IJCRR

IJCRR - 11(13), July, 2019

Pages: 13-25

Date of Publication: 06-Jul-2019

Species Diversity and Vegetation Structure of Coal Mine Generated Wasteland of Raniganj Coal Field, West Bengal, India

Author: Saikat Mondal, Debnath Palit, Pinaki Chattopadhyay

Category: Life Sciences

Abstract:Aim: The main aim of the study was to study the vegetation structure and species diversity of coal mine generated waste land, located in Raniganj coal field area, West Bengal.
Methodology: The survey of vegetation was conducted at both study sites by using standard quadrat method. Study of different phytosociological attribute and species diversity analysis was done using standard methods. Statistical analysis was performed to represent the importance of different phytosociological attributes.
Result: Distribution pattern in both wasteland indicate contagious or clumped type. Butea monosperma and Streblus asper was the most dominant tree species in the two study area respectively whereas, Cynodon dactylon was the most dominant herb species in the study areas. The diversity of herbs was much higher than the others layer of vegetation in both waste lands. Concentration of dominance or Simpson Dominance Index also exhibits variation among the vegetation layers. The Jaccard's Index of similarity for tree, herb shrub and climber vegetation was 57.14%, 71.11%, 50% and 33.33% respectively between the two waste lands. Hierarchical cluster analysis highlights 13 and 7 primary cluster in the two study area respectively based on their phytosociological attributes. Principle component analysis reveals 97.57% and 92% variance for the first two principle components in the study areas respectively.
Conclusion: The present investigation can be concluded that the data of vegetation analysis might be utilized as baseline information and tool to predict the best and effective reclamation procedure of these coal mined areas.

Keywords: Coal mining, Reclamation, Wasteland, Vegetation

Full Text:

INTRODUCTION

The resources from our mother earth are rapidly utilized for improvisation and maintaining the quality of the life in different way. Mining operation for extraction of coal is one of the most familiar and oldest activity but it tend to bring a notable impact on the environment by damaging landscapes and local floral population (Bell et al., 2001; Sarma, 2005). Moreover extensive mining activity can lead to massive destruction of natural ecosystem along with the biodiversity of the area (Ezeaku and Davidson, 2008). In this scenario, full recovery of these ecosystems with their biodiversity may take several years (Cooke, 1999). Therefore, needful attempts have to take to minimize the negative impacts as well as restoration of the degraded environments and these might highlights a significant contribution of the mining sector towards proper development of the impacted area in a sustainable way (Hoadley et al., 2002). The open coal excavations generate wide areas of degraded land or we can say it as wasteland, had gained primary succession conditions but the colonization process is very low, probably due to unfavorable conditions or minimum pioneer plants which suits the environment (Jochimsen et al., 1995). The Damalia and Nimcha-Harabhanga area (Raniganj block of Barddhaman Paschim District, West Bengal) is well known for open cast coal mining. Large-scale open cast mining of these area produced vast barren and unproductive lands and extensive damage to the vegetation. Hence, to counter ecological hazards and restoration of ecological balance, proper reclamation and basic knowledge about it is the priority for these mine area. Better and effective restoration and reclamation process requires detailed concept about the native vegetation and processes of their natural recovery. This study was conducted in coal mine generated waste land of Damalia and Nimcha-Harabhanga area with an aim of gaining knowledge and provide data of natural and compatible vegetation and to formulate any difference in the vegetation composition of these two mine areas of Raniganj Coal Field, West Bengal, India

Materials and Methods:

Study area

Damalia and Nimcha-Harabhanga coal mine generated waste land were selected as the study sites under Satgram mining area and are situated at Raniganj block and Asansol subdivision of West Bengal, India. Damalia waste land is located in between 23?36´31.9´´N and 87?4´6.1´´E at 80.2m elevation and Nimcha-Harabanga waste land is located between 23?36'32.9''N and 87?4'2.4''E at 83.8m elevation (Figure 1).

Vegetation Analysis

The survey of vegetation was conducted at both study sites by using standard quadrat method (Srivastava 2001) during peak growth season.  Sums of 5 sites in each wasteland were selected for sampling. In each sites, 10 quadrats (10m X 10m for trees), within these 100 m² quadrats, 5 m X  5 m quadrats for shrubs and climbers, and 1m x 1 m quadrats for herbs) were laid to quantify various layers of vegetation. Quantitative community characteristics such as frequency, density, abundance and importance value index (IVI) of each plant species were determined, following Misra (1968) and A/F value (Whiteford, 1949). The resultant frequency values were classified into frequency classes following Raunkiaer, 1934 frequency class analysis, such as: class A (1%–20%), class B (21%–40%), class C (41%–60%), class D (61%–80%) and class E (81%-100%) (Hewit and Kellman, 2002).

