Assessments Of Plant Diversity, Biomass And Carbon Pool In Natural Forests Of Doon Valley Using Geospatial Technology

by Dr. Mohommad Shahid (Author) Dr. S.P. Joshi (Author)

Doctoral Thesis / Dissertation 2013 270 Pages

Biology - Botany







2.5 SOIL

Chapter – III SOIL
3.2.1 Physico-Chemical Analysis of Soil
3.2.2 Mechanical analysis of Soil (Texture Analysis)
3.2.3 Soil Organic Carbon Estimation Methodology
3.3.1 Physico-Chemical Characteristics of Soils
3.3.2 Mechanical Characteristics of Soils

Chapter – IV Plant Diversity

Chapter – V Phytosociology
5.2.1 Important Value Index (IVI)
5.2.2 Diversity Indices and Evenness
5.2.3 Dominance – Diversity Curves (D –D curves)
5.3.1 Herb Layer
5.3.2 Shrub Layer
5.3.3 Tree Layer
5.3.4 Diversity and Related Measurements
5.3.5 Dominance-Diversity (D-D) Curve

Chapter – VI Biomass and Carbon Pool
6.2.1 Remote Sensing for Forest Type Mapping
6.2.2. Methodology for Biomass and Carbon Estimation
6.3.1 Barkot Range
6.3.2 Lachchiwala Range
6.3.3 Thano Range
6.3.4 : Forest Type wise Total Biomass and Carbon Content
6.3.5 Contribution of Shorea robusta in Total Biomass of Different Forest Types
6.3.6 Carbon Pool






It gives me great pleasure to certify that Mr. Mohommad Shahid, candidate for the degree of Doctor of Philosophy in Botany of Hemwati Nandan Bahuguna Garhwal University, Srinagar (Garhwal) has worked under my supervision and guidance.

The thesis entitled “Assessments of Plant Diversity, Biomass and Carbon Pool in Natural Forests of Doon Valley using Geospatial Technology” embodies the result of the investigations carried out by him and is his original work

Dr. S.P. Joshi


I express my deep sense of gratitude to my guide Dr. S. P. Joshi, Associate Professor, Department of Botany, D.A.V. (P.G.), College Dehradun, for rendering a helping hand through precious guidance, encouragement and timely suggestions during the course of my research which made this work possible.

I am thankful to Head, Department of Botany, D. A.V. College, Dehradun for allowing me to carry out the present research work in the department. I express my sincere thanks to various research institutes viz., Indian Institute of Remote Sensing, Dehradun, Botanical Survey of India, Northern Circle, Dehradun; Indian Council of Forestry Research and Education, Dehradun; Wildlife Institute of India, and Forest Survey of India for allowing to consult their library and herbarium to consult literature related to the present research work.

This study would not have been possible without the co-operation of Forest Department for providing the permission to work in the Dehra Dun Forest Division. I am very grateful to Dr. Venita Joshi for her valuable suggestions, encouragement and persistent assistance in data analysis and enthusiastic support at all times throughout this work. I would like to express my sincere gratitude and love to many of my friends and colleagues, Dr. Prakriti Dobhal, Dr. Smriti Sawan, Dr. Suman Lata Bist, Dr. Rashmi Bijalwan, Dr. Monika Vats, Dr. Ranjeet Kaur, Mr. Arvind Chauhan, Mr. Vishamber Joshi, Mr. Manmohan Rawat, Mr. Gautam Mandal and Mrs. Seema Manwal for encouragement & co-operation during the work.

I am highly obliged to my father Mr. Mohommad Nasir and my mother Mrs. Afroz Jahan who remained as a constant source of inspiration and my sisters Ms. Gulista Naaz, Mrs. Tarannum Naaz and Mrs. Tabassum Naaz for their quiet and strong support, encouragement, cooperation and love during the preparation and compilation of the thesis. The successful accomplishment of this study owes its proportion to my dear brother Mr. Mohd. Rashid and Mr. Mohd. Tahir for rendering their help in every step from beginning till end during the course of my research.

Finally, I wish to thank all those whose names have not figured but have supported, encouraged and helped me to grow.

(Mohommad Shahid)


Forests as they are an important natural ‘brake’ on climate change sequester and store more carbon than any other terrestrial ecosystem. The main carbon pools in forest ecosystems are the living biomass of trees and understorey vegetation and the dead mass of litter, woody debris and soil organic matter. The carbon stored in the aboveground living biomass of trees is typically the largest pool. Thus, estimating aboveground forest biomass carbon is the most critical step in quantifying carbon stocks and fluxes from forests.

India is a large developing country known for its diverse forest ecosystems and is also a mega-biodiversity country. Forest ecosystems in India are critical for biodiversity, watershed protection, and livelihoods of indigenous and rural communities. The National Communication of the Government of India to the UNFCC has reported that the forest sector is a marginal source of CO2 emissions. India has formulated and implemented a number of policies and programmes aimed at forest and biodiversity conservation, afforestation and reforestation. All forest policies and programmes have implications for carbon sink and forest management.

A number of studies highlighting carbon stocks of India forests at macrolevel utilizing Remote Sensing & Geographic Information System techniques have gained momentum. However, Carbon stock at micro level is still lacking and in view of this, the present study is an attempt to assess the vegetation, biomass and carbon stock of three ranges of Dehra Dun Forest Division.

The present work is discussed under seven chapters. Chapter-I is general introduction about the Plant Diversity, Structure and the role of Forests in Carbon Sequestration. It also incorporates the review of literature for critical analysis of the work. Chapter-II is study site, deals with the three ranges (Barkot Range, Lachchiwala Range and Thano Range) of the Dehra Dun Forest Division of the valley portion of the district of Dehra Dun which is located in the Southwestern part of the state of Uttarakhand, India. Chapter-III is about physical and chemical characteristics and organic carbon content of soil of the study area. Chapter-IV discusses the plant diversity. Chapter-V describe about the association of plant species and the forest structure in the study area. Chapter-VI deals about the Biomass contribution and the Carbon pool in the different forest types of study area. Forest Type maps of the study developed through Remote Sensing and Geographical Information System are depicted in the chapter VI. Chapter VII has covered the summary conclusion of the present study. A list of references in the text is enlisted at the end of the work.


2.1 Meteorological Data of Dehradun during Study Period (2010)

2.2 Meteorological Data of Dehradun during Study Period (2011)

3.1 Water Holding capacity (WHC), Moisture, pH & Conductivity of the soil from different forest types of various Study Sites.

