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Analysis of wave energy reduction and sediment stabilization by mangroves in Gazi Bay, Kenya

. Ndirangu MD, Chira RM, Wang’ondu V, Kairo JG. 2018. Wave energy reduction and sediment stabilization by mangroves in Gazi Bay, Kenya. Biodiversitas 19: 83-94. Mangrove forests provide natural protection to the coast by attenuating wave energy and stabilizing sediments. The efficiency of coastal protection is likely to decline with increased degradation and losses of mangrove forests. Nevertheless, there are few empirical studies to test these hypotheses. The objective of the study was to investigate how wave energy and sediment stabilization vary with tree density in a monospecies stand of mangroves ( Sonneratia alba ) at Gazi Bay, Kenya. Seven belt transects were randomly selected along 900 m stretches of shoreline with homogenous emergent wave energy. Structural parameters, including; tree density, pneumatophores density, and basal areas were quantified using two quadrat measuring 25 m by 20 m along each transect. Three intertidal stations, each with five sampling points were sampled for wave energy using uniform plaster of Paris clod cards. Sediment stability was measured using improvised sinking metal disks made from bicycle spokes, and sediment accretion was monitored by Surface Elevation Tables (SETs). All transects showed significant difference in pneumatophores density (F (2.39) =25.15), tree density (F (2.33) =24.79), and basal area (F (2.39) = 29.66). The wave energy sampled by tree stems between stations and the correlation of wave energy reduction against tree density/ha, pneumatophores density, and basal areas per m 2 also showed a significant difference. Regression analysis showed a significant difference in the sediment stability against tree density (R2 = 61%) and basal areas (R2 = 72.8%) while there was no significant difference between sediment stability and pneumatophores density (R2= 47%). Regression analysis between mean sediment accretion rates against all parameters were not significant. This study will help the managers and the government on the merit of using mangroves as bio-shields in protecting coastlines against erosion and stabilizing sediment in the wake of much anticipated global changing climate and sea-level rise. 2 = 0.530, p = 0.221), fine sand and tree density (r 2 = -0.307, p = 0.503) and coarse sand and tree density (r 2 = 0.083, p = 0.860) among transect in the study site. Correlation between mean silt and pneumatophores density (r 2 = 0.484, p = 0.271), fine sand and pneumatophores density (r 2 = -0.580, p = 0.171) and coarse sand (r 2 = 0.358, p = 0.431) was also not significant in all transect.


INTRODUCTION
Mangrove forests are an important ecosystem that stabilizes coastlines and protect life and property (Keryn et al. 2011). The forest extends to the intertidal areas of sheltered tropical and subtropical shores. They are confined mainly to the tropic region between latitude 30 0 north and 30 0 south (Spalding et al. 2010). Globally, mangroves are estimated to cover 14-24 million ha; spread over 122 territories (Giri et al. 2010). The largest under mangrove forest is in Southeast Asia which occupies 34-42% of global mangroves (Spalding et al. 2010).
In the African continent, Nigeria has the highest density of mangroves with 4.7% followed by Mozambique and Madagascar with 2.3% and 2.0% respectively (Spalding et al. 2010). Considering the multiple goods and services provided by mangrove ecosystem, there is increased effort to restore degraded mangrove forests globally (Gilman et al. 2008). Efforts to replant degraded mangrove forests was started in Kenya in 1990's and is still on-going (Kairo, 1995).
In Kenya, there is some information on human-induced mangrove deforestation and transformation (Abuodha and Kairo 2001). However, only little is known about the effects of degradation on ecosystem functions such as shoreline protection. At Gazi pilot area, for example, removal of the fringing mangroves has led to the erosion of adjacent coconut plantation (Dahdouh-Guebas et al. 2000). Some 30-40% of nearshore mangroves at Gazi comprises of Sonneratia alba forest which is mostly adapted to frequent inundation (Neukermans et al. 2008).
In the context of climate change, mangroves build new land by accreting sediment either in-situ or exogenous (Krauss et al. 2013); thus balancing relative sea level rise (Bell and Lovelock 2013). In the recent past, mangrove forests have proved to provide shoreline protection (Bell and Lovelock 2013). The forest attenuate wave energy and bind sediment by their roots (Mazda et al. 1997). The previous study reported that the Caribbean coast of Belize, Honduras, and Panama (McKee et al. 2007) had shown sediment capture of 4.1 ± 2.2 cm by fringing mangrove forest which is likely to counter the global mean rates of eustatic sea level rise of 1.5-2 mm year -1 (Krauss et al. 2003) This study measured wave attenuation by mangroves at Gazi Bay, Kenya; in a bid to establish baseline data on protective functions of mangroves in the area. In Kenya, mangroves cover was approximately 45,590 ha and are distributed along 600 km of the coastline by the year 2010 (Kirui et al. 2012). The most significant number of mangroves in Kenya is found in Lamu, 33,500 ha, Kwale district, 8375 ha, Kilifi district, 5570ha, Tana River district, The objectives of this research were (i) to determine the effect of trees and pneumatophores density on wave energy reduction; (ii) to assess the impact of tree and pneumatophores density on sediment stability and accretion.

