Search

Mangrove forests and adjacent creeks are known to be highly productive estuaries, which are partly supported by benthic microalgae that grow on the sediments. During surveys investigating the microalgal floras of mangrove swamps in the eastern part of Java Island, a mud sample unexpectedly included large numbers of a notorious fish killer, Chattonella-like motile cells, and its resting cysts. These motile cells were established as clonal cultures for further identification and physiological tests. The cysts were examined through palynological and molecular biological means. Identification based on light microscopy and ribosomal RNA gene sequences confirmed that these cells and cysts were Chattonella marina var. marina. While the strains were genetically identical to the temperate strains isolated from Japan and China, temperature experiments showed that the Indonesian strains possessed a high maximum quantum yield of photosystem II even after exposure to 34 °C, a temperature at which the Japanese strain could not survive. Salinity experiments showed adaptation of the strains to a salinity of 15. These findings, together with the discovery of populations of cysts in the mangrove sediment, highlight the tough and unique nature of the Indonesian strains, which are likely adapted to wide fluctuations of temperature and salinity in mangrove swamps, and pose a potential risk to fisheries in Indonesia.

Myanmar is tenth among the world’s fish-producing countries and third in ASEAN (Association of Southeast Asian Nations). To understand the mechanisms underlying the high production, oceanographic and phytoplankton surveys, including primary productivity measurements based on pulse amplitude modulation fluorometry, were conducted near an active fishing ground near Myeik City. Three surveys, one in each of the representative seasons and covering the characteristic coastal environments, showed well-defined seasonality in primary production and phytoplankton occurrence. End of the dry season was the most productive, with productivity of 2.59 ± 1.56 g C m−2 day−1 and high concentration of chlorophyll a (3.14 ± 2.64 µg L−1). In this season, the phytoplankton population was dominated by high densities of the diatoms Bellerochea horologicalis and Chaetoceros curvisetus, whereas primary productivity was low at the onset of the dry season, 1.36 ± 0.77 g C m−2 day−1. However, this low primary production might be compensated by activation of microbial food chains originating from high dissolved organic carbon. The rainy season exhibited the lowest production, 6.6% of the end of the dry season, due to the extensive discharge of turbid water from the rivers which lowered euphotic layer depth and resulted in an unusually high diffuse attenuation coefficient of 2.30 ± 1.03 m−1. This incident of turbid water may be related to soil erosion from deforestation and mangrove deterioration. This research reveals the seasonal trend in Myanmar’s coastal productivity and its relationship to the tropical monsoon climate as well as emphasizing the importance of tropical coastal environments to the sustainability of the fisheries.

Unlike most bivalve shellfishes, giant clams (tridacnines) harbor symbiotic microalgae (zooxanthellae) in their fleshy bodies. Zooxanthellae are not maternally inherited by tridacnine offspring, hence, the larvae must acquire zooxanthellae from external sources, although such algal populations or sources in the environment are currently unknown. It is well known that giant clams expel fecal pellets that contain viable zooxanthellae cells, but whether these cells are infectious or just an expelled overpopulation from the giant clams has not been investigated. In this study, we observed the ultrastructural and photosynthetic competencies of zooxanthellae in the fecal pellets of Tridacna crocea and further tested the ability of these cells to infect T. squamosa juveniles. The ultrastructure of the zooxanthellae cells showed that the cells were intact and had not undergone digestion. Additionally, these zooxanthellae cells showed a maximum quantum yield of photosystem II (Fv/Fm) as high as those retained in the mantle of the giant clam. Under the assumption that feces might provide symbionts to the larvae of other giant clams, fecal pellets from Tridacna squamosa and T. crocea were given to artificially hatched 1-day-old T. squamosa larvae. On the 9th day, 15–34% of the larvae provided with the fecal pellets took up zooxanthellae in their stomach, and on the 14th day, zooxanthellae cells reached the larval margin, indicating the establishment of symbiosis. The rate reaching this stage was highest, ca. 5.3%, in the larvae given whole (nonhomogenized) pellets from T. crocea. The composition of zooxanthellae genera contained in the larvae were similar to those in the fecal pellets, although the abundance ratios were significantly different. This study is the first to demonstrate the potential of giant clam fecal pellets as symbiont vectors to giant clam larvae. These results also demonstrate the possibility that fecal pellets are a source of zooxanthellae in coral reefs., This work was supported by MEXT/JSPS KAKENHI Grant Number 18K19232 to KK.

