Impact of Coal Mining on Vegetation: A Case Study in Jaintia Hills ...

<strong>Impact</strong> <strong>of</strong> <strong>Coal</strong> <strong>Mining</strong> onVegetation: A Case Studyin Jaintia Hills District <strong>of</strong>Meghalaya, IndiaKiranmay SarmaFebruary, 2005

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIATable <strong>of</strong> ContentsAcknowledgements......................................................................................................................IAbstract...................................................................................................................................... IITable <strong>of</strong> Contents......................................................................................................................IIIList <strong>of</strong> Figures............................................................................................................................ VList <strong>of</strong> Tables ............................................................................................................................VI1. Introduction.........................................................................................................................11.1. Introduction.................................................................................................................11.2. Research Objectives....................................................................................................41.3. Research Questions.....................................................................................................41.4. Research Hypothesis...................................................................................................41.5. Organisation <strong>of</strong> the Study ...........................................................................................51.6. Literature Review .......................................................................................................52. Study Area ..........................................................................................................................92.1. Study Area ..................................................................................................................92.2. Geology.......................................................................................................................92.3. Physiography and Drainage......................................................................................132.4. Climate......................................................................................................................132.5. Soil............................................................................................................................142.6. Natural Vegetation....................................................................................................142.7. Population.................................................................................................................142.8. <strong>Coal</strong> Deposits and <strong>Coal</strong> Fields..................................................................................142.8.1. Bapung Area .....................................................................................................152.8.2. Lakadong Area..................................................................................................152.8.3. Jarain-Shkentalang............................................................................................152.8.4. Lumshnong .......................................................................................................162.8.5. Malwar-Musiang-Lamare.................................................................................162.8.6. Sutnga ...............................................................................................................162.8.7. Ioksi ..................................................................................................................162.8.8. Chyrmang .........................................................................................................162.8.9. Mutang..............................................................................................................162.9. Present Study Area ...................................................................................................173. Materials and Methods .....................................................................................................213.1. Study Area ................................................................................................................213.2. Materials ...................................................................................................................213.3. Research Methods.....................................................................................................213.3.1. Study Initiation .................................................................................................213.3.2. Pre-Field Work .................................................................................................213.3.3. Field and Post-Field Work................................................................................213.3.3.1. Radiometric Correction ............................................................................263.3.3.2. Visual Interpretation .................................................................................263.3.3.3. Change Analysis .......................................................................................263.3.3.4. Forest Fragmentation Analysis.................................................................263.3.3.5. Phytosociological Analysis.......................................................................26III

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIA4. Results and Discussion .....................................................................................................294.1. Community Characteristics ......................................................................................294.1.1. Floristic Composition .......................................................................................294.1.2. Density..............................................................................................................304.1.3. Dominance Pattern............................................................................................314.1.4. Species Diversity ..............................................................................................364.2. <strong>Impact</strong> <strong>of</strong> <strong>Coal</strong> <strong>Mining</strong> on Tree Population Structure ..............................................364.2.1. Density-Diameter Distribution .........................................................................364.2.2. Basal Cover.......................................................................................................384.3. <strong>Impact</strong> <strong>of</strong> <strong>Coal</strong> <strong>Mining</strong> on Species Distribution Pattern...........................................384.4. Change Detection......................................................................................................494.4.1. Land Use/ Land Cover Distribution and Changes............................................494.4.2. Changes in different land use/ land cover categories from 1975 to 2001 ........554.4.3. Forest Fragmentation........................................................................................605. General Discussion and Conclusions ...............................................................................655.1. Discussion and Conclusions .....................................................................................655.2. Review <strong>of</strong> Results and Discussion............................................................................675.3. Summary and Recommendations .............................................................................68References.................................................................................................................................70IV

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIAList <strong>of</strong> FiguresFigure 1.1: Rat-hole mining method - a crude mining technique is the sole method <strong>of</strong> coalextraction in the district (a). Damage to natural vegetation due to piling <strong>of</strong> coal (b).........4Figure 1.2: Landscape degradation (a) and damage to soil system (b) <strong>of</strong> the district due to coalmining.................................................................................................................................4Figure 2.1: Location <strong>of</strong> Jaintia Hills district in Meghalaya, India............................................10Figure 2.2: Geology <strong>of</strong> Jaintia Hills district (Geological Survey <strong>of</strong> India, 1974). ...................11Figure 2.3: Monthly average maximum and minimum temperature and rainfall in Jowai, thedistrict headquarters <strong>of</strong> Jaintia Hills (Mean <strong>of</strong> 1991 to 2001)..........................................14Figure 2.4: Location <strong>of</strong> the study area in Jaintia Hills district..................................................17Figure 2.5: Digital elevation model (m). ..................................................................................18Figure 2.6: Drainage in the study area......................................................................................19Figure 2.7: Settlement and road network..................................................................................20Figure 3.1: Landsat MSS FCC for the period 1975..................................................................22Figure 3.2: Landsat TM FCC for the period 1987....................................................................23Figure 3.3: Landsat ETM + FCC for the period 1999. ..............................................................24Figure 3.4: IRS-1D LISS-III FCC for the period 2001. ...........................................................25Figure 3.5: Conceptual framework <strong>of</strong> different coal mine impact zones. ................................28Figure 3.6: Paradigm for assessment <strong>of</strong> mining impact on vegetation.....................................28Figure 4.1: Dominance-diversity curves <strong>of</strong> trees in control and mined areas. .........................33Figure 4.2: Dominance-diversity curves <strong>of</strong> shrubs in control and mined areas. ......................34Figure 4.3: Dominance-diversity curves <strong>of</strong> herbs in control and mined areas. ........................35Figure 4.4: Density-diameter distribution <strong>of</strong> trees in different girth classes under control andmined areas. ......................................................................................................................37Figure 4.5: Basal area <strong>of</strong> tree species in control and mined areas............................................38Figure 4.6: Land use/ land cover in 1975. ................................................................................50Figure 4.7: Land use/ land cover in 1987. ................................................................................51Figure 4.8: Land use/ land cover in 1999. ................................................................................52Figure 4.9: Land use/ land cover in 2001. ................................................................................53Figure 4.10: Area under different land use/ land cover categories in different years. .............54Figure 4.12: Unsuccessful forest plantations were carried out by the Govt. Departments on themine spoils........................................................................................................................54Figure 4.13: Changes in different land use/ land cover categories in different years. .............56Figure 4.14: Changes <strong>of</strong> land use/ land cover from 1975 to 1987............................................57Figure 4.15: Changes <strong>of</strong> land use/ land cover from 1987 to 1999............................................58Figure 4.16: Changes <strong>of</strong> land use/ land cover from 1999 to 2001............................................59Figure 4.17: Areas under different fragmentation classes in different years............................60Figure 4.18: Forest fragmentation in 1975. ..............................................................................61Figure 4.19: Forest fragmentation in 1987. ..............................................................................62Figure 4.20: Forest fragmentation in 1999. ..............................................................................63Figure 4.21: Forest fragmentation in 2001. ..............................................................................64Figure 5.1: The Nepenthes khasiana (pitcher plant), an endangered species, threatened due toindiscriminate mining. ......................................................................................................65V

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIAList <strong>of</strong> TablesTable 2.1: Lithostratigraphic Succession <strong>of</strong> Jaintia Hills district.............................................12Table 2.2: <strong>Coal</strong> deposits (million tonnes) in different districts <strong>of</strong> Meghalaya .........................14Table 2.3: <strong>Coal</strong> production (’000 tonnes) and percentage in Jaintia Hills district <strong>of</strong> Meghalaya..........................................................................................................................................15Table 4.1: Species, generic and family compositions in different zones..................................30Table 4.2: Stand density as affected by mining in different zones...........................................31Table 4.3: Plant species with higher importance value index in control and mined areas.......32Table 4.4: Shannon-Weaver diversity index in control and mined areas.................................36Table 4.5: Proportion (%) <strong>of</strong> tree species under different distribution pattern in control andmined areas .......................................................................................................................39Table 4.6: Overall community structure <strong>of</strong> control and coal mined areas................................39Table 4.7: Density, basal area, importance value index and distribution pattern <strong>of</strong> trees,.......40shrubs and herbs in control stands............................................................................................40Table 4.8: Density, basal area, importance value index and distribution pattern <strong>of</strong> trees,.......41shrubs and herbs in zone-I ........................................................................................................41Table 4.9: Density, basal area, importance value index and distribution pattern <strong>of</strong> trees,.......43shrubs and herbs in zone-II......................................................................................................43Table 4.10: Density, basal area, importance value index and distribution pattern <strong>of</strong>...............45trees, shrubs and herbs in the zone-III......................................................................................45Table 4.11: Density, basal area, importance value index and distribution pattern <strong>of</strong> trees,shrubs and herbs in the zone-IV .......................................................................................46Table 4.12: Area (km 2 ) under different land use/ land cover categories in different years......49Table 4.13: Changes in land use/ land cover in different years................................................55Table 4.14: Area (km 2 ) and proportion (%) <strong>of</strong> different fragmentation classes in differentyears..................................................................................................................................60VI

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIA1. Introduction1.1. Introduction<strong>Mining</strong> tends to make a notable impact on the environment, the impacts varying in severity dependingon whether the mine is working or abandoned, the mining methods used, and the geological conditions(Bell et al., 2001). It causes massive damage to landscapes and biological communities <strong>of</strong> the earth(Down and Stock, 1977). Natural plant communities get disturbed and the habitats becomeimpoverished due to mining, presenting a very rigorous condition for plant growth. The unscientificmining <strong>of</strong> minerals poses a serious threat to the environment, resulting in the reduction <strong>of</strong> forest cover,erosion <strong>of</strong> soil in a greater scale, pollution <strong>of</strong> air, water and land and reduction in biodiversity(UNESCO, 1985). The problems <strong>of</strong> waste rock damps become devastating to the landscape aroundmining areas (Goretti, 1998).<strong>Mining</strong> operations, which involve extraction <strong>of</strong> minerals from the earth’s crust is second only toagriculture as the world’s oldest and important activity. In a sense, the history <strong>of</strong> mining is the history<strong>of</strong> civilization (Khoshoo, 1984). From the pre-historic days man has been interested about earth’smineral wealth. The crude stone implements <strong>of</strong> the early Paleolithic period, post-Neolithic pottery, theEgyptian pyramids, iron and copper smelting in various civilizations, and the modern steel-age are alltestimony <strong>of</strong> mining activities <strong>of</strong> man (Sarma, 2002). Natural resources have been over-exploited foralmost two centuries, without any concern for the environment.<strong>Coal</strong> was known as burning rock and believed to possess supernatural power (Sharan et al., 1994). Itwas known to the Chinese before Christian era and the Greeks knew about the use <strong>of</strong> coal in the 4 thcentury A.D. It was used as a domestic fuel in England in the 9 th century. The invention <strong>of</strong> the steamengine in England and the consequent industrial revolution in the 18 th century provided great impetusto coal mining. The demand for coal got further increased when coke made from bituminous coalbegan replacing charcoal in the iron ore smelting industries (Brown et al., 1975). Today coal is usedprimarily for producing electricity and, to a lesser extent, by heavy industries such as iron and steelindustries (Raven et al., 1993). <strong>Coal</strong> contains a significant amount <strong>of</strong> ferrous sulphate in the form <strong>of</strong>pyrites. The exposure <strong>of</strong> pyrite to atmospheric oxygen through the mining operation, brings about anoxidation process in which pyrite is converted into ferrous sulphate and sulphuric acid in the presence<strong>of</strong> bacteria. The sulphuric acid thus formed, lowers the pH <strong>of</strong> the soil and water in the terrestrial andaquatic environments, respectively, which affects the population and activity <strong>of</strong> organisms inhabitingthose environments. Chemicals released from the coal mines, overburden and tailings also containhigh concentration <strong>of</strong> metals such as Cu, Cd, Fe, Hg and Zn, which also affect the organismsadversely.The Indian sub-continent is replete with minerals and many states have rich coal resources. Soon afterindependence, India witnessed a spurt in the growth <strong>of</strong> heavy industries that needed a large amount <strong>of</strong>mining <strong>of</strong> coal and metals. Thus the mining operations in India began on a large scale in 1950s.Presently, in India, more than 80,000 ha <strong>of</strong> land are under various types <strong>of</strong> mining (Valdiya, 1988).<strong>Coal</strong> is the most abundantly available fossil fuel in India and provides a substantial part <strong>of</strong> energyneeds. It is used for power generation, supply <strong>of</strong> energies to industry as well as for domestic needs.1

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIAIndia is highly dependent on coal for meeting its commercial energy requirements. India ranks thethird largest coal producer <strong>of</strong> the world next only to China and USA. <strong>Coal</strong> mining in India was startedin the year 1774 in the state <strong>of</strong> West Bengal. At the beginning <strong>of</strong> 20th century, the total production <strong>of</strong>coal was just about 6 million tonnes per year. The production was 154.30 million tones in 1985-86 andit reached 298 million tonnes in the year 1997-98. The expectation to reach the production <strong>of</strong> coal by2000 A.D. was 417 million tonnes (<strong>Coal</strong> India, 1997).In north-east India, coal mining was initiated by Medlicott in 1869 and 1874. Some coal occurrencesin Jaintia Hills were examined by shallow drilling by Dias in 1962-63 and Goswami and Dhara in1963-64 (Bulletin <strong>of</strong> Geological Survey <strong>of</strong> India, 1969). Commercial exploitation <strong>of</strong> coal inMeghalaya started in the Khasi Hills during the 19th century. Since most <strong>of</strong> the coal deposits weresmall and isolated and it was not amenable for scientific mining to be conducted in the organizedsector and mining operations were left to the local miners to take up coal mining as a cottage industry.In due course <strong>of</strong> time, the tribal miners accepted coal mining as one <strong>of</strong> their customary rights. FromKhasi Hills these activities proliferated to other parts <strong>of</strong> the state, viz., Jaintia Hills and Garo Hills inthe beginning <strong>of</strong> the 1970s (Directorate <strong>of</strong> Mineral Resource, 1992).Meghalaya, one <strong>of</strong> the seven states <strong>of</strong> north-east India, is bestowed with rich natural vegetation as wellas large reserve <strong>of</strong> mineral resources. During the last few decades, there have been phenomenalincrease in mining <strong>of</strong> coal, limestone, sillimanite and clay causing large-scale destruction anddeterioration to the environment <strong>of</strong> the state. The forests and the mining are intimately linked. Theforests are the greatest victims <strong>of</strong> the mining activities, which can be gauged from the denudation <strong>of</strong>the forest cover in all the mine belts. Because <strong>of</strong> the complex landholding systems, and exclusiverights <strong>of</strong> land owners on land resources as guaranteed under 6 th Schedule <strong>of</strong> Indian constitution, verylittle governmental control can be exercised on the lands in Meghalaya. <strong>Mining</strong> is done undercustomary rights and are not covered by any mining acts, rules or any other legislations. Noenvironmental acts and rules can be enforced in these areas. As a result, in most parts <strong>of</strong> the state coalis being indiscriminately mined in most unscientific manners, causing large-scale damage to thenatural ecosystems (Tiwari, 1996).<strong>Coal</strong> deposits <strong>of</strong> the state occur as thin seams, which range in thickness from 30 cm to 1.5 m insedimentary rock, sandstone and shale <strong>of</strong> the Eocene age (Guha Roy, 1991). The coal deposits arefound along the southern fringe <strong>of</strong> the Shillong plateau extending over a length <strong>of</strong> 400 km. In the hills<strong>of</strong> Meghalaya, the coal bearing sedimentary formations are sub-horizontal to gently dipping in nature.It is estimated that there is 562.8 million tonnes <strong>of</strong> coal reserve in 20 major or minor depositsdistributed throughout the state. Some <strong>of</strong> the areas where extensive coal mining is going on within thestate are: Laitryngew, Cherrapunjee, Laitduh, Mawbehlarkar, Mawsynram, Lumdidon, Langrin,Pynursla, Lyngkyrdem, Mawlong-Shella-Ishamati in Khasi Hills, Bapung, Lakadong, Sutnga, Jarain,Musiang-Lamare and Ioksi in Jaintia Hills and West Darrangiri, Siju, Pyndengru-Balphakram, SelselaBlock in Garo Hills.The total deposit <strong>of</strong> coal in Jaintia Hills district <strong>of</strong> the state is approximately 40 million tonnesspreading over patches <strong>of</strong> different sizes. The areas where coal mining is prominent are Bapung,Lakadong, Jarain-Shkentalang, Lumshnong, Malwar-Musiang-Lamare, Sutnga, Ioksi, Chyrmang andMutang. Bapung has the largest deposit <strong>of</strong> 34 million tonnes covering an area <strong>of</strong> 12 km 2 . The maincharacteristics <strong>of</strong> the coal found in Jaintia Hills are its low ash content, high volatile matter, high2

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIAcalorific value and comparatively high sulphur content. The coal is mostly sub-bituminous incharacter. The physical characteristics <strong>of</strong> the coal <strong>of</strong> Jaintia Hills district are that it is hard, lumpy,bright and jointed. Composition <strong>of</strong> the coal revealed by chemical analysis indicates moisture contentbetween 0.4 to 9.2 percent, ash content between 1.3 to 24.7 percent, and sulphur content between 2.7to 5.0 percent. The calorific value ranges from 5,694 to 8230 kilo calories/kilogram (Directorate <strong>of</strong>Mineral Resources, 1985).The mining activities in Jaintia Hills district are small scale ventures controlled by individual owners<strong>of</strong> the land. <strong>Coal</strong> extraction is done by primitive sub-surface mining method commonly known as ‘rathole’mining. In this method, the land is first cleared by cutting and removing the ground vegetationand then pits ranging from 5 to 100 m 2 are dug into the ground to reach the coal seam. Thereafter,tunnels are made into the seam sideways to extract coal which is first brought into the pit by using aconical basket or a wheel barrow and then taken out and dumped on nearby unmined area. Finally, thecoal is carried by trucks to the larger dumping places near highways for its trade and transportation.Entire road sides in and around mining areas are used for piling <strong>of</strong> coal which is a major source <strong>of</strong> air,water and soil pollution. Off road movement <strong>of</strong> trucks and other vehicles in the area causes furtherdamage to the ecology <strong>of</strong> the area. Hence, a large extent <strong>of</strong> the land is spoiled and denuded <strong>of</strong> vegetalcover not only by mining but also by dumping and storage <strong>of</strong> coal and associated vehicular movement(Figure 1.1). <strong>Mining</strong> operation, undoubtedly has brought wealth and employment opportunity in thearea, but simultaneously has lead to extensive environmental degradation and erosion <strong>of</strong> traditionalvalues in the society. Environmental problems associated with mining have been felt severely because<strong>of</strong> the region’s fragile ecosystems and richness <strong>of</strong> biological and cultural diversity. The indiscriminateand unscientific mining, absence <strong>of</strong> post mining treatment and management <strong>of</strong> mined areas are makingthe fragile ecosystems more vulnerable to environmental degradation and leading to large scale landcover/ land use changes. The current modus operandi <strong>of</strong> sub-surface mining in the area generates hugequantity <strong>of</strong> mine spoil or overburden (consolidated and unconsolidated materials overlying the coalseam) in the form <strong>of</strong> gravels, rocks, sand, soil, etc., which are dumped over a large area adjacent to themine pits (Figure 1.2). The dumping <strong>of</strong> overburden and coal destroys the surrounding vegetation andleads to severe soil and water pollution. Large-scale denudation <strong>of</strong> forest cover, scarcity <strong>of</strong> water,pollution <strong>of</strong> air, water and soil, and degradation <strong>of</strong> agricultural lands are some <strong>of</strong> the conspicuousenvironmental implications <strong>of</strong> coal mining in Jaintia Hills. The district <strong>of</strong> Jaintia Hills has been mostextensively extracted in terms <strong>of</strong> coal, among all the districts <strong>of</strong> the state (Das Gupta, 1999). As aresult <strong>of</strong> this, in many parts <strong>of</strong> the district there has been conversion <strong>of</strong> the original lush greenlandscape into mine spoils. The crude and unscientific ‘rat-hole’ method <strong>of</strong> mining adopted by theprimitive operators lead to the degradation <strong>of</strong> the landscape (Sarma, 2002).The studies related to the floristic composition <strong>of</strong> the mining areas have been conducted by severalworkers in different parts <strong>of</strong> the world (Cornwell, 1971; Fyles et al., 1985; Game et al., 1982; Singhand Jha, 1987; Prasad and Pandey, 1985). An understanding <strong>of</strong> the impact <strong>of</strong> mining on theenvironment particularly on vegetation characteristics is a prerequisite. However, only a few studies(Lyngdoh et al., 1992; Lyngdoh, 1995; Pandey et al., 1993; Das Gupta, 1999; Das Gupta et al., 2002;Dkhar, 2002; Rai, 2002; Swer and Singh, 2004) have been conducted in this field <strong>of</strong> research in thecoal mine affected areas in Jaintia Hills district <strong>of</strong> Meghalaya. Here an attempt has been made to findout the impact <strong>of</strong> coal mining on the vegetation by using remote sensing and geographic informationsystem (GIS) techniques in Jaintia Hills district <strong>of</strong> Meghalaya.3

