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  • San Diego :Elsevier,  (1)
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  • GEOMAR Catalogue / E-Books  (2)
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  • 1
    Keywords: Ecology--Simulation methods. ; Ecosystem management--Simulation methods. ; Environmental sciences--Simulation methods. ; Electronic books.
    Type of Medium: Online Resource
    Pages: 1 online resource (381 pages)
    Edition: 1st ed.
    ISBN: 9780444635433
    Series Statement: Issn Series ; v.Volume 27
    DDC: 577.0113
    Language: English
    Note: Front Cover -- Advanced Modelling Techniques Studying Global Changes in Environmental Sciences -- Copyright -- Contents -- Contributors -- Preface -- Chapter 1: Introduction: Global changes and sustainable ecosystem management -- 1.1. Effects of Global Changes -- 1.2. Sustainable Ecosystem Management -- 1.3. Outline of This Book -- 1.3.1. Review of ecological models -- 1.3.2. Ecological network analysis and structurally dynamic models -- 1.3.3. Behavioral monitoring and species distribution models -- 1.3.4. Ecological risk assessment -- 1.3.5. Agriculture and forest ecosystems -- 1.3.6. Urban ecosystems -- 1.3.7. Estuary and marine ecosystems -- References -- Chapter 2: Toward a new generation of ecological modelling techniques: Review and bibliometrics -- 2.1. Introduction -- 2.2. Historical Development of Ecological Modelling -- 2.3. Bibliometric Analysis of Modelling Approaches -- 2.3.1. Data Sources and Analysis -- 2.3.2. Publication Output -- 2.3.3. Journal Distribution -- 2.3.4. Country/Territory Distribution and International Collaboration -- 2.3.5. Keyword Analysis -- 2.4. Brief Review of Modelling Techniques -- 2.4.1. Structurally Dynamic Model -- 2.4.2. Individual-Based Models -- 2.4.3. Support Vector Machine -- 2.4.4. Artificial Neural Networks -- 2.4.5. Tree-Based Model -- 2.4.6. Evolutionary Computation -- 2.4.7. Ordination and Classification Models -- 2.4.8. k-Nearest Neighbors -- 2.5. Future Perspectives of Ecological Modelling -- 2.5.1. Big Data Age: Data-Intensive Modelling -- 2.5.2. Hybrid Models -- 2.5.3. Model Sensitivities and Uncertainties -- References -- Chapter 3: System-wide measures in ecological network analysis -- 3.1. Introduction -- 3.2. Description of system-wide Measures -- 3.3. Ecosystem Models Used for Comparison -- 3.4. Methods -- 3.5. Observations and Discussion -- 3.5.1. Clusters of Structure-Based Measures. , 3.5.2. Clusters of Flow-Based Measures -- 3.5.3. Clusters of Storage-Based Measures -- References -- Chapter 4: Application of structurally dynamic models (SDMs) to determine impacts of climate changes -- 4.1. Introduction -- 4.2. Development of SDM -- 4.2.1. The Number of Feedbacks and Regulations Is Extremely High and Makes It Possible for the Living Organisms and Populatio -- 4.2.2. Ecosystems Show a High Degree of Heterogeneity in Space and in Time -- 4.2.3. Ecosystems and Their Biological Components, the Species, Evolve Steadily and over the Long-Term Toward Higher Complexi -- 4.3. Application of SDMs for the Assessment of Ecological Changes due to Climate Changes -- 4.4. Conclusions -- References -- Chapter 5: Modelling animal behavior to monitor effects of stressors -- 5.1. Introduction -- 5.2. Behavior Modelling: Dealing with Instantaneous or Whole Data Sets -- 5.2.1. Parameter Extraction and State Identification -- 5.2.2. Filtering and Intermittency -- 5.2.3. Statistics and Informatics -- 5.3. Higher Moments in Position Distribution -- 5.4. Identifying Behavioral States -- 5.5. Data Transformation and Filtering by Integration -- 5.6. Intermittency -- 5.7. Discussion and Conclusion -- Acknowledgment -- References -- Chapter 6: Species distribution models for sustainable ecosystem management -- 6.1. Introduction -- 6.2. Model Development Procedure -- 6.3. Selected Models: Characteristics and Examples -- 6.3.1. Decision Trees -- 6.3.1.1. General characteristics -- 6.3.1.2. Examples -- 6.3.1.3. Additional remarks -- 6.3.2. Generalised Linear Models -- 6.3.2.1. General characteristics -- 6.3.2.2. Examples -- 6.3.2.3. Additional remarks -- 6.3.3. Artificial Neural Networks -- 6.3.3.1. General characteristics -- 6.3.3.2. Examples -- 6.3.3.3. Additional remarks -- 6.3.4. Fuzzy Logic -- 6.3.4.1. General characteristics -- 6.3.4.2. Examples. , 6.3.4.3. Additional remarks -- 6.3.5. Bayesian Belief Networks -- 6.3.5.1. General characteristics -- 6.3.5.2. Examples -- 6.3.5.3. Additional remarks -- 6.3.6. Summary of Advantages and Drawbacks -- 6.4. Future Perspectives -- References -- Chapter 7: Ecosystem risk assessment modelling method for emerging pollutants -- 7.1. Review of Ecological Risk Assessment Model Methods -- 7.2. The Selected Model Method -- 7.3. Case Study: Application of AQUATOX Models for Ecosystem Risk Assessment of Polycyclic Aromatic Hydrocarbons in Lake Ecos -- 7.3.1. Application of Models -- 7.3.2. Models -- 7.3.2.1. AQUATOX model -- 7.3.2.2. Parameterization -- 7.3.2.2.1. Biomass and physiological parameters of organisms -- 7.3.2.2.2. Characteristics of Baiyangdian Lake -- 7.3.2.2.3. PAHs model parameters -- 7.3.2.2.4. Determining PAHs water contamination -- 7.3.2.2.5. Sensitivity analysis -- 7.3.3. Results of Model Application -- 7.3.3.1. Model calibration -- 7.3.3.2. Sensitivity analysis -- 7.3.3.3. PAHs risk estimation -- 7.3.4. Discussion on the Model Application -- 7.3.4.1. Compare experiment-derived NOEC with model NOEC for PAHs -- 7.3.4.2. Compare traditional method with model method for ecological risk assessment for PAHs -- 7.4. Perspectives -- Acknowledgments -- References -- Chapter 8: Development of species sensitivity distribution (SSD) models for setting up the management priority with water qua -- 8.1. Introduction -- 8.2. Methods -- 8.2.1. BMC Platform Development for SSD Models -- 8.2.1.1. BMC structure -- 8.2.1.2. BMC functions -- 8.2.1.2.1. Fitting SSD models -- 8.2.1.2.2. Determining the best fitting model based on DIC -- 8.2.1.2.3. Uncertainty analysis -- 8.2.1.2.4. Calculating the eco-risk indicator: PAF and msPAF -- 8.2.2. Framework for Determination of WQC and Screening of PCCs -- 8.2.2.1. WQCs calculation -- 8.2.2.2. PCCs screening. , 8.2.3. Overview of BTB Areas, Occurrence of PTSs, and Ecotoxicity Data Preprocessing -- 8.3. Results and Discussion -- 8.3.1. Evaluation of the BMC Platform -- 8.3.1.1. Selection of the best SSD models -- 8.3.1.2. Priority and posterior distribution of SSDs parameters -- 8.3.1.3. CI for uncertainty analysis -- 8.3.1.4. Validation of SSD models -- 8.3.2. Eco-risks with Uncertainty -- 8.3.2.1. Generic eco-risks for a specific substance -- 8.3.2.2. Joint eco-risk for multiple substances based on response addition -- 8.3.3. Evaluation of Various WQC Strategies -- 8.3.3.1. Abundance of toxicity data -- 8.3.3.2. Limitation of toxicity data -- 8.3.3.3. Lack of toxicity data -- 