Study areas
The study was performed at Gazi Bay, approximately 60 km from Mombasa Kenya, on the south coast of Kenya (4 0 25'S and 4 0 27'S; 39 0 50'E and 39 ' 50 o E). With a surface area of 18km 2 , the Gazi Bay has an estimated mangrove cover of 615 ha ). The bay is sheltered by Chale peninsula to the east and a fringing reef to the south, where a distance further on-shore a degraded and semipristine fringing mangrove forest occurs ( Figure 1). The study site was severely degraded following deforestation in 1970's and early 1980's through unsustainable harvesting of industrial wood fuel. The width of the fringing mangrove forest ranges between 40-90 m width and 800 m long. The narrow stretch of fringing mangrove forest is inundated daily during spring and neap tide (Kairo 1995).

Hydrology and rainfall
The climate of Gazi Bay resembles that of Kenyan coast which is influenced by both southeast and northeast monsoons. Total annual precipitation exhibits a bimodal pattern of precipitation, ranging between 1000 mm to 1600 mm (Kairo, 1995). During spring, the tidal range in Gazi Bay falls around ~4.0 m (Kirui et al. 2012). Long rains are under the influence of southeast monsoon, starts in April to August while northeast monsoon influences the short rains starting from October to December. The average annual temperature is 26°C and the humidity is approximately 65-80% (Bosire et al. 2003).
The Gazi Bay is an estuary of two seasonal rivers, Kidogoweni River and Mkurumuji River which depend on rainfall experienced inland. River Mkurumuji is more prominent with a catchment of 175km 2 inland and has high flow rates; a maximum and minimum flow of 0.02m 3 /s and 5.90 m 3 respectively while groundwater seepage is restricted to small parts (Kitheka et al. 2003). The hydrology of the more significant Mkurumuji river contributes positively to allochthonous nutrients together with the upcoming anthropogenic inputs from agricultural farms and mining industries during the rainy season (Kitheka et al. 2003). Human activities mainly sugar plantations at Ramisi and Titanium mining both in Kwale County may affect allochthonous sediment input negatively due to damming upstream in both rivers.

Geology
Geologically, Kenyan coast comprises of rocks mostly marls and limestone, and are represented by sandstones, clays, conglomerates, and gravels (GOK 2009). These well-developed reef complex consisting of coral reefs, coral rubble and sandstones are extensively exploited by the building industry (GOK 2009). Fringing reef crests dominate the Kenyan coast forming a natural barrier to the wave energy from the ocean with a shoreline comprising of reef terraces and mangroves, with a tidal flat in Gazi Bay fronting the mangroves (GOK 2010). The study site is conducted on low shore beach that receives daily inundation (Watson inundation class 1) and has moderate wave exposure and sandy sediments. The highest spring tide is approximately 4 m above datum (Kitheka et al. 2003).

Mangroves of gazi
Gazi Bay posses all the nine mangrove species described in the western Indian Ocean region. The dominant species that makes more than 70% of the formation are Ceriops tagal (Perr) C.B Robinson and Rhizophora mucronata (Lam) . A typical pattern of species which occurs from the sea to the land are S. alba, R. Mucronata, Bruguiera gymnorrhiza, (L) Lam C. tagal, Avicennia marina (Forsk) Vierh, Xylocarpus granatum (Koen), Lumnitzera racemosa (Willd), Xylocarpus muluccensis (Lam) Roem and Heritiera Littoralis (Dryand) (Dahdouh-Guebas et al. 2000). The massive tidal regime controls these species. Animal species ranges from mollusks; sesarmid crabs which are keystone species due to their high rate of nutrient cycling . Other common species of crabs include Uca annulipes and Uca inverse (Skove et al. 2002).
Epibiotic communities of algal species encountered in both seaward and landward zones include Enteromorpha ramulosa, Polysiphonia sp., Hypnea sp. and Caloglossa leprieuri attached to pneumatophores of S. alba at different pneumatophores height. Poriferans are found growing on the pneumatophores of S. Alba stands with Tedania digitata vulcanis as a common example (Crona et al. 2006).
Gazi Mangrove forests are habitat for juvenile fish which are either planktivorous or benthic feeders. Common juvenile species of fish located in the fringing mangrove forest are Gerres oyena and lutjanus fulviflamma (Kirui et al. 2012). Also, the forest forms a suitable habitat for different species of snakes, resident and migratory birds that commonly feed in the nearshore environments (Kairo 1995).

