• ALGAE
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• v.19 no.2
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• pp.145-148
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• 2004

As a result of the 2-year monthly monitoring of the phytoplankton community at 3 stations in Mankyeong Estuary, Korea, we learned that cyan bacterial species of the genus Anabaena occurred at most sampling points with huge salinity differences (0.1-32.5 psu). We isolated several clones of Anabaena spp. from the monitoring stations, and screen out two euryhaline and nitrogen-fixing Anabaena clones, CB-MAL21 and CB-MAL22. The two clones were grown under various environmental gradients such as temperature (20, 30, 35 and 40$^{\circ}C$), salinity (0, 2, 5, 15 and 30psu), and $PO_4^{3-}$-P concentration (0, 1.6, 8.0, 40 and 200 ${\mu}M$M). Growth of CB-MAL21 and CB-MAL22 was measured by daily monitoring of chlorophyll fluorescence from each experimental culture for more than three serial transfers. Both the two experimental clones did not grow at 0psu. Maximal growth rates of the two clones were markedly reduced at lower $PO_4^{3-}$-P concentrations showing negligible growth at 0 and 1.6 ${\mu}M$M. However, growth of CB-MAL21 was not affected by low $NO_3^--$ concentration in culture media, showing the nitrogen-fixing ability. Maximum biomass yields of the two clones decreased dramatically at 35 and 40$^{\circ}C$. Optimal growth conditions for the two experimental clones were determined to be 20-30$^{\circ}C$, 40 ${\mu}M$M $PO_4^{3-}$-P, and wide salinity range from 5.0 to over 30psu. Best growth of CB-MAL21 was shown at (20$^{\circ}C$-15psu), which is less saline and cooler condition than those (i.e., 30$^{\circ}C$-30psu) for the best growth of CB-MAL22. The euryhaline and nitrogen-fixing CB-MAL21 strain thus can be a candidate laboratory culture for the future cyan bacterial marine biotechnology in temperate coastal waters.

• ALGAE
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• v.34 no.2
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• pp.141-151
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• 2019

The 1982-83, 1986-87, 1991-92, and 1997-98 El $Ni{\tilde{n}}o$-Southern Oscillations (ENSOs) were compared with regards to their strength and timing in the tropical Pacific Ocean, changes in ocean temperature and wave intensity, and their impacts to giant kelp populations in the Northeast Pacific. The Multivariate ENSO Index, oceanographic data, and kelp abundance data all show that the 1982-83 and 1997-98 ENSOs were stronger and resulted in greater losses of giant kelp than the 1986-87 and 1991-92 ENSOs, but that the 1982-83 and 1997-98 ENSOs differed with regard to the arrival of destructive waves relative to when the ocean waters warmed and cooled. The 1982-83 ENSO was more destructive to the giant kelp populations in central California, USA than the 1997-98 ENSO, but the 1997-98 ENSO was more destructive to the giant kelp in southern California. These events appeared similarly destructive to the populations in Baja California, Mexico. Recovery of the kelp populations also varied among the two strong ENSOs due to the ocean conditions following each ENSO. In southern and Baja California, recovery was slow following the 1982-83 ENSO, while recovery was more rapid following the 1997-98 ENSO. Unfortunately, the monitoring programs used to evaluate the kelp populations stopped shortly after the 1997-98 ENSO, resulting in a lack of data for comparisons with the more recent weak ENSOs that occurred between 2002 and 2010, or with the strong ENSO that occurred in 2014-2016. This supports the need for continued long-term monitoring programs to better understand how climate anomalies impact coastal ecosystems.

• Korean Journal of Ecology and Environment
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• v.49 no.4
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• pp.258-270
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• 2016

This study was conducted to test the green-tide mitigation technique in the lower part of the Sook Stream (Chusori) of Daecheong Reservoir from June 27 to August 24, 2014. And the effects were compared with weekly monitoring result of the watching station of the algae alert system (AAS) as well as test beds reach. The green-tide in a test bed was begun from the upstream, and it was gradually transferred and spread toward the downstream by the hydrological factors. The total amount of algae removed by algae removal device during the test period was 33,920 kg, and solids dewatered by natural gravity was 8,480 kg. Also chlorophyll-a content was 2.83 kg, the number of blue-green algae cells was equivalent to $78.6{\times}10^{14}$ cells. Compared with the results of the watching station of AAS, the pre-concentrate removal work in the outbreak waters was able to suggest the possibility of green-tide mitigation. In addition, an effective management of the green-tide was required spatial and temporal occurrence information and practical device technology. Particularly, the optimal timing of algae removal in the river-reservoir hybrid system was recommended at times before the monsoon rainy season and reached the lowest water level.

