Meiofaunal Distribution on Coral Reefs of Pangkajene Islands, South Sulawesi, Indonesia |Chapter 1 | Research Perspective on Biological Science Vol. 7

 

This study investigates the composition and spatial distribution of meiofauna within the shallow coral reef ecosystem of the Pangkajene Islands, South Sulawesi, Indonesia. Samples were collected from 19 sites at depths of 6 to 8 meters, which showed stable oceanographic conditions but significant variation in live coral cover, ranging from 10.27% to 78.47%. A total of 13 meiofaunal taxa were identified from the sediment samples, with Nematoda being the most dominant group, making up more than 50% of the total population recorded. Other frequently present taxa included Harpacticoida, Polychaeta, Turbellaria, Foraminifera, and Nauplii. Meiofaunal density varied widely across the sites, from as low as 123 individuals per 10 cm² to as high as 5,235 individuals per 10 cm², with an overall average of 1,037±1,145 individuals per 10 cm². Multivariate analyses, including cluster analysis and non-metric multidimensional scaling (nMDS), identified three distinct station groups, indicating a high level of spatial variation in environmental conditions. Although habitat complexity from live coral structures is a key ecological factor, the study found no direct link between meiofaunal density and live coral cover. Instead, sediment properties such as grain size and organic matter availability had a more substantial influence on meiofaunal distribution. Stations with fine sand sediments generally supported higher meiofaunal abundance. These findings emphasise the importance of benthic microhabitat conditions, especially sediment characteristics, in shaping meiofaunal community structure in coral reef ecosystems. The study also supports the potential of meiofauna as sensitive bioindicators for assessing the health of these habitats.

 

 

Author(s) Details

Susetiono
Research Centre for Oceanography, National Research and Innovation Agency (BRIN), Indonesia.

 

H.A.W. Cappenberg
Research Centre for Oceanography, National Research and Innovation Agency (BRIN), Indonesia.

 

J. Souhoka
Research Centre for Oceanography, National Research and Innovation Agency (BRIN), Indonesia.

 

Endang S. Srimariana
Department of Marine Science and Technology, Faculty of Fisheries and Marine Sciences, IPB University Dramaga Bogor, Jawa Barat-166680, Indonesia.

 

E. Widyastuti
Research Centre for Oceanography, National Research and Innovation Agency (BRIN), Indonesia.

 

T. Sidabutar
Research Centre for Oceanography, National Research and Innovation Agency (BRIN), Indonesia.

 

Please see the book here :- https://doi.org/10.9734/bpi/rpbs/v7/6212

 

Coral Reef Distribution in Raja Ampat: A Study of Marine Conservation Areas in West Papua | Chapter 3 | Science and Technology - Recent Updates and Future Prospects Vol. 7

 

This study investigates the distribution and diversity of hard coral reefs in the Raja Ampat Regency Marine Conservation Area (MCA) in West Papua, home to numerous islands and diverse marine species. The data was collected using the UPT (Underwater Photo Transect) method. The researchers identified 108 hard coral species from 49 genera and 15 families. In 2015, hard coral cover (HC) ranged from 18.60% to 49.33%, averaging 32.24%. In 2019, HC coverage varied between 17.80% and 68.93%, an average of 37.84%, an increase of 5.59% from 2015. The distribution of hard corals varied between 26 and 51 species per station, with the family Acroporidae being the most diverse, with 34 species. Eleven other families had 2–14 species, while Helioporidae, Milleporidae, and Dendrophyllidae were each represented by one species with a limited distribution. Species such as Montipora sp., Porites lobata, Porites nigrecens, and Porites sp. were widespread and were found at nine stations, while 39 species had a limited distribution. Bray-Curtis similarity matrix dendrogram analysis showed similar coral types between transect stations. The diversity of coral reefs increases the complexity and fertility of the surrounding waters. However, threats such as destructive fishing, coral mining, tourism, and climate change are impacting these ecosystems, leading to algae dominance and reduced living coral cover. Understanding these dynamics is critical to implementing conservation strategies to protect coral reefs and prevent overfishing.

 

 

Author(s) Details

Jemmy Souhoka

Research Centre for Oceanography, National Research and Innovation Agency (BRIN), Indonesia.

H. A. W. Cappenberg

Research Centre for Oceanography, National Research and Innovation Agency (BRIN), Indonesia.

Susetiono

Research Centre for Oceanography, National Research and Innovation Agency (BRIN), Indonesia.

Nurjamin

Research Centre for Oceanography, National Research and Innovation Agency (BRIN), Indonesia.

I. H. Supriyadi

Research Centre for Oceanography, National Research and Innovation Agency (BRIN), Indonesia.

Suyarso

Research Centre for Oceanography, National Research and Innovation Agency (BRIN), Indonesia.

