Predicting changes in molluscan spatial distributions in mangrove forests in response to sea-level rise

Molluscs are an important component of the mangrove ecosystem, and the vertical distributions of molluscan species in this ecosystem are primarily dictated by tidal inundation. Thus, sea-level rise (SLR) may have profound effects on mangrove mollusc communities. Here, we used two dynamic empirical models based on measurements of surface elevation change, sediment accretion and zonation patterns of molluscs to predict changes in molluscan spatial distributions in response to different sea-level rise rates in the mangrove forests of Zhenzhu Bay (Guangxi, China). The change in surface elevation was 4.76–9.61 mm a during the study period (2016–2020), and the magnitude of surface-elevation change decreased exponentially as original surface elevation increased. Based on our model results, we predicted that mangrove molluscs might successfully adapt to a low rate of SLR (marker-horizon model: 2–4.57 mm a; plate model: 2–5.20 mm a) by 2100, with molluscs moving seaward and those in the lower intertidal zones expanding into newly available zones. However, as SLR rate increased (marker-horizon model: 4.57–8.14 mm a; plate model: 5.20–6.88 mm a), our models predicted that surface elevations would decrease beginning in the high intertidal zones and gradually spreading to the low intertidal zones. Finally, at high rates of SLR (marker-horizon model: 8.14–16.00 mm a; plate model: 6.88–16.00 mm a), surface elevations were predicted to decrease across the elevation gradient, with molluscs moving landward and species in higher intertidal zones would be blocked by landward barriers. Tidal inundation and the consequent increase in interspecific competition and predation pressure were predicted to threaten the survival of many molluscan groups in higher intertidal zones, especially species at the landward edge of the mangroves. Thus, future efforts to conserve mangrove floral and faunal diversity should prioritize species restricted to landward mangrove areas.

Assessing the Effect of Age and Geomorphic Setting on Organic Carbon Accumulation in High-Latitude Human-Planted Mangroves

Mangroves are highly productive blue carbon ecosystems that preserve high organic carbon concentrations in soils. In this study, particle size, bulk elemental composition and stable carbon isotope were determined for the sediment cores collected from the landward and seaward sides of two mangrove forests of different ages (M1, ca. 60; M2, ca. 4 years old) to determine the effects of geomorphic setting and age (L1 = old mangrove and S1 = salt marsh stand in M1; L2 = young mangrove and S2 = bare mudflat in M2) on sediments and organic carbon accumulation. The objective of this study was to determine the feasibility of the northernmost human-planted mangroves in China to accumulate sediment and carbon. Our results showed that fine-grained materials were preserved well in the interior part of the mangroves, and the capacity to capture fine-grained materials increased as the forest aged. The biogeochemical properties (C/N: 5.9 to 10.8; δ13C: −21.60‰ to −26.07‰) indicated that the local organic carbon pool was composed of a mixture of autochthonous and allochthonous sources. Moreover, the accumulation of organic carbon increased with the forest age. The interior part of the old mangrove had the highest organic carbon stock (81.93 Mg Corg ha−1). These findings revealed that mangrove reforestation had positive effects on sediments and organic carbon accretion.

Spatiotemporal variations in length-weight relationship, growth pattern and condition factor of Periophthalmus variabilis Eggert, 1935 in Vietnamese Mekong Delta

Length-weight relationship (LWR), growth pattern and condition factor (CF) play a vital role in fish resource evaluation and management but data on this is limited for Periophthalmus variabilis. This is an amphibious fish that lives in the mudflats of the mangrove forests in the Western Pacific regions, including the Vietnamese Mekong Delta (VMD). This paper contributes to the understanding of the LWR, growth pattern and CF of P. variabilis. Fish specimens were collected by hand at four sites in the VMD from April 2020 to March 2021. The analysis of 495 individual fish (259 females and 236 males) showed that fish weight could be estimated from a given fish length due to high determination values (r2 = 0.70 − 0.97). Dusky-gilled mudskippers of the VMD exhibited positive allometry, as indicated by their larger than 3 b value (b = 3.094 ± 0.045, p = 0.04). However, the growth pattern of the mudskipper between the sex and maturation stage (immature versus mature) showed isometry. These fish displayed positive allometry in the dry season (b = 3.138 ± 0.065) (>3, p = 0.04) but isometry in the wet season (b = 3.058 ± 0.061) (≈3, p = 0.34). Fish growth ranged from isometry to positive allometry and varied by site (b = 2.850 ± 0.103–3.370 ± 0.114) and month (b = 2.668 ± 0.184–3.588 ± 0.299) based on the b value. The CF of P. variabilis was not affected by sex (p = 0.29), body size (p = 0.64) or season (p = 0.43), but was affected by site (p = 0.01) and month (p = 0.01). The CF of this species (1.05 ± 0.02) was higher than 1 (p < 0.001), indicating that the fish adapted well to their habitat.

