Benoa Bay Research Articles

Actor Networks and Environmental Conflicts: The Case of Benoa Bay Reclamation (2014-2019)

This study explores the formation of actor networks in developing conservation areas, specifically focusing on the Benoa Bay conservation area in Bali from 2014 to 2019. This period marks the beginning and temporary cessation of reclamation development permits in the area, instigated by a Presidential Decree. The study examines how actor networks form through material negotiations, categorizing actors into pros (supporting reclamation) and cons (opposing reclamation). It employs the Actor Network Theory (ANT) framework, particularly the moments concept developed by Callon, to analyze these networks and negotiations. The research is qualitative, using case studies and field data collected through interviews with relevant stakeholders. The primary findings reveal that actors on both sides—pro and con—form networks based on the material narratives they promote. For the pros, the need for tourism space justifies reclamation, while the cons focus on conservation values upheld by the Balinese community. The reclamation issue acts as a moment of problematization, bringing these opposing material narratives into conflict within the conservation area. The study follows ANT’s stages from problematization to mobilization, highlighting how the conflicting material narratives of both pro and con actors interact and influence the network formation. Ultimately, the research illustrates the dynamics of actor networks in the context of reclamation, showing how material negotiations shape these networks and the contestation over spatial production in Benoa Bay networks.

Heavy metals concentration in sediment and their bioaccumulation in several organisms in Benoa Bay and Lembongan Island, Bali, Indonesia

Abstract. Putri PYA, Rastina, Prartono T, Ismet MS. 2024. Heavy metals concentration in sediment and their bioaccumulation in several organisms in Benoa Bay and Lembongan Island, Bali, Indonesia. Biodiversitas 25: 3230-3238. Human activities could be responsible for introducing heavy metals into coastal areas, and it can contaminate coastal waters such as the tourism area of Benoa Bay and coastal ecosystems of Lembongan Island, Bali, Indonesia. This study aimed to assess the extent of heavy metals on the sediment of those area and their accumulation rate in several marine organisms, including macro-algae (Ulva sp.), seagrass (Thalassia hemprichii), and sea urchin (Diadema sp.). Samples of surface sediments and marine organisms were collected at six stations for both areas and the presence of five heavy metals (Fe, Pb, Cd, Cu, and Cr) was determined using the AAS method. The concentration those metals varied significantly across the six stations. The geo-accumulation index showed that the sediment has been contaminated by Pb and Cd. The ecological risk of heavy metals contamination in Benoa Bay was apparently higher compared to that in Lembongan Island. Marine organisms in Benoa Bay also significantly accumulated heavy metals than those observed in Lembongan Island. Bioconcentration factor (BCF) shows that Cd, Cr, and Pb were the most accumulated heavy metals in marine organisms (BCF>1). It, therefore, suggest that future studies of the bioavailability of heavy metals and exploration the varying capacities of marine organisms are required. Such important information can be used to predict the accumulation of heavy metals in human bodies, and the possibly daily consumption of marine organisms caught from Benoa Bay and Lembongan Island waters.

Assessment of soil fraction, carbon storage capacity, and rate of carbon uptake from three coastal ecosystems: Mangroves, seagrass, and mudflats in Benoa Bay, Indonesia

Abstract. Dharmayasa IGNP, Sugiana IP, Putri PYA, Boonyasana K. 2024. Assessment of soil fraction, carbon storage capacity, and rate of carbon uptake from three coastal ecosystems: Mangroves, seagrass, and mudflats in Benoa Bay, Indonesia. Biodiversitas 25: 2541-2549. Coastal habitats, known as blue carbon ecosystems, are highly productive at absorbing and storing carbon. Most carbon is stored as soil organic carbon, and its quantity can vary depending on various factors, including the presence of plants such as mangroves and seagrass, and environmental conditions, including soil fraction. This study quantifies soil carbon stored and its burial rate in three primary coastal ecosystems: mangroves, seagrasses, and mudflats. The ashing method (loss on ignition) is used to quantify carbon content, which is then converted into soil carbon storage and burial rate. Gravimetry and the settling time method are used to determine the soil fraction. We also measure the soil and water properties directly during the sampling time. This study revealed significant soil carbon stock and burial rate variations across different ecosystems. The order of ecosystems with the most extensive carbon stock and burial rate is as follows: mangrove (69-145 tC ha-1 and 1.6-3.4 tCha-1yr-1)>seagrass (63-75 tC ha-1 and 1.5-1.7 tCha-1yr-1)>mudflat (49-61 tC ha-1 and 1.2-1.4 tCha-1yr-1). Mangroves with natural growth have a higher carbon storage capacity than rehabilitated ones. Soil carbon content is highly correlated with the soil and water pH, Dissolved Oxygen (DO), water content, bulk density, and soil type. The findings demonstrate that carbon absorption capability varies among coastal habitats, with vegetated environments exhibiting higher carbon storage levels. Converting land, particularly mudflats, into seagrass beds or mangrove forests may maximize the efficiency of coastal ecosystems as carbon sinks. However, it should be noted that these findings are only estimates, and the precise measurement numbers may differ due to seasonal circumstances or reclamation activities, which might cause oscillations in sedimentation rates. These variations, in turn, could affect the levels of carbon stored and the speed at which it is buried.

