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Mechanism of critical metal and REE enrichment and paleoclimatic signatures from Northwest Pacific Magellan Seamounts Ferromanganese Crusts
No full textThis study investigates the mineralogy, crystal chemistry, and paleoclimatic implications of hydrogenetic ferromanganese crusts (HFMCs) collected from the Magellan Seamounts in the Northwest Pacific. To characterize the crystal chemistry and structure of the poorly crystalline nanominerals within the HFMCs, we employed a combination of advanced techniques, including synchrotron-based X-ray diffraction (XRD), pair distribution function (PDF) analysis, and high-resolution transmission electron microscopy (TEM). Our results from synchrotron XRD, PDF, and TEM analyses revealed that the HFMCs are primarily composed of poorly crystalline vernadite, a nanophase mineral. The vernadite exhibits a complex structure, consisting of a mixture of ~7.2 Å and ~9.6 Å vernadite components, along with interstratified phases. This vernadite plays a crucial role in the sequestration of platinum group elements (PGEs), rare earth elements (REEs), and critical metals such as cobalt and nickel. Detailed chemical analyses demonstrate a partitioning of elements within the vernadite structure. PGEs, Co, and Ni are predominantly concentrated within the Mn-rich vernadite. In contrast, REEs and phosphorus are preferentially adsorbed onto the Fe-rich vernadite. The formation and chemical variations observed within the HFMC layers are strongly influenced by redox changes in the oxygen minimum zone (OMZ). These redox fluctuations are linked to global sea level changes and glacial-interglacial cycles. Specifically, we observed evidence of millennia-scale paleoclimatic oscillations within the uppermost layer of the HFMC. Furthermore, fine-scale chemical oscillations, exhibiting cycles of approximately 1600 years during the Middle to Late Pleistocene and Holocene, were identified. These cycles include a prominent glacial termination event around 126,000 years ago. A notable increase in the Mn/Fe ratio within the HFMC layer is associated with this period of glacial melting. The micro-bands present in HFMCs serve as a valuable proxy for paleoclimatic changes, as they are highly sensitive to fluctuations in dissolved oxygen levels in seawater. Further research encompassing HFMC samples from diverse locations, depths, and origins is essential to gain a more comprehensive understanding of both long-term and short-term paleoclimatic variability.2
해양생태계 먹이망을 통한 137Cs의 생물축적 가능성 평가
No full text일본 후쿠시마 원전 방사능 오염수 유출 및 방류와 관련하여 바다로 유입된 방사성 핵종이 해양생태계에 서식하는 생물들에게 미치는 부정적인 영향에 대한 우려가 제기되고 있다. 특히 세슘은 근육에 축적되어 먹이사슬을 통해 상위 영양단계 생물에게 전달될 수 있다고 보고된 바 있으나, 실제 현장에 서식하고 있는 다양한 생물군에 대해 세슘의 축적 가능성을 평가할 수 있는 자료는 부족한 실정이다. 본 연구에서는 2024년 3월과 6월 제주도 인근 해역 2개 정점에서 현장 생물시료를 직접 채집하여 체내 137Cs을 분석하였으며, 이들의 먹이사슬 관계를 파악하기 위하여 탄소 및 질소 안정동위원소 비를 함께 분석하였다. 또한 다수의 연구에서 생물 농축 확대 특성을 보임이 확인된 수은을 함께 분석하여 137Cs의 농도 증가 경향과 비교하였다. 그 결과, 수은은 질소 안정동위원소 비가 무거운 생물에서 높은 농도를 보이며 생물농축이 일어나는 것이 확인되었으며, 이는 이전의 연구결과와 일치한다. 한편, 137Cs는 일부 생물군에서 수은과 유사한 농축 특성을 보였으나, 해조류와 여과섭식자인 해면과 맨드라미류에서는 비슷한 질소 안정동위원소 비를 보이는 다른 생물군에 비해 높은 137Cs 농도를 보였다(안전기준 이하). 이러한 결과는 동일한 서식처에 서식하는 생물군이라도 섭식방법 등 다양한 생태학적 특성에 따라 137Cs의 생물축적의 정도가 다를 수 있음을 보여준다.2
