Coastal Vegetation Research Articles

POTENTIAL OF CARBON SINK IN MANGROVE SUBSTRATES IN LEMBAR BAY, WEST LOMBOK, INDONESIA

Mangroves are one of the coastal vegetation that can mitigate carbon (carbon sink and carbon storage). This study aimed to determine the potential for soil carbon stock found under stands of mangroves in Lembar Bay, West Lombok, and West Nusa Tenggara. The research began with the identification of the species and then proceeded toa sampling of the soil, which was then analyzed using the Walkley and Black method. The results showed that there were ten species of mangroves, namely, Rhizophora stylosa, Avicennia lanata, Avicennia marina, Bruguiera gymnorrhiza, Ceriops decandra, Excoecaria agallocha, Lumnitzera racemosa, Scyphiphora hydrophyllacea, Thespesia populnea, and Xylocarpus maluccensis. The highest soil carbon content percentage was found in the lower soil of the A. lanata (1.43 %C) mangrove, and the lowest was found in the lower-stand soil of E. agallocha (0.21 %C). Meanwhile, the carbon sinks per meter were 0.002-0.066 gC/m2, with an average of 0.020±0.020 gC/m2. The estimated total soil carbon sink in 10 mangrove stands was 0.20-6.60 tons C/ha, with an average of 2.18±2.010 tons C/ha. The average total estimated soil carbon stock found in 20.49 ha of the mangrove area studied was 44.67 tonsC, which is equivalent to 263.69 tonsC in a mangrove area of ​​120.96 ha in Lembar Bay.

Numerical simulations of breaking wave propagation through the vegetation on a slope based on a drag coefficient prediction model

Coastal vegetation plays a key role in wave attenuation on sloping beaches. However, accurately predicting the vegetation-related drag coefficient (CD) under breaking waves on slopes remains a challenge. In this study, the Reynolds-averaged Navier–Stokes equations were modified by incorporating a vegetation resistance term to consider the vegetation-induced momentum loss. The stabilized k-ω shear stress transport turbulence model was improved by introducing the vegetation-induced turbulence generation and dissipation terms. The numerical model was validated by two laboratory experiments. Based on experimental wave height data, the CD was determined via a calibration method. The numerical results were found to be highly sensitive to the CD. The calibrated CD achieved excellent agreement with experimental data (RMSE < 0.2). In addition, the calibrated CD showed a high correlation (R2 = 0.85) with the Iribarren number ξ. Finally, a CD prediction formula expressed by the combination of Reynolds number and ξ was proposed via regression analysis, and its performance was evaluated by two additional cases. The limitations and applicability of the CD prediction formula were also discussed. The proposed numerical model and CD prediction formula have the potential to be useful for the numerical simulation of wave interactions with vegetation on slopes.

Diminishing Coastal Vegetation in Parts of Rivers State: An Emphasis on Mangrove Depletion

Diminishing Coastal Vegetation in Parts of Rivers State: An Emphasis on Mangrove Depletion

The Remarkable Diversity of Parasitic Flowering Plants in Colombia

Parasitic plants have evolved independently in 12 Angiosperm orders. Nine of them (Boraginales, Cucurbitales, Ericales, Lamiales, Laurales, Malvales, Santalales, Solanales, and Zygophyllales) are represented in Colombia by 17 families, 44 genera and 246 species, including facultative (37) and obligate (187) hemiparasites, holoexoparasites (19) and holoendoparasites (3). Cladocolea coriacea (Loranthaceae) is reported for the first time in Colombia. One genus (Sanguisuga, Cytinaceae) and 69 species (28.04%) are endemic to the country. Endemism decreases with elevation, ranging from 26 species (37.68%) below 1000 m, to one species (1.44%) above 4000 m. Speciation in Aetanthus, Psittacanthus and Tristerix (Loranthaceae), Dendrophthora and Phoradendron (Viscaceae), and Castilleja and Neobartsia (Orobanchaceae) was likely prompted by the Andean uplift. The highest number of species (169) are found in the Andean Region, whereas the Orinoco Region contains the lowest number (29). Dry forests and thickets, and coastal vegetation of the Caribbean Region are the preferred ecosystems for Krameria (Krameriaceae), Sanguisuga, Acanthosyris (Cervantesiaceae), Maracanthus (Loranthaceae), Ximenia (Ximeniaceae), Lennoa (Ehretiaceae), and Anisantherina (Orobanchaceae). Orobanche minor, recently introduced to the country, is the only potential weed for crops between 2500 and 3200 m in the Eastern Cordillera. Convergent lifeforms include: the obligate, twining stem holoparasitic Cassytha (Lauraceae) and Cuscuta (Convolvulaceae); the root holoexoparasitic Sanguisuga, Mitrastemon (Mitrastemonaceae), all Balanophoraceae, and Lennoa; and the root obligate hemiparasitic Krameria, Gaiadendron (Loranthaceae), and all Cervantesiaceae, Opiliaceae, Schoepfiaceae, Strombosiaceae and Ximeniaceae. Holoendoparasitism occurs only in Apodanthaceae, whereas root facultative hemiparasitism is restricted to the Orobanchaceae.

