ECO-CHRONICLE 59

ECO CHRONICLE ISSN: 0973-4155 Vol. 12, No. 3, September, 2017 PP: 59 - 65

SPATIO-TEMPORAL VARIABILITY IN SOIL CHARACTERISTICS AND ITS INFLUENCE ON THE RETENTION OF CHLORPYRIPHOS AND QUINALPHOS IN CARDAMOM GROWING SOILS OF ,

Bindumol, G. P. and Harilal, C. C. Division of Environmental Science, Department of Botany, University of Calicut, Kerala. Corresponding author: [email protected]

ABSTRACT

A study was conducted for a period of one year to evaluate the zonal and seasonal variations in the physico-chemical characteristics of soil and their influence on the retention of pesticides like chlorpyriphos and quinalphos. Fifty four soil samples were collected from large and medium sized cardamom plantations falling in three zones of Cardamom Hill Reserve during pre-monsoon, monsoon and post-monsoon seasons and analysed for various physico-chemical properties and residues of chlorpyriphos (O, O-diethyl O-3, 5, 6- trichloro-2-pyridyl phosphorothioate) and quinalphos (O, O-diethyl O-quinoxalin-2-yl phosphorothioate) following standard methods. The extent of pesticide residues in the study area were then correlated with soil characteristics and meteorological data.

Cardamom growing soils from the study area are of sandy clay loam type with acidic nature. Spatio-temporal variation was observed in the residues of chlorpyriphos and quinalphos. Seasonal variability was noticed in the concentration of pesticide residues and total phosphorus content, whereas it was not much reflected in organic matter content and cation exchange capacity of soil samples. Pesticide residues in soil were positively correlated with clay content in all seasons except monsoon. Soil organic matter has not found to have any influence on the retention of pesticide residues in soil. Low soil pH, high clay content and rainfall pattern has great influence in the persistence and leaching of pesticide residues in soils of the Cardamom Hill Reserve.

Keywords: Chlorpyriphos, Quinalphos, total phosphorus, persistence.

INTRODUCTION

Kerala, the land of spices, surrounded by Major pesticide consuming crops in India are rice and in the east and Sea in the west (between 80 cotton. Cardamom is not an exemption. Various chemicals to 120 N and 740 to 770 E) enjoys humid tropical climate. are frequently applied in cardamom plantations either as The major land forms are highland, midland and lowland, foliar spray or through soil drenching (George et al. 2013). each with its own geomorphic features. Idukki district of Among such chemicals, Chlorpyriphos is the widely used Kerala is famous for its scenic beauty and largest area organophosphorus insecticides in cardamom plantations. under forest cover. It is situated completely under Western Chlorpyriphos is used both by soil drenching and foliar Ghat region. The annual average rainfall is 3555.6 mm spray for the control of root grub and root borers. and temperature is 21.330C (Premachandran, 2007). The Quinalphos is yet another pesticide widely used for the district is popularly known as the spice district of Kerala, management of cardamom trips and other pests. owing to the cultivation of high yielding varieties of spices such as cardamom, pepper, turmeric, ginger etc. together On the basis of soil productivity and other factors governing with other plantation crops. All these crops demand the yield, cardamom hill reserve of the state of Kerala is divided usage of considerable quantity of chemicals for crop into three zones; zone A, B, and C. Zone A having highest protection and production. productivity, which includes Peerumedu Taluk excluding Peruvanthanam and Kokkayar villages and Chakkupallam, Synthetic pesticides have become one of the important Ayyappankovil and Vandenmedu villages of parts of integrated pest management for last few decades. taluk. Zone B has comparatively lower A wide range of chemicals are being used in this category. productivity and includes Chathurangappara, , 60 ECO-CHRONICLE

Santhanpara, Pampadumpara, Parathode and intervals during 2014-15 (figure.1). Soil samples were Udumbanchola villages of Udumbanchola taluk. The rest collected from root zone area of cardamom plants, of cardamom growing area comes under zone C (MSSRF, according to the cardamom package of practices of Spices 2008). Board, Cochin. Each soil sample has been collected from a 5acre plot, leaving 30 cm from plant base. Selected sites Pesticides, in addition to their activity on target organisms, for sampling were cleaned from weeds, dry leaves and will have multi-dimensional impacts on non-target other mulch materials. Soil was taken using a spade, after organisms. They may even persist in associated domains cutting and removing a V shaped hole at a depth of 15 cm like soil, water and air for a longer period of time. with the help of a spatula. Soil was scraped from both the Cardamom growing regions of Kerala have an undulating sides of V shaped pit in a thin layer of 2 cm along the terrain. Moreover they also form catchment basins of cutting of the full length (Jackson, 1973). From each 5 important rivers. Surveillance on the persistence and acre plot, 10 sub samples were collected diagonally and reactivity of applied chemicals is a major concern in most samples were gathered in a polythene sheet. It was then agro ecosystems. Hence a study has been undertaken to mixed well, removed all plant materials and spread in a assess the spatio-temporal variation in the physico- square shape in thin layer and sectioned to four quarters chemical characteristics of soils and to assess their impact by drawing diagonal lines. The two quarters falling on the retention of major pesticides such as chlorpyriphos opposite were discarded. The process was continued till and quinalphos in cardamom growing ecosystems. the sample become 500 g. From each sample, 10g was taken for the determination of moisture content. The soil MATERIALS AND METHODS sample thus collected from the field was dried under shade Soil samples were collected from cardamom plantations and sieved using 2mm sieve. The material on the sieve in zone A, B, and C, for a period of one year at bimonthly was again ground and sieved till all the aggregate particles were fine enough to pass through and only stones and organic matter remain on the sieve. The whole samples Figure 1. Cardamom cultivating areas in Idukki district were kept in plastic containers. Accordingly, three soil samples were collected from each zone at bimonthly interval for a period of one year. Altogether 54 soil samples Zone were collected. The samples were then analysed for soil C physical constants and texture (Clarson, 2002), chemical properties such as pH, electrical conductivity, organic matter content, cation exchange capacity and total phosphorus content (Jackson, 1973) and residues of chlorpyriphos and quinalphos following extraction (Kumari et al., 2008). The extracted pesticides were estimated Zone B using GC –FPD.

Pesticide concentrations were measured using Shimadzu GLC 2014 equipped with Flame Photometric detector and Zone a RESTEK 30 m x 0.25 mm RTX -5 fused silica capillary A column with 0.25 µm film of phenyldimethylpolysiloxane. The injector was kept at 290 0C throughout the analysis within a split ratio of 1:10. The column head pressure of

Table 1. Seasonal variation in soil physical properties of cardamom cultivating zones in Idukki.

Zone pH Moisture content (%) Electrical conductivity (dS/cm) PRM M POM PRM M POM PRM M POM A 4.85 5.37 4.80 19.04 20.72 15.15 0.276 0.238 0.221 ±0.16 ±0.23 ±0.0 ±3.2 ±1.0 ±3.5 ±0.01 ±0.06 ±0.01 B 4.94 5.15 5.22 18.78 17.95 14.62 0.217 0.166 0.205 ±0.37 ±0.12 ±0.09 ±2.4 ±1.2 ±0.0 ±0.01 ±0.04 ±0.0 C 5.01 5.62 5.46 22.76 20.74 18.43 0.195 0.145 0.157 ±0.18 ±0.12 ±0.41 ±0.5 ±0.1 ±0.1 ±0.02 ±0.03 ±0.04 PRM - Pre Monsoon; M - Monsoon; POM - Post Monsoon ECO-CHRONICLE 61 carrier gas (nitrogen) was maintained at 169.7 kPa. The to May at an interval of 10 to 15 days until the onset of oven temperature was initially maintained at 200 0C for 1 monsoon. Since flowering season commences from min and then increased and held at 290 0C for 15 min. February onwards, irrigation is essential for flower setting Pesticide residues (µg g-1) in soil samples were calculated and yield setting. Hence most of the cardamom plantations as per George et al. (2013). are under irrigation. The soil moisture remains constant throughout the year due to constant irrigation practices. RESULTS AND DISCUSSION Organic matter content is a measure of soil health. Since The results of pH, moisture content and electrical cardamom plants grow under canopy, organic matter conductivity of soil samples are presented in Table 1. content in these plantations will be comparatively higher Seasonal changes in soil organic matter and cation than any other crop. The optimum soil organic carbon exchange capacity are given in Table 2 and those of bulk content for cardamom cultivation is 1.5 to 2.0 %, which density, particle density and water holding capacity in Table corresponds to 2.6 to 3.5 % of soil organic matter. The 3. Spatial variation in soil texture is depicted in Table 4. analytical data shows that all soil samples from the study site have high organic matter content. pH value of soils collected from the study area ranged from very acidic to near normal range (4.80 to 5.62). Soil Decomposition of organic matter is an integral part of any samples collected during pre-monsoon season showed natural process. Microbial decomposition of litter low pH compared to monsoon and post monsoon seasons. contributes a major portion of organic matter. Slow rate of Samples from zone A was more acidic and average pH decomposition of organic matter in high acidic soils and was only 5.01, where as that of zone B and zone C were at higher elevation are reported by Firsova (1967). Despite 5.29 and 5.36, respectively. these facts, the present study areas reported higher extent of soil organic matter. Usually in these agro ecosystems, The moisture content of soil samples varied over the period planters apply 1 kg neem cake and 10 kg farm yard manure of study. The average moisture content was almost similar per plant for enhancing soil physical qualities. The in all zones and was about 20% in pre monsoon and repeated application of farm yard manure is likely to monsoon seasons. Lowest moisture content in soil was improve soil humus, which might have reflected in high noted in zone B. Cardamom plants are very sensitive to organic matter content associated with the cardamom moisture and air temperature. In order to regulate soil ecosystems. moisture and temperature, irrigation starts from January Cation Exchange Capacity (CEC) of all soil samples from Table 2. Seasonal changes in soil chemical properties the present study area was relatively high. Soil organic in cardamom growing zones matter has charge properties and that make it a site for Zone Organic matter (%) Cation exchange ion exchange. Generally 1 % Soil organic matter capacity (meq/100g contributes to 2 meq. The mean value of CEC in the soil) present study ranged from 16.68 to 19.35 meq /100g soil. PRM M POM PRM M POM The CEC of zone A samples declined during monsoon. 3.96 4.17 4.39 17.84 16.68 18.18 A This phenomenon was not observed in zone B & C. Zone ±0.26 ±0.50 ±0.50 ±0.42 ±5.42 ±0.93 4.27 4.33 4.85 16.67 18.84 17.06 C has recorded high CEC during pre-monsoon and B ±0.11 ±0.80 ±0.33 ±1.69 ±6.19 ±1.92 monsoon. CEC of soils vary with pH, organic matter 5.11 4.40 4.61 18.54 19.35 18.05 C content and clay content of soils. The higher CEC ±0.65 ±1.02 ±0.71 ±0.70 ±0.43 ±0.17 associated with soil samples from the present study area PRM - Pre Monsoon; M - Monsoon; POM - Post Monsoon can be attributed to higher organic matter. It is being