Eating Habits and Dietary Strategies of the Glass Perchlet Fish (Ambassis macracanthus) In Benoa Bay Waters, Bali in Two Different Seasons

The Benoa Bay area and its surroundings are a center of biodiversity at the ecosystem level in the southern coastal region of Bali. This area exhibits diverse ecosystems, including mangrove ecosystems, coral reefs, seagrass beds, and tidal flats. This research aims to analyze and describe the feeding ecology of Ambassis macracanthus in the waters of Benoa Bay. The study was conducted in May, at the end of the transitional season, and in July and August, during the eastern monsoon season in Benoa Bay Waters. Modified gill nets with mesh sizes of 0.5, 1.0, 1.5, 2.0, 2.5, and 3.0 cm were used for capturing the fish. The fish were caught at three stations, which represented the characteristic conditions of the Benoa Bay Waters. Out of the 396 individuals caught during the study, only 100 were selected for examination. The average relative fullness gut index (RGI) of Ambassis macracanthus ranged from 0.39 to 0.67. The total Important Relative Index (IRI) value for the food of Ambassis macracanthus in Benoa Bay Waters was 951.27. Ambassis macracanthus in Benoa Bay Waters is an omnivorous species with a tendency towards herbivory, and 21 different organisms were found in its diet, including three classes of phytoplankton and three classes of zooplankton. The feeding strategy developed by Ambassis macracanthus in Benoa Bay Waters is generalist. This information about the fish can be used as a fundamental basis for managing fish in the waters of Benoa Bay.

Monitoring Total Suspended Solid Distribution In Coastal Bali Area Using MODIS Satellite Data

Total Suspended Solid (TSS) is one important parameter for water quality. This research aims to analyze MODIS feasibility for identifying TSS, to identify TSS monthly patterns and annual patterns variability, and to analyze the TSS distribution patterns around Bali coastal area. Observation data of the wet season was observed in Benoa Bay on 2nd October 2013 and the dry season was observed in Perancak from July on 28th to July 31st, 2009. The comparison between observation data and satellite data was used to establish a new modification algorithm for suitable conditions around Bali coastal area. Based on research analysis, the feasibility of MODIS was different in each season. In the wet season, the coefficient correlation was (r) = 0.55 and in the dry season, it was (r) = 0.68. poor correlation in the wet season indicated the bottom effect of the area which has a shallow and heterogeneous depth. The TSS average in the wet season was 75.55 mg/l and 55.97 mg/l in the dry season. The highest value was analyzed in November (82.74 mg/l) and the lowest value in June (46.41 mg/l). During wet season, the stream volume and the stream flow rate increase and bring the TSS into coastal areas through the runoff process. The mapping patterns showed that the southern coastal area and western coastal area of Bali had a high value every month. The northern coastal had a high value only in the wet season. The characteristic of Bali river area, which is perennial and intermittent rivers caused this phenomenon. The population and Bali land-use area also affected the high TSS in these areas. Yearly patterns of TSS from 2009 to 2013 around Bali coastal areas were different every year. The highest TSS distribution observed in 2013 wet season is 87.75 mg/l. The lowest TSS distribution occurred in 2009 dry season with a value of 52.2 mg/l. The TSS tends to increase every year due to the changing in Bali land use. TSS patterns from 2009 to 2013 were dynamic every year. The El Nina and La Nino events also gave impact on the patterns. The MODIS feasibility in different locations was different depending on the characteristic of the physical property of water. The shallow and small area causes misinterpretation of the satellite reflectance. The TSS monthly patterns depended on the season and the mapping can be used to describe the sources of TSS pollution, the distribution, and the quantity of TSS in the coastal area.

