Changes In Mangrove Area Research Articles

USG matrix analysis and power interest to improve community environmental awareness: A case study of mangrove land cover to support community and environmental education

This study employed a mixed-method approach to analyze the composition of mangrove forests. The transect method and remote sensing through supervised classification using Google Earth Engine (GEE) were utilized to assess changes in mangrove areas in 2017, 2019, and 2021. The findings suggest that this study should be included in population and environmental education courses. The results revealed that Avicennia marina mangroves had the highest importance index (INP) values at three different locations. Between 2017 and 2019, mangrove areas decreased from 30.62 hectares to 27.98 hectares. However, from 2019 to 2021, the mangrove area increased from 27.98 hectares to 29.18 hectares, largely due to reforestation efforts in the Pulau Dua Nature Reserve. The NDVI (Normalized Difference Vegetation Index) values indicated "bushy" criteria, ranging from 0.43 to 1.00. The Normalized Difference Mangrove Index (NDMI) values fell into the "Rare" (-1.00 to 0.32) and "Medium" (0.33 to 0.43) categories. The Urgency, Seriousness, and Growth (USG) matrix analysis and Power Interest assessment identified illegal logging, erosion, and waste as significant causes of mangrove decline. Stakeholders, including village chiefs, religious leaders, traditional leaders, and youth leaders, must focus on preserving the mangrove ecosystem in the CAPD. The study's results are vital for educational purposes, particularly in population and environmental education courses. These courses should address environmental issues, prevention strategies, and conservation activities, which can be integrated into the curriculum. This will enable youth to contribute effectively to environmental awareness programs.

Study of Changes in Mangrove Areas Around the Barombong Maritime Polytechnic

Recently, coastlines in several areas of Indonesia have experienced erosion, which is quite worrying. Makassar City is one of 30 coastal cities in Indonesia that is estimated to be potentially affected by rising sea levels. As is the case in the Tanjung Bunga and Barombong Beach areas, the level of abrasion is very high. The beaches in these two areas have experienced a decline in coastline over the years, so they have moved far inland. This is caused by several factors, such as the influence of waves that occur in coastal waters, the influence of local winds, the presence of tides and the existence of coastal currents around Tanjung Bunga due to the lack of physical wave dampening structures, such as the lack of artificial structures/ buildings and mangrove forests. as physical protection of the coast.
 This study was conducted to identify changes in the extent of mangrove cover around the Barombong Shipping Polytechnic campus concerning data and information processing using a geographic information system (GIS). Based on the results of the data analysis, there has been a change in the extent of the mangrove ecosystem around the study location. This change in area can be seen from the upward trend over the last ten years. In 2013-2018, there was an increase of ​​30.38% or around 8.2 ha. In 2018-2023, there was an increase in the area of ​​7.36% or around 2.6 ha; in 2013-2023, there was an increase of ​​39.97% or around 10.8 ha.

Mangrove Management Model Towards Net Zero Emissions in Sinjai Regency, South Sulawesi Province.

Mangrove ecosystem plays a very vital role in mitigating climate change, through carbon CO2 absorption. Mangroves have high potential as carbon sequestration. Sinjai Regency is one of the pilot project locations for district/city involvement in the Regional Low Carbon Development Plan in South Sulawesi Province, so that the policy continues to be implemented in various regions. Sinjai Regency has a Mangrove Area which is the result of rehabilitation, but there are indications of changes in land cover that are used conventionally and not integrated, causing a reduction in the area of mangrove land cover. This study aims to analyze the behavior of the model using three policy scenarios with the concept of environmental sustainability in terms of the contribution of mangrove forest utilization to emission absorption. The method used to see changes in land use from year to year is the spatial analysis method, then the data is analyzed using a dynamic system. This research was conducted from January to June 2022 in Sinjai Regency, South Sulawesi Province. The results of the analysis reveal that there are several types of land use that have decreased in area and some have increased in area from year to year. The simulation results show that the proportion of emissions is inversely proportional to changes in mangrove area. The recommended policy is to maintain a minimum land area in the Mangrove Area which is a Protected and Conservation Area and carry out mangrove rehabilitation. The policy structure in the mangrove sector is divided into three parts, scenarios under baseline, fair and ambitious conditions. The mangrove sector in baseline conditions can achieve net zero emissions in 2041, while fair conditions are achieved in 2027 and ambitious conditions are achieved in 2024.

