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163 results for “Bay Study”
Figure 4 in Study of ecosystem of the Sukhum Bay with emphasis anthropogenic impact, Abkhazian Black Sea coast
Figure 4. Dynamics of holoplankton (а): numerical abundance (N, 103∙ ind./m3), biomass (B, mg/m3) and meroplankton (b): numerical abundance (N, 103∙ ind./m3), biomass (B, mg/m3).
Figure 2 in Study of ecosystem of the Sukhum Bay with emphasis anthropogenic impact, Abkhazian Black Sea coast
Figure 2. Dynamics of phytoplankton (а): numerical abundance (N, 106∙ cell/m3), biomass (B, mg/m3), temperature of seawater (°C) and planktonic ciliates (b): numerical abundance (N, 106∙ ind./m3), biomass (B, mg/m3)
Рис. 22. ГнезΑа поΛярных овсянок Schoeniclus pallasi. Остров БайΑуков, заΛив Счастья, июΛь 2022 г. Фото Δ. В. Коробова Fig. 22. Nests of Pallasꞌs Buntings Schoeniclus pallasi. Baydukova Island, Bay of Schastꞌе, July 2022. Photo by D. V. Korobov in New data on rare and insufficiently studied birds of the Shchastya Bay, the Sea of Okhotsk, and adjacent territories (Khabarovsk Krai)
Рис. 22. ГнезΑа поΛярных овсянок Schoeniclus pallasi. Остров БайΑуков, заΛив Счастья, июΛь 2022 г. Фото Δ. В. Коробова Fig. 22. Nests of Pallasꞌs Buntings Schoeniclus pallasi. Baydukova Island, Bay of Schastꞌе, July 2022. Photo by D. V. Korobov
Рис. 19. ПоΛные кΛаΑки камчатской крачки Sterna camtschatica. Остров БайΑукова, заΛив Счастья, 29.07.2022. Фото Δ. В. Коробова Fig. 19. Full clutches of Kamchatka Tern. Baydukova Island, Bay of Schastꞌе, 29.07.2022. Photo by D. V. Korobov in New data on rare and insufficiently studied birds of the Shchastya Bay, the Sea of Okhotsk, and adjacent territories (Khabarovsk Krai)
Рис. 19. ПоΛные кΛаΑки камчатской крачки Sterna camtschatica. Остров БайΑукова, заΛив Счастья, 29.07.2022. Фото Δ. В. Коробова Fig. 19. Full clutches of Kamchatka Tern. Baydukova Island, Bay of Schastꞌе, 29.07.2022. Photo by D. V. Korobov
Рис. 18. ПоΛярная крачка Sterna paradisaea (в центре Λибо на переΑнем пΛане). Остров БайΑукова, заΛив Счастья, 30.06.2022. Фото Δ. В. Коробова Fig. 18. Arctic Tern Sterna paradisaea (in the center or in the foreground). Baydukova Island, Bay of Schastꞌе, 30.06.2022. Photo by D. V. Korobov in New data on rare and insufficiently studied birds of the Shchastya Bay, the Sea of Okhotsk, and adjacent territories (Khabarovsk Krai)
Рис. 18. ПоΛярная крачка Sterna paradisaea (в центре Λибо на переΑнем пΛане). Остров БайΑукова, заΛив Счастья, 30.06.2022. Фото Δ. В. Коробова Fig. 18. Arctic Tern Sterna paradisaea (in the center or in the foreground). Baydukova Island, Bay of Schastꞌе, 30.06.2022. Photo by D. V. Korobov
Рис. 16. Пуховой птенец тихоокеанской чайки Larus schistisagus. ЗаΛив Счастья, остров Чаечный, 14.07.2018. Фото В. В. Пронкевича Fig. 16. Downy chick of the Slaty-backed Gull Larus schistisagus. Bay of Schastꞌе, Chaechny Island, 14.07.2018. Photo by V. V. Pronkevich in New data on rare and insufficiently studied birds of the Shchastya Bay, the Sea of Okhotsk, and adjacent territories (Khabarovsk Krai)
Рис. 16. Пуховой птенец тихоокеанской чайки Larus schistisagus. ЗаΛив Счастья, остров Чаечный, 14.07.2018. Фото В. В. Пронкевича Fig. 16. Downy chick of the Slaty-backed Gull Larus schistisagus. Bay of Schastꞌе, Chaechny Island, 14.07.2018. Photo by V. V. Pronkevich
Рис. 8. РаспреΑеΛение гнезΑ беΛопΛечего орΛана в заΛиве Счастья по состоянию на 2018–2020 гг. Красными точками показаны занятые гнезΑа, сиреневыми — незанятые, жеΛтыми — брошенные Fig. 8. Distribution of Steller's sea eagle nests of the Bay of Schastꞌе as of 2018–2020. Red dots indicate occupied nests, purple dots indicate unoccupied nests, and yellow dots indicate abandoned nests in New data on rare and insufficiently studied birds of the Shchastya Bay, the Sea of Okhotsk, and adjacent territories (Khabarovsk Krai)