Ecosystem carbon stock and annual sequestration rate from three genera-dominated mangrove zones in Benoa Bay, Bali, Indonesia

Abstract. Sugiana IP, Prartono T, Rastina, Koropitan AF. 2024. Ecosystem carbon stock and annual sequestration rate from three genera-dominated mangrove zones in Benoa Bay, Bali, Indonesia. Biodiversitas 25: 287-299. The mangrove ecosystem is an ecologically productive wetland system that serves as a carbon sink. However, various factors have contributed to the variation in values when calculating ecosystem carbon stock and the sequestration rate in the mangrove ecosystem. The presence of varying environmental conditions has resulted in the categorizing different species of mangroves, which may lead to variations in ecosystem carbon stock and sequestration rates. In this study, we aim to assess the ecosystem carbon stock and sequestration rate of the mangrove ecosystem in Benoa Bay, Bali, Indonesia. The ecosystem has been categorized into three zones based on the dominant genera: Bruguiera, Rhizophora, and Sonneratia. This research aimed to investigate the influence of mangrove zoning on the variability of carbon stock values and sequestration rates within the ecosystem. The allometric calculation technique and net primary productivity and soil organic carbon percentage values obtained using the Loss on Ignition (LOI) method are used to estimate each zone's ecosystem carbon stock and sequestration rate. The findings of our study indicate that there are notable variations in the carbon stock of ecosystems across different zones. However, we did not observe any substantial changes in the annual carbon sequestration rates. The Sonneratia zone exhibits the maximum value of ecosystem carbon stock and sequestration rate (1,570.9±248.0 tCO2ha-1 and 81.8 tCO2ha-1yr-1), while the Bruguiera zone demonstrates the lowest values (1,029.6±130.9 tCO2ha-1 and 75.6 tCO2ha-1yr-1). The three zones' average carbon stock and sequestration rate are estimated as 338.2 tCha-1 (1239.9 tCO2ha-1) and 21.5 tCha-1yr-1 (78.9 tCO2ha-1yr-1), respectively. In total, the carbon storage and absorption capacity of Benoa Bay amounts to 421,149 tC (equivalent to 1.5 million tCO2), with an annual rate of 25,769.4 tCyr-1 (equivalent to 94,573.6 tCO2yr-1). We recommended that future ecosystem carbon stock evaluations consider mangrove-type zoning characteristics due to significant value fluctuations in various mangrove zones found.

Mapping mangrove above ground carbon stock of benoa bay bali using sentinel-1 satellite imagery

Mangrove forest ecosystems distributed in tropical countries play an important role in carbon sequestration. The presence of mangrove forests is estimated to be capable of reducing CO2 levels caused by air pollution. The process of photosynthesis absorbs CO2 gas from the atmosphere and stores it as organic matter in the form of plant biomass. The amount of carbon stock stored in mangrove forests can be estimated using a regression model based on satellite imagery pixel values and above ground biomass (AGB) measurements. This study used the backscattering value of SAR Sentinel 1 images and field AGB measurements to map carbon stocks in the mangrove forest ecosystem of Benoa Bay, Bali. The processed backscattering value is the result of VV and VH polarization in the SAR Sentinel 1 image acquired in 2022. Meanwhile, AGB is calculated using the allometric equation based on the mangrove’s species found at the study site. The biomass at the study location was estimated to be in the range of 64.18 Mg/Ha to 175.24 Mg/Ha, with an average of 115.34 ± 25.33 Mg/Ha. Therefore, the carbon stock of Benoa Bay can be estimated to have values in the range of 30.16 MgC/Ha to 82.36 MgC/Ha, with an average of 54.21 ± 11.09 MgC/Ha. In terms of estimating AGB biomass based on SAR pixel values, the VH polarization produces a better model (R2 = 0.635) than the VV polarization.