Gene expression differences between floating and benthic populations of the golden tide seaweeds, based on field based transcriptomic analysis
No full text2
Volatile organic compounds as fingerprints for identifying marine plastics
No full textThe increase in global marine plastic pollution highlights the need for more advanced yet simplified methods of plastic analysis. This study investigated the potential of volatile organic compounds (VOCs) emitted from plastics as fingerprints for plastic identification. Selected ion flow tube–mass spectrometry was used to conduct real-time analysis of VOCs emitted from heated (20–80 °C) pellets of plastic types commonly encountered in marine environments, including low-density polyethylene (LDPE), high-density polyethylene (HDPE), polypropylene (PP), expanded polystyrene (EPS), and poly(ethylene terephthalate) (PET). VOCs consistently reflected the compositional characteristics of each plastic type: alkanes, characterised by their monomer units, were dominant in LDPE, HDPE, and PP; aromatics were prevalent in EPS; and ethylene glycol was observed in PET. The concentrations of these components varied with temperature, reflecting their unique thermal properties. A tiered classification model employing partial least squares discriminant analysis based on key mass fragment ions of emitted VOCs successfully distinguished among polymer types, achieving 100 % accuracy in determination of plastic products. This novel approach offers a simplified plastic polymer identification method, demonstrating that the chemical signatures of VOCs emitted from plastics can serve as unique and reliable fingerprints.33Nscopu
Characterization of Atmospheric Particulate Matter (PM) in the Port of Busan and Adjacent Areas
No full text본 연구는 항만 내 미세먼지 입자의 화학적 특성분석과 지역사회 영향평가를 위한 데이터 수집 및 평가를 목적으로 하였다. 2024년 12월부터 현재까지 부산항 신선대부두에서 대용량 대기입자 채취기(high volume air sampler, HVAS)를 이용해 대기 미세먼지의 총 입자성 물질(Total Suspended Particle, TSP)을 수집하여 중금속 분포특성을 조사하였으며, SERINUS를 이용해 관측된 PM2.5와 PM10의 분포에 대한 예측모델을 검토하였다. 모니터링 기간 중 TSP는 계절적 변화가 크지 않으나 봄철의 농도가 다소 높은 것으로 나타났으며 주요 중금속의 농도분포 순위는 아연(Zn) > 망간(Mn) > 바륨(Ba) > 납(Pb) > 구리(Cu), 스트론튬(Sr) > 크로뮴(Cr) 순으로 나타났다. 모니터링 기간 납(Pb)의 평균 농도는 0.039 μg/m3으로 국내 대기환경기준(연평균 0.5 μg/m3)을 넘지 않는 것으로 나타났으며, 카드뮴(Cd) 평균농도는 0.0015 ㎍/㎥, 망간(Mn) 평균농도 0.09 ㎍/㎥으로 각각 WHO 권고기준(연평균 Cd 0.005 ㎍/㎥, Mn 0.15 ㎍/㎥) 을 초과하지 않았다. 농축계수(enrichment factor, EF) 계산을 통한 중금속의 인위적인 오염의 정도를 평가한 결과 모니터링 기간 인위적인 오염이 심한 정도는 ‘안티몬(Sb) > 아연(Zn) > 카드뮴(Cd) > 납(Pb) > 구리(Cu) > 크로뮴(Cr) > 비소(As)’ 순이었고, 계절적 차이는 크지 않은 것으로 나타났다. 모니터링 기간 채취된 TSP 의 중금속 농도 특성을 활용하여 PMF 모델을 이용한 오염원 구분과 기여도를 평가하였다. 주요 요인으로 3개의 요인이 산출되었으며, 해당 요인의 계절 및 시계열의 중금속 성분의 기여도가 다른 것이 명확히 확인되어, 시료 및 데이터 축적과 함께, 배출원 분석을 병행하면 시기에 따른 주요 오염원을 파악할 수 있을것으로 평가되었다. 또한, 부산 항만권역의 오염물질 기여도를 파악하PM2.5 예측을 위해 높은 설명력, 낮은 과적합정도, 데이터 규모 등을 고려하여 예측 모델을 선정하였다. PM10이 가장 높은 기여도를 보였으며, 부산항만권역에서의 월별 변수 기여도는 CO 물질이 0.21~0.70로 모든 계절에 우세하였다. 다음으로 NO2의 기여도가 0.06~0.32로 나타났고, 여름철(7~8월)에는SO2(0.38)와 NO2(0.32)의 기여도가 상대적으로 높아졌다. 본 연구결과는 항만 미세먼지에 대한 장기 모니터링 및 데이터 분석 연구를 통해 명확한 주요 오염원 규명이 필요하며, 이는 항만 발생 미세먼지로 인한 지역사회 건강 위해도 저감을 위한 환경정책 운영 전략 도출을 위한 과학적 결과를 축적할 수 있을 것으로 판단된다.2
