Understanding of the area under forest is necessary while studying the geography of India. Hence, in this module, the following aspects are highlighted:
1. forest area in India
2. forest areas classified
3. distribution of forest areas
4. state-wise forest areas
5. mangrove and tree cover.
Understanding of the area under forest is necessary while studying the geography of India. Hence, in this module, the following aspects are highlighted:
1. forest area in India
2. forest areas classified
3. distribution of forest areas
4. state-wise forest areas
5. mangrove and tree cover.
Patrick McAuslan: Legal dimensions to providing for customary forest rightsRights and Resources
Day 1, Session 1: Current status of tenure and emerging lessons from ongoing reform
Presentation by Patrick McAuslan, Professor of Law, Birkbeck, University of London
A Future for Social Forestry in the Indonesia and ASEAN Economic Community (AEC)CIFOR-ICRAF
This presentation by Wiratno, Director of Social Forestry Development and chairperson of the ASFN Secretariat given during the Forests Asia Summit in the Discussion Forum "Social Forestry and Sustainable Value Chains for a Green Community in ASEAN" focuses on social forestry as a solution to forestry problems in Indonesia.
Global forestry outlook and recommendations for Vietnam Forestry Development ...CIFOR-ICRAF
Presented by Phạm Thu Thủy and Nguyễn Quang Tân, at "National consultation workshop on Vietnam Forestry Development Strategy 2021- 2030, with vision to 2050", on 5 November 2020
The purpose of per is to review and assess the status of forests in India, analyze the trends in production and consumption of forest products, estimate demand and supply of forest products in relation to build national economy with sound environment.
Patrick McAuslan: Legal dimensions to providing for customary forest rightsRights and Resources
Day 1, Session 1: Current status of tenure and emerging lessons from ongoing reform
Presentation by Patrick McAuslan, Professor of Law, Birkbeck, University of London
A Future for Social Forestry in the Indonesia and ASEAN Economic Community (AEC)CIFOR-ICRAF
This presentation by Wiratno, Director of Social Forestry Development and chairperson of the ASFN Secretariat given during the Forests Asia Summit in the Discussion Forum "Social Forestry and Sustainable Value Chains for a Green Community in ASEAN" focuses on social forestry as a solution to forestry problems in Indonesia.
Global forestry outlook and recommendations for Vietnam Forestry Development ...CIFOR-ICRAF
Presented by Phạm Thu Thủy and Nguyễn Quang Tân, at "National consultation workshop on Vietnam Forestry Development Strategy 2021- 2030, with vision to 2050", on 5 November 2020
The purpose of per is to review and assess the status of forests in India, analyze the trends in production and consumption of forest products, estimate demand and supply of forest products in relation to build national economy with sound environment.
Structure, Biomass Carbon Stock and Sequestration Rate of Mangroves in the Ba...ijtsrd
The forest plays a major role in stabilizing increasing temperatures due to its climate mitigation capacity. This is not unconnected to the carbon storing and sequestration potentials of forests. The mangrove as one of the global forest types is said to be a major carbon store. This conclusion is characterized by some knowledge gaps on the actual carbon stock and sequestration potentials of some mangroves forest on the Central African Sub regional landscape. Some of these areas are the Bakassi mangroves in the South West Cameroon. Cross border conflicts, piracy and over exploitation have rendered the sourcing of appropriate data on its carbon stock and sequestration potentials difficult. In strive to bridge this knowledge gap, this work carried out a baseline assessment of the carbon stock and sequestration rate of the area. To achieve the study objectives, stratified random opportunistic sampling inventory design based on five forest canopy height classes, tree Diameter at Breast Height DBH and canopy nature using digital elevation model DEM of the shuttle Radar Topographic Mission SRTM . This combination evaluated the species type and forest structure around the areas. Carbon stocks were estimated with the use of allometric equations using biomass data collected within main plots, sub plots, micro plots and transects. Results showed that mean biomass carbon stock density for the height classes for Bakassi ranged from 33.5 Mg ha to 598.9Mg ha. Thus on average, for a hectare in Bakassi, the carbon stock is 880.437 Mg ha and a sequestration rate of 3231.204 tCO2e ha . Kamah Pascal Bumtu | Nkwatoh Athanasius Fuashi | Longonje Simon Ngomba ""Structure, Biomass Carbon Stock and Sequestration Rate of Mangroves in the Bakassi Peninsula, S-W Cameroon"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-2 , February 2020,
URL: https://www.ijtsrd.com/papers/ijtsrd30171.pdf
Paper Url : https://www.ijtsrd.com/humanities-and-the-arts/environmental-science/30171/structure-biomass-carbon-stock-and-sequestration-rate-of-mangroves-in-the-bakassi-peninsula-s-w-cameroon/kamah-pascal-bumtu
Role of primary forests for climate change mitigationCIFOR-ICRAF
Presented by Haruni Krisnawati of the Forest Research and Development Center Research Development and Innovation Agency, Ministry of Environment and at the 3rd Asia-Pacific Rainforest Summit, on 21-22 April 2018 in Yogyakarta, Indonesia
Mapping of Wood Carbon Stocks in the Classified Forest of Wari-Maro in Benin ...AI Publications
The Emissions Reducing program related to Deforestation and Forest Degradation (Redd +) calls for the development of approaches to quantify and spatialize forest carbon in order to design more appropriate forest management policies. The mapping of carbon stocks was done in the Wari-Maro Forest Reserve. To achieve this, forest inventory data (in situ) and remotely sensed data (Landsat 8 image) were used to construct a wood carbon stock forecasting model. Simple linear regression was used to test the correlation between these two variables. In situ surveys indicate that 64% of carbon stocks are contributed by forest formations, 32.72% are provided by savannah formations and 3.27% are from anthropogenic formations. The quantitative relationship between NDVI and carbon in situ shows a very good correlation with a high coefficient of determination R² = 91%. The carbon map generated from the model identified fronts of deforestation through their low carbon content. This remote sensing approach indicates that forest formations sequester 60% of forest carbon. The savannah formations reserve 33%, the anthropic formations bring only 6% of the stocks. Mapping has further captured the spatial variability among land use types, thus providing arguments to fully meet the objectives of Redd +.
