표제지
목차
요약문 5
SUMMARY 6
제1장 연구개발 과제의 개요 9
제1절 연구개발의 목적 및 필요성 9
1. 연구 목적 9
2. 연구 필요성 9
제2장 국내외 기술개발 현황 11
1. 국내 기술개발 현황 11
2. 국외 기술개발 현황 11
제3장 연구개발 수행내용 및 결과 13
제1절 연근해 해양먹이망 구조 파악 및 모델 파라미터 확보 13
1. 수ㆍ저질 물리ㆍ화학적 환경특성 조사 13
2. 부유생태계 조사 23
3. 저서생태계 조사 39
제2절 연근해 식물플랑크톤 구성에 따른 기초생산력 구명 51
1. 기초생산력 51
2. 박테리아 생산력 58
제3절 IoT 기반 무인관측 이용 빅데이터 생산ㆍ활용 기술개발 61
1. Wave glider 이용 실시간 해양조사 관측 및 자료 활용기술 개발 61
2. Underwater glider를 활용한 관측한 고해상도 동해 해양 물리특성 파악 연구 64
제4절 맞춤형 수산정보 서비스 활성화 등 성과활용 방안 수립 68
1. 생태계 평가 성과목표 수립 및 정책 활용방안 등 68
제5절 해양먹이생물 종 조성 분석 및 먹이망 구조 파악 74
1. 먹이망 분석 방법 74
2. 동물플랑크톤 및 어류 안정동위원소 비 75
제4장 목표달성도 및 관련분야에의 기여도 79
1. 목표 달성도 79
2. 대표성과 및 기여도 79
제5장 연구개발 결과의 활용계획 81
1. 추가 연구의 필요성 81
2. 2단계 사업 추진 전략 81
제6장 참고문헌 82
제7장 부록 88
판권기 89
Table 1. Spearman's correlation analysis between surface water N* and Si* value and inorganic nutrient 20
Table 2. Dominant phytoplankton species in the East Sea, West Sea, South Sea, and East China Sea in winter from 2018 to 2022 24
Table 3. Dominant phytoplankton species in the East Sea, West Sea, South Sea, and East China Sea in spring from 2018 to 2022 24
Table 4. Dominant phytoplankton species in the East Sea, West Sea, South Sea, and East China Sea in summer from 2018 to 2022 25
Table 5. Dominant phytoplankton species in the East Sea, West Sea, South Sea, and East China Sea in autumn from 2018 to 2022 25
Table 6. Correlation of environments factors and zooplankton abundance and copepod abundance in the study area 28
Table 7. The mean annual primary production (APP) previously reported in the East Sea (ES), West Sea (WS), South Sea (SS), and East China Sea (ECS) 56
Table 8. Linear regression analysis between Chl-a and bacterial production (BP) in the euphotic depth in the northern East China Sea 60
Table 9. Linear regression analysis between dissolved organic carbon (DOC) and bacterial production (BP) in the whole depth in the northern East China Sea 60
Table 10. Major policies and strategies of the Fishery Conservation and Management Act 69
Table 11. The obligations and reporting cycles for the Joint Fisheries Statement implementation 69
Table 12. Performance evaluation indicator (PEI) in this R&D 71
Table 13. Assessment of technology levels in this R&D 72
Fig. 1. Study sites located in the East Sea, West Sea, South Sea and East China Sea 13
Fig. 2. Seasonal variations of sea surface temperature in the East Sea, West Sea, South Sea, and East China Sea from 2018 to 2022 14
Fig. 3. Seasonal variations of surface salinity in the East Sea, West Sea, South Sea, and East China Sea from 2018 to 2022 15
Fig. 4. Changjiang River discharge at Datong station from 2015 to 2022 15
Fig. 5. Seasonal variations of surface dissolved oxygen (DO) in the East Sea, West Sea, South Sea, and East China Sea from 2018 to 2022 16
Fig. 6. Seasonal variations of surface dissolved inorganic nitrogen (DIN) concentrations in the East Sea, West Sea, South Sea, and East China Sea from 2018 to 2022 17
Fig. 7. Seasonal variations of surface dissolved inorganic phosphorus (DIP) concentrations in the East Sea, West Sea, South Sea, and East China Sea from 2018 to 2022 17
Fig. 8. Seasonal variations of surface dissolved inorganic silicate (DSi) concentrations in the East Sea, West Sea, South Sea, and East China Sea from 2018 to 2022 18
Fig. 9. Seasonal variations of surface water N* (N deficit) values in the East Sea, West Sea, South Sea, and East China Sea from 2018 to 2022 19
Fig. 10. Seasonal variations of surface water Si* (Si deficit) values in the East Sea, West Sea, South Sea, and East China Sea from 2018 to 2022 20
Fig. 11. Surface distributions of Chl- a (µg L⁻¹) in the East Sea, West Sea, South Sea, and East China Sea in winter from 2018 to 2022 21
Fig. 12. Surface distributions of Chl- a (µg L⁻¹) in the East Sea, West Sea, South Sea, and East China Sea in spring from 2018 to 2022 21
