate and select models to assess climate Evaluate and select models to assess climate

impacts on forestsimpacts on forests Regional Climate Model; Regional Climate Model; Vegetation Response Model; Vegetation Response Model;

Assess impacts of climate change on forest Assess impacts of climate change on forest ecosystems at national levelecosystems at national level

Assess impacts on biodiversity and socio-Assess impacts on biodiversity and socio-economic systems through case studieseconomic systems through case studies

Analyze policy implications of climate impactsAnalyze policy implications of climate impacts Strategies for futureStrategies for future

Research; modeling and databaseResearch; modeling and database Adaptation strategiesAdaptation strategies

Impact of Climate Change Impact of Climate Change on Forest Ecosystemson Forest Ecosystems

SELECTION OF VEGETATION SELECTION OF VEGETATION MODELMODEL

Equilibrium models: BIOME 3Equilibrium models: BIOME 3

Dynamic model: HYBRID 4.2Dynamic model: HYBRID 4.2

BIOME3 used due to input data BIOME3 used due to input data limitations for the HYBRID Modellimitations for the HYBRID Model

CLIMATE DATA FOR BIOMESCLIMATE DATA FOR BIOMESModel used:Model used: Hadley Centre Regional Model; Had RM3 Hadley Centre Regional Model; Had RM3

Mean monthly temp. & rainfall, cloud coverMean monthly temp. & rainfall, cloud coverScale:Scale: 0.44 x 0.44 degree RCM grid 0.44 x 0.44 degree RCM grid

Scenarios:Scenarios: SRES; A2 and B2 SRES; A2 and B2

Period:Period: 2071-2100 mid period: 20852071-2100 mid period: 2085

Observed Climate data:Observed Climate data: CRU data set for 1901-1995 CRU data set for 1901-1995 from East Anglia (0.5x0.5 degree grid)from East Anglia (0.5x0.5 degree grid)

Projections of seasonal surface air Projections of seasonal surface air temperature for the period 2041-60, based temperature for the period 2041-60, based

on the regional climate model HadRM2.on the regional climate model HadRM2.

Source:

IITM Pune

Natcom

Projections of seasonal precipitation for Projections of seasonal precipitation for the period 2041-60, based on the regional the period 2041-60, based on the regional

climate model HadRM2.climate model HadRM2.  

Source:

IITM Pune

Natcom

Potential impact on forest biomes (B-2 scenario)

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

0

20

40

60

80

100

120 W

este

rn G

hat s

emi-e

verg

reen

Wes

tern

Gha

t eve

rgre

en fo

rest

Man

grov

e

Spr

uce

Kha

ir fo

rest

Deo

dar

Har

dwoo

ds C

onif

ers

mix

Dec

iduo

us fo

rest

Sal

ai fo

rest

Mix

ed c

onif

er

Blu

e-Pi

ne(K

ail)

Fir

SCR

UB

Mis

cella

neou

s for

est

Up-

land

Har

dwoo

ds

Chi

r-pi

ne

Tea

k

Sal

Fir-

Spru

ce

Bam

boo

Fore

st

Kha

si pi

ne

Dep

tero

carp

us (G

urja

n) H

ollo

ng

% g

rids

unde

rgoi

ng c

hang

e

A2 B2

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

0 500 1000 1500 2000 2500 3000

NPP Present NPP A2GHG NPP B2GHG

SUMMARY OF IMPACTSSUMMARY OF IMPACTSHad RM3 Model outputs using SRES: A2 and Had RM3 Model outputs using SRES: A2 and

B2 scenarios & BIOME3 show;B2 scenarios & BIOME3 show;1.1. Over 85% of forest grids will undergo Over 85% of forest grids will undergo

changes in forest type (similar trend changes in forest type (similar trend using Had RM2)using Had RM2)

2.2. Regional assessment shows;Regional assessment shows;- Higher impact on Savanna biomes, Teak and Higher impact on Savanna biomes, Teak and

Sal forests of central and east, temperate Sal forests of central and east, temperate biomes of Himalayasbiomes of Himalayas