• Journal of the Korean Society of Marine Environment & Safety
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• v.25 no.2
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• pp.212-219
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• 2019

This study was conducted to investigate marine algal community characteristics and the status of barren ground in the summer at study sites on Jeju Island, Korea. Sampling was carried out from July to September 2017 using a qualitative and quantitative survey (including coverage of non-geniculated coralline algae and density of grazer) by scuba diving. A total of 121 species were identified, including 11 (9.1 %) green algae, 24 (19.8 %) brown algae, and 86 (71.1 %) red algae. Hyeongjeseom had the greatest diversity, with 60 species, and Harye the least, with 18 species. The mean biomass at the study sites was $1,503.0g{\cdot}m^{-2}$, while the mean for the neighboring islets ($3,268.7g{\cdot}m^{-2}$) was higher than that of the main island ($914.7g{\cdot}m^{-2}$). Also, dominant species was identified: Sargassum macrocarpum at the neighboring islets, and Ecklonia cava at the main island, with differences showing not only in biomass but also species composition. In conclusion, the marine algal community status in summer at the study sites was evaluated based on the algal community characteristics (species composition, biomass, biomass ratio of kelp species), coverage of non-geniculated coralline algae, and density of grazer. As a result, both Hyeongjeseom and Marado require preservation and management to maintain their excellent marine algal communities, and other sites on the main island require the creation and/or restoration of marine algal communities. In addition, as the generation of barren ground accelerates, it is urgent not only to grasp existing monitoring research but also to identify the status of the marine algal community where it is not known at present.

• Korean Journal of Remote Sensing
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• v.37 no.3
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• pp.493-502
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• 2021

Recently, because of changes in temperature and rising water temperatures due to increased pollution sources, many algae have been produced in the water system. Therefore, there has been a lot of research using satellite images for the generation and monitoring of green algae. However, in prior studies, it is difficult to consider the optical properties of the local water system by using only a single index, and by using medium and low-resolution satellite images to conduct large-scale algae detection, there is a problem of accuracy in narrow, broad rivers. Therefore, in this work, we utilize high-resolution images of Sentinel-2 satellites to perform green algae detection on a single index (NDVI, SEI, FGAI) and development index (NDVI & SEI, FGAI & SEI) that mixes single indices. In this study, POD, FAR, and PC values were utilized to evaluate the accuracy of green algae detection algorithms, and the FGAI & SEI index showed the highest accuracy with 98.29% overall accuracy PC.

• ALGAE
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• v.33 no.1
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• pp.85-99
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• 2018

Crustose calcareous algae (CCA) constitute one of the main reef builders on the Abrolhos Bank, Brazil. Once CCA taxonomy is locally understood, differences in growth-forms may be useful for the delimitation of taxa using characteristics such as the presence or absence of surface protuberances. Here, growth-forms were used to identify and quantify the most common CCA taxa on the shallow reefs (3-10 m) of the Abrolhos Bank to determine possible changes in the CCA community over a period of 10 years, and the ecological significance of CCA to local reefs was interpreted. The CCA assemblages were surveyed from 2006-2015 by using fixed photoquadrats at four sites in the inner (10-20 km from the mainland) and mid-shelf reefs (40-75 km from the mainland). The five most common CCA taxa were Pneophyllum conicum, the Lithophyllum kaiserii / Lithophyllum sp. complex, Melyvonnea erubescens, the Hydrolithon boergesenii / Porolithon onkodes complex and Peyssonelia sp. The overall mean CCA cover on the reefs was 20%. A comparison with a previous monitoring study in the same region indicated that the CCA cover nearly doubled from 2003-2008 to 2006-2015. This study reveals that the coral-killing species P. conicum dominated CCA flora on the shallow Abrolhos reefs in the last decade, and the local specific abundance of CCA slightly fluctuated over time and was species- and site-specific. The information obtained in this study contributes to the understanding of the ecology of the key calcifying components of the Abrolhos reefs and provides a useful baseline for exploring the responses of CCA to future environmental changes.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.42-42
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• 2022

