International Journal of Applied Environmental Sciences ISSN 0973-6077 Volume 11, Number 1 (2016), pp. 279-293 © Research India Publications http://www.ripublication.com

Dynamic Linkages of Mangrove Rhizophora Mucronata and its Environment Parameters in Semarang and Demak Coastal Area

Endah Dwi Hastuti1*, Sutrisno Anggoro2 and Rudhi Pribadi3

1Department of Biology, Faculty of Scince and Mathematics, Diponegoro University, Jl. Prof. Soedharto, SH, Semarang, Central Java, Indonesia. E-mail: [email protected]

2Department of Fisheries, Faculty of Fisheries and Marine Science, Diponegoro University, Jl. Prof. Soedharto, SH, Semarang, Central Java, Indonesia.

3Department of Marine Science, Faculty of Fisheries and Marine Science, Diponegoro University, Jl. Prof. Soedharto, SH, Semarang, Central Java, Indonesia.

Abstract

Mangrove is the most dynamic ecosystem existed in coastal area which is effected by land and marine dynamic. There had been studies relating the effect of environment parameters to mangrove development and effect of mangrove abundance to environment parameters. But, the dynamic linkage of mangrove structure and environment parameters had never been revealed. This research aimed to study the dynamic vice versa linkage of mangrove structure of Rhizophora mucronata and the environment parameters in Semarang and Demak coastal area. Research was conducted through field observation and laboratory analysis. Observation was conducted through transect plotted in Semarang and Demak region where 4 observation station was occupied with 3 transect on each station. Dynamic linkage was analyzed through modeling occupied Powersim as the analysis tool. The result showed there were vice versa linkage of mangrove structure and environment parameters. The effect of environment parameters to mangrove dynamic including to growth rate and mortality rate of mangrove sapling and seedling, and reproduction rate of mangrove tree. While the effect of mangrove structure on environment parameters including temperature, TSS, salinity, pH, DO, organic matter, soil N, soil P, dissolved N, dissolved P and dissolved K. The development of dynamic model was also consider the effect of mangrove abundance which create limit on mangrove growth and reduce the reproduction rate and growth rate of mangrove. Further study concerning dynamic model of mangrove 280 Endah Dwi Hastuti et al

development should be conducted to investigate the potential of mangrove and environment parameters change.

Keywords: Mangrove, Structure, Parameters, Dynamic, Model

Introduction Coastal area including mangrove ecosystem are the most dynamic area compared to marine and land ecosystem. Mangrove vegetations lived in unique habitat where marine and land activities were met and create a highly dynamic condition. The condition of the habitat changed by the effect of marine and land dynamic. According to [1], intertidal environment including hydrological and geomorphological condition define the structural variation of mangrove ecosystem.Inundation by salt water is the main character of mangrove ecosystem [2]. Mangrove ecosystems are under great pressure of population and development activities [3]. A research conducted by [4] noted that human activities including urban expansion, landuse conversion was the main cause of mangrove decline. While [5] mentioned that sea level rise also caused mangrove decrease. Sea level rise caused sediment elevation to be lowered. Hence, inundated area of mangrove ecosystem increased which caused disturbance on mangrove vegetations. Variability of mangrove ecosystem is defined by water mass dynamic from marine and land. According to [6], hydrographic, nutrient distribution and water biomass of mangrove ecosystem were influenced by freshwater input from rivers and marine water input from wave and tide. Hence, the distribution of salinity and nutrient are dynamically change. The growth of mangrove vegetation such as Rhizophora mucronata is affected by the condition of environment parameters. The condition of environment variables simultaneously effect the growth rate of the vegetation as well as its reproduction. According to [7], the habitat of R. mucronata were characterized with low soil salinity, silt and pH value. Rhizophora mucronata is salinity tolerance species though its less tolerance than Avicennia marina[8]. A research conducted by [9] considered that the growth of Rhizophora mucronata was limited as the seawater concentration raised above 50%. According to [10], there were correlation between mangrove species richness and ecosystem function. Variation in the stages of plants effects manifest themselves.The growth of mangrove vegetation differs among ages. According to [11], growth of young stages mangrove inhibition were observed within 2 m circular distance, while old stages (after 20 years) inhibitin were observed within 3 m circular distance. It showed that mangrove growth would increase competition among vegetations. Hence, mangrove abundance would dynamically change as well as the community structure. Unfortunately, the condition of coastal environment is dynamically change. Marine and land dynamic are the main factors affecting the change of coastal environment. As well as the marine and land dynamic, the mangrove vegetation itself are growing which lead to the change on the condition of the ecosystem. Hence, physical, chemical and biological parameters change by time. This caused to inter ecosystem Dynamic Linkages of Mangrove Rhizophora Mucronata and its Environment 281 dynamic. A research conducted by [12] showed that the decrease of sediment pH would decrease the growth of R. mucronata. Further effect of mangrove growth is colonization provided from reproduction processes [13]. Most mangrove mortality was caused by environment stresses. In some regions, mangrove recruitment do not suffice to balance the mortality rate [14]. According to [15], reproduction of mangrove were generated from mangrove tree. According to [2], to understand the response of mangrove ecosystem, further concern on the environment condition within mangrove ecosystem is needed. Dynamic model estimating further development of mangrove ecosystem could be arranged by considering dynamic reciprocal relation of mangrove structure and environment variables. This research aimed to observe and build the simultaneus and continuous dynamic relation of mangrove structure and environment variables.