8.3.3.4. Implication for improvement of the local WQC in BTB -- 8.3.4. Ranking and Screening Using Various PCC Strategies -- 8.3.4.1. PNEC -- 8.3.4.2. Eco-risk calculated by BMC -- 8.3.4.3. EEC/PNEC -- 8.3.4.4. PCC list in BTB area -- 8.3.4.5. Implication for update of the local PCC list in BTB -- 8.4. Conclusion -- Acknowledgments -- References -- Chapter 9: Modelling mixed forest stands: Methodological challenges and approaches -- 9.1. Introduction -- 9.2. Review Methodology -- 9.2.1. Literature Review on Modelling Mixed Forest Stands -- 9.2.2. Ranking of Forest Models -- 9.3. Results and Discussion -- 9.3.1. Patterns of Ecological Model Use in Mixed Forests -- 9.3.2. Model Ranking -- 9.3.2.1. FORMIX -- 9.3.2.2. FORMIND -- 9.3.2.3. SILVA -- 9.3.2.4. FORECAST -- 9.3.3. Comparison of the Top-Ranked Models -- 9.4. Conclusions -- Acknowledgments -- References -- Chapter 10: Decision in agroecosystems advanced modelling techniques studying global changes in environmental sciences -- 10.1. Introduction -- 10.2. Approaches Based on Management Strategy Simulation -- 10.2.1. Simulation of Discrete Events in Agroecosystem Dynamics -- 10.2.2. Simulation of Agroecosystem Control. , 10.3. Design of Agroecosystem Management Strategy -- 10.3.1. Hierarchical Planning -- 10.3.1.1. HTN planning concepts -- 10.3.1.2. Planning approach in HTNs -- 10.3.1.3. Illustration based on the problem of selecting an operating mode in agriculture -- 10.3.2. Planning as Weighted Constraint Satisfaction -- 10.3.2.1. Constraint satisfaction problem -- 10.3.2.2. Networks of weighted constraints -- 10.3.2.3. Illustration based on crop allocation -- 10.3.3. Planning Under Uncertainty with Markov Decision Processes -- 10.3.3.1. Markov decision processes -- 10.3.3.2. Illustration using a forest management problem -- 10.4. Strategy Design by Simulation and Learning -- 10.5. Illustrations -- 10.5.1. SAFIHR: Modelling a Farming Agent -- 10.5.1.1. Decision problem -- 10.5.1.2. SAFIHR: Continuous planning -- 10.5.1.3. Overview of the overall operation -- 10.6. Conclusion -- References -- Chapter 11: Ecosystem services in relation to carbon cycle of Asansol-Durgapur urban system, India -- 11.1. Introduction -- 11.2. Methods -- 11.2.1. Study Area -- 11.2.2. Urban Forest -- 11.2.3. Agriculture -- 11.2.4. Anthropogenic Activities -- 11.2.5. Cattle Production -- 11.3. Analysis and Discussion -- 11.3.1. Ecosystem Services and Disservices of Urban Forest -- 11.3.2. Ecosystem Services and Disservices of Agricultural Field -- 11.3.3. Ecosystem Services and Disservices Through Anthropogenic Activities -- 11.3.4. Ecosystem Services and Disservices Through Cattle Production -- 11.3.5. Impact on Biodiversity -- 11.3.6. Cultural Services and Disservices -- 11.3.7. Future Perspective of Ecosystem Services -- 11.4. Conclusions -- Acknowledgments -- References -- Chapter 12: Modelling the effects of climate change in estuarine ecosystems with coupled hydrodynamic and biogeochemical mode -- 12.1. Introduction -- 12.2. Coupled Hydrodynamic and Biogeochemical Models. , 12.3. Models as Effective Tools to Support Estuarine Climate Change Impacts Assessment.
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  • 2
    Online Resource
    Online Resource
    Newark :John Wiley & Sons, Incorporated,
    Keywords: Microplastics-Environmental aspects. ; Electronic books.
    Type of Medium: Online Resource
    Pages: 1 online resource (531 pages)
    Edition: 1st ed.