자력자료 및 암석 연대를 활용한 독도 해저화산체의 구조 해석 연구
No full text본 연구는 독도 해저화산체의 형성과 구조적 특성을 파악하기 위해 자력자료를 활용한 3차원 자화벡터 역산 모델링을 수행하였다. 연구 대상인 화산체는 해저 기반부로부터 정상부까지 약 2.1 km 높이로, 동–서 약 26 km, 남–북 약 21 km의 평정 해산형 지형을 이룬다. 정상부의 소규모 분화구는 형성 이후 후기 분출 가능성을 시사한다. 자력 이상 분석 결과, 중앙의 저이상대를 고이상대가 둘러싸는 분포가 나타났으며, 고이상대는 특히 남쪽 사면에서 강하게 분포하고 지형 경계와도 일치하였다. 자화벡터 역산은 유도자화와 잔류자화를 함께 고려해 수행되었으며, 자성물질은 주로 심부에서 천부로 상승하며 중심부 또는 남–남동 사면을 따라 이동한 것으로 보인다. 정상부 서쪽–남서쪽의 소규모 고이상대는 잔류자화 또는 후기 화산 활동의 결과로 해석된다. 암석 연대와 자력 구조 모델 비교 결과, 독도 화산체는 Matuyama 역자기극 시대에 역자기극기의 첫번째 주요 분출이 있었고 그 이후 정자기극기의 두번째 주요분출이 있었을 것으로 판단된다. 정자기극기에는 마그마가 중앙부를 통해 상승해 남부 및 남서 사면으로 흐른 것으로 판단된다. 이후 평평한 독도 화산체 정상부가 형성된 후 후기 분출에 의해 기생화산에 생성된 것으로 판단된다. 천부층과 심부층 고이상대의 구분, 자화벡터 방향의 불일치는 독도 화산체가 여러 시기의 분출로 형성된 복합 지자기 구조를 가짐을 시사한다. 본 연구는 자력자료와 지형 정보를 융합한 3차원 모델링을 통해 독도 해저화산체의 내부 구조와 형성 메커니즘을 규명하였으며, 향후 심흥택해산과 이사부해산을 포함한 확장 연구를 통해 정밀한 지구조 해석이 가능할 것으로 기대된다.2
Food consumption rates of the sea urchin Mesocentrotus nudus and top shell Turbo sazae: Potential impacts of seaweed beds
No full textThe expansion of barren ground and a shift in macrograzer habitats due to increasing water temperatures associated with climate change are becoming increasingly problematic in Korea. This study assessed the potential effects of Mesocentrotus nudus (sea urchin) and Turbo sazae
(top shell) on seaweed beds by examining changes in their food consumption rates (FCR) in response to water temperature, food source, nutritional status and reproductive cycle. (1) water temperature: T. sazae consistently showed a higher FCR for single seaweed (brown algae) than M. nudus across temperatures ranging from 5 to 25 ℃, with the gap widening as water temperature increased. (2) food source: Among brown, red, green seaweeds, M. nudus and T. sazae strongly preferred brown algae, while M. nudus avoided red algae and T. sazae did not
favor green algae. M. nudus showed a higher FCR for multiple seaweeds compared to a single seaweed, whereas T. sazae showed the opposite tendency at 20 ℃. Although both species ingested coralline algae at similar rates, their FCR for coralline algae was significantly lower
than those for seaweed at 20 ℃. (3) nutritional status: M. nudus maintained consistent FCR for non-preferred seaweed before and after starvation, indicating that seaweed preference had a greater influence on its feeding than nutritional status. In contrast, T. sazae showed a
significant increase in FCR after starvation compared to before, its suggesting its feeding was strongly influenced by nutritional status. (4) reproductive cycle: The FCR in both species remained unchanged by artificial increases or decreases in water temperature, with each
species showing FCR in accordance with its reproductive cycle. These findings suggested that reproductive cycle is the most significant factor influencing FCR for both species rather than other factors. Therefore, our findings suggest that evaluating FCR in a specific condition without
accounting for the ecological characteristics of both species provides only a limited understanding of their impact on seaweed beds. Nonetheless, given that the FCR of T. sazae increases with increasing water temperatures, the continued ocean warming may result in T.