Evaluation of mangrove restoration effectiveness using remote sensing indices - a case study in Guangxi Shankou Mangrove National Natural Reserve, China

As one of the most productive marine ecosystems in the coastal wetlands, mangrove forests have been severely threatened by intensive human activities. Many countries and regions have carried out mangrove restoration projects. The evaluation of mangrove restoration effectiveness is of great significance for scientific decision-making for restoration engineering and wetland management. In this study, we presented a remote-sensing-based Mangrove Restoration Effectiveness Index (MREI) to evaluate mangrove restoration effectiveness. We took the Guangxi Shankou Mangrove National Natural Reserve (GSMNNR) in China, a UNESCO Biosphere Reserve, as our study area, where four phases of afforestation were implemented during 1990-2022. The MREI was developed based on Landsat-series images by considering the change in mangrove area and the Normalized Difference Vegetation Index (NDVI) from the start year to the end year of each afforestation phase (evaluation period). We further evaluated the Persistence of Restoration Effectiveness (PRE) based on the MREI change trajectory during the whole evaluation period, and the Process-based Restoration Effectiveness Index (PREI) was developed to evaluate the restoration effectiveness at village scale. The results showed that MREI can effectively represent the trajectory of mangrove restoration and showed consistent pattern with high-spatial-resolution imagery. From 1990 to 2022, the mangrove forest area increased from 235.26 ha in 1990 to 873.27 ha in 2022, and 84.59% of the mangrove forest was converted from tidal flats in the reserve. The average value of MREI in the five evaluation phases were 0.48, 0.24, 0.29, 0.17, and 0.72, respectively. The dynamic change of MREI showed that 5.24% of the zones had poor PRE, 44.17% of the zones had excellent PRE. From the perspective of spatial distribution, the Zones with PREI values ranging from high to low were follows: Zone A, E, J, G, C, H, I (D), F, B. Overall, the high value zones of PREI were mainly distributed in the central of the Dandou Sea and the northern part of the Yingluo Bay. The low value zones were distributed in the northwest of the Dandou Sea. We expect the MREI and PREI have great potential to be applied to other regions to evaluate mangrove restoration effectiveness.

UTILIZATION OF LANDSAT 7 AND 8 IMAGES FOR MAPPING OF CHANGES IN THE NORTH COAST MANGROVE AREA, AESESA DISTRICT

<p>In 2019 there was damage to the mangrove forest which was converted into fish ponds by cutting down 200 hectares of mangrove land in Aeramo Village, which is the northern coastal area of Aesesa District, Nagekeo Regency. This study aims to map changes in mangrove areas and determine mangrove density values.This study uses the NDVI (Normalized Difference Vegetation Index) analysis technique to determine the density of mangrove vegetation in 2011, 2016 and 2021 using Landsat 7 and Landsat 8 imagery and uses an overlay analysis technique from the results of classifying mangrove density classes to determine changes in the area of mangrove areas. The results of the study show that the mangrove area on the north coast of Aesesa District shows density values that vary with The range of vegetation density index in Landsat 7 imagery in 2011 is from -0.573770464 to 0.54666682, in 2016 it has a vegetation density index range from -0.291984737 to 0.609456897 and in 2021 it has a vegetation density index range from -0.067266561 to 0.579148531 which is divided into 5 density classes namely; very rare, rare, moderate, rare and very tight. Based on the classification results, the results of changes in the mangrove area decreased to the medium class with forest area from 102.35 hectares to 66.86 hectares from 2011 to 2016 and experienced the largest increase in the very dense class in 2011-2016 where the forest area was in the very dense class. meeting from 128.86 hectares to 210.65 hectares.</p>

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.

Assessment of The Antropogenic Impact on Mangrove Ecosystem and Endemic Fauna in Muaragembong, Bekasi, West Java

The Muaragembong coast is degraded by anthropogenic factors such as pollution and ponds. The area that used to be a mangrove ecosystem is now experiencing abrasion. Trash trapped in the mangrove ecosystem also affects the ecosystem and its biodiversity. This research is descriptive in nature with the aim of knowing changes in mangrove areas through analysis of Landsat satellite imagery and identifying the causes of changes and impacts on endemic species. This research was conducted with the stages of literature study, analysis of satellite imagery in 2000, 2009, 2010, 2014, 2019 and 2020. Based on the analysis of satellite imagery, it was found that changes in mangrove area were confirmed with secondary data so that the factors that caused these changes were known. The results of the analysis show that the degradation of the mangrove ecosystem in 2017 was approximately 2800 ha and affected the existence of the Lutung Jawa (Trachypithecus auratus) as an endemic fauna in Muaragembong which inhabits the mangrove ecosystem on the north coast of Bekasi. It is currently estimated that there are no more than 50 present in the area, therefore the Lutung Jawa is considered a vulnerable species as cited in CITES Annex II 2008.