Harmful algal blooms (HABs) occur frequently in the Seto Inland Sea, bringing significant economic and environmental losses for the area, which is well known as one of the world&rsquo, s most productive fisheries. Our objective was to develop a quantitative model using in situ hyperspectral measurements in the Seto Inland Sea to estimate chlorophyll a (Chl-a) concentration, which is a significant parameter for detecting HABs. We obtained spectra and Chl-a data at six stations from 12 ship-based surveys between December 2015 and September 2017. In this study, we used an iterative stepwise elimination partial least squares (ISE-PLS) regression method along with several empirical and semi-analytical methods such as ocean chlorophyll, three-band model, and two-band model algorithms to retrieve Chl-a. Our results showed that ISE-PLS using both the water-leaving reflectance (RL) and the first derivative reflectance (FDR) had a better predictive ability with higher coefficient of determination (R2), lower root mean squared error (RMSE), and higher residual predictive deviation (RPD) values (R2 = 0.77, RMSE = 1.47 and RPD = 2.1 for RL, R2 = 0.78, RMSE = 1.45 and RPD = 2.13 for FDR). However, in this study the ocean chlorophyll (OC) algorithms had poor predictive ability and the three-band and two-band model algorithms did not perform well in areas with lower Chl-a concentrations. These results support ISE-PLS as a potential coastal water quality assessment method using hyperspectral measurements.

Harmful algal blooms (HABs) occur frequently in the Seto Inland Sea, bringing significant economic and environmental losses for the area, which is well known as one of the world’s most productive fisheries. Our objective was to develop a quantitative model using in situ hyperspectral measurements in the Seto Inland Sea to estimate chlorophyll a (Chl-a) concentration, which is a significant parameter for detecting HABs. We obtained spectra and Chl-a data at six stations from 12 ship-based surveys between December 2015 and September 2017. In this study, we used an iterative stepwise elimination partial least squares (ISE-PLS) regression method along with several empirical and semi-analytical methods such as ocean chlorophyll, three-band model, and two-band model algorithms to retrieve Chl-a. Our results showed that ISE-PLS using both the water-leaving reflectance (RL) and the first derivative reflectance (FDR) had a better predictive ability with higher coefficient of determination (R2), lower root mean squared error (RMSE), and higher residual predictive deviation (RPD) values (R2 = 0.77, RMSE = 1.47 and RPD = 2.1 for RL; R2 = 0.78, RMSE = 1.45 and RPD = 2.13 for FDR). However, in this study the ocean chlorophyll (OC) algorithms had poor predictive ability and the three-band and two-band model algorithms did not perform well in areas with lower Chl-a concentrations. These results support ISE-PLS as a potential coastal water quality assessment method using hyperspectral measurements.

Sea surface salinity (SSS) is playing a critical role for studying biological and physical processes in the ocean. The objective of this study is to establish a model for estimating SSS using in situ measurement datasets from FY2015 to FY2016 in Seto Inland Sea. To estimate SSS, we performed a bio-optical model combined with the CDOM absorption coefficient at 440 nm (ay(440)) as a proxy. Results showed that the estimated ay(440) had a reversely linear relationship with in situ SSS using winter datasets (R2=0.66), which indicated the ay(440) is potential for modeling to estimate SSS, furthermore, the bio-optical model can be used for water quality assessment in Seto Inland Sea.