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.

Modelling of drifting object dispersion in linear wave-induced flow

The dispersal of drifting objects like plant propagule under wave action can provide important information for the restoration of the plant community in coastal areas. An improved motion equation of the drift under wave action is established by coordinate transformation under the premise that the buoyancy is always perpendicular to the free surface, considering the variation of submerged height and the pressure gradient. Its numerical solution obtained by the fourth order Runge-Kutta method was compared with the experimental results in the literature, and the rationality of the improved motion equation is then verified. Then the perturbation method and Lagrange tracking principle were used to obtain the average longitudinal drift velocity expressed by Stokes drift velocity. The effect of different forces in the motion equations to the longitudinal diffusive motion was analyzed. Finally, the hydrodynamic coefficients affecting the prediction were analyzed, and the results show that the effects of the added mass coefficient and the drag coefficient are mainly reflected in the region with higher wave heights. The findings may provide certain scientific guidance for the restoration of coastal vegetation ecology through natural colonization.

A new model for quantifying wave damping by vegetation in combined wave–current flow

The propagation of waves in nearshore areas is often accompanied by the presence of tidal currents, which have an impact on the dissipation of wave energy in coastal vegetation regions. However, the existing models generally do not consider the in-canopy velocity, resulting incomplete energy dissipation terms and thus inaccurate estimation of drag coefficients. In this study, we developed a new analytical model to incorporate vertical velocity distribution and full energy dissipation terms in energy flux balance equation. This model is applied to interpret the data from a new flume experiment of vegetation in combined wave-current flows. New CD-Re relationships were derived by applying the new model. Additionally, we extracted the wave energy passage time and decay rate from both the experimental data and the model results, which shows that the wave energy passage time of opposing currents is up to 75% longer than that of following currents. This disparity in passage time is the primary factor contributing to the greater wave dissipation observed in the cases of opposing currents. This study offers novel insights into the process of wave dissipation, and can potentially improve our capability in predicting wave dissipation.

A multi-proxy reconstruction of the late Holocene vegetation dynamics in Krabi mangroves, Thailand Andaman Sea

Pollen, charcoal, loss on ignition, geochemistry, and geophysical analyses were used to reveal the palaeoenvironment, vegetation, and sedimentary dynamics of the Krabi mangroves and the Andaman coast during the late Holocene. Two sediment cores, radiocarbon dated to ∼4400 cal BP, were collected from the Nai Nang mangroves in Krabi Province, the Thailand Andaman coast. This analysis documented how the area evolved from a tidal channel to a tidal area dominated by mangrove ecosystems. During the tidal channel phase (∼4400–2700 cal yr BP), the study site was characterized by a high-energy depositional environment, where sediment accumulated along tidal channels. Mangrove development began around 4400 cal yr BP and was influenced by varying contributions from tidal and freshwater inputs. Sea level during this period showed a slight rise until ∼4200 cal yr BP, followed by a subsequent fall. From ∼2700 to 1050 cal yr BP, the tidal channel was filled with finer sediments, forming intertidal flats that supported mangroves, back mangroves, and freshwater forest taxa, indicating a transition to mixed coastal vegetation. Sea levels remained relatively low during this period. From around 1050 cal yr BP to the present, mangroves replaced the previous mixed coastal vegetation, most likely driven by rising sea levels, particularly during the last 200 years. The observed sedimentation rates indicate that mangroves in Krabi will need to undergo continued future landward migration to adapt to changing coastal conditions, given the current and projected global sea-level rise.

