Seagrass Cover Research Articles

Cloud Processing for Simultaneous Mapping of Seagrass Meadows in Optically Complex and Varied Water

Improved development of remote sensing approaches to deliver timely and accurate measurements for environmental monitoring, particularly with respect to marine and estuarine environments is a priority. We describe a machine learning, cloud processing protocol for simultaneous mapping seagrass meadows in waters of variable quality across Moreton Bay, Australia. This method was adapted from a protocol developed for mapping coral reef areas. Georeferenced spot check field-survey data were obtained across Moreton Bay, covering areas of differing water quality, and categorized into either substrate or ≥25% seagrass cover. These point data with coincident Landsat 8 OLI satellite imagery (30 m resolution; pulled directly from Google Earth Engine’s public archive) and a bathymetric layer (30 m resolution) were incorporated to train a random forest classifier. The semiautomated machine learning algorithm was applied to map seagrass in shallow areas of variable water quality simultaneously, and a bay-wide map was created for Moreton Bay. The output benthic habitat map representing seagrass presence/absence was accurate (63%) as determined by validation with an independent data set.

New distribution record of globally threatened Ocean Turf Grass Halophila beccarii Ascherson, 1871 from the North Andaman Islands highlights the importance of seagrass exploratory surveys

Halophila beccarii, listed as ‘Vulnerable’ on the IUCN Red List, aids in seagrass and mangrove succession, acts as a substrate stabilizer and provides feeding grounds for mega-herbivores like dugongs. This species was first recorded from the Andaman & Nicobar Islands in 2015, and its distribution status within the archipelago remains under-investigated. We report a new distribution record of H. beccarii from the North Andamans and shed light on its inter-island distribution. H. beccarii was recorded from a mixed meadow comprising of Cymodocea rotundata (20.5 ± 28.8%, mean seagrass cover), Thalassia hemprichii (16.3 ± 23.3%, mean seagrass cover), and Halodule pinifolia (6.3 ± 12.1%, mean seagrass cover) at Pokkadera, North and Middle Andaman district. H. beccarii had the highest mean seagrass cover (30 ± 34.7%) and shoot density (103.5 ± 68.3 shoots/ m2) among sympatric seagrass species. We also recorded eight seagrass-associated macrofaunal groups (gastropods, bivalves, polychaetes, foraminiferans, nematodes, brachyurans, decapods and asteroids) from the infaunal and epibenthic micro-habitats within the meadow. Infaunal macrobenthos had a much higher density (73.5 ± 129.7 individuals/m2) than the epibenthic macrofauna (0.4 ± 1.5 individuals/m2), possibly influenced by the seagrass canopy structure and biomass. Overall, gastropods were the most dominant macrobenthic faunal group (overall mean 95.0 ± 106.1 individuals/m2). The present findings emphasize the need for more exploratory surveys to understand H. beccarii distribution in the Andaman & Nicobar archipelago to identify priority conservation areas.

Using Unoccupied Aerial Vehicles (UAVs) to Map Seagrass Cover from Sentinel-2 Imagery