Spatial Evolution of Coastal Tourist City Using the Dyna-CLUE Model in Koh Chang of Thailand during 1990–2050

Spatial evolution can be traced by land-use change (LUC), which is a frontier issue in the field of geography. Using the limited areas of Koh Chang in Thailand as the research case, this study analyzed the simulation of its spatial evolution from a multi-scenario perspective on the basis of the 1900–2020 thematic mapper/operational land imager (TM/OLI) remote sensing data obtained through the transfer matrix model, and modified LUC and the dynamic land-use change model (Dyna-CLUE). Over the past 30 years, the expansion of recreation areas and urban and built-up land has been very high (2944.44% and 486.99%, respectively) along the western coast of Koh Chang, which replaced the original mangrove forests, orchards, and communities. Logistic regression analysis of important variables affecting LUC revealed that population density variables and coastal plain topography significantly affected LUC, which showed strong β coefficients prominently in the context of a coastal tourist city. The results of the LUC and logistic regression analyses were used to predict future LUCs in the Dyna-CLUE model to simulate 2050 land-use in three scenarios: (1) natural evolution scenario, where a large patch expansion of agricultural land extends along the edge of the entire forest boundary around the island, particularly the southwestern areas of the island that should be monitored; (2) reserved area protection scenario, where the boundary of the conservation area is incorporated into the model, enabling forest preservation in conjunction with tourism development; and (3) recreation area growth scenario, where the southern area is the most susceptible to change at the new road crossing between Khlong Kloi village to Salak Phet village, and where land-use of the recreation area type is expanding. The model-projected LUC maps provide insights into possible changes under multiple pathways, which could help local communities, government agencies, and stakeholders jointly allocate resource planning in a systematic way, so that the development of various infrastructures to realize the potential impact on the environment is a sustainable coastal tourist city development.

Land cover classification using Landsat 8 OLI in West Langsa Sub district, Langsa City

Land cover information is needed by various parties as a consideration in controlling land cover changes. The latest land cover information can be obtained using remote sensing techniques in the form of image classification maps. This technique is very effective in monitoring land cover because of its ability to quickly, precisely, and easily provide spatial information on the earth’s surface. The purpose of this study was to classify land cover in West Langsa Sub district, Langsa City using Landsat 8 OLI (Operational Land Imager) imagery. The classification method used in this study is the maximum likelihood classification (MLC) method. There are several considerations of various factors in the MLC method, including the probability of a pixel to be classified into a certain type or class. The results of Landsat 8 OLI image classification in West Langsa Sub district resulted in 6 land cover classes, namely mangrove forests, settlements, rice fields, shrubs, ponds and bodies of water. The largest land cover class is ponds with an area of 1981.54 ha (38.71%) and the smallest land cover is rice fields with an area of 115.58 ha (2.26%) of the total land cover class. Classification accuracy is indicated by the overall accuracy and kappa accuracy of 91.15% and 82.75%, respectively. These results meet the requirements set by the USGS (Overall Accuracy > 85%) and indicate that the Landsat 8 OLI image classification map can be used for various purposes.

Spectral Reflectance-Based Mangrove Species Mapping from WorldView-2 Imagery of Karimunjawa and Kemujan Island, Central Java Province, Indonesia