Dynamic Model of Segara Anakan Mangrove Crab’s Habitat Management, Indonesia

The mangrove area in Segara Anakan lagoon (Cilacap, Central Java) is a good habitat for mangrove crabs and other mangrove biota life and growth. However, in recent years, the condition of the mangroves in the area has been degraded due to land conversion. This condition also occurs in the production of mangrove crabs in the Cilacap Regency which has decreased (2012-2017 production data). Good management efforts of the mangrove forests will also have a good impact on the growth and production of these biota in nature. This study aims to create a dynamic model of mangrove crab habitat management at Segara Anakan Lagoon in order to increase the optimization of mangrove crab production in that regency. The study method used was a dynamic systems approach that considers the relationship between crab production and the conversion of mangrove land. The results of the study showed a model of the relationship between mangrove crab production and changes in mangrove area in the Segara Anakan area with the equation: Y = 14951X − 88357 (R2 = 0.5382), with structural validation as follows: land conversion increases (rice field area) (+) and then increase the income from rice fields (+). Meanwhile, land conversion reduces mangrove area (-), reduces crab habitat function (-), reduces crab catch (-), further reduces mud crab production, and finally reduces income from mud crab production (-). The validation of the model output is the average mean error (AME) of crabs at 4.93%, while the AME of mangroves is 7.38%. This model can be concluded as a valid (acceptable) model and can be continued to the simulation stage.

Utilization of the Indices to Detect and Monitor the Landcover Changes of Mangroves

Mangrove are a transitional ecosystem between land and sea along the coast and rivers that are influenced by tides. Information about mangroves is needed by using the use of cloud computing. The purpose of this study was to monitor mangroves and identify causes of changes in mangrove areas using NDVI (Normalized Difference Vegetation Index), MNDWI (Modified Normalized Vegetation Index), NDMI (Normalized Difference Vegetation Index), and GCVI (Green Chlorophyll Vegetation Index). The research method is Google Earth Engine with Random Forest Method approach. Based on this, we monitored changes in mangrove land cover in Karangsong Indramayu, Pandansari Kaliwlingi Brebes, Segara Anakan Cilacap for the period 1991-2021, 2011 and 2021. The results of this study are changes in mangrove area in Pandansari Kaliwlingi Brebes in 1991-2021 831.80 hectares, in 2011-2021 628.25 hectares, in 2001-2011 205.26 hectares but in 1991-2001 decreased by 1.71 hectares, for Karangsong Indramayu in 1991, 2001, 2011 and 2021 it decreased from 1991-2011 by 7.84 hectares, in 2001-2011 by 7.00 hectares, in 2011-2021 by 1.44 hectares. While in Segara Anakan in 1991-2001 it was 1384.14 hectares, in 2001-2011 it was 115.26 hectares, in 2011-2021 it was reduced to 850.12 hectares, in 1991-2021 it was 649.28 hectares.

Mapping of mangrove forest and carbon stock estimation of east coast Surabaya, Indonesia

Abstract. Hidayah Z, Rachman HA, As-Syakur AR. 2022. Mapping of mangrove forest and carbon stock estimation of east coast Surabaya, Indonesia. Biodiversitas 23: 4826-4837. The mangrove forests on Surabaya's east coast are an important protected area, providing habitat for a variety of marine organisms and water birds. This area is also vital for carbon storage and sequestration. The purpose of this research is to determine the changes in mangrove areas over the last 20 years and to calculate the amount of carbon stored in these mangrove forests. Changes in the area of mangrove forests and Normalized Difference Vegetation Indices (NDVI) were determined using Landsat-7 in 2000 and Landsat-8 in 2020. The vegetative carbon stock of mangrove stands was calculated using allometric measurements. The study results reveal that the mangrove forest area has increased significantly from 257.13 ha in 2000 to 753.48 ha in 2020. The results of regression models also show that NDVI has a significant influence on aboveground biomass (AGB), as indicated by the coefficient of determination (R2) = 0.7 (F test, df = 28, p-value < 0.05). The estimated aboveground and belowground carbon stock is 46.35 ± 13.65 ton C ha-1 and 13.65 ± 6.74 ton C ha-1 respectively. Accordingly, it is observed that the mangrove forest of East Coast Surabaya can sequester at least a total of 192.72 tons CO2 ha-1 in above and belowground biomass.