Materials and Method This research was conducted in Semarang and Demak coastal area where mangrove ecosystem existed. Both locations had the same sediment characteristics since both locations are in the same sediment cell. The observation was conducted in 2009, including 8 observation stations and 24 observation transects. Observation was conducted to mangrove structure and environment parameters. Observation of mangrove structure was including mangrove specieses, abundance and basal area of each mangrove stages (tree, sapling and seedling). Observation was differed by mangrove stages, where tree stage utilized 10 x 10 m2 of transect size, while sapling stage utilized 5 x 5 m2 of transect size and 1 x 1 m2 of transect size for seedling stage. Transects for lower mangrove stages of mangrove was placed within the transects of higher mangrove stages. While observation of environment parameters was conducted within the transect as well. Environment parameters including physical (soil texture, TSS, temperature) and chemical (salinity, dissolved oxygen, pH, concentration of organic matters, sediment N & P concentration, dissolved N, P & K concentration). While biological parameters including abundance, relative abundance, dominance, relative dominance, importance index of vegetation, heterogeneity index and evenness index of mangrove vegetations. To analyze the development of mangrove structure, a model was developed. To understand the dynamic reciprocal relation of mangrove structure and environment parameters, the effect of each mangrove structure to environment parameters vice versa should be understood. Regression analysis correlating mangrove structure and environmnet parameters was conducted as initial analysis and to provide the basic numeric relation of reciprocal model. The analysis including linear, logarithmic and polynomial regression models were conducted to achieve the best model fit. The result of regression analysis was filtered to provide a suitable model. Filtering was conducted through determination index and / or probability index. Corelation between each mangrove structure and environmnet parameters which have determination index ≥ 50% or probability index ≤ 0,1 was utilized for model development. Model development was conducted with Powersim Studio 2005.

282 Endah Dwi Hastuti et al

Result The result showed significant vice versa relations of mangrove structure of Rhizophora mucronata and environment parameters. The effect of the environment parameters including to the growth rate and mortality rate of Rhizophora mucronata seedling and sapling and reproduction rate of Rhizophora mucronata tree. The effect of environment parameters on the growth rate of Rhizophora mucronata sapling and seedling achieved from regression analysis are shown in Table 1 and Table 2. Table 1 showed that growth rate of Rhizophora mucronata sapling was effected by temperature, pH, organic matter, soil N, silt and clay. While growth rate of Rhizophora mucronata seedling was effected by temperature, organic matter, soil N and soil P. Based on the regression result showed in Table 1 and Table 2, a model was developed to the linked variables as shown in Figure 1.

The environment parameters also effect the reproduction rate of Rhizophora mucronata tree. The regression analysis result is shown in Table 3. The growth rate of Rhizophora mucronata was effected by salinity, DO, organic matter, soil P, dissolved N and dissolved K. Figure 2 showed the linkage model of environment parameters and reproduction rate of Rhizophora mucronata.

Instead of effecting the growth rate of sapling and seedling, and reproduction rate of tree, environment parameters also effect the mortality rate of sapling and seedling of Rhizophora mucronata as well. The effect of environment parameters to mortality of Rhizophora mucronata sapling and seedling was achieved from regression analysis as shown in Table 4 and Table 5.

Table 4 showed that mortality rate of Rhizophora mucronata sapling was effected by temperature, soil N, dissolved N and silt. While mortality rate of Rhizophora mucronata seedling was effected by temperature, salinity, pH, DO, organic matter, soil N, soil P, dissolved N and dissolved K. Linkage model of environment parameters and mortality rate of Rhizophora mucronata sapling and seedling is shown in Figure 3.

Vice versa relation of environment parameters and mangrove structure of Rhizophora mucronata was shown by the effect of Rhizophora mucronata abundance to the environment parameters dynamic. Table 6-Table 8 showed the effect of mangrove abundance of Rhizophora mucronata tree, sapling and seedling to the environment parameters.

Table 6 showed that tree abundance of Rhizophora mucronata effected the environment parameters such as TSS, salinity, organic matter, soil P, dissolved N, dissolved K and clay.