Table 3. Changes in physical attributes of soil collected from cardamom growing zones in Idukki Zone Bulk density (g/cc) Particle density (g/cc) Water holding capacity (%) PRM M POM PRM M POM PRM M POM A 0.99 0.95 1.0 2.20 2.60 2.43 65.3 72.18 63.56 ±0.1 ±0.1 ±0.6 ±0.6 ±0.3 ±0.1 ±10.6 ±3.5 ±0.7 B 1.22 1.04 1.08 1.94 2.57 2.43 56.51 63.18 62.77 ±0.2 ±0.1 ±0.1 ±0.8 ±0.2 ±0.1 ±3.3 ±2.9 ±2.9 C 0.06 1.06 1.13 1.13 1.63 1.67 60.84 63.91 55.36 ±0.1 ±0.1 ±0.1 ±0.1 ±0.7 ±0.2 ±11.2 ±0.6 ±0.1 PRM - Pre Monsoon; M - Monsoon; POM - Post Monsoon 62 ECO-CHRONICLE reported that the open pores in kaolinite type of clay Air and water have dynamic relationship in occupying pore minerals can exchange calcium and magnesium ions with space of soil. Water present in saturated soil drain rapidly other ions (Lal and Shukla, 2004). Continuous rain could and can quickly bring back to saturation during heavy have accelerated leaching of calcium and magnesium ions rainfall. The presence of more organic matter in soil during with other ions. This might have resulted in low CEC of monsoon also would have contributed to the increase in soil samples from certain zones under study during water holding capacity. Significant positive relationship monsoon season. was observed between water and organic carbon, clay and porosity, and negative relationship was found with Bulk density of samples from zone A was lower than zone pH, bulk density, sand and silt content (Deb et al., 2014). B & C. The lowest levels of bulk density were recorded in samples from zone A collected during monsoon. Highest Sand, silt and clay are the three standard fractions bulk density was observed in soil samples collected from determining soil texture. In all the samples, sand and clay zone B during pre-monsoon. Even though there was slight contributes the major portion. Silt content was only 10%. variation in individual values, bulk density of all soil There was marked variation in texture properties of all samples were around 1.0. Bulk density of zone C samples the three cardamom cultivating zones. Zone A samples was higher from pre monsoon to post monsoon. Bulk were low in sand content but noticeable difference was density was reported to be inversely related to organic not observed in zone B & C. Samples collected during matter (Korschens and Greilich, 1981). Organic matter monsoon has recorded low sand content in all the three enhances water holding capacity, decreases soil zones. Soil interaction with environment depends mainly compaction, breaking strength and bulk density (Cherreau, on soil texture and soil physico-chemical properties. All 1975; Ushakumari, 1987). Close association between the soil properties are determined by geochemical organic matter and aggregation was reported by Singhal formations. Low sand content in zone A attributes to fine et al. (1976). The results of the present study are also in weathering of parent rock and it was supported by more agreement with the previous findings. amount of clay particles having Silt content in zone A was Usually particle density of mineral soils varies from 2.6 to almost same in all the seasons, whereas in zone B, 2.8 with an average of 2.65 g/cc. If soil organic matter is average silt content has increased over a period of time high, particle density even goes below 2.5 (Donahue, from pre monsoon to post monsoon. Similar observations 1961). Particle density of soil samples in the present study were obtained in zone C also. Clay content in zone A has ranged from 1.63 to 2.67. Zone A samples have higher ranged from 34.25 to 34.70 %. A slight increase in clay particle density than other zones. Particle density was more content was noticed during monsoon. Marked difference in samples collected during monsoon, followed by post in clay content was not obtained from the analytical values monsoon. Mulching of plant base with organic materials of clay in zone B, whereas clay content has increased and tillage might have contributed to the decline in particle from 31.10 to 39.21% in zone C. density during pre-monsoon. Sand and silt particles are crystalline mineral matter of Water holding capacity ranged from 55.36 to 72.18%. soils having high particle density. During rainy season, Higher water holding capacity was noticed in zone A the secondary materials such as clay and organic matter samples during monsoon. This trend has been noticed for might have lost from plough layer through runoff, which the entire samples studied. In pre monsoon, minimum was supported by decrease in soil organic matter content water holding capacity was observed in zone B samples, in zone C from pre monsoon to post monsoon. As the where it was low for zone C samples in post monsoon. clay minerals are amorphous, its lattice is built as stacked

Table 4. Spatial variation in soil texture in different cardamom growing areas in Idukki

Zone Sand content (%) Silt content (%) Clay content (%)

PRM M POM PRM M POM PRM M POM A 37.49 36.96 41.04 9.67 9.70 10.31 34.7 37.83 34.25 ±1.5 ±3.2 ±3.25 ±0.26 ±0.8 ±0.0 ±2.5 ±2.1 ±2.8 B 42.75 41.60 43.27 9.72 10.03 12.76 36.2 33.92 33.35 ±6.6 ±2.9 ±1.5 ±2.85 ±1.1 ±2.9 ±10.0 ±4.6 ±3.4 C 46.57 34.39 39.88 10.6 11.26 12.12 31.1 36.23 39.21 ±3.7 ±5.1 ±3.6 ±1.3 ±0.1 ±0.8 ±6.5 ±2.5 ±4.5 PRM - Pre Monsoon; M - Monsoon; POM - Post Monsoon ECO-CHRONICLE 63

Figure. 2 . Seasonal variations in Total phosphorus Figure.5. Rainfall and rain days in cardamom cultivating content of soil areas in Idukki during study period

Figure.3. Chlorpyriphos content in cardamom growing layer of oxygen and hydroxyl ions. Cations of silicon and soils of Idukki aluminium can be bonded between the layers. In Kaoline group of clay minerals, cations can be substituted with other cations. Hence clay minerals are very reactive part of soil. Organic matter and silt content have direct relationship with moisture retention (Verma et al. 1990).

Total phosphorus content in soil samples were analyzed using acid digestion method. Total phosphorus includes all inorganic and organic phosphorus compounds including residues of pesticides by exhaustive digestion.

The average concentration of total phosphorus in zone A has ranged from 306.3 mg Kg-1 to 348 mg Kg-1 (Figure 2). The average total phosphorus content was recorded very Figure.4. Quinalphos content in cardamom growing high in zone A, where as it was almost same in zone B & soils of Idukki C. Seasonal variation was also observed in the case of total phosphorus content. Pre monsoon samples have high total phosphorus content than other two seasons. Pre monsoon samples were having relatively high total phosphorus than other seasons.

Normally in cardamom plantations, fertilizer application will be initiated from the onset of monsoon. Due to acidic nature of cardamom growing soils, all available phosphorus in the form of calcium phosphate will converted to plant unavailable form of iron and aluminum phosphate. If the total phosphorus estimated would have extracted from soil fixed phosphorus of rock phosphates, total phosphorus estimated should have been more in Table 5. Correlation coefficient values between pesticide monsoon and post monsoons. Hence it can be presumed residues and clay content that soil bound residues of pesticides also might have

Clay content (R2 values) contributed to the high value of total phosphorus in soil. Seasons Zone PRM M POM A B C With regard to the estimation of pesticides, the residue of Chlorpyriphos 0.476* -0.536* 0.669** 0.306 0.43 -0.597** Quinalphos 0.395 0.189 0.276 0.478* 0.067 0.158 chlorpyriphos was detected in all soil samples in various quantities (figure 3). There was seasonal variation in the PRM - Pre Monsoon; M - Monsoon; POM - Post Monsoon residue of chlorpyriphos in soil samples. Chlorpyriphos 64 ECO-CHRONICLE residue was recorded more in pre monsoon season in zone chlorpyriphos and quinalphos were correlated with soil A & B. The highest quantity of chlorpyriphos residue organic matter content, Total phosphorus content, pore detected in post monsoon soil samples collected from zone space and clay content. Correlation of pesticide residues C was 254.3µg/g. Average chlorpyriphos residue with soil organic matter, total phosphorus and pore space estimated in all locations were low during monsoon. It were not significant and negatively correlated. Irrespective was also noted that, out of nine plantations, only one of seasonal variation, residues of chlorpyriphos and plantation had very low content of chlorpyriphos residue, quinalphos in soil were positively correlated to clay content irrespective of seasonal variation. In all other cardamom (table 6). plantations, chlorpyriphos might have applied in any of the seasons for the control of pests like root grub or shoot Residues of pesticides were not correlated with other soil borers. Drenching of 3-4 litre of Chlorpyriphos (0.04 % properties, except for clay, in all the three zones. Zonal a.i.) is recommended as per the Package of Practices by variation was not affected in the interaction with clay. Kerala Agricultural University (2007) during May - June Mineral soils perform as sink to retain nitrogen within the and September – October seasons every year for the ecosystem (Huntington et al. 1988). Soil organic carbon control of root grub / shoot borers. The analytical results content influences positively on the degradation of of chlorpyriphos in soil samples of the present study are pesticides (Kah et al. 2007). Adsorption of soil organic in agreement with these recommendations. matter was reported as reverse process (Carringer et al. 1975). Soil organic matter had little effect on the The residue of quinalphos was also detected in all soil persistence of pesticides in soil, but clay mineral content samples throughout the year. Quinalphos content was is a leading factor in sorption of pesticide in soil (Spark more in monsoon season in zone A and B (figure.4). In and Swift, 2002). Bound residues of pesticides play a major zone C, quinalphos residue was more during post role in immobilization of soil applied chemicals in monsoon. Moreover, in one location in zone C, the residue environment. was extremely high. Among the two pesticides studied, residue of quinalphos in soil was less than that of Residue of chlorpyriphos and quinalphos content were chlorpyriphos. Peak season of cardamom productivity is compared with meteorological parameters like rainfall and monsoon, during which quinalphos is sprayed in rain days obtained during 2014-15 in Idukki (figure. 5). cardamom plantations to control pests like shoot borer, Residue of chlorpyriphos was more in pre-monsoon shoot fly, cardamom thrips and other minor pests. period, whereas quinalphos was detected in both pre- monsoon and post-monsoon seasons. Climatic variations While examining the concentration of the residues of in cardamom hills of Idukki might have demanded the various pesticides in soil, it has been noticed that the frequent application of pesticides to control cardamom chemicals which were used for controlling pests persisted pests. in the soil samples throughout the year. The concentration REFERENCES of pesticide applied through soil drenching has persisted in the soil for longer period of time than sprays. The Arora, S., Mukherjee, I., Kumar, A. and Garg, D. K. (2014). persistence of these pesticides in soil and associated Comparative assessment of pesticide residues in grain, environments for a longer period of time is a matter of soil, and water from IPM and non - IPM trials of basmati serious health concern seeking immediate attention. rice. Environmental Monitoring and. Assessment, 186, 361-366. Pesticides and their degradation products are directly related to the ecology of agro ecosystems in many ways. Carringer, R. D., Weber, J. B. and Monaco, T. J. (1975). SPSS statistical software was used in the present study Adsorption-Desorption of selected pesticides by organic to select the best interaction of soil physico-chemical matter and montmorillonite. Journal of Agricultural and properties with the residues of chlorpyriphos and Food Chemistry, 23, 568-572. quinalphos, to explain their seasonal and zonal variation. Separate analysis was carried out for both pesticides and Cherreau, C. (1975). Organic matter and biochemical seasons. Tests of Pearson’s correlation were done by properties of soil in the dry tropical zone of west Africa. testing null hypothesis according to significance level at FAO Soils Bulletin 27, Rome, 313. 0.01. Seasonal and zonal variation in pesticide residues and soil properties are presented in table 5. Deb, P., Debnath, P. and Pattannaik, S.K. (2014). Physico- chemical properties and water holding capacity of cultivated Interaction between residues of individual pesticides and soils along altitudinal gradient in south Sikkim, India. Indian most related soil properties were analysed. Residues of Journal of Agricultural Research, 8(2), 120-126. ECO-CHRONICLE 65