Diversity indices analysis

Species diversity (Shannon and Weiner, 1963), Concentration of dominance (Simpson, 1949), Species richness (Margalef, 1978) and Evenness index (Pielou, 1966) were calculated for undisturbed and disturbed sites. The distribution pattern of the species was studied by using Whiteford’s index (Whiteford, 1949). Similarity index of different layer of wasteland vegetation between two study areas was determined following Jaccard’s index of similarity (Krebs, 1999).                                         

Statistical analysis

Hierarchial cluster analysis was performed to interpret the similarity level of the tree species based on their phytosociological parameters for both the waste land and principle component analysis through statistical computer software.

Results

The density, frequency, frequency class, abundance, importance value index (IVI), Whiteford’s index of vegetation at two study area are shown in Table 1 and 2 respectively. The A/F ratio showed Contagious or clumped distribution pattern in both wasteland which stipulates fragmented and patchy type of natural vegetation because of mining. Similar types of distribution pattern were also observed by Sarma (2005) in the coal mining areas of Nokrek biosphere reserve of Meghalaya. At Damalia wasteland area, the most dominating tree species was Butea monosperma with the highest IVI value, whereas, Streblus asper was the most dominant one in Nimcha-Harabhanga (Table 1 and 2). Cynodon dactylon was the most dominant herb species in both Damalia and Nimcha-Harabhanga wasteland in terms of IVI value (Table 1 and 2). Tephrosia purpuria and Jatropha gossipyfolia was the dominant shrub species in Damalia and Nimcha-harabhanga waste land respectively (Table.1 and 2) Higher importance value indicated its ability to grow in the degraded environment. Species, family compositions of Damalia and Nimcha-Harabhanga waste land are represented in table 3. The study highlights that asteraceae and fabaceae (7 species each) are the most dominant family in Damalia waste land and asteraceae in case of Nimcha-Harabhanga waste land. Present study reflected density of tree in Damalia was higher than in Nimcha- Harabhanga but the density of herbs was lower in Damalia.

Diversity indices analysis

Species diversity indices (Shannon-Weaver) reveal variation among the tree, herb, shrubs and climber species (Table 4). Herbs species shows higher diversity than the other types of vegetation in both study area. Concentration of dominance or Simpson Dominance Index also exhibits variation among the vegetation layers. The Evenness Index (Pielous Index) and Margalef Index for species richness also highlights variation among different vegetation layers in both waste lands (Table 4). The Jaccard’s Index of similarity for tree, herb shrub and climber vegetation was 57.14%, 71.11%, 50% and 33.33% respectively between the two waste lands (Table 4) The present study of the two wasteland flora according to Raunkiaer’s life form (Raunkiaer 1934) reveals that the dominance of Phanerophyte in Damalia wasteland and therophytes in Nimcha-Harabhanga wasteland.(Table 5 & Fig.2).

