Estimates of Carbon Stock of India s forests

Transcription

1 Estimates of Carbon Stock of India s forests GOFC-GOLD Symposium April 2013 Wageningen University, Netherlands Devendra PANDEY Consultant/ Fmr DG, Forest Survey of India ID: dpandeyifs@rediffmail.com; pandeyd30@gmail.com

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3 Methodology for estimating carbon stock India estimates forest carbon stocks as a compliance to National Communication for UNFCCC following IPCC guidelines 1 st time in 2004 only of woody biomass using old NFI data & forest cover assessed by remote sensing. 2 nd time in input -recent NFI data for woody biomass & SOM -supplementary inventory data of for carbon in other pools -forest cover assessment more refined - forest type overlay on forest cover 2 nd Carbon estimation IPCC Tier 2 approach 3

4 Forest Cover Mapping in India using satellite imagery over the years Cycle Year of Assessment Satellite & Sensor Resolution Scale I 1987 LANDSAT MSS 80m x 80m 1:1million II 1989 III 1991 LANDSAT TM 30m x 30m IV 1993 V 1995 IRS-1B LISS-II 36m x 36m 1:250,000 VI 1997 VII 1999 IRS-1C LISS-III 23m x 23m VIII 2001 IRS-1C/1D LISS-III 23m x 23m 1:50,000 IX/X 2003/2005 IRS-1D, LISS-III 23m x 23m 1:50,000 XI/XII 2007/2009 IRS-P6, LISS-III 23m x 23m 1:50,000

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8 Methodology of Growing Stock National Forest Inventory The country has been stratified into 14 physiographic zones- based on climate, vegetation, physiography Ten percent (60) districts are selected and inventoried in a two years period. India has about 600 civil districts. The selection of districts is random from each physiographic zone with probability proportion to size. Topographic sheets of 1:50,000 scale forms the base map for the inventory. Along with the Forest inventory, vegetation survey of herbs and shrubs is also carried out. Measurement of soil and litter carbon is also carried. 8

9 National Forest Inventory - Methodology -contd Randomly Selected 60 districts 9

10 Sample Plots In a District Inventory of 179 districts (total no. of districts 612) No.Sample plots = 21,000

11 Supplementary Study of FSI launched a new biomass study in August 2008 to measure missing components of forest biomass (not measured by NFI) as per REDD requirement The study has followed two approaches (a) measure biomass of herb, shrub, climber, dead wood and litter by laying out sample plots (about 100 plots in each physiographic zone thus in all 1,400 sample plots) (b) select 20 to 30 number of trees for each species in different zones cut and measure their biomass to generate biomass equations for: i) Dbh of NFI trees Vs. biomass of branch for trees above 10 cm dbh. ii) dbh/collar dia Vs. total biomass of trees below 10 cm dbh.

12 Outcome of supplementary Study Based on the data collected in the supplementary study FSI has developed new allometric equations about 200 new regressions equations for small sized trees/ seedlings for different species below 10 cm diameter growing in to estimate their biomass Similarly new equations have been developed to biomass of branch wood and leaf of trees above 10 cm diameter measured during regular NFI 12

13 An example- Biomass allometric equations of a few species Species Name Eqn Descri Equation R 2 1 Careya arborea small wood->10cmdbh y = 460.4x x Careya arborea foliage->10cmdbh y = 15.21x x Careya arborea small wood-<10cmdbh y = 0.108x x Careya arborea foliage-<10cmdbh y = x x Schima wallichii small wood->10cmdbh y = 1319.x x Schima wallichii foliage->10cmdbh y = 57.1x x Schima wallichii small wood-<10cmdbh y = 0.127x x Schima wallichii foliage-<10cmdbh y = 0.006x x Shorea robusta small wood->10cmdbh y = 111.8x Shorea robusta foliage->10cmdbh y = 31.40x Shorea robusta small wood-<10cmdbh y = 0.093x x Shorea robusta foliage-<10cmdbh y = 0.019x x Tectona grandis small wood->10cmdbh y = 302.2x Tectona grandis foliage->10cmdbh y = 10.72x Tectona grandis small wood-<10cmdbh y = 0.177x x Tectona grandis foliage-<10cmdbh y = 0.009x x