Spatio-temporal of mangrove vegetation based on the analysis of multi-temporal sentinel-2 satellite imageries at Jepara Regency, Indonesia

Mangrove areas in the northern coast of Jepara Regency have been threatened by coastal erosion and changes in land use since 1980. These areas represent coastal ecosystems with significant ecological, biological, and economic importance. The status of these ecosystems needs to be monitored; the latest condition is important to local authorities. Rate of change in mangrove conditions can be used to forecast the future condition of these coastal areas. This study aims to determine the temporal changes in the area and density of mangrove vegetation in Jepara Regency in 2017 and 2020. This study applied analysis of Sentinel 2-A multitemporal satellite imagery and classification using random forest on the Google Earth Engine platform. It was found that the mangrove area shrank from 103 ha in 2017 to 95 ha in 2020. The vegetations showed that changes in mangrove area in Jepara Regency have decreased in the rare and dense mangrove density types. The density of rare and dense mangroves experienced a decrease in area of 6 and 5 hectares, respectively. No mangroves with dense cover were found in 2020. Meanwhile, mangroves with moderate cover experienced an increase in area of 3 hectares in 2020 compared to last year 2017.

Temporal dynamics and land use in the marine protected area of Baía do Iguape in Northeastern Brazil

This study investigated land-use dynamics in a protected area and how dams and hydroelectric as anthropic tensors of spatial changes in mangrove areas, in addition to evaluating the spectral response for vegetative vigor, efficiently use radiation in the photosynthetic process and the flux of atmospheric carbon by vegetation indices. The temporal mapping and the transition of land use were evaluated between 1986 and 2020, using images from the Landsat 5 and Landsat 8 satellites using a visual interpretation technique. Spectral analysis of mangroves was performed using vegetation indices. The results showed that the establishment of the protected area decreased the rate of conversion from natural to anthropic areas, allowing natural areas to increase by 332 ha, driven by the increase in mangroves by 240 ha. Mangroves, dense ombrophilous forests, and grasslands are the classes that most transit between categories temporally. The combination of the dam and power generation reduced the flow to the estuary, causing an increase in saline intrusion, which contributed to the increase in the mangrove area in areas distant from anthropic activities, suggesting the maintenance of the protected area and the greater flow of atmospheric carbon.

Mangrove Cover in Jakarta: An Output of GNRM Program on Strengthening Lecturers and Students Awareness to the Sustainability of Jakarta Coastal Environment

Jakarta is very vulnerable to erosion and tidal flooding. Mangrove forest on the Jakarta coastal has a very important role because it can reduces the damage caused by seawater tidal flooding and erosion. However, the existence of mangrove forests is threatened by various natural factors, human activities and a combination of both. Given the important role of mangroves for the city, data and information on temporal changes in the distribution of mangrove cover in this area need to be monitored annually to evaluate changes in cover holistically. Therefore, this study was conducted to detect changes in the spatial and temporal distribution of mangroves on the Jakarta coastal. Landsat 7 ETM satellite image data from 2014 to 2018 were analyzed using medium resolution combined with visual interpretation and literature review to detect changes in mangrove areas. Mangrove forest cover was estimated at 111.58 hectares in 2014 and decreased to 103.84 hectares in 2018. That means Jakarta has lost 7.74 hectares over 4 years. This review article will also discuss the main factors that influence, changes in area, the impact of Jakarta Bay reclamation on North Jakarta's mangroves. Keywords: GNRM program, mangrove cover, Jakarta coast DOI: 10.7176/JESD/12-18-06 Publication date: September 30 th 2021

Monitoring the Land Cover Changes in Mangrove Areas and Urbanization using Normalized Difference Vegetation Index and Normalized Difference Built-up Index in Krabi Estuary Wetland, Krabi Province, Thailand