Carbon Stock Estimation in Standing Tree of Chir Pine and Banj Oak Pure Fores...science journals
A study was conducted to measure carbon stock in two Van Panchayat forest of Garhwal Himalaya. For comparative study, we selected the degraded and non-degraded site in Pine and Oak Forest and estimated total carbon stock (above and below ground).
A MODEL TO ESTIMATE STORED CARBON IN THE UPLAND FORESTS OF THE WANGGU WATERSHEDAsramid Yasin
Abstract
Climate change coupled with deforestation has brought about an increase in greenhouse gas emissions in the
atmosphere. One way to control climate change is to reduce greenhouse gas emissions by maintaining the integrity
of natural forests and increasing the density of tree populations. This research aimed to (a) identifies the density
of stand trees in the upland forests of the Wanggu Watershed; (b) analyze the potential carbon stocks contained in
the upstream forests of the Wanggu Watershed; (c) develop a model to estimate potential carbon stocks in the
upland forests of the Wanggu Watershed. The land cover classification in this study used the guided classification
with the Object-Based Image algorithm. Normalized Difference Vegetation Index (NDVI) was employed as an
indicator of vegetation cover density. Field measurements were carried out by calculating the diameter of the stand
trees in 30 observation plots. Field biomass values were obtained through allometric equations. Regression analysis
was conducted to determine the correlation between NDVI densities and field biomass. The results showed that
the best equation for estimating potential carbon stocks in the Wanggu Watershed forest area was y = 3.48 (Exp.
7,435x), with an R2 of 50.2%. Potential above ground biomass carbon in the Wanggu Watershed based on NDVI
values was 414,043.26 tons in 2019, consist of protected forest areas of 279,070.15 tons and production forests of
134,973.11 tons. While total above biomass carbon based on field measurement reached 529,541.01 tons, consist
of protected forests of 419,197.82 tons and production forests of 110,343.20 tons.
Carbon stock assessment of the undisturbed forest in the heavily mined Island...Open Access Research Paper
Forest serves as a significant carbon sink that helps minimize carbon concentrations in the atmosphere through the process of carbon sequestration. The purpose of this study was to determine the total carbon storage of the forest reserve area in Nonoc Island, Surigao City, as one of the areas in Surigao del Norte facing threats of forest degradation from mining and anthropogenic activities. Non-destructive and destructive sampling methods were used to determine the total aboveground (TAG) and belowground (BG) biomass density (BD) and carbon stock of the natural forest’s various carbon pools. Results revealed a total BD of 606Mg ha-1 composed of 484Mg ha-1 TAG while BG is 122Mg ha-1. The forest has an estimated carbon stock value of 368Mg ha-1. Artocarpus blancoi has the highest carbon stock value of 41Mg ha-1 among the 19 species of trees recorded in the area. This implies that the Nonoc Island Forest reserve stored a significant amount of carbon, similar to the reports of other natural forests in the country that may help reduce carbon concentration. As a result, this study would like to recommend preserving and improving the island’s remaining forest areas, not only for forest resource conservation but also for climate change mitigation measures.
Ecosystem Carbon Storage and Partitioning in Chato Afromontane Forest: Its Cl...IJEAB
Forests trap carbon dioxide (CO2) from the atmosphere, store in the form of carbon (C) and regulate climate change. In this study, C storage and climate change mitigation potential of Chato Afromontane forest was assessed from measurement of the major pools including the aboveground biomass, belowground biomass, dead tree biomass, plant litter and soil organic carbon (SOC). The result showed that biomass accumulation was comparatively larger for natural forest than plantations due to maturity, intactness and species diversity. The total C storage capacity of the forest ranged from 107.12 Mg ha-1 for acacia plantation to 453.21 Mg ha-1 for the intact natural forest. The mean C storage capacity by major pools ranged from 1.36 Mg ha-1 for the dead tree C to 157.95 Mg ha-1 for the aboveground C pool. The forest ecosystem accumulated a total of nearly 6371.30 Gg C in the vegetation plus soil to a depth of 60 cm. Conservation of the sacred forest will have an imperative implication to net positive C addition and regulation of climate change.
RNS State Action Plan on Climate Change EPCO_forest_cc_20.09.2018RavindraSaksena
Presentation on "Impact of Climate Change on Forests of Madhya Pradesh" made in a workshop organised by the Environment Protetion & Conservation Organisation for State Action Plan on Climate Change
Measures for prevention, control and abatement of environmental pollution in river Ganga and to ensure continuous adequate flow of water so as to rejuvenate the river Ganga.
MATATAG CURRICULUM: ASSESSING THE READINESS OF ELEM. PUBLIC SCHOOL TEACHERS I...NelTorrente
In this research, it concludes that while the readiness of teachers in Caloocan City to implement the MATATAG Curriculum is generally positive, targeted efforts in professional development, resource distribution, support networks, and comprehensive preparation can address the existing gaps and ensure successful curriculum implementation.
A review of the growth of the Israel Genealogy Research Association Database Collection for the last 12 months. Our collection is now passed the 3 million mark and still growing. See which archives have contributed the most. See the different types of records we have, and which years have had records added. You can also see what we have for the future.