Table 7 showed the effect of Rhizophora mucronata sapling abundance on the environment parameters including temperature, TSS and pH.

Dynamic Linkages of Mangrove Rhizophora Mucronata and its Environment 283

Table 8 showed the effect of Rhizophora mucronata seedling on the environment parameters including DO, soil P, dissolved N and dissolved K.

Instead of mangrove abundance, environment parameters within mangrove ecosystem was also effected by mangrove mortality, including sapling and seedling mortality. The effect of mangrove mortality of Rhizophora mucronata sapling and seedling is shown in Table 9 and Table 10.

Table 9 showed that environment parameters effected by sapling mortality of Rhizophora mucronata sapling was including temperature, TSS, salinity, BO, soil N, soil P, dissolved N, sand and silt.

Table 10 showed the effect of Rhizophora mucronata seedling mortality on the environment parameters including to organic matter, soil P, dissolved N and dissolved K. Mangrove abundance and mortality simultaneously effect the dynamic of environment parameters. Dynamic model was developed to show the link of mangrove structure and the environment parameters as shown in Figure 4.

Instead of being effected by environment parameters, mangrove abundance was also limited by its own abundance and basal area. Mangrove abundance and its limitation effect dynamic model is shown in Figure 5.

Table 1: Effect of Environment Parameters on the Growth Rate of Rhizophora mucronata Sapling

No. Effecting Parameter Equation P R2 1. Temperature Y = 28,879-2,012 X + 0,035 X2 0,108 0,671 2. pH Y = 47,419-14,681 X + 1,136 X2 0,052 0,773 3. Organic Matter Y = 1,146-0,401.ln(X) 0,103 0,443 4. Soil N Y = 0,701-3,881 X + 5,222 X2 0,002 0,961 5. Silt Y = 0,223-0,048.ln(X) 0,07 0,514

Table 2: Effect of Environment Parameters on the Growth Rate of Rhizophora mucronata Seedling

No. Effecting Parameter Equation P R2 1. Temperature Y = 0,823-0,241.ln(X) 0,292 0,351 2. Organic Matter Y =-1,040 + 0,138X-4,406e-3 X2 0,503 0,497 3. Soil N Y =-0,034-0,051.ln(X) 0,293 0,351 4. Soil P Y = 7,853e-3-2,438e-4 X + 1,605e-6 X2 0,195 0,805

284 Endah Dwi Hastuti et al

Table 3: Effect of Environment Parameters on the Reproduction Rate of Rhizophora mucronata

No. Effecting Parameter Equation P R2 1. Salinity Y = 172,572-50,718.ln(X) 0,179 0,505 2. DO Y =-7,153 + 4,601 X-0,534 X2 0,365 0,635 3. Organic Matter Y = 73,668-9,590 X + 0,312 X2 0,100 0,900 4. Soil P Y = 0,458 + 2,270e-2 X-9,409e-5 X2 0,592 0,408 5. Dissolved N Y = 5,716-3,682 X + 0,582 X2 0,408 0,592 6. Dissolved K Y = 2,182-8,668e-3 X + 7,143e-6 X2 0,049 0,951

Table 4: Effect of Environment Parameters on the Mortality Rate of Rhizophora mucronata Sapling

No. Effecting Parameter Equation P R2 1. Temperature Y = 50,740-3,457 X + 0,059 X2 0,079 0,719 2. Soil N Y = 1,652-7,137 X + 7,952 X2 0,169 0,589 3. Dissolved N Y =-0,216 + 0,387 X-0,082 X2 0,1 0,684

Table 5: Effect of Environment Parameters on the Mortality Rate of Rhizophora mucronata Seedling

No. Effecting Parameter Equation P R2 1. Temperature Y =-15,178 + 4,629.ln(X) 0,115 0,618 2. Salinity Y = 69,067-20,331.ln(X) 0,028 0,844 3. pH Y =-19,095 + 10,295.ln(X) 0,262 0,388 4. DO Y =-2,404 + 1,432 X-0,156 X2 0,133 0,867 5. Organic Matter Y = 5,048-1,742.ln(X) 0,197 0,477 6. Soil N Y = 1,307 + 0,977.ln(X) 0,123 0,602 7. Soil P Y = 0,511 + 8,960e-4 X-1,127e-5 X2 0,598 0,402 8. Dissolved N Y = 2,218-1,652 X + 0,293 X2 0,201 0,799 9. Dissolved K Y = 5,805e-2 + 6,289e-4 X 0,061 0,742

Table 6: Effect of Rhizophora mucronata Tree Abundance on the Environment Parameters

