Mangrove Ecosystem Management Research Articles

Analisis Persepsi Masyarakat Terhadap Pengelolaan Ekosistem Mangrov di Kawasan Mangrov Biringkassi Kabupaten Pangkep

This study aims to analyze public perception of mangrove management in the Biringkassi mangrove area of Pangkep regency. This research is important because the surrounding community does not get more education and attention from the government. This research is a descriptive research with a qualitative approach. Researchers conducted in-depth interviews with 45 purposively selected respondents using thematic category content analysis techniques to identify themes or patterns in the interview. The result: The level of understanding and knowledge of the community is low. Community participation is in the moderate category even though it is known that public perception of the benefits of mangrove ecosystems for them is quite good. Therefore, citizen involvement in maintaining mangrove ecosystems that are still at the middle level needs to be increased, and implementing programs such as: (1) increasing public awareness of the importance of mangrove ecosystems, (2) educating the public about mangrove ecosystem management, (3) intensifying government policies on planting and conservation, and (4) establishing effective communication between the government and the community

Identification of mangrove damage and mangrove ecosystem management efforts in Ekasoghi Tourism, Saronggi District, Sumenep Regency

The Saronggi District area, Tanjung Village has experienced changes in the structure of mangroves which resulted in a decrease in the number of mangroves due to mangrove tourism, lack of awareness of the importance of mangroves, and damage due to human activities. The purpose of this study is to find the causes of mangrove damage and formulate policies in the management of mangrove ecosystems in the Ekagoghi tourist area. This research was conducted with visual observation (descriptive narrative) and SWOT analysis to consider management policy strategies. The types of mangroves found on the coast of Ekasoghi in Sumenep Regency consist of species Osbornia octodonta, Sonneratia alba, Avicennia marina, Rhizophora mucronata, Lumnitzera racemosa, and Rhizopora apiculata which have been damaged by natural factors and human actions. The causes of mangrove damage include high beach abrasion so that beach erosion occurs and causes a reduction in nutrients and seaweed cultivation which causes damage to mangrove trees due to the charts used. Policies that need to be carried out for the management of mangrove ecosystems on Ekasoghi Beach, namely by holding wanamina cultivation (silvofishery) and the implementation of an ecopreneurship system, can be considered to develop policies directed to explore profit potential and maintain the sustainability of the existence of preserving mangrove ecosystems. This policy certainly needs to be supported by strengthening community institutions and cooperation between government institutions.

Evaluating Feature Selection Methods and Machine Learning Algorithms for Mapping Mangrove Forests Using Optical and Synthetic Aperture Radar Data

Mangrove forests, mostly found in the intertidal zone, are among the highest-productivity ecosystems and have great ecological and economic value. The accurate mapping of mangrove forests is essential for the scientific management and restoration of mangrove ecosystems. However, it is still challenging to perform the rapid and accurate information mapping of mangrove forests due to the complexity of mangrove forests themselves and their environments. Utilizing multi-source remote sensing data is an effective approach to address this challenge. Feature extraction and selection, as well as the selection of classification models, are crucial for accurate mangrove mapping using multi-source remote sensing data. This study constructs multi-source feature sets based on optical (Sentinel-2) and SAR (synthetic aperture radar) (C-band: Sentinel-1; L-band: ALOS-2) remote sensing data, aiming to compare the impact of three feature selection methods (RFS, random forest; ERT, extremely randomized tree; MIC, maximal information coefficient) and four machine learning algorithms (DT, decision tree; RF, random forest; XGBoost, extreme gradient boosting; LightGBM, light gradient-boosting machine) on classification accuracy, identify sensitive feature variables that contribute to mangrove mapping, and formulate a classification framework for accurately recognizing mangrove forests. The experimental results demonstrated that using the feature combination selected via the ERT method could obtain higher accuracy with fewer features compared to other methods. Among the feature combinations, the visible bands, shortwave infrared bands, and the vegetation indices constructed from these bands contributed the greatest to the classification accuracy. The classification performance of optical data was significantly better than SAR data in terms of data sources. The combination of optical and SAR data could improve the accuracy of mangrove mapping to a certain extent (0.33% to 4.67%), which is essential for the research of mangrove mapping in a larger area. The XGBoost classification model performed optimally in mangrove mapping, with the highest overall accuracy of 95.00% among all the classification models. The results of the study show that combining optical and SAR remote sensing data with the ERT feature selection method and XGBoost classification model has great potential for accurate mangrove mapping at a regional scale, which is important for mangrove restoration and protection and provides a reliable database for mangrove scientific management.