Social economic activities
Gazi Bay has a population of approximately 4825 people according to the national census of 2009, the majority being women and children. The men (90%) are involved in artisanal fishing and mangrove cutting for sale to Mombasa and other coastal towns (Hamsa 2013). Approximately 90% of mangroves harvested are used for building houses, tannins, provision of wood fuel, ribs for boat manufacture and furniture, traditional medicine (Dahdouh-Guebas et al. 2000). Meanwhile, women are mostly engaged in small businesses and weaving makuti (roof thatches made from coconut fronds) farming (Dahdouh-Guebas et al. 2000). Mangroves have also been used extensively by both undergraduate and postgraduate research student from various disciplines to address various research questions (Kairo et al. 2009).
Recently, Mikoko Pamoja, a community-based mangrove conservation initiative, have started mangrove restoration and protection in the bay. Together with KMFRI and Universities in the UK, their attempt for mangrove restoration and protection are made through the sale of carbon credits in the voluntary carbon market (Hamsa 2013).

Project design
Change in wave energy was measured across seven belt transects selected randomly and perpendicular to the shoreline in a monospecies of fringing of Sonneratia forest ( Figure 2). The seven transects had a varying tree and pneumatophores densities and were denoted with letters K, L, M, N, O, and P. Among the seven transects, transect Q had no mangrove cover and was selected as a control. The belt-transect were set a short distance from river Mkurumuji heading north towards the Bay. This selection was made to incorporate vegetation structural differences of fringing mangroves.
The positioning of transects was done in areas where the band width of the mangrove trees stretch was ≥ 80m. This positioning was made because the band width of the mangrove forest was not uniform at the study site and it was the most extensive stretch of mangrove cover that existed and allowed a sufficient number of transects.

Sampling design
The density of mangrove trees was quantified in seven; 80 m long belt transects by utilizing two plots each measuring 25 m long and 20 m width. The plots were systematically selected along each transect which was set perpendicular to the shoreline. The first plot was established 20 m from the lowest mangrove tree on the seaward side while the second plot was set 5 m from the first plot toward the landward side. Pneumatophores density was determined by systematically selecting five quadrats each measuring 1m by1 m nested in each of the more prominent plots of 25 m by 20 m. At each corner, the four plots of 1 m by 1 m were set, and one at the middle of each of the two plots. A total of ten plots per transect were selected to estimate pneumatophore density per transect A total of 12 plots were selected to calculate mangrove trees and pneumatophores density respectively at the study site.
Wave energy was measured at three stations marked A B and C across seven transects set perpendicular to the shoreline. A total of 21 stations were characterized in the study area. Station A was ~20 m from the last mangrove trees on the seaward side which measured incident wave energy before mangrove influence; station B was 50 m from station A while station C was 80 m from station A. Both station B and C measured incident wave energy passing through the mangrove forest. Each station was marked with five wooden poles of 10cm girth, 1.5m high, driven 70 cm into the ground.
Paris clods were used to measure wave energy. The clods were prepared by mixing 11.4ml of fresh water with 14.3g plaster of Paris powder manufactured by LAFARGE PRESTIA (www.lafargeprestia.fr) ( Figure 3). The powder was slowly added to water and stirred with a spoon. The slurry was poured into a plastic ice cube trays. The trays were tapped several times vigorously to dislodge air bubbles, and allowed to harden for between 20-30 minutes before removing them. Following this step, the cards were oven dried for 48 hours at 40 degrees centigrade. The final weight of the clod after exposure to the field was determined by subtracting the total weight of the clod plus the plastic plate and the silicon cement before exposure. The basic assumption was that the weight of the plastic and that of the silicon cement remained constant and did not change due to corrosion by sea water. The clod cards were then sanded at the bottom to attain a uniform weight of 14 ± 1.5 g within a batch. They were glued to a 3 cm×8 cm plastic plate with silicone cement (No Nonsense Ltd.BA 228RT). These cards were taken to the field and mounted on the poles at 15 cm and 50 cm from the substrate surface respectively as shown in Figure  4. The clod cards mounted at 15 cm measured wave energy reduction by pneumatophores while the clod cards mounted at 50 cm measured wave energy reduction by mangrove tree stems.
Soil samples were collected at 10 points extending the three stations for each transect namely; station A, on the seaward side, station B in the middle of mangrove forest and C on the landward side. The soil samples were obtained using a corer at approximately 5 cm depth. The points at which the samples were collected covers a distance of 25 m along each station, and is separated 5 corerm away from each other. The ten samples for each station were pooled in one labeled plastic bag and mixed thoroughly to make one composite.
The stability of sediment was measured using cheap and inexpensive bicycle spokes fitted with metal disks at the three stations in the same transects set perpendicular to the shoreline where wave energy was determined. As many as ten replicate points, which were 2.5 m apart were systematically selected covering a distance of 25 m along each station. The spokes were fitted with the metal disks weighing 2.8 g and 1.7 cm in diameter and inserted in the sediment approximately 5 cm Bicycle. The metal disks were held in position by the spokes and left at the substrate surface such that unstable sediment could cover them as sediment settles down during the alternating high and low tide regimes. A total of 30 spokes per transect were used in six transects with contrasting mangrove tree density. One transect without tree cover was established perpendicular to the shore as a control. The use of bicycle spokes and the metal disc was inexpensive for estimating sediment stability because the materials used were cheap and locally available. We suggest that; first, the metal disk was denser than seawater and therefore sunk during high tide. Second, the dimension of the spoke such as thickness did not modify the site by reducing water velocity thus facilitating sediment to settle. Furthermore, all spokes and metal discs at station A before the mangroves on the seaward side were used as a control for all transects.
Measurement of sediment accretion was done using a 3 m long and 1 cm diameter of stainless steel rods. Two metal rods were set 50 cm apart and driven 280 cm into the sediment at station B which was almost in the middle of the transect. A portion of 20 cm ± 0.1 cm of each rod was left projecting perpendicular above the substrate surface. Leveling was done using the spirit level to ensure both steel rods were at the same height. Thus, sediment accretion was estimated at six sites in six transects set perpendicular to the shoreline.
Use of steel rods has an advantage of determining not only accretion and erosion but also gives information about subsurface processes down to the maximum level at which the pins are driven. Use of rods in surface elevation table (R-SET) is advantageous since it is cheap regarding cost, high-precision, simple, and it is accessible to economically developing countries with coastal wetlands. In this experiment, wooden board 4.2 cm × 2.2 cm and 50 cm long smoothened flat and the square was used to determine sediment accretion. The wooden board was placed on the two rods projecting above the substrate. Ten replicate points were marked along its entire length of the wooden board. To determine surface elevation changes at each transect, the wooden board was set on the two rods projecting on the substrate surface.