Eaton, D. L., Daroff, R. B., Autrup, H., Bridges, J., Buffler, Kumari, B., Madan, V. K. and Kathpal, T. S. (2008). Status P., Costa, L. G., Coyle, J., McKhann, G., Mobley, W. C., of insecticide contamination of soil and water in Haryana, Nadel, L., Neubert, D., Schutle-Hermann, R. and Spencer, India. Environmental Monitoring and Assessment, 136, 239- P.S. (2008). Review of the toxicity of chlorpyrifos with an 244. emphasis on human exposure and neurodevelopment. Critical Reviews in Toxicology., 38(2), 1-125. Lal, R. and Shukla, M. K. (2004). Principles of soil physics (pp.78-100). USA: CRC press George, T., Beevi, S. N., Xavier, G., Kumar, N. P. and George, J. (2013). Dissipation kinetics and assessment M. S. Swaminathan Research Foundation (2008). of processing factor for chlorpyrifos and lambda- Measures to mitigate agrarian distress in Idukki district of cyhalothrin in cardamom. Environmental Monitoring and Kerala (pp. 87-102). Assessment, 185, 5277-5284. Premachandran, P. N. (2007). Benchmark soils of Kerala Jackson, M. L. (1973). Soil chemical analysis. New Delhi: (pp. 249-283), Kerala: Soil Survey Organisation. Prentice Hall of India Pvt. Ltd. Singhal, R. M., Pathak, T. C. and Banerjee, S. P. (1976). A Kah, M., Beulke, S. and Brown, C. D. (2007). Factors comparative study of some tropical sal forest soils of Doon influencing degradation of pesticides in soil. Journal of valley with reference to their organic matter. Indian Forest, Agricultural and Food Chemistry, 55, 4487-4492. 102, 814-823.

Kerala Agricultural University (2007). Package of practices Spark, K. M. and Swift, R. S. (2002). Effect of soil composition recommendations: crops (pp. 80-87), India: KAU press. and dissolved organic matter on pesticide sorption. The Science of the Total Environment, 298, 147-161. Kittusamy, G., Kandaswamy, C., Kandan, N. and Subramanian, M. (2014). Pesticide Residues in two Frog Ushakumai, K., Leela, K. and Sharda, A. K. (1987). species in a paddy agroecosystem in District, Structural status in relation to physico-chemical Kerala, India. Bulletin of .Environmental Contamination characteristics of soil, Agricultural Research Journal of Toxicology, 93, 728-734. Kerala, 25, 36-44.

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ECO CHRONICLE ISSN: 0973-4155 Vol. 12, No. 3, September, 2017 PP: 67 - 74

LAND USE AND LAND COVER CHANGE DETECTION IN RIVER BASIN, DISTRICT, KERALA USING REMOTE SENSING AND GIS

Gopinathan , A1., Mohammed-Aslam, M. A2. and K. Ibrahim - Bathis3

1 Department of Geology, Government College, Kasaragod, Kerala. 2 Department of Geology, Central University of Karnataka, Kalaburagi, Karnataka. 3 Department of Applied Geology, Kuvempu University, Shankara ghatta, Karnataka. Corresponding Author: [email protected]

ABSTRACT

Land cover of an area is undergoing various transformations due to natural and man-made processes. Information about land use change is needed for planning and development of an area. This study is proposed with an objective for the inventory of various land cover classes in Mogral river basin of , Kerala. The higher value of NDVI is seen along the eastern portion of the study area and also along the banks of stream course. The eastern part of the basin was having comparatively higher NDVI value due to the reserve forest. Compared to the NDVI value of 2009, the NDVI value of the basin in 2016 was decreased. This decrease in value indicated the loss of vegetation due to human encroachment. The changes were identified, in which the decrease of agricultural land, natural vegetation, and water body and increase of urban land and laterite exposure were observed. About 7.75 % decrease in area under forest land, had been noticed. The area under water bodies was also found to be depleting over the years. About 0.11 % of decrease in area under water bodies have been found out. Quarrying, agriculture expansions, deforestation have a crucial role in the reduction of this land cover.

Key words: Remote sensing, GIS, Mogral river basin, NDVI, Laterite.

INTRODUCTION resources in most parts of the world, is facing severe crisis in demand due to contamination and unsustainable water Land is one of the most valuable and constant natural use aggravated by the unpredictable and unforeseen resource of a nation. The land surface is undergoing slow climatic changes caused by deforestation. The climate or fast changes, naturally or due to anthroprogenic change along with urbanization and adverse alterations activities with time. Land Use Land Cover change in land use made most of the world’s fresh water resources detection is the process of detecting the changes in the under severe pressure and change. River banks and its physical features and identifying the effects on the associated landforms act as prominent sites of human environment. It is an important component to understand settlements all over the world, and now they were among the global land status. It can show the present and past the important natural systems receiving the impact of status of the earth’s surface. Land cover is a natural basic pressures of development. Degradation of river basins parameter which evaluates the content of earth’s surface concomitant to depletion of resource is one of the serious on the ecosystem. Land Use and Land Cover studies are environmental issues of Kerala that require quick attention playing important role in environment, ecological studies and corrective measures (Krishnakumar et al., 2017). and natural resource management. Land Use refers to utilization of land by human beings. The changes in land Location use and land cover have intense consequences for the biodiversity and economic rise of the people (Binutha and The river Mogral is a west flowing river in Kerala having a Somashekar, 2014). Land Use and Land Cover changes length of 34 km. It is lying between Chandragiri river basin provide a relation between anthropogenic and natural in the south and Shiriya river basin in the north. The activities in earth. The land use and land cover of an area catchment area of the river basin is 113 sq.km. It lies in varies with its various geological and geomorphological between N12029 00"toN120 36 00" and E740 57, 00" to750 features (Ansari et al., 2013). At present, fresh water 09 30" (Figure.1). 68 ECO-CHRONICLE

Figure 1. Location of Mogral river basin. METHODOLOGY

Two software were used, namely ERDAS Imagine 9.2 and Arc GIS10.1 to analyze the spatial changes in Mogral River basin. ERDAS Imagine 9.2 software is used specifically for image processing and image classification. ArcGIS 10.1 software is used specifically for database maintenance and to prepare interactive layouts. The data used for the analysis is derived from the satellite imageries of IRS P6 and LANDSAT 8. The details are shown in Table 1.

The downloaded zip files were extracted using WinRAR software. Individual bands were layer stacked to get a composite image. The composite image Figure 2. Satellite imagery of Mogral river basin in the year 2009. is extracted to the study area using extract by mask in ArcGIS 10.1. The Focal analysis tool is used in ERDAS Imagine 9.2 software to remove strips in IRS images. Supervised classification is performed using the signature training set collected from the field work. The classification is recoded and area of each class is calculated by adding add area column. The same procedure is applied to all 3 imageries to get the spatial and temporal change analysis of the parameters like water body, vegetation, Agricultural land, forest land, urban land and laterite exposure (Figure 2, 3 and 4). The analysis clearly shows the applications of Remote Sensing and GIS Figure 3. Satellite imagery of Mogral river basin in the year 2013. in Land Use Land Cover analysis.

Table 1. Details of satellite imageries.

Satellite Sensor Resolution Date of the image IRS-P6 LISS- 23.5 15 (RESOURCE III meter Dec SAT-1) 2009 28 Jan 2013 Landsat 8 OLI 30 meter 24 Dec 2016 ECO-CHRONICLE 69

Figure 4. Satellite imagery of Mogral river basin in the year 2016. Normalized Difference Vegetation Index (NDVI)

Remote sensing data are widely used for vegetation mapping and monitoring. The NDVI derived from satellite imageries is one of the useful criteria of vegetation index for the detection of change in vegetation and classification of vegetation into various types. The NDVI also provides a measure of the cover of vegetation and its density on a land surface (Badamasi et al., 2012). Areas of dense vegetation show up very strongly in the imagery than the areas of no vegetation. Natural vegetation shows a tendency to absorb strongly the red wave length of sunlight and it reflects the near Figure 5. NDVI of Mogral river basin in the year 2009. infrared wave lengths. Hence the areas of vegetative cover that appear on a satellite imagery are highly differs from other land surfaces (Jwan Al- doski et al., 2013). The images of a given area, separated by a definite duration of time, are compared to find the change in land cover with respect to pixels of image that changed during the selected interval (Lillesand et al., 2004). Vegetation density is changed by seasonal and annual dynamics (Ozyavuz et al., 2015). The acquisition dates of images are normally selected so that they fall in the same month or season annually. This reduces spectral difference between the images due to seasonal vegetation phenology, angle of sunlight and shading, cloud cover Figure 6. NDVI of Mogral River basin in the year 2013. and concentration of particles in the atmosphere.

In the present study, three satellite images (December 2009, January 2013 and December 2016) of Mogral river basin (Figure 5, 6 and 7) have been classified based on NDVI calculated by using the formula (Tucker, 1979 ).

NDVI = (NIR - RED) / (NIR + RED) (1)

Where, NIR is near-infrared radiation and RED is the red visible radiation. The result obtained out of this formula is called the Normalized Difference Vegetation Index (NDVI). The value of NDVI ranges between -1 to +1. The water bodies, 70 ECO-CHRONICLE

Figure 7. NDVI of Mogral River basin in the year 2016. clouds, and snow cover reflect more in the visible band than that in the near- infrared band .So they have negative NDVI values. The NDVI value of bare soil and rock outcrops are around zero. Healthy green vegetation, on the other hand, has higher near-infrared reflectance there by providing NDVI values close to +1 (Lillesand et al., 2004). A greater value of NDVI infers the presence of dense vegetation on a terrain and its lesser value infers sparse vegetation (Ravi Prakash et al., 2016). Based on this information, the two-date NDVI images were classified into five classes The NDVI derived from IRS P6 satellite image of the year 2009 of Mogral river basin ranges from + 0.71 to - 0.41 Figure 8. Land cover of Mogral river basin in the year 2009. and that of the year 2013 ranges from + 0.75 to - 0.24. In 2016, the NDVI value of the basin derived from LANDSAT image ranges between + 0.520 to - 0.128. The higher value of NDVI is seen along the eastern portion of the study area and also along the banks of stream course. The eastern part of the basin having comparatively higher NDVI value belongs to the Karadka reserve forest. Compared to the NDVI value of 2009 the NDVI value of the basin in 2016 is decreased. This decrease in value indicates the loss of vegetation due to human encroachment.