Fig. 13. Surface distributions of Chl- a (µg L⁻¹) in the East Sea, West Sea, South Sea, and East China Sea in summer from 2018 to 2022 22
Fig. 14. Surface distributions of Chl- a (µg L⁻¹) in the East Sea, West Sea, South Sea, and East China Sea in autumn from 2018 to 2022 22
Fig. 15. Surface distributions of phytoplankton size index in the East Sea, West Sea, South Sea, and East China Sea from 2018 to 2022 23
Fig. 16. Seasonal variations of surface average chlorophyll- a (Chl- a) concentrations in the East Sea, West Sea, South Sea, and East China Sea from 2018 to 2022 23
Fig. 17. Number of mesozooplankton taxa from 2018 to 2022 26
Fig. 18. Abundance of major taxa of mesozooplankton from 2018 to 2022 27
Fig. 19. Species diversity index from 2018 to 2022 28
Fig. 20. Regression line between environmental factors and mesozooplankton 29
Fig. 21. Anomaly analysis of taxa number from 2018 to 2022 29
Fig. 22. Anomaly analysis of copepoda abundance from 2018 to 2022 30
Fig. 23. Carbon contents of dominant copepoda from 2018 to 2022 30
Fig. 24. Abundance of major taxa of macrozooplankton from 2020 to 2022 31
Fig. 25. Carbon contents of macrozooplankton from 2020 to 2022 31
Fig. 26. Abundance of ciliates from 2018 to 2022 32
Fig. 27. Averaged abundance of ciliates by season from 2018 to 2022. (Wi., winter; Sp., spring; Su., summer; Au., autumn) 33
Fig. 28. Averaged carbon contents of ciliates by season from 2018 to 2022 34
Fig. 29. Averaged abundance of ciliates by sea area from 2018 to 2022 35
Fig. 30. Averaged carbon contents of ciliates by sea area from 2018 to 2022 35
Fig. 31. Seasonal variations of abundance (inds. 1,000m⁻³) of fish eggs in the waters around the Korean Peninsula from 2018 to 2022 36
Fig. 32. Seasonal variations of abundance (inds. 1,000m⁻³) of fish larvae in the waters around the Korean Peninsula from 2018 to 2022 37
Fig. 33. Changes in the ratios of dominant taxa ichthyoplankton community (A) and sea surface temperature (B) in the East Sea, Korea, from 2018 to 2022 38
Fig. 34. Fluctuation of meiofaunal abundance (A) and biomass (B) in the East Sea 39
Fig. 35. Fluctuation of meiofaunal abundance (A) and biomass (B) in the West Sea 40
Fig. 36. Fluctuation of meiofaunal abundance (A) and biomass (B) in the South Sea 40
Fig. 37. Fluctuation of meiofaunal abundance and biomass in the East China sea 41
Fig. 38. Meiofaunal density (A) and biomass (B) in the East China Sea area from 2018 to 2022 41
Fig. 39. Fluctuation of the number of species (A) and biological indices (specific diversity index, B; evenness index, C; richness index, D) in each study area 42
Fig. 40. By taxonomic groups of macrobenthic animals, seasonal variations in species number (A), abundance (C) and biomass (E) from 2018 to 2022. Trend line... 43
Fig. 41. Spatio-temporal variations of species number (A, B), abundance (C, D) and biomass (E, F) of macrobenthic animals in the East Sea (Win., winter; Spr,... 44
Fig. 42. Spatio-temporal variations of species number (A, B), abundance (C, D) and biomass (E, F) of macrobenthic animals in the West Sea from 2018 to 2022... 45
Fig. 43. Spatio-temporal variations of species number (A, B), abundance (C, D) and biomass (E, F) of macrobenthic animals in the South Sea from 2018 to 2022... 46
Fig. 44. Spatio-temporal variations of species number (A, B), abundance (C, D) and biomass (E, F) of macrobenthic animals in the East China Sea from 2018 to... 46
Fig. 45. Spatio-temporal variations of the diversity of macrobenthic animals in the East Sea (A, B), West Sea (C, D), South Sea (E, F) and East China Sea (G, H)... 47
Fig. 46. Temporal variations of the top 5 dominant species in the East Sea (ES) and West Sea (WS) 48
Fig. 47. Temporal variations of the top 5 dominant species in the South Sea (SS) and East China Sea (ECS) 48