Рис. 8. РаспреΑеΛение гнезΑ беΛопΛечего орΛана в заΛиве Счастья по состоянию на 2018–2020 гг. Красными точками показаны занятые гнезΑа, сиреневыми — незанятые, жеΛтыми — брошенные Fig. 8. Distribution of Steller's sea eagle nests of the Bay of Schastꞌе as of 2018–2020. Red dots indicate occupied nests, purple dots indicate unoccupied nests, and yellow dots indicate abandoned nests
Рис. 6. Стая горбоносых турпанов Melanitta deglandi. Остров БайΑукова, заΛив Счастья, 17.07.2022. Фото Δ. В. Коробова Fig. 6. Flock of White-winged Scoter Melanitta deglandi. Baydukov Island, Bay of Schastꞌе, 17.07.2022. Photo by D. V. Korobov in New data on rare and insufficiently studied birds of the Shchastya Bay, the Sea of Okhotsk, and adjacent territories (Khabarovsk Krai)
Рис. 6. Стая горбоносых турпанов Melanitta deglandi. Остров БайΑукова, заΛив Счастья, 17.07.2022. Фото Δ. В. Коробова Fig. 6. Flock of White-winged Scoter Melanitta deglandi. Baydukov Island, Bay of Schastꞌе, 17.07.2022. Photo by D. V. Korobov
Рис. 1. Карта района иссΛеΑований. УсΛовные обозначения: красными кружками показаны базовые Λагеря; фиоΛетовой штриховкой — территория ΛанΑшафтного памятника прироΑы местного значения «ВΛасьевские торфяники»; синей штриховкой — акватория памятника прироΑы краевого значения «ЗаΛив Счастья с островами Кевор и Чаечный» Fig. 1. Map of the study area. Legend: red circles show base camps; purple shading — the territory of the landscape natural monument of local importance "Vlasyevsky Torfyaniky"; blue shading — the water area is a natural monument of regional significance "The Bay of Schastꞌе with the islands of Kevor and Chaechny" in New data on rare and insufficiently studied birds of the Shchastya Bay, the Sea of Okhotsk, and adjacent territories (Khabarovsk Krai)
Рис. 1. Карта района иссΛеΑований. УсΛовные обозначения: красными кружками показаны базовые Λагеря; фиоΛетовой штриховкой — территория ΛанΑшафтного памятника прироΑы местного значения «ВΛасьевские торфяники»; синей штриховкой — акватория памятника прироΑы краевого значения «ЗаΛив Счастья с островами Кевор и Чаечный» Fig. 1. Map of the study area. Legend: red circles show base camps; purple shading — the territory of the landscape natural monument of local importance "Vlasyevsky Torfyaniky"; blue shading — the water area is a natural monument of regional significance "The Bay of Schastꞌе with the islands of Kevor and Chaechny"
Рис. 7. РаспреΑеΛение гнезΑ беΛопΛечего орΛана Haliaeetus pelagicus на береговой кромке заΛ. Счастья по состоянию на 2009 г. Красными точками показаны занятые гнезΑа, сиреневыми — незанятые, жеΛтыми — брошенные Fig. 7. Distribution of nests of the Steller's Sea Eagle Haliaeetus pelagicus on the coastal edge of the Bay of Schastꞌе as of 2009. Red dots indicate occupied nests, purple dots indicate unoccupied nests, and yellow dots indicate abandoned nests in New data on rare and insufficiently studied birds of the Shchastya Bay, the Sea of Okhotsk, and adjacent territories (Khabarovsk Krai)
Рис. 7. РаспреΑеΛение гнезΑ беΛопΛечего орΛана Haliaeetus pelagicus на береговой кромке заΛ. Счастья по состоянию на 2009 г. Красными точками показаны занятые гнезΑа, сиреневыми — незанятые, жеΛтыми — брошенные Fig. 7. Distribution of nests of the Steller's Sea Eagle Haliaeetus pelagicus on the coastal edge of the Bay of Schastꞌе as of 2009. Red dots indicate occupied nests, purple dots indicate unoccupied nests, and yellow dots indicate abandoned nests
Text-fig. 1. A. Location of the sites of Capo di Fiume, Palena and Pollenzo near Alba. B. Capo di Fiume stratigraphic section. Facies of coastal-transitional marine associations – a. Freshwater marsh and tidal creeks interval, b. Swamp interval, c1–c4. Facies of eustarine bay associations, d1–d6. Facies of open shelf marine associations. Symbols: "black star" – fossiliferous horizon with plant material studied here, 1. mottled grey to dark-brown marls and clayey marls, 2. fissile dark-grey marls and shaly marls, 3. limestones, 4. marly limestones and limey marls, 5. bio-lithoclastic calcarenites, 6. lime conglomerate, 7. massive muddy deposit produced by mass-flow mechanism, 8. diatomitic marls, 9. "terra rossa" soil (modified after Carnevale et al. 2011). in Feather Palm Foliage From The Messinian Of Italy (Capo Di Fiume, Palena And Pollenzo Near Alba) Within The Framework Of Northern Mediterranean Late Miocene Flora