지금까지도 유역에서의 녹조 모니터링은 현장채수를 통한 점 단위 모니터링에 크게 의존하고 있어 기후, 유속, 수온조건 등에 따라 수체에 광범위하게 발생하는 녹조를 효율적으로 모니터링하고 대응하기에는 어려운 점들이 있어왔다. 또한, 그동안 제한된 관측 데이터로 인해 현장 측정된 실측 데이터 보다는 녹조와 관련이 높은 NDVI, FGAI, SEI 등의 파생적인 지수를 산정하여 원격탐사자료와 매핑하는 방식의 분석연구 등이 선행되었다. 본 연구는 녹조의 모니터링시 정확도와 효율성을 향상을 목표로 하여, 우선은 녹조 측정장비를 활용, 7000개 이상의 녹조 관측 데이터를 확보하였으며, 이를 바탕으로 동기간의 고해상도 위성 자료와 실측자료를 매핑하기 위해 다양한Machine Learning기법을 적용함으로써 그 효과성을 검토하고자 하였다. 연구대상지는 낙동강 내성천 상류에 위치한 영주댐 유역으로서 데이터 수집단계에서는 면단위 현장(in-situ) 관측을 위해 2020년 2~9월까지 4회에 걸쳐 7291개의 녹조를 측정하고, 동일 시간 및 공간의 Sentinel-2자료 중 Band 1~12까지 총 13개(Band 8은 8과 8A로 2개)의 분광특성자료를 추출하였다. 다음으로 Machine Learning 분석기법의 적용을 위해 algae_monitoring Python library를 구축하였다. 개발된 library는 1) Training Set과 Test Set의 구분을 위한 Data 준비단계, 2) Random Forest, Gradient Boosting Regression, XGBoosting 알고리즘 중 선택하여 적용할 수 있는 모델적용단계, 3) 모델적용결과를 확인하는 Performance test단계(R², MSE, MAE, RMSE, NSE, KGE 등), 4) 모델결과의 Visualization단계, 5) 선정된 모델을 활용 위성자료를 녹조값으로 변환하는 적용단계로 구분하여 영주댐뿐만 아니라 다양한 유역에 범용적으로 적용할 수 있도록 구성하였다. 본 연구의 사례에서는 Sentinel-2위성의 12개 밴드, 기상자료(대기온도, 구름비율) 총 14개자료를 활용하여 Machine Learning기법 중 Random Forest를 적용하였을 경우에, 전반적으로 가장 높은 적합도를 나타내었으며, 적용결과 Test Set을 기준으로 NSE(Nash Sutcliffe Efficiency)가 0.96(Training Set의 경우에는 0.99) 수준의 성능을 나타내어, 광역적인 위성자료와 충분히 확보된 현장실측 자료간의 데이터 학습을 통해서 조류 모니터링 분석의 효율성이 획기적으로 증대될 수 있음을 확인하였다.

• Journal of The Korean Society of Agricultural Engineers
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• v.58 no.2
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• pp.53-63
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• 2016

Monitoring of cyanobacteria bloom in reservoir systems is important for water managers responsible of water supply system. Cyanobacteria affect the taste and smell of water and pose considerable filtration problems at water use places. Harmful cyanobacteria bloom in reservoir have significant economic impacts. We develop a new method for estimating the cyanobacteria bloom using Landsat TM and ETM+ data. Developed model was calibrated and cross-validated with existing in situ measurements from Daecheong Reservoir's Water Quality Monitoring Program and Algae Alarm System. Measurements data of three stations taken from 2004 to 2012 were matched with radiometrically converted reflectance data from the Landsat TM and ETM+ sensor. Stepwise multiple linear regression was used to select wavelengths in the Landsat TM and ETM+ bands 1, 2 and 4 that were most significant for predicting cyanobacteria cell number and bio-volume. Based on statistical analysis, the linear models were that included visible band ratios slightly outperformed single band models. The final monitoring models captured the extents of cyanobacteria blooms throughout the 2004-2012 study period. The results serve as an added broad area monitoring tool for water resource managers and present new insight into the initiation and propagation of cyanobacteria blooms in Daecheong reservoir.

• Ocean and Polar Research
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• v.24 no.4
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• pp.325-329
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• 2002

Concentrations of Fe, Mn, Zn, Cu, Pb and Cd in two seaweed species (Sargassum miyabei and S. pallidum) from different areas in Amursky Bay near Vladivostok were determined. An assessment of heavy metal pollution in this bay was made and the results were compared with those from some localities in the world ocean.

• Journal of the Korean Society for Marine Environment & Energy
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• v.19 no.4
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• pp.341-348
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• 2016

Micro-algae, one of the biological resources for alternative energy, has been heavily studied. Among various methods to analyze the status of the micro-algae including counting, screening, and flocculation, the flocculation approach has been widely accepted in many critical applications such as red tide removal study or microalgae resource study. To characterize the flocculation status of the micro-alga. A traditional optical modality, i.e., photospectrometry, measuring the optical density of the flocs has been frequently employed. While this traditional optical method needs shorter time than the counting method in flocculation status analysis, it has relatively lower detection accuracy. To address this issue, a novel real-time micro-algae flocculation analysis method based on the lens-free shadow imaging technique (LSIT) is introduced. Both single cell detection and floc detection are simultaneously available with a proposed lens-free shadow image, confirmed by comparing the results with optical microscope images. And three shadow parameters, e.g., number of flocs, effective area of flocs, and maximum size of floc, enabling quantification of the flocculation phenomenon of micro-alga, are firstly demonstrated in this article. The efficacy of each shadow parameter is verified with the real-time flocculation monitoring experiments using custom developed cohesive agents.