    ISBN: 9781119879527
    DDC: 363.738
    Language: English
    Note: Cover -- Title Page -- Copyright Page -- Contents -- List of Contributors -- Preface -- Section I Single Use Plastics -- Chapter 1 Scientometric Analysis of Microplastics across the Globe -- 1.1 Introduction -- 1.2 Materials and Methods -- 1.3 Results and Discussion -- 1.3.1 Trends in Scientific Production and Citations -- 1.3.2 Top Funding Agencies -- 1.3.3 Top 10 Global Affiliations -- 1.3.4 Top Countries -- 1.3.5 Top 10 Databases and Journals -- 1.3.6 Top 10 Published Articles -- 1.3.7 Top 10 Author Keywords and Research Areas -- 1.4 Conclusion -- Acknowledgments -- References -- Chapter 2 Microplastic Pollution in the Polar Oceans - A Review -- 2.1 Introduction -- 2.1.1 Plastics -- 2.1.2 Plastic Pollution -- 2.1.3 Microplastics -- 2.1.4 Importance of Microplastic Pollution in the Polar Oceans -- 2.2 Polar Regions -- 2.2.1 General -- 2.2.2 Sea Ice -- 2.2.3 Water -- 2.2.4 Sediments -- 2.2.5 Biota -- 2.3 Future Perspectives -- 2.4 Conclusions -- References -- Chapter 3 Microplastics - Global Scenario -- 3.1 Introduction -- 3.2 Environmental Issues of Plastic Waste -- 3.3 Coprocessing of Plastic Waste in Cement Kilns -- 3.3.1 Cost of Plants to Convert Plastic Waste to Refused-Derived Fuel (RDF) -- 3.4 Disposal of Plastic Waste Through Plasma Pyrolysis Technology (PPT) -- 3.4.1 Merits of PPT -- 3.5 Constraints on the Use of Plastic Waste Disposal Technologies -- 3.6 Alternate to Conventional Petro-based Plastic Carry Bags and Films -- 3.7 Improving Waste Management -- 3.7.1 Phasing Out Microplastics -- 3.7.2 Promoting Research into Alternatives -- 3.7.3 Actions and Resolutions -- References -- Chapter 4 The Single-Use Plastic Pandemic in the COVID-19 Era -- 4.1 Introduction -- 4.2 Materials and Methods -- 4.2.1 Data Sources -- 4.2.2 Estimation of the General population's Daily Use of Face Masks. , 4.2.3 Estimation of the Daily Amount of Medical Waste in Hospitals -- 4.3 Trends in Production and Consumption of SUPs during the Pandemic -- 4.3.1 Personal Protective Equipment -- 4.3.2 Packaging SUPs -- 4.3.2.1 Trends in Plastic Waste Generation, Management, and Environmental Fate during the COVID-19 Era -- 4.4 SUP Waste from the Pandemic -- 4.4.1 Environmental Impacts from SUP Waste -- 4.4.2 Management of SUP Waste -- 4.5 Conclusions and Future Prospects -- References -- Section II Microplastics in the Aerosphere -- Chapter 5 Atmospheric Microplastic Transport -- 5.1 The Phenomenon of Microplastic Transport -- 5.2 Factors Affecting Microplastic Transport -- 5.2.1 Types of MPs -- 5.2.2 Characteristics and Sources of Microplastics Emitters -- 5.2.3 Meteorological Conditions -- 5.2.4 Altitude and Surface Roughness -- 5.2.5 Microplastic Deposition Processes in the Ocean -- 5.2.6 Microplastics Deposition Processes in the Air -- 5.3 Microplastic Transport Modelling -- 5.3.1 Eulerian Method -- 5.3.2 Lagrangian Method -- References -- Chapter 6 Microplastics in the Atmosphere and Their Human and Eco Risks -- 6.1 Introduction -- 6.2 Microplastics in the Atmosphere -- 6.2.1 Size, Shapes, and Colours -- 6.2.2 Chemical Composition -- 6.2.3 Sources of Microplastics -- 6.2.4 Spatial Distribution and Rate of Deposition -- 6.2.5 Effects of Climatic Conditions on MP Distribution -- 6.2.6 Transport Pathways -- 6.2.7 Pollutants Associated with MPs -- 6.3 Impact of Microplastics on Human Health and the Eco Risk -- 6.3.1 Impact on Human Health -- 6.3.2 Eco Risk -- 6.4 Strategies to Minimise Atmospheric MPs through Future Research -- 6.5 Conclusion -- Acknowledgements -- References -- Chapter 7 Sampling and Detection of Microplastics in the Atmosphere -- 7.1 Introduction -- 7.2 Classification -- 7.3 Sampling Microplastics -- 7.3.1 Sampling Airborne Microplastics. , 7.3.2 Sediment -- 7.3.3 Water -- 7.3.4 Biota -- 7.4 Sample Preparation -- 7.5 Detection and Characterisation of MPs in the Atmosphere -- 7.5.1 Microscopic Techniques for Detecting MPs -- 7.5.1.1 