Mangrove mapping at the species level enables the creation of a detailed inventory of mangrove forest biodiversity and supports coastal ecosystem management. The Karimunjawa National Park in Central Java Province is one of Indonesia’s mangrove habitats with high biodiversity, namely, 44 species representing 25 true mangroves and 19 mangrove associates. This study aims to (1) classify and group mangrove species by their spectral reflectance characteristics, (2) map mangrove species by applying their spectral reflectance to WorldView-2 satellite imagery with the spectral angle mapper (SAM), spectral information divergence (SID), and spectral feature fitting (SFF) algorithms, and (3) assess the accuracy of the produced mangrove species mapping of the Karimunjawa and Kemujan Islands. The collected field data included (1) mangrove species identification, (2) coordinate locations of targeted mangrove species, and (3) the spectral reflectance of mangrove species measured with a field spectrometer. Dendrogram analysis was conducted with the Ward linkage method to classify mangrove species based on the distance between the closest clusters of spectral reflectance patterns. The dendrogram showed that the 24 mangrove species found in the field could be grouped into four levels. They consisted of two, four, and five species groups for Levels 1 to 3, respectively, and individual species for Level 4. The mapping results indicated that the SID algorithm had the highest overall accuracy (OA) at 49.72%, 22.60%, and 15.20% for Levels 1 to 3, respectively, while SFF produced the most accurate results for individual species mapping (Level 4) with an OA of 5.08%. The results suggest that the greater the number of classes to be mapped, the lower the mapping accuracy. The results can be used to model the spatial distribution of mangrove species or the composition of mangrove forests and update databases related to coastal management.

Surface Elevation Changes Estimation Underneath Mangrove Canopy Using SNERL Filtering Algorithm and DoD Technique on UAV-Derived DSM Data

Estimating surface elevation changes in mangrove forests requires a technique to filter the mangrove canopy and quantify the changes underneath. Hence, this study estimates surface elevation changes underneath the mangrove canopy through vegetation filtering and Difference of DEM (DoD) techniques using two epochs of unmanned aerial vehicle (UAV) data carried out during 2016 and 2017. A novel filtering algorithm named Surface estimation from Nearest Elevation and Repetitive Lowering (SNERL) is used to estimate the elevation height underneath the mangrove canopy. Consequently, DoD technique is used to quantify the elevation change rates at the ground surface, which comprise erosion, accretion, and sedimentation. The significant findings showed that region of interest (ROI) 5 experienced the highest volumetric accretion (surface raising) at 0.566 cm3. The most increased erosion (surface lowering) was identified at ROI 8 at −2.469 cm3. In contrast, for vertical change average rates, ROI 6 experienced the highest vertical accretion (surface raising) at 1.281 m. In comparison, the most increased vertical erosion (surface lowering) was spotted at ROI 3 at −0.568 m. The change detection map and the rates of surface elevation changes at Kilim River enabled authorities to understand the situation thoroughly and indicate the future situation, including its interaction with sea-level rise impacts.

