Journal of Coastal Conservation

, Volume 13, Issue 4, pp 217–234

Forest structure of arid zone mangroves in relation to their physical and chemical environment in the western Gulf of Kachchh, Gujarat, Northwest coast of India


  • Ayyappan Saravanakumar
    • Centre of Advanced Study in Marine BiologyAnnamalai University
    • Centre of Advanced Study in Marine BiologyAnnamalai University
    • Key Laboratory of Marine Ecology and Environmental Sciences, Institute of OceanologyChinese Academy of Sciences
  • Jun Sun
    • Institute of OceanologyChinese Academy of Sciences
  • Jebaraj Sesh Serebiah
    • Marine Studies & Coastal Resource ManagementMadras Christian College
  • Gobi Alagiri Thivakaran
    • Gujarat Institute of Desert Ecology

DOI: 10.1007/s11852-009-0070-y

Cite this article as:
Saravanakumar, A., Rajkumar, M., Sun, J. et al. J Coast Conserv (2009) 13: 217. doi:10.1007/s11852-009-0070-y


To understand natural and anthropic control of mangrove vegetation in the Gulf of Kachchh, a study was undertaken of its vegetation structure. Over 2 years (1999–2000) at three sites, mangrove vegetation was studied, including tree density, tree height, tree girth at breast height (GBH), canopy index, regeneration class and recruitment class, together with physico-chemical characteristics of water and sediment and the textural aspects of sediments. Reflecting the hot, arid hinterland of Gujarat, ambient temperatures and salinities are high in this macrotidal estuary, decreasing somewhat during the monsoon. The littoral soil supporting the mangrove is abundant in silty loam, silty clay and slity clay loam. The density of mature trees (Mangrove plants of GBH > 25 cm) ranged from 2088/ha to 3011/ha, the height of the trees ranged from 1.42 m to 9 m and the maximum mean GBH at all three sites was 33 cm, and the mean canopy indices ranged between 4.77 m2 and 10.45 m2. The maximum density of regeneration stages was 100,800/ha while that of recruitment stages was only 3,040/ha. While quite severely impacted by anthropic exploitation at one site, the mangrove ecosystem of Gulf of Kachchh was found to be mainly healthy and supporting associated organisms. The ecological and social role of the mangrove, and the potential for its future conservation are briefly discussed in the light of current legislation.


Arid-zone vegetationAvicennia marinaMangroveRegenerationEstuaryLittoral


India is bestowed with a coastline of 8,000 km (Ganapathy 2002), along certain stretches of which, mangroves—“the life line and cradle of a vast array of fin and shellfish juveniles”—are distributed intermittently. Indian mangroves contribute about 4,482 sq. km (Kathiresan and Bingham 2001), constituting 7% of the total coastline (Untawale 1985). World-wide, mangroves comprise approximately 59 species, in 41 genera, of which 34 species in 29 genera are present in India. This includes 25 species along the east coast and 25 species on the west coast (Banerjee et al. 1989; Singh et al. 1990; Deshmukh 1994). Mangroves in the Gulf of Kachchh stand as the second largest mangrove forest in the Indian coastal belt, extending to about 991 km².

The mangrove ecosystem of Kachchh resembles that of the Persian Gulf in several respects (Dodd et al. 1999). The ecosystem experiences a semi-arid climate (Aridity Index 3–4) with an extremely low annual rainfall (av. 272 mm). A high variability in seasonal temperature, a high rate of evapotranspiration (146 mm yr−1), high salinity in both the sediment and the water column, and a tidal amplitude of 0.03 m (MLLW) to 3.06 m (MHHW) subject the mangroves of this region to an extreme environment (Unnikrishnan 1997; Shetye 1999; Saravanakumar et al. 2008a). In response, these mangroves are monospecific and constituted by Avicennia marina (Forsk.) Vierh., already known for its tolerance to extreme environments. Besides this species, the grass Urochondra setulosa, (Trin.) Hubb., a mangrove associate and an endemic species of this coast, was often encountered along the banks of tidal creeks. The mangrove stands of the northwestern part of Kachchh have been totally neglected by researchers despite representing 88% of the Gujarat coast and a large proportion of the west coast of India. Earlier works recorded these mangroves stands as shrubby, degraded formations with no dense growth (Blasco 1977; Untawale 1985). However, studies by Singh (1999) revealed significant increase in the extent of dense mangrove cover in the study area, from 150 km2 to 938 km2 from 1986 to 1998, representing a large mangrove cover in this region (Singh 1999; Thivakaran et al. 2003). Studies pertaining to the structural characteristics of mangrove flora are essential to understand the faunal assemblage and its diversity. It is well known that the canopy cover, tree density and height have a profound role in influencing the distribution of macrofauna. Investigations on vegetation structure are needed as the beginning of environmental studies.

Most of the studies on mangrove forest structure and regeneration have focused on natural stands (FAO 1985; Srivastava and Bal 1984; Cole et al. 1999; Kairo et al. 2002; Bosire et al. 2006, 2008); with relatively few references on reforested stands such as in the Matang forest reserve (Putz and Chan 1986; Ong et al. 1995); as well as Ranong in Thailand (FAO 1985; Choudhury 1997) and Sundarban in India (Hussain 1995; Choudhury 1997). Apart from studies by Bosire et al. (2003, 2006), and Kairo et al. (2008), at Gazi bay in Kenya.