Text-fig. 1. A. Location of the sites of Capo di Fiume, Palena and Pollenzo near Alba. B. Capo di Fiume stratigraphic section. Facies of coastal-transitional marine associations – a. Freshwater marsh and tidal creeks interval, b. Swamp interval, c1–c4. Facies of eustarine bay associations, d1–d6. Facies of open shelf marine associations. Symbols: "black star" – fossiliferous horizon with plant material studied here, 1. mottled grey to dark-brown marls and clayey marls, 2. fissile dark-grey marls and shaly marls, 3. limestones, 4. marly limestones and limey marls, 5. bio-lithoclastic calcarenites, 6. lime conglomerate, 7. massive muddy deposit produced by mass-flow mechanism, 8. diatomitic marls, 9. "terra rossa" soil (modified after Carnevale et al. 2011).
Data from Diel Studies of the vertical migration of Margalefidinium polykrikoides in a lower Chesapeake Bay tributary.
<p>This dataset is in support of the publication "Diel vertical migration rates of the harmful algal bloom dinoflagellate species <em>Margalefidinium polykrikoides</em> in a lower Chesapeake Bay tributary." published in Frontiers in Aquatic Microbiology. The paper provides field-derived estimates of <em>M. polykrikoides’</em> diel vertical migration (DVM) rates have been made in the Chesapeake Bay. In this study, we conducted four targeted field experiments to investigate the DVM of M. polykrikoides in the Lafayette River, a sub-tributary of the Chesapeake Bay. Vertical profiles of chlorophyll a fluorescence collected at least every 2 h over diel periods were used to track the DVM of M. polykrikoides during blooms. Here we provide two supporting data files: 1) vertical profile data collected during the diel studies; and 2) cell counts for vertically migrating dinoflagellate species present during the first three diel studies.</p>
Integration of environmental DNA metabarcoding technique to reinforce fish biodiversity assessments in seagrass ecosystems: A case study of Gazi Bay Seagrass meadows
<p><span>Assessing biodiversity in marine nearshore ecosystems is crucial for effective management, especially in the context of climate change and overexploitation of marine resources. Conventional methods often fall short in providing comprehensive information for managing seagrass ecosystems. However, the emergence of environmental DNA (eDNA) techniques has transformed the field by enabling non-invasive surveys that are cost-effective and provide detailed information with high resolution. In this study, we utilized eDNA to assess fish diversity and compared its effectiveness to conventional techniques such as catch assessment surveys and underwater surveys. </span>We sampled three habitats (A: mangrove-seagrass, B: seagrass only, and C: coral-seagrass) with 4 replicates. Site A recorded 8 fish species, site B had 16 species, and site C, characterized by coral and seagrass habitats, exhibited the highest fish diversity with 45 species (mean H' index = 2.455), underscoring its ecological importance. To ensure accurate taxonomic identification, we utilized an updated MiFish reference database containing a larger number of fish species compared to the initial library. This expanded reference database with 9,569 fish species, facilitated more precise identification and enhanced the reliability of our findings. Notably, the eDNA technique outperformed conventional methods by detecting 23 additional fish species that went undetected using traditional surveys. Moreover, our study documented five fish species previously unknown to occur within the study region, further emphasizing the value of eDNA analysis in uncovering hidden biodiversity. These findings strongly advocate for integrating eDNA techniques into the monitoring and assessment of biodiversity in shallow tropical habitats of the Western Indian Ocean. By leveraging eDNA surveys, we can gain valuable insights into fish diversity, discover hidden species, and make informed decisions for the conservation and management of these ecologically significant areas.</p>