Krabi Estuary Wetland (KEW) is an outstanding wetland with an estuary environment. At present, the tourism industry has rapidly grown, resulting in the impact of land cover changes. This research aims to assess the changes that have occurred in the KEW from 1999 to 2020 using NDVI and NDBI for monitoring changes in mangrove areas and urbanization in Krabi Province, Thailand. Landsat satellite images in years 1999, 2009 and 2020 were classified by using a band ratio to create land cover maps. The results show that NDVI between 0.41–1.00 clearly shows the mangrove forest area, while NDBI between 0.01–0.40 shows urban and built-up land, and 0.41–1.00 appears as bare land. The NDVI overall accuracy assessment is 82.88%, 97.46% and 88.25% with Kappa values of 0.64, 0.92, and 0.85 for year 1999, 2009 and 2020, respectively. The NDBI overall accuracy assessment is 92.81%, 77.11% and 64% with Kappa values of 0.93, 0.77, and 0.63 for year 1999, 2009 and 2020, respectively. In addition, areas that are sensitive to land-cover change appear around the Chi rat River, Pak Nam Krabi River, and Yuan River, which are tourist areas close to the Krabi and Ao Nang communities. Therefore, it is necessary to speed up the problem solving and find measures to prevent mangrove forest degradation in these 3 mangrove forest areas so that the mangrove forest areas will not decrease rapidly in the future. This research can be valuable for land-cover management in the KEW by policy and decision makers.

Temporal and Spatial Analysis of Mangrove Forest Change in the North Coast of East Java

The north coast of East Java has high human activities and needs. These human needs include opening new land for housing areas, so that some mangrove areas have begun to be converted into residential areas. This can directly cause ecological impacts that threaten the sustainability of the coastal environment, but on the other hand, mangrove areas on the north coast of East Java are also developed as conservation and tourism areas. The purpose of this study is to determine changes in mangrove area and changes in coastlines in the northern coastal region of East Java during the period 2013 to 2019 based on Geographical Information Systems (GIS) using the Supervised-Maximum Likelihood image classification method. The results of this study showed that the largest change in mangrove forest area was in Sidoarjo Regency by 95%, while the lowest change in mangrove forest area was in Tuban Regency at 7.20%.

Assessing changes of mangrove forest in Bac Lieu Province using multi-temporal satellite images during 1988-2018

This study is done to determine the current status of mangrove forests (mangroves) in Bac Lieu Province over the years (1988, 1998, 2013 and 2018), assess the change in mangrove area over specific periods, and at the same time determine causes of disappear and recovery processes. Landsat 5-TM, 8-OLI remote sensing image and Maximum Likelihood Classifier - MCL method were used to classify and assess the changes in the area of mangrove forests in Bac Lieu Province over the period 1988-2018. The results of the image interpretation in 1988, 1998, 2013, 2018 and the overlapping of the above maps show the area of mangroves in Bac Lieu Province has increased continuously from 1988 to 2018. During the 30-year period from 1988 to 2018, the total mangrove area in Bac Lieu increased by 1,069.4 hectares, 1.5 times higher than the original. The recovery rate of mangroves was determined to be 64.3 ha/year, 2 times higher than their disappearance rate during this period (28,7 ha/year). The main reason to the disappearance of mangroves is the conversion from mangroves to aquaculture (accounting for 91.1%), coastal erosion (accounting for 7,9%). Mangroves are restored mainly from coastal seawater surface (accounting for 46,3%), from agricultural land (27.8%), planting mangroves in abandoned shrimp ponds or planting mangroves in combination with aquaculture (accounting for 25,8%).

ANALISIS PERUBAHAN LUAS HUTAN MANGROVE DAN FAKTOR YANG MEMPENGARUHINYA DI PULAU TANAKEKE KAB. TAKALAR

Knowing how the changes in the area of mangrove forest on Tanakeke Island, Takalar Regency in 1998 - 2018, Knowing the factors that influence changes in the area of mangrove forests on Tanakeke Island, Takalar Regency.Analysis of changes used is remote sensing image analysis. The imagery used is LANDSAT 5 TM satellite imagery acquisition in 1998, LANDSAT 7 + ETM satellite imagery acquisition in 2008 and LANDSAT 8 imagery OLI acquisition in 2018. Guided classification method with maximum like-lihood method is used to determine changes in mangrove forest area, while for activity factors humans that affect changes in mangrove area are analyzed in terms of percentage descriptions. The area of Tanakeke Island's mangrove forests in 1998 was 3,309.93 hectares, in 2008 it was 2,699.2 hectares, which was reduced by 621.91 hectares. And in 2018 the area will be 2,421.38 hectares and the total change in the area of mangove forests will be reduced by 908.55 hectares. The factors of human activity that affect changes in the area of mangrove forests most importantly is the conversion of mangrove forest land into ponds and uncontrolled collection of firewood for firewood.