Data collection methods
Within the two plots measuring 25 m by 20 m along each transect, diameter at breast height (DBH) of mangrove tree stem was measured at D130 or diameters at 1.3 m above the ground (Cintron and Schaeffer-Novelli, 1984). All mangrove tree stems in diameter D130 ≥ 2.5 m were measured and recorded. Stand density per hectare for each transect was calculated using the relation. Di = ni/Ai. Where; D i is the density for species i, n i is the total number of individuals counted for species and A i is the total area sampled (Brower and Carl., 1990). Basal areas were calculated using the formula; BA= 0.00007854×DBH2 (where DBH is diameter at breast height). Ten pneumatophores were selected randomly in ten quadrats per transect measuring 1m× 1 m. Their height and diameter at ½ heights were measured using a standard ruler and Vanier calipers respectively. The density of the pneumatophores was calculated per meter square in each transect and recorded.
Wave energy was sampled twice covering northeast monsoon season by exposing clod cards to wave action for 48 hours on the 8th to 10th October 2012 during spring. A replicate sampling of wave energy was taken during neap tide on the 16th -18th of November 2012. During the southeast monsoon season, wave energy sampling was done by exposing clod cards for 48 hours on the 1st to 3rd March 2013 during spring tide. A replicate sampling of wave energy was retaken on the 25th to 27th May 2013. During the four sampling regimes, clod cards were mounted and retrieved during low water.  The underlying assumptions were; First, station A, in all transects would be impacted more by high water velocity due to the absence of mangrove forest structures thus experience high rates of dissolution of clod cards. Secondly, lower clod cards sampled the energy absorbed by pneumatophores while the upper clod card sampled the hydrological energy consumed by the tree stems and pneumatophores. Also, the magnitude of tide could not change within the same tide cycle during the period of clod card exposure.
Data collection of the soil samples was done in the laboratory. After drying, the samples were weighed; oven dried at 80C for 24 hours, to determine the percentage moisture content. From the dried soil samples, a subsample of 25 g from each station was accurately weighed for grain size analysis. The second set of samples weighing 25 g were labeled and preserved for organic matter analysis.
The sediment (25 g) was put in a labeled beaker and treated with (6.2g/1 dilution) of 250 ml water and 10 ml aqueous sodium hexametaphosphate ((NaPO3)6). The solutions were stirred for 10 minutes and left for four hours then further stirred for 10 more minutes. The content of the beaker was flushed through 63 µm sieve with fresh water until no further silt was lost. The wet sediment was carefully flushed into a pre-weighed foil boat and oven dried at 80 0 C for 12 hours. Next, the dry content was weighed to determine the weight of silt. The dry sediment was then flushed through 500 µm sieve. The sediment grain size >500 µm were weighed and recorded and used to calculate the weight of the 63-500 µm fraction. From the oven dried preserved sample of 25 g, a sub-sample of 10 g was weighed and put in pre-weighed aluminum crucibles and set in a muffle furnace for combustion at 440 0 C for 6 hours. The procedure was followed by cooling the samples in a desiccator and weighed to determine the organic matter in the sediment.
The sediment stability was monitored by estimating the depth at which the metal disks sunk in the sediment. Every month, the depth of sinking metal disks was estimated using a standard ruler during low tide. New spokes and metal disks were reset for the presiding month to avoid confounding due to changes in mass of the disks as a result of corrosive nature of seawater. Sediment accretion was estimated using a standard ruler by measuring the height from the substrate to the wooden board placed on the two rods. For all the six transects from the ten points marked on the wooden board, ten replicate measurements were taken and recorded once in each month ( Figure 5). The measurements were taken for 8 months covering a total of 240 days.