Coastal vegetation responses to large dam removal on the Elwha River

IntroductionLarge dam removals provide a restoration opportunity for shrinking coastal wetland habitats. Dam removal can increase sediment delivery to sediment-starved river deltas and estuaries by restoring natural sediment transport and mobilizing reservoir-impounded sediment. However, rapid mobilization of massive quantities of sediment stored behind large dams also constitutes a major ecological perturbation. Information is lacking on coastal habitat responses to sediment pulses of this magnitude.MethodsRemoval of two large dams along the Elwha River (Washington, USA) in 2011–2014 released ~20.5 Mt of impounded sediment, ~5.4 Mt of which were deposited in the delta and estuary (hereafter, delta). We used time series of aerial imagery, digital elevation models, and vegetation field sampling to examine plant community responses to this sediment pulse across seven years during and after dam removal.ResultsBetween 2011 and 2018, the Elwha River delta increased by ~26.8 ha. Vegetation colonized ~16.4 ha of new surfaces, with mixed pioneer vegetation on supratidal beach, river bars, and river mouth bars and emergent marsh vegetation in intertidal aquatic habitats. Colonization occurred on surfaces that were higher and more stable in elevation and farther from the shoreline. Compared to established delta plant communities, vegetation on new surfaces had lower cover of dominant species and functional groups, with very low woody cover, and lower graminoid cover than dunegrass and emergent marsh communities. Over time following surface stabilization, however, vegetation on new surfaces increased in species richness, cover, and similarity to established communities. By 2018, ~1.0 ha of vegetation on new surfaces had developed into dunegrass or willow–alder communities and ~5.9 ha had developed into emergent marsh. At the same time, dam removal had few discernible effects on established delta plant communities.DiscussionTogether, these results suggest that rapid sediment mobilization during large dam removal has potential to expand coastal wetland habitat without negatively affecting established plant communities. However, as sediment loads declined in 2016–2018, new delta surfaces decreased by ~4.5 ha, and ~1.6 ha of new vegetation reverted to no vegetation. Long-term persistence of the expanded coastal habitat will depend on ongoing erosional and depositional processes under the restored natural sediment regime.

From coastal geomorphometry to virtual environments

Communicating environmental change and mitigation scenarios to stakeholders and decision-makers can be challenging. Immersive environments offer an innovative approach for knowledge transfer, allowing science-based scenarios to be discussed interactively. The use of such environments is particularly helpful for the analysis of large, multi-component geospatial datasets, as commonly employed in the classification of ecosystems. Virtual environments can play an important role in conveying and discussing the findings gathered from these geomorphometric datasets. However, textured meshes and point clouds are not always well suited for direct import to a virtual reality or the creation of a truly immersive environment, and often result in geometrical artifacts, which can be misinterpreted during the import to a game engine. Such technical hurdles may lead to viewers rejecting the experience altogether, failing to achieve a higher educational purpose. In this study, we apply an asset-based approach to create an immersive virtual representation of a coastal environment. The focus hereby is on the coastal vegetation and changes in species distribution, which could potentially be triggered by the impact of climate change. We present an easy-to-use blueprint for the game engine EPIC Unreal Engine 5. In contrast to traditional virtual reality environments, which use static textured mesh data derived from photogrammetry, this asset-based approach enables the use of dynamic and physical properties (e.g. vegetation moving due to wind or waves), which makes the virtual environment more immersive. This will help to stimulate understanding and discussion amongst different stakeholders, and will also help to foster inclusion in earth- and environmental science education.

A GLOBAL CHARACTERISATION OF COASTAL REGIONS TO GUIDE NATURE-BASED SOLUTIONS TO SEA TURTLE NESTING BEACHES

Sea turtles are an important part of marine and coastal ecosystems around the world. Yet, six of seven sea turtle species are endangered (IUCN, 2021). While they spend most of their lives at sea, female turtles use sandy beaches as nesting habitat, where they dig their nests in the sand to incubate for up to two months. A major challenge to sea turtles is the degradation of their nesting beaches due to anthropogenic climate-change effects, such as accelerated sea level rise (SLR) and anomalous storm activity. While it is still uncertain how sandy beaches will respond to SLR, beaches backed by hard structures cannot migrate landward, leading to ‘coastal squeeze’—the erosion and consequential narrowing of beaches. Increased storm activity may lead to persistently high water levels at nesting beaches, resulting in the flooding or even erosion of incubating nests. Moreover, beach erosion during storms can bury nests under excessive sand and limit beach access through the formation of scarps. Nature-based solutions—for example in the form of turtle-friendly design of beaches along new land reclamations or by adding coastal vegetation or reefs to limit runup and reduce erosion on existing beaches—may offer promising opportunities to preserve and even expand global habitats for turtle nesting.