T. Sidabutar

Research Centre for Oceanography, National Research and Innovation Agency (BRIN), Indonesia.

 

Please see the link:- https://doi.org/10.9734/bpi/strufp/v7/1030

 

The Condition of Megabenthos in the Coral Reef Ecosystem on Salawati-Batanta Island, West Papua | Chapter 4 | Advanced Research in Biological Science Vol. 1

 This study investigates the rank of the megabenthos population in the underwater or partially submerged ledge ecosystem of Salawati-Batanta Island in West Papua. Salawati-Batanta Island is known for allure extensive pink reefs and rich variety of megabenthos, including polychaetes, crustaceans, echinoderms and mollusks. The study tries the abundance, difference, and distribution of megabenthos species in this place region. Data on megabenthos was calm from transects conducted along the coast at wisdoms of 3 to 7 meters. Observations were conducted middle from two points 2015 and 2019, with additional dossier collected in 2021 to guarantee a comprehensive analysis. The results usually showed a fixed diversity of eight megabenthos class, which could be top-secret into different environmental groups based on their importance. These groups contain indicator class, coralivorous species, and economically valuable species. It has happened found that the allocation of certain species, to a degree L. laevigata and Tridacna spp. is widespread during the whole of the study area, indicating a athletic population. Species like Panulirus sp. and A. planci granted a more restricted distribution. The study still found that pink-eating groups were low in number and formal no significant warning to the coral communities. The density of L. laevigata and Tridacna spp. remained approximately stable during the whole of the observation period, while Holothuria spp. displayed a declining style, particularly in commercially valuable species, suggesting attainable overexploitation. Overall, the study suggests that the megabenthos society in the coral reef ecosystem of Salawati-Batanta Island is now in good condition. However, it stresses the importance of implementing persuasive conservation measures to guarantee the long-term sustainability of these coral reefs and bar over-exploitation of economically valuable variety.

Author(s) Details:

Hendrik A. W. Cappenberg,
Research Centre for Oceanography, National Research and Innovation Agency (BRIN), Indonesia.

U. Y. Arbi,
Research Centre for Oceanography, National Research and Innovation Agency (BRIN), Indonesia.

J. Souhoka,
Research Centre for Oceanography, National Research and Innovation Agency (BRIN), Indonesia.

N. W. P. Sari,
Research Centre for Oceanography, National Research and Innovation Agency (BRIN), Indonesia.

E. Widyastuti,
Research Centre for Oceanography, National Research and Innovation Agency (BRIN), Indonesia.

Susetiono,
Research Centre for Oceanography, National Research and Innovation Agency (BRIN), Indonesia.

F. D. Hukom,
Research Centre for Oceanography, National Research and Innovation Agency (BRIN), Indonesia.

T. Sidabutar,
Research Centre for Oceanography, National Research and Innovation Agency (BRIN), Indonesia.

Please see the link here: https://stm.bookpi.org/ARBS-V1/article/view/11466

Neural Network Classification of Corals | Chapter 7 | International Research in Environment, Geography and Earth Science Vol. 7

 The recording of ecological change over time is a key challenge of contemporary ecology. The most diverse and complex of marine environments are coral reefs. In addition, coral reefs worldwide are suffering a serious decline due to the detrimental synergistic effects of global climate change, ocean acidification and seawater warming, intensified by anthropogenic eutrophication and pollution. These factors influence the decrease in live reef cover and the decrease in coral species, depending on site exposure to stressors, taking place at various rates and grades of severity. Any remediation steps include intensive monitoring, over long periods and short intervals, at numerous locations. The time-consuming, boring, manual classification of coral species and their real-time abundance in many reefs is a daunting task that is almost impossible. Deep learning (DL) has unique features for streamlining the description, analysis and monitoring of coral reefs, saving time and achieving greater reliability and accuracy compared to error-prone human results, and for managing and analysing the vast quantities of resulting data. Live coral cover and coral biodiversity are two key reef health indicators. The main objective of this analysis is to highlight the intensity and reliability of the deep learning approach to the documentation of the features of coral reefs, based on the assessment of the published application of this method to the definition of coral reefs and their assemblages of organisms. We evaluate the latest trends in the sector, describe its present constraints and future developments.

Author(s) Details

Alina Raphael
The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat-Gan 5290002, Israel.

Zvy Dubinsky
The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat-Gan 5290002, Israel.

Nathan Netanyahu
Department of Computer Science, Bar-Ilan University, Ramat-Gan 5290002, Israel.

David Iluz
The Mina and Everard Goodman Faculty of Life Sciences, Bar-Ilan University, Ramat-Gan 5290002, Israel.

View Book :- https://bp.bookpi.org/index.php/bpi/catalog/book/358