Potentials of mangrove ecosystem as storage of carbon for global warming mitigation

Abstract. Dinilhuda A, Akbar AA, Jumiati, Herawati H. 2020. Potential of mangrove ecosystem as carbon storage for global warming mitigation. Biodiversitas 21: 5353-5362. The mangrove ecosystem in Karimunting Bay of West Kalimantan, Indonesia is one of the conservation areas with an area of 138.2 ha. Vegetation making up of that mangrove ecosystem is dominated by Avicennia marina. The existence of mangroves has a role in carbon storage. The ability to store carbon in mangrove forest ecosystems is four times greater than in other tropical forests around the world. Mangrove stems have the greatest ability in storing carbon by up to 55.52%. The research objective was to analyze the potential for carbon storage in the fringe mangrove ecosystem which was dominated by A. marina. This research method is based on a survey of vegetation density in the field. The survey was carried out in Karimunting Bay in three parts of the bay, north, central, and south. Each part of the bay consists of two locations, namely at the front of the breakwater towards the sea and behind the breakwater towards the land. Each location consisted of a plot of 10 x 10 with five replications. The vegetation parameters measured are the types of growth forms, the mangrove ecosystem species, and the diameter and height of the trees, as well as environmental parameters (pH, temperature, and salinity). Destructive method was used on A. marina stems for estimating analysis of mangrove carbon storage in the laboratory. A. marina stem samples were used to test the carbon content with LOI (Lost on Ignition) analysis. Analysis of changes in mangrove area is based on the 2009 and 2019 landscape images. The results show that the mangrove ecosystem of Karimunting Bay has a total density of 177,480 individuals/ha. The amount of carbon storage reached 99,231 mg/ha in 2019 and predictions of total carbon storage over the last 10 years are as much as 13,717,951 tons. Deposits of carbon in fringe mangrove illustrate the carbon dioxide absorption potential of 36,390,608 tons of CO2. The amount of CO2 absorption in fringe mangrove ecosystem type plays a role in reducing greenhouse gas (GHG) emissions with a conditional target according to the Nationally Determined Contribution (NDC) in 2030 of 834 million tons of CO2 to prevent temperature increases.

Analysis of mangrove forest changes as a natural beach protection in Surabaya, East Java Indonesia

Surabaya is the most populous city in East Java with high human activities and needs. These human needs include opening new land for residential areas so that some mangrove areas began to be converted into residential areas. This activity can directly cause ecological impacts and threaten the sustainability of the coastal environment. On the other hand, mangrove areas in Surabaya are also developed for conservation and tourism areas. The purpose of this study is to determine the changes in mangrove area in the Surabaya area during the period 2015 to 2019 based on GIS. This study is using maximum likelihood classification method then the area calculation is done by calculate geometric method. The results were obtained from 2015 to 2019 shows an area change every year. So far the exact cause is unknown, but the condition of area changes can occur due to several things, for example from the conversion of mangrove forests to residential areas, drainage needs in rivers or estuaries and stand growth.

Carbon stock losses and recovery observed for a mangrove ecosystem following a major hurricane in Southwest Florida

Studies integrating mangrove in-situ observations and remote sensing analysis for specific sites often lack precise estimates of carbon stocks over time frames that include disturbance events. This study quantifies change in mangrove area from 1985 to 2018 with Landsat time series analysis, estimates above and belowground stored carbon using field data, and evaluates aboveground carbon stock changes after the 2004 Category 4, Hurricane Charley, in J.N. “Ding” Darling National Wildlife Refuge. Two allometric equation methods yielding similar results were used to estimate aboveground carbon content in three mangrove species found in the refuge. Aboveground carbon contained 67 (SE = 2) MgC ha−1 with a total refuge estimate of 74,504 MgC in 2018. Sediment contained 259 (SE = 28) MgC ha−1 for a total of 288,008 MgC in the refuge. The initial reduction in mangrove area caused by Hurricane Charley was between 0.6% and 5.3%, equivalent to between 427 MgC and 3,599 MgC under three different scenarios of carbon loss. As a result of the hurricane, approximately 61 ha of mangroves were disturbed, of which 24 ha had recovered by 2018, with 37 ha (~3% of the pre-hurricane mangrove area) still not recovered 14 years after the event. The 37 ha of mangroves that have not recovered are located in a tidally restricted area of the refuge. A longer recovery time in this area will likely result in a greater loss of carbon storage than in the rest of the refuge.