The simplified electron and muon model, Oscillating Spacetime: The Foundation...RitikBhardwaj56
Discover the Simplified Electron and Muon Model: A New Wave-Based Approach to Understanding Particles delves into a groundbreaking theory that presents electrons and muons as rotating soliton waves within oscillating spacetime. Geared towards students, researchers, and science buffs, this book breaks down complex ideas into simple explanations. It covers topics such as electron waves, temporal dynamics, and the implications of this model on particle physics. With clear illustrations and easy-to-follow explanations, readers will gain a new outlook on the universe's fundamental nature.
This presentation includes basic of PCOS their pathology and treatment and also Ayurveda correlation of PCOS and Ayurvedic line of treatment mentioned in classics.
This presentation was provided by Steph Pollock of The American Psychological Association’s Journals Program, and Damita Snow, of The American Society of Civil Engineers (ASCE), for the initial session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session One: 'Setting Expectations: a DEIA Primer,' was held June 6, 2024.
Delivering Micro-Credentials in Technical and Vocational Education and TrainingAG2 Design
Explore how micro-credentials are transforming Technical and Vocational Education and Training (TVET) with this comprehensive slide deck. Discover what micro-credentials are, their importance in TVET, the advantages they offer, and the insights from industry experts. Additionally, learn about the top software applications available for creating and managing micro-credentials. This presentation also includes valuable resources and a discussion on the future of these specialised certifications.
For more detailed information on delivering micro-credentials in TVET, visit this https://tvettrainer.com/delivering-micro-credentials-in-tvet/
Macroeconomics- Movie Location
This will be used as part of your Personal Professional Portfolio once graded.
Objective:
Prepare a presentation or a paper using research, basic comparative analysis, data organization and application of economic information. You will make an informed assessment of an economic climate outside of the United States to accomplish an entertainment industry objective.
How to Build a Module in Odoo 17 Using the Scaffold MethodCeline George
Odoo provides an option for creating a module by using a single line command. By using this command the user can make a whole structure of a module. It is very easy for a beginner to make a module. There is no need to make each file manually. This slide will show how to create a module using the scaffold method.
How to Add Chatter in the odoo 17 ERP ModuleCeline George
In Odoo, the chatter is like a chat tool that helps you work together on records. You can leave notes and track things, making it easier to talk with your team and partners. Inside chatter, all communication history, activity, and changes will be displayed.
A Survey of Techniques for Maximizing LLM Performance.pptx
Forests India
1. INDIAN COUNCIL OF FORESTRY RESEARCH AND EDUCATION
PO: New Forest, Dehradun – 248006 (Uttarakhand) India
India’s Forest and Tree Cover:
Contribution as a Carbon Sink
Technical Paper
Jagdish Kishwan
Director General
Indian Council of Forestry
Research and Education,
Dehradun
E-mail: jkishwan@nic.in
Rajiv Pandey
Scientist (Statistics)
Indian Council of Forestry
Research and Education,
Dehradun
E-mail: rajivfri@yahoo.com
VK Dadhwal
Dean
Indian Institute of Remote
Sensing, Dehradun
E-mail: dean@iirs.gov.in
2.
3. India’s Forest and Tree Cover: Contribution as a Carbon Sink 1
TECHNICAL PAPER
Jagdish Kishwan1
, Rajiv Pandey1
and V K Dadhwal2
1
Indian Council of Forestry Research and Education, Dehradun,
Uttarakhand
2
Indian Institute of Remote Sensing, Dehradun, Uttarakhand
India’s Forest and Tree Cover:
Contribution as a Carbon Sink
Abstract
India ranks 10th
in the list of most forested na-
tions in the world with 76.87 million ha of forest
and tree cover. Like other forests of the world,
our forests also provide critical ecosystem goods
and services. However, the significant role of
forests in carbon storage and sequestration has
increased their importance manifold and
brought them to the centre-stage of climate
change mitigation strategies.
India’s forest and tree cover accounts for about
23.4% of the total geographical area of the
country. Over the past decades, national poli-
cies of India aimed at conservation and sustain-
able management of forests have transformed
India’s forests into a net sink of CO2
. From 1995
to 2005, carbon stocks stored in our forests have
increased from 6244.78 to 6621.55 million
tonnes (mt) registering an annual increment of
37.68 mt of carbon = 138.15 mt of CO2
eq. This
annual removal by forests is enough to neutralise
9.31% of our total annual emissions of 2000.
This amount of carbon sequestration will still be
adequate to dent our emissions even when
these will be on the increase due to our accel-
erated development process. Estimates show
that the continued removals by the forests
would still be able to offset 6.53% and 4.87%
of our projected annual emissions in 2010 and
2020 respectively. It is estimated that emissions
in 2010 and 2020 will respectively be 45% and
95% higher than those in 2000.
And, if over and above the current trend, the
National Mission for a Green India as part of
the ‘National Action Plan on Climate Change’
(NAPCC) becomes operational, the capability
of the forestry sector to contribute in GHG re-
moval will further enhance. Afforestation and
reforestation of 6 million hectares of degraded
forest land covered under the National Mission
with participation of Joint Forest Management
Committees (JFMCs) would be able to add an-
other 18 mt of carbon = 66 mt of CO2
eq by
2020. Annual addition of 6 mt of biomass due
to operationalization of the Mission will increase
the annual emissions removal capability of the
forests from 4.87% to 5.18% of the correspond-
ing projected emissions in 2020. Even if half
(3 mt) of the annual biomass increment (6 mt)
is removed annually on a sustainable basis from
2025 onwards, the emission removal capability
of forestry sector would still be able to offset
every year 5.02% of the 2020 level emissions.