Determination of Health Index Classification and Management Sustainable Mangrove Ecosystems Using a Combination of Fuzzy and ISM Methods

The area of mangrove forests in Indonesia in 2021, according to the Ministry of Environment and Forestry, is around 3,364,080 Ha; this amount is equivalent to 23% of the world’s mangrove ecosystem, which is from a total of 16,530,000 Ha (FAO, 2005). Information on the condition of mangrove ecosystems is important to know whether or not an area is good. Studies related to the condition of mangrove ecosystems based on environmental quality and mangrove health index to determine the environmental quality and mangrove health are needed for ecosystem management in the future. This article describes the health parameters of mangrove ecosystems that will be analyzed with the help of a combination of decision support software such as fuzzy and ISM so that priority mangrove ecosystem locations can be determined, mangrove health index values to determine the health status of mangrove ecosystems and determine alternative sustainable mangrove ecosystem management policies that will be applied to the object of study. In addition, the study also discusses the concept of determining standard criteria for the level of damage to mangrove ecosystems and determining the status of mangrove ecosystems. Based on fuzzy logic, data analysis shows that the output of the Mangrove Health Index can be determined with 3 variables and 27 rules, with key factors in Mangrove Density, Canopy Cover and Number of saplings. The results of ISM show that management institutions that must be actively involved in supporting the success of sustainable mangrove forest ecosystem management in Batam City are KLHK, DLHK Riau Islands Province, and BPDAS Sei Jang Duriangkang. Proper handling of constraints and management institutions that are actively involved in mangrove forest ecosystem management will ultimately encourage budget effectiveness and efficiency to meet the main goal, namely sustainable mangrove forest ecosystem management in Batam City.

Mangrove Ecosystem Management Strategy In Biringkassi Mangrove Area Pangkep Regency

The mangrove ecosystem has an important role in the balance of the coastal area and the living things that surround it. The magnitude of the role of the mangrove ecosystem as a multifunctional resource and its existence which is very vulnerable to pressure requires a mangrove ecosystem management by integrating all aspects so that the existence of the mangrove ecosystem can be managed and its sustainability can be increased. This study aims to assess the condition and potential of mangrove forests in the Biringkassi mangrove area and determine sustainable management strategies for mangrove ecosystems based on influencing factors. This study uses an ecological analysis of mangrove ecosystems and SWOT analysis to determine sustainable management strategies. The results showed that the identification of Biringkassi mangroves in the three sample areas found 3 families of 3 species, Rhizopora mucronata, Sonneratia alba, And Avicennia alba. The type of Rhizopora mucronata had the highest density among all species found at 3 sample locations. The total density is 293 ind./hectare. Management strategies that are a priority in sustainable management of the Biringkassi mangrove area are: Developing a mangrove data bank through cooperation with the government, communities, and NGOs, strengthening institutional coordination that is more measurable and structured in the context of ecological sustainability, through conservation the establishment and arrangement of the Biringkassi mangrove management area, developing community-based management such as nursery and ecotourism management, improving the quality of human resources and maximizing the role of the community local communities in maintaining mangroves. The condition of the density of the Biringkassi mangrove ecosystem is categorized as less dense.

Molecular barcoding of the Persian Gulf mangrove associated brachyuran crabs

Brachyuran crabs constitute the dominant fauna in intertidal and supratidal coasts of mangrove forests. We sampled the most commonly occurring crab species from the biodiversity rich Persian Gulf mangrove forest. We identified crabs from Camptandriidae, Dotillidae, Ocypodidae, Macrophthalmidae, and Sesarmidae as the most common species in the sampled regions. Molecular barcoding was applied to determine 11 species (29 specimens) of the mangrove crabs. Two mitochondrial genes were used to barcode the specimens and these were included in a larger phylogenetic data set. Many of the analyzed species showed a close phylogenetic relationship with species from the Northern Arabian Sea. The results provide the first steps to study the genetic diversity of the mangrove crab community along the Iranian coasts to support protection and management of mangrove ecosystems and its associated taxa.