Edukasi Eksistensi dan Keberlanjutan Ekosistem Hutan Mangrove untuk Remaja

Indonesia has 3.4 million hectares or 24% of the world's 13.8 million hectares of mangrove forests. In its development, Indonesia's mangrove area continues to decline and it is recorded that an area of ​​637,624 hectares (18.95%) is in critical condition due to canopy cover which is less than 60%. Mangrove forests can absorb large waves including tsunamis, prevent abrasion, absorb carbon dioxide 5 times greater than tropical forests in the highlands, and are a habitat for several types of wildlife. Thus, Indonesia has a very significant role in the existence and sustainability of the world's mangrove forests. Based on 2018 data, DKI Jakarta Province has 300 hectares or about 10.7% of the total mangrove forest in Indonesia which is spread in the Angke Kapuk Nature Park, Muara Angke Wildlife Sanctuary, Angke Kapuk Protection Forest and Kamal Muara Production Forest as well as part of the last remaining mangrove forest in DKI Jakarta province. Based on this phenomenon, efforts are needed to maintain the existence and sustainability of mangrove forests, especially in the city of Jakarta. One of the important actors in this effort is the youth with growing awareness of environmental issues. Teenagers as future milestone holders need to understand the importance of the existence and sustainability of mangrove forests. The problem faced is the need for an educational activity that is by the characteristics of adolescents. Therefore, the implementing team initiated education on the existence and sustainability of the mangrove forest ecosystem for youth (12-24 years old) in Tanjung Gedong Village who are members of the At-Taufiq Tanjung Gedong Mosque Youth with an Experiential Learning Discovery Journey approach which was carried out in 3 (three) stages, namely the introduction stage by providing infographics and videographics materials, the observation stage with a visit to the Mangrove Nature Tourism Park, Angke Kapuk, North Jakarta; and the reflection stage through reflection instruments filled out by partners. Based on the results of the activity, it is known that all respondents have theoretical experience about the existence and sustainability of mangrove forests obtained from the school. Community service activities (PkM) provide new experiences in the creative process to understand the topic of PkM, namely the existence and sustainability of mangrove forest ecosystems in Jakarta. Abstrak Indonesia memiliki 3,4 juta hektar atau 24% dari total 13,8 juta hektar hutan mangrove dunia. Dalam perkembangannya, luas mangrove Indonesia terus mengalami penurunan dan tercatat seluas 637.624 hektar (18,95%) dalam kondisi kritis karena penutupan tajuk yang kurang dari 60%. Hutan mangrove bermanfaat untuk meredam gelombang besar termasuk tsunami, mencegah abrasi, menyerap karbondioksida 5 kali lebih besar daripada hutan tropis di dataran tinggi, dan sebagai habitat bagi beberapa jenis satwa liar. Dengan demikian, Indonesia memiliki peranan yang sangat signifikan bagi eksistensi dan keberlanjutan hutan mangrove dunia. Berdasarkan data tahun 2018, Propinsi DKI Jakarta memiliki 300 hektar atau sekitar 10,7% dari total hutan mangrove di Indonesia yang tersebar di Taman Wisata Alam Angke Kapuk, Suaka Margasatwa Muara Angke, Hutan Lindung Angke Kapuk dan Hutan Produksi Kamal Muara sekaligus merupakan bagian dari hutan mangrove terakhir yang tersisa di provinsi DKI Jakarta. Berdasarkan fenomena tersebut, maka diperlukan upaya untuk menjaga eksistensi dan keberlanjutan hutan mangrove khususnya di Kota Jakarta. Salah satu aktor penting dalam upaya tersebut adalah kalangan remaja dengan tumbuhnya kesadaran akan isu lingkungan. Remaja sebagai pemegang tonggak masa depan perlu memahami pentingnya eksistensi dan keberlanjutan hutan mangrove. Permasalahan yang dihadapi adalah perlunya sebuah kegiatan edukasi yang sesuai dengan karakteristik bagi remaja. Oleh karena itu, tim pelaksana menginisiasi edukasi eksistensi dan keberlanjutan ekosistem hutan mangrove bagi remaja (berusia 12 – 24 tahun) di Kampung Tanjung Gedong yang tergabung dalam Remaja Masjid At-Taufiq Tanjung Gedong dengan pendekatan Experiential Learning Discovery Journey yang dilaksanakan dalam 3 (tiga) tahap, yaitu tahap pengenalan dengan memberikan materi infografis dan videografis, tahap observasi dengan kunjungan ke Taman Wisata Alam Mangrove, Angke Kapuk, Jakarta Utara; dan tahap refleksi melalui instrumen refleksi yang diisi oleh mitra. Berdasarkan hasil kegiatan, diketahui seluruh responden telah memiliki pengalaman teoretis tentang eksistensi dan keberlanjutan hutan mangrove yang diperoleh dari bangku sekolah. Kegiatan pengabdian kepada masyarakat (PkM) memberikan pengalaman baru dalam proses kreatif untuk memahami topik PkM yaitu eksistensi dan keberlanjutan ekosistem hutan mangrove di Jakarta.

Mangrove Vegetation Mapping Using Sentinel-2A Imagery Based on Google Earth Engine Cloud Computing Platform

Mangroves are trees whose habitat is affected by tides, and their presence has decreased from year to year. Today, mapping technology has undergone many developments, including the availability of images of various resolutions and cloud-based image processing. One of the popular platforms today is the Google Earth Engine. Google Earth Engine is a cloud-based platform that makes it easy to access high-performance computing resources for extensive processing. The advantage of using Google Earth Engine is that users do not have to be IT experts without experts in application development, WEB programming, and HTML. This study aims to conduct a study on mangrove mapping in Gili Genting District with Sentinel-2A imagery using a Google Earth Engine. This location was chosen since there are still many mangroves, especially on the Gili Raja and Gili Genting Islands. From this research, it can be concluded that cloud computing-based Sentinel-2A image processing shows that the vegetation value of NDVI results ranges from -0.923208 to 0.75579. The classification results show that mangrove forests' overall presence on Gili Genting Island is more expansive than Gili Raja Island with 16.74 ha and 14.75 ha. The use of the Google Earth Engine platform simplifies the analysis process because image processing can be done once with various scripts so that analysis becomes faster.