Data analysis methods
Data were analyzed using MINITAB 14.0 software package. One way analysis of variance (ANOVA) was performed to test the variations in three parameters: tree density, pneumatophores density, and basal areas between transect. The same data analysis was also performed to examine how wave energy varied between the three stations in different transects with varying tree and pneumatophores densities. Pearson's correlation analysis was carried out to investigate the significance of the forest structure namely; tree density, pneumatophores density and basal areas against wave energy.
Correlation analysis was carried to test for significant difference between silt, fine sand, coarse sand and organic matter against tree and pneumatophores density. ANOVA was used to test for variation in sediment stability during the two sampling regimes and also differences between stations in different transects. Regression analysis was carried out to check for sediment stability and sediment accretion against tree density/ha and pneumatophores density m 2 .

Effect of tree and pneumatophores density on wave energy reduction
Wave energy sampled by stems in all station A on the seaward side before the mangrove influence had the highest mean in wave energy expressing 81.4 ± 5.1% (SE) reducing gradually from station B (73.1 ± 4.9% (SE)) to C (65.5 ± 5.5% (SE)). Transect Q with no mangrove cover had the highest mean in wave energy sampled by tree stems expressing a mean of 84.3 ± 1.7% (SE) in station A, 81.5± 1.4% and 77.9 ± 2.0% (SE) in station B and C respectively. The mean wave energy sampled by mangrove stems was 73.4 ± 4.8 while the mean of the control station Q had 81.2 ± 2.9. The mean wave energy expressed in the control denoted with letter Q (without mangrove trees) was higher by 7.8% compared to the mean of wave energy reduction in the six transect with mangrove tree cover. Table 2 summarized the results for wave energy reduction along station A, B, and C in all transects sampled at 50 cm by tree stems and the mean of the three stations per transect.
Wave energy sampled at 15 cm which expressed energy reduction by pneumatophores in all station A on the seaward side before mangrove influence had the highest mean of wave energy expressing 84.7 ± 2.7% (SE). Results for wave energy reduction across station A, B, and C in all transects sampled at 15 cm by pneumatophores and the mean of the three stations per transect are shown in (Table  3).
The energy from station B to C has gradually reduced at the average of 77.5 ±2.8 and 73.5 ± 2.8% (SE) respectively. Transect Q (Control) without pneumatophores cover had the highest mean in wave energy in station A expressing 86.4 ± 2.5, while station B and C expressed 84.3 ± 1.5 and 81.3 ± 1.6% (SE) respectively. In average, wave energy reduced by pneumatophores in the six transect with varying pneumatophore cover was 79.0 ± 1.9. Meanwhile, the mean wave energy measured at the three stations (A, B, and C) in transect without pneumatophore cover (control transect ) had 84.0 ± 2.9. Therefore, the difference in wave energy reduction by areas covered by pneumatophores and the areas without (the control transect was 5%. ANOVA showed a significant difference in the wave energy reduction by pneumatophores between stations A, without pneumatophores cover and stations B and C with pneumatophores cover (F (2.18) =17.05, p = 0.000).
Total energy reduced by mangrove trees reached 7.8% while the energy reduced by pneumatophores was 5.0%. The entire wave energy reduced by both tree density and pneumatophore density was 12.8%. To get the relation between wave energy change across the mangrove forest, as well as to better understand the effect of tree density on the wave energy, a plot of wave energy on the Y-axis and transects with different tree density on the X-axis was plotted. The wave energy reduction measured at 50 cm above the substrate (energy reduction by mangrove tree stems) is shown in Figure 7. The result showed wave energy decreasing with increasing tree density.
The plot for hydrological energy sampled at 15 cm above (energy reduction by pneumatophores density) against pneumatophores density in the seven transect showed the same trend as the energy reduction sampled by tree density where wave energy reduced with increasing pneumatophore density (Figure 8).