Numerical modeling of ocean currents and suspended sediment distribution in Benoa Bay, Bali

Benoa Bay is a semi-enclosed water body that includes a shallow estuary area that supports important aquatic ecosystems, including mangrove ecosystems, seagrass beds, and coral reefs. The reclamation of Benoa Harbor and the construction of a toll road in Benoa Bay are suspected to have increased sedimentation. The objective of this study is to model ocean currents and suspended sediment distribution during the Northwest and Southeast monsoons in the waters of Benoa Bay. Numerical models are used to describe the hydrodynamic process as the main driver of the process of pollutant movement in the waters. The current pattern resulting from the model in the waters of Benoa Bay has the same pattern in the Northwest and Southeast Monsoons, with the current velocity of the Northwest Monsoon ranging from 0 – 1.6583 m/s and the Southeast Monsoon ranging from 0 – 1.4729 m/s. The distribution of suspended sediment in the Northwest Monsoon is quite high compared to the Southeast Monsoon. The distribution of suspended sediment in the Northwest Monsoon ranges from 0 – 846 mg/L and in the Southeast Monsoon, it ranges from 0 – 598 mg/L.

IDENTIFIKASI MAKROZOOBENTOS SEBAGAI BIOINDIKATOR KUALITAS PERAIRAN DI PANTAI TELUK BENOA, BADUNG

Utilization of coastal waters for aquaculture activities or for other activities provides positive value for human welfare but can also provide the potential for reducing water quality. The decline in environmental quality can be seen from changes in components such as biology, chemistry, and beach physics. Changes in chemical and physical components cause sediment to decrease, which will affect the life of marine biotas, such as the community structure, especially the slow-moving and relatively settled biota on the bottom of the waters (macrozoobenthos). Macrozoobenthos are very appropriate to be used as an indicator of changes in water quality due to their benthic nature which is relatively silent or has low mobility so it is strongly influenced by the environment. The purpose of the study was to determine the structure of the macrozoobenthos community and the condition of seawater quality. There were 25 species of gastropods and 3 other classes. The macrozoobenthos species diversity index on the Benoa Bay Coast showed a moderate level of diversity with the highest value of 2.4576. The uniformity index at each station ranges from 0.0894 – 0.5337. The value of the dominance index ranges between 0.000004-0.7656. Based on the relative abundance, the macrobenthos community is dominated by the Gastropod class. The temperature values ??at each station were relatively the same, ranging from 29.3°C– 30.8°C, and the pH was in accordance with quality standards for macrozoobenthos growth. Some indicators of water quality are still below the quality standard threshold, but the concentration of phosphate (PO4) at all locations is already above the predetermined quality standard of 0.015 mg/L?.
 Keyword: Macrozoobenthos; Bioindicator; Benoa Bay; Bali

Strategi Pengembangan Wisata Snorkeling di Pantai Tanjung Benoa, Bali

The island of Bali as one of the icons of Indonesian tourism is famous for its natural potential, community hospitality, cultural values and the value of the natural beauty of the sea which is packaged in marine tourism attractions. Marine tourism is a tourism activity in the form of enjoying the beauty, uniqueness, comfort and other values of marine nature and other values and water sports including the provision of facilities and infrastructure as well as other services that are managed commercially. Tanjung Benoa is a marine tourism destination that is favored as a Tourist Attraction (ODTW) in Badung Regency with water sports, snorkeling and diving attractions. This study aimed to determine the current condition of snorkeling tourism and determined the strategy for developing snorkeling tourism at Tanjung Benoa Beach. The study was conducted from January 2021 to February 2021, using quantitative descriptive methods and data analysis using SWOT analysis. The results showed that the condition of tourist visits for integrated snorkeling activities in marine tourism attractions experienced a drastic decline as a result of the 2020-2021 COVID-19 pandemic conditions. The potential for marine tourism, especially snorkeling activities in Tanjung Benoa, is coral reefs, reef fish and other marine biotas. Based on the results of the SWOT analysis, Tanjung Benoa Beach was in quadrant II. The strategy for developing snorkeling tourism on the Tanjung Benoa beach was in quadrant II or the ST (Strength and Threat) strategy. The ST strategy included maintaining the condition of coral reefs and marine life and studying the reclamation of Benoa Bay. The next strategy was to increase village rules related to health protocols and e-commerce-based marine tourism marketing.