Seagrass habitats are ecologically valuable and play an important role in sequestering and storing carbon. There is, thus, a need to estimate seagrass percentage cover in diverse environments in support of climate change mitigation, marine spatial planning and coastal zone management. In situ approaches are accurate but time-consuming, expensive and may not represent the larger spatial units collected by satellite imaging. Hence, there is a need for a consistent methodology that uses accurate point-based field surveys to deliver high-quality mapping of percentage seagrass cover at large spatial scales. Here, we develop a three-step approach that combines in situ (quadrats), aerial (unoccupied aerial vehicle—UAV) and satellite data to map percentage seagrass cover at Turneffe Atoll, Belize, the largest atoll in the northern hemisphere. First, the optical bands of four UAV images were used to calculate seagrass cover, in combination with in situ data. The seagrass cover calculated from the UAV was then used to develop training and validation datasets to estimate seagrass cover in Sentinel-2 pixels. Next, non-seagrass areas were identified in the Sentinel-2 data and removed by object-based classification, followed by a pixel-based regression to calculate seagrass percentage cover. Using this approach, percentage seagrass cover was mapped using UAVs (R2 = 0.91 between observed and mapped distributions) and using Sentinel-2 data (R2 = 0.73). This work provides the first openly available and explorable map of seagrass percentage cover across Turneffe Atoll, where we estimate approximately 242 km2 of seagrass above 10% cover is located. We estimate that this approach offers 30 times more data for training satellite data than traditional methods, therefore presenting a substantial reduction in cost-per-point for data. Furthermore, the increase in data helps deliver a high-quality seagrass cover map, suitable for resolving trends of deteriorating, stable or recovering seagrass environments at 10 m2 resolution to underpin evidence-based management and conservation of seagrass.

Methane Emissions From Nordic Seagrass Meadow Sediments

Shallow coastal soft bottoms are important carbon sinks. Submerged vegetation has been shown to sequester carbon, increase sedimentary organic carbon (Corg) and thus suppress greenhouse gas (GHG) emissions. The ongoing regression of seagrass cover in many areas of the world can therefore lead to accelerated emission of GHGs. In Nordic waters, seagrass meadows have a high capacity for carbon storage, with some areas being recognized as blue carbon hotspots. To what extent these carbon stocks lead to emission of methane (CH4) is not yet known. We investigated benthic CH4 emission (i.e., net release from the sediment) in relation to seagrass (i.e. Zostera marina) cover and sedimentary Corg content (%) during the warm summer period (when emissions are likely to be highest). Methane exchange was measured in situ with benthic chambers at nine sites distributed in three regions along a salinity gradient from ∼6 in the Baltic Sea (Finland) to ∼20 in Kattegat (Denmark) and ∼26 in Skagerrak (Sweden). The net release of CH4 from seagrass sediments and adjacent unvegetated areas was generally low compared to other coastal habitats in the region (such as mussel banks and wetlands) and to other seagrass areas worldwide. The lowest net release was found in Finland. We found a positive relationship between CH4 net release and sedimentary Corg content in both seagrass meadows and unvegetated areas, whereas no clear relationship between seagrass cover and CH4 net release was observed. Overall, the data suggest that Nordic Zostera marina meadows release average levels of CH4 ranging from 0.3 to 3.0 μg CH4 m–2 h–1, which is at least 12–78 times lower (CO2 equivalents) than their carbon accumulation rates previously estimated from seagrass meadows in the region, thereby not hampering their role as carbon sinks. Thus, the relatively weak CH4 emissions from Nordic Z. marina meadows will not outweigh their importance as carbon sinks under present environmental conditions.

Effects of environmental factors on the detection of subsurface green turtles in aerial drone surveys

Abstract Context Aerial video surveys from unpiloted aerial systems (UAS) have become popular in wildlife research because of increased accessibility to remote areas, reduction of anthropogenic disruption to habitats and wildlife, low operating costs, and improved researcher safety. In shallow marine systems, they can provide opportunities to rapidly survey species that cannot easily be surveyed using boat- or land-based techniques. However, detectability of subsurface animals in marine habitats may be affected by environmental factors. Aims We investigated the effects of water depth, seagrass cover, surface glare, and observer numbers and expertise on the probability of detecting subsurface green turtles in UAS video surveys. Methods We deployed inanimate green turtle decoys at randomised intervals along 24 pre-determined transects across a depth gradient in a seagrass-dominated bay off Great Abaco, The Bahamas. We collected aerial videos of the transects by flying a DJI Phantom 3 Advanced quadcopter drone at an altitude of 10 m over each transect. Three independent observers watched each video and recorded decoy sightings to compare detection probabilities across observer experience levels. We used a generalised linear model to test for the effects of glare, water depth, wind speed, and seagrass cover on the detectability of turtle decoys. We also recorded glare conditions with aerial videos taken at 2-h intervals over a still body of water on cloudless days off North Miami, FL. Key results Individual observers performed similarly, but adding one additional observer increased detection by 11–12% and adding a third observer increased detections by up to 15%. Depth, seagrass cover, and glare significantly affected decoy detections. In both summer and fall, the optimal times and directions to minimise glare in aerial video surveys were 0800 hours, facing any direction other than north, and 1800 hours, facing any direction other than south. Conclusions The number of human observers and environmental variables, especially depth, seagrass cover, and glare, are important to explicitly consider when designing and analysing data from UAS surveys of subsurface animal abundances and distribution. Implications Our study draws attention to potential limitations of UAS-acquired data for subsurface observations if environmental conditions are not explicitly accounted for. Quantifying the effects of environmental factors, designing surveys to minimise variance in these factors, and having multiple observers are crucial for optimising UAS use in research and conservation of sea turtles and other marine fauna.