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIA1.5. Organisation <strong>of</strong> the StudyThe present thesis on “<strong>Impact</strong> <strong>of</strong> coal mining on vegetation: a case study in Jaintia Hills district <strong>of</strong>Meghalaya, India” has been divided into five chapters.1. Introduction2. Study Area3. Materials and Methods4. Results and Discussion5. General Discussion and Conclusions1.6. Literature ReviewEcosystem disturbance may be defined as an event or series <strong>of</strong> events that alters the relationship <strong>of</strong>organisms and their habitat in time and space. Ecosystem disturbance by mining is an evitable fall out<strong>of</strong> industrialization and modern civilization. With accelerating demand for fuel energy the world over,coal is certainly going to retain its place <strong>of</strong> primacy well in to the future. <strong>Mining</strong> <strong>of</strong> coal causesenormous damage to the flora, fauna, hydrological relations and soil biological systems. Destruction <strong>of</strong>the vegetal cover during the mining activity is invariably accompanied by an extensive damage andloss <strong>of</strong> the system. The disturbed and haphazardly mixed infertile, consolidated and unconsolidatedmaterials overlying a coal seam are known as overburdens. These overburdens when dumped inunmined areas in the vicinity <strong>of</strong> the coal mines create mine spoils. Nutrient deficient sandy spoils aregenerally hostile to plant growth and the regevetation and reclamation strategies other than naturalcolonization <strong>of</strong> mine spoils are very tardy process. Some important researches on the study <strong>of</strong> theimpact <strong>of</strong> mining on the vegetation that relevant to the present study are being reviewed here.<strong>Coal</strong> mine spoils when freshly tipped has a great range <strong>of</strong> particle size ranging from large pieces <strong>of</strong>shale to silt and clay (Molyneux, 1963). These mine spoils represent extremely rigid substrata for plantgrowth and development. Colonization, establishment and maintenance <strong>of</strong> vegetation on these spoilsare enormously difficult. Among the factors which hinder the growth <strong>of</strong> plant species on these spoils,acidity merits special attention. Extreme acidity is caused due to the oxidation <strong>of</strong> iron pyrites(Chadwick, 1973). Continued acidification for many years may lead to die back <strong>of</strong> well establishedvegetation (Costigan et al., 1981). Besides acids, coal mine spoils contain toxic levels <strong>of</strong> solubleelements such as Fe, Al, Mn and Cu. The physical factors which limit plant establishment and survivalinclude high temperature, moisture stress (Richardson, 1975), soil particle size (Down, 1974) andcompaction (Hall, 1957, Richardson, 1975). Soil fertility is also a major factor regulating plant growth.The two limiting nutrient on coal mine spoils are nitrogen and phosphorus (William, 1975). Theshortage <strong>of</strong> organic matter is attributed to the absence <strong>of</strong> litter (Schafer et al., 1980). Power (1978)considers soil physico-chemical characteristics like texture, pH, electrical conductivity, soluble Ca,Mg, Na, B, cation exchange capacity, exchangeable cations, gypsum and calcium carbonateequivalents as being crucial to the prediction <strong>of</strong> plant growth potential <strong>of</strong> mine overburdens with waterholding capacity and infiltration rates as the other important variables. Bradshaw et al. (1975) and Belland Ungar (1981) found high temperature and low moisture <strong>of</strong> surface coal mine spoils to be importantfactors limiting plant growth.The colonization <strong>of</strong> plant species on coal mine spoils is influenced by the particle size <strong>of</strong> the soilderived from the overburden and coal mine wastes. This was conclusively proved by Richardson et al.(1971). They reported that with high clay content, the soils become water logged, whereas with high5

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIAsilt content, the soils become compact forming crust which <strong>of</strong>ten restrict seedling growth and entry <strong>of</strong>water and air into the soil system. pH is a major determinant in controlling plant growth onimpoverished lands such as mine spoils. The average value <strong>of</strong> pH is 3.5, which indicates the acuteacidity <strong>of</strong> the soil (Johnson and Bradshaw, 1977).Intensive studies on the vegetation characteristics <strong>of</strong> the mined areas have been undertaken in differentparts <strong>of</strong> the globe. The development <strong>of</strong> an ecosystem on china-clay wastes was studied by Dancer etal. (1977). The vegetation establishment on asbestos waste was studied by Moore and Zimmermann(1977). Saxena (1979) has provided a list <strong>of</strong> plant species for revegetation <strong>of</strong> gypsum, bentomite andfuller’s earth mined areas in Rajasthan. Revegetation <strong>of</strong> iron-ore mine areas <strong>of</strong> Madhya Pradesh wasstudied by Prasad in 1989 who observed better growth performance <strong>of</strong> Dalbergia sisso, Albizziaprocera, Pongamia pinnata etc. in the manured pits.The factors contributing to the early colonization <strong>of</strong> mine dumps have given considerable attention byvarious workers. Bradshaw (1983), Chadwick (1973), Byrnes et al. (1973) found natural succession oncoal mine spoils a slow process due to surface mining altering physico-chemical properties. Thesespoils present a special habitat where conditions are extremely unfavourable for plant growth andestablishment. Marrs and Bradshaw (1980) and Marrs et al. (1980 and 1981) studied the development<strong>of</strong> ecosystem <strong>of</strong> China clay waste. Iron mine tailings were studied by Leisman (1957) and Shetron andDuffek (1970). Floristic diversity <strong>of</strong> lead mining wastes was studied by Clarke and Clarke (1981), leadand zinc by Kimmerer (1984) and copper mining wastes by Goodman and Gemmel (1978) andVeeranjaneyulu and Dhanaraju (1990).Doerr and Guernsey (1956) dealt with the environmental effects <strong>of</strong> strip mining and undergroundmining, which create conspicuous landscape features and associated phenomena. Mukherjee (1987 and1988) described about the land degradation associated with surface and sub-surface mining. Chadwicket al. (1987) outlined the environmental implications <strong>of</strong> increased coal production and utilization.Chaudhury (1992) dealt with the impact on mining activities on environment and also the managementand protection <strong>of</strong> the mined areas.The ecology <strong>of</strong> the mined lands has been the subject <strong>of</strong> extensive study the world over (Bradshaw etal., 1986, Brenner et al., 1994, Rodrigues et al., 2004, Fretas et al., 2004, Wiegleb et al., 2001, Grant2003, Bell et al., 2001, Goretti 1998, Game et al., 1982). In India, Banerjee (1981), Singh and Jha(1987), Valdiya (1988), Saxena (1979), Mann and Chatterjee (1979), Prakash (1998), Soni et al.(1989) have made pioneering contributions to the ecology <strong>of</strong> Indian mines. In the context <strong>of</strong>Meghalaya, studies have been done by Lyngdoh et al. (1992), Uma Shankar et al. (1993), Lyngdoh(1995), Tiwari (1996), Rai (1996), Das Gupta (1999), Das Gupta et al. (2002), Sarma (2002), Rai(2002), Dkhar (2002) and Swer and Singh (2004).The state <strong>of</strong> Meghalaya is rich in mineral resources. The coal deposits occur as thin seams, whichrange in thickness from 30 cm to 1.5 m in sedimentary rocks, sandstone and shale <strong>of</strong> the Eocene age.The deposits <strong>of</strong> coal in the state are Cretaceous origin (Guha Roy, 1991). The unscientific mining <strong>of</strong>coal poses a serious threat to the environment (Dadhwal, 1999). <strong>Mining</strong> <strong>of</strong> coal causes massivedamage to landscape and biological communities. The natural plant communities are disturbed bymining activity because the mining environment alters the climatic and edaphic complexes <strong>of</strong> the plantcommunities leading to a drastic reduction in the plant growth (Down and Stock, 1977). Acute scarcity6

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIA<strong>of</strong> potable and irrigated water, pollution <strong>of</strong> air, water and soil, soil erosion, reduced soil fertility andloss <strong>of</strong> biodiversity are some <strong>of</strong> the manifestations <strong>of</strong> coal mining (Das Gupta et al., 2002).Rai (1996) involved in study <strong>of</strong> coal mining and environmental degradation with special reference tosoil, water and air pollution <strong>of</strong> Meghalaya. Sarma (2002) has studied the impact <strong>of</strong> coal mining on theenvironment <strong>of</strong> Nokrek biosphere reserve, Meghalaya. He analysed different phyto-sociologicalcharacteristics <strong>of</strong> the mined and unmined areas <strong>of</strong> the biosphere reserve. The impact <strong>of</strong> coal mining onecosystem health in Jaintia Hills district <strong>of</strong> Meghalaya was studied by Tiwari (1996) and Das Gupta etal. (2002) put efforts to give an ecological perspective <strong>of</strong> the district due to the impact <strong>of</strong> coal mining.Rai (2002) also alalysed the implication <strong>of</strong> coal mining on environment in the district. Dkhar (2002)studied the micro-landforms <strong>of</strong> the district, which were affected due to the sub-surface coal mining.Swer and Singh (2004) analysed the water quality and its availability in the coal mining areas <strong>of</strong> thedistrict. They also studied the impact <strong>of</strong> mining on the aquatic fauna and flora <strong>of</strong> the region. Das Gupta(1999) analysed the vegetal and microbiological processes in coal mining affected areas. In his studyvegetation changes on coal mine spoils in different years was carried out. Pandey et al. (1993) studiedvegetation and soil <strong>of</strong> the coal mining areas <strong>of</strong> the district. Physico-chemical properties in the aquaticsystem in the mining affected areas was analysed by Sharma and Das (1993). The study related to themicrobiology <strong>of</strong> soil and water bodies was carried out by Tiwari and Das Gupta (1993). Socioeconomic,anthropological and epidemiological impact <strong>of</strong> mining was studied by Mishra and Lyngdoh(1993) and Pathak and Dkhar (1993).There have been several major developments in the assessment <strong>of</strong> forest condition by visual methodsover the past decades. Remote sensing and GIS techniques are useful to identify the areas <strong>of</strong>degradation due to mining activity. These are important tools for studying the pattern <strong>of</strong> vegetationdynamics. The changes <strong>of</strong> land cover are invariably associated with mining <strong>of</strong> natural resources.Remote sensing provides multi-spectral and multi-temporal synoptic coverages for any area <strong>of</strong> interest.The satellite data provides a permanent and authentic record <strong>of</strong> the land-use patterns <strong>of</strong> a particulararea at any given time, which can be re-used for verification and re-assessment. Kushwaha (1990)explained the use <strong>of</strong> multi-time data in detecting changes in the forest cover. GIS provides the facilityto integrate multi-disciplinary data for dedicated interpretations in an easy and logical way. Thisintegrated approach proves to be time saving and cost-effective (Prakash and Gupta, 1998). Satellitedata has provided an important basis for vegetation mapping, monitoring and understanding ecosystemfunctions, primarily through the relationships between reflectance and vegetation structure andcomposition (Joshi et al., 2003). Kushwaha et al. (2000) studied the land area change and habitatsuitability analysis in the national park. Kushwaha and Kuntz (1993) analysed the changes in theenvironment in the tropical forests <strong>of</strong> north-east India by using multi-time remote sensing data.Airborne multi-spectral techniques are the most effective way to detect and monitor vegetationdamage at mine sites and have been used successfully by Singh Roy and Kruse (1991), King (1993)and Singh Roy (1995). Multi-spectral remote sensing technique can detect the vegetation damagecaused by the acid drainage from mine and mill tailings and waste rock and can monitor regenerationsuccess at sites undergoing restoration. Graham et al. (1994) used Principal Component Analysistechnique on Landsat Thematic Mapper images to monitor vegetation change in large areas affected byiron ore mining operation at Noranda, Quebec. The normalized difference vegetation index (NDVI) isan index that provides a standard method <strong>of</strong> comparing vegetation greenness between satelliteimageries. This can be used as an indicator <strong>of</strong> relative biomass and greenness (Boone et al., 2000,7

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIAChen, 1998). This is used to calculate primary production, dominant species, and anthropogenicimpact, and stocking rates with the help <strong>of</strong> field study (Ricotta et al., 1999; Paruelo et al., 1997).Prakash and Gupta (1998) studied the impact <strong>of</strong> coal mining on the land use changes by usingtemporal remote sensing data. Change detection analysis method was conducted in their study. Kosterand Slob (1994), Scheijbal (1995), Ghosh (1998), Rathore and Wright (1993) studied the changes andimpact on the land use/ land cover due to the mining activities. Goretti (1998) concluded the result thatthe vegetal cover got lost due to the spread out <strong>of</strong> waste materials haphazardly, which were coming outfrom the mines, in and around the coal mining.8

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIA2. Study Area2.1. Study AreaJaintia Hills district is located in the eastern most part <strong>of</strong> Meghalaya. It lies between 91°58'E to92°50'E longitudes and 25°02'N to 25°45'N latitudes. The district is bounded in the north and east bythe state <strong>of</strong> Assam; west by East Khasi Hills district <strong>of</strong> the state and south by Bangladesh (Figure 2.1).The total area <strong>of</strong> the district is 3819 km 2 , which is about 17 percent <strong>of</strong> the total area <strong>of</strong> the state.2.2. GeologyJaintia Hills district <strong>of</strong> Meghalaya form a continuous part <strong>of</strong> the Meghalaya Plateau that represents aremnant <strong>of</strong> the ancient plateau <strong>of</strong> Pre-Cambrian Indian peninsular shield. The district is composed <strong>of</strong> avariety <strong>of</strong> rock formations ranging from Pre-Cambrian to Recent. The Pre-Cambrian formation istraversed by swarms <strong>of</strong> dykes and sills <strong>of</strong> both acidic and basic nature. The major part <strong>of</strong> the district iscovered by the rocks <strong>of</strong> Jaintia series <strong>of</strong> Eocene period and Barail and Simsang formation <strong>of</strong> Oligoceneperiods. A considerable portion is covered by the Gneissic Complex <strong>of</strong> Pre-Cambrian. TertiaryFormation <strong>of</strong> Shangpung and Laskein are encountered with the host <strong>of</strong> Quartzites and Gneissic rocks(Figure 2.2). The general stratigraphic sequence <strong>of</strong> the formation in Jaintia Hills is given Table 2.1.The consolidated hard crystalline rocks <strong>of</strong> granite gneiss, amphibolite, poroxenite, carbonatites alongwith quartzites <strong>of</strong> Pre-Cambrian period occur in the northern part occupying an area <strong>of</strong> about 1300 km 2mainly in the Thadlaskein and Laskein C.D. Blocks. The rocks are highly fractured and jointed andwere subjected to intense weathering. The Shillong group <strong>of</strong> rocks including granite, schist,conglomerate etc., overlies the gneissic complex and are marked by the presence <strong>of</strong> sills and dykes.The Tertiary group <strong>of</strong> rocks is represented by the Shella formation comprising alterations <strong>of</strong> sandstoneand limestone and cover extensive areas <strong>of</strong> Amlarem and Khliehriat C.D. Blocks <strong>of</strong> the district. Thesealso include formation <strong>of</strong> Kopili, Borail, Surma and Dupitala. The Quaternary deposits (olderalluvium) overlie the Tertiary rocks. They occur in separate patches along the southern border <strong>of</strong> thedistrict. These deposits include assorted pebbles with coarse and brown coloured clay. Recentalluvium is found in the river valleys and consists <strong>of</strong> fine silt and light to dark grey clay with pocketsand layers <strong>of</strong> coarse sand and shingles. From the structural point <strong>of</strong> view the Gneissic group <strong>of</strong> rocksshow evidence <strong>of</strong> basement deformation through intricate folding and faulting, having a general trend<strong>of</strong> NE-SW. The Shillong group <strong>of</strong> rocks usually shows broad open folds with a steep dipping zone,apparently due to faulting.In the southern part, the predominant structural feature is the Dawki fault that runs in E-W directionand continues towards east in the North Cachar Hills district <strong>of</strong> Assam. At the closure <strong>of</strong> the Jurassicperiod, faulting made the southern block to subside and the area the northern block upheaved. The rate<strong>of</strong> subsidence gradually slowed down towards Paleocene-Eocene times during which the area attaineda stable shelf condition and the calcareous formation <strong>of</strong> the Jaintia group were deposited (Anon, 1964).The district <strong>of</strong> Jaintia Hills reveals that most <strong>of</strong> the lineaments have NE-SW trend but a few haveNNE, SSW and ENE-WSW. Concentration <strong>of</strong> lineaments in the western part shows that this part hadmore tectonic activities than the other parts.9

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIAINDIAMEGHALAYAFigure 2.1: Location <strong>of</strong> Jaintia Hills district in Meghalaya, India.10

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIAFigure 2.2: Geology <strong>of</strong> Jaintia Hills district (Geological Survey <strong>of</strong> India, 1974).11

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIATable 2.1: Lithostratigraphic Succession <strong>of</strong> Jaintia Hills districtAge Group Formation Rock typeRecentNewer alluvium Unclassified Sand, silt and clay(Thickness not known)Pleistocene Older alluvium(Thickness not known)Unclassified Sand, clay, pebble, gravel andboulder deposits~~~~~~~~~~~~~~~~~~~~~~~~~~~~Unconformity~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~Mio-Pliocene Dupitila Mottled clays, felsphathicsandstone and conglomerate~~~~~~~~~~~~~~~~~~~~~~~~~~~~Unconformity~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~Oligo-Miocene Surma Sandstone, shale, siltstone,mudstone~~~~~~~~~~~~~~~~~~~~~~~~~~~~Unconformity~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~Oligocene Barail Hard, compact, fine grained greysandstone,shale, siltstone~~~~~~~~~~~~~~~~~~~~~~~~~~~~Unconformity~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~Eocene Jaintia KopiliShellaLangparShale, sandstone, marlAlteration <strong>of</strong> sndstone-limestoneCalcareous shale, sandstone,limestone~~~~~~~~~~~~~~~~~~~~~~~~~~~~Unconformity~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ProterozoicIntrusivesShillongPorphyrytic and coarse granite,doleritesQuartzites, phyllites, conglomerates~~~~~~~~~~~~~~~~~~~~~~~~~~~~Unconformity~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~Precambrian Gneissic Complex Biotite gneiss, granitic gneiss,migmatite, mica, schist,amphiboliteSource: Anon, 197412