Soil greenhouse gas fluxes to the atmosphere during the wet season across mangrove zones in Benoa Bay, Indonesia

Behind their role as carbon sinks, mangrove soil can also emit greenhouse gases (GHG) through microbial metabolism. GHG flux measurments of mangroves are scarce in many locations, including Indonesia, which has one of the world’s most extensive and carbon-rich mangrove forests. We measured GHG fluxes (CO2, CH4, and N2O) during the wet season in Benoa Bay, Bali, a bay with considerable anthropogenic pressures. The mangroves of this Bay are dominated by Rhizophora and Sonneratia spp and have a characteristic zonation pattern. We used closed chambers to measure GHG at the three mangrove zones within three sites. Emissions ranged from 1563.5 to 2644.7 µmol m−2 h−1 for CO2, 10.0 to 34.7 µmol m−2 h−1 for CH4, and 0.6 to 1.4 µmol m−2 h−1 for N2O. All GHG fluxes were not significantly different across zones. However, most of the GHG fluxes decreased landward to seaward. Higher soil organic carbon was associated with larger CO2 and CH4 emissions, while lower redox potential and porewater salinity were associated with larger CH4 emissions. These data suggest that soil characteristics, which are partially determined by location in the intertidal, significantly influence GHG emissions in soils of these mangroves.

Ludic cybermilitias: shadow play and computational propaganda in the Indonesian predatory state

Abstract This article ties the studies of computational propaganda to studies of the state in the Global South by examining “political buzzers”—actors of Indonesian computational propaganda. Rather than an extension of state propaganda, I argue that buzzers are a “twilight institution” straddling the boundaries between state and society. As cybermilitias, they are rooted in the historical conjuncture of Indonesian state practices in deploying privatized violence for extractive capitalist accumulation, exhibited by two cases in this article: the reclamation of Benoa Bay in Bali and the Ciliwung forced evictions in Jakarta. Informed by ethnographic fieldwork, I delve into buzzers’ experience of computational propaganda as an avenue for political agency. They conceive their clandestine labor into a play, conjuring the political metaphor of dalang (master puppeteers) pulling strings from behind the scenes. These shadow play theatrics constitute the ludic aspect of buzzers as ludic cybermilitias. By exploring how computational propaganda is shaped by and shapes state power in Indonesia, I problematize the notion that political buzzers signify “democratic regression” or “digital authoritarianism.” Instead, I propose that buzzers represent the latest manifestation of privatized violence within the predatory logic of post-authoritarian states in the Global South.

Sustainability Index of Benoa Bay Beach Reclamation Against National Resistance

This study aims to analyze systematically and thoroughly about how the impact of coastal reclamation on National Resilience. The activity starts from a thorough understanding of the system that occurs in the reclamation and variable processes that affect national security. The research method used analysis Multi-Dimensional Scaling Method. The Benoa Bay reclamation activity plan, multi-dimensional analysis is not or less sustainable, with an index of 42.93 %. The most sensitive attribute influences the dimensions of the environment, is the attribute of potential sedimentation is the most sensitive attribute with a value of 0.13. The most sensitive attribute affecting the economic dimension is an increase in regional revenue. In the sensitivity test of the socio-cultural dimension, the most sensitive and influential attribute obtained is the perception of the community shop. The most sensitive attribute influencing the legal dimension is the formal rules, there must be formal rules, indeed administratively the formal rules are legal products that are approved by the institutions governed by the law, but usually what is forgotten is the process of realizing formal rules.

Estimation and Mapping Above-Ground Mangrove Carbon Stock Using Sentinel-2 Data Derived Vegetation Indices in Benoa Bay of Bali Province, Indonesia

Carbon dioxide (CO2) is one of the greenhouse gases that causes global warming with the highest concentration in the atmosphere. Mangrove forests can absorb CO2 three times higher than terrestrial forests and tropical rainforests. Moreover, mangrove forests can be a source of Indonesian income in the form of a blue economy, therefore an accurate method is needed to investigates mangrove carbon stock. Utilization of remote sensing data with the results of the above-ground carbon (AGC) detection model of mangrove forests based on multispectral imaging and vegetation index, can be a solution to get fast, cheap, and accurate information related to AGC estimation. This study aimed to investigates the best model for estimating the AGC of mangroves using Sentinel-2 imagery in Benoa Bay, Bali Province. The random forest (RF) method was used to classified the difference between mangrove and non-mangrove with the treatment of several parameters. Furthermore, a semi-empirical approach was used to assessed and map the AGC of mangroves. Allometric equations were used to calculated and produced AGC per species. Moreover, the model was built with linear regression equations for one variable x, and multiple regression equations for more than one x variable. Root Mean Square Error (RMSE) was used to assess the validation of the model results. The results of the mangrove forests area detected in the research location around 1134.92 ha, with an Overall Accuracy (OA) of 0.984 and a kappa coefficient of 0.961. This study highlights that the best model was the combination of IRECI and TRVI vegetation indices (RMSE: 11.09 Mg/ha) for a model based on red edge bands. Meanwhile, the best results from the model that does not use the red edge band were the combination of TRVI and DVI vegetation indices (RMSE: 13.63 Mg/ha). The use of red edge and NIR bands is highly recommended in building the AGC model of mangrove forests because they can increase the accuracy value. Thus, the results of this study are highly recommended in estimating the AGC of mangrove forests, because it has been proven to be able to increase the accuracy value of previous studies using optical images.