Studies of mangrove structure have been very limited along the Indian coast (Muniyandi 1985; Azariah et al. 1986, 1992; Chakrabarti 1986; Singh et al. 1986; Rao and Rao 1988; Gosh and Choudhury 1989; Selvam et al. 1991; Ramana Murty and Kondala Rao 1993; Nayak 1994; Kathiresan et al. 1994; Saha and Choudhury 1995; GUIDE 2000; Singh 2000). Furthermore, such studies have not yet been made on Kachchh mangroves. Earlier works on the mangrove vegetation of Gujarat, have dealt with mapping and inventorying, using remote sensing (Anjali et al. 1987; Nayak 1994; Bahuguna 1997; Thivakaran et al. 2003), and giving only fleeting information about the Kachchh mangroves of Gujarat.

Industrial and other developments along the Gulf have accelerated in recent years and many industries make use of the Gulf either directly or indirectly. Hence, it is necessary that the existing and proposed developments are planned in an eco-friendly manner to maintain the high bio-productivity and biodiversity of the Gulf region. In this context, the Department of Ocean Development, the Government of India is planning a strategy for management of the Gulf by adopting the framework of Integrated Coastal and Marine Area Management (ICMAM), which is the most appropriate way to achieve the required balance between the environment and development. Mangrove vegetation characteristics and their governing environmental factors on the Gujarat coast in general, and Kachchh in particular, is, however, still limited. This has prompted the present study to be undertaken to improve understanding of the mangrove vegetation characteristics in the western Gulf of Kachchh.

Materials and methods

Study area

Three sites were selected, based on their proximity to the open coast and the level of anthropogenic pressure site 1—Jakhau—Babber Creek (Lat. 23° 13 59′2 N; Long. 68° 36 38′1 E), Site 2—Sangi—Kharo Creek (Lat. 23° 17′ 36.4 N; Long. 68° 31′ 21′ E) and site 3—Medi—Sinthodi Creek (Lat. 23° 27 54.8 N; Long. 68° 29 15.1 E) (Fig. 1) were 5 km distance between each other. These three stations were sampled over a period of 2 years from January, 1999 to December, 2000.
Fig. 1

Map showing the study area

Environmental factors

Along with vegetation sampling, environmental parameters including temperature (sediment and water), pH (sediment and water), salinity (water), dissolved oxygen, nutrients, sedimentary total organic carbon (TOC), total inorganic phosphorus, total nitrogen and sediment texture of mangrove sites were recorded. For the analysis of nutrients, surface water samples were collected in clean polypropylene/glass containers and kept in an icebox and transported immediately to the laboratory. The water and sediment temperatures were recorded with a standard mercury thermometer of 0.02°C precision. Sediment and water pH was measured using a pH meter (Weathertronics model, type 705). While creek water pH was measured directly, sediment pH was measured by making a sediment-water suspension of 1:2.5 ratio. Water salinity was measured using a salinity refractometer (Atago, Japan model). Dissolved oxygen in the surface water was estimated by Winkler’s titrimetric method and inorganic nutrients were measured by adopting standard methods described (Strickland and Parsons 1972). Sediment samples were collected using a Peterson grab (size 0.08 m2). A total of 24 samples were analyzed for each station. Total organic carbon (TOC), total phosphorus and the total nitrogen content of sediment were determined by the methods of El Wakeel and Riley (1956) and Rochford (1951). The percentage compositions of sand, silt and clay in the sediment samples were determined by the method of Krumbein and Pettijohn (1938), that combines sieving and pipetting.

Vegetation characteristics

The mangrove vegetation study was carried out during low tide, when the greatest extents of both intertidal zone and mangrove were exposed. Quantitative data on mangrove vegetation structure at each site were collected using quadrates. At each station at a random point, five transect lines were laid, running perpendicular to the waterfront towards land from the lowest tidal level. Along each transect three plots 10 × 10 m were laid every 50 m with the first one at the water’s edge. In total at each site 15 plots were enumerated (Cintron and Novelli 1984; Deshmukh 1994). A total of 45 plots were sampled, covering three stations along a 15-km stretch of coast. In each plot the total numbers of trees were counted, tree height and both canopy height and width were recorded. Girth at breast height (GBH) was measured for all trees. For each tree, canopy height was multiplied by canopy width to calculate canopy index (Rudran 1978). Within this larger plot one 5 × 5 m plot and three sub plots each of 1 × 1 m were laid randomly to enumerate regeneration and recruitment classes. The regeneration class includes germinating saplings, which are <50 cm tall, and the recruitment class includes well established saplings 50 cm to 1 m tall and <25 cm GBH. Mangrove plants >25 cm GBH are considered as mature trees. The respective densities of mature trees, regeneration and recruitment classes for each island /creek were expressed as density per hectare. Tree height, GBH and canopy index were binned into different frequency classes to allow study of the distributions and compositions of different age classes as well as to calculate their correlation. The number of individuals divided by the area sampled in hectares gives the stand density for the species at that station.

Statistical analysis

Correlation coefficients (r) were calculated for the physico-chemical characteristics, and two-way analysis (ANOVA) was employed on all hydrographic parameters between stations and seasons. The data were then subjected to standard statistical analysis using PRIMER—6.0. A suite of Statistical analyses was also carried out using the statistical packages OriginPro (Version 7.5) and SPSS (Version 16) to elucidate the intra- and interannual variations among the physico-chemical parameters.