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIA2.3. Physiography and DrainageThe relative relief <strong>of</strong> the district is 1200 m. The elevation ranges from 76m (at Dawki) and 1627m (atMaryngksih). Physiographically the district is divided into three broad divisions. They are (i) thenorthern hills, (ii) the central plateau or the central Jowai upland and (iii) the southern escarpment. Thenorthern hills exhibit undulating topography. Denudational hills and less dissected topography coversthe northern part <strong>of</strong> the district. The area is less dissected showing youthful topography withdenudational hills trending N-S, E-W, NE-SW. The central plateau is characterized by rolling moundsand hummocks <strong>of</strong> gentle height and shows flat topography. The southern escarpment exhibits denudostructural hills, highly dissected undulating topography with sharp crested hills, deep gorges andwaterfalls. The region is at higher elevation than the northern hills. The district is drained in the northby the Umkhen river, in the northeast by Kopili river and its main tributaries like Kharkor, Saipung,Umluren, Myntang, Mynriang and Litang. In the southern part, the district is drained by Myntdu riverand its tributaries. The main tributaries are Umlatang, Lynriang, Lubha, Umlunar and Lukha. In thewest Umngot river separating the East Khasi Hills district with the Jaintia Hills.2.4. ClimateThe district experiences a tropical monsoon climate. From the prevailing weather conditions the rainyseason occurs during mid May to September. October and November is the transition period betweenrainy and winter seasons and it represents the autumn. The period between December and February ischaracterized by cold and dry weather conditions. The period between March to mid-May is warmer.The annual rainfall from 1991 to 2001 <strong>of</strong> the district varies from 3797 mm and 7912 mm. December isthe driest month as it contributes average rainfall <strong>of</strong> 18.8 mm and June is the wettest month withaverage rainfall <strong>of</strong> 1326.2 mm. It is observed that summer months (May to September) only contributemore than 70 percent <strong>of</strong> the total rainfall. August is the hottest month <strong>of</strong> the district with averageminimum and maximum temperatures <strong>of</strong> 18.4°C and 24.5°C, respectively. The coldest month isJanuary where the average minimum and maximum temperatures are 7.8°C and 15.6°C (Figure 2.3).The average relative humidity is highest in the month <strong>of</strong> July (85.2 percent) while December recordsthe lowest relative humidity <strong>of</strong> 61.2 percent.Temperature (°C)302520151050Jan Feb March April May June July Aug Sept Oct Nov DecMonths140012001000Max. Temp (°C) Min. Temp. (°C) Rainfall8006004002000Rainfall (mm)13

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIAFigure 2.3: Monthly average maximum and minimum temperature and rainfall in Jowai,the district headquarters <strong>of</strong> Jaintia Hills (Mean <strong>of</strong> 1991 to 2001).2.5. SoilThe soil is mostly sandy, reddish brown to yellow brown in colour, acidic in reaction with low waterholding capacity and has poor contents <strong>of</strong> organic matter and nutrients. The pH value ranges between4.1 to 5.6. The concentration <strong>of</strong> organic carbon content varies from 0.28 to 3.1 percent. Lowphosphorus content is the characteristics <strong>of</strong> the soil <strong>of</strong> the district, varying between 1.8 and 4.5 kg/ha.The potassium content ranges between 28.0 and 112.0 kg/ha, which is quite lower than normal soil(Dkhar 2002).2.6. Natural VegetationThe district <strong>of</strong> Jaintia Hills claims to have the biggest forest reserve in the state <strong>of</strong> Meghalaya.According to the 1991 Census, the total area under forest in the district is 1436.1 km 2 , which is 37.6%<strong>of</strong> the total area <strong>of</strong> the district. The natural vegetation <strong>of</strong> the district is subtropical (Chouhan and Singh,1992). The large scale unscientific land use practices have resulted in the depletion <strong>of</strong> primary forestand colonization <strong>of</strong> the degraded sites by Pinus kesiya, which grows well to develop into secondaryforests. Besides, the forest floor is covered with the species like Eupatorium adenophorum, Lantanacamara, Rubus sp. Paspalum orbiculare, Isachne himalaica, Globba clarkii etc. The presence <strong>of</strong>isolated patches <strong>of</strong> degraded forests amidst the grassland imparts a savanna like appearance to thelandscape <strong>of</strong> the region. The acidic and highly impoverished shallow soil layer is neither conductivefor regeneration through seeds nor for healthy plant growth.2.7. PopulationAccording to the Census <strong>of</strong> India, 2001, the total population <strong>of</strong> the district is 295692. The literacy rateis 52.8 percent. The settlement pattern in the district is mainly compact or nucleated.2.8. <strong>Coal</strong> Deposits and <strong>Coal</strong> FieldsIn Meghalaya, coal occurrence is confined to the Tertiary sediments. The coal is deposited over aplatform (Shillong plateau) under stable shelf conditions. The coal occurrences are developed more orless along the southern fringe <strong>of</strong> the state. The coalfields <strong>of</strong> the Jaintia Hills are small and spread out indifferent patches. <strong>Coal</strong> occurs in nine important deposits <strong>of</strong> the district. They are Bapung, Lakadong,Jarain-Shkentalang, Lumshnong, Malwar-Musiang-Lamare, Sutnga, Ioksi, Chyrmang and Mutang.Jaintia Hills district has a total coal deposit <strong>of</strong> about 40 million tonnes, which is only 7 percent <strong>of</strong> thetotal coal deposits <strong>of</strong> the state (Table 2.2). The district has been most extensively exploited in terms <strong>of</strong>coal, though it has the lowest deposits among all the districts. The district contributes more than 74percent <strong>of</strong> the total coal production <strong>of</strong> the state (Table 2.3).Table 2.2: <strong>Coal</strong> deposits (million tonnes) in different districts <strong>of</strong> MeghalayaDistrict Deposit % <strong>of</strong> depositKhasi Hills 164.57 29.2Garo Hills 359 63.8Jaintia Hills 39.25 7.0State 562.82 10014

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIASource: Directorate <strong>of</strong> Mineral Resources, Government <strong>of</strong> Meghalaya, 2003Table 2.3: <strong>Coal</strong> production (’000 tonnes) and percentage in Jaintia Hills district <strong>of</strong> MeghalayaYear Meghalaya Jaintia Hills % <strong>of</strong> the district1992-1993 3487.7 3040.80 87.181993-1994 2583.5 2062.20 79.821994-1995 3266.2 2389.70 73.161995-1996 3247.5 2159.50 66.491996-1997 3240.9 2273.60 70.151997-1998 3233.5 2414.60 74.671998-1999 4237.8 3246.10 76.591999-2000 4057.0 2935.00 72.342000-2001 4160.8 2839.80 68.252001-2002 5149.32 3869.32 75.14Total 36664.22 27230.62 74.27Source: Directorate <strong>of</strong> Mineral Resources, Government <strong>of</strong> Meghalaya, 20032.8.1. Bapung AreaBapung coalfield has the largest deposit <strong>of</strong> coal (34 million tonnes) covering an area <strong>of</strong> 12 km 2 . Twocoal seams producing good quality coal occur within the undifferentiated Sylhet sandstone in andaround Bapung (25°25' N and 91°49'E). The lower seam varies from 0.3 to 1.2m in thickness. Theupper seam is thin, and the thickness is 0.3m. The NH-44 passes through the heart <strong>of</strong> the coalfieldconnecting Shillong and Silchar. The area represents a vast undulating surface with gentle slopestowards south. The general elevation varies from 1073m to 1370m above mean sea level (Rai, 2002).The coal seams around Bapung are hard, lumpy, bright and sub-bituminous type. The coal shows themoisture content from 2.2 to 9.2 percent, ash from 2.6 to 7.8 percent, volatile matter from 38.3 to 44.3percent, fixed carbon from 46.2 to 52.3 percent, sulphur from 3.2 to 7.1 percent and calorific valuefrom 6080 to 7494 k. cal/kg (DMR, 1985).2.8.2. Lakadong AreaThe Lakadong coal field covering the Umlatdoh (25°12'N and 92°17'E) plateau between the Myntduand Prang rivers in the southern part <strong>of</strong> the district. <strong>Coal</strong> occurrence is found around Umlatdoh andPamsaru area. The reserve <strong>of</strong> coal has been estimated to be 1.5 million tonnes and exposes a veryirregular and inconsistent coal seam varying from 0.3 to 3.0m in thickness. This spreads over an area<strong>of</strong> 3 km 2 . The coal shows the moisture content from 0.4 to 0.8 percent, ash from 2.3 to 24.7 percent,volatile matter from 29.7 to 33.5 percent, fixed carbon from 44.7 to 59.8 percent, sulphur from 3.4 to4.9 percent and calorific value from 5694 to 7500 k. cal/kg (DMR, 1985).2.8.3. Jarain-ShkentalangThe Jarain-Shkentalang area is located in the western part <strong>of</strong> the district. The total inferred reserve <strong>of</strong>coal is 1.1 million tonnes covering an area <strong>of</strong> 2.8 km 2 . In Jarain there is only one coal seam with athickness <strong>of</strong> 0.3 to 1.1m, whereas there are two coal seams in the Shkentalang coalfield that rangesfrom 0.1 to 1.0m. The coal found in the Shkentalang is bright and hard but in Jarain area coal is s<strong>of</strong>tand friable (GSI, 1974). The coal shows the moisture content from 1.2 to 1.6 percent, ash from 4.4 to15

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIA6.7 percent, volatile matter from 41.6 to 48.1 percent, fixed carbon from 45.9 to 50.5 percent, sulphuris 2.7 percent and calorific value is 6944 k. cal/kg (DMR, 1985).2.8.4. LumshnongSeveral isolated exposures <strong>of</strong> coal have been recorded to the west and southwest <strong>of</strong> Lumshnong(25°10'N and 92°23'E) over an area <strong>of</strong> 0.6 km 2 . The estimated reserve <strong>of</strong> coal in this field is 0.2million tonnes. The seam thickness varies from 0.3 to 0.6m (GSI, 1974). The coal seams in this areaare hard and lumpy and strongly coking. The coal shows the moisture content from 1.6 to 1.8 percent,ash from 3.2 to 3.8 percent, volatile matter from 30.8 to 45.5 percent, fixed carbon from 42.1 to 64.6percent and calorific value from 7250 to 8230 k. cal/kg (DMR, 1985).2.8.5. Malwar-Musiang-LamareExposure <strong>of</strong> coal have been recorded around Malwar (25°12'30''N and 92°24'00''E) and Musiang-Lamare (25°13'N and 92°21'E) villages over an area <strong>of</strong> 2.3 km 2 . The total reserve <strong>of</strong> coal is estimatedto be 1.1 million tonnes. The coal field includes a thin, inconsistent coal seam, extremely variable inthickness ranging from 0.3 to 1.6m (GSI, 1974). The coal shows the moisture content from 0.6 to 3.6percent, ash from 1.3 to 21.2 percent, volatile matter from 32.6 to 40.0 percent and fixed carbon from42.1 to 60.4 percent (DMR, 1985). The coal seams in this area are hard and lumpy.2.8.6. SutngaSutnga coalfield is the eastern extension <strong>of</strong> Bapung coalfield. The coal seams occur in the Shellaformation <strong>of</strong> the Paleocene age. The coal seams are interbedded with shales and sandstone. <strong>Coal</strong> isfound in two seams, the top one being only 0.1 to 0.2m and the bottom seam varies in thickness from0.3 to 0.6m and the vertical interval between the two seams is 3 to 5m. The total reserve <strong>of</strong> coal is 0.65million tonnes over an area <strong>of</strong> 0.16 km 2 . The physical characteristics <strong>of</strong> coal <strong>of</strong> this area is hard, lumpyand bright (GSI, 1974). The coal <strong>of</strong> Sutnga coalfield shows the moisture content from 1.3 to 7.0percent, ash from 2.2 to 9.7 percent, volatile matter from 32.9 to 42.8 percent and fixed carbon from49.9 to 53.2 percent (DMR, 1985).2.8.7. IoksiIoksi is located in the eastern part <strong>of</strong> the district. The estimated reserve <strong>of</strong> coal in this area is 1.3million tones covering an area <strong>of</strong> 3.6 km 2 . The thickness <strong>of</strong> seams varies from 0.5 to 0.9m. The coal inIoksi area occurs in the Lower Sylhet sandstone <strong>of</strong> Eocene age. The nature <strong>of</strong> coal deposits is beddedtype. The physical characteristics <strong>of</strong> coal in this area is hard, bright and jointed (GSI, 1974). The coal<strong>of</strong> Ioksi coalfield shows the moisture content from 4.2 to 7.5 percent, ash from 6.0 to 18.1 percent,volatile matter from 33.0 to 43.4 percent and fixed carbon from 41.3 to 46.4 percent (DMR, 1985).2.8.8. ChyrmangAn outlier <strong>of</strong> the undifferentiated Sylhet sandstone covering the Chyrmang (25°26'N and 92°25'E) areain the Jaintai Hills exposes two thin seams <strong>of</strong> coal. The average thickness <strong>of</strong> the seam is 0.6m. Thecharacteristic <strong>of</strong> the coal is similar to that <strong>of</strong> the Bapung coal field. The reserve <strong>of</strong> coal is not fullyassessed (GSI, 1974).2.8.9. MutangMutang coal field is located in the southwest extension <strong>of</strong> the Malwar. The thickness <strong>of</strong> the coal seamvaries from 0.25 to 1.08m. The seam shows conspicuous pinching and swelling.16

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIA2.9. Present Study AreaAn area <strong>of</strong> about 420 km 2 in the core <strong>of</strong> the coal mining areas <strong>of</strong> the district is selected for the presentstudy. The area is extended from 92°13'52''E and 92°25'16''E longitudes to 25°16'7''N and 25°27'28''Nlatitudes (Figure 2.4). The topography <strong>of</strong> the area is undulating and elevation ranges from 700m to1400m (Figure 2.5). The area is drained by Laphirawi river and its tributaries (Figure 2.6). The totalnumber <strong>of</strong> settlement <strong>of</strong> different sizes covered under the study area was 45. The length total roadnetwork was 520 km (Figure 2.7).Figure 2.4: Location <strong>of</strong> the study area in Jaintia Hills district.17

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIAFigure 2.5: Digital elevation model (m).18

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIAFigure 2.6: Drainage in the study area.19

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIAFigure 2.7: Settlement and road network.20

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIA3. Materials and Methods3.1. Study AreaThe Jaintia Hills district <strong>of</strong> Meghalaya is bestowed with rich natural vegetation as well as large reserve<strong>of</strong> mineral resources. During the last few decades, there have been phenomenal increases in mining <strong>of</strong>coal, limestone, sillimanite and clay causing large-scale destructions and deterioration <strong>of</strong> the naturalvegetation. The district has been most extensively extracted in terms <strong>of</strong> coal, among all districts <strong>of</strong> thestate. Excessive mining operation <strong>of</strong> coal in many parts <strong>of</strong> the district has been responsible for theconversion <strong>of</strong> original lush green landscape <strong>of</strong> the area into mine spoils. The crude and unscientificmethod <strong>of</strong> mining adopted by the primitive operators in several parts <strong>of</strong> the district has caused severeecosystem destruction. Uncontrolled and unscientific mining operation within the district has beendetrimental to the fragile ecosystem. It is <strong>of</strong> urgent need to understand the impact <strong>of</strong> mining on thevegetation characteristics <strong>of</strong> the district for further management plan.For the present study an area <strong>of</strong> approximately 420 km 2 was delineated in the core <strong>of</strong> the coal miningareas <strong>of</strong> the district (92°13'52''E to 92°25'16''E longitudes and 25°16'7''N and 25°27'28''N latitudes).Lad Rymbai (25°21'53.2''N and 92°19'15.8''E), the major centre for coal mining was taken as thecentre <strong>of</strong> the study area.3.2. MaterialsIRS Satellite data for four different years period <strong>of</strong> 1975, 1987, 1999 and 2001 were used for temporalanalysis. The data used are Landsat MSS for 1975, Landsat TM for 1987, Landsat ETM+ for 1999and IRS-1D-LISS III data for 2001 (Figure 3.1, Figure 3.2, Figure 3.3, Figure 3.4).The ancillary data used for the study are topographic maps <strong>of</strong> the study area, GSI map, GPS andCompass.The s<strong>of</strong>tware used are ERDAS IMAGINE 8.7, ArcGIS, ILWIS 3.2 and MS Office.3.3. Research MethodsTo fulfil the objectives following methods will be adopted:3.3.1. Study InitiationIdentification <strong>of</strong> study area followed by literature review.3.3.2. Pre-Field WorkDelineation <strong>of</strong> study area followed by reconnaissance survey.3.3.3. Field and Post-Field WorkAnalysis and interpretation <strong>of</strong> four different years satellite data with the help <strong>of</strong> remote sensing andGIS.21

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIAFigure 3.1: Landsat MSS FCC for the period 1975.22

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIAFigure 3.2: Landsat TM FCC for the period 1987.23

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIAFigure 3.3: Landsat ETM + FCC for the period 1999.24

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIAFigure 3.4: IRS-1D LISS-III FCC for the period 2001.25

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIA3.3.3.1. Radiometric CorrectionFirst order corrections were done by dark pixel subtraction technique followed by Lilles and Kiefer(1999).3.3.3.2. Visual InterpretationStudying changes in land use pattern using remotely sensed data is based on the comparison <strong>of</strong> thetime sequential data. Differences in surface phenomenon over time can be determined and evaluatedby visual interpretation with local knowledge (Garg et al., 1988; SAC, 1999). For the present purposevisual interpretation technique was used for land use/ land cover mapping for four different yearsremote sensing data <strong>of</strong> the study area.3.3.3.3. Change AnalysisThe land use/ land cover maps <strong>of</strong> 1975, 1987, 1999 and 2001 were converted into grid format usingIntergraph MGE Grid Analyst. Maps <strong>of</strong> different time periods were overlaid to find changes. Theincrease or decrease in different land use/ land cover is obtained by intersecting and generating thematrices <strong>of</strong> change-no change for different years.3.3.3.4. Forest Fragmentation AnalysisIt was measured by calculating the amount <strong>of</strong> forest patches occurring in a landscape with respect tonon-forest patches. In the programme, Bio_CAP the area was reclassified into three categories viz.,non-forest, high fragmentation and low fragmentation.3.3.3.5. Phytosociological AnalysisThe community characteristics <strong>of</strong> vegetation in coal mining areas <strong>of</strong> Jaintia Hills district <strong>of</strong> Meghalayawere studied during the last week <strong>of</strong> October, 2004. To find out the impact <strong>of</strong> coal mining onvegetation distant gradient analysis was carried out. In this method, from the center <strong>of</strong> the study area,i.e., Lad Rymbai, structure and composition <strong>of</strong> vegetation is observed in four different zones. Theradius <strong>of</strong> the first circle i.e., zone-I is 2 km. The distance from the periphery <strong>of</strong> the first circle to theperiphery <strong>of</strong> the second circle is also 2 km and is considered as zone-II. Likewise, zone-III and zone-IV are delineated (Figure 3.5). In each circle 24 sample plots each for tree, shrub and herbs were laid.Each sample plot was supported by 3 replicas. The total number <strong>of</strong> sample plots for tree, shrub andherbs came to 72 each in each zone. The overall number <strong>of</strong> sample plots for tree, shrub and herbspecies was 288 each in the mining areas, i.e., in all the four zones. The vegetation characteristics <strong>of</strong>the mined areas were compared with that <strong>of</strong> an adjacent undisturbed forest, i.e., Tubre Sacred Grove.The total number <strong>of</strong> quadrats laid in the control site was 10.For tree component a quadrat <strong>of</strong> 10m x 10m size was laid while for the shrub species it was 5m x 5m.For the herbaceous species the size <strong>of</strong> the quadrat was 1m x 1m. The species found in the quadratswere identified with the help <strong>of</strong> the herbaria <strong>of</strong> Botany Department, North-Eastern Hill University,Shillong and Botanical Survey <strong>of</strong> India, North-Eastern Circle, Shillong. The plants having CBH>15cm was considered as tree, stem diameter 5-15cm at basal level was considered as shrubs and stemdiameter

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIANumber <strong>of</strong> quadrats <strong>of</strong> occurrence <strong>of</strong> a speciesFrequency (%) = ------------------------------------------------------------ x 100Total number <strong>of</strong> quadrats studiedTotal number <strong>of</strong> individuals <strong>of</strong> a speciesDensity = ----------------------------------------------------Total number <strong>of</strong> quadrats studiedBasal cover = Density x average basal area <strong>of</strong> individuals <strong>of</strong> a speciesBasal area was calculated based on the measurement <strong>of</strong> CHB at 1.37m heights.Number <strong>of</strong> individuals <strong>of</strong> a speciesAbundance = -------------------------------------------------------------Number <strong>of</strong> quadrats <strong>of</strong> occurrence <strong>of</strong> the speciesSimpson Dominance Index (1949) = (n i / N) 2where, n i = importance value indexN = total importance value <strong>of</strong> all speciesThe distribution pattern <strong>of</strong> the species was studied by using Whitford’s index (Whitford 1948).Abundance (A)Whitford’ s index = ----------------------;Frequency (F)if A/F ratio:< 0.025 :Regular distribution0.025 - 0.05 :Random distribution> 0.05 :Contagious or clumped distributionShannon-Weaver index <strong>of</strong> general diversity was calculated by using the formulaH = - ∑ (n i / N) ln (n i / N)where, H = Shannon-Weaver indexn i = importance value indexN = total importance value <strong>of</strong> all species27