Mangrove biomass sequestration in Benoa Bay

Mangrove ecosystems are coastal ecosystems that can store carbon three times higher than all other forests on earth. Current conditions show a decrease in mangrove forests and damage to mangrove ecosystem conditions that impact reducing mangrove carbon sequestration. Data relating to the potential of sustainable mangrove biomass is currently lacking, so research is needed. The purpose of this study was to determine changes in the amount of mangrove biomass at permanent stations temporally. This research was conducted at 10 sample points in the Benoa Bay area using a stratified purposive sampling method with a quadrant transect measuring 10 meters x 10 meters. Data were collected by measuring DBH on each mangrove stand within the transect. Data analysis was conducted using the common allometric equation by including the wood-specific gravity per species. In general, there was an increase in the average biomass in each plot with an average of 1.315 tons/ha at six months different. This shows that the larger the diameter of the stand, the greater the biomass produced.

Spatial Analysis of Mangrove Distribution Using Landsat 8 Oli in Badung Regency and Denpasar City, Bali Province, Indonesia

Bali is an island situated among the Indonesian archipelago with huge potential to host mangrove forests. Using remote sensing technology advances, satellite images, such as Landsat images, might be employed to analyse mangrove forest distribution and density. This paper presents an analysis of mangrove distribution in Badung Regency and Denpasar City, Bali, as a basis for the management and conservation of mangrove ecosystems. This study used Landsat 8 OLI images and a vegetation index to analyse the mangrove forest distribution and density in this area. It started by identifying mangrove forests using the RGB 564 band and continued to distinguish between mangrove and non-mangrove objects using unsupervised classification, before analysing mangrove density using the NDVI formula. The results show that the mangrove forest area in 2020 was 1,269.20 ha, with an accuracy rate of 83%. Mangroves were found on the deepest or most curved coastline of the Benoa Bay area, on enclosed waters. This distribution follows the river network in the lower reach, which has thick deposits and is uninfluenced by large currents and waves. Based on the vegetation index analysis results, the mangrove forest area observed mainly had a moderate density, with a total area of 510.85 ha (40%), followed by high density (413.15 ha/ 33%) and low density (340.51 ha/ 27%).

Spatial distribution of mangrove health index on three genera dominated zones in Benoa Bay, Bali, Indonesia

Abstract. Sugiana IP, Andiani AAE, Dewi IGAIP, Karang IWGA, As-Syakur AR, Fharmawan IWE. 2022. Spatial distribution of mangrove health index on three genera dominated zones in Benoa Bay, Bali, Indonesia. Biodiversitas 23: 3407-3418. A study of mangrove forest stratification was conducted in Benoa Bay which experienced high coastal development pressures during the last decade. The study aimed to determine mangrove health index distribution (MHI) and forest community structures along three genera-dominated zones which were Sonneratia, Rhizophora and Bruguiera. Random forest method was applied to classify the areas of distributed genera along the bay. Forest structure was assessed with 54 plots. The forest was mainly composed of Rhizophora and Sonneratia-dominated zones in a respective forest area proportion at approximately 51% and 45%. Those zones were dominated by R. mucronata and S. alba with an importance value index (IVI) at 266.35% and 145.57%, respectively. A narrow Bruguiera zone composed of B. gymnorrhiza domination was found in the most landward area, only covering 4% of the mangrove area. Overall accuracy and a kappa coefficient indicated high accuracy of forest classification at 97% and 0.94 respectively. We found that 47.44% of mangrove areas could be classified into the highest healthiness category indicating that the mangrove forest in Benoa Bay is in excellent condition. The Rhizophora zone made a significant contribution to the entire forest state since the excellent category coverage in this zone was approximately 73.80%.