Cluster analysis

Cluster analysis was carried out to determine similarities between groups. The most commonly used clustering technique is the hierarchical agglomerative method. The results of this are represented by a dendrogram with the x- axis representing the full set of samples and the y-axis defining the similarity level at which the samples or groups are fused. Bray–Curtis coefficients (Bray and Curtis 1957) were used to produce the dendrogram. The coefficient was calculated by the following formula:
$$ \begin{gathered} \begin{array}{*{20}c} {S_{{jk}} = 100\,\,\,\left\{ {1 - \frac{{\sum\nolimits_{{i = 1}}^p {\left| {y_{{ij}} - y_{{ik}} } \right|} }}{{\sum\nolimits_{{i = 1}}^p {\left( {y_{{ij}} + y_{{ik}} } \right)} }}} \right\}} \\ { = 100\,\,\,\,\,\frac{{\sum\nolimits_{{i = 1}}^p {\,\,\,2\,\,\min \left( {y_{{ij}}, y_{{ik}} } \right)} }}{{\sum\nolimits_{{i = 1}}^p {\left( {y_{{ij}} + y_{{ik}} } \right)} }}} \\ \end{array} \hfill \\ \hfill \\ \end{gathered} $$

where, yij represents the entry in the ith row and jth column of the data matrix i.e. the abundance or biomass for the ith species in the jth sample; yik is the count for the ith species in the kth sample; | … | represents the absolute value of the difference; ‘min’ stands for the minimum of the two counts and Σ represents the sum over all the rows in the matrix.

MDS (non—metric multi dimensional scaling)

This method was proposed by Shepard (1962) and Kruskal (1964) and this was used to find out the similarities (or dissimilarities) between each pair of entities so as to produce a ‘map’ that would ideally show all the interrelationships. Samples lying closer have more similarity in species composition and abundance while samples lying further apart have more dissimilarity in species composition and abundance.


Physics and chemistry of water and sediment

Tidal amplitude varied from 0.03 m to 3.06 m. Surface water temperature varied from 17°C to 37°C for all the three sites, with minimum and maximum mean values (±SD) of 27.41 ± 4.70 (Site I) and 27.74 ± 5.40 (Site III) (Fig. 2). Sediment temperatures ranged between 18.4°C and 37°C for all the three sites, with a minimum and maximum mean values (±SD) of 27.19 ± 4.92 (Site I) and 28.66 ± 4.36 (Site II) (Fig. 3). Salinity varied from 34.0‰ to 44.0‰ for all the three sites, with minimum and maximum mean values (±SD) of 38.91 ± 2.30‰ (Site II) and 39.08 ± 1.91‰ (Site I) (Fig. 4). pH in water ranged between 7.0 and 8.9 for all the three sites, with a minimum and maximum mean values (±SD) of 7.74 ± 0.45 (Site I) and 7.84 ± 0.40 (Site II) (Fig. 5). pH in sediment varied from 6.29 to 8.45 for all the three sites, with a minimum and maximum mean values (±SD) of 7.18 ± 0.50 (Site II) and 7.32 ± 0.45 (Site III) (Fig. 6).
Fig. 2

Seasonal changes in water temperature during 1999 to 2000 at sites I, II and III. Data presented as mean (squares), ±1 SE (boxes) and ±1 SD (whiskers). Upside-down triangles: minimum; right-side-up triangles: maximum
Fig. 3

Seasonal changes in sediment temperature during 1999 to 2000 at sites I, II and III
Fig. 4

Seasonal changes in water salinity during 1999 to 2000 at sites I, II and III
Fig. 5

Seasonal changes in water pH during 1999 to 2000 at sites I, II and III
Fig. 6

Seasonal changes in sediment pH during 1999 to 2000 at sites I, II and III

Variation in dissolved oxygen content was from 3.42 ml l−1 to 5.85 ml l−1 for all the three sites, with minimum and maximum mean values (±SD) of 4.38 ± 0.64 ml l−1 (Site I) and 4.73 ± 0.55 ml l−1 (Site II) (Fig. 7). Nitrate varied from 0.23 µM to 7.26 µM for all the three sites, with minimum and maximum mean values (±SD) of 1.65 ± 1.29 µM (Site I) and 2.29 ± 1.68 µM (Site III) (Fig. 8). Nitrite ranged between 0.04 µM and 0.87 µM for all the three sites, with minimum and maximum mean values (±SD) of 0.38 ± 0.18 µM (Site I) and 0.54 ± 0.21 µM (Site III) (Fig. 9). Phosphate varied from 0.13 µM to 3.12 µM for all the three sites, with minimum and maximum mean values (±SD) of 0.92 ± 0.65 µM (Site I) and 1.25 ± 0.67 µM (Site III) (Fig. 10). Silicate ranged between 4.23 µM to 19.02 µM for all the three sites, with minimum and maximum mean values (±SD) of 8.78 ± 2.44 µM (Site I) and 10.29 ± 3.28 µM (Site III) (Fig. 11).
Fig. 7

Seasonal changes in dissolved oxygen during 1999 to 2000 at sites I, II and III
Fig. 8