3.2 Nitrogen, Potassium and Phosphorus of the soil from different forest types of the various study sites.

3.3 Organic Carbon and Organic Matter of the soil from various Study Sites.

3.4 Mechanical Characteristic of the soils from the different forest types of various study sites.

3.5 Soil Organic Carbon Density in different forest types of study sites

4.1 Floristic Diversity at various study sites

4.2 Tree Diversity with blooming period from the Study Area

4.3 Shrub Diversity with blooming period from the Study Area

4.4 Herb Diversity with blooming period from the Study Area

4.5 Dominant ranks of Taxa from the Study Area

5.1 Distribution Analysis of Herb species in Barkot Range

5.2 Distribution Analysis of Herb species in Lachchiwala Range.

5.3 Distribution Analysis of Herb species in Thano Range.

5.4 Distribution Analysis of shrub species in Barkot Range.

5.5 Distribution Analysis of shrub species in Lachchiwala Range.

5.6 Distribution Analysis of shrub species in Thano Range.

5.7 Distribution Analysis of Tree species in Barkot Range.

5.8 Distribution Analysis of Tree species in Lachchiwala Range.

5.9 Distribution Analysis of Tree species in Thano Range.

5.10 Diversity Index of Herbs at various study sites.

5.11 Diversity Index of Shrubs at various study sites.

5.12 Diversity Index of Trees at various study sites.

5.13 Clustering of Herb species in various study sites.

5.14 Clustering of Shrub species in various study sites.

5.15 Clustering of Tree species at various study sites.

6.1 Volume equations used for computation of above ground volume of different tree species.

6.2 Mean Wood Density used in the present study.

6.3 Organic Matter Availability & Carbon Stock of the Dry Deciduous Forest in Barkot Range.

6.4 Organic Matter Availability & Carbon Stock of the Moist Deciduous Forest in Barkot Range.

6.5 Organic Matter Availability & Carbon Stock of the Pure Sal Forest in Barkot Range

6.6 Organic Matter Availability & Carbon Stock of the Dry Deciduous Forest in Lachchiwala Range.

6.7 Organic Matter Availability & Carbon Stock of the Moist Deciduous Forest in Lachchiwala Range.

6.8 Organic Matter Availability & Carbon Stock of the Lachchiwala Pure Sal Forest in Lachchiwala Range.

6.9 Organic Matter Availability & Carbon Stock of the Dry Deciduous Forest in Thano Range

6.10 Organic Matter Availability & Carbon Stock of the Moist Deciduous Forest in Thano Range

6.11 Organic Matter Availability & Carbon Stock of the Pure Sal Forest in Thano Range.

6.12 Organic Matter Availability & Carbon Stock of the Pure Pine Forest in Thano Range.

6.13 Organic Matter Availability & Carbon Stock of the Degraded Forest in Thano Range.

6.14 Organic Matter Availability & Carbon stock of the Scrub in Thano Range

6.15 Total Carbon Pool in different Forest Types of Study Area.

6.16 Comparison of Volume, Biomass and Carbon of various forest types with present study.


2.1 Location Map of the District Dehra Dun

2.2 Location Map of the Doon Valley

2.3 Ombrothermic diagram showing the climatological data of the study site during 2010.

2.4 Ombrothermic diagram showing the climatological data of the study site during 2011.

3.1 Comparison of Soil Organic Carbon Density in different Forest Types of Study Sites.

4.1 Taxonomic Ranks of Various Growth Forms in the Study Area.

4.2 Tree Diversity of the Study site at various Ranks of Taxa.

4.3 Percentage Contribution of the Shrub Genera Diversity at the rank of family.

4.4 Percentage Contribution of the Shrub Species at the rank of family

4.5 Genera and Species representation of the Herb species at the rank of family.

4.6 Diversity of herbs at the taxonomic rank of Family, Genera & Species in three forest ranges.

4.7 Diversity of shrubs at the taxonomic rank of Family, Genera & Species in three forest ranges.

4.8 Diversity of trees at the taxonomic rank of Family, Genera and Species in three forest ranges.

5.1 Dominance – Diversity curve of the Herbs at various Study Sites.

5.2 Dominance – Diversity curve of the Shrubs at various Study Sites

5.3 Dominance – Diversity curve of the Trees at various Study Sites

5.4 Classification of Herb Species on the basis of TWINSPAN

5.5 Classification of Shrub Species on the basis of TWINSPAN.

5.6 Classification of Tree Species on the basis of TWINSPAN

6.1 Methodology for the preparation of Forest type maps.

6.2 False Color Composite Map of District Dehra Dun

6.3 Forest Type Map of Study Area (Barkot Range, Lachchiwala Range, Thano Range)

6.4 Forest Type Map of Barkot Range

6.5 Forest Type Map of Lachchiwala Range.

6.6 Forest Type Map of Thano Range.

6.7 Study Area with Study Sites & major characteristics of sub-site.

6.8 Organic Matter availability and Carbon Stock in Different Forest Types of Barkot Range.

6.9 Organic Matter availability and Carbon Stock in Different Forest Types of Lachchiwala Range.

6.10 Organic Matter availability and Carbon Stock in Different Forest Types of Thano Range.

6.11 Total Biomass and Carbon Stocks in Dry Deciduous Forests in the three ranges of the study site.

6.12 Total Biomass and Carbon Stocks in Moist Deciduous Forest of all the three ranges of the study site.

6.13 Total Biomass and Carbon Stocks in Pure Sal Forests of all the three ranges of study site.

6.14a % Contribution of Biomass of Shorea robusta in Dry Deciduous Forest in Barkot Range

6.14b % Contribution of Biomass of Shorea robusta in Moist Deciduous Forest in Barkot Range

6.15a % Contribution of Biomass of Shorea robusta in Dry Deciduous Forest of Lachchiwala Range

6.15b % Contribution of Biomass of Shorea robusta in Moist Deciduous Forest of Lachchiwala Range.

6.16a % Contribution of Biomass of Shorea robusta in Dry Deciduous Forest of Thano Range.

6.16b % Contribution of Biomass of Shorea robusta in Moist Deciduous Forest of Thano Range

6.16c % Contribution of Biomass of Shorea robusta in Degraded Forest of Thano Range.

6.16d % Contribution of Biomass of Shorea robusta in Scrub Forest of Thano Range


2.1 Road Leading towards forest at Barkot Range

2.2 A Termetarium : Unique feature of Sal Forests of Doon Valley

2.3 Shorea robusta Tallest Tree of the Doon Valley Forests

2.4 Structure of Forest at Lachchiwala Range

2.5 General View of Forest at Thano Range

2.6 Inner View of the Pure Sal Forest at Barkot Range

2.7 A General View of the Moist Deciduous Forest at Lachchiwala Range

2.8 Moist Deciduous Forest at Barkot Range

2.9 ‘Seasonal Rau’ through the Sal Forest of Doon Valley

2.10 General View of the Forest at Lachchiwala Range

2.11 Fuelwood Collection from the Barkot Forest

2.12 Gujjars Dwelling in the Forest at Lachchiwala Range

2.13(A-D) Biotic pressure – fuelwood & fodder dependency, unrestricted cattle grazing

2. 13(E-F) Biotic pressure – Habitat Destruction through trampling

2. 13(G-H) Biotic pressure – Collection of Pterospermum acerifolium and Rorippa nasturtium-aquaticum

2. 13(I) Biotic pressure – Dumping of the non degradable wastes

2. 13(J) Biotic pressure - Collection of Fuelwood from Lachchiwala Range

4.1(A-D) Tree diversity of Barkot Range

4.2(A-C) Tree diversity of Lachchiwala Range

4.3(A-D) Shrub diversity of Thano Range

4.4(A-D) Shrub diversity of Lachchiwala Range

4.5(A-D) Herbaceous diversity of Barkot Range

4.6(A-D) Herbaceous diversity of Thano Range

4.7(A-B) Herbaceous Diversity of Lachchiwala Range

4.8(A-B) Orchids of Lachchiwala Range

4.9(A-B) Invasive species of Thano Range



A forest is defined as an ecosystem or assemblage of ecosystems dominated by trees and other woody vegetation. The living parts of a forest include trees, shrubs, vines, grasses and other herbaceous (non-woody) plants, mosses, algae, fungi, insects, mammals, birds, reptiles, amphibians, and microorganisms living on the plants and animals and in the soil. These interact with one another and with the non-living part of the environment - including the soil, water, and minerals, to make up what we know as a forest. Plant communities covering large areas of the globe provide goods and services like, carbon-sink, oxygen-release, habitat, and soil-retention functions. Therefore, Earth's forests constitute one of the most important aspects of our biosphere. They provide many of the benefits like habitat, quality water, recreation, climatic amelioration and wood products. The plants and animals that make up a forest are inter-dependent and often essential to its integrity.