Integration of environmental DNA metabarcoding technique to reinforce fish biodiversity assessments in seagrass ecosystems: A case study of Gazi Bay Seagrass meadows
Open the record for dataset details and reuse information.
Investigating morphological complexes using informational dissonance and bayes factors: A case study in corbiculate bees
<p>It is widely recognized that different regions of a genome often have different evolutionary histories and that ignoring this variation when estimating phylogenies can be misleading. However, the extent to which this is also true for morphological data is still largely unknown. Discordance among morphological traits might plausibly arise due to either variable convergent selection pressures or else phenomena such as hemiplasy. Here we investigate patterns of discordance among 282 morphological characters, which we scored for 50 bee species particularly targeting corbiculate bees, a group that includes the well-known eusocial honeybees and bumblebees. As a starting point for selecting the most meaningful partitions in the data, we grouped characters as morphological modules, highly integrated trait complexes that as a result of developmental constraints or coordinated selection we expect to share an evolutionary history and trajectory. In order to assess conflict and coherence across and within these morphological modules, we used recently developed approaches for computing Bayesian phylogenetic information allied with model comparisons using Bayes factors. We found that despite considerable conflict among morphological complexes, accounting for among-character and among-partition rate variation with individual gamma distributions, rate multipliers, and linked branch lengths can lead to coherent phylogenetic inference using morphological data. We suggest that evaluating information content and dissonance among partitions is useful step in estimating phylogenies from morphological data, just as it is with molecular data. Furthermore, we argue that adopting emerging approaches for investigating dissonance in genomic datasets may provide new insights into the integration and evolution of anatomical complexes.</p>
Algoa Bay 2018/2019 LC-MS/MS DOM study
<p>This dataset contains the raw and processed data for a nontargeted tandem mass spectrometry study of dissolved organic matter (DOM) in surface water collected from the Algoa Bay system in the Eastern Cape of South Africa in 2018/2019</p>
In-situ Liaodong Bay Sea Ice Data for the Study of Remotely Estimating Absorptive Substances within Sea Ice
<p>This dataset was used for a study trying to develop remote rensing retrieval model and analyse the uncertainties of impurity content in sea ice from the optics perspective.</p>
Рис. 5. Рост мидий-сеголетков в подвесной культуре в б. Миноносок (Зал. Посьета) с 1975 по 1996 г. in Study on the growth rates of mollusks in hanging culture in Possjet Bay (Sea of Japan)
Рис. 5. Рост мидий-сеголетков в подвесной культуре в б. Миноносок (Зал. Посьета) с 1975 по 1996 г.
A case study of the Chesapeake Bay using the CAFE framework
<p>This file includes nutrient budget data for the Chesapeake Bay watershed, organized by county, year, and system.</p>
Figure 1 in Study of ecosystem of the Sukhum Bay with emphasis anthropogenic impact, Abkhazian Black Sea coast
Figure 1. The map of sampling survey in the port of Sukhum.
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Allen Brain Atlas
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OpenNeuro
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