In the year 2009, area under moderate vegetation, in the basins was estimated as 41.14 km2. This has decreased to Figure 9. Land cover of Mogral river basin in 2013. 38.24 km2 by 2013, and it was again reduced into 35.76 km2 in the basin (Figure 8, 9 and 10). The area of high vegetation of the basin in the years 2009, 2013 and 2016 are 47.46, 44.80 and 40.02 km2 respectively. This shows a declination in the aerial cover of high vegetation from 42.00 % in 2009, to 33.56 % in 2016. This change was due to the deforestation in the area for laterite quarrying and construction activities .Consequently the percentage of the area of no vegetation land increased in the basin.

NDVI also identifies water bodies. In 2009, area under water body in the basins was ECO-CHRONICLE 71

estimated as 0.982 km2. This has come Figure 10. Land cover of Mogral river basin in the year 2016. down to 0.900 km2 by 2013, and it was again reduced into 0.86 in 2016. In the year of 2009 the area of water body was 0.87 % and in 2013 it was reduced to 0.80 % .The water body is further reduced to 0.76 % in the year 2016. It is observed that about 11 % of water body has been lost in Mogral river basins during a time span of 7 years.The land cover changes of water bodies, high vegetation, moderate vegetation and no vegetation in the study area is summarized in Table 2 and Figure 11.

Changes in Land use and Land cover

Analyzing the spatial and temporal changes in land use and land cover (LULC) is one of the diagnostic methods Figure 12. Land use of Mogral river basin in the year 2009 to understand the problems persisting in a river basin. Rapid growth of urbanization along with other increasing human intervention factors have been identified as major reasons of land use changes and land conversions (Mayaja and Srinivasa, 2017). Many studies have been done on land use changes by using satellite imageries and GIS by different workers (Bisht and Kothari 2001, Bhaskaran et al., 2008; Nikhil Raj and Azeez,2010 ; Mahapatra et al., 2013). In the present work, an attempt was made to assess and evaluate the land use and land cover change in Mogral river basin between the years 2009 and 2016 by using Remote Sensing and GIS. Land is used for different purposes including agriculture, Table 2. Land cover changes of Mogral river basin. mining, forestry and nature protection, leisure, and urban and industrial Year development (Willy H. Verheye, 1997). Land use of the Mogral river basin was Class 2009 2013 2016 categorized under five broad groups. Area Area Area Area Area Area km2 % km2 % km2 % The categories are as follows: water bodies, agriculture, forest, urban land Water 0.98 0.87 0.90 0.80 0.86 0.76 and laterite exposure (Figures 12, 13 No 23.42 20.45 29.06 25.39 36.36 25.60 and 14).The type of the land use and Vegetation the area under each category within the Moderate 41.14 36.68 38.24 34.16 35.76 39.99 Vegetation Mogral river basin for the years 2009, High 2013 and 2016 is summarized in Table 47.46 42.00 44.80 39.65 40.02 33.56 Vegetation 3 and graphical representation of LULC by supervised classification are shown Total 113 100 113 100 113 100 in figure 15. 72 ECO-CHRONICLE

Figure 13. Land use of Mogral river basin in 2013. Water body

River flow, ponds and estuary are the prominent water bodies observed in the basin. In general water bodies are represented by light blue to dark blue in tone and the texture show smooth to mottled appearance in satellite imagery. The changes shown by the satellite imagery owing to intensity of absorption of incoming infrared radiation (Nagaraju et al., 2016).The areal extension of water bodies showed a decrease in trend from the year 2009 to 2016 .In the year 2009, an area of 0.87 % of the basin was covered with water and by 2016 it was reduced to 0.76%.

Agriculture land Agricultural land can be defined as the Figure 14. Land use of Mogral river basin in 2016. land which primarily used for farming which includes production of food, fibre, horticultural crops etc. The agricultural areas are largely developed along the flood plains and coastal low lands of the Mogral river basin. Paddy and vegetables are the major food crops that have been cultivating on these areas. The analysis of imageries of the years 2009, 2013 and 2016, revealed that the area under agriculture land does not varied much.

Forest land Forst land perhaps described as the areas which associated with trees and other vegetation types within the notified forest territory. Vast areas of forest is seen on the eastern portion of the basin and intermitttently along the bank zone of the Table 3. Land Use / Land Cover Statistics of Mogral rive basin. river course.In the year 2009 an area of 57.25 km2 was observed under forest Year cover. It has been declined by 51.59 km2 2009 2013 2016 in 2013 and 48.49 km2 in the year 2016. Class A total of 7.75 % of loss of forest cover Area Area Area Area Area Area km2 % km2 % km2 % between the years 2009 and 2016.The widening of laterite quarries and Urban 0.29 0.26 0.34 0.31 0.41 0.36 construction activities has removed large Water 0.98 0.87 0.90 0.80 0.86 0.76 forest cover form the study area. Agriculture 31.37 27.76 31.47 27.85 30.90 27.35 Forest 57.25 50.66 51.59 45.64 48.49 42.91 Urban land In the year of 2009 the urban area in the Laterite 23.11 20.45 28.70 25.40 32.34 28.62 2 exposure basin was 0.29 km and it was spread to 0.34 km2 in 2013. It is again inceased to Total 113 100 113 100 113 100 an area of 0.41 km2 in the year 2016.It is ECO-CHRONICLE 73

Figure 11. Changes of NDVI classes in the study area. had been witnessed. The area under water bodies was also found to be depleting over the years. About 0.11 % decrease in area under water bodies have been found out. It was supported by clear evidences that forest cover decrease occurred due to quarrying activates and cultivation of agriculture crops. It can be concluded that quarrying, agriculture expansions, deforestation has a crucial role in this degradation. The present study also suggested that preventive measures should be taken to reduce forest disturbances and for implementing sustainable management of the developmental activities in Mogral river basin.

Figure 15. Land use / Land cover changes in Mogral river basin. REFERENCES Ansari, Z.R., Rao, L. A. K. and Sameer Saran. (2013). Effect of geology and geomorphology on Land use / Land cover in Himalyan Foothill, Dehradun, Journal Gological Society of India, 81, 827 – 834.

Badamasi, M. M., Yelwa, S.A., Abdul Rahim, M. A. and Noma, S. S.(2012 ). NDVI threshold classification and change detection of vegetation cover at the Falgore Game reserve in Kano state, Nigeria, Sokoto Journal of the Social Sciences, 2(2), 174-194.

Bhaskaran, Baijulal and P. Prateesh (2008). Land use change in upper catchment of Pampa river basin clearly understand that urbanization processes are severe - A GIS based approach, Journal Eco-chronicle, 3(2). 127- in the study region ,hence it is anthroprogenic damge to 130. the Mogral river basin.

Binutha, R. and Somashekar, R.K. (2014). Future Laterite exposure prediction of land cover in taluk, Kerala, The crystalline rocks of the basin are concealed by laterite International journal of science and nature, 5 (4), 677-683. cover.Lateries are developed by intensive and prolonged chemical weathering of the underlying rock and leaching Bisht, B. S. and Kothari, B. P.,(2001). Land cover changes of mineral elements (Ronald, 2012). In the year 2009 the analysis of Garur Ganga Watershed Using GIS/Remote exposed laterite cover of the basin was 23.11 km2 and it Sensing Technique, Journal Indian Soceity of Remote increased to 28.70 km2 in the year 2013. The laterite Sensing, 29: 137-141. exposure further increased to 32.34 km2 by the year 2016.This indicate a hike in 8.17 % of barren laterite Jwan Al-doski, Shattri, B. Mansor and Helmi Zulhaidi Mohd between years 2009 and 2006 within the basin. Shafri.(2013). NDVI Differencing and Post-classification to Detect Vegetation Changes in Halabja City, Iraq, IOSR CONCLUSION Journal of Applied Geology and Geophysics (IOSR-JAGG), The land use land cover classification of the study area 1( 2), 01-10. comprises of urban land, water bodies, agricultural land, forests (dense vegetation) and laterite exposure. From the Krishnakumar, A., Revathy Das and Dhanya, T. Dharan. land use land cover classification, it was clear that there (2017). Land Cover Change Analysis with Special has been a decreasing trend in forest land of the study Reference to Forests and Paddy Wetlands of Neyyar and area. About 7.75 % decrease in area under forest land Karamana River Basins, Kerala, SW India Using GISand 74 ECO-CHRONICLE

Remote sensing, International Journal of Scientific and Nikhil Raj, P.P. and Azeez, P.A. (2010). “Land Use and Research Publications, 7(11),190 - 198. Land Cover Changes in a Tropical River Basin: A Case from Bharathapuzha River Basin, Southern India”, Journal Lillesand, T.M., R.W. Kiefer and J.W. Chipman. (2004). of Geographic Information System, 2,185-193. Remote Sensing and Image Interpretation. John Wiley & Sons Ltd. Ozyavuz, M., Bilgili, B. C. and Salici, A., (2015). Determination of vegetation changes with NDVI method, Mahapatra, M., Ramakrishnan, R., and Rajawat, A. S., Journal of Environmental Protection and Ecology, 16( 1), (2013). Mapping and Monitoring of Land use and Land 264–273. cover Changes using Remote Sensing and GIS Techniques, International Journal of Geomatics and Ravi Prakash Singh, Neha Singh, Saumya Singh, and Geosciences, 4(1), 242-248. Saumitra Mukherjee.(2016). Normalized Difference Vegetation Index (NDVI) Based Classification to Assess Mayaja, N. A. and Srinivasa, C.V. (2017). Land use and the Change in Land Use/Land Cover (LULC) in Lower land cover changes and their impacts in Pampa river basin Assam, India; Cloud Publications, International Journal in Kerala: A remote sensing based analysis, Journal of of Advanced Remote Sensing and GIS, 5 (10), 1963-1970. Geomatics, Indian Society of Geomatics, 11 (1).779 – 783. Ronald Louis Bonewitz (2012).Rocks and Minerals, DK Myneni, R.B., Hall F.G., Sellers P.J., and Marshak A.L., Nature Guide,Dorling Kindersley Ltd., 352. (1995). Interpretation of Spectral Vegetation Indexes, IEEE Trans.Geoscience Remote Sensing, 33, 481-486. Tucker, C.J. (1979). Red and Photographic Infrared Linear Combinations for Monitoring Vegetation, Remote Sensing Nagaraju, A., Balaji, E. and Padmanava, D. (2016). Land and Enviroment, 8, 127-150. Use/Land Cover Analysis Based on Various Comprehensive Geospatial Data Sets: A Case Study from Willy, H. Verheye (1997). Land Use Planning and National Tirupati Area, South India, Advances in Remote Sensing, Soils Policies Agricultural Systems, 53, Elsevier Science 5, 73 - 82. Ltd., 161-174.