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIA8 km6 km4 km1.1. 2 kmZone-IZone-IIZone-IIIZone-IVFigure 3.5: Conceptual framework <strong>of</strong> different coal mine impact zones.Reconnaissance Survey and Collection <strong>of</strong> Secondary InformationInterpretation <strong>of</strong> Satellite data Generation <strong>of</strong> Spatial Database(1975, 1987, 1999 and 2001)Trend AnalysisPhytosociological AnalysisChange AnalysisMined AreaUnmined AreaFragmentation Analysis<strong>Impact</strong> AnalysisConclusionFigure 3.6: Paradigm for assessment <strong>of</strong> mining impact on vegetation.28

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIA4. Results and DiscussionEcosystem disturbance may be defined as an event or series <strong>of</strong> events that alters the relationship <strong>of</strong>organisms and their habitat in time and space. Ecosystem disturbance by mining is an evitable fall out<strong>of</strong> industrialization and modern civilization. <strong>Mining</strong> <strong>of</strong> coal both surface and subsurface causesenormous damage to the flora, fauna, hydrological relations and soil biological systems. Destruction <strong>of</strong>the vegetal cover during mining operation is invariably accompanied by an extensive damage and lossto the system. The disturbed and haphazardly mixed infertile, consolidated and unconsolidatedmaterials overlying the coal seams are known as overburdens. These overburdens when dumped inunmined areas in the vicinity <strong>of</strong> the coal mines create mine spoils. Nutrient deficient sandy spoils aregenerally hostile to plant growth. The dumping <strong>of</strong> spoils and coal destroys even the surroundingvegetation and leads to severe soil and water pollution. The Jaintia Hills district <strong>of</strong> Meghalaya hasbeen extensively extracted in terms <strong>of</strong> coal. As a result <strong>of</strong> this, many parts <strong>of</strong> the district has beenconverted from lush green landscape into mine spoils. Large scale denudation <strong>of</strong> forest cover, scarcity<strong>of</strong> water, pollution <strong>of</strong> air, water and soil, and degradation <strong>of</strong> agricultural lands are some <strong>of</strong> theconspicuous environmental implications <strong>of</strong> coal mining in Jaintia Hills.A detailed understanding <strong>of</strong> the impact <strong>of</strong> coal mining on vegetation and plant diversity on time andspace is pre-requisite for the district. Keeping this objective in view, the first part <strong>of</strong> this chapter willdiscuss the plant community characteristics <strong>of</strong> the area and the impact <strong>of</strong> coal mining on them hasbeen assessed by comparing certain community attributes <strong>of</strong> the mined areas with that <strong>of</strong> the adjacentumined area. The second part will deal with temporal impact <strong>of</strong> mining activities on vegetation. Inorder to achieve this objective the land cover types <strong>of</strong> dense forest, open forest and mining area weredelineated. The area under crop, settlement and grassland/ non-forest were also taken intoconsideration to know the trend due to the impact <strong>of</strong> mining activities in different time periods.4.1. Community Characteristics4.1.1. Floristic CompositionThere were variations in the composition <strong>of</strong> plant in the mined and unmined areas. The tree speciesshowed a drastic reduction in their number in all zones <strong>of</strong> the mining sites (3-11) with that <strong>of</strong> theunmined sites (27). In the unmined site 27 tree species belonging to 22 genera and 19 families wereregistered. Four (4) tree species belonging to 4 genera and 4 families, 7 tree species belonging to 7genera and 7 families, 3 tree species belonging to 3 genera and 3 families, and 11tree speciesbelonging to 10 genera and 9 families were recorded in the mined areas <strong>of</strong> zone-I, zone-II, zone-IIIand zone-IV, respectively. It was apparent from the study that the number <strong>of</strong> tree species was more inthe peripheral zone than the inner zones. There was not much variation in the number in first threezones <strong>of</strong> the area. The shrub species did not show much variation in the unmined and all the zones <strong>of</strong>the mined areas. In the unmined area, total 27 shrub species belonging to 22 genera and 18 familieswere found. Shrubs were represented by 19, 25, 22 and 34 species from 18, 25, 23 and 33 genera, and13, 17, 16 and 21 families were recorded from zone-I, zone-II, zone-III and zone-IV, respectively.There was remarkable increase in the number <strong>of</strong> herbaceous species in the mined areas. In theunmined area total number <strong>of</strong> ground species recorded were 23 belonging to 21 genera and 15families. In the mined areas herbaceous layer was composed <strong>of</strong> 39 species, 38 genera, 25 families inthe zone-I, 41 species belonging to 41 genera and 26 families in the zone-II, 40 species from 39 genera29

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIAand 23 families in zone-III, and 34 species belonging to 33 genera and 21 families in zone-IV (Table4.1).Table 4.1: Species, generic and family compositions in different zonesSpecies composition Control Zone-I Zone-II Zone-III Zone-IVTreesNo. <strong>of</strong> species 27 4 7 3 11No. <strong>of</strong> genera 24 4 7 3 10No. <strong>of</strong> family 19 4 7 3 9ShrubsNo. <strong>of</strong> species 27 19 25 22 34No. <strong>of</strong> genera 22 18 25 23 33No. <strong>of</strong> family 18 13 17 16 21HerbsNo. <strong>of</strong> species 23 39 41 40 34No. <strong>of</strong> genera 21 38 41 39 33No. <strong>of</strong> family 15 25 26 23 21Since the mined and unmined areas had similar climatic, edaphic and physiographic features thedifferences in species composition could be attributed to the mining activities. This is in agreementwith the findings <strong>of</strong> Das Gupta (1999), Baig (1992), Jha and Singh (1990). Sarma (2002), whilestudying the impact <strong>of</strong> coal mining on the vegetation characteristics <strong>of</strong> the Nokrek Biosphere Reserve<strong>of</strong> Meghalaya outlined that the composition <strong>of</strong> vegetation reduces in the mined areas with that <strong>of</strong> theadjacent unmined areas. Lyngdoh et al. (1992) reported less number <strong>of</strong> species in the mine spoils <strong>of</strong>different ages to that the unmind sites. Iverson and Wali (1982) observed an increase in speciesrichness with age in reclaimed coal mine spoils.4.1.2. DensityThe tree density in the mined areas ranged between 515 and 647 stems per ha while in the unminedarea it was 1040 stems per ha. There was not much variation in the shrub density but density <strong>of</strong>herbaceous species was remarkably higher in the mined areas (154-178 individual/m 2 ) than theunmined area (32 individual/m 2 ) (Table 4.2).The unmined area had greater plant density compared to that <strong>of</strong> the mined areas because <strong>of</strong> the acidicpH, moisture stress and nutrient property <strong>of</strong> litter. Low grow form, sparse density and ability totolerate low nutrient levels and low moisture conditions are probably the adaptations to the harshphysical nature <strong>of</strong> substrate. Low nutrient habitats are usually colonized by species with low relativegrowth rates. These adaptations enable colonizing species to maximize the nutrient uptake and ensurehigh nutrient use efficiency in low nutrient environments (Baig, 1992). Lyngdoh (1995), Das Gupta(1999) and Sarma’s (2002) works lend support to the present findings. Bradshaw and Chadwick(1980) working on the colliery spoils reported that the number <strong>of</strong> species colonizing on the minedareas was influenced by its pH.30

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIATable 4.2: Stand density as affected by mining in different zonesSpecies Control Zone-I Zone-II Zone-III Zone-IVTrees (individual/ha) 1040 561 515 603 647Shrubs (individual/m 2 ) 1 2 1 1 2Herbs (individual/m 2 ) 32 165 178 154 1574.1.3. Dominance PatternThe dominance were different for tree, shrub and herb component in mined and the unmined controlarea <strong>of</strong> the study area. In terms <strong>of</strong> importance value Pinus kesiya (IVI: 243.97-280.27) was thedominant tree species in the mining area and presented in all the zones, which was followed by theSchima wallichii (IVI: 10.05-46.36). In the control site Camelia caudata (IVI: 54.5), Castanopsispurpurella (IVI: 44.9) and Quercus griffithii (IVI: 30.7) were the dominant tree species.In the shrub layer, Eupatorium adenophorum (IVI: 22.78-53.74) and Melastoma nepalensis (IVI:23.36-48.86) were the two dominant species followed by Lantana camara (IVI: 23.93-49.44) indifferent zones <strong>of</strong> the mining area. Control site was dominated by Psychotria erratica (IVI: 16.13),Cassia floribunda (IVI: 14.52), Shutaria vestida (IVI: 14.52), and Plectranthus striantus (IVI: 14.52).Among herbaceous species Paspalum orbiculare (IVI: 68.42-95.47) dominated all the zones <strong>of</strong> themining area, which was followed by Isachne himalaica (IVI: 15.75-19.57). Globba clarkii (IVI:38.73), Selaginella semicordata (IVI: 29.52) and Panicum brevifolium (IVI: 24.13) were the dominantground species in the control site (Table 4.3).The high importance value <strong>of</strong> Pinus kesiya in mining areas suggesting its ability to grow in thedisturbed environments and its dominance in the harsh conditions. Higher importance value <strong>of</strong> Schimawallichii indicates the degraded environment. The higher importance value <strong>of</strong> Paspalum orbicularesuggests that it can multiply rapidly in the disturbed environments. This perennial grass by virtue <strong>of</strong> itsstolon and rooting at each node can bind the soil particles, making the soil more stable. The dominance<strong>of</strong> one or two species explain the low diversity and high dominance in the mined affected areas.Dominance-diversity curves have been used to interpret the dominance <strong>of</strong> species in the community inrelation to resource apportionment and niche space (Whittaker, 1975). The curves (Figure 4.1, Figure4.2, Figure 4.3) in the unmined sites resemble the log normal suggesting that there was more or less aneven apportionment <strong>of</strong> resources among the members <strong>of</strong> the important species. The curves for themined sites resemble with broken-stick series model (Poole, 1974). This could be attributed to thelesser number <strong>of</strong> species occurring in these areas and also represent a stress environment whereconditions were not favourable for plant growth. Species diversity was low on these stands, but thespecies that grow here appear to have developed tolerance that enable them to grow in such anenvironment.31

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIATable 4.3: Plant species with higher importance value index in control and mined areasSpecies Control Zone-I Zone-II Zone-III Zone-IVTreesPinus kesiya - 264.47 280.27 246.05 243.93Schima wallichii - - 10.05 46.36 18.91Persea odoratissima - 20.58 - - -Quercus griffithii 30.7 - - -Camelia caudata 54.5 - - -Castanopsis purpurella 44.9 - - - -ShrubsEupatorium adenophorum - 53.74 27.55 22.78 40.52Lantana camara - - 26.41 23.93 49.44Melastoma nepalensis - 25.28 48.86 37.86 23.36Rubus ellipticus - - 23.15 - -Rubus khasiana - 12.30 - 9.83 -Shutaria vestida 14.52 - - - -Cassia floribunda 14.52 - - - -Psychotria erratica 16.13 - - - -Plectranthus striantus 14.52 - - - -HerbsPaspalum orbiculare - 68.42 89.45 83.29 95.47Gnaphalium pensylvanium - - - - 9.05Plantago erosa - - - - 7.27Borreria sp. - - - 12.7 -Isachne himalaica - 15.75 16.29 19.57 -Ageratum conyzoides - 10.44 - 11.68 -Borreria articularis - 9.97 - 14.47 -Selaginella semicordata 29.52 - - - -Panicum brevifolium 24.13 - - - -Globba clarkii 38.73 - - - -32

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIA10001000ControlControl100Zone-I100Zone-IIImportance Value Index1011010.10 10 20 300.10 10 20 3010001000100ControlZone-III100ControlZone-IVImportance Value Index1011010.10 10 20 30Species Ranking0.10 10 20 30Species RankingFigure 4.1: Dominance-diversity curves <strong>of</strong> trees in control and mined areas.33

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIA100100ControlZone-IControlZone-IIImportance Value Index1011010.10 10 20 30 400.10 10 20 30 40100100Importance Value IndexControlZone-III101ControlZone-IV1010.10 10 20 30 40Species Ranking0.10 10 20 30 40Species RankingFigure 4.2: Dominance-diversity curves <strong>of</strong> shrubs in control and mined areas.34

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIA100ControlZone-I100ControlZone-IIImportance Value Index1011010.10 10 20 30 40 500.10 10 20 30 40 50100100ControlZone-IIIControlZone-IVImportance Value Index1011010.10 10 20 30 40 50Species Ranking0.10 10 20 30 40 50Species RankingFigure 4.3: Dominance-diversity curves <strong>of</strong> herbs in control and mined areas.35

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIA4.1.4. Species DiversityShannon-Weaver diversity index for tree and shrub species were less in the mined areas as comparedto that <strong>of</strong> the unmined area. Diversity in tree species was drastically reduced in the mined areas. Therewere not much differences in the diversity <strong>of</strong> ground vegetation both in mined and unmined areas(Table 4.4). The diversity index for herbaceous species increased with mining suggesting that miningoperation enhanced the colonization <strong>of</strong> certain species in the newly created habitats due to mining.This is in agreement with the findings <strong>of</strong> Lyngdoh (1995), Das Gupta (1999) and Sarma (2002).Table 4.4: Shannon-Weaver diversity index in control and mined areasSpecies Control Zone-I Zone-II Zone-III Zone-IVTrees 2.8 0.47 0.34 0.54 0.85Shrubs 3.13 2.59 2.51 2.84 2.56Herbs 2.69 2.83 2.44 2.48 2.414.2. <strong>Impact</strong> <strong>of</strong> <strong>Coal</strong> <strong>Mining</strong> on Tree Population Structure4.2.1. Density-Diameter DistributionThe trees <strong>of</strong> medium girth class (55-95cm) dominated in the mined areas in all the zones. In thecontrol site the trees with low girth class (15-35cm) had the maximum individuals (Figure 4.4).In the unmined site, it was found from the study that density <strong>of</strong> young and middle sized trees washigher than the older tree, indicating stable tree population structure. Such a tree population structureis represented by a normal case and suggests that the forest is growing and would continue to exist.However, in the mined areas, the tree density in all the girth classes was extremely low and did notfollow any standard density diameter population curve (Rao et al., 1990). This has been due torampant and random clearing <strong>of</strong> forest areas for mining purpose that has led to drastic change in treepopulation structure. Such a trend in population structure does not indicate the continued existence <strong>of</strong>the forest.36

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIA800800Number <strong>of</strong> individuals/ ha700600500400300200Zone-IControl700600500400300200Zone-IIControl100100015-35 36-55 56-75 76-95 96-115116-135>135015-35 36-55 56-75 76-95 96-115116-135>135800800700Zone-IIIControl700Zone-IVControl600600Number <strong>of</strong> individuals/ ha500400300200500400300200100100015-35 36-55 56-75 76-95 96-115Girth-class (cm)116-135>135015-35 36-55 56-75 76-95 96-115Girth-class (cm)116-135>135Figure 4.4: Density-diameter distribution <strong>of</strong> trees in different girth classes under control andmined areas.37

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIA4.2.2. Basal CoverThe basal area (m 2 ha -1 ) in both mined and unmined areas showed no trend and were almost equallydistributed. Comparatively low basal area in spite <strong>of</strong> high population density (individuals ha -1 ) in theunmined site attributed that the trees dominated were <strong>of</strong> smaller in size (Figure 4.5). The higher basalarea in the mined areas though it had low density, could be attributed to the existence <strong>of</strong> bigger treesand causing no damage to these trees during mining operations by the miners. This indicates theremoval <strong>of</strong> younger trees during mining. Such a trend leads to the failure <strong>of</strong> the community to generateback naturally. Similar trend were also observed by Paijman (1970) in New Guinea, Newbery et al.(1992) in Malayasia and Parthasarathi and Karthikeyan (1997) in India for various disturbed foreststands.35Total basal area (m 2 ha -1 )302520151050Control Zone-I Zone-II Zone-III Zone-IVStudy sitesFigure 4.5: Basal area <strong>of</strong> tree species in control and mined areas.4.3. <strong>Impact</strong> <strong>of</strong> <strong>Coal</strong> <strong>Mining</strong> on Species Distribution PatternPlant populations exhibit three patterns <strong>of</strong> spatial distribution, viz., contagious or clumped, randomand regular or uniform. Patchiness, or the degree to which individuals are aggregated or dispersed, iscrucial to the understanding <strong>of</strong> how species uses resources, and how it is used as a resource. Besides,the distribution pattern <strong>of</strong> species population is <strong>of</strong>ten related to its productive biology. Webb et al.(1967), Ashton (1972) and Austin et al. (1972) indicated that in the absence <strong>of</strong> major disturbance, soiland water conditions play major roles in controlling species distribution pattern.In the unmined area most <strong>of</strong> the tree and shrub species showed contagious distribution pattern (85 and89%). In the mined areas all the component <strong>of</strong> the plant species represented contagious pattern <strong>of</strong>distribution (Table 4.5). The contagious distribution pattern <strong>of</strong> species indicated the mosaicness <strong>of</strong> theforest stand. The contagious <strong>of</strong> the species suggests the increase in fragmentation <strong>of</strong> the naturalvegetation due to mining. Similar species distribution pattern was observed by Sarma (2002) in coalmining areas <strong>of</strong> Nokrek biosphere reserve <strong>of</strong> Meghalaya.38

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIATable 4.5: Proportion (%) <strong>of</strong> tree species under different distribution pattern in controland mined areasSpecies Control Zone-I Zone-II Zone-III Zone-IVTreeRegular - - - - -Random 15 - - - -Contagious or clumped 85 100 100 100 100ShrubRegular - - - - -Random 11 - - - -Contagious or clumped 89 100 100 100 100HerbsRegular - - - - -Random - - - - -Contagious or clumped 100 100 100 100 100Table 4.6: Overall community structure <strong>of</strong> control and coal mined areasSpecies Control Zone-I Zone-II Zone-III Zone-IVTreesNo. <strong>of</strong> species 27 4 7 3 11No. <strong>of</strong> genera 24 4 7 3 10No. <strong>of</strong> family 19 4 7 3 9Density (individuals ha -1 ) 1040 561 515 603 647Basal area (m 2 ha -1 ) 21.94 26.36 29.38 20.06 32.61Shannon-Weaver diversity index 2.8 0.47 0.34 0.54 0.85Simpson dominance index 0.085 0.783 0.87 0.697 0.67ShrubsNo. <strong>of</strong> species 27 19 25 22 34No. <strong>of</strong> genera 22 18 25 23 33No. <strong>of</strong> family 18 13 17 16 21Density (individuals/m 2 ) 1 2 1 1 2Shannon-Weaver diversity index 3.13 2.59 2.51 2.84 2.56Simpson dominance index 0.049 0.113 0.12 0.08 0.13HerbsNo. <strong>of</strong> species 23 39 41 40 34No. <strong>of</strong> genera 21 38 41 39 33No. <strong>of</strong> family 15 25 26 23 21Density (individuals/m 2 ) 32 165 178 154 157Shannon-Weaver diversity index 2.69 2.83 2.44 2.48 2.41Simpson dominance index 0.097 0.138 0.22 0.198 0.2439