Kajian Pengelolaan Wilayah Pesisir dan Laut Indonesia (Review: Reklamasi Teluk Benoa)

Benoa Bay is part of the waters of Bali which contributes very positively to the Balinese people, especially to the surrounding community, especially in maintaining the stability of various ecosystems and hydrology as well as its contribution in providing protection, economic, and socio-cultural services for the local community. Proper management of the Benoa Bay area will be able to minimize the risks that will occur. Therefore, good management of coastal and marine areas is needed through an integrated management program that is supported by the availability of objective, accurate, and up-to-date information sources. This study was carried out by collecting literature from relevant research on reclamation in Benoa Bay. The results of the study found that PT. Tirta Wahana Bali International (PT. TWBI) as the holder of the Benoa Bay Utilization and Development permit will develop the Benoa Bay area including (1) Pudut Island Restoration; (2) Firsherman's Cove; (3) Botanical Garden, meanwhile the Benoa Bay area is a center of biodiversity and there is a high and complete diversity of ecosystems, namely; Ecosystems of mangroves, coral reefs, seagrass beds, andtidal flats. This illustrates that integrated management must and immediately be carried out to assist in the formulation of policies and planning for the management of coastal and marine areas that are more effective and targeted so that there are no mistakes in policy making that lead to social conflicts.Keywords: Benoa Bay, ecosystem diversity, integrated program, policy

Distribusi Spasial Klorofil-A di Perairan Teluk Benoa Bali

Benoa Bay is an estuary that gets input of waste and nutrients from six rivers and inderectly influenced water productivity in Benoa Bay. The nutrients flow from the river to domestic, industrial, and agricultural activities into Benoa Bay. The amount of nutrient inputs accumulated in Benoa Bay this could affect the chlorophyll-a consentrations. The purpose of this study was to determine the spatial distribution and influence nitrate and phosphate on chlorophyll-a concentration. Water surface sampling carried out on February 2019. The method used was purposive sampling and chlorophyll-a concentration was analysed using spectrophotometer Shimadzu UV-2600, based on the maximum absorption of four wavelengths (quadrichroic). The results showed that the chlorophyll-a concentration ranged from 0.22 - 8.53 g/m3 with an average of 5.58 g/m3. Nitrate concentration ranged from 0,004 - 0,180 mg/L with an average 0,107 mg/L. Phosphate concentration ranged from 0,005 - 0,229 mg/L with an average 0,101 mg/L. Spatial distributions of chlorophyll-a concentration in Benoa Bay higher in the estuary area compare to sea area. The different concentration of chlorophyll-a in Benoa Bay were affected by physical and biological processes. The result of statistic regression of the nitrate and phosphate influence on chlorophyll-a concentration in Benoa Bay was 39,2% (R² = 0.392) for nitrate, meanwile 20,5% (R² = 0.205) for phosphate.

Study of management of Indonesian Coastal and Marine seas (Review: Benoa Bay Reclamation)

Benoa Bay is part of the waters of Bali which contributes very positively to the Balinese people, especially to the surrounding community, especially in maintaining the stability of various ecosystems and hydrology as well as its contribution in providing protection, economic, and socio-cultural services for the local community. Proper management of the Benoa Bay area will be able to minimize the risks that will occur. Therefore, good management of coastal and marine areas is needed through an integrated management program that is supported by the availability of objective, accurate, and up-to-date information sources. This study was carried out by collecting literature from relevant research on reclamation in Benoa Bay. The results of the study found that PT. Tirta Wahana Bali International (PT. TWBI) as the holder of the Benoa Bay Utilization and Development permit will develop the Benoa Bay area including (1) Pudut Island Restoration; (2) Firsherman's Cove; (3) Botanical Garden, meanwhile the Benoa Bay area is a center of biodiversity and there is a high and complete diversity of ecosystems, namely; Ecosystems of mangroves,coral reefs,seagrass beds, andtidal flats. This illustrates that integrated management must and immediately be carried out to assist in the formulation of policies and planning for the management of coastal and marine areas that are more effective and targeted so that there are no mistakes in policy making that lead to social conflicts.Keywords: Benoa Bay, ecosystem diversity, integrated program, policy