EXPANDING COASTSAT SHORELINE DETECTION ALGORITHM TO TRACK COASTAL VEGETATION AND URBAN CHARACTERISTICS FROM SATELLITE DATA

Classical survey methods involve making in situ measurements of shoreline locations, which can never scale to the time spans and spatial extent necessary to cover large coastal areas. For 50 years now, satellites have provided images of the earth with reasonable resolution that can provide some insight into shoreline evolution over large timescales and wide areas. Determining shoreline location from satellite imagery involves a general pipeline of image pre-processing, segmentation of the image into water and beach, and then determination of the shoreline location. The goal of the research here is to expand the capabilities of CoastSat to include identification of coastal vegetation and tracking of vegetated shoreline evolution. Accurate measurements of coastal vegetation extent and evolution from satellites may help our understanding of the health of shoreline ecosystems as sea levels rise and storms become more intense. Shoreline trends observed from satellite imagery will provide information to coastal communities that can be used for effective spatial planning, sustainable coastal development, coastal engineering projects, and mitigation of climate change impacts.

Methanogens limited to lower rhizosphere and to an atypical salt marsh niche along a pristine intertidal mangrove continuum

AbstractMangroves are valuable ecosystems that facilitate primary production, carbon sequestration, and regulation of greenhouse gas (GHG) cycles in coastal sediments, with microorganisms playing key roles. Specialized bacteria and archaea compete for energy and resources in mangrove sediments to inhabit optimal ecological niches and can produce or consume methane (CH4)—a potent GHG—in the process. CH4 cycling in mangroves has gained growing attention, yet uncertainties regarding functional and spatial distributions of microorganisms remain. Here, we demonstrate that in a pristine mangrove forest, CH4 concentrations and methanogen communities are concentrated within lower or below rhizosphere depths. We also reveal atypical niches for methanogens in the upper tidal salt marsh zone where vegetation is sparse and highest methanogens abundances were detected at deepest depths (4715 reads g−1) despite relatively high redox potentials (&gt; 250 mV). Pore water CH4 concentrations were highest at the deepest depth within the mangrove forest (max. 3.40 ± 0.21 μM) and coincided with the highest sediment CH4 fluxes (276.4 ± 54.2 μmol m−2d−1) and methanotroph abundances at the surface (1309 reads g−1). Sediment CH4 oxidation fractions between the deepest (60 cm) and shallowest (5 cm) depths were estimated between 18.8% and 64.9%. Positive correlation between crab burrows and CH4 fluxes suggests that CH4 from deeper sediment and salt marsh niches can be transported via conduits to the atmosphere. The spatial data from this study highlights the importance of investigating CH4 dynamics across estuarine ecosystem gradients to better understand the complex roles of vital coastal vegetation zones in the face of a changing climate.

Impact of Urban Expansion on Coastal Vegetation Conservation in Buffalo City Metropolitan Municipality, South Africa

The ethical clearance certificate number for this research is KUL011SOLA01. This research elucidates the conceptualization of urbanization, urban sustainability, merits of coastal vegetation, and threats to urban expansion. Furthermore, this paper focuses on the analysis of the questionnaire, of which 300 copies were distributed to different categories of individuals in the study area, out of which a total of 254 copies were returned. The results revealed that 197 (80.7%) respondents confirmed the occurrence of environmental challenges, 33 (13.5%) others stated otherwise, while 14 (5.7%) claimed ignorance. Further, the researcher sought to know the causes of coastal vegetation loss; 190 (74.8%) respondents blamed it on urban expansion, 169 (66.8%) respondents stated it was due to deforestation activities. Other views cited by the respondents in this regard and their corresponding frequencies are as follows: bush fires (132/52.0%) and conversion of ecosystem land uses for crop cultivation (112/44.1%).

Floristic similarity of lycophytes and ferns in the Amazonia/Cerrado transition zone in the central region of northern Maranhão state, Brazil

Floristic similarity studies make it possible to compare species richness between different phytophysiognomies and to assess whether species are typical of a phytophysiognomies or if they are common to two or more phytophysiognomies. The Immediate Geographic Region of São Luís (IGR), in the central region of northern Maranhão, is characterized by the presence of Amazonia, Cerrado, and coastal vegetation phytophysiognomies. The objectives of this work were to verify if the fern and lycophyte species in the IGR are similar to those in another Amazonia and Cerrado phytophysiognomies in Maranhão and Brazil. Sixty-three species of lycophytes and ferns were identified, with a predominance of individuals in the families Pteridaceae and Polypodiaceae. A similarity analysis indicated the study area has a greater affinity with the Amazonia. This is the first floristic similarity study that emphasizes ferns and lycophytes in Maranhão. However, the scarcity of floristic surveys in Maranhão and other ecotonal areas in Brazil hindered a more complex analysis of the floristic similarity of these phytophysiognomies.