Sediment grain size and organic matter distribution
The analysis of grain size showed a higher percentage of silt in transect M, K and L expressing 15.2 ± 5.8%, 15.0 ± 2.2% and 8.8 ±2 1.2% (SE) while coarse sand was highest in transects P, O and N expressing 39.7 ± 0.1, 18.1 ± 0.5 and 12.8 ± 0.9 (SE) respectively. All transects expressed mean fine sand as the highest proportion of sediment by 79.5±4.7 % (SE). Coarse sand was least frequent in all transect with exception of transect P which had a mean of 39.7 ± 0.1%. Transect Q displayed the highest percentage of fine sand with 93.1 ± 0.4% (SE).
Organic matter distribution was highest in transect K, M, and N expressing 2.1 ± 0.5, 1.9 ± 0.4 and 1.6 ± 0.5 (SE) respectively while the control transect (Q) with no mangrove cover expressed the lowest percentage of 0.8 ± 0.1 (SE). No significant correlation of organic matter between tree density/ha (r = 0.521, p = 0.230) and also in pneumatophores density/m 2 (r = 0.367, p = 0.419). Results for sediment grain sizes and organic matter content during the study period are summarized in (Table 4).

Effect of tree and pneumatophores density on sediment stability and accretion
Mean sinking depths of metal disks in the entire sampling period were pooled per station A, B, and C covering both southeast and north-east monsoon seasons. All stations before the mangrove influence on the seaward side (station A) displayed the highest means of sinking depths of metal disks of 14.6 ± 3.1mm (SE). The depth reduced gradually from station B to C which attained a sinking depth of 8.2 ± 2.7 mm (SE) and 7.4 ± 3.5 mm (SE) respectively. In contrast, transect P which was near river Mkurumuji recorded slightly high sinking depth in station C on the landward side with 7.35 ± 0.8 (SE) than station B and C which had similar values of 5.78 ±0.6 (SE). On the other hand, Transect Q with no mangrove cover registered the highest mean depth of 23.2 ± 2.3 mm (SE) in the three station. Unlike most station in another transect with varying tree cover, station A in the open area (control transect Q) had the least depth of 19.9 ± 2.4 (SE) compared with station B and C which recorded 21.9 ± 2.2 and 27.7 ± 2.9 (SE) respectively. Transect M had the least mean depth of 2.9 ± 1.1 1.6 (SE) in all transects.  ANOVA showed a significant difference in sinking depth of metal disks between stations A B and C in transects with varying mangrove tree cover (F (2, 15) = 4.57, p = 0.028). The results for sediment stability comparing different stations along seven transects are shown in (Figure 9).

Effect of tree and pneumatophores density on sinking metal disks
The means for sinking metal disks of different stations were determined and results compared with tree density/ha and pneumatophores density per m 2 . The depth of metal disks decreased with increase in mangrove tree density ( Figure 10).
A plot of sinking metal disk against pneumatophores density per m 2 showed the similar treads with the one plotted against tree density/ha where the depth of metal disks decreased with increase in pneumatophores density per m 2 ( Figure 11).
Sediment accretion rates in six transects showed a net positive gain of 6.3±2.1mm (±SE). For 330 days. When extrapolated to annual rates, the transects showed values equal to a mean of-of 5.4±1.7mm (±SE). The mean range between the highest and the lowest accreting transect was 12.2mm recorded between transect M and transect O respectively. Mean sediment accretion rates were highest in transects K 13.3 ± 1.8mm (±SE), followed by transect M with 11.5 ±2.1 (mm ) (±SE). The lowest mean accretion rates were recorded in transect P with 1.4±1.2mm (±SE) and transect O with 1.1±2.8mm (±SE) within the same period. Sediment accretion rates as shown in (Figure 12).
Regression analysis between mean sediment accretion rates against forest structures showed no significant difference namely; tree density/ ha showed no significant (R 2 = 7.2%, p = 0.608), basal areas (R 2 = 8.9%, p = 0.566) and pneumatophores density/m 2 (R 2 = 11.1%, p= 0.415) In addition, regression analysis between sediment accretion and wave energy reduction along transects was also not significant (R 2 = 16.7, p = 0.489).  Figure 9. Mean values (± SE) of sinking depth of metal discs across station A, B, and C along the seven transects