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIATable 4.7: Density, basal area, importance value index and distribution pattern <strong>of</strong> trees,shrubs and herbs in control standsTrees Family TI BA IVI A/FPithecellobium monadelphum (Roxb.) Koster Mimosaceae 2 0.03 5.3 0.200Castanopsis tribuloides (Sm.) DC Fagaceae 2 0.21 13.2 0.200Diospyros kaki Thunb. Ebenaceae 2 0.02 4.6 0.200Rhus acuminata DC. Anacardiaceae 3 0.04 8.3 0.075Quercus griffithii Hk.f&Th ex DC Fagaceae 7 0.32 30.7 0.028Schima wallichii (DC.)Korth Theaceae 1 0.00 3.0 0.100Eurya acuminata DC. Theaceae 2 0.01 4.4 0.200Syzygium tetragonum (Wt.) Kurz Myrtaceae 2 0.01 6.0 0.050Sapindus rarak DC. Sapindaceae 1 0.01 3.4 0.100Podocarpus nerrifolia D.Don. Podocarpaceae 1 0.05 5.3 0.100Camellia caudata Wall. Theaceae 38 0.11 54.5 0.078Beilschmedia roxburghiana Nees Laraceae 3 0.21 14.4 0.300Castanopsis purpurella (Miq.) Balak. Fagaceae 8 0.61 44.9 0.032Styrax serrulatum Roxb. Styraceae 1 0.00 2.9 0.100Cinnamomum granduliflerum (Wall.) Meissn. Lauraceae 2 0.21 15.1 0.050Pyrularia edulies A. DC Santalaceae 2 0.02 4.6 0.200Ficus nerifolia J.E.Sm. Moraceae 1 0.05 4.9 0.100Schefflera hypoleucea (Kurz) Harms Araliaceae 1 0.00 3.0 0.100Lindera latifolia Hk.f. Lauraceae 6 0.06 16.0 0.038Lithocarpus elagans (Bl.) Hatus ex Soep Fagaceae 5 0.10 14.7 0.056Eurya cerasifolia (D.Don) Kobuski Theaceae 4 0.06 12.0 0.044C<strong>of</strong>fea khasiana Hook.f. Rubiaceae 4 0.01 9.9 0.044Itea macrophylla Wall Itaceae 1 0.00 3.0 0.100Picresema sp. Simaroubiaceae 1 0.02 3.7 0.100Citrus latipes (Swingle)Tanaka Rutaceae 2 0.01 6.0 0.050Ficus hirta var Roxb (Mig.) King Moraceae 1 0.00 3.0 0.100Dysoxylum gobara (Buch.-Ham) Merr. Meliaceae 1 0.01 3.2 0.100104 2.19 300Shrubs Family TI IVI A/FRubus ellipticus Smith Rosaceae 5 7.26 0.125Rubus khasiana Cordat. Rosaceae 3 5.65 0.075Embelia vestita Roxb. Myrsinaceae 4 6.45 0.100Viburnum foetidum Wall. Caprifoliaceae 8 12.90 0.050Cassia floribunda Cav. Fabaceae 10 14.52 0.063Shutaria vestida W. & A. Rubiaceae 10 14.52 0.063Psychortia erratica Hook.f. Rubiaceae 10 16.13 0.040Psychortria curviflora Wall. Rubiaceae 7 13.71 0.028Erythroxylum kunthianum Wall. Ex Kurz Erythroxylaceae 1 2.42 0.100Prinsepia utilis Royle Rosaceae 3 5.65 0.075Jasminium dispermum Wall. Oleaceae 4 6.45 0.100Rubus assamensis Focke Rosaceae 1 2.42 0.100Rhynchotecum vestitum Wall. Ex Cl. Gesneriaceae 3 4.03 0.300Lasianthus sikkimensis Hook.f. Rubiaceae 5 8.87 0.056Polygonum molle D.Don Polygonaceae 6 9.68 0.067Ficus clavata Wall ex Miq. Moraceae 3 5.65 0.07540

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIAMeasa indica (Roxb.) Wall Myrsinaceae 4 6.45 0.100Lasianthus lucidus Bl. Rubiaceae 3 4.03 0.300Aralia thomsonii Seem. Araliaceae 1 2.42 0.100Euonymus lowsonii Clarke & Prain Celastraceae 4 6.45 0.100Corylopsis himalayana Griff. Hamamelidaceae 1 2.42 0.100Embelia subcoriaceae (Clarks) Mez. Myrsinaceae 1 2.42 0.100Breynia retusa (Dennst) Alst. Euphobiaceae 4 8.06 0.044Boehmeria sidaefolia Wedd. Urticaceae 4 4.84 0.400Solanum aculeatissimum Jacq. Solanaceae 2 3.23 0.200Plectranthus striatus Benth. Lamiaceae 10 14.52 0.063124 200Herbs Family TI IVI A/FLophatherum gracile Brongn. Poaceae 15 9.12 0.375Isachne himalaica Hook.f. Poaceae 31 20.95 0.124Selaginella semicordata (Wall ex. Hk.Et.Grev.) Selaginallaceae 44 29.52 0.090Hedychium ellepticum Smith Zingiberaceae 17 9.84 0.425Globba clarkii Baker. Zingiberaceae 73 38.73 0.149Begonia palmata D.Don Begoniaceae 4 3.49 0.400Impatiens khasiana Hk..f. Balsaminaceae 6 6.35 0.150Impatiens banthamii V.Steenis Balsaminaceae 5 3.81 0.500Commelina paludosca Bl. Commelinaceae 4 5.71 0.100Panicum brevifolium L. Poaceae 55 24.13 0.611Murdannia gigantean (Vahl.) Bruck. Commelinaceae 2 2.86 0.200Aeginetia indica Linn. Orobanchaceae 2 2.86 0.200Carex filicina Nees. Cyperaceae 1 2.54 0.100Crassocephalum crepidioides (Benth.) Moore Asteraceae 1 2.54 0.100Achyrospermum wallichianum (Benth.) Hk.f. Lamiaceae 8 4.76 0.800Elatostema dissectum Wedd. Urticaceae 10 5.40 1.000Elsholtzia blanda (Benth.) Benth. Lamiaceae 12 6.03 1.200Arisaema tortuosum (Wall.) Schott. Araceae 1 2.54 0.100Dianella ensata (Thunb.) R.J.Handerson Liliaceae 1 2.54 0.100Cyanotis vaga (Lour.) J.A.&J.H.Schult. Commelinaceae 5 3.81 0.500Balanophora dioica R.Br. Balanophoraceae 8 4.76 0.800Murdannia nudiflora (Linn.) Brenan Commelinaceae 2 2.86 0.200Sonerila khasiana Clarke Melastomaceae 8 4.76 0.800315 200TI= Total Individual IVI= Importance Value Index A= Abundance F=FrequencyTable 4.8: Density, basal area, importance value index and distribution pattern <strong>of</strong> trees,shrubs and herbs in zone-ITrees Family TI BA IVI A/FCamellia caudata Wall Theaceae 10 0.160 9.84 0.200Pinus kesiya Royle. Ex Gordon. Pinaceae 367 18.098 264.47 0.051Persea odoristimma (nees) Koster. Lauraceae 23 0.556 20.58 0.137Helecia nilagirica Bedd. Proteaceae 4 0.162 5.10 0.320404 18.98 30041

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIAShrubs TI IVI A/FCircium sp. Asteraceae 112 9.62 0.180Clerodendrum wallichii Merr. Verbenaceae 61 8.90 0.070Eupatorium adenophorum Spreng Asteraceae 1185 53.74 0.440Urena lobata Linn. Malvaceae 65 6.88 0.160Ficus clavata Wall ex Miq. Moraceae 55 5.99 0.180Lasianthus lucidus Bl. Rubiaceae 80 6.60 0.290Lantana camara Linn. Verbenaceae 174 11.54 0.310Lindera caudata Benth. Lauraceae 61 5.39 0.310Melastoma nepalensis Lodd. Melastomaceae 410 25.28 0.180Plectranthus striatus Benth. Lamiaceae 76 5.92 0.380Padocarpus neriifolia D.Don Podocaraceae 38 3.77 0.344Persea duthei (King ex Hk.f) Koster. Lauraceae 82 8.56 0.130Rhus acuminata DC. Anacardiaceae 22 4.28 0.090Rubus ellipticus Smith Rosaceae 20 2.59 0.290Rubus khasianas Cordat. Rosaceae 119 12.30 0.100Senecio cappa Buch.-Ham.ex D.Don Asteraceae 44 5.60 0.144Sida rhombilolia Linn. Malvaceae 133 11.44 0.150Solanum aculeatissimum Jacq. Solanaceae 52 5.88 0.170Symplocos pyrifolia Wall. Ex G.Don Symplocaceae 40 5.73 0.1002829 200Herbs Family TI IVI A/FAgeratum conyzoides Linn. Asteraceae 370 10.44 0.130Borreria articularis (L.f) F.N. Williams Rubiaceae 390 9.97 0.166Bidens pilosa (Bl.) Sherff Asteraceae 154 5.59 0.150Breynia retusa (Dennst) Alst. Euphorbiaceae 31 2.17 0.160Centella asiatica (Linn.) Urban Apiaceae 250 5.13 0.50Commelina paludosca Bl. Commelinaceae 213 5.77 0.250Crossouphalum sp. Asteraceae 30 1.69 0.270Crotalaria anagyroides HBK. Fabaceae 95 3.98 0.170Cyperus flavidus Tetz. Cyperaceae 79 3.53 0.180Emilia sonchifolia (Linn.) DC. Asteraceae 21 0.97 0.600Eupatorium adenophorum Spreng. Asteraceae 394 8.89 0.230Asplenium phyllitides D.Don Aspleniaceae 79 3.05 0.250Floscopa scandens Lour. Commelinaceae 11 1.05 0.220Gnaphalium pensylvanicum Willd. Asteraceae 43 2.75 0.140Hedera nepalensis K.Koch. Araliaceae 13 1.22 0.190Hedychium coccineum Smith Zingiberaceae 28 2.46 0.100Hodgsonia macrocarpa (Bl.) Cogn. Cucurbitaceae 19 1.59 0.170Isachne himalaica Hook.f. Poaceae 1324 15.75 1.130Lobelia angulata Forst. Campanulaceae 38 2.39 0.160Lycopodium cernum Linn. Lycopodeaceae 45 2.61 0.170Linderbergia muraria (Roxb.) Bruhl Scrophulariaceae 23 1.95 0.144Melastoma nepalensis Lodd. Melastomaceae 14 0.91 0.44Oxalis anaphelein L. Oxalidaceae 70 4.09 0.100Oxalis corniculata L. Oxalidaceae 129 4.11 0.260Pouzolzia hirta (Bl.) Hassk. Urticaceae 14 0.60 1.120Paspalum orbiculare Forst. Poaceae 7283 68.42 2.590Persea duthei (King ex Hk.f.) Koster. Lauraceae 29 1.36 0.430Plantago erosa Wall. Plantaginaceae 109 3.62 0.27042

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIAPolygonum barbata L Polygonaceae 30 2.00 0.180Potentilla fulgens Wall. Rosaceae 43 1.48 0.630Girardinia palmate (Forsk) Gaud. Urticaceae 82 1.65 1.640Pratia begonifolia (Wall.) Lindl. Campanulaceae 26 1.17 0.520Rubus ellipticus Smith. Rosaceae 50 2.97 0.140Scutelleria discolor Benth. Lamiaceae 8 0.70 0.360Senecio cappa Buch.-Ham. Ex D.Don Asteraceae 10 1.04 0.200Smithia ciliata Royle Fabaceae 46 1.50 0.680Solanum aculeatissimum Jacq. Solanaceae 107 5.20 0.110Viola palmaris Ging. Violaceae 98 3.53 0.240Unidentified 91 2.68 0.46011889 200TI= Total Individual IVI= Importance Value Index A= Abundance F=FrequencyTable 4.9: Density, basal area, importance value index and distribution pattern <strong>of</strong> trees,shrubs and herbs in zone-IITrees Family TI BA IVI A/FPinus kesiya Royle. Ex Gordon. Pinaceae 355 20.90 280.27 0.049Schima wallichii (DC.) Korth Theaceae 9 0.10 10.05 0.180Saurauria punduana Wall. Saurauiceae 1 0.01 1.49 0.720Rhus acuminata DC. Anacardiaceae 1 0.07 1.80 0.720Exbucklandia populnea Hammamalidaceae 2 0.03 3.07 0.360Macaranga denticulate Muell.-Arg. Verbenaceae 2 0.04 1.91 1.440Helecia nilagirica Bedd. Proteaceae 1 0.01 1.47 0.720371 21.16 300Shrubs Family TI IVI A/FCastanopsis indica A.Dc. Fagaceae 39 5.83 0.440Circium sp. Asteraceae 18 2.83 0.810Clerodendrum wallichii Merr. Verbenaceae 57 8.66 0.290Eupatorium adenophorum Spreng Asteraceae 271 27.55 0.290Eurya acuminata DC. Theaceae 76 10.67 0.280Ficus clavata Wall ex Miq. Moraceae 1 0.50 0.720Lantana camara Linn. Verbenaceae 274 26.41 0.370Lindera caudata Benth. Lauraceae 7 1.29 1.260Macaranga denticulate Muell.-Arg. Verbenaceae 2 0.56 1.440Melastoma nepalensis Lodd. Melastomaceae 533 48.86 0.250Mahonia pycnophylla (Fedde) Takeda Berberidaceae 10 2.35 0.450Nellia thyrsiflora D.Don Rosaceae 9 1.41 1.620Padocarpus neriifolia D.Don Podocaraceae 5 0.74 3.600Persea duthei (King ex Hk.f) Koster. Lauraceae 2 0.56 1.440Plectranthus striatus Benth. Lamiaceae 37 5.27 0.540Rhus acuminata DC. Anacardiaceae 5 0.74 3.600Rubus ellipticus Smith Rosaceae 153 23.15 0.110Saurauia punduana Wall. Saurauiaceae 18 4.14 0.260Schima wallichii (DC.) Korth Theaceae 8 1.79 0.640Senecio cappa Buch.-Ham.ex D.Don Asteraceae 65 9.14 0.330Sida rhombilolia Linn. Malvaceae 24 4.06 0.480Smilax aspera L. Smilacaceae 11 1.97 0.880Solanum aculeatissimum Jacq. Solanaceae 20 3.82 0.400Symplocos spicata Roxb. Symplocaceae 24 5.38 0.21043

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIAUrena lobata Linn. Malvaceae 9 2.29 0.4101678 200Herbs Family TI IVI A/FAgeratum conyzoides Linn. Asteraceae 160 5.73 0.450Anaphalis adnata DC. Asteraceae 41 1.72 1.180Borreria articularis (L.f) F.N. Williams Rubiaceae 60 1.03 1.080Borreria sp. Rubiaceae 363 12.07 0.240Bidens pilosa (Bl.) Sherff Asteraceae 87 4.32 0.370Breynia retusa (Dennst) Alst. Euphorbiaceae 42 2.57 0.470Carytia japonica L. Vitaceae 3 0.30 2.160Centella asiatica (Linn.) Urban Apiaceae 64 4.14 0.270Commelina paludosca Bl. Commelinaceae 199 7.43 0.320Crassocephalum sp. Asteraceae 55 3.23 0.400Crotalaria anagyroides HBK. Fabaceae 14 0.67 2.520Cyperus flavidus Tetz. Cyperaceae 71 3.63 0.420Drymaria cordata (Linn.) Roem. & Schult. Caryophyllaceae 178 4.75 0.890Emilia sonchifolia (Linn.) DC. Asteraceae 54 1.82 1.560Eriosaema himalaicum Ohashi Fabaceae 8 0.34 5.760Eupatorium adenophorum Spreng. Asteraceae 118 3.16 1.330Asplenium phyllitides D.Don Aspleniaceae 87 2.08 2.510Floscopa scandens Lour. Commelinaceae 1 0.29 0.720Gnaphalium pensylvanicum Willd. Asteraceae 100 4.42 0.430Hedera nepalensis K.Koch. Araliaceae 2 0.30 1.444Hedychium coccineum Smith Zingiberaceae 3 0.30 2.160Hedyotis tenelliflora Bl. Rubiaceae 10 0.36 7.200Hodgsonia macrocarpa (Bl.) Cogn. Cucurbitaceae 13 0.94 1.040Isachne himalaica Hook.f. Poaceae 976 16.29 0.730Lantana camara Linn. Verbenaceae 2 0.30 1.440Melastoma nepalensis Lodd. Melastomataceae 289 5.61 1.450Nepenthus khasiana L Nepenthaceae 4 0.31 2.880Osbeckia capitala Benth. Melastomataceae 64 2.46 0.940Oxalis corniculata L. Oxalidaceae 33 1.38 1.490Pouzolzia hirta (Bl.) Hassk. Urticaceae 13 0.66 2.340Paspalum orbiculare Forst. Poaceae 9290 89.45 1.800Persea duthei (King ex Hk.f.) Koster. Lauraceae 8 0.34 5.760Plantago erosa Wall. Plantaginaceae 145 3.93 1.040Polygonum barbata L Polygonaceae 25 1.04 2.000Potentilla fulgens Wall. Rosaceae 69 2.50 1.010Pratia begonifolia (Wall.) Lindl. Campanulaceae 95 4.10 0.480Rubus sp. Rosaceae 7 0.61 1.260Senecio cappa Buch.-Ham. Ex D.Don Asteraceae 25 1.60 0.720Smithia ciliata Royle Fabaceae 21 0.72 3.780Solanum aculeatissimum Jacq. Solanaceae 5 0.32 3.600Viola palmaris Ging. Violaceae 30 2.75 0.27012834 200TI= Total Individual IVI= Importance Value Index A= Abundance F=Frequency44

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIATable 4.10: Density, basal area, importance value index and distribution pattern <strong>of</strong>trees, shrubs and herbs in the zone-IIITrees Family TI BA IVI A/FPinus kesiya Royle. Ex Gordon. Pinaceae 357 13.848 246.05 0.050Schima wallichii (DC.) Korth Theaceae 67 0.516 46.36 0.057Ligustrum robustum (Roxb.) Warb. Oleaceae 10 0.076 7.54 0.288434 14.44 300Shrubs Family TI IVI A/FCastanopsis indica A.Dc. Fagaceae 46 7.70 0.070Clerodendrum wallichii Merr. Verbenaceae 59 7.59 0.120Datura stromonium Linn. Solanaceae 17 3.06 0.150Eurya acuminata DC. Theaceae 36 5.97 0.090Eupatorium adenophorum Spreng Asteraceae 345 22.78 0.430Ficus clavata Wall ex Miq. Moraceae 28 4.59 0.120Lasianthus lucidus Bl. Rubiaceae 79 8.07 0.200Lyonia ovalifolia var. ovalifolia (Wall.) Drude Ericaceae 24 3.40 0.210Lantana camara Linn. Verbenaceae 333 23.93 0.250Lindera caudata Benth. Lauraceae 11 2.27 0.166Melastoma nepalensis Lodd. Melastomaceae 527 37.86 0.166Nellia thyrsiflora D.Don Rosaceae 20 2.96 0.230Padocarpus neriifolia D.Don Podocaraceae 13 2.87 0.120Persea duthei (King ex Hk.f) Koster. Lauraceae 20 3.70 0.120Plectranthus striatus Benth. Lamiaceae 43 6.07 0.120Rhus acuminata DC. Anacardiaceae 29 4.39 0.150Rubus ellipticus Smith Rosaceae 76 7.92 0.190Rubus khasianas Cordat. Rosaceae 85 9.85 0.120Senecio cappa Buch.-Ham.ex D.Don Asteraceae 49 6.61 0.120Sida rhombilolia Linn. Malvaceae 21 3.01 0.240Schima wallichii (DC.) Korth Theaceae 42 5.52 0.150Solanum aculeatissimum Jacq. Solanaceae 41 4.98 0.210Symplocos spicata Roxb. Symplocaceae 27 5.04 0.090Urena lobata Linn. Malvaceae 79 9.81 0.1002050 200Herbs Family TI IVI A/FAgeratum conyzoides Linn. Asteraceae 231 11.68 0.140Anaphalis adnata DC. Asteraceae 7 1.43 0.200Ainsliaea latifolia (D.Don) Sch. Asteraceae 23 2.13 0.340Borreria articularis (L.f) F.N. Williams Rubiaceae 358 14.47 0.150Bidens pilosa (Bl.) Sherff Asteraceae 28 1.62 0.810Breynia retusa (Dennst) Alst. Euphorbiaceae 15 1.51 0.430Crotalaria anagyroides HBK. Fabaceae 14 0.95 1.122Centella asiatica (Linn.) Urban Apiaceae 44 2.86 0.390Commelina paludosca Bl. Commelinaceae 146 7.35 0.222Crossouphalum sp. Asteraceae 25 2.14 0.370Cyperus flavidus Tetz. Cyperaceae 69 4.46 0.250Drymaria cordata (Linn.) Roem. & Schult. Caryophyllaceae 368 6.62 1.84045