It is abundantly clear that forestry sector has sig-
nificant emissions removal capability which can
further be enhanced by operationalizing major
afforestation and reforestation initiatives like Na-
tional Mission for a Green India besides contin-
ued strengthening of the present protection re-
gime of forests. Launching a programme to pro-
4. India’s Forest and Tree Cover: Contribution as a Carbon Sink2
TECHNICAL PAPER
vide LPG in hilly areas of Himalayan region and
in central tribal belt offers another potential op-
portunity to further improve the carbon seques-
tration potential of our forests as this kind of fuel
switching by the hilly and tribal communities
would reduce pressure of fuelwood removal
from forests.
Key words: Emissions Removal, Capability of
Forests, GHG Emissions, Carbon Storage, For-
est Carbon Stocks, Joint Forest Management
Committees, Green India
Introduction
Forests provide a wide range of goods and ser-
vices. Goods include timber, fuelwood, as well
as food products (berries, mushrooms, etc.) and
fodder. As regards important services, forests
and trees play a role in the conservation of eco-
systems, in maintaining quality of water, and in
preventing or reducing the severity of floods,
avalanches, erosion, and drought. Forests pro-
vide a wide range of economic and social ben-
efits, such as employment, forest products, and
protection of sites of cultural value (FAO, 2006).
Forests, like other ecosystems, are affected by
climate change. The impacts due to climate
change may be negative in some areas, and
positive in others. However, forests also influ-
ence climate and the climate change process
mainly by effecting the changes in the quantum
of carbon dioxide in the atmosphere. They ab-
sorb CO2
from atmosphere, and store carbon
in wood, leaves, litter, roots and soil by acting
as “carbon sinks”. Carbon is released back into
the atmosphere when forests are cleared or
burned. Forests by acting as sinks are consid-
ered to moderate the global climate. Overall,
the world’s forest ecosystems are estimated to
store more carbon than the entire atmosphere
(FAO, 2006).
However, deforestation, mainly conversion of
forests to agricultural land, is continuing at an
alarmingly high rate. Forest area, which is about
30% (4 billion hectares) of the global total land
area decreased worldwide by 0.22% per year
in the period 1990-2000 and 0.18% per year
between 2000 and 2005. However, the net loss
of forest is slowing down as a result of the plant-
ing of new forests and of natural expansion of
forests. Forests and trees are being planted for
many purposes and at increasing rates, yet the
plantations still account for only 5 percent of
5. India’s Forest and Tree Cover: Contribution as a Carbon Sink 3
TECHNICAL PAPER
total forest area (FAO, 2006). Quantifying the
substantial roles of forests as carbon stores, as
sources of carbon emissions and as carbon sinks
has become one of the keys to understanding
and modifying the global carbon cycle.
Worldwide numerous ecological studies have
been conducted to assess carbon stocks based
on carbon density of vegetation and soils (Atjay
et. al., 1979; Olson et. al., 1983; Saugier and Roy,
2001). The results of these studies are not uni-
form and have wide variations and uncertain-
ties probably due to aggregation of spatial and
temporal heterogeneity and adaptation of dif-
ferent methodologies. IPCC (2000) estimated
an average carbon stock of 86 tonnes per hect-
are in the vegetation of the world’s forests for
the mid-1990s. The corresponding carbon in
biomass and dead wood in forests reported in
FRA, 2005 amounts to 82 tonnes per hectare
for the year 1990 and 81 tonnes per hectare for
the year 2005. Each cubic metre of growing
stock equals different amounts of biomass and
carbon (in biomass) in different regions. Glo-
bally, each cubic metre of growing stock equals,
on an average, 1 tonne of above-ground biom-
ass, 1.3 tonnes of total biomass and 0.7 tonnes
of carbon in biomass (FAO, 2006). The country
reports of FAO indicate that global forest veg-
etation stores 283 Gt of carbon in its biomass,
and an additional 38 Gt in dead wood, for a
total of 321 Gt and IPCC (2000) assumed 359
Gt of carbon in these pools.
Total growing stock shows a slight overall down-
ward tendency – mainly owing to a decrease in
forest area. However, some regions also show
significant positive trends in growing stock per
hectare. For example, Europe shows an increase
and Southeast Asia a decrease. It is estimated
that the world’s forests store 638 Gt of carbon
in the ecosystem as a whole (to a soil depth of
30 cm). Thus forests contain more carbon than
the entire atmosphere. Roughly half of total car-
bon is found in forest biomass and dead wood
combined and half in soils and litter combined
(FAO, 2006).
India is a large developing country known for
its diverse forest ecosystems and mega-
biodiversity. It ranks 10th
amongst the most for-
ested nations of the world (FAO, 2006) with 23.4
percent (76.87 million ha) of its geographical
area under forest and tree cover (FSI, 2008).
With nearly 173,000 villages classified as forest
fringe villages, there is obviously a large depen-
dence of communities on forest resources. Thus,
it is very important to assess the likely impacts
of projected climate change on forests, to de-
velop and implement adaptation strategies both
for biodiversity conservation and protection and
for safeguarding the livelihoods of forest depen-
dent people, and to ensure production of round
wood for industrial and commercial needs.
The forest carbon was assessed in different ways
by different researchers. Earlier attempts for es-
timating forest carbon did not take into consid-
eration soil carbon. The biomass carbon stock
in India’s forests was estimated at 7.94 MtC dur-
ing 1880 and nearly half of that after a period of
100 years (Richards and Flint, 1994). The first
available estimates for forest carbon stocks (bio-
mass and soil) for the year 1986, are in the range
of 8.58 to 9.57 GtC (Ravindranath, et al., 1997;
Haripriya, 2003; Chhabra and Dadhwal, 2004).