Discussion
Provision of natural defenses by mangroves to both human being and artificial structures along the coast has in the recent past been given a lot of attention following the lessons learned during the 26 th December 2004 tsunami in Asia. Along the Kenya coast, many of the degraded mangroves sites has witnessed accelerated the rate of shoreline erosion prompting the government and local communities to put up artificial structures to mitigate the problem with little or no success. However, the restoration attempt guided by scientific findings have proved to provide a lasting and sustainable solution by restocking the degraded sites with suitable species. Increasing the mangrove tree densities has led to stability and functioning of the ecosystem by reducing shoreline erosion and binding of sediment by mangrove forest structures.

Effect of tree and pneumatophores density on wave energy
This study demonstrated that wave energy was gradually reduced along 80 m transects that had different tree and pneumatophore m densities. The data was obtained by comparing dissolution rates of percentage loss of clods card as a proxy to wave energy attenuation across the reforested mangrove forest. The energy reduction by tree stems alone was 7.8% while the energy reduction by pneumatophores was 5%. In total energy reduction by the two mangrove forest structures was 12.8%. Similar studies were done in Vinh Quang village along Red River (Song Hong) Vietnam showed that 100 m of intact mangrove attenuate wave energy up to 45% (Mazda et al. 1997). This study has proved that mangroves are suitable for coastal vegetation defense that can protect shoreline erosion against average wave energy.
The clod cards exposed to water current in the sea were used to express a loss of their weight as a function of water velocity since plaster of Paris objects erodes with the friction with water. The higher the water velocity, the higher the clod card weight loss. Therefore, it is interesting to compare the relationship between weight losses of the clod cards versus tree and pneumatophores density along transects of the known distance across the mangrove forest. Change in wave energy was plotted as the weight loss of clods (in the y-axis) versus transects with varying pneumatophores density and tree density (in the x-axis). The regression slope was the change in wave energy as tree and pneumatophores density varied among transects.
High wave energy was recorded at 15 cm above the substrate as demonstrated by high clod card weight loss at this height with a mean of 78.3 ± 2.3% (SE) compared to the means of clod cards mounted at 50 cm which recorded 73.4 ± 2.4 in transect that had mangrove trees. A similar power of high wave energy was experienced at 15 cm above the substrate in the control transect without mangrove cover registering a mean of 84.0 ±2.9% ) SE) while energy sampled at 50 cm was 81.2 ± 2.9% (SE). However, the capacity to reduce wave energy is known to depend on forest width, tree density and tree species (Alongi 2009). Mangrove reforestation initiatives at Gazi have seen an increase in tree density of fringing Sonneratia alba from diminishing levels to 448 ±212.3 (SD) at the time of the study. In this study, the site comprised of one species (Sonneratia alba), the semipristine nature of the forest stand coupled with narrow width limited the ability to reduce considerable wave energy contrary to Vinh Quang village along Red River (Song Hong) Vietnam with pristine fringing mangrove (Mazda et al. 1997). Figure 10. Mean of sinking depth of metal disks against; Tree density/ha across fringing mangrove forest Figure 11. Means of sinking depth of metal disks against pneumatophores density/m 2 across fringing mangrove forest Figure 12. Mean values ± SE of sediment accretion rate in study area observed for 330 days The effect of tree and pneumatophores density on wave energy reduction among different transects demonstrated that increasing tree density enhances the frictional drag by the mangrove forest structures. Pneumatophores of Sonneratia alba taper off upwards thus reducing their efficiency to maintain high drag force explaining the reason why more wave energy was experienced at 15 cm due to pneumatophores influence as compared to energy sampled at 50 cm due to mangrove tree density (Mazda et al. 1997).
Effect of tree and pneumatophores density on sediment stability and accretion Sinking depth of metal disks along transects with different tree densities demonstrated that sediment gains stability with increasing tree and pneumatophores density. The deeper the metal disks sunk in the sediment, the more the unstable the sediment was. Therefore, this study showed sinking depth of metal disk reducing gradually with distance from the open areas on the seaward side towards the shoreline as tree and pneumatophores densities varied among transects The trends in sediment stability demonstrated in this study is similar to those reported in mangroves along Cairns boardwalk in wet tropical Australia within a fringing Rhizophora sp. (Furukawa and Wolanski, 1996). The mechanisms of sediment transport in both sites are dominated by hydrodynamics from waves, and sediment gained stability with increasing distance from the seaward side towards the shore. The particles of sediment settled as wave energy reduced across the mangrove forest demonstrating the net effect of forest width and tree density on sediment stability as reported elsewhere in the world (Alongi 2009).