STRUKTUR KOMUNITAS LAMUN PADA PULAU SARANGBAUNG, KABUPATEN NIAS UTARA

Seagrass is a coastal vegetation that has various ecological, social, and economic roles for marine biota and humans. However, until now there is little current information regarding the status and inventory Sarangbaung Island which is administratively located in North Nias Regency and geographically located in the Indian Ocean. This study aims to examine the distribution and status of seagrasses in the waters of Sarangbaung Island, North Nias Regency. The research was conducted in December 2022. Observations of seagrass were carried out using the line and square transect method of 0.5 m x 0.5 m which refers to the seagrasswatch method. In total, 3 species were found during this study namely Syringodium isoetifolium, Cymodocea rotundata, and Cymodocea serrulate. Seagrass density on Sarangbaung Island ranges from 53-728 ind/m2. Meanwhile, seagrass coverage is 82%, which indicated that seagrass was in a good category with rich/healthy conditions.

Upaya Pelestarian Hutan Mangrove Melalui Pembibitan Di Desa Sungsang IV Kabupaten Banyuasin

Mangroves are typical coastal vegetation which one of the functions is as the main protector of coastal areas, where the existence of mangroves is very important but conditions are increasingly critical. In South Sumatra, the condition of mangroves, of 158,734 hectares, 20% are critical. The purpose of this research is how the nursery was carried out in the village of Sungsang IV, Banyuasin Regency and what types of mangroves were bred as an effort to preserve mangroves in South Sumatra and its surroundings. The benefit of this research is to get to know more about the wetland ecosystem. This research is a descriptive research with a qualitative approach. For collecting data, the writer uses a technique, namely observation, interview. Document. While qualitative data analysis is carried out interactively and continues continuously until complete, so that the data is saturated. Activities in the analysis consist of data condensation. The results of research on the location of a nursery area of ¼ hectare with 2 methods of seeding through propagules and mangrove seeds. Meanwhile, there are 12 mangrove species with 5 families. The mangrove festival was held in two places, namely Tanjung Api Api and Sungsang IV. And for the zoning of the Breech waters planted on the shoreline are Sonneratia alba and the embankment of Bruguiera gymnorrhiza while for planting in Tanjung Api Api the mangroves planted outside are Avicennia marina and Rhizophora apiculata on the inside.&#x0D;

Autochthonous Versus Allochthonous Resources in a Tropical Rocky Shore Trophic Web Adjacent to a Marine Riparian Area

Marine riparian areas and coastal vegetation are essential and important to the coastal marine ecosystem, although their interactions and functions are still unknown and ignored in marine ecological studies and integrated management planning. In southeastern Brazil, allochthonous resources derived from riparian Atlantic rainforests bordering rocky shores have been observed in abundance together with the shallow subtidal rocky reef benthos. In this study, we used stable isotopes (δ13C and δ15N) to characterize the main components in a benthic trophic web on a shallow tropical rocky shore, to identify the proportional contributions of allochthonous (marine riparian vegetation—MRV) to autochthonous (phytoplankton and algae) inputs and to test which basal food resources contributed most to the marine community on the Atlantic Forest–rocky coast interface. We found eight major food resources and seventeen consumers that we classified into different groups according to their feeding habits and biology. Although the main source of basal resources in the benthic trophic web in the present study remained autochthonous, the allochthonous resources were assimilated by all consumers. MRV is thus an important resource for some primary consumers and it should be included as a potential source of basal resources in marine ecosystems adjacent to marine riparian areas.

Coastal vegetation and estuaries are collectively a greenhouse gas sink

Coastal vegetation and estuaries are collectively a greenhouse gas sink

Numerical simulation of wave propagation through rigid vegetation and a predictive model of drag coefficient using an artificial neural network

Coastal vegetation has been widely recognized as an effective nature-based measure for coastal protection. Numerous studies based on macroscopic models have been performed to simulate vegetation-induced wave attenuation. The modeling accuracy is closely related to a key input parameter, the drag coefficient (CD). To date, however, no reliable prediction method is available for determining CD, limiting the practical application of the macroscopic models. In this study, vegetation-induced wave attenuation was investigated using a macroscopic model that solved Reynolds-averaged Navier-Stokes equations by introducing a vegetation resistance force to account for momentum loss. A stabilized k-ε turbulence model considering vegetation effects was developed for turbulence closure. The volume-of-fluid technique was used to capture the free surface. Using a calibration method to determine CD, the numerical model was validated based on several laboratory experiments. A correlation analysis was performed to reveal the potential contributions of dimensionless parameters about waves and vegetation to the calibrated CD. Multivariate non-linear regression (MNLR) and artificial neural network (ANN) methods were adopted to develop a CD predictive model. Comparisons indicated that the prediction performance of ANN model is superior to that of the MNLR model. The ANN model has the potential as a promising predictive tool for obtaining CD when simulating wave propagation through rigid vegetation.