Carrying capacity of mangrove ecotourism area in Pantai Indah Kapuk, North Jakarta, Indonesia

Abstract. Ewaldo K, Karuniasa M, Takarina ND. 2023. Carrying capacity of mangrove ecotourism area in Pantai Indah Kapuk, North Jakarta, Indonesia. Biodiversitas 24: 5809-5820. Mangroves are crucial in providing various ecological and economic benefits to local communities. This study focuses on the economic aspect of mangroves by analyzing their potential as a tourist attraction in the Mangrove Ecotourism, Pantai Indah Kapuk (PIK). The objective of this study is to analyze the carrying capacity of the mangroves as a tourist attraction to ensure sustainable tourism development. The study was conducted in the Mangrove Ecotourism area, Pantai Indah Kapuk, from January to March 2023, utilizing a quantitative approach. The carrying capacity of the mangrove ecosystem was assessed using the Physical Carrying Capacity (PCC), Real Carrying Capacity (RCC), and Effective Carrying Capacity (ECC) methods. The calculated values for PCC, RCC, and ECC were 107, 16, and 313 visitors/day, respectively. The analysis revealed that the number of visitors at the PIK Mangrove Ecotourism in 2022 had exceeded the PCC and RCC limits, indicating potential ecological impacts. However, the number of visitors had remained within the ECC limits, suggesting that with proper management, the site could accommodate the current visitor levels sustainably. To achieve long-term sustainability, several initiatives are recommended, such as creating zoning in tourist areas to distribute visitor pressure, increasing the number of field officers to monitor the site, and implementing an online ordering system to manage visitor flow efficiently. The findings of this study contribute to the understanding of the carrying capacity concept in ecotourism and provide valuable insights for the management and conservation of mangrove ecosystems as tourist attractions.

Using Multisource High-Resolution Remote Sensing Data (2 m) with a Habitat–Tide–Semantic Segmentation Approach for Mangrove Mapping

Mangrove wetlands are hotspots of global biodiversity and blue carbon reserves in coastal wetlands, with unique ecological functions and significant socioeconomic value. Annual fine-scale monitoring of mangroves is crucial for evaluating national conservation programs and implementing sustainable mangrove management strategies. However, annual fine-scale mapping of mangroves over large areas using remote sensing remains a challenge due to spectral similarities with coastal vegetation, tidal periodic fluctuations, and the need for consistent and dependable samples across different years. In previous research, there has been a lack of strategies that simultaneously consider spatial, temporal, and methodological aspects of mangrove extraction. Therefore, based on an approach that considers mangrove habitat, tides, and a semantic segmentation approach, we propose a method for fine-scale mangrove mapping suitable for long time-series data. This is an optimized hybrid model that integrates spatial, temporal, and methodological considerations. The model uses five sensors (GF-1, GF-2, GF-6, ZY-301, ZY-302) to combine deep learning U-Net models with mangrove habitat information and algorithms during low-tide periods. This method produces a mangrove map with a spatial resolution of 2 m. We applied this algorithm to three typical mangrove regions in the Beibu Gulf of Guangxi Province. The results showed the following: (1) The model scored above 0.9 in terms of its F1-score in all three study areas at the time of training, with an average accuracy of 92.54% for mangrove extraction. (2) The average overall accuracy (OA) for the extraction of mangrove distribution in three typical areas in the Beibu Gulf was 93.29%. When comparing the validation of different regions and years, the overall OA accuracy exceeded 89.84% and the Kappa coefficient exceeded 0.74. (3) The model results are reliable for extracting sparse and slow-growing young mangroves and narrow mangrove belts along roadsides. In some areas where tidal flooding occurs, the existing dataset underestimates mangrove extraction to a certain extent. The fine-scale mangrove extraction method provides a foundation for the implementation of fine-scale management of mangrove ecosystems, support for species diversity conservation, blue carbon recovery, and sustainable development goals related to coastal development.