A plant community is a complex assemblage of plant species which interact with each other as well as with the elements of their environment and is distinct from adjacent assemblages. A plant community is not a static entity rather it may vary in appearance and species composition from location to location and also over time. This overall appearance is created by the particular species present, as well as their size, abundance, and distribution relative to one another. Community structure is inclusive of all plants that occur in the tree, sapling and shrub, and herbs. Community structure and distribution are dictated by the delicate balance of environmental factors: soils, climate, topography, geography, fire, time, and humans and other living beings. The study of floristic composition and phytosociological attributes are useful for comparing one community with the other from season and year to year. Plant that growing together have mutual relationship among themselves and with the environment (Mishra et al., 1997). Plant community plays a pivotal role in sustainable management by maintaining biodiversity and conserving the environment (Farooquee & Saxena, 1996).

The science of ecology with the use of remote sensing and GIS tool is highly useful to derive quantitative and qualitative information about ecosystem biodiversity and ecosystem dynamics. On the short time span the degraded areas for conservation, vegetation type map, biomass and other important parameters can be studied. Satellite remote sensing and GIS has emerged as a vital tool in understanding and monitoring the spatial and structural changes in vegetation and other earth surface features (Pant and Kharkwal, 1997; Pant and Singh, 1992).

Biodiversity is an essential component of ecosystem, where population of species interacts with each other and with their abiotic environment to form a community of organism that is relatively stable over time. Biodiversity is the diversity among living organisms in terrestrial, marine, and other aquatic ecosystems and the ecological complexes of which they are part. They help to determine the boundaries of ecosystem (Gaston, 2000). They are essential for maintaining environmental balance and health of an ecosystem. The species composition and characteristics of a forest understorey depend to a great extent on both past and present events, including the frequency and intensity of disturbances.

The biological diversity that forest contains and the ecological functions they have are boon to mankind. The goods and the ecosystem services provided by them could be summarized below under supporting, regulatory, cultural and provisioning role. Supporting roles include foundation of ecosystems through structural, compositional, and functional diversity. Regulatory roles through the influence of biodiversity on the production, stability and resilience of ecosystems. Cultural roles include the aesthetic, spiritual, and recreational elements of biodiversity. Provisioning roles include direct and indirect supply of food, fibre, water etc.

Biomass forms the entire energy source in the ecosystems. It is the largest energy source in India also. It can be potentially used as fuel. The quantity of biomass is the result of the difference between production through photosynthesis and consumption by respiration and harvest processes. Terrestrial ecosystems of India are extensively studied for plant biomass, productivity and carbon estimations using ecological methods.

Biomass can be defined as the total amount of live organic matter and inert organic matter (IOM) aboveground and belowground in tons of dry matter per unit area (individual plant, hectare, region or country) in a particular ecosystem. Or in other words it can be defined as the total amount of living organic matter in trees expressed as oven-dry tons per unit area. It is referred to as biomass density when expressed as mass per unit area, e.g. tons per hectare. Forest biomass consists primarily of above-ground (stems, branches, leaves) and below-ground (and roots) tree components; other woody vegetation; and mosses, lichens and herbs. The total biomass for a region or country is obtained from the product of biomass density and the corresponding area of forests. Only small portion of the forest biomass is consisted of animal biomass. The addition of biomass over a time is called as productivity. It is the rate of production of biomass. It can be also be referred as the gain in weight which the total number of a species in a specified area or the total number of all living organisms in a specified area, accumulates in a given period of time.

Several methods have been used to estimate forest biomass. There are two main approaches for estimating biomass are (a) destructive (conventional method) and (b) nondestructive. Destructive methods can further be categorized into (i) by harvesting of all materials in an unit area, (ii) by harvesting average tree size (girth or height) classes, or (iii) by harvesting of individuals over a wide range in size and establishing the relationship between biomass and easily measurable plant parameters, such as diameter/ girth and/or height (Roy & Shirish, 1996). Non-destructive methods involve application of component wise equations for different species, through sampling of tree components like bole, branch, twig and leaves. In last couple of decade’s satellite remote sensing has been successfully used for biomass and productivity estimation. (Chabbra et. al., 2002) has used three main approaches to estimate the forest biomass for large areas (nation, continents and even globe): a) biomass estimates using mean biomass density from ecological studies b) for Indian and global estimates, field inventory of growing stock and biomass expansion factors are used c) spatial modeling approach in geographic information system using spatial data bases of physiography, climatic, soil and forest distribution and models of biomass productivity. Satellite remote sensing technique provides a synoptic view of the object which can be effectively utilized for deriving valuable information at regional and global level. Remote sensing images are useful in the estimation of aboveground biomass.


The greenhouse effect was described as early as 1827 by the French scientist Fourier. At Fourier´s time, the greenhouse effect was discussed mainly with view on its role for maintaining a life-sustaining environment on the earth. In 1896, a Swedish chemist, Svante Arrhenius made a prediction of climate change due to human activities. Over, 100 years now after this prediction, the world is aware that carbon dioxide (CO2) emissions particularly those from fossil fuel burning are increasing and causing global warming.

The First World Climate Conference in 1979 was one of the first major international meetings on the issue of climate change (UNFCCC, 2003a). A result of this conference was the increased support of research on the scientific basis of climate change which finally led to the establishment of the Intergovernmental Panel on Climate Change (IPCC) in 1988. The findings of the First and Second Assessment Report of the IPCC published in 1990 and 1996 concluded that the concentration of greenhouse gases in the atmosphere was rising due to human activities and that this would lead to rising temperatures and a human-induced climate change (Grubb et al., 1999). The Third Assessment Report of the IPCC published in 2001 reinforced the conclusions of the earlier reports, stating that the global average surface temperature has increased over the 20th century by about 0.6° C, and, that there is evidence that most of the warming observed over the last 50 years is caused by anthropogenic activities (IPCC, 2001).


In 1992, the INC adopted the United Nations Framework Convention on Climate Change (UNFCCC) which was subsequently opened for signature at the United Nations Conference on Environment and Development in the same year. The UNFCCC entered into force on 21 March 1994 (UNFCCC, 2003a).

A framework sketching basic rules and including legally binding commitments for a set of industrialized countries and countries with economies in transition - now known as the Kyoto Protocol - was adopted at COP 3 in Kyoto, Japan in December 1997. In the Kyoto Protocol, member countries have agreed to reduce their overall greenhouse gas emissions by at least 5% below 1990 levels in the first commitment period (2008- 2012). The three flexible mechanisms of the Kyoto Protocol – Joint Implementation (JI), the Clean Development Mechanism (CDM) and emissions trading are supposed to lead to an efficient compliance with the Kyoto commitments. The first two allow Parties with emission targets to conduct emission reduction or sink enhancement projects in other countries and use the resulting emission credits for compliance with their commitments. Emission trading creates an international market on which emission allowances and credits can be traded.


Forests store large quantities of carbon i.e. below ground (soil) and above ground (vegetation). Through photosynthesis and respiration they exchange large quantities of carbon with atmosphere. For photosynthesis trees or plants absorb a portion of electro-magnetic radiation called photosynthetically active radiation (PAR). By the activity of the photosynthesis this absorbed energy is utilized to produce organic matter in plants. The organic matter stored constitutes the biomass of the plant.

Carbon circulates among the oceans, terrestrial biosphere and atmosphere. In addition, human activities, such as fuel combustion and deforestation, affect the carbon dioxide (CO2) concentration of the atmosphere (IPCC, 2001; Grace, 2004). Growing trees and other vegetation capture CO2 from the atmosphere and combine it with water, further producing sugars and carbohydrates. Meanwhile, it has been assumed that mature forests act as a carbon stock in which net exchange is close to nil, although this assumption has been questioned recently (Carey et al., 2001; Pregitzer and Euskirchen, 2004).