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ECO CHRONICLE ISSN: 0973-4155 Vol. 12, No. 2, June, 2017 PP: 75 - 82

EVALUATION OF SHORELINE SEDIMENT QUALITY FOR THE DELINEATION OF SITES FOR MANGROVE AFFORESTATION ALONG THE COASTAL AND INLAND AQUATIC ENVIRONMENTS OF DISTRICT, KERALA, INDIA.

Harilal, C.C., Sajith, U. and Shilna, E.P.

Division of Environmental science, Department of Botany, University of Calicut, , Kerala, India. corresponding author: [email protected]

ABSTRACT

Mangroves are ecologically important tropical forests that are one among the most threatened habitat in the World. In addition to many of the anthropogenic threats, mangroves are also threatened by the impact of global climate change. Both water and sediment characteristics are known to influence the growth and development of different mangrove species. The primary objective of this study was to demarcate ideal sites that uphold adequate growth requirements for mangrove afforestation along the coastal and inland aquatic environments of Malappuram district, Kerala, India, in terms of assessing selected sediment quality parameters.

Collection of sediment samples were carried out from38 sites representing 4 habitats during Pre-monsoon, Monsoon and Post-monsoon seasons. Physico-chemical characteristics of the collected samples were analyzed following standard procedures (Trivedi et al,1987).

Out of the 38sites studied, results of the analysis of various parameters of sediment samples indicated that, seasonal changes in parameters like pH, Electrical conductivity, Salinity, Chloride, soil moisture, organic carbon and texture were found to be influential on the growth of mangroves. Sites already having mangrove population limited to 11 in numbers, wherein optimum values for all the parameters were noticed irrespective of seasons. Comparison of the present results with earlier standardized optimum growth requirements of selected mangrove species has revealed the possibilities of afforestation practices along the study area in all the season of the year.

The overall study revealed that mangrove species such as Bruguiera gymnoriza, Avicennia marina, Sonneratia apellata, Sonneratia caseolaris, Rhizhophora mucronata, Avicennia officinalis, Vitis vitigenia, Deris trifoliate, Cerbera odollam, Premna seratifolia were suitable for afforestation along selected sampling stations. Species such as Rhizhophora apiculata, Kandelia kandel and Acrostichum aureum were not suitable for the afforestation in any of the sites under study.

Key words: Coastal environment, Sediment, Mangroves, Afforestation.

INTRODUCTION area in the world (Naskar and Mandal, 1999). Reports on mangrove habitat of Kerala revealed that the states once Mangroves are taxonomically diverse group of salt tolerant, had a mangrove cover of 700km2 that now drastically mainly arboreal flowering plants that grow primarly in declined 17km2. It indicates that as in many other parts of tropical and subtropical regions (Ellison and Stoddart, the world the vegetation has diminished in its extend 1991). Mangrove forests are one among the most severely and has acquired a threatened status in Kerala productive ecosystem having so many ecological, (Basha, 1991). socioeconomic and physical (Rambok et al, 2010). One of the important functions of mangrove to environment is The loss of mangroves has been significant in recent to provide mechanism for trapping sediment and thus the decades although in some places mangroves are still mangrove forest are considered as an important sink of extensive ( Spadling, 1998). Meanwhile existing suspended sediment (Wolanski, 1994 and Furukawa et mangroves suffer from direct impacts of environmental al, 1997) . pollutants such as heavy metals that are associated with anthropogenic activities (Cuong et al., 2005). A large Mangrove ecosystem currently cover 146530 km of the fraction of mangroves in India was destroyed due to tropical shoreline of the world (FAO, 2003). India has a aquaculture and agriculture expansion. Because of high mangrove cover of about 6749km2,fourth largest mangrove caloric value and high strength of mangrove wood, people 76 ECO-CHRONICLE are destroying mangroves for firewood, charcoal and pH, Electrical conductivity, salinity, alkalinity, chloride, timber (Sahu et al., 2015). moisture percentage, organic carbon and texture along the coastal and inland aquatic environments of Restoration and rehabilitation of existing or former Malappuram District, Kerala, India. mangrove forest areas is extremely important today. MATERIALS AND METHODS Mangrove restoration is re-introduction and re- establishment of assemblages of native mangrove species Study Area to sites that can support them to be developed into District of Malappuram, Kerala state, India is bounded by mangrove ecosystems which perform similar functions as Nilgiri hills on the east, Arabian Sea on the west and has that were there originally. Mangrove restoration programs three distinct topographic features. The coastal are necessary for the protection of coastal areas. environment of the district, extending from Chaliyam to Restoration or rehabilitation may be recommended when Perumpadappu covering a distance of approx.50kms is a system has been altered to such an extent that it can no characterized by a network of estuaries, back waters and longer undergo a self-renew. Under such conditions, confluence point of major rivers like Chaliyar, Kadalundy, ecosystem homeostasis has been permanently stopped and Bharathapuzha. 38 sites represented by 4 and the normal processes of secondary succession or habitats were selected for the study. There were 12 marine natural recovery from damage are inhibited in some way coasts, 15 estuarine, 10 riverine and 1 freshwater habitats. (Clements, 1928). Collection and analysis of sediment samples The present study has been carried out to demarcate the ideal sites for mangrove afforestation on the basis of Sediment samples were collected from 38 sites (Plate 1) seasonal assessment of sediment quality parameters like along the coastal and inland aquatic environments of Plate 1. Sampling sites along the Coastal stretches of Malappuram District. ECO-CHRONICLE 77

Sampling sites along the Coastal stretches of maximum and minimum values have been discussed in Malappuram District. the following.

pH The ranges of pH during premonsoon, monsoon and post monsoonal seasons were 6.15 - 7.96, 4.56 - 7.09 and 3.12 - 7.06 respectively. Maximum pH has been noticed at S 36 (Tanur) durind pre monsoon season and minimum at S 27 (Olipram Kadavu) during post monsoon season.

Electrical conductivity (EC) 103.3-5336µS, 11.80 -1891µS, 27.37-7.06 µS were the ranges of electrical conductivity during pre monsoon, monsoon and post monsoon seasons. The maximum electrical conductivity was reported at S 28 (Athanikal Bridge) and minimum at S 2 (Uppungal Kadavu).

Salinity Ranges of salinity during pre monsoon, monsoon and post monsoon seasons were (5.56-3402 ppm), (27.46- 994.40 ppm) and (21.76 - 1187 ppm) respectively. Salinity was highest in pre monsoon season at S 13 (Puthuponnani Bridge East) and lowest during post monsoon season at S 17(Eswaramangalam).

Alkalinity 200 - 2800 mg/l, 100 - 2000mg/l, 125 - 750 mg/l were the ranges of alkalinity during pre monsoon, monsoon and post monsoon seasons respectively. Highest value of 2800mg/l has been noticed at S 26 (Paravanna) and S 33 (Alungal) during pre monsoon season and lowest value of 100mg/l at S 34 (Poorapuzha Eastern side) and S18 (Athaloor Nedat kadavu) during monsoon season. Malappuram district during three seasons representing Pre-monsoon, Monsoon and Post-monsoon respectively. Chloride Sediment samples from each site were analyzed for its The ranges of chloride concentration during pre monsoon, physico- chemical parameters like pH, Electrical monsoon and post monsoon seasons were (1106.56 - Conductivity, Salinity, alkalinity, Chloride, Soil moisture, 24344.41 mg/l),(88.52 - 6904.98 mg/l) and(132.78 - Organic carbon, Texture following standard procedures 5090.21mg/l), respectively. Highest concentration has (Trivedi,1987). been reported at S13 (Puthuponnani Bridge east) during pre monsoon season and lowest at S 38 (Thayyilakadavu) RESULTS AND DISCUSSION during monsoon season. A total of 38 sediment samples were collected from different coastal and inland aquatic ecosystems of the Moisture percentage Malappuram district. Results of the analysis of various Ranges of moisture percentage during pre monsoon, qualities attributes of sediment during Pre monsoon, monsoon and post monsoons were (11.52 - 57.20%), (6.97 Monsoon and Post monsoon seasons are depicted in - 46.53%) and (0.08 -15.44%) respectively. Moisture Table 1, 2 and 3 respectively. Among various parameters percentage was maximum at S 29 (Kadalundi community studied, organic carbon has been found to have supreme reserve) during pre monsoon season and minimum at S influence on the growth and development of mangrove 36 (Tanur) during monsoon season. species. This was in accordance with other attributes which likely or unlikely affected the growth progress of Organic carbon the mangroves on a seasonal basis. The ranges of each 0.13 -16.56%, 0.03 -29.70%, 0.08 -15.44% were the parameter in all the seasons and sites pertaining to ranges of organic carbon during pre monsoon, monsoon 78 ECO-CHRONICLE

Table 1. Result of analysis of sediment quality parameters during pre monsoon season