No. Effected Parameter Equation P R2 1. TSS Y = 463,465 + 0,065X 0,072 0,2 2. Salinity Y = 20,890 + 1,010.ln(X) 0,108 0,163 3. Organic Matter Y = 31,935-2,280.ln(X) 0,011 0,357 4. Soil P Y = 290,300-0,057 X 0,085 0,185 5. Dissolved N Y = 4,012-5,817e-4 X 0,079 0,192 6. Dissolved K Y = 459,828-0,269 X + 9,093e-5 X2 0,001 0,642

Dynamic Linkages of Mangrove Rhizophora Mucronata and its Environment 285

Table 7: Effect of Rhizophora mucronata Sapling Abundance on the Environment Parameters

No. Effected Parameter Equation P R2 1. Temperature Y = 29,996-1,430e-4.ln(X) 0,039 0,288 2. TSS Y = 696,263-2,676e-2 X + 2,316e-6 X2 0,016 0,5 3. pH Y = 5,437 + 0,125.ln(X) 0,088 0,207

Table 8: Effect of Rhizophora mucronata Seedling Abundance on the Environment Parameters

No. Effected Parameter Equation P R2 1. DO Y = 2,517 + 7,940e-6 X 0,078 0,22 2. Soil P Y = 667,971-49,474.ln(X) 0,068 0,234 3. Dissolved N Y = 2,736-9,809e-9 X + 1,364e-11 X2 0,084 0,338 4. Dissolved K Y = 216,176 + 5,889e-3 X-7,608e-9 X2 0,003 0,618

Table 9: Effect of Rhizophora mucronata Sapling Mortality on the Environment Parameters

No. Effected Parameter Equation P R2 1. Temperature Y = 30,336-1,986e-3 X + 2,369e-7 X2 0,009 0,607 2. TSS Y = 688,266-4,664e-2 X + 2,153e-5 X2 0,009 0,607 3. Salinity Y = 28,611 + 0,133.ln(X) 0,093 0,235 4. Organic Matter Y = 13,187 + 3,056e-3 X-4,306e-7 X2 0,099 0,371 5. Soil N Y = 0,583-0,034.ln(X) 0,05 0,306 6. Soil P Y =-81,472 + 30,761.ln(X) 0,002 0,612 7. Dissolved N Y = 3,089-0,227.ln(X) 0,05 0,306

Table 10: Effect of Rhizophora mucronata Seedling Mortality on the Environment Parameters

No. Effected Parameter Equation P R2 1. Organic Matter Y = 15,165-2,706e-5 X + 4,930e-11 X2 0,092 0,411 2. Soil P Y = 423,947-33,028.ln(X) 0,046 0,342 3. Dissolved N Y = 2,389-1,015e-5X + 1,679e-11 X2 0,14 0,354 4. Dissolved K Y = 244,130 + 1,005e-2 X-1,849e-8 X2 0,002 0,739

286 Endah Dwi Hastuti et al

P tnh_gr_se_rhi suhu_du lpg_du

%_lanau pH lanau_du %_lempung

lnau_gr_pa_rhi

du_lanau du_BO du_lpg suhu_gr_se_rhi en_gr_pa_rhi pH_gr_pa_rhi en_gr_se_rhi lpg_gr_pa_rhi

suhu_gr_pa_rhi N_tnh_gr_se_rhi BO_gr_pa_rhi BO_du du_suhu

DO_gr_pa_rhi N_tnh_gr_pa_rhi BO_gr_se_rhi

suhu_du BO N_tnh_du DO_du

N_tnh_du suhu du_DO DO du_N_tnh N tnh

Figure 1: Dynamic Effect of Environment Parameters on the Growth Rate of Mangrove Rhizophora mucronata

du_K air K air_re_rhi sal_du

K air

K air_du

DO du_sal

DO_du en_re_rhi sal_re_rhi DO_re_rhi sal du_DO

du_N air BO_re_rhi

N air_du N air_re_rhi N air BO_du

du_BO P tnh_re_rhi P_tnh_du

BO P tnh du_P_tnh

Figure 2: Dynamic Effect of Environment Parameters on the Reproduction Rate of Mangrove Rhizophora mucronata Dynamic Linkages of Mangrove Rhizophora Mucronata and its Environment 287

du_lpg suhu N air_du suhu_du N air_mo_pa_rhi du_P_tnh du_suhu N air_mo_se_rhi lpg_mo_pa_rhi

pH suhu_mo_se_rhi N_tnh_du P tnh lpg_du

P_tnh_du pH_mo_se_rhi en_mo_pa_rhi BO %_lempung N tnh_mo_se_rhi en_mo_se_rhi P tnh_mo_se_rhi sal_du du_BO BO_du N tnh N tnh_mo_pa_rhi BO_mo_se_rhi sal_mo_se_rhi du_K air du_N_tnh