As per FAO estimates (FAO, 2005), the total for-
est carbon stocks in India have increased over a
period of 20 years (1986–2005) and amount to
10.01 GtC. The carbon stock projections for the
period 2006–30 is projected to be increasing
from 8.79 to 9.75 GtC (IISc, 2006) with forest
cover becoming more or less stable, and new
forest carbon accretions coming from the cur-
rent initiatives of afforestation and reforestation
programme (Ravindranath, et al., 2008). Need-
6. India’s Forest and Tree Cover: Contribution as a Carbon Sink4
TECHNICAL PAPER
less to say that the present state of forest car-
bon stocks owes its origin to the drive of planta-
tion forestry in India started in the late 1950s
and supplemented later by the social and farm
forestry initiatives of the 1980s and early 1990s.
All the same, the National Communication of
the Government of India to the UNFCCC for
1994 has reported that the LULUCF sector is a
marginal source of emissions with a figure of
14.29 mt (million tonnes) of CO2
. However, in
the LULUCF sector ‘changes in forest and other
woody biomass stock’ account for a net removal
of 14.25 mt of CO2
(NATCOM, 2004).Thus, for
forests alone, the NATCOM presents a net sink
of 14.25 mt CO2
eq. With the knowledge and
the information that is now emerging, the role
of forests and plantations in mitigation is becom-
ing more and more important. NATCOM re-
ports a comprehensive inventory of India’s emis-
sions from all energy, industrial processes, agri-
culture activities, land use, land use change and
forestry and waste management practices to the
United Nations Framework Convention on Cli-
mate Change (UNFCCC) for the base year 1994.
It is a useful reference document to compare
the contribution of different sectors in the na-
tional level emissions.
The compounded annual growth rate of CO2
eq
emissions in India is 4.2 per cent. Some may
consider this to be higher than the desired, but
the absolute value of these emissions is still one-
sixth that of the United States and lowest for
the per capita GHG emissions (Rawat and
Kishwan, 2008).
In India, CO2
emissions from forest diversion or
loss are largely offset by carbon uptake due to
forest increment and afforestation. Many au-
thors concluded that for the recent period, the
Indian forests are nationally a small source with
some regions acting as small sinks of carbon as
well (Ravindranath, et al.1997; Haripriya, 2003;
Chhabra and Dadhwal, 2004; Ravindranath, et
al., 2008). The improved quantification of pools
and fluxes related to the forest carbon cycle is
important for understanding the contribution of
India’s forests to net carbon emissions as well
as their potential for carbon sequestration in the
context of the Kyoto Protocol (Chhabra and
Dadhwal, 2004).
It was in this background that the country rec-
ognized the importance of pursuing the poli-
cies of conservation and expanding the areas
of woodlots that besides goods and other ser-
vices allowed the forests to sequester more and
more carbon in biomass and the soil. This is
happening not only in India, but in many other
developing countries. To encourage conserva-
tion and expansion of forests world-wide, India
internationally supported compensation for
nations in return for the carbon services they
are, and will be, providing by conserving, stabi-
lizing and/or increasing their forest cover. The
policy approach advocated by India in the con-
text of the agenda item of “Reducing emissions
from deforestation in developing countries” of
the United Nations Framework Convention on
Climate Change (UNFCCC), also known as
REDD or REDD-plus was named “compensated
conservation” (Kishwan, 2007). However, any
future agreement on REDD/REDD-plus would
require assessment and monitoring of forest
carbon stocks of a country at regular intervals
through application of scientifically acceptable
methodologies.
Purpose of this study is to compute improved
estimates for biomass, and therefrom biomass
carbon in forests taking into account the inven-
tory data for diversified forest types present in
the country, and also by accounting for biom-
ass in other vegetation on forest floor (other than
trees). It may also be mentioned that most stud-
ies related to estimation of biomass have not
7. India’s Forest and Tree Cover: Contribution as a Carbon Sink 5
TECHNICAL PAPER
incorporated the biomass stored in the under-
story of the forest (Brown and Lugo, 1991;
Manhas, et al., 2006).
Methodology
Estimation of carbon stocks in forestry sector,
present in biomass and soil, is based either on
IPCC guidelines or through use of actual con-
version and other factors starting from the grow-
ing stock (GS) data of forest inventories. Forest
Survey of India is primary source of these data
in the country. However, some other sources
such as FAO, and research papers complement
these inventories. The present study for the as-
sessment of forest carbon stocks uses primary
data for the soil carbon pool and secondary data
of growing stock from various sources for esti-
mating the biomass carbon (Brown and Lugo,
1984; Houghton, et al. 1985; Dadhwal and
Nayak, 1993). Approach of the study being a
combination of primary and secondary data
with large number of samples for assessment of
soil organic carbon (SOC) makes it more reli-
able for carbon pool estimates. Mathematically,
assessment of forest carbon stocks in the study
can be represented as:
CCarbon
= CBiomass
+ CSoil
Where,
CCarbon
= Total available carbon in the forest,
i.e., in the vegetation and in soil
CBiomass
= Total available carbon in the above
and below ground biomass of all for-
est vegetation
CSoil
= Total available soil organic carbon
(SOC) up to 30cm depth in the forest
Soil Organic Carbon (SOC) Pool -
For estimating SOC, the IPCC guidelines (IPCC,
1997) prescribe that only the upper 30 cm layer
of soil, which contains the actively changing soil
carbon pool in the forest, should be considered.
For this purpose, the representative soil samples
were collected from a pit of 30 cm wide, 30 cm
deep and 50 cm in length. The samples con-
tained thoroughly mixed soil with gravels re-
moved, and were collected randomly from all
forest types by digging a fresh rectangular pit in
the forest and by clearing the top layer of grass,
litter and humus in an area of 50 cm x 50 cm.
However, no samples were taken from eroded
land, or from near the trunk of trees, roads,
houses and construction sites, etc. For estimat-
ing bulk density, two to three clods of about 2
to 3 cm size were picked from each pit from
top to bottom using standard collectors. Soil
samples were collected from a total of 571
sample points laid in different forest types cov-
ering the whole country. Forest types were used
as strata for sampling and equal number of
sample points were allocated to each stratum.