ID pH Electrical Salinity Alkalinity Chloride Moisture Organic Texture conductivity (ppm) (mg/l) (mg/l) Percentage carbon (µS) (%) (%) Sand (%) Silt (%) Clay (%) S 1 6.85 313.4 121.6 200 4426.27 44.42 6.46 88.59 10.84 0.56 S 2 6.82 169.8 5.56 400 1106.56 19.57 2.07 55.38 43.04 1.57 S 3 6.15 3079 1649 1600 14385.38 16.11 1.54 92.83 6.47 0.69 S 4 6.43 2587 1381 2200 16598.52 18.78 3.27 73.87 25.86 0.25 S 5 7.25 103.3 64.27 800 5532.84 40.03 3.62 79.68 18.55 1.75 S 6 6.95 134.5 68.65 400 2213.13 19.61 0.82 80.55 17.63 1.80 S 7 6.84 255.9 129.6 800 5532.84 22.36 2.45 95.02 3.26 1.71 S 8 6.65 3300 1799 800 15491.95 22.00 2.09 59.64 37.85 2.50 S 9 7.04 2327 1230 600 15491.95 22.54 0.14 71.14 27.71 1.14 S 10 7.28 1896 995.4 1000 12172.24 15.33 1.75 78.48 21.24 0.26 S 11 7.34 1691 888.4 1200 8852.54 11.52 0.16 70.03 28.08 1.87 S 12 7.29 2928 1569 400 16598.52 16.50 7.12 79.65 19.88 0.46 S 13 7.34 1846 3402 800 24344.41 22.29 1.77 81.78 16.75 1.46 S 14 7.22 3852 2471 800 17705.08 15.19 0.61 83.12 15.76 1.10 S 15 7.26 1669 1369 2200 15491.95 16.92 3.85 86.86 13.00 0.12 S 16 7.54 1227 982.5 1400 9959.11 20.42 0.73 96.05 3.81 0.12 S 17 7.60 1168 601.2 600 5532.84 15.39 2.78 64.12 35.03 0.84 S 18 7.52 172.4 88.43 400 3319.70 19.76 6.90 79.08 19.94 0.96 S 19 6.87 2354 1249 400 9959.11 24.87 2.63 82.73 16.27 0.98 S 20 7.02 2236 1177 400 12172.24 17.87 2.25 80.28 18.95 0.76 S 21 7.24 3877 2036 600 15163.31 25.28 1.04 86.74 12.26 0.99 S 22 7.52 3990 2191 600 11065.62 23.49 2.09 76.56 22.55 0.87 S 23 7.40 4908 2703 800 22131.23 20.09 0.77 76.97 22.16 0.86 S 24 7.71 2634 1400 2400 11065.62 18.98 1.45 88.67 10.63 0.69 S 25 7.63 2558 1370 2600 8852.54 22.04 1.58 86.53 12.86 0.60 S 26 7.80 1553 944.5 2800 3319.70 20.95 0.53 84.10 15.55 0.34 S 27 7.56 2840 1528 400 4426.27 19.72 11.12 45.88 25.43 28.68 S 28 7.42 5336 3045 600 4426.27 37.50 14.15 62.57 15.24 22.17 S 29 7.58 4581 3112 200 2213.13 57.20 16.56 49.70 29.04 21.24 S 30 7.85 2133 1136 1000 44262.27 26.38 1.28 86.00 12.51 1.48 S 31 7.49 2767 1496 1200 11065.62 21.98 1.56 87.77 11.71 0.50 S 32 7.35 3398 1837 1400 3319.70 26.67 2.49 97.39 1.68 0.92 S 33 7.57 2228 1219 2800 22131.23 16.23 0.24 88.81 10.90 0.27 S 34 7.50 3296 1796 400 3319.70 19.12 1.60 98.08 1.66 0.25 S 35 7.45 3867 2120 200 7748.95 17.66 1.09 86.29 13.14 0.55 S 36 7.96 1222 1862 2200 15163.31 13.67 0.13 97.11 2.40 0.48 S 37 7.79 2158 1764 600 14385.38 16.58 0.41 88.14 11.60 0.24 S 38 7.48 800.2 448.2 400 2213.23 31.32 9.80 72.15 20.42 1.42 and post monsoon seasons respectively. Both highest and Clay lowest concentrations of organic carbon have been noticed Ranges of clay during pre monsoon, monsoon and post during monsoon season and at S 27(Olipram kadavu) and monsoon seasons were (0.12 - 28.68%),( 0.11 - 24.11%) S 36 (Tanur) respectively. and (0.25-24.11%) respectively. Highest concentration was at S 27 (Olipram kadavu) during pre monsoon season Texture and lowest at S 36 (Tanur) during monsoon season. Sand Ranges of percentage sand during pre monsoon, monsoon The data revealed that, the mangrove species Bruguiera and post monsoon season were (45.88 - 98.08 %), (42.42 gymnoriza, Rhizhophora mucronata and Avicennia - 99.41%) and (46.70 - 98.71%) respectively. Maximum officinalis are suitable for afforestation along 12 sampling and minimum values were reported at S36 (Tanur) and sites (S2, S5, S6, S8, S14, S18, S19, S21, S22, S23 and S5 (Naranipuzha bridge) during monsoon season. S30) during pre monsoon season, 5 sites (S1, S6, S7, S8, S18) during monsoon season 7 sampling sites (S1, Silt S3, S18, S22, S25, S31, S32) during post monsoon 1.66-43.04 %, 0.46-54.72% and 0.38-48.44% were the ranges season. It has been noticed that Avicennia marina is not of silt during pre monsoon, monsoon and post monsoon suitable for afforestation during pre monsoon and post seasons, respectively. Highest vaue was at S5 (Navanipuzha monsoon season. In monsoon season, it is suitable for bridge) during monsoon season and lowest was at S20 afforestation at S18. Except S3 and S4, all other sites (Pallikadavu munambam) during post monsoon season. have been noticed to be ideal for afforestation of ECO-CHRONICLE 79

Table 2. Result of analysis of sediment quality parameters during monsoon season

ID pH Electrical Salinity Alkalinity Chloride Moisture Organic Texture conductivity (mg/l) (mg/l) (mg/l) percentage carbon (µS) (%) (%) Sand (%) Silt (%) Clay (%) S 1 4.56 349.80 194.90 400 531.15 29.37 1.67 56.29 41.60 0.98 S 2 6.37 11.80 58.93 1000 221.31 20.09 8.41 84.31 14.74 2.09 S 3 5.95 928.98 419.89 1400 5577.10 12.50 1.92 78.44 21.19 0.36 S 4 6.73 992.70 417.3 1000 6904.98 18.82 0.48 97.18 2.53 0.28 S 5 6.66 112.0 60.06 400 575.41 36.65 19.57 42.42 54.72 2.85 S 6 6.04 73.59 41.47 600 619.67 23.89 4.47 83.56 14.44 1.99 S 7 5.92 53.87 27.46 200 442.62 28.45 3.53 73.93 24.92 1.13 S 8 5.74 604.10 302.10 600 1681.98 43.21 4.36 62.39 36.52 1.07 S 9 6.70 479.90 241.50 1800 663.94 6.90 80.67 19.05 0.27 25.75 S 10 5.79 312.40 150.30 600 4382.09 24.37 2.95 84.55 14.68 0.75 S 11 6.20 1481 757.40 800 7562.92 17.64 3.53 90.64 9.11 0.24 S 12 6.72 410.40 204.70 1200 929.51 17.69 0.57 86.09 12.40 1.50 S 13 4.92 1586 780.20 1200 840.99 19.78 4.97 91.77 7.93 0.28 S 14 7.01 489.90 241.20 600 1549.19 6.77 84.86 14.87 0.25 19.10 S 15 6.03 1863 789.20 400 3629.54 19.04 0.24 92.09 6.94 0.95 S 16 6.13 1034 529.20 600 3363.96 13.66 0.56 85.39 14.20 0.39 S 17 6.68 61.61 36.55 600 619.67 16.55 1.18 88.93 10.92 0.13 S 18 6.78 96.66 53.72 100 309.83 23.95 3.26 78.54 19.56 1.88 S 19 6.05 90.53 48.67 800 398.36 2.55 92.19 7.24 0.56 18.11 S 20 5.03 183.70 65.81 400 354.10 18.60 1.21 95.55 1.54 0.90 S 21 6.15 233.10 134.20 800 1106.56 21.90 1.65 87.74 11.46 0.79 S 22 5.59 387.60 127.90 800 1106.56 17.93 2.17 96.00 3.35 0.64 S 23 7.09 157.10 81.46 1000 354.10 18.82 2.03 91.75 7.70 0.54 S 24 5.44 1831 964.10 1800 5577.10 0.89 94.98 4.61 0.39 22.35 S 25 6.18 922.30 471.70 1000 2832.81 8.22 7.15 71.44 27.44 1.10 S 26 6.17 861.10 435.10 1000 2567.23 6.97 0.21 88.22 11.52 0.25 S 27 6.30 817.30 397.50 600 398.36 24.92 29.70 94.36 2.25 24.11 S 28 6.14 513.70 317.30 400 575.41 44.49 11.39 71.56 4.31 3.38 S 29 5.72 476.30 216.20 1000 1704.78 17.76 55.27 26.75 17.96 37.77 S 30 6.39 369.70 182.90 800 1283.61 24.60 5.83 95.94 3.07 0.97 S 31 5.62 705.30 362.50 800 1681.98 21.12 1.44 92.49 6.88 0.62 S 32 6.54 1667 873.20 1400 3496.75 46.53 5.94 50.57 48.42 1.00 S 33 5.88 1891 994.40 600 6063.99 20.61 2.06 97.28 2.59 0.12 S 34 6.12 116.50 61.89 100 973.77 2.65 72.51 26.70 0.78 18.32 S 35 6.69 84.43 46.95 800 486.88 24.24 11.05 81.28 18.03 0.68 S 36 5.88 957.30 426.01 400 2832.81 9.67 0.03 99.41 0.46 0.11 S 37 5.67 1771 928.10 2000 5532.84 23.09 1.14 87.04 12.71 0.24 S 38 6.36 187.40 98.43 800 88.52 32.94 11.85 76.00 22.46 1.53

Sonneratia apellata during post monsoon season. In monsoon season. During monsoon season 8 sites (S1,S6, monsoon season S4, S 5, S8, S9, S14, S17, S18 were found S7, S8, S12, S18, S19 and S30) were noticed to be ideal to be suitable for afforestation of Sonneratia apellata and for afforestation of the above species and during post during post monsoon season S 35 and S38 only were monsoon season S2, S5, S6, S8, S13, S14, S17, S18, S19 suitable for afforestation. Sonneratia caseolaris, Vitis and S30 are suitable for planting. None of the sampling vitigenia, Deris trifoliate, Cerbera odollam, Premna sites in all the three season were found to be suitable for seratifolia were found to be ideal at 10 sampling sites (S1, afforestation of mangrove species such as Rhizhophora S2, S3, S10, S15, S18, S22, S25, S31 and S32) during pre apiculata, Kandelia kandel, and Acrostichum aureum. 80 ECO-CHRONICLE

Table 3. Result of analysis of sediment quality parameters during post monsoon season