sazae having a greater impact on seaweed beds than M. nudus, posing a more significant ecological threat.1
Determining ecological interactions of key dinoflagellate species using an intensive metabarcoding approach in a semi-closed coastal ecosystem of South Korea
No full textMarine phytoplankton communities are pivotal in biogeochemical cycles and impact global climate change. However, the dynamics of the dinoflagellate community, its co-occurrence relationship with other eukaryotic plankton communities, and environmental factors remain poorly understood. In this study, we aimed to analyze the temporal changes in the eukaryotic plankton community using a 18S rDNA metabarcoding approach. We performed intensive monitoring for 439 days at intervals of three days during the period from November 2018 to June 2020 (n = 260) in Jangmok Bay Time-series Monitoring Site in South Korea. Among the 16,224 amplicon sequence variants (ASVs) obtained, dinoflagellates were the most abundant in the plankton community (38 % of total relative abundance). The dinoflagellate community was divided into 21 groups via cluster analysis, which showed an annually similar distribution of low-temperature periods. Additionally, we selected 11 taxa that had an occurrence mean exceeding 1 % of the total dinoflagellate abundance, accounting for 93 % of the total dinoflagellate community: namely Heterocapsa rotundata, Gymnodinium sp., Akashiwo sanguinea, Amoebophrya sp., Euduboscquella sp., Spiniferites ramosus, Dissodinium pseudolunula, Sinophysis sp., Karlodinium veneficum, and Katodinium glaucum. The key dinoflagellate species were well represented at temporally variable levels over an entire year. Heterocapsa rotundata was not significantly affected by water temperature, whereas its dynamics were largely influenced by strong predation pressure, competition, and/or the supplementation of food sources. The growth of A. sanguinea was associated with dissolved inorganic phosphorus concentrations, while Eudu- boscquella sp. showed a significant relationship with D. pseudolunula and K. glaucum, largely representing a positive association that implies possible parasitic mechanisms. This study demonstrated interactions between key dinoflagellate species and the environment, as well as parasites, predators, competitors, and feeders.1
An advanced approach to spatial data on the abundance of multiple macroinvertebrate species in intertidal sediments using drones and artificial intelligence
No full textUnderstanding the spatial distribution of macroinvertebrates is essential for ecological monitoring and habitat management. However, conventional burrow-counting methods are labor-intensive, and model-based estimations often fail to fully capture natural conditions. This study introduces an integrated approach using high-resolution drone orthophotos and artificial intelligence (AI)-based object detection to estimate abundance of tidal flat macroinvertebrates. We developed training and validation datasets for five species—Urechis unicinctus, Ocypode stimpsoni, Laomedia sp., Uca arcuata, and Macrophthalmus japonicus—incorporating species-specific burrow openings and associated biogenic traces. A YOLO algorithm was used to detect burrows in both single- and multi- class configurations. The single-class detection accuracy exceeded 90% for U. unicinctus and O. stimpsoni, while multi-class detection for Laomedia sp., U. arcuata, and M. japonicus averaged around 75%, with performance variations linked to species-specific burrow characteristics. The AI-based detection approach demonstrated accuracy comparable to or exceeding that of complex model-based methods and showed potential for broader regional applicability. This study is the first attempt to estimate the abundance of multiple macroinvertebrate species using drones and AI, indicating the potential to develop a method that derives spatial information based on precise measurements reflecting actual abundance.1
Sea Level Data Reconstruction Challenges: An Exploration of AI/ML and Reanalysis at Ieodo Ocean Research Station
No full textThis study applies artificial intelligence (AI) to analyze sea level variability in the East Sea (ES) and East China Sea (ECS) using in-situ observations, satellite altimetry from the Copernicus Marine Environment Monitoring Service (CMEMS), and reanalysis datasets (HYCOM, ORAS5, GLORYS) for 1993–2023. Sea level changes are decomposed into steric and mass contributions, excluding atmospheric pressure effects. Key observation sites include the Ieodo Ocean Research Station (IORS) in the ECS and Ulleungdo and Dokdo in the ES. To enhance data completeness and predictive accuracy, we employ an ensemble AI approach incoporating models. AI-based reconstructions are validated against independent datasets and tide gauge records. Sea Level trends vary across datasets, with IORS rates of 5.82 mm yr⁻¹(in-situ, 2003–2023), 3.53 mm yr⁻¹(CMEMS, 1993–2023), 3.09 mmyr⁻¹(GLORYS, 1993–2023), 2.27 mm yr⁻¹(ORAS5, 1993–2023), and -0.09 mm yr⁻¹(HYCOM,1994–2023). HYCOM exhibits substantial variability over sub-periods, underscoring the complexity of regional sea level trends. Cross-correlation analysis reveals strong agreement between detrended sea levels, with coefficients of 0.92 (CMEMS-GLORYS), 0.90 (CMEMSHYCOM), 0.89 (CMEMS-ORAS5), and 0.80 (CMEMS-in-situ). This study advances the understanding of sea level dynamics in this climatically sensitive region, improving methodologies for future projections and coastal risk assessments under ongoing climate change.2