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIAEmilia sonchifolia (Linn.) DC. Asteraceae 1 0.28 0.720Eupatorium adenophorum Spreng. Asteraceae 2 0.57 0.360Asplenium phyllitides D.Don Aspleniaceae 93 3.86 0.550Floscopa scandens Lour. Commelinaceae 2 0.29 1.444Gnaphalium pensylvanicum Willd. Asteraceae 40 1.73 1.150Hedera nepalensis K.Koch. Araliaceae 2 0.29 1.444Impatiens khasiana Hk..f. Balsaminaceae 55 2.42 0.810Isachne himalaica Hook.f. Poaceae 1254 19.57 1.000Lophatherum gracile Brongn. Poaceae 23 1.58 0.660Leucus ciliata L. Lamiaceae 23 1.30 1.040Lobelia angulata Forst. Campanulaceae 11 0.65 1.980Lycopodium cernum Linn. Lycopodiaceae 44 2.59 0.500Oxalis corniculata L. Oxalidaceae 34 1.13 2.720Polygonum barbata L Polygonaceae 7 0.61 1.260Pouzolzia hirta (Bl.) Hassk. Urticaceae 20 1.28 0.900Paspalum orbiculare Forst. Poaceae 7721 83.29 2.320Persea duthei (King ex Hk.f.) Koster. Lauraceae 3 0.58 0.540Plantago erosa Wall. Plantaginaceae 136 4.24 0.810Polygonum viscosum D.Don Polygonaceae 3 0.30 2.160Potentilla fulgens Wall. Rosaceae 8 0.62 1.444Pratia begonifolia (Wall.) Lindl. Campanulaceae 84 4.05 0.420Rubus sp. Rosaceae 13 0.94 1.040Scutelleria discolor Benth. Lamiaceae 11 1.47 0.320Senecio cappa Buch.-Ham. Ex D.Don Asteraceae 25 1.32 1.130Smithia ciliata Royle Fabaceae 53 3.77 0.270Solanum aculeatissimum Jacq. Solanaceae 31 1.92 0.620Viola palmaris Ging. Violaceae 7 0.34 5.040Unidentified 18 1.81 0.36011052 200TI= Total Individual IVI= Importance Value Index A= Abundance F=FrequencyTable 4.11: Density, basal area, importance value index and distribution pattern <strong>of</strong> trees, shrubsand herbs in the zone-IVTrees Family TI BA IVI A/FPinus kesiya Royle. Ex Gordon. Pinaceae 398 22.25 243.93 0.060Schima wallichii (DC.) Korth Theaceae 23 0.37 18.91 0.080Saurauria punduana Wall. Saurauiceae 21 0.50 11.06 0.610Rhus javanica Linn. Anacardiaceae 1 0.03 1.24 0.720Rhus acuminata DC. Anacardiaceae 3 0.04 3.48 0.240Plangium chinensis L. Cornaceae 2 0.04 2.37 0.360Litsea citrata Bl. Lauraceae 4 0.05 4.60 0.180Lindera caudata Benth. Lauraceae 5 0.09 4.98 0.230Myrica esculanta Buch.-Ham. Ex D.Don Myricaceae 3 0.03 3.42 0.240Macaranga denticulate Muell.-Arg. Verbenaceae 3 0.04 2.57 0.540Helecia nilagirica Bedd. Proteaceae 3 0.04 3.47 0.240466 23.48 30046

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIAShrubs Family TI IVI A/FCastanopsis indica A.Dc. Fagaceae 15 1.60 1.200Circium sp. Asteraceae 32 6.24 0.120Clerodendrum wallichii Merr. Verbenaceae 14 2.31 0.400Datura stromonium Linn. Solanaceae 14 1.94 0.633Elaegnus sp. Eleagnaceae 4 0.87 0.720Eupatorium adenophorum Spreng Asteraceae 920 40.52 0.740Eurya acuminata DC. Theaceae 71 5.99 0.510Ficus clavata Wall ex Miq. Moraceae 1 0.41 0.720Lasianthus lucidus Bl. Rubiaceae 2 0.81 0.360Lantana camara Linn. Verbenaceae 1071 49.44 0.460Lyonia ovalifolia var. ovalifolia (Wall.) Drude Ericaceae 18 2.07 0.810Lindera caudata Benth. Lauraceae 5 0.53 3.600Itea macrophylla Wall. Iteaceae 75 3.14 13.500Macaranga denticulate Muell.-Arg. Verbenaceae 18 2.07 0.810Melastoma nepalensis Lodd. Melastomaceae 370 23.36 0.280Nellia thyrsiflora D.Don Rosaceae 20 2.88 0.400Girardinia palmata (Forsk) Gaud. Urticaceae 2 0.81 0.360Persea duthei (King ex Hk.f) Koster. Lauraceae 7 1.72 0.320Prunus acuminata (Wall.) Dietr. Rosaceae 1 0.41 0.720Rhus acuminata DC. Anacardiaceae 23 3.35 0.344Prinsepia utilis Royle Rosaceae 4 0.87 0.720Rubus ellipticus Smith Rosaceae 4 0.87 0.720Rubus khasianas Cordat. Rosaceae 125 14.81 0.111Saurauia punduana Wall. Saurauiaceae 11 1.84 0.500Schima wallichii (DC.) Korth Theaceae 1 0.41 0.720Senecio cappa Buch.-Ham.ex D.Don Asteraceae 169 13.22 0.280Sida rhombilolia Linn. Malvaceae 1 0.41 0.720Smilax myrtillus DC. Smilacaceae 13 2.65 0.260Solanum aculeatissimum Jacq. Solanaceae 32 4.01 0.360Symplocos spicata Roxb. Symplocaceae 9 1.03 1.620Thysanolaena maxima (Roxb.) O. Ktze. Poaceae 30 2.08 2.400Triumfetta tomentosa Bojer Tiliaceae 10 0.69 7.200Urena lobata Linn. Malvaceae 20 2.13 0.900Wendlandia wallichii W.&A.Prodr. Rubiaceae 25 4.53 0.1803137 200Herbs Family TI IVI A/FAgeratum conyzoides Linn. Asteraceae 132 6.00 0.560Anaphalis adnata DC. Asteraceae 61 3.14 0.900Borreria articularis (L.f) F.N. Williams Rubiaceae 49 2.67 0.980Barreria sp. Rubiaceae 95 4.93 0.570Bidens pilosa (Bl.) Sherff Asteraceae 139 4.95 1.000Breynia retusa (Dennst) Alst. Euphorbiaceae 43 2.24 1.240Centella asiatica (Linn.) Urban Apiaceae 31 2.13 0.890Commelina paludosca Bl. Commelinaceae 118 6.62 0.380Crossouphalum sp. Asteraceae 76 4.39 0.550Cyperus flavidus Tetz. Cyperaceae 90 6.00 0.333Dicranopteris linearis (Burm.f) Undewood Gleicheniaceae 20 0.92 3.600Drymaria cordata (Linn.) Roem. & Schult. Caryophyllaceae 72 2.50 2.070Emilia sonchifolia (Linn.) DC. Asteraceae 55 3.09 0.810Eupatorium adenophorum Spreng. Asteraceae 96 3.83 1.080Asplenium phyllitides D.Don Aspleniaceae 64 2.80 1.280Gnaphalium pensylvanicum Willd. Asteraceae 224 9.05 0.450Hedychium coccineum Smith Zingiberaceae 41 1.48 3.280Hedyotis tenelliflora Bl. Rubiaceae 45 1.14 8.10047

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIAIsachne himalaica Hook.f. Poaceae 75 1.78 6.000Lobelia angulata Forst. Campanulaceae 10 1.20 0.800Elsholtzia blanda (Benth.) Benth. Lamiaceae 23 1.32 1.840Melastoma nepalensis Lodd. Melastomaceae 77 3.29 1.130Osbeckia capitala Benth. Melastomaceae 136 5.30 0.810Oxalis corniculata L. Oxalidaceae 55 3.46 0.620Paspalum orbiculare Forst. Poaceae 9125 95.47 4.320Plantago erosa Wall. Plantaginaceae 107 7.27 0.270Polygonum barbata L Polygonaceae 27 1.73 1.220Potentilla fulgens Wall. Rosaceae 19 0.91 3.420Pratia begonifolia (Wall.) Lindl. Campanulaceae 74 5.12 0.370Rubus sp. Rosaceae 7 0.81 1.260Smithia ciliata Royle Fabaceae 43 1.50 3.440Smilax aspera L. Smilacaceae 18 1.27 1.440Viola palmaris Ging. Violaceae 5 0.42 3.600Unidentified 21 1.30 1.68011273 200TI= Total Individual IVI= Importance Value Index A= Abundance F=Frequency48

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIA4.4. Change Detection4.4.1. Land Use/ Land Cover Distribution and ChangesIn order to put any change into a proper perspective, it is useful to establish the state <strong>of</strong> theenvironment in the selected base year. The aerial extent <strong>of</strong> each land use/ land cover class in thedifferent years i.e., 1975, 1987, 1999 and 2001 was analysed in order to get an overview <strong>of</strong> changes inmagnitude so as to justify the change analysis (Figure 4.6, Figure 4.7, Figure 4.8, Figure 4.9).It was found that most <strong>of</strong> the areas were dominated by grassland/ non-forest (64.7 to 66.1 percent)during the course <strong>of</strong> the study. The forest area covered about 25 percent <strong>of</strong> the total area during 1975.This had decreased to about 16 percent in the year 2001. The coal mining areas occupied aconsiderable portion that ranged between 3 to more than 10 percent <strong>of</strong> the area. The settlement arearanged between 4 and 7 percent and the crop area was found quite less (1.5-2.7 percent) (Table 4.12).Table 4.12: Area (km 2 ) under different land use/ land cover categories in different yearsYears <strong>Mining</strong> area Dense forestGrassland/Non-forest Open forest Settlement Cropped area1975 13.76 (3.26%) 95.12 (22.5%) 271.23 (64.65%) 11.69 (2.76%) 17.63 (4.17%) 11.21 (2.65%)1987 28.86 (6.78%) 65.04 (15.7%) 272.39 (64.71%) 24.16 (5.68%) 23.48 (5.52%) 6.57 (1.54%)1999 40.21 (9.05%) 51.64 (12.23%) 273.01 (66.07%) 18.95 (4.38%) 28.49 (6.75%) 6.88 (1.52%)2001 45.24 (10.75%) 51.52 (12.34%) 273.36 (64.98%) 14.12 (3.35%) 29.20 (6.94%) 6.83 (1.62%)During the entire study period there were changes in the land cover and land uses. <strong>Mining</strong> wasinitiated in the area in early 1970s. As a result <strong>of</strong> what lots <strong>of</strong> the area were converted into miningareas. The forests were mostly victimized due to mining activity (13 to 45 km 2 ). There was gradualdecrease <strong>of</strong> forest both dense and open during the course <strong>of</strong> time. The total forest area lost during thestudy period was 40.53 km 2 , which was about 40 percent <strong>of</strong> the total forest area. There was loss <strong>of</strong>43.5 km 2 dense forest area from the study area, which was 45.7 percent <strong>of</strong> the total area under denseforest. There was increase <strong>of</strong> 2.43 km 2 open forest area during the study period. This was due to theconversion <strong>of</strong> the dense forest to the open forest (95 to 65 km 2 ). There were not much variation indense forest during the year 1999 and 2001. But area under open forest had reduced during this period(Figure 4.10).As the mining operation started, there was lots <strong>of</strong> demand <strong>of</strong> manpower to work in the coalfields.Development <strong>of</strong> the infrastructure started in this period (Figure 4.11). Dense forest areas were targetedto accommodate these facilities. During this period a considerable portion <strong>of</strong> the dense forest area wereconverted into non-forest like, settlement, roads and grasslands. Grasslands were outcome <strong>of</strong> themining. When extraction and supply <strong>of</strong> coal was over the areas kept fallow. In course <strong>of</strong> time thoseareas were covered with grasses that could grow in the harsh edaphic conditions. No other plantspecies could grow in that area and it became completely abandoned (Figure 4.12). The local peoplealso inclined towards the mining activities and most <strong>of</strong> the agricultural fields were converted intomining areas. It was found that there was not much impact on the grassland and existing non-forestareas <strong>of</strong> the region since the mining was introduced.49

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIAFigure 4.6: Land use/ land cover in 1975.50




IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIAPrakash and Gupta (1998) studied the land use/ land cover changes <strong>of</strong> Jharia coal field <strong>of</strong> India andconcluded that there were gradual decrease and threat to the vegetation present in the area wheremining was prominent. Ghosh (1998) emphasized that due to the consequences <strong>of</strong> mining activitiesthere were thorough change in the natural topography <strong>of</strong> the region.1000Area (km 2 )1001011975 1987 1999 2001Years<strong>Mining</strong> area Dense forest Grassland/ Non-forestOpen forest Settlement Cropped areaFigure 4.10: Area under different land use/ land cover categories in different years.(a)(b)Figure 4.11: <strong>Mining</strong> operation attracted people from far-flung areas. Growth <strong>of</strong> urbancentre (a) and hamlets (b) around mines are the result <strong>of</strong> mining.(a)(b)Figure 4.12: Unsuccessful forest plantations were carried out by the Govt. Departments onthe mine spoils.54

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIA4.4.2. Changes in different land use/ land cover categories from 1975 to 2001To understand the land use dynamics related to vegetation and mining, successive land cover changemaps <strong>of</strong> 1975 and 1987, 1987 and 1999 and 1999 and 2001 has been prepared. Seven classes <strong>of</strong>changes i.e., dense forest to open forest, dense forest to mining, dense forest to non-forest, open forestto mining, open forest to non-forest, no change and others are considered (Figure 4.14, Figure 4.15,Figure 4.16).It was found from the change analysis that there was impact <strong>of</strong> mining to different land uses, whichwere directly or indirectly related to vegetation. About 6 km 2 <strong>of</strong> the dense forest <strong>of</strong> the study area werechanged to the open forest during 1975 to 1987. This rate <strong>of</strong> change was not maintained in theproceeding years. More than 6 km 2 area <strong>of</strong> open forest converted into non-forest during that period.The changes <strong>of</strong> about 25 percent <strong>of</strong> the total area could tell how much stress was going on to thelandscape during 12 years <strong>of</strong> time. During 1987 to 1999 changes occurred in about 20 percent <strong>of</strong> thetotal area. About 4 km 2 <strong>of</strong> the dense forest were converted into open forest during this period. Thechange <strong>of</strong> open forest area to the non-forest recorded a considerable portion (12.87 km 2 ). During theyears 1999 and 2001 about 7 percent <strong>of</strong> the total area undergone changes. During this period about 3percent <strong>of</strong> the area were converted into non-forest either from dense forest or open forest (Table 4.13).The changes that occurred due to the direct or indirect impact <strong>of</strong> mining are represented in Figure 4.13.Prakash and Gupta (1998) while studying the change analysis <strong>of</strong> the Jharia coal field found that therewere changes in different land uses. They concluded that there was general decrease in the vegetationcover. But after the change detection analysis it was apparent that due to the initiation <strong>of</strong> afforestationactivities there were increase in the vegetation cover in the study area. The classification done for thechange analysis for the study were open cast mining, new plantation level out area and area <strong>of</strong> nochange. Rathore and Wright (1993) emphasized that the mining and changes were correlated to eachother.Table 4.13: Changes in land use/ land cover in different yearsChange type 1975-87 1987-99 1999-2001Dense to open Forest 5.92 (1.41%) 3.68 (0.88%) 0.86 (0.21%)Dense forest to mining 0.61 (0.15%) 0.09 (0.02%) 0.06 (0.01%)Dense forest to non-forest 29.35 (6.99%) 19.25 (4.58%) 4.64 (1.11%)Open forest to mining 0.22 (0.05%) 0.41 (0.1%) 0.12 (0.03%)Open forest to non-forest 6.53 (1.55%) 12.87 (3.07%) 5.51 (1.31%)No change 318.16 (75.75%) 335.81 (79.96%) 390.35 (92.94%)Others 59.19 (14.09%) 47.86 (11.4%) 18.46 (4.4%)Total 420 (100%) 420 (100%) 420 (100%)55

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIA1000100Area (km 2 )1010.10.011975-87 1987-99 1999-2001YearsDense to open forestDense forest to non-forestOpen forest to non-forestOthersDense forest to miningOpen forest to miningNo changeFigure 4.13: Changes in different land use/ land cover categories in different years.56

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIAFigure 4.14: Changes <strong>of</strong> land use/ land cover from 1975 to 1987.57



IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIA4.4.3. Forest FragmentationForest fragmentation occurs when large, continuous forests are converted into smaller blocks, either byroads, clearing for agriculture, urbanization, or other human developments. The forest fragmentationmaps <strong>of</strong> four different years have been prepared for the present study to delineate the areas, which areunder risk due to the impact <strong>of</strong> coal mining. The degree <strong>of</strong> fragmentation is classified as non-forestarea, high fragmentation area and low fragmentation area (Figure 4.18, Figure 4.19, Figure 4.20,Figure 4.21).A considerable portion <strong>of</strong> the study area were dominated by non-forest (68.4-75 percent). It wasapparent from the maps that high fragmentation areas were located close to the mines. During the year1975 and 2001 more than 20 km 2 area <strong>of</strong> low fragmentation were converted either to highlyfragmented or non-forest areas. As expected there was increasing trend for the areas under highfragmentation. In case <strong>of</strong> the year 1999 to 2001 there were loss <strong>of</strong> high fragmentation area <strong>of</strong> about 9km 2 and those areas were converted to the non-forest area. More than 68 km 2 (16 percent) area wereidentified as the areas at risk. The area under non-forest was more in 2001 than the past years (Table4.14). The areas under different fragmentation classes are represented in Figure 4.17.Table 4.14: Area (km 2 ) and proportion (%) <strong>of</strong> different fragmentation classes in different years1975 1987 1999 2001Low fragmentation 74.58 (17.76%) 56.49 (13.45%) 37.37 (8.90%) 36.92 (8.79%)High fragmentation 57.05 (13.58%) 76.29 (18.17%) 77.44 (18.44%) 68.23 (16.24%)Non-forest 288.37 (68.66%) 287.22 (68.39%) 305.19 (72.66%) 314.85 (74.96%)Total 420 (100%) 420 (100%) 420 (100%) 420 (100%)350300250Area (km 2 )2001501005001975 1987 1999 2001YearsLow fragmentation High fragmentation Non-forestFigure 4.17: Areas under different fragmentation classes in different years.60

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIAFigure 4.18: Forest fragmentation in 1975.61




IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIA5. General Discussion andConclusions5.1. Discussion and ConclusionsJaintia Hills district <strong>of</strong> Meghalaya has a total coal deposit <strong>of</strong> about 40 million tonnes. The district hasbeen most extensively exploited for coal. Although only 7 percent coal deposits are found in thedistrict, it contributes more than 74 percent <strong>of</strong> the total coal production in Meghalaya. The coalfields<strong>of</strong> the Jaintia Hills district are small and highly dispersed. <strong>Coal</strong> is mostly found in Bapung, Lakadong,Jarain-Shkentalang, Lumshnong, Malwar-Musiang-Lamare, Sutnga, Ioksi, Chyrmang and Mutang.The unscientific extraction <strong>of</strong> coal in unorganized sector is going on since long and the area affectedby coal mining is increasing day by day.Due to extensive coal mining, large areas <strong>of</strong> the district have been turned into degraded land, creatingunfavourable habitat conditions for plants and animals. <strong>Mining</strong> <strong>of</strong> coal has caused massive damage tothe landscape and biological communities. It was found that the number <strong>of</strong> tree and shrub speciesdecreased due to mining. The unfavourable habitat conditions prevailing in the coal-mined areas havereduced the chances <strong>of</strong> regeneration <strong>of</strong> many a species, thereby reducing the number <strong>of</strong> species in themined areas. Although the number <strong>of</strong> trees and shrubs have decreased, the number <strong>of</strong> herbaceousspecies colonizing the mined areas were found to be higher than in unmined areas. Similarobservations were made by several workers in the coal mining areas in different parts <strong>of</strong> the world(Cornwell, 1971; Fyles et al., 1985; Game et al., 1982; Singh and Jha, 1987; Jha and Singh, 1990).The density <strong>of</strong> tree species decreased considerably in the mined areas. The density <strong>of</strong> the shrub speciesdid not vary much. Lyngdoh (1995) and Das Gupta (1999) in Jaintia Hills, and Sarma (2002) in GaroHills district <strong>of</strong> the state had similar observations. This could be due to the better ability <strong>of</strong> herbs toadapt to the disturbed sites. Some herbaceous species invaded the newly created habitats. Nepentheskhasiana was documented from the mined areas (Figure 5.1). Meghalaya is the only home for thisendangered species. Due to indiscriminate mining throughout the district this rare species is highlythreatened.Figure 5.1: The Nepenthes khasiana (pitcher plant), an endangered species, threateneddue to indiscriminate mining.65