The nexus between stakeholders’ role, eco-empowerment, and community perceptions on mangrove ecosystem management’s sustainability

Managing coastal ecosystem resources and mangrove forests in Sayung District, Demak Regency faces many challenges if it does not involve the community’s active role and stakeholders. Ecological empowerment faces the abrasion, erosion, and sedimentation of coastal areas that mangrove stands have not covered. On the other hand, the revitalization and rehabilitation program is still not optimal, so it requires the participation of many institutions, not only from the government but also from non-government, so that all management programs run in tandem are integrated and is following regulations. This study aims to determine the relationship between the role of stakeholders, eco-empowerment, and community perceptions of the sustainability of mangrove ecosystem management. The location selection used the purposive method. While the sample selection used the purposive and snowball random sampling methods. Data analysis used the partial least square method. The study’s results indicate that the stakeholders’ role has a direct positive and significant impact on eco-empowerment and perceptions of sustainability. Eco-empowerment has a direct positive and significant effect on the perception of sustainability. The role of stakeholders has a positive and indirect influence on the perception of sustainability through eco-empowerment activities.

Analysis of mangrove dynamics and its protection effect in the Guangdong-Hong Kong-Macao Coastal Area based on the Google Earth Engine platform

Mangroves are rapidly disappearing in several places of the world, and mangrove dynamics are becoming important evidence of ecological restoration and protection along the coast. Mangrove populations in the Guangdong-Hong Kong-Macao Coastal Area (GCA) have experienced a substantial impact of anthropogenic pressure in the 20th century. Monitoring its spatio-temporal variation and protection effect has been regarded as an important task in coastal management. In this study, we provided the comprehensive assessment of mangrove dynamics in the GCA and typical sites from 1988 to 2020 at eight-year intervals. At this time interval, mangrove ecosystems changed significantly as a result of global warming and human impacts. The geographical distribution of mangroves was obtained by applying the Random Forest (RF) classifier on Landsat images with a 30 m spatial resolution on the Google Earth Engine (GEE) platform, based on relevant indices such as Normalized Difference Mangrove Index (NDMI), Normalized Difference Vegetation Index (NDVI), Normalized Difference Suspended Sediment Index (NDSSI), Normalized Difference Built-up Index (NDBI) and Soil Adjusted Vegetation Index (SAVI). Quantitative evaluation indicated that overall accuracy of over 88% was achieved with RF classifier for mangrove extraction. In the GCA, mangrove area was 95.4 km2 in 1988, dropped to 71.4 km2 in 1996, then expanded to 127.5 km2 in 2020, with an overall dynamic rate of 1.02%. In typical sites, mangroves show a similar trend to the overall area. The subsequent mangrove growth is attributed to reserve establishment, accompanied by the expansion of replanted mangrove areas. In the GCA, provincial-level and county-level reserves show a high rate of mangrove dynamic, while national-level reserves display a low rate of mangrove dynamic. The dynamic rate in reserves of the Guangdong-Hong Kong-Macao Greater Bay Area (GBA) is higher than other parts of the GCA, indicating that the effect of mangrove protection is better in the GBA. The results of this study will provide scientific foundations for the sustainable management and conservation of mangrove ecosystem, the quantification of ecosystem services (such as coastal protection and carbon storage), as well as the formulation of strategies for mitigating and adapting to climate change.

Length – Weight Relationship of Bivalves and Gastropods from Mangrove Forest of Brgy. Nabago, Surigao City, Philippines

Bivalves and gastropods are among the most important food resource in coastal communities. The destructive ways of harvesting these mangrove associate fauna may cause a threat to the forest and may alter the physiological condition of these organisms. The length-weight relationship of two bivalves (Anodontia edentula and Saccostrea cuccullata) and 11 gastropods (Littoraria angulifera, Littoraria melanostoma, Littoraria scabra, Chicoreus capunicus, Tenguella musiva, Nerita exuvia, Nerita lineata, Cerithidea decollate, Terebralia palustris, and Terebralia sulcata) species collected from the mangrove forest of Barangay Nabago, Surigao City was assessed in this study. A. edentula exhibits positive allometry (b=3.7002) while S. cuccullata shows negative allometry (b=2.6145). The 11 gastropod species demonstrate a negative allometric pattern (b<3). The negative allometric pattern of these species indicates that the length increased faster than the weight, which could be attributed to the different environmental factors in the area. The data obtained in this study is essential for the monitoring of these organisms and management of the entire mangrove ecosystem in the area.