The study covered a total of 571 samples in for-
est area and 101 additional samples in the
nearby non-forest areas. But, for assessment of
SOC in forests, 101 samples collected from non-
forest areas were not taken into account. Addi-
tionally, 15 samples falling in alpine scrub were
discarded as area of this forest type was not
available. Soil organic carbon was estimated by
standard Walkley and Black method and bulk
density was estimated using standard Clod
method. All measurements, observations and in-
formation required for each sample were sys-
tematically recorded. The bulk density (D) was
calculated as under:
D = weight of soil (gm)/volume of core (cyl-
inder) in cm3
8. India’s Forest and Tree Cover: Contribution as a Carbon Sink6
TECHNICAL PAPER
Soil organic carbon stock Qi
(Mg m-2
) in a soil
layer or sampling level i with a depth of Ei
(m)
depends on the carbon content Ci
(g C g-1
), bulk
density Di
(Mg m-3
) and on the volume fraction
of coarse elements Gi
, given by the formula
(Batjes, 1996):
Qi
= Ci
Di
Ei
(1–Gi
)
For the soil thickness z with k levels of depar-
ture, the total stock of carbon was obtained by
adding the stocks for each of the k levels
(Schwartz and Namri, 2002):
)1(
11
iiii
k
i
k
i
itsoil GEDCQQC −=== ∑∑ ==
Rock outcrop at a site affects the representa-
tive elementary volume and the regolith volume
available for root growth. This attribute was
eliminated by using a simple estimate of areal
percentage (McDonald et al., 1990).
Biomass Carbon-
Biomass carbon can be disaggregated into
above ground and below ground biomass.
Change in forest carbon stocks during a time
period is an indicator of the net emissions or
removals of CO2
in that period. Total biomass
was calculated for the years 1995 and 2005, and
linearly projected for the year 2015.
Assessment of biomass was based on the con-
sideration that all lands, more than one hectare
in area, with a tree canopy density of more than
10 per cent are defined as ‘Forest’. The country’s
forest carbon estimate is based on the forest
cover assessment of 1997 and 2005 by Forest
Survey of India (FSI). Additionally, data for the
year 2003 was also considered. The satellite data
used for 1997 assessment related to the period
from 1993 to 1995, and for 2005, pertained to
2003 to 2005. Therefore, we have safely pre-
sumed that these assessments are sufficiently
and adequately representative, and thus can be
used for forest carbon stock estimation for 1995
and 2005 (Saxena, et al., 2003). The total forest
cover in India according to the State of Forest Re-
port 2005 is 67.71 mha or 20.60% of the geo-
graphic area (FSI, 2008), and as per 1995 report,
the forest cover is 63.34 mha covering 19.27% of
geographicareaofcountry(Manhas, et al., 2006).
The component-wise, i.e., growing stock sepa-
rately for forest and tree cover of the country
for the years 2003 and 2005 is respectively avail-
able in State of Forest Report 2003 (FSI, 2005)
and State of Forest Report 2005 (FSI, 2008).
However, for 1995, growing stock only for for-
est cover is available at the national level. Grow-
ing stock for the tree cover for 1995 at the coun-
try level was estimated based on the mean of
the ratio between growing stock of tree cover
and that of forest cover for the years 2003 and
2005 with the assumption that during the pe-
riod of about a decade between 1993, and
2003-2005, the increment in growing stock of
the tree cover and that of forest cover have fol-
lowed a uniform pattern. As regards, state-wise
break-up of data relating to the quantum of
growing stock for forest cover, and that for tree
cover, the same is not available for 2005, which
makes it difficult to estimate state-wise figures
for such data for 1995 also.
Suitable biomass increment values (expansion
and conversion for calculating total tree above
ground biomass) and the ratio of below and
above ground biomass (for calculating total tree
biomass above and below ground) as available
in different studies covering a range of forest
types of the country were used in the present
study. The referred studies measured directly or
indirectly the total biomass of the stand broken
down into the individual components (Chhabra,
et al., 2002; Kaul, et al., 2009). These compo-
9. India’s Forest and Tree Cover: Contribution as a Carbon Sink 7
TECHNICAL PAPER
nents were stemwood, branches, leaves and
roots of the tree in a stand or even in a larger
area depending on the study. The biomass of
other vegetation on forest floor (understory) was
estimated based on the ratio of total tree biom-
ass to the total forest floor biomass excluding the
tree component in the area. In general, other for-
est floor biomass accounts for less than 2 percent
of total biomass of closed forest formations
(Ogawa, et al., 1965; Rai, 1981; Brown and Lugo,
1984). However for this study, ratio was adopted
based on the published records for different veg-
etation types and different localities, and also
keeping in view its application and representa-
tion for the country level estimates (Singh and
Singh, 1985; Rawat and Singh, 1988; Negi, 1984;
Roy and Ravan, 1996). Mathematically, the
above ground biomass of tree component is as
follows:
VegetaionOtherTreeTotal GSGSGS .+=
=TotalGS Total growing stock in forest
=TreeGS Growing stock of tree component
=VegetaionOtherGS . Growing stock of other
vegetation on forest floor
GroundBelowGroundAboveTree VVGS .. +=
GroundAboveV . = Above ground volume
GroundBelowV . = Below ground volume
GroundAboveV . = CommercialGS x Expansion factor
CommercialGS = Growing stock of tree bole
upto 10 cm diameter
Expansion factor = Adjusted mean biomass (vol-
ume) expansion factor for the country
GroundBelowV . = GroundAboveV . x Ratio
Ratio = Adjusted mean ratio between below and
above ground biomass (volume)
=VegetaionOtherGS . TreeGS x R
R = Ratio of other forest floor biomass to grow-
ing stock of tree component
The biomass is estimated by taking into account
the total growing stock of the forest including
the above and below ground volume of all veg-
etation in the forest and multiplying it with a
‘volume to mass’ conversion factor. The conver-
sion factor adopted in this study is influenced
by the contents of studies of Brown, Gillespie
and Lugo, 1991; Rajput, et al., 1996 and Kaul, et
al., 2009.