K air_du K air_mo_se_rhi N_tnh_du du_sal sal K air

Figure 3: Dynamic Effect of Environment Parameters on the Mortality Rate of Mangrove Rhizophora mucronata

mo_pa_rhi_du mo_pa_rhi_Ntnh_o u du_pa_rhi N_tnh_du pa_rhi P_tnh_du se_rhi du_se_rhi

du_suhu po_avi_Ntnh_ou pa_rhi_pH

N_tnh_pH mo_pa_rhi_Ntnh_in P_tnh_pH pa_rhi_du

suhu_du se_rhi_du N tnh N_tnh_in N_tnh_out pa_rhi_pasir_in pH

se_rhi_DO pa_rhi_TSS suhu_DO N_tnh_du mo_pa_rhi_TSS suhu pH_DO mo_pa_rhi_du TSS po_rhi DO du_mo_pa_rhi BO_du

po_rhi_Kair sal pa_rhi pa_rhi_suhu mo_pa_rhi mo_pa_rhi_suhu mo_pa_rhi_du du_N_tnh

BO_Kair po_rhi_TSS po_rhi_sal

du_po_rhi mo_pa_rhi_Ptnh_ou mo-se_rhi_Kair K_air

po_rhi_du se_rhi_Kair po_rhi_Ptnh_ou pa_rhi_du

po_rhi_Nair mo_pa_rhi_Ptnh_in se_rhi_du po_rhi_BO_ou

po_rhi_bo_in N_air P tnh BO P_tnh_in P_tnh_out mo_se_rhi_du BO_in BO_out

se_rhi se_rhi_Nair mo_pa_rhi_BO_ou mo_se_rhi_Nair du_BO mo_se_rhi_BO_in P_tnh_du BO_du

mo_se_rhi mo_pa_rhi_BO_in mo_pa_rhi_du du_P_tnh mo_se_rhi_BO_ou mo_se_rhi_du du_mo_se_rhi

Figure 4: Dynamic Effect of Mangrove Rhizophora mucronata Structure on the Environment Parameters

288 Endah Dwi Hastuti et al

max_ba_po veg_lim_re_avi d_po_mo_po_rhi max_po d_ba_po co_ba_po_rhi_ex

en_re_rhi re_po_rhi d_po mo_po_rhi init_re_rhi

po_rhi co_ba_se_rhi re_rhi exp_po_rhi max_se d_ba_se co_ba_po_rhi co_ba_se_rhi_ex

init_gr_pa_rhi max_ba_real ba_po_rhi d_se d_po

max_po co_ba_po_rhi_ex ex_ba_se_rhi en_gr_pa_rhi d_ba ba_se_rhi d_ba_se ex_ba_po_rhi d_se_mo_se_rhi

gr_pa_rhi ba_tot d_ba_se d_po_gr_pa_rhi max_ba_se se_rhi d_ba_po f_gr_pa_rhi max_ba_po d_ba_po max_ba_pa max_ba_se fa_mo_se_rhi ex_ba_pa_rhi max_se lmt_gr_pa_rhi co_ba_pa_rhi ba_pa_rhi co_ba_pa_rhi_ex d_ba_pa mo_se_rhi lmt_mo_pa_rhi