Mangrove Ecosystem Management for Sustainable Renewable Energy Production: A Multi-Dimensional Analysis

Mangrove ecosystems have become a critical habitat for sustaining renewable energy production, and their management is essential to maintain their ecological, economic, and social functions. This study aimed to analyze the multidimensional aspects of mangrove ecosystem management for sustainable renewable energy production in the Tebing Tinggi, Kepulauan Meranti, Riau. This study formulates sustainable management schemes for the mangrove ecosystem in the Tebing Tinggi, Kepulauan Meranti, Riau by analyzing the ecological, economic, social, legal-institutional, and technological aspects of the ecosystem. To conduct this analysis, researchers used the Multidimensional Scaling (MDS) approach, which relies on an algorithm called the MDS algorithm. The findings from the study reveal that the use of mangroves can increase people's income, but the level of community education is still low, and there is a lack of community participation in mangrove ecosystem management activities. Based on the Rap-Mangrove analysis, the multidimensional index of mangrove ecosystem management is considered sufficiently sustainable. The findings emphasized the significance of community participation and education in managing mangrove ecosystems. The study concludes that sustainable management schemes for mangrove ecosystems are necessary to ensure their continued contribution to renewable energy production.

The Analysis of Land Use Change of Mangrove Ecosystem in Langkat, North Sumatera, Indonesia

Mangroves are subtropical and warm temperate intertidal ecosystems that sustain the well-being of humans and wildlife through a variety of services. However, the existence of mangroves is presently threatened by alterations in land use. From 2010 to 2022, mangrove areas in Pasar Rawa Village, Gebang District, Langkat Regency, North Sumatra province have decreased significantly. The destruction of mangrove forests is primarily caused by the neighboring community's activities. The purpose of this study was to assess the level of damage and density of mangroves in Pasar Rawa Village, as well as to examine the perceptions of locals regarding the management of mangrove ecosystems. The investigation was carried out from January to March 2023 by distributing the questionnaires to the 286 respondents. Based on the vegetation analysis and indexing vegetation analysis through Landsat 7 and Landsat 8 image processing, the amount of mangrove areas in Pasar Rawa Village decreased by 52.97 ha between 2010 and 2022, with the majority of mangrove areas being converted into oil palm plantations and fish farming ponds. It is dominated by the dense class of the Normalized Difference Vegetation Index (NDVI) in 2022, despite the condition of the mangroves in Pasar Rawa Village still being classified as damaged during this recovery process. In addition, the outcome of public perception demonstrates that the management of the mangrove ecosystem is suitable and supports the capacity to create a sustainable mangrove ecosystem.

Kajian Valuasi Ekonomi Sumberdaya Hutan Mangrove di Desa Bone Pute Kecamatan Tonra Kabupaten Bone

Bone Regency is geographically located in an area that is influenced by the coast. The coastal resource ecosystem in Bone Regency is dominated by mangrove forests. Mangrove utilization activities that have been carried out so far are physical utilization in the form of continuous use of wood without any replanting activities. The objectives of this study are: 1) To determine the economic value of mangrove forest resources in Bone Pute Village, Tonra District, Bone Regency. 2) To analyze how much the contribution of mangrove forest resources is to the community in the research area of ​​Bone Pute Village, Tonra District, Bone Regency. while the expected benefits of this research are as follows: 1) The results of this study can provide information on the economic value of mangrove forest resources to the community in Bone Pute Village, Tonra District, Bone Regency. 2) For local governments, as input in making policies, planning and managing mangrove forest resources. 3) The knowledge of this research can be used as a reference in the management and development of mangrove ecosystems in other sectors.This research was conducted in the village of Bone Pute, Tonra District, Bone Regency, South Sulawesi Province. The research activity lasted for 6 (six) months, from May to July 2017. From the results of the research it was found that the Total Economic Value of the mangrove ecosystem in Bone Pute Village, Tonra District, Bone Regency with an area of ​​15.20 ha amounted to Rp. 499,469,964, -/year, while the direct benefits of the mangrove ecosystem for the community made the largest contribution, namely Rp. 336,864,000, -/year, indirect benefits of Rp. 128,468,690, existence benefits of Rp. Rp. 31,032,894, while the optional benefits contributed very little, namely Rp. 3,104,220. The potential of mangrove forests in the mangrove forest area of ​​Bone Pute Village, Tonra District, Bone Regency with an area of ​​15.2 ha, and has a contribution to the community in the mangrove forest area of ​​81.13% of the total economic value of mangrove forests / year