Seasonal changes in nitrate during 1999 to 2000 at sites I, II and III
Fig. 9

Seasonal changes nitrite during 1999 to 2000 at sites I, II and III
Fig. 10

Seasonal changes in phosphate during 1999 to 2000 at sites I, II and III
Fig. 11

Seasonal changes in silicate during 1999 to 2000 at sites I, II and III

Organic matter and sedimentology

Total organic carbon varied from 0.29% to 2.56% for all the three sites, with minimum and maximum mean values (±SD) of 1.16 ± 0.31% (Site I) and 1.41 ± 0.55% (Site III) (Fig. 12). Total phosphorus ranged between 0.12 mg. g−1 and 1.97 mg. g−1 for all the three sites, with minimum and maximum mean values (±SD) of 0.63 ± 0.39 mg. g−1 (Site I) and 0.90 ± 0.46 mg. g−1 (Site III) (Fig. 13). Total nitrogen varied from 0.02 mg. g−1 to 1.95 mg. g−1 for all the three sites, with minimum and maximum mean values (±SD) of 0.62 ± 0.46 mg. g−1 (Site I) and 0.78 ± 0.55 mg. g−1 (Site III) (Fig. 14). Sediment texture ranges in terms of % of sand, clay and silt were: 0.26–19.2; 7.6–47 and 47–87.4 respectively at all the three stations (Figs. 15, 16 & 17). The nature of sediment texture is characterized by the abundance of silty loam, silty clay and silty clay loam (Fig. 18).
Fig. 12

Seasonal changes in organic carbon during 1999 to 2000 at sites I, II and III
Fig. 13

Seasonal changes in total phosphorous during 1999 to 2000 at sites I, II and III
Fig. 14

Seasonal changes total nitrogen during 1999 to 2000 at sites I, II and III
Fig. 15

Monthly variations in sediment texture in site I during 1999 to 2000
Fig. 16

Monthly variations in sediment texture in site II during 1999 to 2000
Fig. 17

Monthly variations in sediment texture in site III during 1999 to 2000
Fig. 18

Variations in sediment texture in the study areas

Mangrove characteristics

Tree density varied between different creeks. Density of trees in the sampled area ranged from a minimum of 2088 /ha at site I (Jakhau–Babber creek) and maximum of 3011/ha recorded at site III (Medi–Sinthodi creek) (Fig. 20 & 23). In cluster analysis (Fig. 19) tree density clustered with sites II and III at 95.57% similarity level, while sites II and III, taken together, clustered with site I at 93.09% similarity level. The tree density is correlated with soil pH and temperature regression equation, Tree density = −33649.396 + 3872.028 Soil pH + 292.428 Soil Temperature (Figs. 20, 21, 22, 23). At site II (Sangi–Kharo creek), the tree density was 2522/ha. Mean density of trees in the study areas decreased in the order of site III (Sinthodi creek-Medi)–Site II (Kharo creek-Sangi) and site I (Babber Creek-Jakhau). At all three sites studied the tree density was most near the low water mark, and gradually decreased towards the supratidal zone.
Fig. 19

Tree density similarity at sites I, II and III
Fig. 20

MDS plot for site I
Fig. 21

MDS plot for site II
Fig. 22

MDS plot for site III
Fig. 23

Tree density at sites I, II and III

The height of trees at site I ranged from 1.42 m to 4.81 m, while at site II tree height ranged between 1.98 m and 9 m and at site III between 2.37 m and 8.5 m. Site I had shorter trees, with a mean tree height of (2.59 ± 1.14 m), than site III, (3.79 ± 1.55 m) and site II (4.3 ± 1.71 m) which both had taller stands. Only at site III were all the height classes represented, thus showing the diverse structure of the stand and high quality of the habitat (Fig. 24).
Fig. 24

A. marina height classes at sites I, II and III

In general, the lower tree height class was well represented at site I, whereas sites II and III were dominated by intermediate tree height class; the tallest tree height class was represented only at sites II and III, being totally absent at site I. Similarly, tree densities were higher at sites III and II than at site I.

Mean GBH (Girth at breast height) recorded at site I (36.42 ± 13.64 cm), site II (35.7 ± 17.25 cm) and site III (33.36 ± 13.54 cm) showed little variation between sites. At site I the GBH ranged from 27 cm to 57.33 cm, while in site II it varied from 25.67 cm to 50.74 cm and at site III from 24.76 cm to 48.79 cm. The most trees fell within the smaller GBH size class of 21–40 cm and the fewest trees in the larger size class (<96 cm) (Fig. 25). However, all the stands seem to be represented by large numbers of younger trees, while sites II and I had larger trees than site III, which would suggest an older stand. Figure 26 shows the mean canopy indices at all the three sites. Among the sites, site I showed the lowest mean canopy index (4.77 ± 5.10 m2) compared to site II (10.45 ± 11.17 m2) and site III (8.70 ± 7.33 m2).
Fig. 25

Tree GBH at sites I, II and III
Fig. 26

Tree mean canopy index at sites I, II and III

The lowest canopy index of 0.98 m2 was recorded at site I and the largest of 20.69 m2 at site III. In total site III had a larger canopy index than sites II and I. In most of the places the canopy was uneven taking different shapes in relation to tree spacing, topography and local environmental conditions. Generally trees with larger canopies were recorded within 100 m of the waterfront. The spatial distribution of foliage varied appreciably both in horizontal and vertical strata. In most cases the canopy started from a height of 0.5–1 m on the trunk. In general the bottom of the tree canopy, particularly to the seaward side of the stand, gets submerged at high tide, and there appears to be a uniform decrease in canopy index from the low tide mark to high tide at all the sites.