Quantification of forests as carbon sinks has been a challenge, and these estimates involve high degrees of uncertainty (Grace 2004) and discrepancies between methods (Houghton, 2003). The terrestrial sink amounted to 1.9 Pg of carbon annually in the 1980s, while carbon source due to deforestation was 1.7 Pg of carbon annually (IPCC, 2001). These estimates are based on various studies and models. Houghton (2003) suggested that the various sink estimates obtained with different methods were not due to high levels of uncertainty, but simply to incomplete counting of pools.


Biomass Proportions of Trees

Theories on the allocation rules of carbohydrates can be used for quantifying biomass of trees at various scales, e.g. tree, stand and region. The functional balance theory (Davidson, 1969) states plants balance between shoot and root biomass. This theory underlines the correlation between the nitrogen uptake of roots and carbon assimilation of foliage. The basis of the theory according to Davidson (1969) is that the carbon and nitrogen are used at a constant ratio and that the assimilation of carbon and nitrogen must be in balance with this use. The pipe model theory was proposed by Shinozaki et al., (1964), they claimed that the sapwood area at a certain height is proportional to the foliage biomass above that height. This theory has been widely applied and further developed. Mäkelä, (1990) showed that the total sapwood area of primary branches also correlates with tree foliage. These dependencies are often used in models that describe canopy structure and its function (Mäkelä and Vanninen, 1998).

Stand-level biomass proportions

Stand-level biomass is an aggregation of single-tree biomass. Destructive biomass measurements are conducted at the tree-level and the selection of sample trees is done based on certain criteria. Biomass measurements at the stand-level do not really exist and therefore up-scaling from tree to stand-level is needed. When this up-scaling is done one must assume that the biomass of a sample tree represents well the biomass of a stand.

A pool of resources is available for the vegetation at the stand-level, and an individual tree acquires resources according to its competitive status among other trees, while the sum of resources at the stand-level is rather constant, affected by use or by external input. In growth and yield studies the productivity of a site is measured by the dominant height that has been achieved at a certain stand age. This variable describes the fertility of soil and also the ability of trees to transport water to the canopy. This relationship of height and stand age aggregates a wide range of effects that influence the growth of trees (Assmann, 1970) and reflect the overall resources of a site.

Remote sensing can be used with process-based models to quantify the net primary production of forests (NPP) (Myneni et al., 2001; Nemani et al., 2003). The advantage of this approach is that it can cover large areas with a uniform method, while the disadvantages are that it indirectly measures carbon and is not able to quantify the understorey or belowground biomasses. On the other hand, this method requires extensive ground surveys to calibrate reflectance values from images with actual biomass and/or NPP.

Forest inventory-based approaches to estimate carbon stocks and flows use the NFI (national forest inventory) or other sampling networks that cover a wide range of conditions across a country or region. The output variables of traditional forest inventories are forest area and stem volume, and the latter is then converted to biomass and carbon. If other pools in addition to carbon of living biomass are to be quantified, then turnover rates can be applied to estimate the litter flux to soil (Kurz and Apps, 1999, Liski et al., 2002). The flux of understorey vegetation litter to soil should also be quantified. After estimating all litterfall components, one can estimate the changes in soil carbon stock through the soil model. The concepts of inventory-based approach that cover all these 5 carbon pools specified by IPCC (2003) were presented by Kurz and Apps (1999) and more recently by Liski et al., (2002).


Soil carbon stocks are built up during time spans of tens of thousands years. The vegetation produces organic matter (by litter and mortality), which is thereafter decomposed by soil flora and fauna. Small fractions of this organic matter are left to accumulate and form more permanent carbon compounds. Inert carbon forms are also stored in soils during forest fires. Soil carbon stocks and the changes that occur in them are the results of climate, soil properties, litter quality and litter production by vegetation; the more productive the site is the more litter is fed into soil (Schimel et al., 1994, Liski and Westman, 1997). Tamminen (1991) also found an increasing trend in soil carbon according to site type, indicating that more fertile soils had more carbon. Organic matter that is fed into soil originates from vegetation and soil microbes, which constitutes mainly carbohydrates, lignin, nitrogen compounds, fats and minerals, The decomposition of organic matter in boreal soils is mainly driven by temperature (Mikola 1960, Kirschbaum, 1994; Liski and Westman 1997, Liski et al., 2005), while also nutrient availability and drought has impacts to the decomposition (Berg and Matzner, 1997).


Carbon sequestration is one such instrument in the environmental toolbox that has great potential for success as a market mechanism to help ameliorate some major environmental problems and provide income for sustainable development initiatives. Though it is a relatively new topic in the international arena, carbon sequestration and the role of carbon sinks in emissions trading plays a vital role in addressing the dangers of global warming. The Kyoto Protocol and its three flexibility mechanisms: Joint Implementation, the Clean Development Mechanism (CDM) and Emissions Trading, have been criticized over the years for their inefficiency, weak structure and lack of enforcement mechanisms. However, while many of the criticisms are valid, the basic objectives are worthy of further exploration and analysis.

In recent times, the world’s forests have been cut at a rapid rate both for timber and to make room for agriculture and other developments. If deforestation is not controlled, the world will lose most of its forests in the next several decades. Modern forest practices have developed in response to this crisis, as a means of halting forest destruction while still providing valuable forest products and protecting and preserving the habitats of many endangered species of plants and wildlife. Likewise carbon sequestration has become a valuable tool in helping to reduce deforestation and redefining the ‘value products’ of forests, for example, placing value on the carbon capture potential of this endangered resource.

Unlike other sequestration options, which have short duration times before carbon is automatically released back into the atmosphere, forest sequestration projects have the potential to accumulate carbon over decades and centuries. Additionally forest-based projects can sequester large amounts of carbon within relatively short periods (decades). The short fall is that large amounts of carbon can also be released very quickly into the atmosphere if there are forest fires. What makes this approach attractive is that forests which are already being utilized through sustainable forestry practices, wildlife habitat protection and for recreation can provide carbon sequestration as an additional benefit. The option also remains to utilize forests strictly to sequester carbon which has the additional benefit of helping to promote and increase biodiversity.

Though CO2 concentrations are fairly uniform around the globe, higher concentrations can be found in the Northern Hemisphere than in the Southern, which can be indicative of the higher fossil-fuel consumption in the northern regions.

Forests sequester and store more carbon than any other terrestrial ecosystem and are an important natural ‘brake’ on climate change. When forest are cleared or degraded, their stored carbon is released into the atmosphere as carbon dioxide (CO2). The main carbon pools in forest ecosystems are the living biomass of trees and understorey vegetation and the dead mass of litter, woody debris and soil organic matter. The carbon stored in the aboveground living biomass of trees is typically the largest pool and the most directly impacted by deforestation and degradation. Thus, estimating aboveground forest biomass carbon is the most critical step in quantifying carbon stocks and fluxes from forests.

India is a large developing country known for its diverse forest ecosystems and is also a mega-biodiversity country. Forest ecosystems in India are critical for biodiversity, watershed protection, and livelihoods of indigenous and rural communities. The National Communication of the Government of India to the UNFCC has reported that the forest sector is a marginal source of CO2 emissions. India has formulated and implemented a number of policies and programmes aimed at forest and biodiversity conservation, afforestation and reforestation. All forest policies and programmes have implications for carbon sink and forest management.

The Himalaya although cover only 18% of the geographical area of India, account for more than 50% of the India’s forest cover, and 40% of the species endemic to the India sub-continent (Maikhuri et al. , 2000).Various programmes have been implemented, for the conservation of biological resources in the Indian Himalaya under the protected area network by establishing 3 biosphere reserves, 18 national parks and 71 wild life sanctuaries (covering 9.2% area of the Indian Himalaya). Enforcement in these protected areas has created a lot of conflicts between local people and protected area managers due to restrictions imposed on the traditional usufruct rights of the local people. These conflicts are causing major hurdles to achieve the goal of biodiversity conservation for which the protected areas have been setup (Gadgil, et al. , 1993; Nautiyal, 1998; Maikhuri et al. , 2000).