Changes in density level and mangrove land cover on Teluk Pandan Coast, Lampung, Indonesia, after 10 years of community-based management

Abstract. Hasani Q, Anisa A, Damai AA, Yuliana D, Yudha IG, Julian D. 2023. Changes in density level and mangrove land cover on Teluk Pandan Coast, Lampung, Indonesia, after 10 years of community-based management. Biodiversitas 24: 3735-3742. The mangrove ecosystem in the Teluk Pandan coastal area, Pesawaran District, Lampung Province, Indonesia, is part of the mega-biodiversity of mangroves in Indonesia. Specifically, the mangrove in this region has changed due to tourism, aquaculture, settlement activities and coastal abrasion. This study aimed to assess the changes in density level and area change of the mangrove forests at five coastal villages in Teluk Pandan during the period of community management from 2010 to 2020. The effort and success of the rehabilitation were reported in this study can be useful as a consideration of sustainable management of mangrove ecosystem both in Lampung and in other areas in Indonesia. Mangrove area was estimated through field surveys and data processing of satellite imagery from Landsat 5 in 2010 and Landsat 8 in 2020. The mangrove density level and area change were calculated by layering images of mangrove distribution from different years. The classification of mangrove density was determined based on the NDVI value. Satellite imagery was compared with field data collected from 20 observation points at five villages to ensure the density level and interpretation accuracy. Image data analysis showed the changes in mangrove area from 109.80 ha in 2010, an increase of 16.39% to 127.80 ha in 2020. The area of mangrove forest in the rare category decreased by 49.35%, the moderate category increased by 39.13%, and the dense category increased by 109.71%. The study confirmed the successful effort to manage and preserve mangroves in Teluk Pandan Sub-district. Eventually, community-based mangrove management (CBMM) and cross-sectoral and multi-stakeholder management (co-management) has become the core strategy in the successful management of mangrove at five coastal villages in Teluk Pandan Sub-district.

Economic Valuation of Mangrove Carbon Stock on Payung Island, Banyuasin Regency, South Sumatra Province

This study aims to conduct an economic valuation of mangrove carbon stocks found on Payung Island, Banyuasin Regency, South Sumatra Province. Mangroves are coastal ecosystems that play an important role in storing carbon and providing ecological and socio-economic benefits to local communities. The research method used is a field survey and analysis of the latest data on carbon content in mangrove ecosystems. In addition, interviews were also conducted with relevant stakeholders to understand the economic benefits generated from mangrove ecosystems, such as income from the fisheries sector, tourism, and conservation efforts. The results of this study are expected to provide information about the economic value of mangrove carbon stocks on Payung Island. The implications of this research are expected to be used as a basis for decision making related to mangrove ecosystem management and preservation. In addition, this research can also provide a better understanding of the importance of mangrove conservation as a valuable natural resource, both in terms of environment and economy

Assessing mangrove conservation in China by integrating mangrove ecosystem into ecological footprint accounting

Mangrove conservation effort have been undertaken in China, but there is still a lack of quantitative assessment of its eco-environmental benefits. The ecological footprint (EF) is an important indicator of the sustainability of ecosystems, with carbon footprint (CF) and biocapacity (BC) being key indicators of forest ecosystems. Despite the high carbon sequestration capacity of mangrove ecosystems, they have not yet been included in EF. This study introduces mangrove ecosystems into EF accounting and assesses the eco-environmental benefits of mangrove conservation in China. To achieve this, the net ecosystem exchange (NEE) of mangrove forests was estimated based on the gross primary production and respiration rates. Average forest carbon sequestration (AFCS) and yield factor, key parameters of CF and BC, were calculated from NEE for the first time. The CF and BC of mangrove ecosystems were then refined using newly defined AFCS and yield factor. The proposed framework was applied to the whole mangrove forests in China to assess mangrove conservation efforts. The results showed that the average CF of mangrove forests is about 1000 M ha, which is lower than that of terrestrial forests, while the BC of mangroves is not as high as expected due to the limited area of mangroves. CF and BC vary along the coastline, whereby CF tends to decrease with decreasing latitude while BC remains high at low latitudes owing to the large mangrove area. There is no significant decreasing trend in CF, but BC increases with increasing mangrove area. The newly introduced ecological footprint accounting of mangrove ecosystems suggests that mangrove conservation in China should focus on ecosystem health and expand the area of forestable land. These findings will benefit future management of mangrove ecosystems in China and other countries.