B = TotalGS x MD
B = Biomass (million tonnes)
TotalGS = Total forest growing stock (million m3
)
MD = Mean wood density
Biomass material contains about 40% carbon
by weight, with the hydrogen (6.7%) and oxy-
gen (53.3%). The remaining proportions include
nitrogen with a share of 0.3-3.8%, and sulfur 0.1-
0.9%. The variability of approximately 9% de-
pends on the nature of the biomass material
(Bowen, 1979; Levine, 1996). Although most
studies have used the carbon proportions be-
tween 40 to 50% depending on the require-
ments (IPCC, 1997; 2004; Andreae, 1991; 1993
Susott, et al., 1996; Ludwig, et al., 2003), the
present study uses the conservative value of
40% carbon content keeping in view the fact
that the study deals with mixed biomass com-
prising timber, fuelwood, leaves, twigs, roots,
etc. The study also assumes the presence of an
average moisture content of 20% mcdb (mois-
10. India’s Forest and Tree Cover: Contribution as a Carbon Sink8
TECHNICAL PAPER
ture content on dry basis) in dry wood and other
biomass. This has also been suggested by Leach
and Gowen, 1987; Hall, et al., 1994 for getting
more realistic estimate considering that good
amount of water still remains in wood even af-
ter proper drying (Ludwig, et al., 2003). Conser-
vative values of carbon content and mcdb have
been adopted to have realistic estimates in view
of the errors that are generally associated with
use of such values and factors in computation
of total growing stock, wood densities, expan-
sion and conversion factor, etc. Mathematically,
the biomass carbon can be estimated as follows:
=BiomassC Biomass x (1 - mcdb) x Proportion
of Carbon Content
Based on the carbon estimates for the year 2005
and 1995, the annual addition of carbon in
India’s forest was calculated. This increment was
converted into the CO2
equivalent for compar-
ing and estimating the emissions offsetting ca-
pability of India’s forest in relation to the national
level GHG emissions. Figures for GHG emis-
sions of the country were available in published
records for the year 1990, 1994 and 2000 in
Sharma, et al., 2006, and for 2000, 2010 and
2020 in Shukla, 2006 with corresponding CO2
equivalent value. Emissions removal or offset-
ting capability of forests was calculated as a
percentage of these projected values. Incre-
ment in forest carbon stocks over a period of
time is calculated as under:
Carbon Increment in m years ( mI ) = CarbonC in
tth
year - CarbonC in (t-m)th
year
Based on above, the annual increment ( AI ) in
forest carbon stocks is
m
I
I m
A =
Result
The growing stock of the country for the year
2005 is 6,218 million cubic meter comprising
4,602 million cubic meter corresponding to the
forest cover and 1,616 million cubic meter cor-
responding to the tree cover. Average growing
stock in the recorded forest area per hectare is
59.79 cubic meter. However, in 2003, the grow-
ing stock under tree cover was 1,632 million
cubic meter and for forest cover was 4,781 mil-
lion cubic meter. The proportion of growing
stock for tree cover as compared to that for
forest cover is 35.12% and 34.14% in 2005 and
2003 respectively (FSI, 2005, 2008). The mean
of these proportions (34.63 %) is utilized for
estimating the growing stock under tree cover
for the country in the year 1995, as the figure
for this growing stock for 1995 is not available.
In this year, the growing stock under forest cover
was 4,339.55 million cubic meter (FSI, 1997;
Manhas, et. al., 2006), and the estimated grow-
ing stock under tree cover worked out on the
basis of average proportion is 1,502.77 million
cubic meter, making the total growing stock of
5,842.32 million cubic meter for both forest and
tree cover. Following the description in meth-
odology, the adjusted mean biomass expansion
factor, ratio between below and above ground
biomass, mean density, and ratio between other
forest floor biomass to the tree biomass were esti-
mated, and are presented below in Table 1 to-
gether with calculation for forest biomass carbon
in the country’s forests. The calculation uses con-
version of commercial wood volume (growing
stock) into total biomass using average adjusted
wood density and expansion factors and ratios as
alsosuggestedbyBrown,GillespieandLugo,1991.
Soil organic carbon pool for different forest
groups was estimated based on the primary data
as described in methodology and reported in
Table 2 for 1995 and 2003.
11. India’s Forest and Tree Cover: Contribution as a Carbon Sink 9
TECHNICAL PAPER
Table 1: Forest Biomass Carbon in India (million tonnes)
Item with symbolic description Factor 1995 2005
Growing Stock of Country in Mm3
- GS 5842.320 6218.282
Mean Biomass Expansion Factor - EF 1.575
Ratio (Below to Above Ground Biomass) - RBA 0.266
Above Ground Biomass (Volume) - AGB = GS X EF 9201.654 9793.794
Below Ground Biomass (Volume) - BGB = AGB X RBA 2447.640 2605.149
Total Biomass (Volume) – TB = AGB + BGB 11649.294 12398.943
Mean Density - MD 0.7116
Biomass in Mt = Growing Stock (Mm3
) x Mean Density (MD) 8289.638 8823.088
Ratio (Other Forest Floor Biomass except tree to Tree Biomass) 0.015
Total Forest Biomass in Mt (Trees + Shrubs + Herbs) - TFB 8413.982 8955.434
Dry Weight in Mt (80% of TFB) - DW 6731.186 7164.348
Carbon in Mt (40 % of DW) 2692.474 2865.739
Factors for various items were derived from mainly Kaul, et.al., 2009; Ray and Ravan, 1996 and Singh and Singh, 1985.