- Lower impact on Western ghats and North-Lower impact on Western ghats and North-east; Evergreen biomeseast; Evergreen biomes

3.3. Large (potential) increase in Net primary Large (potential) increase in Net primary productivityproductivity

-- 70% (B2) to 100% (A2)70% (B2) to 100% (A2)

GAPS IN UNDERSTANDINGGAPS IN UNDERSTANDINGCURRENT STATUSCURRENT STATUS Large uncertainty in climate and Large uncertainty in climate and

vegetation response models; vegetation response models; regional climate levelregional climate level equilibrium vegetation modelequilibrium vegetation model

Inadequate or lack of data for the Inadequate or lack of data for the models models

Adaptation not incorporated in impact Adaptation not incorporated in impact modelsmodels

Location of Mudumalai WLSLocation of Mudumalai WLS

Location of the Mudumalai 50 ha Forest Dynamics Plot

Detailed studies on the forest communityOver 50000 individuals from 250+ species monitored

Topography of the Mudumalai Topography of the Mudumalai plotplot

Recruitment and Mortality in the 50 ha Recruitment and Mortality in the 50 ha plotplot

0

2

4

6

8

10

12

14

16

18

Year

% In

divi

dual

s

% Mortality

% Recruitment

Dry season fire

Mortality due to various causesMortality due to various causes

0

2

4

6

8

10

12

14

16

18

Year

Mor

talit

y ra

te (%

) MortFire

MortEle

MortOthers

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

0 20 40 60 80 100 120

-20

24

68

10

Dbh (cm)

Ave

rage

gro

wth

(mm

/yr)

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

1988-19921992-19961996-2000

Basal area changes (m2 /ha)

1988 = 24.4

1992 = 24.8

1996 = 24.7

2000 = 25.9

2004 = 25.5

Carbon stocks probablyincreased to a greater degree becauseof shift from lower wood density tohigher wood density species

Flux programme should ideally complement “on Flux programme should ideally complement “on the ground” studies on soils and vegetationthe ground” studies on soils and vegetation

Spatial data on land use, landuse changes & Spatial data on land use, landuse changes &

forests (partly available)forests (partly available) Data on carbon stocks and fluxes under different Data on carbon stocks and fluxes under different

land use and landuse change systems (lacking)land use and landuse change systems (lacking) Spatial data on soil, water and plant physiological Spatial data on soil, water and plant physiological

functions (limited availability)functions (limited availability)

Flux programme should thus network with Flux programme should thus network with institutions in order to extract maximum scientific institutions in order to extract maximum scientific understanding of C dynamics from the soil, understanding of C dynamics from the soil, through vegetation to the atmospherethrough vegetation to the atmosphere

SCIENTIFIC DATA NEEDS FOR CLIMATE CHANGESCIENTIFIC DATA NEEDS FOR CLIMATE CHANGEAND LANDUSE AND LANDUSE CHANGE RESEARCHAND LANDUSE AND LANDUSE CHANGE RESEARCH

Networking on InstitutionsNetworking on Institutions Land use systems – NRSA, IRS, ISRO, Land use systems – NRSA, IRS, ISRO,

SAC & FSISAC & FSI Vegetation carbon flux - IISc, KFRI, Vegetation carbon flux - IISc, KFRI,

ICFRE, NHU, BHU, etcICFRE, NHU, BHU, etc Soil carbon flux – NBSSLUP, ICAR Soil carbon flux – NBSSLUP, ICAR

institutes, Agric. Univinstitutes, Agric. Univ Climate data – IITM, IISc, IMDClimate data – IITM, IISc, IMD Modeling of fluxes – IISc, IITM, IIT, Modeling of fluxes – IISc, IITM, IIT,

National Coordination National Coordination DSTDST Dedicated institution?? Dedicated institution??

Regional lead institutions – Research areaRegional lead institutions – Research area Networking of all institutions Networking of all institutions Funding Funding

DST, MoEF, ICAR, ICFREDST, MoEF, ICAR, ICFRE External fundingExternal fundingLinking with endusers such as – MoEF, ICAR, Linking with endusers such as – MoEF, ICAR,

research institutionsresearch institutions