pa_rhi d_po en_mo_se_rhi gr_se_rhi

lmt_mo_se_rhi

mo_pa_rhi d_pa_mo_po_rhi d_pa init_mo_se_rhi fa_gr_se_rhi

f_mo_pa_rhi max_po d_se_gr_pa_rhi init_gr_se_rhi d_pa_mo_pa_rhi max_pa

en_gr_se_rhi init_mo_pa_rhi max_ba_po d_ba_po en_mo_pa_rhi max_ba_pa d_ba_pa

Figure 5: Dynamic Model of Mangrove Structure of Rhizophora mucronata

Discussion The result above showed the dynamic vice versa effect of mangrove structure of Rhizophora mucronata and environment parameters. Growth of Rhizophora mucronata at sapling and seedling stages are significantly effected by temperature, organic matter and soil N. Higher temperature provide better growth rate on sapling growth rate, while on seedling growth rate it provide inhibition. According to [16], high temperature lead to photo inhibition and heat temperature damage of photosynthetic organ. The effect of organic matter to the growth rate of mangrove sapling and seedling was negative, which means that the growth rate of mangrove sapling and seedling would be decreased as the organic matter concentration raised. According to [17], accumulation of organic matter in mangrove ecosystem caused to the increase of soil volume and sediment elevation. Hence, the function of mangrove root is limited. The abundance of soil N concentration was the effect of high decomposition rate of organic matter in mangrove ecosystem. Soil N is the source of nutrient for mangrove vegetations where the abundance of soil N support growth rate of mangrove Dynamic Linkages of Mangrove Rhizophora Mucronata and its Environment 289 vegetation [18]. Even though the N is one of nutrient which is needed by mangrove vegetation, concentration of N can also be a limiting factor for mangrove growth rate. As well as soil N, growth rate of mangrove seedling was also effected by soil P. Both are essential nutrients for mangrove growth, especially at seedling stages. Soil structure had significant effect on growth rate of mangrove sapling. According to [7], soil structure define the distribution pattern of mangrove species. It means that the growth of mangrove species is effected by soil structure. Sediment composition including sand, silt and clay devine the soil structure. Among the three sediment fraction, silt and clay have significant effect on the growth rate of Rhizophora mucronata. Both fraction has negative effect on the growth rate, which means that more composition of both fraction would lead to decrease of growth rate. The reproduction rate of Rhizophora mucronata was significantly effected by salinity, DO, organic matter, soil P, dissolved N and dissolved K. Salinity is the most important parameter for mangrove. Mangrove had been well known to be tollerant to salinity stress. According to [15], Avicennia marina and Rhizophora mucronata were mangrove specieses with better salinity tollerance than any other specieses. Nutrient has essential value in mangrove reproduction. Mangrove seed require adequate nutrient to support its survival and growth. A research conducted by [19] noted that seedling survival and growth was effected by light, nutrient, sulfide and elevation. Even though nutrient availability become a limiting factor of mangrove reproduction, mangrove vegetation has adaptation pattern as its response to nutrient limit [20]. Mortality rate of mangrove sapling and seedling was effected by temperature, soil N, dissolved N. According to [21], temperature varies greatly within the forest. Mangrove ecosystem may encounter high or low temperature. High temperature in the mangrove ecosystem tend to increase mortality rate of mangrove vegetaion. This should be a major thread to mangrove ecosystem since the atmosphere had encounter global warming which lead to the increase of temperature raising in the atmosphere. Soil nutrient showed positive effect on mangrove mortality at sapling and seedling stages. This means that nutrient enrichment lead to higher mortality rate of mangrove. According to [22] mortality of mangrove by nutrient enrichment occured on addition of N fertilizer while the rainfall was low. This lead to lower productivity and enhance mortality of mangrove. This match with the result of the research which mortality rate increased by soil N enrichment. The effect of salinity on the mortality rate of mangrove seedling showed negative value which means the increasing salinity would lower the mortality rate of Rhizophora mucronata seedling. According to [23], Rhizophora mucronata responded high salinity stress by decreasing stomatal conductance rate. According to [24], Rhizophora mucronata is mangrove species with high salinity tollerance instead of Avicennia marina. Effect of mangrove abundance including to temperature, TSS, salinity, pH, DO, organic matter, soil P, dissolved N, dissolved K and clay. Mangrove abundance increase the absorbtion of ambient temperature which lead to temperature decrease [25]. TSS increase as the increase of mangrove abundance since mangrove root

290 Endah Dwi Hastuti et al system create barrier for water current. Hence, water flowed slower and TSS concentration increase [26]. The increase of pH was caused by decomposition rate of mangrove litters [27], hence organic acid was produced and define the pH. As the abundance of mangrove increase, photosynthetic processes increased as well and produce more oxygen [28]. Effect of mangrove abundance to nutrient balance was caused by mangrove productivity resulted from litter decomposition. But, in certain case, mangrove also utilize nutrient for its growth. A research conducted by [29] showed that the dynamic of soil P concentration significantly affected by litter production and absorbtion by mangrove vegetation. Instead of mangrove abundance, mangrove mortality also had significant effect on the environment parameters. Environment parameters affected by mangrove mortality, including sapling and seedling stages were: temperature, TSS, salinity, BO, soil N, soil P, dissolved N, dissolved K. Those parameters were affected since there were changes in mangrove abundance. The dynamic linkage model resulted from this research should provide information concerning further development of mangrove ecosystem. Such research concerning ecosystem dynamic within mangrove forest had been conducted in several research such as [30] and [31]. A research conducted by [30], showed the ecological interaction model in the mangrove estuaries related to global warming effect such as sea level rise and reduced freshwater flow. While [31] showed the dynamic interaction of sedimentation and mangrove seedling. A research conducted by [14] showed dynamic development of mangrove seedling in certain abundance. According to [11], the competition within mangrove ecosystem by mangrove development. Further information is needed to study the potential development and stress of mangrove ecosystem. This study provide early information concerning dynamic lingkage model of Rhizophora mucronata development in Semarang and Demak area. Further studies are needed to understand the environment and mangrove dynamic response to related development of mangrove ecosystem.