ID pH Electrical Salinity Alkalinity Chloride Moisture Organic Texture conductivity (ppm) (mg/l) (mg/l) percentage carbon (µS) (%) (%) Sand (%) Silt (%) Clay (%) S 1 3.44 259.6 122.8 500 265.57 17.93 2.76 46.70 48.44 1.73 S 2 4.63 76.32 42.54 500 177.05 29.29 0.46 57.90 40.11 1.98 S 3 5.70 947.5 449.3 250 1106.56 16.15 2.29 75.62 23.19 1.18 S 4 5.15 992.8 502.0 250 2965.60 12.48 0.27 87.78 11.40 0.80 S 5 4.97 225.5 105.2 125 398.36 44.20 4.56 54.86 44.75 0.37 S 6 4.79 171.3 86.83 125 132.78 42.86 6.62 84.58 14.04 1.37 S 7 5.36 39.07 26.47 250 265.57 22.26 7.36 77.59 21.66 0.73 S 8 3.28 1658 870.3 250 309.83 35.66 2.28 72.56 26.79 0.64 S 9 3.50 418.9 209.3 375 2257.39 29.54 7.81 87.29 12.11 0.58 S 10 3.54 360.2 174.9 500 4824.63 14.75 6.44 56.86 41.54 1.59 S 11 4.88 1066 541.3 250 177.05 15.29 0.08 84.35 15.14 0.49 S 12 5.20 293.4 145.9 375 132.78 16.33 4.80 90.35 7.76 1.87 S 13 3.85 1186 604.8 250 2522.97 23.92 1.69 72.63 26.85 0.51 S 14 5.23 653.7 327.1 500 1991.82 20.20 1.06 77.52 22.07 0.39 S 15 5.34 1131 575.5 250 2877.07 17.79 7.16 84.49 14.49 1.01 S 16 5.51 1778 992.8 500 531.15 22.35 5.31 91.23 8.36 0.39 S 17 6.23 27.37 21.76 125 708.20 16.62 0.06 88.93 9.82 1.24 S 18 6.16 29.44 22.59 250 265.57 22.35 2.87 78.54 19.56 1.88 S 19 6.09 29.31 22.38 375 398.36 18.09 1.43 92.19 7.23 0.56 S 20 6.03 29.09 22.48 250 354.10 18.18 0.27 98.71 0.38 0.90 S 21 3.71 173.2 117.4 625 398.36 18.49 0.16 87.74 11.46 0.79 S 22 5.49 392.3 119.5 250 309.83 21.62 1.40 78.13 20.71 1.15 S 23 5.10 92.17 54.40 375 4337 20.68 0.53 78.24 21.21 0.54 S 24 4.91 1709 892.1 625 5090.21 17.5 0.2 94.98 4.35 0.65 S 25 5.74 1913 1015 375 4899.88 19.45 2.05 70.75 28.13 1.10 S 26 6.05 1333 683.7 250 663.94 11.78 0.82 88.77 10.97 0.25 S 27 3.12 991.2 508.1 250 752.46 28.16 15.44 80.28 2.25 17.46 S 28 3.45 442.7 222.8 750 796.72 30.79 14.42 71.56 4.31 24.11 S 29 5.49 426.5 214.1 500 840.99 29.55 13.59 50.07 29.67 19.65 S 30 6.01 391.5 202.3 250 1372.14 29.32 1.59 74.31 25.13 0.54 S 31 5.88 959.3 493.9 500 885.25 21.85 1.38 64.16 34.83 1.00 S 32 6.15 605.2 306.0 250 929.51 26.09 1.54 80.87 18.10 1.02 S 33 6.35 1302 679.9 250 5045.95 20.66 6.59 96.27 3.70 0.26 S 34 6.39 2247 1187 375 619.67 20.02 14.97 70.95 27.81 1.22 S 35 7.06 92.12 55.64 125 486.88 21.32 2.55 98.66 0.80 0.53 S 36 6.27 2470 1205 375 2434.43 19.49 0.16 83.12 16.5 0.33 S 37 6.30 2015 1061 250 1859.03 17.17 0.6 91.19 8.49 0.30 S 38 6.76 248.6 124.3 375 177.05 28.50 14.62 73.25 17.50 9.23

CONCLUSION suitable for monsoon season at S18. Mangrove species such as Rhizhophora apiculata, Kandelia kandel, and The present study investigated the possibilities of Acrostichum aureum were noticed to be unsuitable for mangrove afforestation along the coastal and inland afforestation along all the sites during any of the seasons aquatic environments of Malappuram district in terms of under study. assessment of selected sediment quality parameters. Samples were collected from 38 sites and characterized ACKNOWLEDGEMENT in the laboratory. Comparison of the present results with earlier standardized optimum growth requirements of The authors are thankful to the Kerala State Council for selected mangrove species has revealed the possibilities Science, Technology and Environment for financial of afforestation practices along the study area in all the assistance under SRS project season of the year. Seasonal variations in parameters like pH, organic carbon and texture have been found REFERENCES influential on the growth of different mangrove species. Mangrove species such as Bruguiera gymnoriza, Badarudeen, A., Sajan, K., Reji Srinivas., Maya, K. and Rhizhophora mucronata and Avicennia officinalis have Padmalal, D. (2014). Environmental significance of heavy been noticed to be suitable for planting along 12 sites metals in leaves and stems of Kerala mangroves, SW during premonsoon, 5 sites during monsoon and 7 sites coast of India. Indian journal of Marine Science,43 during post monsoon season. Avicennia marina is only (6),1021-1029. ECO-CHRONICLE 81

Table 4. Optimized ranges of pH, Organic carbon,Texture for the growth of different mangrove species Sl Name of the Range of parameters Author / Reference no mangrove species pH Organic Sand (%) Silt (%) Clay (%) carbon (%) 1 Avicennia marina 1.675-4.741 Chaudhari.et al (2010)

6.76- 8.74- 5.32- 0.80-35.10 8.08 96.94 71.79 Badarudeen et al 2 Avicennia marina 0.32-7.29 (2014)

3 Avicennia officinalis 1.99-5 23.86- 12.37- 5.35-32.33 Badarudeen et al 79.97 50.11 (2014)

4 Sonneratia apellata 6.6-8.08 1.781-3.665 Chaudhari.et al (2010) 5 Sonneratia 0.32-7.29 8.74- 5.32- 3.87-35.10 Badarudeen et al caseolaris 96.94 71.79 (2014) 6 Bruguiera 0.52-4.89 27.10- 5.86- 0.80-27.69 Badarudeen et al gymnoriza 93.33 50.83 (2014) 7 Rhizhophora 1.99-5 23.86- 12.37- 5.35-32.33 Badarudeen et al mucronata 79.97 50.11 (2014) 8 Rhizhophora 1.99-5 23.86- 12.37- 5.35-32.33 Badarudeen et al apiculata 79.97 50.11 (2014) 9 Kandelia kandel 1.99-5 23.86- 12.37- 5.35-32.33 Badarudeen et al 79.97 50.11 (2014) 10 Acrostichum 1.99-5 23.86- 12.37- 5.35-32.33 Badarudeen et al aureum 79.97 50.11 (2014) 11 Vitis vitigenia 0.32-7.29 8.74- 5.32- 3.87-35.10 (Badarudeen et al 96.94 71.79 (2014) 12 Deris trifoliate 0.32-7.29 8.74- 5.32- 3.87-35.10 (Badarudeen et al 96.94 71.79 (2014) 13 Cerbera odollam 0.32-7.29 8.74- 5.32- 3.87-35.10 (Badarudeen et al 96.94 71.79 (2014) 14 Premna seratifolia 0.32-7.29 8.74- 5.32- 3.87-35.10 (Badarudeen et al 96.94 71.79 (2014)

Basha, S. C. (1991). Distribution of mangroves in redox state,sulphide concentration and salinity in Gazi Bay Kerala. Indian Forester, 117(6), 439 - 448. (Kenya) a preliliminary study. Mangroves & salt marshes, 3. 243 - 249. Clements, F. E. (1928). Plant succession and indicators. Carnegie Institute of Washington.The HW Wilson Co., NY. Naskar, K.R. and Mandal, R.N. (1999) Ecology and Biodiversity of Indian Mangroves. Daya Publishing House, Cuong, D.T., Bayen, S., Wurl, O., Subramanian,K., Wong, Delhi, India. pp.386 - 388. K.K.S., Sivothi, N. and Obbard, J.P. (2005). Heavy metal contamination in mangrove habitats of Singapore. Rambok, E., Gandaseca,S., Ahmed,O.H. and Majid, Baseline / Marine pollution Bulletin, 50,1713 - 1744. N.M.A.(2010). Comparison of selected soil chemical properties of two different mangrove forests in Sarawak. Ellison, J.C. and Stoddart, D.R. (1991). Mangrove Am. J. Environ. Sci., 6, 438 - 441. ecosystem collapse during predicted sea-level rise: Holocene analogues and implications. Journal of Coastal Sahu, S.C., Suresh,H.S., Murthy, I.K. and Ravindranath, N.H. Research, 7, 151-165. (2015). Mangrove area assessment in India: Implications of loss of mangroves, J Earth Sci Cli Change. 6, 280. Furukawa, E., Wolanski, E. and Mueller, H. (1997). Currents and sediment transport in mangrove forests. Sheetal chaudhari and Madhuri Pejaver (2010). Papua New Guinea. Estuar. coast. Shelf Sci. 301-310. Conservation of mangroves with respect to their potentialities of organic crbon accumulation of sediment Mattthijs, S.,Tack, T., Van Speybroeck, D., Koedam, N. of Thane creek, Maharashtra india. Lake 2010. Wetlands, and Koedam (1999). Mangrove species zonation and soil biodiversity and climate change. 82 ECO-CHRONICLE

Trivedy, R. K., Goel, P. K. and Trisal, C.L. (1987). Practical Wolanski, E., King, B. and Galloway, D. (1995). Dynamics methods in Ecology and Environmental Science. of the turbidity maximum in the Fly river estuary,Papua Environmental Science. Pages 340. New Guinea. Estuar.coast. Shelf Sci, 40, 321- 337.

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Review Article

ECO CHRONICLE ISSN: 0973-4155 Vol. 12, No. 3, September, 2017 PP: 83 - 91

SEAWEED RESOURCES OF INDIA AND ITS ECONOMIC IMPORTANCE

Palanisamy, M., S.K. Yadav and Althaf Ahamed Kabeer

Botanical Survey of India, Southern Regional Centre, TNAU Campus, Coimbatore – 641 003, Tamil Nadu, India Corresponding author:[email protected]

ABSTRACT

Seaweeds (marine macro algae) are the integral component of the marine biodiversity and play an important role in the stability of the marine ecosystems. India, with a coastline of about 7500 km length and Exclusive Economic Zone (EEZ) of around 2.5 million sq. km., is endowed with diverse habitats like rocks, corals, reefs, estuaries, lagoons, islands, etc. These diverse habitats support excellent growth of a wide range of seaweeds in Indian coast. Presently, 865 species of seaweeds belonging to 442 species of Rhodophyceae, 212 species of Chlorophyceae and 211 species of Phaeophyceae are reported from India. Many species of these seaweeds are economically important resources and are used for food, fodder, raw materials for various biochemical industries like Agar-Agar, Algin, Carageenans, textiles, pharmaceuticals etc. Therefore these resources should be utilized sustainably for the welfare of the mankind.

Keywords: Seaweeds, Marine Macro Algae, Indian coast, Economical importance.

INTRODUCTION Indian seaweed habitats

Seaweeds are the marine macro algae and exclusively India (8°-37° N & 68°-97° E) being a peninsular country, found in marine habitats. It grows mainly on rocks, has a coastline of about 7500 km including those of islands coralline beds, reefs, pebbles, shells, dead corals and of Andaman & Nicobar and Lakshadweep and endowed also as epiphytes on other plants like seagrasses in the with unique marine habitats (Fig. 1). It has an Exclusive intertidal shallow sub-tidal and deep sea areas up to 180 Economic Zone (EEZ) of around 2.5 million sq km and m depth where the sunlight can penetrate water and gifted with 97 major estuaries, 34 major lagoons, 31 provide energy for photosynthesis. The plant body of mangroves areas, 5 coral reefs, 31 Marine Protected Areas seaweeds is called thallus and it consists of 3 parts: (1) or MPAs (Singh, 2003). These diverse habitats support a Holdfast, the basal part which is analogous to roots of wide range of marine biological diversity and constitute the higher plants; (2) stipe, the middle portion, acting as an integral part of the floral diversity of India (Plate 1). stem of the vascular plants and supports seaweeds to withstand and (3) fronds, the apical portion, somewhat The mainland coast of India is broadly divided into the similar to leaves (lamina) of higher plants. Based on the East and the West coasts. The west coast is usually photosynthetic pigments, colours, and reserve food exposed with heavy surf, rocky shores and headlands materials, seaweeds are classified into three groups viz. while the East coast is generally shelving with beaches, Chlorophyceae (green algae), Phaeophyceae (brown lagoons, delta and marshes. Some of the important places algae) and Rhodophyceae (red algae). Seaweeds play of algal occurrence in India are Okha port, Dwarka, Gulf an important role in sustainability of the marine of Kutch, Bombay, Malvan, Goa, Majali, Karwar, Serikuli, ecosystems. Presently, there are 11,500 taxa of Taderi, Surathkal, , Thikkodi, Thirumullavaram, seaweeds reported and described from the world (Guiry , Somatheeram in the west coast and & Guiry, 2016). Kanyakumari, Mahabalipuram, Gulf of Mannar, Tuticorin, 84 ECO-CHRONICLE

Figure 1. claim to have a complete picture of the seaweed flora of Map showing Indian coastlines. the country.