Seagrass rehabilitation in Thousand Islands, Jakarta: step to restore

Seagrass plays an essential role in coastal areas with ecological functions as a marine habitat, sediment trap, sediment stabilizer, nutrients filter, and dampen current. Fisheries and tourism are the seagrass ecosystem services that are the primary community livelihood in Thousand Island. However, seagrass condition has decreased in the last decade, influenced by coastal development, mass tourism, and climate change. This study aims to assessed the seagrass status and identify the threat in the last decade. Seagrass coverage was assessed in 2007 and 2018 using plot transect, and then seagrass threats were documented and collected from research articles, manuscripts, proceedings, and unpublished reports. Seagrass coverage has significantly decreased on Thousand Islands. Seagrass threats include pollution, reclamation, vessel activities, mass tourism, coastal development, climate change, and biotic factors (macroalgae and epiphyte coverage). The threats impact seagrass conditions, such as species diversity, area, and ecosystem services. Rehabilitation is needed to recover seagrass conditions using a direct or indirect approach. These findings recommend that managers should arrange the seagrass rehabilitation action plan to minimize seagrass degradation.

Seagrass, dugong, and people: Lessons learned from community-based conservation in Tolitoli Regency, Sulawesi Tengah, Indonesia

Dugong (Dugong dugon) is a protected mammal in Indonesia. Hunting for dugongs is still very high, so that the status of this animal is threatened, one of which is in Tolitoli Regency, Central Sulawesi. Hence, conservation efforts need to be carried out, both species and habitat area. Based on observation and interviews, dugong conservation in Tolitoli Regency was community-based habitat management. Kelompok Masyarakat Pengawas or Monitoring Community Group (Pokmaswas) was a form of community-based management in charge of maintaining, protecting, and preserving the existence of dugong and seagrass protection. From a community perspective, significant indicators in the management of dugong habitats were community awareness, seagrass percentage, and management quality. There was 11 kind of seagrass species have been identified in Tolitoli Regency. Seagrass conditions in all three villages were characterized by less than 60% of seagrass cover, especially seagrass that was close to the shoreline. The appearance of dugongs is based not only on good seagrass conditions but also on sea conditions and ship traffic.

Management status of blue swimming crab (Portunus pelagicus Linnaeus, 1758) based on EAFM in the coastal of Pangkep Regency, South Sulawesi

The Blue Swimming Crab (BSC) is the main export commodity of Indonesia and one of the BSC agribusinesses in the coastal waters of the Pangkep Regency. However, in recent years, BSC agribusiness in this region has been estimated to be unsustainable. The purpose of this study is to formulate the management of BSC (Portunus pelagicus) resources with the Ecosystem Approach to Fisheries Management (EAFM) in the coastal of the Pangkep Regency. The average value score in the BSC management domain is in the medium category (resource, habitat, economic, and institutional domains); the fishing techniques domain is in the good category, while the social domain is in the poor category. In general, the status of BSC fisheries management is categorized as medium (value = 194.25), therefore it can still be developed and improved. To repair the BSC fisheries management for gradually, tactical decisions were made to enhance the indicator conditions. To make the fishery activities sustainable, recommendations to improve the condition of the BSC fisheries in the Pangkep Regency include strengthening the supervision, improving the seagrass cover, improving coordination among institutions on the BSC fisheries management, and increasing stakeholder participation in the effort to manage the BSC fisheries.