The density of the regeneration class was found to be much higher than that of the recruitment class at all sites, which showed that there was loss of individuals at the regeneration stage. The maximum density of regeneration was recorded in site III (100800/ha) and the lowest density in (29333 /ha) site I (Fig. 27). Thus, site III (Medi) exhibited a potential for the highest regeneration compared to the other two sites. The most frequent regeneration was also represented by the youngest stands within the three sites studied. This might be because of far less disturbance as the border security force shelters site III. Site I (Jakhau) had the least regeneration, associated with the highest disturbance in the form of lopping and cutting of the mangrove trees by the people and more grazing by the livestock populations.
Fig. 27

Regeneration and recruitment at sites I, II and III

The highest number of recruitments was recorded at site II (3,040/ha) and lowest was found at station I (1,440/ha). At site III, the recruitment numbers was normally intermediate (2,240/ha) (Fig. 27). The drastic reduction in number of individuals from regeneration to recruitment stage is a clear indication of loss of individuals from the regeneration stage due to anthropogenic pressures and also natural competition. Correlations between the physical, chemical and biological variables are shown for each of the three stations in Appendix Tables 1, 2 and 3 respectively.


The tides in the study sites are of the mixed semi diurnal type with a large diurnal inequality and varying amplitude. Gujarat coast experiences very high tides roughly the highest that occur anywhere along the Indian coasts (Unnikrishnan 1997; Shetye 1999; Gupta and Deshmukh 2000). However, in the study area of Kharo creek, maximum and minimum tidal amplitude was 0.03–3.06 m respectively.

During winter and summer, there is a steady increase in surface-water temperature from March to June, which peaks during May, while low temperature prevails in winter. All the stations show similar trends with similar seasonal changes. Generally, surface water temperature is influenced by the intensity of solar radiation, evaporation, insolation, freshwater influx, cooling and vertical mixing by the ebb from and the flow to adjoining neritic waters (Saravanakumar et al. 2008b; 2009). In the present study, summer peaks and monsoonal troughs in air and water temperature were noticed, as observed earlier in the west coast of India (Arthur 2000). A positive correlation was shown between air and surface water temperatures for all the three stations.

Salinity acts as a limiting factor in the distributions of living organisms, and its variation caused by dilution and evaporation is most likely to influence the fauna in the intertidal zone (Asha and Diwakar 2007). Generally, changes in salinity of brackish-water habitats such as estuaries, backwaters and mangroves are due to influx of freshwater from land run off, caused by monsoon or by tidal variations. This is further evidenced by the negative correlation (r = −0.35 at station 1, r = −0.51 at station 2 and r = −0.50 at station 3) between salinity and rainfall. Salinity showed a significant positive correlation with temperature. In the present study, salinity in all the stations was high during summer season and low during the monsoon season. Higher values during summer may be attributed to high degree of evaporation and also due to dominance of neritic water from open sea (Ashok Prabu et al. 2008). The minimum salinity was presumably due to the influence of heavy rainfall and the resultant river run-off, which is a regular annual event in this area during monsoon. On the other hand during the monsoon season, rainfall and the consequent freshwater inflow from the land in turn would have moderately reduced the salinity. Thus the variations in salinity in the study sites were mainly influenced by the rainfall and entry of freshwater as reported earlier for Gulf of Kachchh by Vijayalaksmi et al. (1993) and for Godavari estuary by Sai Sastry and Chandramohan (1990).

Season-wise observation of dissolved oxygen showed an inverse trend against both temperature and salinity. It is well known that temperature and salinity affect dissolution of oxygen in seawater (Saravanakumar et al. 2007a, b). In the present investigation, higher values of dissolved oxygen were recorded during monsoon months in all the stations. The relatively lower values found during winter could be mainly due to reduced agitation and turbulence in the coastal and estuarine waters. The higher dissolved oxygen concentration observed during the monsoon season might be due to the cumulative effects of higher wind velocity coupled with heavy rainfall and the resultant freshwater mixing. Saravanakumar et al. (2007a, b) attributed seasonal variation of dissolved oxygen mainly to freshwater influx and ferruginous impact of sediments. Further, significant inverse relationship between rainfall and nutrients indicated that freshwater input constituted the main source of nutrients in the mangroves. Two way analysis of variance on the results showed that there was no significant variation between stations and seasons.

Hydrogen ion concentration (pH) in surface waters remained alkaline throughout the study period in all the stations with the maximum values occurring in the summer and winter seasons and minimum values occurring in the monsoon season. Generally, increases in pH values during different seasons of the year is attributed to factors like removal of CO2 by photosynthesis through bicarbonate cleavage, dilution of seawater by freshwater influx, reduction of salinity and temperature, and decomposition of organic matter (Rajasegar 2003). Salinity of course had highly significant negative correlation with rainfall.