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIAThe Khasi pine, Pinus kesiya was the dominant tree species in the study area. The high importancevalue index <strong>of</strong> Pinus kesiya in mining areas suggests its ability to grow in the disturbed environments.The importance value index <strong>of</strong> Schima wallichii was next to Pinus kesiya, which indicates thedegraded environment <strong>of</strong> the area. The dominant shrub species in the mined areas were Eupatoriumadenophorum, Melastoma nepalensis and Lantana camara. The dominant herbaceous species in themining area was Paspalum orbiculare, which suggests that it can multiply rapidly in the disturbedenvironments. The characteristics <strong>of</strong> this perennial grass by virtue <strong>of</strong> its stolon and rooting at eachnode can bind the soil particles, making the soil more stable. This grass plays an important role in soilstabilization. This is in agreement with the findings <strong>of</strong> Ries and H<strong>of</strong>man (1983), who observed thatperennial grasses were well-suited to grow on the mine spoils.Dominance-diversity curves for the mined sites resembled with broken-stick series model. This couldbe attributed to the lesser number <strong>of</strong> species occurring in these stressed environments where conditionsare not favourable for plant growth. Species diversity was low on these sites, but the species that growhere appear to have developed tolerance.Shannon-Weaver index <strong>of</strong> diversity for tree species was much lower in the mined areas compre tocontrol. This suggests dominance <strong>of</strong> one or two species in the mined area. The Shannon-Weaverdiversity index for the shrub species was lower in the mined areas than the control. There were notmany differences in the diversity <strong>of</strong> herbaceous vegetation in both the areas. The diversity index forherbaceous species increased with mining proximities suggesting that mining operation favouredcolonization <strong>of</strong> certain species in the newly created habitats. Similar observation was made byLyngdoh (1995), Das Gupta (1999) and Sarma (2002).The trees <strong>of</strong> medium girth class (55-95cm) dominated the mined areas. Unmined area had moreindividuals <strong>of</strong> lower girth class (15-35cm) even though trees <strong>of</strong> all girth classes were present in thearea. In unmined areas, it was found that density <strong>of</strong> smaller and middle sized trees was higher than theold trees. This indicates a stable tree population structure. Such population structure is represented bya normal case and suggests that the forest is growing and would continue to exist. However, in themined areas, the tree density in all the girth classes was extremely low and did not follow any standarddensity diameter population curve. This has been due to rampant and random clearing <strong>of</strong> forest areasfor mining purpose that has led to drastic change in tree population structure. Such a trend inpopulation structure does not indicate the continued existence <strong>of</strong> the forest.The basal area in the unmined areas was found lower than the mined area. This was due to thedominance <strong>of</strong> low girth class trees, which had regenerated in the unmined area. The higher basal areain the mined areas could be attributed to the existence <strong>of</strong> bigger trees. Bigger trees are normally sparedduring mining operations by the miners. This indicates the removal <strong>of</strong> younger trees during miningactivities. Such a trend leads to the failure <strong>of</strong> the community to generate back. Paijman (1970) andParthasarathi and Karthikeyan (1997) made similar observations in New Guinea and India,respectively.In the unmined area both trees and shrubs showed contagious distribution pattern. All species in themined areas showed contagious pattern <strong>of</strong> distribution. The contagious distribution pattern <strong>of</strong> speciesindicated the mosaiced structure <strong>of</strong> the forest stand. The contagious <strong>of</strong> the species suggests theincrease in patchiness <strong>of</strong> the natural vegetation due to mining. This is in agreement with the findings <strong>of</strong>66

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIARao et al. (1990), who observed that due to disturbance contagiousness increased. Webb et al. (1967),Austin et al. (1972) and Ashton (1972) indicated that in the absence <strong>of</strong> major disturbances, soil andwater conditions play significant roles in controlling such distribution pattern.The mining <strong>of</strong> coal initiated in Jaintia Hills district <strong>of</strong> Meghalaya in the early 1970s. As the miningoperation started, there was lots <strong>of</strong> demand <strong>of</strong> manpower to work in the coalfields. Development <strong>of</strong> theinfrastructure started in this period. Dense forest areas were targeted to accommodate these facilities.During this period a considerable portion <strong>of</strong> the dense forest were converted into non-forest like,settlement, roads and grassland. Grasslands were outcome <strong>of</strong> the mining. When extraction and supply<strong>of</strong> coal was over the areas kept fallow. In course <strong>of</strong> time those areas were covered with grasses thatcould grow in the harsh edaphic conditions. No other plant species could grow in that area and itbecame completely abandoned. The local people also inclined towards the mining activities and most<strong>of</strong> the agricultural fields were converted into mining areas. The decrease in cropped area might also bedue to the loss <strong>of</strong> nutrient in the soil as a result <strong>of</strong> the dumping <strong>of</strong> the waste materials in and around themining. It was found that there was not much impact on the grassland and existing non-forest areas <strong>of</strong>the region since the mining was introduced. There was gradual decrease <strong>of</strong> forest both dense and openduring the course <strong>of</strong> time. There was an increase in the open forest during 1975 and 1987. This wasdue to the conversion <strong>of</strong> the dense forest into the open forest. There were not much variation in denseforest during the year 1999 and 2001. But area under open forest had reduced during this period.The study on the impact <strong>of</strong> coal mining on land use changes have been carried out world wide (Kosterand Slob, 1994; Schejbal, 1995; Prakash and Gupta, 1998; Ghosh, 1998; Rathore and Wright, 1993).The change analysis <strong>of</strong> different components showed that there was decrease in the change <strong>of</strong> denseforest to open forest as time passed, also dense forest to mining. During the initial stage mining wascarried out mostly in the dense forest areas <strong>of</strong> the state. These forest areas got fragmented and existedas the open forest. The conversion <strong>of</strong> the dense forest into non-forest also showed the decreasing trend.The reason may be the same. There was gradual increase in the change <strong>of</strong> open forest to mining andnon-forest areas. This could be concluded that there was lots <strong>of</strong> impact on the open forest areas inrecent years.The area under low fragmentation decreased significantly as the time passed. The high fragmentationarea, which were the areas at risk increased as the activity <strong>of</strong> coal mining had increased since itsinception. More than 68 km 2 (16 percent) area were identified the areas at risk. The areas <strong>of</strong> non-forestalso increased from the starting. There was loss <strong>of</strong> about 9 km 2 area <strong>of</strong> high fragmentation in threeyears period from 1999 to 2001 and was converted into non-forest area. Goretti (1998), Koster andSlob (1994) and Schejbal (1995) concluded that the vegetation got lost due to the spread out <strong>of</strong> wastematerials haphazardly in the areas <strong>of</strong> coal mining, which were very unhealthy for its growth.5.2. Review <strong>of</strong> Results and DiscussionIn executing this study, the different vegetation community characteristics, tree population structure,distribution pattern, land use/ land cover distribution and changes, change analysis <strong>of</strong> different landuses related to forest and mining and forest fragmentation were analysed to achieve the objectives <strong>of</strong>the study. The result <strong>of</strong> the study shows that:• There were more or less same impact on the community characteristics <strong>of</strong> vegetation due tocoal mining in the first three impact zones. The impact was less in the fourth zone.67

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIA• Number <strong>of</strong> tree and shrub species got reduced and herbaceous species increased in number inthe mined areas as compared to the unmined area.• Pinus kesiya was dominant tree species followed by the Schima wallichii, Eupatoriumadenophorum, Melastoma nepalensis and Lantana camara. Paspalum orbiculare was thedominant herbaceous species in all the zones <strong>of</strong> the mined.• Dominance-diversity curves showed the broken stick model in the mine areas.• Shannon-Weaver index <strong>of</strong> diversity was low in all the zones <strong>of</strong> mining areas compared tounmind area in case <strong>of</strong> trees and shrubs. Herbaceous species had higher value in the minedareas.• Dominance-diameter distribution curves showed that most <strong>of</strong> the trees in the mined areas were<strong>of</strong> medium girth classes. Unmined area had more individuals <strong>of</strong> lower girth class even thoughtrees <strong>of</strong> all girth classes were present in the area.• Basal area found lesser in the unmined area as compared to the mined areas.• Distribution pattern <strong>of</strong> the vegetation found was contagious in the mined area. In the unminedarea also most <strong>of</strong> the species showed contagious pattern <strong>of</strong> distribution.• There was loss <strong>of</strong> 40.5 km 2 (40 percent) <strong>of</strong> forest area in 26 years.• Dense forest lost about 48 percent.• Increase in the open forest areas.• Increase in mining area from 13.76 km 2 to 45.24 km 2 . The rate <strong>of</strong> increase was 1.2 km 2 peryear.• Settlement area increased from 17.63 km 2 to 29.20 km 2 .• Cropped area reduced about 5 km 2 during the period 1975 to 1987.• There were not much temporal changes in the grassland and non-forest areas.• The trend <strong>of</strong> change from dense forest to open forest decreased.• Decrease in dense forest to mining and non-forest areas.• Increasing trend <strong>of</strong> open forest to non-forest, i.e., from 6.5 km 2 during 1975 to 1987 to 5.5 km 2in three years during 1999 to 2001.• Area under low fragmentation decreased with time.• Area under non-forest increased with time.• More than 68 km 2 i.e., more than 16 percent <strong>of</strong> the total study area were under highfragmentation and identified the areas as risk.• There was loss <strong>of</strong> about 9 km 2 high fragmentation area in three year period from 1999 to 2001and was converted into non-forest area.5.3. Summary and RecommendationsExtensive coal mining has led to shrinking <strong>of</strong> land base and creation <strong>of</strong> a landscape dotted with minespoils. The pitfalls <strong>of</strong> such activities are felt in the impairment <strong>of</strong> vegetation in these ecosystems. Thepresent study analyses the plant community characteristics in the mine affected areas and impact <strong>of</strong>coal mining on vegetation during different periods <strong>of</strong> time.It was found that there were more or less same impact in the inner zones <strong>of</strong> the mining impact areasdelineated for the present study. The impact was less in the outer most zone. <strong>Mining</strong> <strong>of</strong> coal has causeddamage to the landscape and the biological communities in enormous ways. The number <strong>of</strong> tree andshrub species drastically decreased in their number due to mining. The unfavourable habitat conditions68

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIAprevailing in the coal-mined areas has reduced the chances <strong>of</strong> regeneration <strong>of</strong> species, thereby,reducing the number <strong>of</strong> species in the mined areas. The number <strong>of</strong> herbaceous species colonizing inthe mined areas were found to be higher than in the unmined areas. Species like Pinus kesiya, Schimawallichii, Persea odoratissima, Eupatorium adenophorum, Lantana camara, Melastoma nepalensis,Rubus ellipticus, Rubus khasiana, Paspalum orbiculare, Plantago erosa, Gnaphalium pensylvanium,Isachne himalaica, Ageratum conyzoides, Borreria articularis dominate in mined areas and thesespecies can grow in the degraded environment. The Shannon-Weaver index <strong>of</strong> diversity for trees andshrubs was lower in the mined areas. On the other hand, the diversity index for herbaceous speciesincreased with mining proximities suggesting that mining operation favoured colonizing <strong>of</strong> certainspecies in newly created habitats.The mining <strong>of</strong> coal initiated in Jaintia Hills district <strong>of</strong> Meghalaya in early 1970s. Since then the mininghas been increasing and the area affected by coal mining is increasing day by day. A considerableportion <strong>of</strong> the forest area was converted into non-forest. The dense forest areas converted into the openforests and there was gradual decrease <strong>of</strong> these two forest types during the course <strong>of</strong> time. The areaunder low risk i.e., low fragmentation area, decreased significantly with time. The area under nonforestincreased with time. About 68 km 2 <strong>of</strong> the study area (16 percent) were identified as the areas atrisk. These high fragmentation areas are located in the proximity to mining.The present study revealed that coal mining has adversely affected the vegetation in the coal miningareas <strong>of</strong> Jaintia Hills district. Such habitats do not permit proper plant growth and development.The present study led to the conclusions that phytosociological analysis can be used as important toolsfor predicting the suitability <strong>of</strong> mine spoil habitats for the plant growth. The information gathered onvarious aspects <strong>of</strong> vegetation and colonization <strong>of</strong> plants in mined areas would be helpful inrevegetating the mined areas. The change analysis can be useful in finding out the change <strong>of</strong> trend <strong>of</strong>different land use/ land covers. To understand the land use dynamics related to vegetation and miningthis method can be applied. It helps to delineate the vegetation areas under risk due to miningactivities.It is evident from the above discussion that the mining activities in Jaintia Hills district is detrimentalto the vegetation and general environment <strong>of</strong> the district. It is advisable that such activities have to bestrictly regulated to avoid further damage and scientific mining has to be taken up in a proper mannerto minimize the damage to the vegetation as well as the environment. Appropriate rehabilitationmeasures using the plants that grow in the mine areas need to be taken up in the mine-affected areas.The findings <strong>of</strong> the study could be quite useful while formulating the Management Plan for the district.69

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIAReferencesAnon. 1964. Mineral development in Assam (Symposium volume), Directorate <strong>of</strong> Geologyand <strong>Mining</strong>. Government <strong>of</strong> Assam.Anon, 1974. Geology and mineral resources in the states <strong>of</strong> India. Geological Survey <strong>of</strong> India.Miscellaneous Publication. No.30. pp. 124.Ashton, P.S. 1972. The quarternery geomorphological history <strong>of</strong> Western Malaysis andlowland forest phytogeography. Trans. Second Aberdeen Hull Symp. MalaysianEcology. pp. 35-42.Austin, M.P.; Ashton, P.S. Smith, P.G. (1972). The application quantitative methods tovegetation survey III. A re-examination <strong>of</strong> rain forest data from Brunei. Journal <strong>of</strong>Ecology. 60: 305-324.Baig, M.N. 1992. Natural revegetation <strong>of</strong> coal mine spoils in the rocky mountains <strong>of</strong> Albertaand significant for species selection in land restoration. Mountain Research andDevelopment. 12 (3): 285-300.Banerjee, S.P. 1981. Environmental problem due to mining in Jharia coal field. In: Bandu, D.(ed.), Environmental Management. India Environment Society. New Delhi.Bell, F.G.; Bullock, S.E.T.; Halbich, T.F.J. and Lindsey, P. 2001. Environmental impacts associatedwith an abandoned mine in the Witbank <strong>Coal</strong>field, South Africa. International Journal <strong>of</strong> <strong>Coal</strong>Geology, 45, 195-216.Bell, T.J. and Ungar, I.A. 1981. Factor affecting the establishment <strong>of</strong> natural vegetation on a coal stripmine spoil bank in south eastern Ohio. American Midland Naturalist. 10519-31.Boone, R.B. and Galvin, K.A. 2000. Generalizing El Nino effects upon Maasai livestock usinghierarchical clusters <strong>of</strong> vegetation patterns. Photogrammetric Engineering & Remote Sensing.66(6): 737-744.Bradshaw, A.D. and Chadwick, M.J. 1980. The Restoration <strong>of</strong> Land. Blackwell Scientific Publication.Oxford. England.Bradshaw, A.D.; Dancer, W.S.; Handley, J.F. and Sheldon, J.C. 1975. Biology <strong>of</strong> landrevegetation and reclamation <strong>of</strong> china-clay wastes. In: Chadwick, M.J. and Goodman,G.T. (eds.), The ecology <strong>of</strong> Resource degradation and renewal. Blackwell ScientificPublication. Oxford, England. pp. 363-384.Bradshaw, A.D.; Goode, A.D and Thorpe, E.H.P. 1986. Ecology and design in landscape. 24 thSymposium <strong>of</strong> the British Ecological Society. Blackwell Scientific Publications.Oxford. England.Brenner, F.F.; Brenner, E.K.; Brenner, P.E. and Steiner, R.P. 1994. Evaluation <strong>of</strong> proceduresto estimate biomass on surface coal mine lands reclaimed under the surface-miningcontrol and reclamation act <strong>of</strong> 1970. Environmental Management. 18, 307-315.Brown, C.J. and Dey, A.K. 1975. The mineral and nuclear fuels <strong>of</strong> the India subcontinent andBurma. Oxford University Press. Delhi. pp. 1-170Bulletin <strong>of</strong> Geological Survey <strong>of</strong> India. 1969.Chadwick, K.J. 1973. Methods <strong>of</strong> assessment <strong>of</strong> acid colliery spoils as a medium for plantgrowth. In: Hutnik, R.J. and Davis, G. (eds.), Ecology and reclamation <strong>of</strong> devastatedland. Vol. I. Gordon and Breach. New York. pp. 81-91.Chadwick, M. J.; Highton, N. H. and Lindman, N. 1987. Environmental <strong>Impact</strong> <strong>of</strong> <strong>Coal</strong> <strong>Mining</strong> andUtilization. Pergamon Press. Oxford.Chaudhury, A. B. 1992. Mine Environment and Management (An Indian Scenerio). Ashish PublishingHouse. New Delhi.70

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIAChen, D. and Brutsaert, W. 1998. Satellite sensed distribution and spatial patterns <strong>of</strong>vegetation parameters over a tall grass prairie. Journal <strong>of</strong> the Atmospheric Sciences.55(7): 1225-1238.Clarke, R.K. and Clarke, S.C. 1981. Floristic diversity in relation to soil characteristics in alead mining complex in the Pennines, England. New Phytol. 87, 799-815.CIL. 1997. Report <strong>of</strong> the Department <strong>of</strong> <strong>Coal</strong>. <strong>Coal</strong> India Limited .Cornwell, S.M. 1971. Anthracite mining spoils in Pennsylvania. I. Spoil classification andplant cover studies. Journal <strong>of</strong> Applied Ecology. 8:401-409.Costigan, P.A; Brdshaw, A.D. and Gemmel, R.P. 1981. The reclamation <strong>of</strong> acidic collieryspoils. I. Acid production potential. Journal <strong>of</strong> Applied Ecology. 18: 865-878.Dadhwal, K.S. 1999. Rehabilitation <strong>of</strong> limestone mine spoils with reference to agr<strong>of</strong>orestry.Indian Journal <strong>of</strong> Agr<strong>of</strong>orestry. 1, 141-148.Dancer, W.S.; Handley, J.F. and Bradshaw, A.D. 1977. Nitrogen accumulation in kaolinmining wastes in Cornwall. II. Forage Legumes. Plant and Soil. 48, 303-314.Das Gupta, S. 1999. Studies on vegetal and microbiological processes in coal mining affectedareas. Ph.D. Thesis. North_Eastern Hill University, Shillong. India.Das Gupta, S.; Tiwari, B.K. and Tripathi, R.S. 2002. <strong>Coal</strong> mining in Jaintia Hills, Meghalaya:An Ecological perspective. In: Passah, P.M. and Sarma, A.K. (eds.), Jaintia Hiils, AMeghalaya Tribe: Its Environment, Land and People. Reliance Publishing House.New Delhi. pp. 121-128.Directorate <strong>of</strong> Mineral Resource. 1992. Cottage coal mining in the state <strong>of</strong> Meghalaya and itsimpact on the environment. In Gupta, A and Dhar, D.C. (eds.), EnvironmentConservation and Wasteland Development in Meghalaya. Meghalaya Science Society.Shillong. India.Directorate <strong>of</strong> Mineral Resources. 1985. Technical report <strong>of</strong> the Directorate <strong>of</strong> MineralResources. Government <strong>of</strong> Meghalaya. Shillong. Meghalaya.Dkhar, A. 2002. <strong>Impact</strong> <strong>of</strong> coal mining on micro-landforms in Jaintia Hills district, Meghalya.M. Phil. Dissertation. North_Eastern Hill University, Shillong. IndiaDoerr, A and Guernsely, L. 1956. Man as a geomorphological agent: an example <strong>of</strong> coalmining. Ann. Assoc. Amer. Geog. Vol. 46. pp. 197-210.Down, C.G. 1974. The relationship between colliery waste particle sizes and plant growth.Environmental Conservation. 1:29-40.Freitas, H.; Prasad, M.N.V. and Prtas, J. 2004. Plant community tolerant to trace elementsgrowing on the degraded soils <strong>of</strong> Sao Domingos mine in the south east <strong>of</strong> Portugal:environmental implications. Environment International. 30, 65-72.Fyles, F.W.; Fyles, I.H. and Bell, M.A.M. 1985. Vegetation and soil development on coalmine spoil at high elevation in the Canadian Rockies. Journal <strong>of</strong> Applied Ecology. 22:239-248.Game, M.J.; Carrel, E. and Hotrabhavandra, T. 1982. Patch dynamics <strong>of</strong> plant succession onabandoned surface coal mines: A case history approach. Journal <strong>of</strong> Applied Ecology.Garg, J. K.; Narayan, A. and Basu, A. 1988. Monitoring environmental changes overKudremukh iron ore mining areea, India using remote sensing technique. Proceedings<strong>of</strong> the Indo-British workshop on remote Sensing <strong>of</strong> Environment in <strong>Mining</strong> field. ISM.Dhanbad. pp. 41-47.Geological Survey <strong>of</strong> India. 1974. Miscellaneous publication <strong>of</strong> Geological Survey <strong>of</strong> India.Vol. 3. Government <strong>of</strong> India. pp. 69-91.Ghosh, R., 1989, <strong>Mining</strong> in Jharia coal field, Eastern India: An estimation <strong>of</strong> its impact index.Journal Geological Society <strong>of</strong> India. 33, 353-360.71