Integrating sentinel-2 spectral-imagery and field data of seagrass coverage with species identification in the coastal of Riau Islands, Indonesia

Seagrass plays an important role in marine ecosystem. Plans for sustainable management of marine ecosystem should give due attention to this marine critical habitat. One effort to monitoring the long-term management of seagrass is to use spatial data using remote sensing techniques. Satellite imagery offers an efficient and cost-effective means of estimating water conditions in shallow environments. This study aims to map the coverage of the seagrass meadows using satellite images spatially, determine the species composition of the seagrass meadows, and examine the accuracy level from the results obtained by the Sentinel-2 images. Investigations reported here were conducted in the Riau Islands (4 Stations at Lingga Island and 2 Stations at Singkep Island) in Indonesia from 3 - 7 October 2020. The satellite image data used Sentinel-2 at the acquisition year of 2019 based on the method of Depth Invariant Index (DII) with Support Vector Machine (SVM) classification. The in situ observations were made from 6 October 2020, same with the validation date, to verify the data obtained through satellite imagery. This was needed for calculating the accuracy of results based on seagrass images and identifying the species using the Seagrass-Watch (Transect Quadrant). The result showed that the seagrass in the Riau Islands can be detected with the DII method with seagrass coverage area of 175 km2 from the satellite in Lingga and Singkep Island. Percentage of Seagrass coverage for all transects was estimated to be about 78%. The seagrasses species identified were: Halophila ovalis, Halophila minor, Thalassia hemprichii, and the dominant species was Enhalus acoroides.

Landsat historical records reveal large-scale dynamics and enduring recovery of seagrasses in an impacted seascape

Seagrasses are considered indicators of anthropogenic impact but surprisingly little is known about their temporal and spatial dynamics in impacted seascapes. In this study, we used three decades of Landsat imagery (1988–2018) off the coast of Adelaide, South Australia, to investigate how seagrass cover over 501 km2 responds to changes in land-based inputs, including breakpoints in system trajectory and associated timelags, and the identification of vulnerable meadows. Field data was used to help train benthic classification of summer imagery and define its accuracy. Temporal dynamics of seagrass cover were investigated in relation to annual and multi-year nitrogen and suspended solids loads. Spatial dynamics were inferred from maps of benthic cover persistence and trajectory for each decade. The region experienced a net regrowth of some 11,000 ha of seagrasses since the early 2000s, with the initial large-scale recruitment visible in the imagery 6 years after the closure of sludge outfalls. Seagrass expansion occurred primarily in deeper waters (>10 m) of the central coast and at the seaward edge of the distribution. Recovery continued until 2011 assisted by a window of opportunity created by a decade-long drought and further reductions in nitrogen loads from wastewater treatment plants and industry. Localized seagrass losses however continued to be observed as a result of either permanent or transient increases in suspended solids loads. Seagrass area in the central coast was well correlated (r2 = 0.88) with 5-year running averages of nitrogen and suspended solids loads. Meadows particularly vulnerable to changes in land-based discharges were located at the edges of the distribution, along erosional scarps and at depths >10 m south of the Torrens River. These areas were identified as useful indicators of seagrass status. Overall, seagrass persistence expanded from 48 to 69% of the mapped area, with the region now mostly covered by stable seagrasses.