The types of afforestation and reforestation activities likely to be eligible under clean development mechanism (CDM) of Kyoto protocol include planting trees of farm lands, raising mixed species plantations, assisted natural regeneration of area with potential root stock, planting orchards etc. The land area that could potentially be brought under CDM projects in India, particularly under non-forest and wasteland categories could be large and may vary between 66-130 million ha (Ravindranath and Murthy, 2003).

There are two ways that terrestrial ecosystems can contribute to carbon sequestration:

1. Ecosystems can be protected from land-use changes to assure that carbon sequestration patterns and activities for that ecosystems type will continue.
2. Ecosystems can be manipulated to increase carbon sequestration beyond naturally occurring levels, including carbon stored in harvested products.

Documenting current carbon stocks and expected changes establishes a baseline against which to demonstrate possible increased carbon sequestration through forest management; it also provides an opportunity to benefit from the transfer of carbon credits.


A comprehensive review of literature is prerequisite for any scientific investigation. It helps in great deal in defining the problem, formulating the scientific, deciding methodologies and discussing the findings of the studies.

Distribution and density of flowering plant vary in different habitats and different countries. Mc Neely et al., (1990) estimated that world’s 12 countries: Australia, Brazil, China, Columbia, Ecuador, India, Indonesia, Madagascar, Malaysia, Mexico, Peru and Zaire together hold 70 per cent of its total flowering plant diversity and these have been termed “Mega Diversity” Countries. It is interesting to note that seven of the above megadiversity countries figure among the 10 most species rich countries of the world (Groombridge, 1992; Bisby et al., 1992).

India is a vast country with a rich diversity of biotic resources. The rich biodiversity is largely due to a varied physical environment, latitude, longitude, altitude, geology and climate. The geographical area of India is about 329 million ha and its coastline stretched to over 7000 Km. Almost all shades of climate from hot arid in Thar Desert to arctic in the Himalaya with all intermediate gradations occur here. The rainfall varies from about 100 mm in Thar Desert to over 5,000 mm at Mawsmai in Meghalaya. Though the area of the country is only 2.4 percent of the world landmass, yet it supports over 11 percent of all known species of plants.

Angiosperms comprise ca 17,000 species (excluding infraspecifc categories) under 2984 genera and 247 families and represent roughly 7 per cent of the world’s angiospermic flora (Hooker, 1872-1897; Karthikeyan et al., 1989; Sharma and Balakrishnan, 1993; Sharma and Sanjappa, 1993; Hajra et al., 1995a, 1995b, 1996; Singh et al., 2000; Karthikeyan, 2000; Sharma and Joshi, 2009).

Human disturbance to ecosystems is a phenomenon of general interest and concern throughout the world. The nature, extent and magnitude of these disturbances are staggering. Vitousek et al., (1997) estimated that between one-third and one-half of the earth’s land surface has been transformed by human action. Black (1991) noted that tropical ecosystems alone were being destroyed at the rate of 25 million hectare per year. A study by the United Nations Environment Programme, designed specifically to quantify the extent of disturbance and soil degradation on a world-wide basis, found that approximately 2000 million hectare per year (Oldeman, 1994). Of the total land area of 329 million hectare of India, Khoshoo (1992) reported 175 million hectare prone to severe erosion loss; out of which 129 million hectare could be classified as waste land.

The structure of a vegetation unit depends upon the species composition and their relative number. A community or a vegetation unit is an assemblage or population living in a prescribed area or physical habitat i.e., an aggregation of organisms in space and time, which forms a distinct ecological unit. The species, which extent major controlling influence within a community by virtue of their number, size, production or other activities are described as ecological dominants (Odum, 1971).The forests are fascinating and interesting in its structure and a variety of ecological features, which has attracted the attention of many ecologists, researchers and foresters etc., since time immemorial.

The composition of forest vegetation and community of moist Bhabar and Tarai Sal forest were examined by Mishra et al., (2000) on four different aspects. Namely, North-East, North-West, South-East and South-West in Pauri Garhwal to understand the growth behaviour of Shorea robusta individuals under different microclimatic conditions which was found dominating on all aspects with maximum IVI, density, frequency and TBC values and has reflected random distribution patterns, the highest TBC values of this species was recorded on NE facing slope and highest Cd on SW facing slope, where minimum diversity persisted. The maximum accumulation of organic matter was noticed on NE aspect due to occurrence of mature Sal stand.

Community structure and diversity of the forest of Garhwal Himalaya was studied by Kumar et al., (2000) and analyzed density, total basal cover, diversity index, beta diversity, equability and distribution pattern for tree, sapling, seedling and shrub strata of the forests and the results were compared with those for the other studies in the Himalayan region. Two sites in the sub-tropical zones of Pauri Garhwal Himalayas at an elevation of 900-1300 m amsl were studied for the structure and diversity of forest by Kumar et al., (2004).

Ram et al., (2004) assessed the plant diversity in the six forest types of Uttaranchal Central Himalaya, India and observed that Pinus roxburghii forest is generally pure with low total species richness of shrubs and herbs, while mixed, broadleaved forests reported highest total species richness. Bisht and Lodhiyal, (2005) studied certain soil and vegetation characteristics of forest occurring in Nainital district of Kumaon. Total 17 species were recorded.

Remotely sensed imagery has long been recognised as a fundamental input data for biodiversity estimate and conservation. In particular remotely sensed classified data have been used in a number of monitoring tasks such as resource assessment and management (Defries and Townshend, 1999; Lauver and Whistler, 1993 and Viedma and Meliá, 1999), landscape change detection (Carmel and Kadmon, 1999; De Blois et al., 2001, Peroni et al., 2000 and Rocchini, 2006), mapping of environmental phenomena (Fuller, 1998, Lauver, 1997 and Read, 2003), vegetation mapping (Phinn et al., 1996; Abeyta and Franklin, 1998; and Franco-Lopez, 2001).

Application of remote sensing technology for forest cover type mapping is well established and known. Satellite data have been used for forest cover type and forest cover density mapping both by visual and digital interpretation methods. The applicability of RS and GIS to forest density evaluation, its conservation and proper management has been well demonstrated (Tiwari, 1994; Tiwari et al., 1995; Roy et al., 1996 a, b; Tan and Jishan, 2001). Disturbance has become a widespread feature all over the Himalayan region (Singh and Singh, 1992), therefore the understanding of the ecological processes and biotic and natural pressures can help to know and relate the persistence of plant communities. The rates of the loss of the highly diverse biodiversity of Himalayan mountains pose a great threat to the global biodiversity and it is assumed that after several decades only about 10% of the land area in one off the biodiversity hotspot of India will remain dense forested (Pandit et al., 2006).

Vegetation is an important part of the ecosystem that interprets the effects of the total environment (Billings, 1952). Vegetation structure of an area reveals the sum total of habitat conditions of that area. In past few years many attempts have been made to examine the vegetation demography (Saxena et al., 1978, 1982; Tiwari and Singh, 1981; Pandey and Singh, 1981; Saxena and Singh, 1982; Joshi et al., 1985, 1999; Bankoti et al., 1992; O’Connor, 1993; Lieberman et al., 1996). The spatial pattern of community organisation and its dynamics with time have been widely studied (Botkin et al., 1972; Sprugel, 1976; Hubbel, 1979; Auble et al., 1994; Tockner and Stanford, 2002). Many workers (Champion, 1923; Suri 1933; Puri, 1943; Meher-Homji, 1964;Gaur and Satyanarayan, 1967; Kuruvilla, 1967; Champion and Seth, 1968; Mehrotra, 1973; Raizada, 1978; Singh and Singh; 1987; Sharma and Kumar, 1992; Baduni and Sharma, 1996; have made their noteworthy contributions on the ecology and distribution of flowering plants of different regions of India.