Mangrove cover change (2005–2019) in the Northern of Medan City, North Sumatra, Indonesia

Medan City is the third-largest city in Indonesia and serves as the capital of North Sumatra Province. The city has several sub-districts with mangrove forests, with the largest area located in Medan Belawan Sub-district, followed by Medan Labuhan and Medan Marelan Sub-districts. The mangrove forests are situated in the downstream part of the Deli Watershed or the northern part of Medan City. Over the past fourteen years, there has been a significant change in the mangrove land cover, particularly in Medan Labuhan Sub-district. To address this issue, an integrated remote sensing, Geographic Information Systems (GIS), and Analytical Process Hierarchy (AHP) approach was used to map and analyze changes in mangrove cover and determine priority factors to prevent further changes. The study found that the mangrove forest area in Medan Labuhan Sub-district has decreased by 111.25 ha over the years, and the economy was identified as the top priority criterion for preventing changes in mangrove cover. The study recommends efforts from all parties to minimize changes in mangrove forest cover to maintain the function of the mangrove ecosystem, and this approach can help decision-makers and stakeholders make informed decisions about mangrove ecosystem management and conservation in Medan City.

MANGROVE SIMULATION: ATTENUATION OF STORM SURGES IN PROTECTING COASTAL AREA AND GEOSPATIAL SIMULATION MODEL OF MANGROVE FOREST IN PALSABANGON MANGROVE SWAMP FOREST RESERVE PAGBILAO, QUEZON

The objective of this research is to designed and developed a system known as Mangrove Simulation: Attenuation of Storm Surges in Protecting Coastal Area and Geospatial Simulation Model of Mangrove Forest in Palsabangon Mangrove Swamp Forest Reserve Pagbilao, Quezon. The system incorporates various functionalities including web-based application and geographical information system for administrator and staff of Palsabangon Mangrove Swamp Forest Reserve. To utilize the Agent-Based model that simulate and predict the growth and spatial distribution of various mangrove species with regards to the environment. To evaluate of the accuracy of the algorithm in mangrove simulation with geographic information system mapping aims to improve they understanding of the ecological dynamics and spatial patterns of mangroves, and provide useful information for the management and conservation of mangrove ecosystems. The system underwent a comprehensive testing process to assess its functionality, suitability, reliability, performance efficiency, operability, security, compatibility, and maintainability. The results revealed that the system achieved an overall mean score of 4.09, indicating a "Very Satisfactory" rating. This signifies that both experts and clients were very satisfied with the system's characteristics. Moreover, it passed on the standard rating level of ISO/IEC 25010. This remark indicates that the system performed effectively and achieved its goals.

Vegetation Analysis as Indicator of Mangrove Degradation Level in Keboromo Village, Tayu

Mangrove degradation is one of the most common issues in the coastal areas of Java, which can cause ecological impacts and even disadvantage for local community. The mangrove forest degradation can be identified based on the vegetation analysis results, which could potentially contribute to the mangrove ecosystem management and rehabilitation programs in the coastal areas. Mangroves in Keboromo Village was the rehabilitation and cultivation area, but often get damaged by ocean waves. This study aims to determine the ecological and vegetation conditions of mangrove ecosystems consist of species composition, density, canopy cover, tree height, and environmental parameters were held in February 2023. The method used was direct observation using transect quadrants of 10x10 m2. The average mangrove density of all observation stations was 3.425 individuals/ha for the tree category, 575 individuals/ha for the sapling category, and 250 individuals/ha for the seedling category. The average percentage of canopy cover was 78.41%. The average height of mangrove trees at all stations is 4.15 m. The environmental parameters were still compatible with the water quality standard for biota and mangrove life. The mangrove forest degradation level based on standard criteria and guidelines for determining mangrove degradation is categorized as low, indicated by mangrove density &gt;1500 individuals/ha and canopy cover &gt;75%. Poor conditions were measured for sapling and seedling densities, which may be caused by environmental factors unsupportive for mangrove regeneration. Based on the results of mangrove vegetation analysis in Keboromo Village, it can state the mangrove ecosystem condition is good. However, management programs are needed to keep the mangroves sustainable.