Geomorphic gradients in shallow seagrass carbon stocks

Seagrass meadows are important sinks of organic carbon (Corg), in particular the near-surface Corg pool (≤ 15 cm) compared to deeper sediments. Near-surface carbon is highly susceptible to disturbance and loss to the atmosphere, however, inadequate accounting for variability in this pool of carbon limits their uptake into carbon accounting frameworks. We therefore investigated the spatial variability in seagrass near-surface Corg and biomass Corg across different geomorphic (estuary, lagoonal and reef-associated) and community typologies (pioneer and persistent). Near-surface Corg stock in vegetated areas (25.78 Mg Corg ha−1 ± 26.64) was twice that from unvegetated areas (14.27 Mg Corg ha−1 ± 15.86), reinforcing the paradigm that the presence of seagrass enhances carbon stocks. Lagoonal and reef-associated meadows showed similar Corg stocks (p > 0.05), which were substantially higher (p < 0.05) than estuary meadows. Likewise, persistent seagrass communities (Cymodocea dominance) stored higher (p < 0.05) stocks of Corg than pioneer communities (Halophila and Halodule dominance). Linear regression models showed significant but weak relationships between seagrass cover, shoot density and standing biomass with near-surface Corg stocks, whereas significant and strong relationships were observed for organic matter, dry bulk density and median grain size. The results highlight the need for higher resolution carbon assessments to better understand local and regional variability, in order to better inform carbon accounting and conservation policy.

Flooding of Sandy Beaches in a Changing Climate. The Case of the Balearic Islands (NW Mediterranean)

The fate of the beaches around the world has paramount importance as they are one of the main assets for touristic activities and act as a natural barrier for coastal protection in front of marine storms. Climate change could put them at risk as sea levels rise and changes in the wave characteristics may dramatically modify their shape. In this work, a new methodology has been developed to determine the flooding of sandy beaches due to changes in sea level and waves. The methodology allows a cost-effective and yet accurate estimation of the wave runup for a wide range of beach equilibrium profiles and for different seagrass coverage. This, combined with regional projections of sea level and wave evolution, has allowed a quantification of the future total water level and coastline retreat for 869 beaches across the Balearic Islands for the next decades as a function of greenhouse gases emission scenario. The most pessimistic scenario (RCP8.5) at the end of the century yields an averaged percentage of flooded area of 66% under mean conditions which increases up to 86% under extreme conditions. Moreover, 72 of the 869 beaches of the region would permanently disappear while 314 would be completely flooded during storm episodes. Under a moderate scenario of emissions (RCP4.5), 37 beaches would permanently disappear while 254 would disappear only during storm episodes. In both cases, the average permanent loss of beach surface at the end of the century would be larger than 50%, rising over 80% during storm conditions. The results obtained for the Balearic Islands can be extrapolated to the rest of the Mediterranean as the beaches in all the regions have similar characteristics and will be affected by similar changes in sea level and wave climate. These projections indicate that adaptation plans for beach areas should be put in place as soon as possible.

Mapping the distribution and occurrence of four newly recorded species of seagrasses in the North-West Arabian Gulf