14 2-Eastern Himalayas S. No. Species Name Eqn Descri Equation R2 1 Alnus nepalensis small wood-<10cmdbh y = 0.178x x Alnus nepalensis foliage-<10cmdbh y = 0.008x x Eurya japonica small wood-<10cmdbh y = 0.101x x Eurya japonica foliage-<10cmdbh y = x x Ficus species small wood-<10cmdbh y = 0.145x x Ficus species foliage-<10cmdbh y = 0.012x x Macaranga species small wood-<10cmdbh y = 0.127x x Macaranga species foliage-<10cmdbh y = 0.002x x Machilus species small wood->10cmdbh y = 16.99ln(x) Machilus species foliage->10cmdbh y = 1.421ln(x) Machilus species small wood-<10cmdbh y = x x x Machilus species foliage-<10cmdbh y = 0.007x x Michelia species small wood-<10cmdbh y = 0.169x x Michelia species foliage-<10cmdbh y = x x Quercus species small wood->10cmdbh y = 132.5x x Quercus species foliage->10cmdbh y = 6.755x x Quercus species small wood-<10cmdbh y = 0.137x x Quercus species foliage-<10cmdbh y = 0.003x x Rhododendron arboreum small wood->10cmdbh y = x x Rhododendron arboreum foliage->10cmdbh y = 9.354ln(x) Rhododendron arboreum small wood-<10cmdbh y = 0.119x x Rhododendron 2 14

15 Change in carbon stock in forest land between 1994 & 2004 ( required for 2 nd National Communication) Component Carbon Stock in forest land in 1994 Carbon stock in forest land in 2004 Net change in Carbon stock Above Ground Biomass Below Ground Biomass Dead wood Litter Soil Total # #The change is mainly on account of change in forest area. 16

16 National average of carbon in India s forest t/ha Carbon stock in tone/ha in different pools ABG, SOM, BGB, 9.79 Litter, 1.79 DW,

17 Carbon stock in t/ha in different forest types Tr Wet Evergreen Tr Semi Evergreen Tr Dry/moist Decidous Littoral & swamp Tr Thorn Sub-tropical pine/broadleave Montane Temperate 18

18 Carbon-stock in t/ha in different pools by major forest types Forest types ABG BGB DW Litter SOM Total C Tropical Wet Evergreen Tropical Semi Evergreen Tropical Dry/moist Deciduous Littoral & swamp Tropical Thorn Sub-tropical pine/broadleave Montane Temperate

19 Highest carbon density in some areas of India s forests Montane temperate very dense( Himachal Pradesh Jammu &Kashmir, Sikkim) =268 t/ha (four pools = 169 t/ha, SOM= 99t/ha) Tropical wet evergreen very dense (Andaman & Nicobar, Kerala, Tamilnadu, Karnataka) =200 t/ha (four pools = 106 t/ha, SOM=94 t/ha) 20

20 Global Overview of C-Stock in forests (source: FAO, FRA 2010 of 233 Countries /territories)- reliability level 180 countries reported on carbon in tree/woody biomass 72 countries included deadwood and 124 countries litter mostly default values (2.1 t/ha) 121 countries reported on soil carbon mostly the default values as provided in the IPCC 2006 guidelines. For filling the gaps for remaining countries and areas, FAO estimated carbon stocks by taking the sub-regional averages per hectare and multiplying these by the respective forest areas. 21

21 Global Overview of C-Stock in forests (source: FAO, FRA 2010) Total C- stock in forest ecosystem = 652 billion tones C-stock in total biomass (all four pools) =360 billion tones C- stock in soil =292 billion tones C- stock per ha forest ecosystem C- stock per ha in biomass C- stock per ha in soil =162 tones = 90 tones =72 tones 22

22 Five WHF sites having highest C density in biomass (based on review of Biomass/carbon of 56 country reports) Redwood National and State Parks of USA -573 t/ha (SOM 52 t/ha) Olympic National Park of USA -419 t/ha (SOM 96 t/ha) Te Wahipounamu South West New Zealand 253 t/ha (SOM 65 t/ha) Central Suriname Reserve of Suriname -227 t/ha (SOM 47 t/ha) Tongariro National Park of New Zealand -208 t/ha (SOM 65 t/ha) 23

23 Level of variability in C stock in forests High variability in C stock in biomass = 16 to 573 t/ ha (high C density is found in West coast of USA/Canada in oceanic forests part and also in Redwood & Olympic NP USA) Low variability in C stock of soil = t/ha ( high SOM lies in sub-tropical humid and temperate oceanic forests of Australia, tropical moist deciduous forests of Brazil, Lake Baikal, Virgin Komi Forests in boreal mountain forests of Russian federation) 24

24 Thank you for your attention Questions? 25