In India, Himalayan region has a diverse vegetation composition due to different physiognomic condition and altitudinal range associated with different climatic and biotic features. The available records of Hooker (1872-1897), Duthie (1893-94 and 1906), Osmaston (1922), Dudgeon (1923), Dudgeon and Kenoyer (1925), Smythe (1938), Gupta (1955, 57, 62, and 66), Ghildiyal (1957), Rao (1960), Rau (1961, 63, 64, 74 and 75), Dey et al. (1968), Khera, et al. (2001), Suyal et al (2010) and others mainly reported the floristic composition of Himalaya. Purohit (1977) has studied the floristic pattern of Garhwal Himalaya at different altitude. Supriya and Yadav (2006) observed the floristic diversity assessment of tropical evergreen forest. Mani (1978) described the variation in floristic components mainly due to gradation in the climate. Joshi (1982), Semwal (1984), Bijalwan (2009), Vats (2009) have also given the floristic account of high altitudes. Flora and biological spectrum of the Khoh Valley have described by Rajwar (1980), Rajwar and Gupta (1981, 1988 and 1992).

The history of plant exploration in the Doon Valley goes back to 18th century and may be divided in three successive periods.

First Period (upto 1840): T. Hardwick (1751-1835), a European was the first to collect plants from North-West (NW) Himalayas. With the establishment of Residences at Dehra Dun, Mussoorie, Shimla and other places along the trade routes and after the restoration of Botanical Garden at Saharanpur by Hastings in 1820, there has been an extensive exploration of NW Himalaya and surroundings plains. The first two superintendents, Govan and Royle, particularly the latter, obtained the earliest collection. J.F. Royle (1799-1858), second superintendent of Saharanpur Garden, was a pioneer phytogeographer of NW Himalaya. He collected plants from Dehra Dun which he described in his excellent treatise, Illustration of the Botany of the Himalayan Mountains (1833-1840).

Second Period (1840-1905): As the collections has been accumulated by various explorers from different part of India and other adjacent regions and also with the collection made by J.D. Hooker and T. Thomson over a period of 3-5 years (1848-1851), particularly from Eastern Himalaya, the publication of Flora of India was initiated. The first outcome was Flora Indica (1855) by J.D. Hooker. Stewart and Brandis (1874) published the Forest Flora of NW and Central India, wherein frequent references were made to Dehra Dun collections. A detailed account of Dehra Dun forests was also given in his article “The forest of the outer NW Himalaya” which appeared in The Indian Forester (13:51-70,1887). In the year 1882, Sir George King published a list of Plants of Garhwal, Jaunsar- Bawar and Dehra Dun. J.F. Duthie (1906) was one of the ablest plant explorers and phytogeographer of North and North West India and also made intensive collection in and around Dehra Dun. He published (1903-1929) in 3 volumes his Flora of the Upper Gangetic Plains and of the adjacent Siwalik and Sub-Himalayan Tracts, wherein Dehra Dun formed the northern-most boundary.

Among other important collectors of this period were D.Brandis (1874), King (1882), and U Kanjilal (1901). Kanjilal published Forest Flora of School Circle, which was another landmark in the phytogeography of Dehra Dun. This was revised and enlarged by B.L. Gupta (1928) as Forest Flora of Chakrata, Dehra Dun and Saharanpur Forest Divisions of United Provinces. Thus, this period may be described as Duthie’s period.

Third Period (1905 and onwards): During this period, Forest Research Institute, Dehra Dun became an active centre of research in India, especially in dealing with exploration and publications of forest flora. Several botanists made valuable collections and published their work on this region. Some of the important and noteworthy publications appeared during this period were Raizada (1976) Supplementary lists to the Flora of the Upper Gangetic Plain, in which he dealt Dehra Dun Plants extensively on the basis of his collection as well as collection gathered by P.C. Kanjial, R.N Parker, B.L. Gupta, Sri Ram, Sohan Lal, H.G. Champion. The other important plant collectors of this area are Raizada and Sahni (1966), Rao (1969), R.D. Gaur (1999), Joshi et al., 1999; Dhyani and Joshi (2007); Sharma and Joshi (2008, 2009), Joshi and Joshi (2008); and Dobhal et al., 2010.


Forests play a major role in the global carbon cycle and contain a substantial proportion of the world’s terrestrial biodiversity. Forests also provide a broad range of other ‘ecosystem services’ - the benefits people obtain from ecosystems. These ecosystem services include supporting services such as nutrient cycling, soil formation and primary productivity; provisioning services such as food, water, timber and medicine; regulating services such as erosion control, climate regulation, flood mitigation, purification of water and air, pollination and pest and disease control; and cultural services such as recreation, ecotourism, educational and spiritual values. Deforestation and forest degradation in the tropics and sub-tropics have a large negative impact on terrestrial biodiversity, and thus on the provision of those ecosystem services that are most closely linked to biodiversity.

A larger number of studies have been undertaken in estimating forest biomass and nutrient cycling in nearly all forest types of this country. A very comprehensive review has been given by Cannell (1982) who compiled the primary production data for nearly all countries, dealing with individual tree species, occurring in the respective countries. Duvigneaud (1970) has also reviewed forest ecosystems and its various aspects, while functioning of ecosystems at the primary production level have been reviewed by Eckardt (1968). Other important contributions to forest ecosystems are by Misra (1968), Young (1967, 1971, 1973, and 1976). Riechle (1970, 1981), Golley & Golley (1972) and Swift et al., (1979).


People often think of biodiversity as a list of species without necessarily considering the roles that species perform in ecosystems. However, in recent decades, there has been an improved understanding of important linkages between species and the way that ecosystems function.

A sub-set of ecosystem ‘functions’ (also called ‘ processes ’) are ecosystem services that benefit humans including pollination, nitrogen-fixation and carbon storage. Despite considerable debate over early experimental methods (Huston,1979,1994) and the relevance of biodiversity experiments for the biodiversity crisis, there is now consensus that ecosystem functioning increases with increasing biodiversity (Chapin et al., 2000). This relationship can be obscured by strong environmental effects and appears to be limited via competition for resources or other mechanisms at high levels of species richness (e.g., in natural forests) and depending on the scale. Biodiversity promotes functioning via three main mechanisms. The first is resource (or niche) complementarily (Loreau et al., 2003), whereby different species use different resources or the same resources in different ways, resulting in reduced competition. This positive effect of biodiversity becomes stronger when multiple resources are available (Loreau et al., 2002) and over large spatial and temporal scales because species partition resources in space or time. Complementarily depends on species performing functions in different ways, thus, the strongest increase in functioning is observed when species have different functional traits. Furthermore, there is evidence that turnover of species among regions (Loreau et al., 2003) and evenness in the abundance of different species also promote ecosystem functioning. The second mechanism is facilitation, whereby species provide resources or alter the environment (e.g., legumes), enabling other species to perform better. Facilitation is often used as a silvicultural tool to grow desired shade-tolerant tree species beneath faster growing pioneer tree species. The final mechanism is the ‘sampling effect’, whereby there is a higher probability that a high productivity species will be included in a large group of species compared to a smaller group. Thus, individual species effects differ and are highly important and so the loss of key species can impede forest functioning (Baker et al., 2004).