For a long time the Iraqi regional waters of north-west Arabian Gulf were classified as free of seagrasses due to the absence of the information concerning these important angiosperms. During the survey carried out by scientist of the Marine Science Center and German divers in 2013-2014 to study the Coral reefs distribution and occurrence in this area, the divers with the help of underwater camera caught photos indicates the existence of seagrass meadows in different places of the north-west Arabian Gulf, so the efforts were made to examine this issue and a work were carried out in April 2017 to study the existence, species composition, occurrences and distribution of seagrass species in the Iraqi marine waters of the north-west Arabian Gulf for the first time. Six sites were chosen distributed along the north-west of Arabian Gulf where the depth was ranging from 0.5 to 15.0 m. Six meadows of seagrass were identified, classified, mapped and seagrass diversity and abundance were investigated. Four species of seagrass namely Halophila stipulacea (Forsskal) Ascherson, Halophila ovalis (R. Brown) Hooker f., Halophila decipiens Ostenfeld and Halodule uninervis (Forsskal) were recorded for the first time in Iraq. Halophila decipiens Ostenfeld was recorded as a new to the whole area of the Arabian Gulf and the Iraqi marine waters and found at a depth of 12-15 m. Halodule uninervis was found to be the most dominant species at all the studied sites followed by Halophila stipulacea. The total seagrass area estimated at all the stations was about 678 hectare fluctuated at different stations. Higher Seagrass total coverage area (240 ha) was found at shallower waters (0.5-3.0 m) compared with 60 ha at deeper waters (12-15 m). The exposed locations showed low seagrass coverage of 35 % comparing with sheltered sites (65 %). The relationship between depth and total coverage of seagrass was significant, while it was not significant with sites. Highest richness value was found in the Alkheran area (Khor Al-Zubair) at a depth of 0.5 m. The relative evenness of the seagrasses species, with different depths showed that the depth 0-3 m has the highest value. The distribution of seagrasses in Khor Al-Zubair and Khor Abdullah down to the open area of Khor Al-Omaya was mapped by using the GIS and Arc Map version 10.5 applications.

Diversity, coverage, distribution and ecosystem services of seagrass in three small islands of northern Papua, Indonesia: Liki Island, Meossu Island and Befondi Island

Nugraha AH, Tasabaramo IA, Hernawan UE, Rahmawati S, Putra RD, Darus RF. 2021. Diversity, coverage, distribution and ecosystem services of seagrass in three small islands of northern Papua, Indonesia: Liki Island, Meossu Island and Befondi Island. Biodiversitas 22: 5544-5549. Papua waters are one of the hot spot areas with high marine biodiversity in the world. Yet, the less accessible location and varying geographical conditions become the significant constraints of biodiversity study in this region, resulting in limited information about the diversity of marine resources, including the seagrass ecosystem. This research aims to investigate the diversity, coverage and distribution of seagrass in three small islands in the northern waters of Papua, namely Liki Island, Befondi Island, and Meossu Island, as well as to study the ecosystem services provided by the seagrass. This research is part of the Nusa Manggala Expedition, which was carried out in November 2018, consisted of seven observation stations. Data collection was conducted using the transect line method combined with plot quadrat. Information regarding seagrass ecosystem services was gathered through observation and direct interviews to the community. The results showed that there were seven species of seagrass in the studied sites, namely Cymodocea rotundata, Enhalus acoroides, Halodule uninervis, Halodule pinifolia, Halophila ovalis, Thalassia hemprichii, and Syringodium isoetifolium. Liki Island had the highest seagrass cover value of 82.24%, followed by Meossu Island and Befondi Island with seagrass cover of 63.23% and 31.25%, respectively. There were 13 seagrass ecosystem services identified in this research. The people of Liki Island and Meossu Island get the benefits of the existence of the seagrass ecosystem. The direct benefits are the presence of seagrass is associated with biota commonly used as food sources such as Siganus sp and sea cucumbers. There are efforts made by the community to maintain the sustainability of the seagrass ecosystem, which is known as sasi.

Dugong feeding grounds and spatial feeding patterns in subtidal seagrass: A case study at Sibu Archipelago, Malaysia