Where mangrove tree stems and pneumatophores densities were high, the depth of sinking of metal disks in the sediments was less due to reduced wave energy thus facilitating trapping and holding of sediment. The trapping mechanism resulted from high micro-turbulence created by the flows around the trees structures such as tree stems and pneumatophores (Wolanski 1995;Mazda et al. 1997) during flood tide and settled down at slake water when current flows are low during ebb tide.
The study showed station all A (before the mangroves) in all forested transect having the highest means of sinking depth of metal disks indicating high sediment instability which decreased with increasing distance across station B through station C. The observation witnessed in this study on sediment stability is accurate of studies done by Balke et al. (2013) who found sediment stability rates increasing with distance from the seaward side towards the shore. In the control transect without mangrove there was less microturbulence due to the absence of mangrove, trees thus making the sinking depths of metal disks to increase with distance along the intertidal complex an indication of high sediment instability.
The study has demonstrated that degradation of fringing mangrove forest alters sediment stability due to alteration in their physical roles a condition that has been witnessed elsewhere in the world (Furukawa and Wolanski, 1996). Graphical relationship of sinking depth of metal disks against tree and pneumatophores density showed the mean depth sinking metal disks decreasing with increasing tree stems/ha and pneumatophores density/m 2 highlighting that the replanted fringing forest remains the best option to stabilizing the highly eroded study site at Gazi Bay.
The levels of sinking depth of metal disks improved with reduced exposure to strong wave energy with mangrove forest structures offering a bio-shield by creating frictional drag as reported elsewhere (Furukawa and Wolanski, 1996). In this study, there was high wave energy observed from transect without mangrove cover (Control transect) and reduced gradually to reasonably high forested transect. Reduction of wave energy levels by mangrove forest structures (tree and pneumatophores density) improve sediment stability along the inter-tidal complex. Also, transects with high organic matter content and reasonably high levels of silt had a low sinking depth of metal disk an indication of improving sediment physiochemical characteristic (Macnae 1968) a condition that makes the mangrove forest a fully functional system .
The study showed sediment accretion rates of 5.4 ± 1.7 mm/year -1 (SE) which is more or less similar to that reported in Kosrae, (FSM) at Yale and Utwe river basin of 4.5 ±1.1 and 9.1 ± 2.1 (SE) mm respectively. Various levels of sediment accretion or subsidence due to the influence of mangrove forest structures such as tree and pneumatophores densities using sediment elevation tables (SETS) method has been reported in many studies around the world.
The stems and pneumatophores create frictional drag reducing current flow from wave energy thereby creating eddies that encourage sedimentation when cohesive particles flocculate mainly due to the presence of clay particles (Furukawa et al. 1997). Our study has shown that reforestation efforts in this site have boosted the regulatory services offered by mangroves by modifying physical characteristics of the sediment. The phenomena have been observed in transects M, K, and L which expressed the highest clay particles which bind sediment together thus supporting the sediment accretion. Transect with smallest clay particles as witnessed at transect O and which had the lowest tree and pneumatophores density expressed least mean accretion rates. Thereby, the study shows that by increasing tree stems through reforestation; sediment is less prone to resuspension by waves thus reducing shoreline erosion as compared to other earlier efforts of mitigating shoreline protection through the construction of gabions.

Conclusion
Through the use of inexpensive clod card dissolution method to quantify wave energy attenuation as a regulatory service, this study has established baseline data to help monitor and quantitatively estimate the role of mangrove forests in shoreline protection, and how this change with tree density. Evidence of the study site regaining stability after replanting mangroves is a more sustainable and costeffective method as compared to putting up hard engineering structures. The approach can easily be replicated elsewhere in many such sites along the Kenyan coast and western Indian Ocean region. Mangroves are potentially used as a bio-shield that shall provide other ecosystem benefits such as increased biodiversity, aesthetic beauty and will have potential application in disaster risk reduction in the long term. At the study site in Gazi Bay, mangroves proved to reduce on average 7.8% of wave energy in transects with trees compared to open areas without trees whereas sediment stability correlated positively with an increase in tree and pneumatophores density as wave energy reduces. Stable sediments have shown accretion rates improve as the density of the forest increases over time through reforestation efforts and the shoreline erosion gradually decreases and resist further coastline changes. The primary challenge in the study was lack of baseline data and other comparative studies on the use of mangrove forests as bio-shields to provide coastal protection against average wave energy impacts along the Kenya coast and Western Indian Ocean region.