The sequestration and storage of carbon is one of the many ecosystem services supported by biodiversity. Carbon is initially sequestered through photosynthesis before being transferred to one of a number of terrestrial pools including above-ground biomass (AGB), dead wood, litter, roots (below-ground biomass ) and soil. Species can affect the long-term balance of carbon gains and losses in ecosystems through different components of the carbon cycle, including the magnitude, turnover and longevity of carbon stocks in soils and vegetation.

Several studies have established the fact that carbon sequestration by trees could provide relatively low cost net emission reduction (Adams et al., 1993; Richards et al., 1993; Callaway and Mc Carl, 1996; Stavins, 1999).

The main carbon pools in tropical forest ecosystems are the living biomass of trees and understorey vegetation and the dead mass of litter, woody debris and soil organic matter. The carbon stored in the aboveground living biomass of trees is typically the largest pool and the most directly impacted by deforestation and degradation. Knowledge of the aboveground living biomass density is useful in determining the amount of carbon stored through photosynthesis in the forest stands.

Above-ground biomass (AGB) is a useful measure for assessing changes in forest structure (Brown et al ., 1999) and an essential aspect of studies of carbon cycle (Cairns et al., 2003; Ketterings et al, . 2001). Several studies have suggested that the impacts of disturbance, and recovery from disturbance may account for either the increase in stem turnover rates, or the increase in above-ground biomass. It is well known that the large number of published biomass equations can result in substantial variation in stand-level AGB estimates (Araujo et al., 1999; Baker et al., 2004; Chambers et al. 2001) , because AGB is strongly correlated with trunk diameter (Brown, 1997; Brown & Lugo, 1992; Clark et al., 2001).

Worldwide, numerous ecological studies have been conducted to assess carbon stocks based on carbon density of vegetation and soils (Atjay et al., 1979; Olson, 1963). The results of these studies are not uniform and have wide variations and uncertainties probably due to aggregation of spatial and temporal heterogeneity and adaptation of different methodologies. IPCC (2000) estimated an average carbon stock of 86 tonnes per hectare 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 2005. Each cubic metre of growing stock equals different amounts of biomass and carbon (in biomass) in different regions. Globally, each cubic metre of growing stock equals, , on an average, 1 tonne of above-ground biomass, 1.3 tonnes of total biomass and 0.7 tonnes of carbon in biomass (FAO, 2006).

India is a large developing country known for its diverse forest ecosystems and megabiodiversity. It ranks 10th amongst the most forested nations of the world (FAO, 2006) with 23.4 percent (76.87 million ha) of its geographical area under forest and tree cover (FSI, 2009). With nearly 173,000 villages classified as forest fringe villages, there is obviously a large dependence of communities on forest resources. Thus, it is very important to assess the likely impacts of projected climate changes on forests, to develop and implement adaptation strategies both for biodiversity conservation and protection and for safeguarding the livelihoods of forest dependent people, and to ensure production of round wood for industrial and commercial needs.

The biomass carbon stock in India’s forests was estimated at 7.94 MtC during 1980 and nearly half of that after a period of 100 years (Richards and Flint, 1994). The first available estimates for forest carbon stocks (biomass and soil) for the year 1986, are in the range of 8.58 to 9.57 GtC (Ravindranath et al., 1997; Chabra and Dadhwal, 2004). As per FAO estimates (FAO, 2006), the total forest 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 stable, and new forest carbon accretions coming from the current initiatives of afforestation and reforestation programme.

Indian forests are a major tropical forest ecosystem constituting nearly 67.83 million hectares (Mha), 20.66% of the geographical area of country (329 Mha, FSI, 2003). India’s geographical area constitutes 2.4% of the world land area and about 2% of the global forests, while supporting 16% of the world’s human population. Indian forests are known to be one of the richest in terms of vegetation types and species diversity. The revised forest type classification of Champion and Seth (1968) is the most widely used classification systems for Indian forests. They classified the forests into five major groups based on climatic factors. These major groups have been further divided into 16 types based on temperature and moisture contents.

Studies of Indian forests as part of the national forest carbon balance (Ravindranath et al., 1997; Haripriya, 2000; Chhabra and Dadhwal, 2004; Manhas et al., 2006; and Kaul et al., 2009) have examined strata and state/regional forest area changes. Their results range from the finding that the forests are a major source to the finding that they are a sink for atmospheric carbon. Using a simple book keeping approach, Chhabra and Dadhwal (2004) estimated that the cumulative net carbon flux from Indian forests (1880–1996) due to land use changes (deforestation, afforestation and phytomass degradation) was 5.4 Pg C with the mean annual net C flux as 9.0 Tg (1 Tg = Tera gram, 1012 g) C yr−1. Kaul et al., (2009) indicated that the Indian forest sector acted as a small source of carbon during the period 1982–1992 with the annual net C flux due to land use changes estimated as 5.65 Tg C yr-1. For India, a marginal net sequestration of 5 Tg C for the reference year 1986 and of 1.09 Tg C for 2002 has been estimated by Ravindranath et al., (1997) and Kaul et al., (2009) respectively. The mitigation potential of the forestry sector, based on a biomass demand based scenario, using short or long-term commercial forestry option is estimated to be 122 Tg C for the period 2000-2012.


Weathering of rocks into soil is a another major sink for carbon dioxide as carbon dioxide is combined into soil carbonates when sufficient moisture is present. Thus, the ability of soil formation to act as a carbon sink depends a great deal on the presence of vegetation.

Soil organic carbon (SOC) also plays a very significant role in the global carbon cycle, as it is the largest terrestrial carbon pool. Soil can be a source (CO2, CH4 and N2O) or sink (CO2 and CH4) of greenhouse gases depending on land use and management (Lal and Singh,2000). The total SOC pools in Indian forests have been estimated as 4.13 Pg C (top 50 cm) to 6.81 Pg C (top 1 m soil depths) for the period 1980-1982 (Chhabra et al., 2002). Based on the national and regional soil carbon densities, Indian forest SOC pool estimates are in the range 6.7 to 9.8 Pg C (Jha et al., 2003). Based on different forest types in India, the national average of soil organic carbon per ha in forest soil was estimated as 183 Mg C ha-1 (Jha et al., 2003).

Carbon (C) storage in forest ecosystems involves numerous components including with its environment. Because of the large areas involved at regional/global scale, forest soils play an important role in the global C cycle (Detwiler and Hall, (1988); Bouwman and Leemans, (1995)). Land use change causes perturbation of the ecosystem and can influence the C stocks and fluxes. In particular, conversion of forest to agricultural ecosystems affects several soil properties but especially soil organic carbon (SOC) concentration and stock.


1 . To determine the floristic diversity and dominance status at selected study sites.
2. To determine the structure and composition of plant community in selected sites.
3. To analyse the soil organic carbon content in the study sites.
4. To estimate the biomass availability
5. To analyse the carbon stocks of the study sites.



The state of Uttarakhand is situated in the northern part of India and shares an international boundary with China in the north and Nepal in the east. It has an area of 53483 km2 and lies between latitude 28° 43′ and 31° 28′ N and longitude 77° 34′ and 81° 03′ E. The state has a temperate climate except in the plain areas, where the climate is tropical. The average annual rainfall of the state is 1550 mm and temperatures range from sub-zero to 43°C (FSI, 2009). Of the total geographical area of the state, about 19% is under permanent snow cover, glaciers and steep slopes where tree growth is not possible due to climatic and physical limitations (FSI, 2009). The recorded forest area of the State is 34,691 km2, which constitutes 64.79% of its geographical area (FSI, 2009).