Economical importance of seaweeds Seaweeds are economically one of the most important marine natural resources and have been used by the human being since long time (Plate 5). Presently, 221 species of seaweeds are commercially utilized, which includes 145 species for food and 110 species for phycocolloid production (Sahoo, 2000, Chennubhotla et al., 2013a). In the recent years, several studies have been carried out in different part of the country for various purposes. The economic importance of seaweeds can be dealt under the following headings:

1. Seaweeds as food The utilization of seaweeds as food in the form of recipes, salads, soups, jellies and vinegar dishes is well known in many Indo-Pacific countries since long ago (Chennubhotla et al., 2013a). In recent years, many of the south east Asian countries like China, Japan, Thailand, Korea etc. , Visakhapatnam, Chilka lake and Sundarbans in have started large scale exploitation of seaweeds for food. the east coast. Presently, 865 species of seaweeds have However, in Indian context, the uses of seaweeds in the been reported from various parts of the Indian coasts (Rao form of food are still very limited. With the continuous & Gupta, 2015). increase in human population and shrinking of agricultural lands, the cultivation of seaweeds in coastal areas, on Seaweed diversity in Indian coast large scale, may serve as an alternative source of food Presently, there are about 45,000 species of algae reported for local people. Worldwide, about 145 species of and described from the world wide, of which seaweeds seaweeds, mostly green seaweeds are edible and used constitute about 11, 500 species. Of the total number of as food mainly in the form of soup, salad and curry. seaweeds, Rhodophyceae is dominant with about 6,500 Recently, Kavale & Chaugule (2013) reported that species, followed by Phaeophyceae with 2,000 species Porphyra vietnamensis – a red seaweed, has several and Chlorophyceae with 1,500 species (Guiry & Guiry, nutritional components like proteins, carbohydrates, lipids, 2016). In India, a total of 865 species of seaweeds vitamins and fatty acids and potentially useful for human comprising 442 species of Rhodophyceae in 151 genera, consumption. 212 species of Chlorophyceae in 46 genera and 211 species of Phaeophyceae in 50 genera (Plates 2-4). Major genera of edible seaweeds Chlorophyceae: Enteromorpha, Ulva, Cladophora, The diversity and distribution of seaweeds along the Indian Brypsis, Caulerpa, Codium etc. coast is not uniform in all the coastal areas and it shows Phaeophyceae: Colpomenia, Hydroclathrus, Laminaria wide variations in terms of seaweeds diversity. The Tamil etc. Nadu coast shows the highest number of seaweeds with Rhodophyceae: Porphyra, Gracilaria, Gelidium, 426 species (Anon, 1978), followed by Maharashtra coast Rhodymenia, Chondrus etc. with 240 species (Piwalatkar, 2010); Gujarat coast with 202 species (Jha & al., 2009); Kerala coast with 137 2. Seaweeds as fodder species (Yadav & al., 2015); Lakshadweep islands with Many species of seaweeds are suitable for feeding 82 species (Anon, 1979) and Andaman & Nicobar islands livestock, sheep and are used as fodder on large scale in with 80 species (Muthuvelan & al., 2001); Karnataka with many parts of the world such as Norway, Iceland, France, 78 species (Kaladharan & al., 2011); Diu island with 70 USA and many other European countries. In Norway, species (Mantri & Subba Rao, 2005); Andhra Pradesh with Ascophyllum is used as pigmeal, Rhodymenia as horse 65 species (Anon, 1984); West Bengal with 14 species meal (Kaladharan, 2014). In Iceland, fresh seaweeds are (Mukhopadhyay & Pal, 2002); Odisha with 14 species commonly utilized as fodder for sheep, cattle and horses. (Sahoo & al., 2003). However, many of the Indian maritime In many parts of Europe, dried and processed seaweeds states have not been explored intensively thus we cannot are served for livestocks. Some of the major genera, ECO-CHRONICLE 85

Plate 1. Sea weed habitats in Indian coast

Green seaweeds at Surathkal coast, Karnataka Luxuriant growth of seaweeds exposed during low tide at Thikkodi coast, Kerala

Rocky coast of Kanyakumari, Tamil Nadu Enormous growth of green seaweeds at Idianthakarai coast, Tamil Nadu

Rocks supporting green seaweeds at Puducherry Scenic beauty of sunset at Mahatma Gandhi coast Marine National Park, South Andaman Islands 86 ECO-CHRONICLE

Plate 2. Green Sea Weeds: Chlorophyceae

Enteromorpha compressa (L.) Nees. Ulva fasciata Delile

Chaetomorpha antennina (Bory) Kuetz. Cladophora vagabunda (L.) C. Hoek.

Caulerpa racemosa (Forssk.) J. Agardh Caulerpa taxifolia (Vahl) C. Agardh. ECO-CHRONICLE 87

Plate 3. Brown Sea Weeds: Phaeophyceae

Dictyota dichotoma (Huds.) J.V. Lamour Lobophora variegata (J.V. Lamour) Womersley ex E.C.Oliveira

Padina pavonica (L.) Thivy Padina tetrastromatica Hauck

Stoechospermum marginatum (C. Agardh) Sargassum tenerrimum J. Agardh Kuetz. 88 ECO-CHRONICLE

Plate 4. Red Sea Weeds: Rhodophyceae

Porphyra vietnamensis Tak. Tanaka & P.H. Ho Gelidium micropterum Kuetz.

Gracilaria corticata (J. Agardh) J. Agardh Gracilaria foliifera (Forssk.) Boergesen

Asparagopsis taxiformis (Delile) Trevis. Hypnea esperi Bory ECO-CHRONICLE 89

Plate 5. Economic importance of Sea Weeds

Seaweed cultivation in Tamil Nadu coastal region Seaweed cleaning and segregation for preservation

Seaweed preservation in wet condition Seaweed grazing by domestic animals

Seaweed extracts used for making Agar-Agar, Alginate and various other products and neutraceuticals (courtesy: Late Prof. V. Krishnamurthy) 90 ECO-CHRONICLE mostly brown and green seaweeds which are used as making drugs for human beings. It is widely used by fodder are Chinese, Romans and Europeans for getting relief in Phaeophyceae: Laminaria, Sargassum, Disctyopteris, wounds, burns, rabies etc. Many species are used as a Fucus etc. constituent in modern allopathic medicines like Tetramycin Chlorophyceae: Ulva, Enteromorpha, Cladophora, suspensions, Penicillium suspension, Triple sulpha Bryopsis, Cladophora etc. tablets, Anti acid tablets, Calamine lotions, Surgical jellies, Rhodophyceae: Rhodymenia, Hypnea, Gracilaria etc. Hemostatic powders etc.

3. Seaweeds in Chemical Industries Besides, many seaweeds contain organic and inorganic Many species of seaweeds are used as raw materials for substance which are used as Nutraceuticles (substances supporting various industries for production of used for performing the basic function of nutrition, and phycocolloides (agar-agar, algin, carrageenans, etc.) and improve health). in pharmaceuticals, cosmetics and textile industries. 4. Seaweeds as Fertilizer (SLF) and Manure Agar-Agar The seaweed biomass acts as manures in agricultural Agar is a gelatinous substance and found in the cell wall fields. In the recent years, liquid extracts of seaweeds, of certain red seaweeds. It is widely used in various especially phaeophyceae, are used as Seaweed Liquid biochemical and microbial laboratories. Gelidiacea and Fertilizers (SLF). The successful applications of SLF on Gracilariaceae are two major source of Agar extraction. various crops have been reported recently by various Some of the important and commonly used red seaweeds workers (Rao, 1990; Rani, 2010, 2011; Sujatha & al., 2011; are Gelidium micropterum, G. pusillum Gelidiella acerosa, Usha & al., 2013; Renukabai & al., 2013; Babu & al., 2015). Gracilaria edulis, G. Crassa, G. Crassa, G. foliifera and G. Some of the commonly used seaweeds for SLF are verrucosa. Dictyopteris, Dictyota, Padina, Lobophora, Sargassum etc.

Algin CONCLUSION Algin, also known as Alginic acid or Alginate is a polysaccharide and is mainly extracted from the brown Seaweeds are one of the most important marine natural seaweeds. It is widely used in making medicines as it has resources and integral part of the biodiversity. It has the capacity to reduce Cholesterol level and also to reduce immense economic values and can be used as food, the amount of heavy metals from our body. The commonly fodder and providing raw materials for various industries. used seaweeds for Algin extraction are species of Many species of seaweeds have great potentials in Sargassum, Turbinaria, Cystoceira, Dictyota, Padina, pharmaceutical and food industries. The artificial Hormophysa, Colpomenia, Spatoglossum, cultivation of these economically important seaweeds Stoechospermum etc. (Anantharaman & large scale by the local people in coastal areas can support Balasubramanian, 2010). as an additional source of income and would help in establishing seaweed-based industries. Therefore, more Carrageenans research should be carried out in this field for better Carrageenans or carrageenins are a group of sulphated exploration, documentation and sustainable utilization of polysachharides and are extracted mainly from the red this promising marine natural resources for the welfare of seaweeds. It has gelling, thickening and stabilizing mankind. properties and therefore, widely used in food industries, dairy, ice creams, milkshakes, yogurts, souces, processed ACKNOWLEDGEMENT meats, toothpaste making, shampoo and other cosmetics etc. Initially, it was extracted only from Chondrus crispus, The authors are thankful to the Director, Botanical Survey a red seaweed also called Iris moss or Carageen moss. of India, Kolkata and Head of Office, Botanical Survey of But now it is also obtained from other red seaweeds like India, Southern Regional Centre, Coimbatore for facilities. Gigartina, Kappaphycus (Euchema), Hypnea etc. REFERENCES Pharmaceutical Industries Plants serve as reliable source of medication for nearly Anantharaman, P & T. Balasubramanian, 2010. Seaweeds 60% of the world’s population (Chennubhotla et al., 2013b). and their potential values. In: Souvenir of the National Many species of seaweeds contain secondary metabolites Symposium on Marine plants, 23-25 September, 2010. which are of pharmaceutical importance and used in pp. 29-44. ECO-CHRONICLE 91

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