In Southeast Asia, seagrass meadows are under threat through coastal development and increased pollution, but remain understudied. The dugong is a marine herbivore that is dependent on the availability of seagrass as a primary food source. In this study, we assess the patterns of co-occurrence between dugongs and seagrass. We hypothesize that the changing spatial patterns of dugong feeding are positively correlated to the seasonal variation in distribution and abundance of mixed species in subtidal tropical seagrass meadows. We documented seagrass cover and dugong feeding trails in the Sibu Archipelago meadow in Johor, Malaysia, across the monsoon seasons of 2016–2017 using an underwater towed video method. Moran's I and Getis-Ord Gi* statistics were used to quantify the degree of clustering in feeding trails, feeding patch size, and to identify feeding hotspots and coldspots. This site has the single largest subtidal meadow in Peninsular Malaysia known to date, measuring 12.88 km2. The study captured a reduction in seagrass extent and coverage during the study. Feeding trail occurrence averaged three per image throughout the seasons, with the maximum number being 14 trails per image. Dugongs fed in a spatially clustered manner leaving two distinct feeding trail patterns: (1) a dispersed pattern when seagrass cover was high or low (76–100% and 0–25%) that resulted in larger patch sizes, and (2) a concentrated pattern in moderate seagrass cover (26–75%) that resulted in smaller patch size. Feeding hotspots and coldspots had significantly different seagrass cover, suggesting that dugongs foraged strategically within the meadow. Our results demonstrate that seagrass cover played a significant role in driving dugong feeding patterns and in creating feeding hotspots and coldspots in tropical subtidal meadows.

Variability in site characteristics linked to bay scallop abundance but not tethered survival: Implications for restoration

While predation impacts the abundance and distribution of prey species, the overall impact of predation varies with predator identity, predator density, and habitat complexity, among other factors. Numerous commercially and recreationally important prey species, such as bivalves, face intense predation that may affect management and restoration efforts. Therefore, predicting sites with elevated predation risk can be critical for successful restoration, although making predictions based on lab feeding assays may provide challenges. This study used bay scallops Argopecten irradians as a model organism to examine scallop abundance and survival in relation to predator density, habitat complexity, and predicted consumption, across multiple sites within the same estuary. Published predator-specific relationships between scallop consumption and habitat complexity were combined with field survey data to predict consumption potential at six sites in Shinnecock Bay, NY, USA. Using a series of Pearson correlations, the relationships between scallop abundance and tethered survival and site characteristics (habitat complexity, predator density, estimated consumption, scallop recruitment) were explored. Seagrass cover and recruitment of new individuals both strongly influenced scallop abundance, although tethered survival was not strongly correlated to any site metric (predator density, seagrass complexity, or estimated consumption). This study demonstrates potential issues when trying to link mesocosm studies to the field environment, such as sites with no seagrass but potentially confounding habitat complexity (i.e., Crepidula fornicata) and overestimates of consumption due to lack of realism in mesocosm studies. Overall, our study highlights the necessity of conducting field experiments to test mesocosm results, but also provides several valuable conclusions for shellfish restoration.

Bivalve facilitation mediates seagrass recovery from physical disturbance in a temperate estuary

AbstractRapid global degradation of coastal habitats can be attributed to anthropogenic activities associated with coastal development, aquaculture, and recreational surface water use. Restoration of degraded habitats has proven challenging and costly, and there is a clear need to develop novel approaches that promote resilience to human‐caused disturbances. Positive interactions between species can mitigate environmental stress and recent work suggests that incorporating positive interactions into restoration efforts may improve restoration outcomes. We hypothesized that the addition of a potential facultative mutualist, the native hard clam (Mercenaria mercenaria), could enhance seagrass bed recovery from disturbance. We conducted two experiments to examine the independent and interacting effects of hard clam addition and physical disturbance mimicking propeller scarring on mixed community Zostera marina and Halodule wrightii seagrass beds in North Carolina. Adding clams to seagrass beds exposed to experimental disturbance generally enhanced seagrass summer growth rates and autumn shoot densities. In contrast, clam addition to non‐disturbed seagrass beds did not result in any increase in seagrass growth rates or shoot densities. Clam enhancement of autumn percent cover relative to areas without clam addition was most prominent after Hurricane Dorian, suggesting that clams may also enhance seagrass resilience to repeated disturbances. By June of the next growing season, disturbed areas with clam additions had greater percent cover of seagrass than disturbed areas without clam additions. Beds that were disturbed in April had higher percent cover than areas disturbed in June of the previous growing season. Our results suggest that the timing and occurrence of physical disturbances may modify the ability of clams to facilitate seagrass resiliency and productivity. Understanding when and how to utilize positive, interspecific interactions in coastal restoration is key for improving restoration success rates.