Table 2: Soil Organic Carbon Pool Estimates (0 - 30 cm) in India’s Forests (million tonnes)
Area in 000 ha
Forest Type (Group) Area Area Mean Sample SE Total SOC Total SOC
1995 2005 Soil Num- 1995 2005
Carbon ber
Himalayan dry temperate forest 31 32 36.198 24 5.56 1122.144 1158.343
Himalayan moist temperate forest 2230 2447 71.577 48 7.16 159616.937 175149.168
Littoral and swamp forest 383 481 71.062 70 12.20 27216.904 34181.021
Montane wet temperate forest 2583 2593 115.460 16 14.61 298233.293 299387.893
Sub alpine and alpine forest 2021 2067 74.071 12 12.18 149698.375 153105.661
Sub tropical broad leaved hill forest 260 303 86.611 20 14.97 22518.833 26243.102
Sub tropical dry evergreen forest 1223 1248 65.279 3 10.37 79836.780 81468.766
Sub tropical pine forest 4556 4743 50.270 12 8.08 229031.601 238432.151
Tropical dry deciduous forest 18233 19156 34.195 143 4.16 623475.447 655037.332
Tropical dry evergreen forest 134 165 52.398 10 11.64 7021.363 8645.709
Tropical moist deciduous forest 23091 24284 55.009 57 6.73 1270222.177 1335848.398
Tropical semi evergreen forest 2573 2946 54.625 40 5.71 140549.907 160925.000
Tropical thorn forest 1604 1827 20.375 61 5.75 32681.741 37225.399
Tropical wet evergreen forest 5040 5414 101.404 40 10.04 511078.124 549003.366
Total 63962 67706 556 3552303.628 3755811.310
The area under various forest types are from FSI reports (FSI, 1995 and FSI, 2008).
12. India’s Forest and Tree Cover: Contribution as a Carbon Sink10
TECHNICAL PAPER
Based on the figures for biomass carbon and
SOC in forests given in Table 1 and Table 2
above, the estimates of total forest carbon stocks
comprising components of biomass carbon and
SOC for 1995 and 2005 were computed, and
are presented below in Table 3. Component-
wise changes in the period from 1995-2005
were also worked out.
out the proportion of national level emissions
offset by forests in India. Proportion of emissions
removed/offset by India’s forestry sector in dif-
ferent years is reported below in Table 4.
Implementation of the National Mission for a
Green India as part of the National Action Plan
for Climate Change can further enhance the
present mitigation potential of the forestry sec-
tor. Same methodology as has been used for
calculating forest carbon stocks for forestry sec-
tor can be used for estimating the additional
quantum of carbon sequestered by afforestation
and reforestation of 6 million ha of degraded
forest lands. Presuming a conservative dry bio-
mass accumulation of 1 t ha-1
yr-1
, 18 million
tonnes (mt) of carbon (in 45 mt of dry biomass)
would get accumulated by 2020 when the plan-
tation is done at the rate of 1 million ha per year,
2010 onwards. The figure would rise to 75 mil-
lion tonnes of carbon in 2025. In 2020, when 6
mt of biomass = 2.4 mt of carbon or 8.8 mt of
CO2
eq is sequestered every year; this will be
able to additionally offset 0.31% of projected
2020 level emissions annually. The mission will
have the effect of increasing the emissions re-
moval capability of the country’s forests from
4.87 to 5.18% annually of the 2020 emissions
level. Even if half the biomass of 3 mt from the
total annual incremental biomass is removed
from 2025 onwards on a sustainable basis, the
Table 3: Component-wise Carbon in India’s
Forests in 1995 and 2005 (million tonnes)
Carbon 1995 2005 Incre-
mental
Change
In Biomass 2692.474 2865.739 173.265
In Soil 3552.304 3755.811 203.507
Total 6244.778 6621.55 376.772
The analysis showed that there is improvement
in forest carbon stocks on temporal basis from
1995 to 2005. The difference of 376.772 mt
between figures of 1995 and 2005 shows the
incremental carbon accumulation in India’s for-
ests during the period. On yearly basis, the ad-
dition of carbon was 37.677 mt ≈ 37.68 mt (say),
which means an annual removal of 138.15 mt
CO2
eq. Annual accumulation of forest carbon
stocks was compared with the trend of national
GHG emissions as computed and reported by
Shukla, 2006 and Sharma, et al., 2006 to work
Table 4: Total GHG Emissions (mt CO2
eq) from various sectors, and proportion thereof offset
by forestry sector
Estimate Source/ Proportion 1990 1994 2000 2010 2020
Shukla, 2006 – – 1454 2115 2839
Proportion of Emissions Removed
by India’s Forestry Sector (%) 9.50 6.53 4.87
Sharma et. al. 2006 987.885 1,228.539 1,484.622 – –
Proportion of Emissions Removed
by India’s Forestry Sector (%) 13.98 11.25 9.31
13. India’s Forest and Tree Cover: Contribution as a Carbon Sink 11
TECHNICAL PAPER
plantations of the mission would still be able to
maintain the increased emissions removal ca-
pability of forestry sector at 5.02% of the 2020
level emissions.
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15.
16. For further details, please contact:
Director General
Indian Council of Forestry Research and Education
P.O. New Forest
Dehradun 248006, Uttarakhand, INDIA
Tel: +91 135 2759382 Fax: 0135 2755353
E-mail: jkishwan@nic.in
130 ICFRE BL - 23
2009