Statistical analysis

Hierarchial cluster analysis based on different phytosociological attributes was done for the tree and herb layer of both waste lands (Figure 3 and 4). In Damalia waste land 13 primary clusters and in Nimcha-Harabhanga 7 primary cluster are formed. The more the distance scale of the clusters the more the plant species are remotely related to each other. In Damalia, the 1^st cluster shows close similarity among the Heliotropium indicum, Amaranthus spinosus, Acacia auriculiformis, Alstonia scholaris, Crotalaria juncea, Aerva lanata, Blumea lacera, Oldenlandia corymbosa plant species. Cluster 2 comprises of Hyptis suaveolens, Anisomeles indica, Melochia corchorifolia, Oxalis corniculata, Mimosa pudica Desmodium gangeticum. Cluster 3 comprises of Ailanthus excelsa, Albizzia lebbek, Azadirachta indica, Ziziphus jujube, Dalbergia sissoo, Phoenix dactylifera. Cluster 4,7,8,9,10,11,12 and 13 comprises only 2 plant species in each. Cluster 5 composed of Boerhaavia repens, Achyranthus aspera, Alternanthera sessilis, Cleome viscose and cluster 6 composed of Parthenium histerophorus, Evolvulus nummularis, Gomphrena serrata, Euphorbia hirta, Eclipta alba, Oplismenus composites. In Nimcha-Harabhanga waste land cluster 1 comprises Heliotropium indicum, Amaranthus spinosus, Sida acuta, Eucalyptus globules, Senna siamea, Borassus flabellifer, Dalbergia sissoo, Phoenix dactylifera, Azadirachta indica, Crotalaria juncea, Oxalis corniculata, Mimosa pudica, Solanum virginianum, Desmodium gangeticum, Cyperus rotundus, Ailanthus excels, Alstonia scholaris, Acacia nilotica,  Hyptissu aveolens, Anisomeles indica, Melochia corchorifolia, Senna obtusifolia, Albizzia lebbek. Cluster 2 composed of Acacia nilotica and Alangium salviifolium, cluster 3 contains Triumfetta rhomboidea, Achyranthus aspera, Desmodium triflorum, Parthenium histerophorus, Evolvulus nummularis, Euphorbia hirta, Eclipta alba, Oplismenus composites, Gomphrena serrata, Alternanthera sessilis, Aerva lanata, Boerhaavia repens and Cleome viscose. Cluster 4 comprised of Sida cordata and  Blumea lacera. Cluster 5 includes Coldenia procumbens, Centella asiatica, Gmelina arborea, Lagerstroemia speciosa, Ficus religiosa and Ficus benghalensis. Cluster 6 composed of Eragrostis cilianensis, Dactyloctenium aegyptium and Eupatorium odoratum. Cluster 7 composed of Streblus asper and Ziziphus jujube.

Principle component analysis was done for the tree layer of different phytosociological attributes for two coal mines generated waste lands. For the tree layer of Damalia waste land (Table 6 and Figure 5), the first two principle components account for 97.57% of the total variance in the data set.  Therefore, 65 and 31% of variance were calculated for the first two principle components respectively. From this it can be concluded that the first principle component is probably the most important to represent the variation within the phytosociological attributes in the tree layer of Damalia. In Damalia, Streblus asper (12) and Butea monosperma (8) have similarity regarding their phytosociological attributes and exhibit high correlation with the first axis but Borassus flabellifer (7) and Moringa oleifera (10) shows negative correlation with first axis for the same phytosociological attributes. In Nimcha-Harabhanga waste land (Table 7 and Figure 6), the total variance were 92% for the first two principle components. Therefore, 65 and 26% of variance were calculated for the first and second principle components and first principle is important for representing the variation within the phytosociological attributes of the tree layer like Damalia. Maximum tree species of Nimcha-Harabhanga were located on or near of axis 1 and 2. Hence, indicates strong positive correlation of the concerned species along with the phytosociological attributes represented by the axis respectively. Due to higher distance from both the axis, Butea monosperma (9) has a weak relation with the phytosociological attributes of the respective axis.

CONCLUSION

The principle objective of this research was to analyze the natural occurrence of different plant species native to different habitats across two different coal mine generated waste land of Raniganj Coalfield, West Bengal aiming to enhance diversity and functioning of huge area of coal mine generated waste land. The potentiality of vegetation of an area is based on various environmental constrain and regional variables (Nath 2004). The present study shows that phytosociological analysis can be utilized as important tools to predict the nature of mine soil for the growth of vegetation as well as eco-restoration. The waste land areas of coal field are invaded by some stress tolerant floras which are able to initiate ecological succession and gathering data and information of such kind of stress tolerant plant species have enormous practical application in terms of eco-restoration. The study of natural vegetation in details of coal mine affected area can be implicit to formulate and conduct revegetation programme in any coal mine generated waste lands. Furthermore, this type of data can be utilized to maintain genetic diversity and equally to confirm the use of ecosystem in a sustainable way (Jha and Singh, 1990; Bannerjee et al., 1996).

ACKNOWLEDGEMENT

Authors express their deep sense of gratitude to Department of Botany, Durgapur Govt. college, West Bengal and Department of Zoology, Raghunathpur College, West Bengal, India for their support to conduct the study. Authors also acknowledge the immense help received from the scholars whose articles are cited and included in references of this manuscript. The authors are also grateful to authors / editors / publishers of all those articles, journals and books from where the literature for this article has been reviewed and discussed.

CONFLICT OF INTEREST

As an author we do not have any conflict of interest in the present communication

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