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIAGoodman, G.T. and Gemmel, R.P. 1978. The maintenance <strong>of</strong> grassland on smelter wastes inthe lower Swansea Valley. II. Copper smelter waste. Journal <strong>of</strong> Applied Ecology. 15,875-883Goretti, K. K. M. 1998. The environmental impacts <strong>of</strong> underground coal mining and landcover changes analysis using multi-temporal remotely sensed data and GIS.Unpublished M. Sc. Thesis. International Institute Aerospace Surveys and EarthSciences (ITC). Enschede. The Netherlands.Graham, D.F.; St-Arnand, E.L. and Rencz, A.N. 1994. Canada Geologic survey monitorsMine Tailings, Disposal sites with landsat. EOS Magazine, pp 38-41.Grant, C.D. 2003. Post-burn vegetation development <strong>of</strong> rehabilitated bauxite mines in westernAustralia. Forest Ecology and Management, 186,147-157.Guha Roy, P.K. 1991. coal mining in Meghalaya and its impact on environment. Exposure. 4,31-33.Hall, I.G. 1957. The ecology <strong>of</strong> disused pit heaps in England. Journal <strong>of</strong> Ecology. 45: 689-720.Iverson, L.R. and Wali, M.K. 1982. Buried, viable seeds and their relation to revegetationafter surface mining. Journal <strong>of</strong> Range Management. 35(5): 648-652.Jha, A.K. and Singh, J.S. 1990. Revegetation <strong>of</strong> mine spoils: Review and case study. In: Dhar,B.B. (ed.), Environmental Management <strong>of</strong> <strong>Mining</strong> Operations. Ashish PublishingHouse. New Delhi. pp. 300-326.Johnson, M.S. and Bradshaw, A.D. 1977. Prevention <strong>of</strong> heavy metal pollution from mine wastes byvegetative stabilization. Transactions <strong>of</strong> the Institute <strong>of</strong> <strong>Mining</strong> and Metallurgy. 86A:47-55.Joshi, P.K.; Singh, S.; Agarwal, S.; Roy, P.S. and Joshi, P.C. 2003. Aerospace Technology forForest Vegetation Characterisation and Mapping in Central India. Asian Journal <strong>of</strong>Geoinformatics 4(4), 1-8.Khoshoo, T.N. 1984. 27 th Holland Memorial Lecture. <strong>Mining</strong>, Geological and MetallurgicalInstitute <strong>of</strong> India. Calcutta.Kimmerer, R.W. 1984. Vegetation development on a dated series <strong>of</strong> abandoned lead and zincmines in southwestern Wisconsin. American Midland Naturalist. 111, 332-341.King, D.G. 1993. Digital frame cameras: the next generation <strong>of</strong> low cost remote sensing. In:proc <strong>of</strong> ASPRS Biennial workshop on photography and videography in the plantsciences, logan, Utah.Koster, R.D. and Slob, S. 1994. An application <strong>of</strong> a Geographic Information System for the purpose <strong>of</strong>mining and rehabilitation planning in the Karvina district, Czech Republic. Memoir <strong>of</strong> theCentre <strong>of</strong> Engineering Geology in the Netherlands. No. 116. Delft University <strong>of</strong> Technology.pp. 7-79.Kushwaha, S.P.S., Roy, P.S., Azeem, A., Boruah, P. and Lahan, P. 2000. Land area changeand habitat suitability analysis in Kaziranga National Park, Assam. Tigerpaper 27 (2),9-17.Kushwaha, S.P.S. 1990. Forest-type mapping and change detection from satellite imagery.ISPRS Journal <strong>of</strong> Photogrammetry and Remote Sensing 45, 175 –181Kushwaha, S.P.S. and Kuntz, S.1993. Detection <strong>of</strong> environmental changes in tropical forests <strong>of</strong> northeasternIndia. Proc.15th International symposium, Remote Sensing and Global EnvironmentalChange, 4-8 April, Graz, Austria, pp. 551-558.Leisman, G.A. 1957. A vegetation and soil chronosequence on the Mesabi iron range spoilbanks, Minnesota. Ecological Monograph. 27, 221-245.Liles, T.M. and Kiefer, R.W. 1999. Remote sensing and image interpretation. John Wiley & Sons.New York.Lyngdoh, T. 1995. Community dynamics and edaphic changes in relation to coal mining inJaintia Hills, Meghalaya. Ph.D. Thesis, North-Eastern Hill University, Shillong, India.72

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIALyngdoh, T.; Tripathi, R.S. and Das, A.K. 1992. Vegetation dynamics on coal mine spoils <strong>of</strong>Jaintia Hills in Meghalaya (north-east India) undergoing natural recovery. ActaOecologia. 13(6): 767-775.Mann, H.S. and Chatterjee, P.C. 1979. <strong>Impact</strong> <strong>of</strong> mining operation on the ecosystem inRajasthan, India. In: Wali, M.K. (ed.), Ecology and <strong>Coal</strong> Resource Development.Pergamon Press, New York. pp. 615-625.Marrs, R.H.; and Bradshaw, A.D. 1980. Ecosystem development on reclaimed china-claywastes. III. Leaching <strong>of</strong> nutrients. Journal <strong>of</strong> Applied Ecology. 17, 727-736.Marrs, R.H.; Robert, R.D. and Bradshaw, A.D. 1980. Ecosystem development on reclaimedchina-clay wastes. I. Assessment <strong>of</strong> vegetation and capture <strong>of</strong> nutrients. Journal <strong>of</strong>Applied Ecology. 17, 709-717.Marrs, R.H.; Robert, R.D.; Skeffington, R.A. and Bradshaw, A.D. 1981. Ecosystemdevelopment on naturally colonized china-clay wastes. II. Nutrient compartmentation.Journal <strong>of</strong> Ecology. 69, 163-169.Mishra, S.K. and Lyngdoh, C. 1993. Socio-economic pr<strong>of</strong>ile. Studies on environmentalimpact <strong>of</strong> coal mining in Jaintia Hills District. Meghalaya State Pollution ControlBoard. Final Technical Report. North_Eastern Hill University. Shillong. pp. 153-178.Misra, R. 1968. Ecology Work Book. Oxford & IBH Publication, New DelhiMolyneux, J.K. 1963. Some ecological aspects <strong>of</strong> colliery waste heaps around Wiga, SouthLancashire. Journal <strong>of</strong> Ecology. 51:315-321.Moore, T.R. and Zimmermann, R.C. 1977. Establishment <strong>of</strong> vegetation on serpentine asbestosmine waste, south eastern Quebec, Canada. Journal <strong>of</strong> Applied Ecology. 14, 589-599.Mukherjee, R. 1987. Surface mining and land degradation in Raniganj coal field, Barddmandistrict. Geog. Rev. <strong>of</strong> Ind. Vol. 49. No. 1. pp. 69.Mukherjee, R. 1988. Problem <strong>of</strong> land degradation associated with underground coal mining inRaniganj coal field, Barddman district. Indian Journal <strong>of</strong> Landscape System andEcological Studies. Vol. 11. No. 1. pp. 54-58.Muller-Dombois, D. and Ellenberg, H. 1974. Aims and methods <strong>of</strong> vegetation ecology. John Wiley &Sons. New York.Newbery, D. M.; Canpbell, E.J.F.; Lee, Y.F.;Ridsdale, C.E. and Still, M.J. 1992. Primarylowland dipterocarpus forest at danum valley, Sabah, Malaysia: Structure,relativeabundance and family composition. Proceedings <strong>of</strong> the transactions <strong>of</strong> Ropyal Society.London. 335:341-356.Paijmans, K. 1970. An analysis <strong>of</strong> four tropical rain forest sites in Guinea. Journal <strong>of</strong> Ecology.58: 77-356.Pandey, H.N. 1993. Studies on environmental impact <strong>of</strong> coal mining in Jaintia Hills District.Meghalaya State Pollution Control Board. Final Technical Report. North_Eastern HillUniversity. Shillong.Pandey, H.N; Tripathi, R.S; Umashankar and Boral, L. 1993. Study site, vegetation and soil.Meghalaya State Pollution Control Board. Final Technical Report. North_Eastern HillUniversity. Shillong. pp. 1-63.Parthasarathi, N. and Karthikeyan. 1997. Biodiversity and population density <strong>of</strong> woodyspecies in a tropical evergreen forest in Courtallum Reserve Forest, Western Ghats,India. Tropical Ecology. 38 (2): 297-306.Paruelo, J and Epstein, H.E. 1997. ANPP estimates from NDVI for the Central GrasslandRegion <strong>of</strong> United States. Ecology. 78(3):953-958.Pathak, R.K. and Dkhar, J.W. 1993. Anthropological and epidemiological pr<strong>of</strong>ile <strong>of</strong> thepeople <strong>of</strong> coal mine area. Studies on environmental impact <strong>of</strong> coal mining in JaintiaHills District. Meghalaya State Pollution Control Board. Final Technical Report.North_Eastern Hill University. Shillong. pp. 179-199.73

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIAPoole, R.W. 1974. An introduction to quantitative ecology. Mc Graw Hill. Kogakusha.Tokyo.Power, J.F. 1978. Reclamation research on strip mined lands in dry regions. In: Schaller, F.W.and Sutton, P. (eds.), Reclamation <strong>of</strong> drastically disturbed lands. American Society <strong>of</strong>Agronomy, Madison, Wisconsin. 521-536.Prakash, A. and Gupta, R.K. 1998. Land-use mapping and change detection in a coal miningarea - a case study in the Jharia coal field, India. International journal <strong>of</strong> remotesensing. vol. 19, no. 3, 391- 410.Prasad, R. 1989. Removal <strong>of</strong> forest cover through mining and technology for retrieval. Proceedings <strong>of</strong>National seminar on depletion <strong>of</strong> soil and forest cover. Journal <strong>of</strong> Tropical Forestry. 5:109-116.Prasad, R. and Pandey, R.K. 1985. Natural plant succession in the rehabilitationbauxite andcoal mine overburden in Madhya Pradesh. Journal <strong>of</strong> Tropical Forest. 1: 79-84.Rai, R. K. 2002. Implication <strong>of</strong> coal mining on environment in Jaintia Hils, Meghalaya. In:Passah, P.M. and Sarma, A.K. (eds.), Jaintia Hiils, A Meghalaya Tribe: ItsEnvironment, Land and People. Reliance Publishing House. New Delhi. pp. 113-119.Rai, R.K. 1996. Environmental degradation due to coal mining in Meghalaya. Final Report <strong>of</strong>the project sponsored by Ministry <strong>of</strong> Environment and Forests. New Delhi.Rao, P.; Barik, S.K; Pandey, H.N. and Tripathi, R.S. 1990. Community composition and treepopulation structure in a sub-tropical broad-leaved forest along a disturbance gradient.Veget. 88:151-162.Rathore, C. S., and Wright, R., 1993, Monitoring environmental impacts <strong>of</strong> surface coalmining. International Journal <strong>of</strong> Remote Sensing. 14, 1021-1042Raven, P. H.; Linda, B. and George, B.J. 1993. Environment. Saunders College Publishing.New York. pp. 183-187.Richardson, J.A. 1975. Physical problems <strong>of</strong> growing plants o colliery wastes. In Chadwick,M.J. and Goodman, G.T. (eds.), Ecology <strong>of</strong> resource degradation and renewal.Blackwell Scientific Publication. Oxford, England. pp. 275-285.Richardson, J.A.; Shelton, B.K. and Dicker, R.J. 1971. Botanical studies <strong>of</strong> natural andplanted vegetation on colliery spoil heaps. Landscape Reclamation. IPC Press.Guildford, Surrey. 1: 84-99.Ricotta, C. and Avena, G. 1999. Mapping and monitoring net primary productivity withAVHRR NDVI time-series: statistical equivalence <strong>of</strong> cumulative vegetation indices.ISPRS Journal <strong>of</strong> Photogrammetry and Remote Sensing.54(5): 325-331.Ries, R.E. and H<strong>of</strong>man, L. 1983. Reestablishment and use <strong>of</strong> grassland on reclaimed soils. In: Canland be made better than before? Bismarck. North Dakota. pp. 85-93.Rodrigues, R.R.; Martins, S.V. and Barros, L.C. 2004. Tropical rain forest regeneration in anarea degraded by mining in Mato Grosso state, Brazil. Forest Ecology andManagement. 190, 323-333.SAC (ISRO). 1990. <strong>Impact</strong> <strong>of</strong> mining activities and superthermal power stations onenvironment, Project Report No. RSAM/SAC/ENVN/PR/08/90.Sarma, K. 2002. <strong>Coal</strong> mining and its impact on environment <strong>of</strong> Nokrek Biosphere Reserve,Meghalaya. Ph.D. Thesis. North-Eastern Hill University, Shillong. India.Saxena, S.K. 1979. Degradation <strong>of</strong> vegetation in the surface mined area <strong>of</strong> western Rajasthan.In: Wali, M.K. (ed.), Ecology and <strong>Coal</strong> Resource Development. Pergamon Press, NewYork. pp. 626-633.Schafer, W.M.; Nielsenand, G.A. and Nettleton, W.D. 1980. Mine spoil genesis andmorphology I a spoil chronosequence in Montana. Soil Science Society <strong>of</strong> AmericanJournal. 44:802-807.74

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIASchejbal, C. 1995. Problems <strong>of</strong> mines closure and reviving <strong>of</strong> landscape in the mining area.Proceedings <strong>of</strong> the International Conference. Beijing. China. pp. 681-691.Sharan, A.; Sharma, S. and Govind, P. 1994. impact <strong>of</strong> coal mining on social ecology – Atentative note. In: Dhar, B.B. and Saxena, N.C. (eds.), Socio-economic <strong>Impact</strong> <strong>of</strong>Environment. Akashi Publishing House. New Delhi. pp. 46-65Sharma, B.K. and Das, G.S. Physico-chemical properties and dynamics <strong>of</strong> planktoncommunities in aquatic systems. Studies on environmental impact <strong>of</strong> coal mining inJaintia Hills District. Meghalaya State Pollution Control Board. Final TechnicalReport. North_Eastern Hill University. Shillong. pp. 64-127.Shetron, S.G. and Duffek, R. 1970. Establishing vegetation on iron mine tailings. Journal <strong>of</strong>Soil and Water Conservation. 25, 227-230.Simpson, E.H. 1949. Measurement <strong>of</strong> diversity. Nature. 163:688.Singh Roy, V.H. 1995. Spectral characterization <strong>of</strong> vegetation at mine tailings. <strong>Mining</strong> andthe environment, sudbaay 95 proceedings, Sudbury, pp 193-200.Singh Roy, V.H. and Kruse, F. 1991. Detection <strong>of</strong> metal stress in the boreal forest speciesusing the 670µm chlorophyll band. EMIM, 8 th thematic conf on Geologic Remotesensing. pp 361-372.Singh, J.S. and Jha, A.K. 1987. Ecological aspects <strong>of</strong> reclamation and revegetation <strong>of</strong> coalmine spoils. In: Dhar, D.D. (ed.), Proceedings <strong>of</strong> National Workshop onEnvironmental Management <strong>of</strong> <strong>Mining</strong> Operations in India- A status paper.Department <strong>of</strong> <strong>Mining</strong> Engineering, B.H.U. Vanarasi. India. pp. 73-86.Soni, P.; Vasitha, H.B. and Kumar, O. 1989. Surface mining – its role on site quality. IndianJournal <strong>of</strong> Forestry. 12(3), 233-235.Swer, S and Sigh, O.P. 2004. Water quality, availability and aquatic life affected by coal mining inecologically sensitive areas <strong>of</strong> Meghalaya. Proceedings <strong>of</strong> the 3 rd National Seminar on InlandWater Resources and Environment. University <strong>of</strong> Kerala. 2 nd - 4 th February 2004.Thiruvananthapuram.Tiwari, B.K. 1996. <strong>Impact</strong> <strong>of</strong> coal mining on ecosystem health in Jaintia Hills, Meghalaya. In:Ramakrishnan, P.S.; Purohit, A.N.; Saxena, K.G.; Rao, K.S. and Maikhuri, R.K.(eds.), Conservation and Management <strong>of</strong> bIological Resources in Himalaya. G.B. PantInstitute <strong>of</strong> Himalayan Environment and Development, Almora. Oxford IBH Co. NewDelhi. pp. 466-475.Tiwari, B.K. and Das Gupta, S. 1993. Microbial studies on soil and water bodies. Studies onenvironmental impact <strong>of</strong> coal mining in Jaintia Hills District. Meghalaya StatePollution Control Board. Final Technical Report. North_Eastern Hill University.Shillong. Meghalaya State Pollution Control Board. Final Technical Report.North_Eastern Hill University. Shillong. pp. 129-152.Uma Shankar; Boral, L.; Pandey, H.N. and Tripathi, R.S. 1993. Degradation <strong>of</strong> land due tocoal mining and natural recovery pattern. Current Science. 65, 680-686UNESCO. 1985. Living in the Environment. UNESCO/UNEP.Valdiya, K.S. 1988. Environmental impacts on mining activities. <strong>Mining</strong> and Environment.J.H.R. Publishers, Nainital. India.Veeranjaneyulu, K. and Dhanaraju, R.M. 1990. Geobotanical studies on Nallkonda complexmine. Tropical Ecology. 33, 59-65.Webb, C.J.; Tracey, J.G.; Williums, W.T. and Lance, G.N. 1967. Studies in the numericalanalysis <strong>of</strong> complex rain forest communities 1. A comparison <strong>of</strong> methods, applicableto site/ species data. Journal <strong>of</strong> Ecology. 55: 171-191.Whitford, P.B. 1948. Distribution <strong>of</strong> woodland plants in relation to succession and clonalgrowth. Ecology. 30: 199-20875

IMPACT OF COAL MINING ON VEGETATION: A CASE STUDY IN JAINTIA HILLS DISTRICT OF MEGHALAYA, INDIAWhittakker, R.H. 1975. Communities and Ecosystems. Mc Milan Publishing Company. NewYork.Wiegleb, G and Felink, B. 2001. Primary succession in post-burning landscape <strong>of</strong> LowerLusatia-chance or necessity. Ecological Engineering. 17, 199-217.William, P.J. 1975. Investigations into the nitrogen cycle in colliery spoils. In: Chadwick,M.J. and Goodman, G.T. (eds.), The ecology <strong>of</strong> Resource degradation and renewal.Blackwell Scientific Publication. Oxford, England. pp. 259-274.76

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