Nutrients are considered one of the most important parameters in the mangrove environment influencing growth, reproduction and metabolic activities of biotic components. The distribution of nutrients is mainly influenced by season, tidal conditions and freshwater flow from land. High concentration of inorganic phosphate observed during monsoon season might be possibly due to intrusion of upwelling seawater into the creek, which increased the level of phosphate (Saravanakumar et al. 2008a, b). Further, regeneration and release of total phosphorus from bottom mud into the water column by turbulence and mixing may also have contributed to the higher values during the monsoon Rajkumar et al. 2009). In the present study, influx of nutrients from the hinterland appears to be negligible, apparently due to the low rainfall and to numerous water harvesting structures in Kachchh, which stop even meager land runoff. Hence, the increase of nutrients during the monsoon might be due to influx from neritic waters as inferred by Mishra et al. (1993) and Ragothaman and Jaiswal (1995).

In general the nitrite and nitrate values were high during the monsoon and low during summer. The highest phosphate and nitrate values recorded during the monsoon season may be attributed to heavy rainfall, land runoff, its autochthonous origin and weathering of rocks liberating soluble alkali metal phosphates, the bulk of which are carried into the mangrove waters (Ashok Prabu et al. 2008). Another possible way of nitrate entry is through oxidation of ammonia to nitrite and then consequently to nitrate (Rajasegar 2003). The low values recorded during the non-monsoon period may be due to utilization by phytoplankton as evidenced by high photosynthetic activity and the dominance of neritic seawater having negligible amounts of nitrate (Ashok Prabu et al. 2008). The higher value of nitrite recorded during monsoon season may be due to various reasons including variation in phytoplankton excretion, oxidation of ammonia and reduction of nitrate and by recycling of nitrogen and bacterial decomposition of planktonic detritus present in the environment (Govindasamy et al. 2000) and also due to denitrification and air-sea interaction and exchange of chemicals (Saravanakumar et al. 2008a, b).

The content of silicate was higher than that of the other nutrients (NO3, NO2 and PO4), and the recorded high monsoon values may be due to heavy influx of freshwater derived from land drainage carrying silicate leached out from rocks and also from bottom sediments exchanging with overlying water due to the turbulent nature of water in the mangrove environment. The low concentration during summer may be attributed to uptake of silicate by phytoplankton (Saravanakumar et al. 2008a, b). A two way ANOVA on the results showed significant variations between stations (p < 0.005) and seasons (p < 0.005).

The large thermal inertia characteristic of oceans buffers their seasonal temperature variation (Varadhachari et al. 1987). During the monsoon season, low temperature would be due to freshwater flow as stated by Varadhachari et al. (1987). Soil temperature during winter decreased in tune with the atmospheric temperature. Thus, soil temperature positively correlated with water temperature and soil pH negatively correlated with rainfall, nitrate and phosphate in water.

The sediment pH was high in summer and low during monsoon possibly due to redox changes in the sediments and water column apart from the influence of freshwater (Ramanathan 1997). Mangrove soil is always alkaline (Tam et al. 1995 and Tam and Wong 1998). The low value of pH recorded during monsoon months may be due to the oxidation of Feso4 and FeS to H2So4 (Holmer et al. 1994). In addition, soil acidity may have resulted also from decomposition of mangrove litter (Lacerda et al. 1995). A two way ANOVA showed significant differences in pH with seasons (p < 0.005).

The distribution of total organic carbon closely followed the distribution of sediment type i.e., sediment low in clay content was low in total organic carbon and as the clay content increased, the total organic carbon content also increased which as reported by Reddy and Hariharan (1986). In the present study the total organic carbon value was low during monsoon and high during winter season. An abundant supply of organic matter in the water column, relatively rapid rate of accumulation of fine grained inorganic matter and the low O2 content of the water immediately above the bottom sediments would favor high organic matter in the bottom sediments (Sverdrup et al. 1942). A two way ANOVA on the results showed significant differences between the stations (p < 0.025) and seasons (p < 0.01).

The organic carbon in lake sediments is derived from primary production within the aquatic ecosystem (autochthonous sources) and also from terrestrial biota (allochthonous sources) by transport of leached and eroded material into the lake (Likens 1972). In the present study high organic carbon content was recorded during winter post-monsoon. Normally, the overlying waters in the mangrove ecosystem have high organic carbon content compared to estuarine and coastal waters. Therefore, the high organic carbon in the mangrove waters may be due to the mangrove and terrestrial detritus present in the suspended matter (Jagtap 1987). In addition, an increase in organic matter content in the sediments may be due to the fine nature of sediments (Clayey and silt sediments) and a high rate of sedimentation (Raghunath and Sreedhara Murthy 1996; Bragadeeswaran et al. 2007) as well as decomposition of mangrove foliage and other vegetative remains in the sediments (Ramanathan 1997).

In the present study, total nitrogen in sediment was high during winter and summer due to the oxidation of dead plant organic matter, which had settled on the top layer. The lower value of total nitrogen during monsoon season may be ascribed to low levels of organic matter. In Swartkops estuary in Africa, Dye (1978) observed high nitrogen content in finer substrate and suggested that it was probably due to trapping of detritus by fine particles, resulting in an increase in the bacterial population which could also explain the high level of nitrogen encountered in the present study. Reddy and Hariharan (1986) attributed the high values of nitrogen to release from the decay of abundant phytoplankton in Netravathi–Gurupur estuary. The sediment detritus may be a rich source of nitrogen as shown by low C/N ratios and regular ingestion by crabs. The fragmenting of leaves by crabs may be elevating the nutritional quality of the substrate detritus (Skov and Hartnoll 2002). The low values of total nitrogen observed during monsoon season may result from the low level of organic matter during monsoon season, accompanied by large amounts of sand during the monsoon season. A two-way ANOVA test on the results showed significant differences between stations (p < 0.025) and seasons (p < 0.005).