Conclusion Mangrove ecosystem in Semarang and Demak is dynamically linked and has vice versa effect which lead to dynamic development of mangrove growth and environment parameters. Instead of the effect of environment parameters, mangrove development was also effected by abundance limit which lead to inhibition of growth rate. Increasing abundance created competition among vegetations.

References

[1] Feller, I. C., Lovelock, C. E., Berger, U., McKee, K. L., Joye, S. B., and Ball, M.C., 2010, “Biocomplexity in Mangrove Ecosystem,” Annu. Rev. Mar. Sci., 2, pp. 395-417. Dynamic Linkages of Mangrove Rhizophora Mucronata and its Environment 291

[2] Robert, E., Schmitz, N., Kirauni, H. A., and Koedam, N., 2010, “Salinity Fluctuations in Mangrove Forest of Gazy Bay, Kenya: Lessons for Future Research,” Nature & Faune, 24(1), pp. 89-95. [3] Shazra, A., Rasheed, S., and Ansari, A. A., 2008, “Study on the Mangrove Ecosystem in Maldives,” Global Journal of Environmental Research, 2(2), pp. 84-86. [4] Martinuzzi, S., Gould, W. A., Lugo, A. E., and Medina, E., 2009, “Conversion and Recovery of Puerto Rican Mangroves: 200 Years of Change,” Forest Ecology and Management 257, pp. 75-84. [5] Gilman, E. L., Ellison, J., Duke, N. C., and Field, C., 2008, “Threats to Mangroves from Climate Change and Adaptation Options: A Review,” Aquatic Botany, 89, pp. 237-250. [6] Sylaios, G., Koutrakis, E., and Kallianiotis, A., 2006, “Hydrographic Variability, Nutrient Distribution and Water Mass Dynamics in Strymonikos Gulf (Northern Greece),” Continental Shelf Research, 26, pp. 217-235. [7] Ahmed, E. A., and Abdel-Hamid, K. A., 2007, “Zonation Pattern of Avicennia marina and Rhizophora mucronata Along the Red Sea Coast, Egypt,” World Applied Sciences Journal, 2(4), pp. 283-288. [8] Jayatissa, L. P., Wickramasinghe, W. A. A. D. L., Dahdouh-Guebas, F., and Huxham, M., 2008, “Interspecific Variations in Responses of Mangrove Seedlings to Two Contrasting Salinities,” Internat. Rev. Hydrobiol., 93(6), pp. 700-710. [9] Aziz, I., and Khan, M. A., 2001, “Effect of Seawater on the Growth, Ion Content and Water Potential of Rhizophora mucronata Lam.” J. Plant Res., 114, pp. 369-373. [10] Kirui, B. Y. K., Kairo, J. G., Skov, M. W., Mencuccini, M., and Huxham, M., 2012, “Effects of Species Richness, Identity and Environmental Variables on Growth in Planted Mangroves in Kenya,” Mar. Ecol. Prog. Ser., 465, pp. 1-10. doi: 10.3354/meps09999 [11] Khan, M. N. I., Sharma, S., Berger, U., Koedam, N., Dahdouh-Guebas, F., and Hagihara, A., 2013, “How Do Tree Competition and Stand Dynamics Lead to Spatial Patterns in Monospecific Mangroves?” Biogeosciences, 10, pp. 2803-2814. doi:10.5194/bg-10-2803-2013 [12] Rajkaran, A., and Adams, J., 2012, “The Effects of Environmental Variables on Mortality and Growth of Mangroves at Mngazana Estuary, Eastern Cape, South Africa,” Journal of Wetlands Ecology and Management, 20(4), pp. 297-312. DOI:10.1007/s11273-012-9254-6 [13] Bosire, J. O., Dahdouh-Guebas, F., Kairo, J. G., and Koedam, N., 2003, “Colonization of Non-Planted Mangrove Species into Restored Mangrove Stands in Gazy Bay, Kenya,” Aquatic Botany, 76, pp. 267-279. [14] Ha, H. T., Duarte, C. M., Tri, N. H., Terrados, J., and Borum, J., 2003, “Growth and Population Dynamics During Early Stages of the Mangrove Kandelia candel in Halong Bay, North Viet Nam,” Estuarine, Coastal and Shelf Science, 58, pp. 435-444.