Fig. 48. Spatio-temporal variations of ISEP index of macrobenthic animals in the East Sea (A, B), West Sea (C, D), South Sea (E, F) and East China Sea (G, H).... 50
Fig. 49. Dendrogram for hierarchical clustering (left) and 2-dimensional nMDS configuration (right) using group average linkage by Bray-Curtis similarities calculated... 50
Fig. 50. The averaged community structure of phytoplankton in the East Sea (A), West Sea (B), South Sea (C), and East China Sea (D) during winter, spring,... 52
Fig. 51. The three major community structures of phytoplankton (Cryptophytes, Cyanobacteria, Diatoms) in the East Sea (A), West Sea (B), South Sea (C), and... 53
Fig. 52. Box plot of primary production (mg C m⁻² h⁻¹) by phytoplankton in the East Sea (A), West Sea (B), South Sea (C), and East China Sea (D) during winter,... 54
Fig. 53. Annual primary production in the East Sea, West Sea, South Sea, and East China Sea from 2018 to 2022 55
Fig. 54. Box plot of new production (mg N m⁻² h⁻¹) by phytoplankton in the East Sea (A), West Sea (B), South Sea (C), and East China Sea (D) during winter,... 56
Fig. 55. Relative percentage of new/regenerated production to annual primary production in the East Sea (A), West Sea (B), South Sea (C), and East China Sea (D)... 57
Fig. 56. Correlation between percentage of the contributions of new production to annual primary production and annual primary productions in the East Sea,... 58
Fig. 57. Map of the sampling stations marked with solid dots in the East China Sea with station number above the mark. Bottom depth contours are shown as solid lines 58
Fig. 58. Seasonal variation of bacterial production (BP) in the northern East China Sea. BP is depth integrated down to the euphotic depth 59
Fig. 59. Seasonal variation of Chl- a in the northern East China Sea. Chl- a is averaged down to the euphotic depth 59
Fig. 60. Seasonal variation of dissolved organic carbon (DOC) in the northern East China Sea. DOC is averaged with the whole depth 59
Fig. 61. Seasonal variation of BP:PP in the northern East China Sea. The horizontal dashed line indicates the BP averaged 16% of local PP in various oceanic systems... 61
Fig. 62. Relationships between salinity and dissolved organic carbon (DOC) in the summer northern East China Sea 61
Fig. 63. Wave glider configuration and equipment schematic diagram 62
Fig. 64. Observation results measured by a wave glider in the waters off the southern coast of Jeju in 2018. Time series of surface temperature (A) and surface salinity... 63
Fig. 65. Observation results measured by a wave glider in the waters off the southern coast of Jeju in 2022. Time series of wind toward direction (A) and air temperature (B);... 63
Fig. 66. Observation results measured by a wave gliders in the southern coast of Jeju during the 2021 typhoon period. Time series of wind (A), temperature (B),... 64
Fig. 67. Underwater glider 65
Fig. 68. Zonal sections of Chl-a concentration from six continuous observations 66
Fig. 69. Zonal sections of potential temperature (A), salinity (B) from six continuous observations 67
Fig. 70. Biplot using bulk carbon and nitrogen stable isotope of fish and zooplankton collected in the East Sea (A), West Sea (B), South Sea (C) and East China Sea (D)... 75
Fig. 71. Fingerprinting results using amino acid carbon stable isotope ratio analysis results of zooplankton and fish collected from coastal waters in Korea in February 2020 76
Fig. 72. NMDS ordination of fatty acids and stable isotopes from four zooplankton taxa (Euchaetidae, Chaetognatha, Euphausiid, and Amphipod) during high... 76
Fig. 73. Comparison of Trophic Levels by Sea Area Calculated Using Amino Acid Nitrogen Stable Isotope Ratio (δ15NAA) of Fish and Zooplankton Collected in February 2020 77
Fig. 74. Trophic position trends of Calanus spp. collected from the West Sea (307-05, 309-09), Korea 78