Phosphate is the only plant nutrient anion, which shows exchange with soils (Jackson 1958). The capacity of sediment to buffer phosphate concentrations by retention and release is one of the important factors that influences the concentration of inorganic/organic phosphorus in the overlying waters. In the present study, high values of inorganic phosphorus were recorded during winter and low values during summer. The high values observed may be due to dead organic matter from the top layer and low values may be related to removal of top layer of sediments by heavy floods. A two-way ANOVA test showed significant differences between stations (p < 0.005) and seasons (p < 0.005).

The mangrove flora of the Gujarat coast constitutes eight species, among them Avicennia marina, A. officinalis, Ceriops tagal and Rhizophora mucronata. However, harsh ecological conditions on the Kachchh coast seem to have resulted in monotypic stands of A. marina in the study area. This might be due to the semi arid climate with its very low rainfall, high variability in seasonal temperature, the high rate of evapotranspiration and the exceptionally high salinity in both soil and water. The presence of the vast arid system of the Rann of Kachchh with its extreme climatic conditions in the hinterland plays a great role in determining the physical, chemical, biological and climatic characteristics of these mangroves. In the western Kachchh mangroves are monospecific with only A. marina (Singh 1999; GUIDE 2000). The extraordinary ecological plasticity amongst the functional attributes of A. marina enables it to thrive despite such harsh conditions (Shalom-Gordon and Dubinsky 1993). Mangrove mudflats in the present study were observed to be hyper-saline, enabling the survival of A. marina only. In addition, the non-availability of propagules of other mangrove species in the vicinity, which are recorded in the southern coast of Gulf of Kachchh, appears to be another factor favoring the prevalence of this single species in this study area (Thivakaran et al. 2003). Dodd et al. (1999) reported low floral diversity of mangroves, attributing this to the increasing aridity. A. marina has the largest, almost continuous, biogeographical distribution of any of the other mangrove species in the world (Tomlinson 1986; Duke 1995; Saenger 1997).

Major abiotic factors such as salinity, pH and dissolved oxygen levels (DO) in the study area showed moderate variation among three sites. This relatively low variation is likely because of lack of vegetation and poor terrestrial run-off from the desert hinterland (Rann of Kachchh) mean that they impact only relatively little on the seasonal changes of the nutrient and salinity regimes of the coastal zone, with its concomitant influence on the floral and faunal components. However, seasonal sediment temperature variation in Kachchh is considerable, with mean minima and maxima of 18.4°C and 37°C respectively. Generally sediment and water temperature variation in the intertidal zone is influenced to a great extent by the density and extent of canopy cover.

Values of total organic carbon (TOC) at the study sites were far lower than values reported for other mangrove habitats (Satyanarayana 1973; Naidu 1973; Jagtap 1987). The total lack of terrigenous input of TOC at the study sites appears to be a major reason for these low values. Substrate sediment at all the sites was silty-clay in nature, reflecting the less dynamic and well protected nature of the mangrove habitat characterized by little wave action, that favors fine-particle settlement.

The nature of soil texture of the study areas is shown diagrammatically in Fig. 18. Sediment texture was dominated by silty loam and silty clay at all the stations, in all months, showing little seasonal variation. These consistently high silty loam values may be attributed to the winnowing activity of the sediment transport system. The perennial absence of freshwater flow in the Kachchh district along with lack of wave-induced sand transport from the open sea may also favor this uniformity in soil texture.

The density of trees recorded at all the three stations ranged from 2088/ha to 3011/ha. Corresponding densities were 500/ha to 1900/ha between Mundra and Kori creek mangroves (GUIDE 2000) both part of the Kachchh mangroves and the mangrove of Karachi–Pakistan 4735/ha to 10120/ha (Saifullah et al. 1994). In the Pichavaram mangrove on the southeast coast of Tamil Nadu, the density was 500/ha to 42,100/ha (Kathiresan et al. 1994). The density in this study was much less than in the mangroves of Puerto Rico (Jobus Bay, 47330/ha; Turkey point, 25030/ha) which is in the hurricane belt (Pool et al. 1977). Generally, many natural factors such as the salinity regime, tidal inundation, the absence of freshwater flow etc. as well as anthropogenic impact such as cutting, lopping and grazing pressure, might be the factors responsible for this low density. Similarly, the very low regeneration recruitment ratio is also one of the important factors responsible for the lower density.