Cost‐effective seafloor habitat mapping using a portable speedy sea scanner and deep‐learning‐based segmentation: A sea trial at Pujada Bay, Philippines

Abstract Various sampling and monitoring strategies have been developed to assess marine habitats and life‐forms. However, the cost‐effectiveness of such survey methods (e.g. line intercept transects and autonomous underwater vehicles) is still not high. In this paper, a practical seafloor habitat mapping method combining a cost‐effective survey system (P‐SSS: portable speedy sea scanner) and a deep learning‐based quantification method were proposed. P‐SSS is a highly portable transport system and a towed‐type system with five cameras arrayed on its platform. The sea trial was conducted at Pujada Bay, Philippines, on 7 December 2019. The high‐quality orthophotos of the seafloor with a high resolution of ~3.0 mm/pixel were successfully generated. The attained survey efficiency was 12,900 m2/hr. In addition, in this paper, a segmentation method utilizing the U‐Net architecture to estimate the coverage of corals, seagrass and sea urchins using a large‐scale 2D image is proposed. Overall, this highly portable survey system is expected to become a promising tool for marine environmental surveys, especially in the areas where the rich nature of the oceans is susceptible to environmental changes, such as the remote islands that lack sufficient survey facilities.

Potensi Kandungan Karbon Keragaman Spesies Lamun di Perairan Pesisir Selatan Lombok Timur

through the development of carbon zinc as an organic material produced from photosynthesis and stored and transported in the form of seagrass vegetation biomass. Seagrass is one of the aquatic vegetation that is able to absorb and store carbon. Seagrasses have the ability to absorb carbon through the process of photosynthesis. The purpose of this study was to describe the potential carbon content of seagrass species in the South Coastal Waters of East Lombok. This type of research is an expolarative descriptive research. The research method is a quadratic transect method. The population of this study were all seagrass species contained in 3 research stations. The collected data was then analyzed using analysis of seagrass species composition, seagrass cover, seagrass density, diversity, uniformity, dominance and analysis of carbon content through seagrass stand biomass (leaves, rhizomes/stems and roots). The result of this research is the discovery of 9 species of seagrass on Lungkak Beach and 5 species of seagrass on Gili Kere and Poton Bakau. The species density in the three study sites ranged from 0.09 to 56.91 stands/m2. Seagrass biomass values ranged from 1.47-261.9 gbk/m2 and total carbon content ranged from 295.91±202.88 gC. The value of this biomass and carbon content was dominated by seagrass species with large morphology such as Enhalus acroides, Thalasia hemprici, Cymodocea rotundata, and Cymodocea cerillata and high density and cover values of seagrass. The relationship between seagrass cover and seagrass carbon has a significant relationship where the higher the seagrass cover, the higher the carbon content of the seagrass.

Characterizing Derawan seagrass cover change with time-series Sentinel-2 images

In recent decades, seagrass ecosystems are declining globally. Providing spatial information of seagrasses has become growing needs in which data from satellite remote sensing platforms are proven to be useful. While multi-temporal archives of commercial and open access imagery are available, monitoring activity is rarely done frequently, limiting the information of seagrass dynamics particularly in tropical region. Here, we utilized time-series Sentinel-2 images to map seagrass percentage cover at intra-annual basis in two years’ time frame based on empirical method, while also compared maximum likelihood and random forest classifier to map dominant benthic cover type and determined seagrass spatial extent. We found that random forest classifier outperformed maximum likelihood classifier. Furthermore, a pattern of seagrass percentage cover change was present. Our results demonstrate how freely available Sentinel-2 images and limited field data could be useful in monitoring seagrasses at dense time. We anticipate this study to be a starting point for more complicated seagrass change analysis at denser time and link potential change drivers spatially.