292 Endah Dwi Hastuti et al

[15] Ghosh, A., and Chakraborti, P., 2011, “Evaluation of Some Mangrove Species on the Nature of Their Reproduction Along the Coastal Belt of the Indian Sunderbans,” Journal of Threatened Taxa, 4(3), pp. 2427-2435. [16] Medina, E., 1999, “Mangrove Physiology: the Challenge of Salt, Heat, and Light Stress Under Recurrent Flooding,” Ecosistemas de Manglar en América Tropical, Yáñez-Arancibia, A., and Lara-Domínguez, A. L., eds., Instituto de Ecología A.C. México, UICN/ORMA, Costa Rica, NOAA/NMFS Silver Spring MD USA., pp. 109-126. [17] Cahoon, D. R., Hensel, P. F., Spencer, T., Reed, D. J., McKee, K. L., and Saintilan, N., 2006, “Coastal Wetland Vulnerability to Relative Sea-Level Rise: Wetland Elevation Trends and Process Controls. In: Verhoeven JTA, Beltman B, Bobbink R, Whigham D (Eds.), Wetlands and Natural Resource Management,” Ecological Studies, 190. Springer-Verlag, Berlin/Heidelberg, pp. 271-292. [18] Romero, I. C., Jacobson, M., Fuhrman, J. A., Fogel, M., and Capone, D. G., 2012, “Long-Term Nitrogen and Phosphorus Fertilization Effects on N2 Fixation Rates and nifH Gene Community Patterns in Mangrove Sediments,” Marine Ecology, 33, pp. 117-127. doi:10.1111/j.1439- 0485.2011.00465.x [19] Profitt, C. E., Milbrandt, E. C., and Travis, S. E., 2006, “Red Mangrove (Rhizophora mangle) Reproduction and Seedling Colonization After Hurricane Charley: Comparisons of Charlotte Harbor and Tampa Bay,” Estuaries and Coasts, 29(6A), pp. 972-978. [20] Lin, Y. M., Liu, X. W., Zhang, H., Fan, H. Q., and Lin, G. H., 2009, “Nutrient Conservation Strategies of A Mangrove Species Rhyzophora stylosa Under Nutrient Limitation,” Plant Soil, 326(1), pp. 469-479. DOI 10.1007/s11104-009-0026-x [21] Krauss, K. W., Lovelock, C. E., McKee, K. L., Lopez-Hoffman, L., Ewe, S. M. L., and Sousa, W. P., 2008, “Environmental Drivers in Mangrove Establishment and Early Development: A Review,” Aquatic Botany, 89, pp. 105-127. [22] Lovelock, C. E., Ball, M. C., Martin, K. C., and Feller, I. C., 2009, “Nutrient Enrichment Increases Mortality of Mangroves,” PloS ONE, 4(5), e5600. doi:10.1371/journal.pone.0005600 [23] Biber, P. D., 2006, “Measuring the Effects of Salinity Stress in the Red Mangrove, Rhizophora mangle L,” African Journal of Agricultural Research, 1(1), pp. 1-4. [24] Perera, K. A. R. S., Amarasinghe, M. D., and Somaratna, S., 2013, “Vegetation Structure and Species Distribution of Mangrove Along A Soil Salinity Gradient in Micro Tidal Estuary on the North-Western Coast of Sri Lanka,” American Journal of Marine Science, 1(1), pp. 7-15. doi:10.12691/marine-1-1-2 [25] Hadikusumah, 2007, “Monsoonal Variability of Temperature and Salinity in Jakarta Bay,” Lingkungan Tropis-Edisi Khusus (8), pp. 33-41. Dynamic Linkages of Mangrove Rhizophora Mucronata and its Environment 293

[26] Furukawa, K., and Eric, W., 1996, “Sedimentation in Mangrove Forest,” Mangrove and Salt Marshes, 1 (1), pp. 3-10. [27] Lawson, E. O., 2011, “Physico-Chemical Parameters and Heavy Metal Contents of Water from the Mangrove Swamps of Lagos Lagoon, Lagos, Nigeria,” Advances in Biological Research, 5 (1), pp. 08-21. [28] Kennedy, C. S., Twilley, R. R., Kleypas, J. A., Cowan, J. H., and Hare, S. R., 2002, Coastal and Marine Ecosystems & Global Climate Change, Pew Center on Global Climate Change. [29] Nielsen, E. M., and Andersen, M. T., 2003, “Detection and Characterization of Verocytotoxin-Producing Escherichia coli by Automated 59 Nuclease PCR Assay,” J. Clin. Microbiol., 41, pp. 2884-2893. [30] Davis, S. M., Childers, D. L., Lorenz, J. J., Wanless, H. R., and Hopkins, T. E., 2005, “A Conceptual Model of Ecological Interactions in the Mangrove Estuaries of the Florida Everglades” WETLANDS, 25(4), pp. 832-842. [31] Balke, T., Webb, E. L., Elzen, E., Galli, D., Herman, P. M. J., and Bouma, T. J., 2013, “Seedling Establishment in A Dynamic Sedimentary Environment: A Conceptual Framework Using Mangroves,” Journal of Applied Ecology, 50(3), pp. 740-747. doi: 10.1111/1365-2664.12067

294 Endah Dwi Hastuti et al