The study area is the Dehra Dun Forest Division of the valley portion of the district of Dehra Dun which is located in the Southwestern part of the state of Uttarakhand, India (Fig 2.1). The study has been conducted in the three ranges (Barkot Range, Lachchiwala Range and Thano Range). The word Doon represents the boulder valley that runs parallel to and between the lesser Himalayan range and the Shivalik range. The Doon valley is located in the Siwalik Himalayas, lying between latitudes 29°55 and 30°30 N and longitudes 77°35 and 78°24 E. It is about 20 km wide and 80 km long saucer-shaped valley with a geographical area of ca. 2100 km2 (Fig 2.2) The area is bounded by the river Ganga in the east and river Yamuna in the West. The northern boundary is formed by Mussoorie hills whereas the Shiwalik mountains form the southern boundary of the valley.

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Fig. 2.1 : Location Map of the District Dehra Dun

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Fig. 2.2: Location Map of the Doon Valley


The chief features of interest in the physiography are the numerous river-beds locally known as “Raus” which cut up the valley. These are dry for the greater part of the year, leaving exposed single beds, often of great width. They rise in the hills, forming torrents in the rainy season, bringing down a great quantity of debris. The strata through which they flow consists of sandstone, gravel and conglomerates, with occasional thin bands of clay of loose and easily denuded nature. The area is thus subjected to great erosive action by these rivers, resulting in continual change in the topography. By lateral erosion the rivers are constantly oscillating from side to side, denuding large areas and converting fertile land into single beds, with the formation of flood plains, which may become river terraces, as the beds of the streams are

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Plate 2.1 : Road Leading towards forest at Barkot Range

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Plate 2.2 : A Termetarium : Unique feature of Sal Forests of Doon Valley

lowered by vertical erosion. From time to time these rivers change their courses, converting fertile forest land into a single bed. We may assume, without going very far wrong, that the whole of the area under study has been subjected to this denuding action of rivers, and has been at one time or another in the condition of single bed. In fact the nature of the strata indicates that they have been formed by sub-aerial denudation of the Himalayas, that is to say, they consist of debris brought down and deposited by river action.

The climate of the area under study is practically the same throughout: but we do not find the area occupied throughout by one uniform type of forest characteristics of such climate. There are forests of quite distinct characters e.g.

a) Moist Shiwalik Sal Forest
b) Moist Bhabhar Dun Sal Forest
c) Dry Shiwalik Sal Forest

These differences in the vegetation are due to local differences in the soil, caused by the erosive action of the rivers: or, in other words, to changes in the topography. The main distribution of plants is due to climate, especially rainfall and temperature, but the local differences are due to local factors, especially soil with its water content, aspect, gradient etc.

The physiography is continually changing where erosive rivers are actively at work, as in the Dun, and these changes are followed by changes in the vegetation. If there were no forces at work in changing the physiography, the struggle for existence would uniformly lead to the formation of a more or less uniform type of forest throughout the region with the same climate. Within a certain region having the same climate throughout, there is a steady development of the vegetation towards one type, characteristic of that particular climate. Thus in the Dun, the highest stage in the development of the vegetation is the Sal (Shorea robusta) forest, and all other forests are gradually developing towards this final stage. They have not attained this stage long ago is due to the constant changing of the physiography, caused by the denuding action of the rivers.

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Fig. 2.3 : Shorea robusta Tallest Tree of the Doon Valley Forests

As already stated, it may be presumed that the whole of the Dun has been at one time or other in the condition of single bed, but a large proportion of the area is now covered with sal forest. The sal is a tree of an exacting nature, requiring good fertile moist soil, with good drainage, and is a species severely damaged by frost when young, so much that it cannot come up in open places except under the protection of other trees. The sal forests cannot, therefore, have come directly into existence on open exposed alluvial single soils. Although it is not possible to actually observe the successive stages in the development of the sal forests in the same area, as the changes are gradual and may occupy a long period, yet an examination of the existing types of forests and of what is now taking place leaves little doubt as to the stages through which the sal forests is ultimately developed.


The valley is longitudinal, intermontane, synclinally depressed bouldery filled with coarse clastic fan – Doon gravel of late Pleistocene and Holocene (Puri 1950) . The valley is uniformly oriented in the NW–SE direction, with the Lesser Himalayas in the northeast and the Siwalik ranges in the southwest. The Lesser Himalayan Range, which forms the northeastern boundary of the valley, is part of the Great Himalayan Ranges, while the Shivalik Range, forming the southwestern boundary of the valley, is a younger formation of debris swept from these mountain ranges. The continuous accumulation of debris resulted in a gentle slope of the Shivaliks towards the Himalayan ranges and in turn formed a longitudinal shallow valley that is higher than the Great Plains immediately to the south of the Shivaliks. The valleys are called “Doons” and are often cut by streams that drain the interior mountains. In some places the doons disappear with the merging of the Shivaliks and the Lesser Himalaya. Because of the elevation of the doons, and the short distance over which the drainage from the upper parts of the valley meets the water courses in the plains, the landscape is characterized by deep gorges and gullies that cut through the unconsolidated strata that from the floors of these valleys.

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Plate 2.4 : Structure of Forest at Lachchiwala Range

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Plat 2.5 : General View of Forest at Thano Range

On the basis of rock and soil types the valley can be divided into three distinct belts, the Lesser Himalayan belt, the Doon proper, and the Shivalik belt. At the base, the Himalayan belt consists of high grade limestones and shales, and these changes gradually into dolomite covered by a shallow layer of topsoil. The Doon Valley proper is covered by unstratified mixed pebbles and boulders with very little matrix. The Doon gravels of the Pleistocene age are covered by a thin mantle of soil, except in the river beds. These gravels are highly pervious and form a poor underground water reservoir. The boulder bed of the drainage channels provides the underground course for most streams originating in the Himalayas. Many of these disappear deep into the boulder bed for long stretches and reappear near the edge of the plateau where they find impermeable clay formation. The natural abundance of water in the valley, particularly in the eastern part, is described as follows:

At present the eastern Doon is a vast reservoir or feeder of the Ganga. The forests are intercepted with running streams rising from innumerable springs in every direction and the ground is literally oozing with water. The volume of water poured into the Ganga by the Suswa and Song is immense.”

As almost straight-line from Mohand pass to Dehra Dun, onwards to Rajpur, divides the valley into the two sub-water sheds, one draining eastward into the Ganga and the other watershed into the Yamuna. The two major hydrologic basins of the valley are the Ganga in the southeast with the Song and Suswa as its main tributaries and the Yamuna in the northwest with the river Asan as its main tributary.

Several workers have described the geomorphology (Medlicoot, 1964; Nossin, 1971; Nakata, 1972) and the lithostratigraphy (Thakur, 1995) of the Doon valley in the past. The present study initiated in the sal forests developed on the post-Shiwalik Doon gravels (older Doon gravel, younger Doon gravel and alluvium) of late Pleistocene to Recent age (Singh et al., 2001) originating from the erosional action of the rivers and streams. Of the three geological units, the younger Doon gravels occupy the central and a major part of the valley. They occur in the form of large fans, formed by the reworking of the oldest Doon gravels, also known as the principal Doon fans (Bartarya, 1995) . A poorly sorted mixture of clay, sand and very large boulders characterize this region. In addition to this, the soft sandstones and the quartzite boulders and pebbles are intermixed with the alluvial and colluvial deposits (Sharma et al., 1989). The alluvium consists of very fine clay and partly sand. The soils of the Doon Shiwalik were developed on the deep alluvial deposits with parent material derived from the Doon alluvium. It consists of accumulated beds of clays, boulders, pebbles and sand with the admixture of water-borne small to big size stones in the subsoil in varying proportions (Yadav et al., 1973; Singhal et al., 1982;). This alluvium was deposited by the multilateral, multibraided channel system.



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Title: Assessments Of Plant Diversity, Biomass And Carbon Pool In Natural Forests Of Doon Valley Using Geospatial Technology