A comparable A. marina monospecific stand formation at the mouth of Cooum and Ennore estuaries of Chennai, both under severe human pressure and cattle grazing, had, a far lower density of 30 and 486/ha (Selvam et al. 1991). The higher density at the lower intertidal level over all the study area could be due to the influence of increased nutrient availability through tidal inundation, more water-logging and lower levels of available oxygen (redox potential) which usually characterize the lower intertidal zone. Most of the trees at the study sites were in the height classes of 1 m to 2 m, so that many trees are short at all stations. The very few trees in the 7.6–9 m class were found mostly at stations II and III. Similar observations were made by Perichiappan (1998) in Muthupet mangrove area, when the highest trees were 11.9 m high and the lowest 2.92 m. In the present study, the site near the landing center at station I in Babber creek suffered cutting and lopping of trees and grazing pressure. In Kachchh district the cattle population of the coastal countries (talukas) were 410,463 total live stock population during drought, when they are dependent on these mangroves for fodder (GUIDE 2000). During the summer season, camels consume about 60 kg/day each of A. marina, the coastal villages of Kachchh have in total 4,000 camel i.e., there is requirement of 240,000 kg of grazing for camels alone, and this is largely contributed by A. marina. In addition natural catastrophes such as cyclones during June 1998 and May 1999 brought in much silt and deposited it amongst the pneumatophores (specialized root-like structures which stick up out of the soil like straws for breathing) thus blocking respiration and growth of propagules and seedlings, and ultimately leading to destruction of the habitat. In addition to mangrove sedimentation, high sulfide levels in the pore water also plays a crucial role in mangrove destruction (Smith et al. 1994). Cyclones affect the mangroves by gradually drying the trees in parts of Kharo creek area, some parts of Jakhau and many parts of Kori creek.

The GBH class does not show much variation among the stations. At all the stations trees were predominantly of a smaller size class, 21–40 cm GBH. At station III the density was high (3011/ha) for trees in all the height and GBH classes. At stations I and II the densities were comparatively less, mainly due to the presence of slightly larger GBH-class trees. Soekardjo and Kartawinata (1979) found that as tree density increases the GBH of trees decreases.

Canopy index at the different stations ranged widely between 0.98 m2 to 20.69 m2. Canopies were observed to take different shapes and sizes at different sites in relation to density and cutting pressure. Large canopies were observed at station II Sangi–Kharo creek and station III (Medi–Sinthodi creek), which was due mainly to less human interference. At station I the canopy index was less mainly due to cutting, lopping and cattle grazing. Canopy formation is known to affect soil salinity and transpiration. An increase in canopy gaps leads to an increase in soil salinity (Lockaby et al. 1994). In addition, a close correlation is known to exist between the canopy index and abundance of the faunal diversity, regeneration and recruitment (Ewel et al. 1998).

The densities of regeneration and recruitment classes were fairly high at all the stations. A single tree of A. marina produces thousands of seeds every year. The seeds are deposited along the creek banks and mudflats by wave action and wind. In the present study area, they also enter adjoining land along with water during high tides. Most of these seeds are not washed away with the retreating tide as they get entangled in the preexisting vegetation in the area and germinate profusely. The environment is also attributable to many abiotic and biotic factors such as favorable seed dispersal, availability of limiting nutrients, an absence of foliovores, biofoulers and borers and an absence of grazing pressure GUIDE (2000). At the three stations, the density of regeneration and recruitment classes is higher in the lower intertidal zone and decreases towards the higher intertidal zone, as reported in the Pichavaram mangroves on the east coast of India (Kathiresan et al. 1994).

The value of mangroves has gone unrecognized for many years and the forests are disappearing in many parts of the world. These impacts are likely to continue, and worsen, as human populations expand further into the mangroves. In regions where mangrove removal has produced significant environmental problems, efforts are underway to launch mangrove agro forestry and agriculture projects. Mangrove systems require intensive care to save threatened areas. So far, conservation and management efforts lag behind the destruction, there is still much to learn about proper management and sustainable harvesting of mangrove forests (Kathiresan and Bingham 2001).

In some areas the health and productivity of the forests have declined significantly. The causes of these losses differ from habitat to habitat but are generally tied directly or indirectly to human activities. Case-by-case study is required to determine the most effective remedial measures. Where degraded areas are being regenerated, continued monitoring and thorough assessment must be done to help the recovery process to be understood (Van Speybroeck 1972).

In India the ministry of Environment Forests under the Government of India has overall responsibility for development of the mangrove forest. The Government of India provides 100% financial assistance for implementation of management action plans and research activities related to mangroves. In India a number of laws and policies have been adopted to protect the mangrove forests: Wildlife Act, 1972; Indian forest act; 1927, Environmental protection act, 1986; Coastal Regulation Zone Notification in 1991 under the Environment Protection Act, 1986; and Revision of Coastal Regulation Zone Notification, 2004.


Avicennia marina has been shown to withstand very harsh environmental conditions in Arabian and Persian Gulf coasts, which in many respects resembles the present study area in having monospecific formation with similar environmental condition. High tolerance of A. marina to the prevailing harsh environmental conditions enables it to flourish in this mangrove formation, which however exclude establishment of other mangrove species.


The authors would like to thank the Gujarat State Forest Department for giving permission to carry out this study. We thank the Director, CAS in Marine Biology and authorities of Annamalai University for encouragement and support and the Gujarat Institute of Desert Ecology, Gujarat for providing the facilities. Grateful thanks are also due to Prof. T. Kannupandi, Former Director, CAS in Marine Biology, Parangipettai for their constant encouragement and advice in various stages of the studies. We are also thankful to Dr. Ian Jenkinson, Agency for Consultation and Research in Oceanography, La Roche Canillac, France for his valuable comments. Authors are also thankful to two anonymous reviewer for his valuable comments and suggestions. This work was also supported by Chinese Academy of Sciences Research Fellowship for International Young Researchers to M. Rajkumar and National Natural Science Foundation of China (40776093) to Jun Sun.

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© Springer Science+Business Media B.V. 2009