Stereomicroscopy -- 7.5.1.2 Fluorescence Microscopy -- 7.5.1.3 Polarised Optical Microscopy (POM) -- 7.5.1.4 Scanning Electron Microscopy (SEM) -- 7.5.1.5 Atomic Force Microscopy (AFM) -- 7.5.1.6 Hot Needle Technique -- 7.5.1.7 Digital Holography -- 7.5.2 Spectroscopic Techniques for Analysing MPs -- 7.5.2.1 Fourier Transform Infrared (FTIR) Spectroscopy -- 7.5.2.2 Raman Spectroscopy -- 7.5.3 Thermal Analysis -- 7.5.3.1 Differential Scanning Calorimetry (DSC) -- 7.5.3.2 Thermogravimetric Analysis (TGA) -- 7.5.3.3 Pyrolysis-Gas Chromatography-Mass Spectrometry (Pyr-GC-MS) -- 7.6 Conclusion -- Funding -- References -- Chapter 8 Sources and Circulation of Microplastics in the Aerosphere - Atmospheric Transport of Microplastics -- 8.1 Introduction -- 8.1.1 Occurrence and Abundance of Atmospheric MP -- 8.1.2 Plastic Polymers and Their Properties -- 8.1.3 Sources and Pathways of MPs in the Atmosphere -- 8.2 Temporal and Spatial Trends in MP Accumulation -- 8.2.1 Roadside MPs -- 8.2.2 Agricultural Fields and Soil -- 8.2.3 Wastewater and Sludge -- 8.2.4 Ocean/Marine Debris -- 8.3 Formation of MPs -- 8.3.1 Physical Weathering -- 8.3.2 Chemical Weathering -- 8.3.3 Biodegradation -- 8.3.4 Photo-thermal Oxidation -- 8.3.5 Thermal Degradation -- 8.4 Atmospheric Circulation, Transport, Suspension, and Deposition -- 8.4.1 Wet Deposition -- 8.4.2 Dry Deposition -- 8.4.3 Urban Dust -- 8.4.4 Suspended Atmospheric MPs -- 8.5 Atmospheric Chemistry of MPs -- 8.6 Predicting MP Dispersion and Transport -- 8.7 Eco-Environmental Impacts -- 8.7.1 Impacts on Human and Wildlife Health -- 8.7.2 Impacts on the Climate -- 8.8 Future Perspectives -- References. , Section III Microplastics in the Aquatic Environment -- Chapter 9 Interaction of Chemical Contaminants with Microplastics -- 9.1 Introduction -- 9.2 Interactions -- 9.3 Mechanisms -- 9.3.1 Interactions between Organic Contaminants and Microplastics -- 9.3.2 Interactions between Heavy Metals and Microplastics -- 9.3.3 Kinetics of the Sorption Process -- 9.3.4 Pseudo-First-Order Model -- 9.3.5 Pseudo-Second-Order Model -- 9.3.6 Intraparticle Diffusion Model -- 9.3.7 Film Diffusion Model -- 9.3.8 Isotherm Models -- 9.3.9 Langmuir Model -- 9.3.10 Freundlich Model -- 9.4 Environmental Burden of Microplastics -- 9.5 Future Approaches -- References -- Chapter 10 Microplastics in Freshwater Environments -- 10.1 Introduction -- 10.2 Microplastics in Rivers and Tributaries -- 10.3 Microplastics in Lakes -- 10.4 Microplastics in Groundwater Sources -- 10.5 Microplastics in Glaciers and Ice Caps -- 10.6 Microplastics in Deltas -- 10.7 Conclusion -- Acknowledgment -- References -- Chapter 11 Microplastics in Landfill Leachate: Flow and Transport -- 11.1 Plastics and Microplastics -- 11.2 Microplastics in Landfill Leachate -- 11.3 Summary -- Acknowledgments -- References -- Chapter 12 Microplastics in the Aquatic Environment - Effects on Ocean Carbon Sequestration and Sustenance of Marine Life -- 12.1 Introduction -- 12.2 Microplastics in the Aquatic Environment -- 12.2.1 Major Sources -- 12.2.2 Chemical Nature and Distribution Processes -- 12.2.2.1 Chemical Nature -- 12.2.2.2 Distribution Processes -- 12.3 Microplastics and Ocean Carbon Sequestration -- 12.3.1 Ocean Carbon Sequestration -- 12.3.2 Effect of Microplastics on Ocean Carbon Sequestration -- 12.3.2.1 Effect on Phytoplankton Photosynthesis and Growth -- 12.3.2.2 Effect on Zooplankton Development and Reproduction -- 12.3.2.3 Effect on the Marine Biological Pump -- 12.4 Microplastics and Marine Fauna. , 12.4.1 Effects on Corals -- 12.4.2 Effects on Fisheries and Aquaculture -- 12.4.2.1 Shrimp -- 12.4.2.2 Oysters and Mussels -- 12.4.2.3 Fish -- 12.4.3 Effects on Sea Turtles and Sea Birds -- 12.4.4 Effects on Marine Mammals -- 12.5 Microplastic Pollution, Climate Change, and Antibiotic Resistance - A Unique Trio -- 12.6 Conclusion and Future Perspectives -- Acknowledgments -- References -- Section IV Microplastics in Soil Systems -- Chapter 13 Entry of Microplastics into Agroecosystems: A Serious Threat to Food Security and Human Health -- 13.1 Introduction -- 13.2 Sources of Microplastics in Agroecosystems -- 13.2.1 Plastic Mulching -- 13.2.2 Plastic Use in Modern Agriculture -- 13.2.3 Application of Sewage Sludge/Biosolids -- 13.2.4 Compost and Fertilizers -- 13.2.5 Wastewater Irrigation -- 13.2.6 Landfill Sites -- 13.2.7 Atmospheric Deposition -- 13.2.8 Miscellaneous Sources -- 13.3 Implications of Microplastic Contamination on Agroecosystems -- 13.3.1 Implications for Soil Character -- 13.3.2 Implications for Crop Plants and Food Security -- 13.4 Human Health Risks -- 13.5 Knowledge Gaps -- 13.6 Conclusion and Future Recommendations -- Acknowledgments -- References -- Chapter 14 Migration of Microplastic-Bound Contaminants to Soil and Their Effects -- 14.1 Introduction -- 14.2 Microplastics as Sorbing Materials for Hazardous Chemicals -- 14.3 Types of Microplastic-Bound Contaminants in Soils -- 14.3.1 Heavy Metals and Metalloids - Inorganic Contaminants Adsorbed to MPs -- 14.3.2 Persistent Organic Pollutants, Pharmaceuticals, Antibiotics, Pesticides, and Other Organic Contaminants Adsorbed to MPs -- 14.4 Effects of Exposure and Co-exposure in Soil - Consequences of Contaminant Sorption for MP Toxicity and Bioaccumulation -- 14.5 Microplastic-Bound Contaminants in Soils as Potential Threats to Human Health -- 14.6 Conclusions -- References. , Chapter 15 Plastic Mulch-Derived Microplastics in Agricultural Soil Systems.
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  • 3
    Publication Date: 2024-07-07
    Description: The ²³⁴Th-²³⁸U radioactive pair has been extensively used to evaluate the efficiency with which photosyntetically fixed carbon is exported from the surface ocean by means of the biological pump since the 90's. The seminal work of Buesseler et al. (1992) proposed that particulate organic carbon (POC) flux can be indirectly calculated from ²³⁴Th distributions if the ratio of POC to ²³⁴Th measured on sinking particles (POC:²³⁴Th) at the desired export depth is known. Since then, a huge amount of ²³⁴Th depth profiles have been collected using a variety of sampling instruments and strategies that have changed along years. This is a global oceanic compilation of ²³⁴Th measurements, that collects results from innumerable researchers and laboratories over a period exceeding 50 years. The present compilation is made of a total 223 datasets: 214 from studies published either in articles in referred journals, PhD thesis or repositories, and 9 unpublished datasets. Including measurements from JGOFS, VERTIGO and GEOTRACES programs, with sampling from approximately 5000 locations spanning all the oceans. The compilation includes total ²³⁴Th profiles, dissolved and particulate ²³⁴Th concentrations, and POC:²³⁴Th ratios (both from pumps and sediment traps) for two sizes classes (1-53 μm and 〈 53 μm) when available. Appropriate metadata have been included, including geographic location, date, and sample depth, among others. When available, we also include water temperature, salinity, ²³⁸U data and particulate organic nitrogen data. Data sources and methods information (including ²³⁸U and ²³⁴Th) are also detailed along with valuable information for future data analysis such as bloom stage and steady/non-steady state conditions at the sampling moment. This undertaking is a treasure of data to understand and quantify how oceanic carbon cycle functions and how it will change in future. The compilation can be downloaded in three different ways: 1) A single merged file including all the individual excel files. This option can be accessed under "Other version: More than 50 years of Th-234 data: a comprehensive global oceanic compilation (single xlsx file)". 2) A summary table that includes details from cruise, sampling dates, techniques applied, authors and DOI of the compiled ²³⁴Th data, among others, each line corresponds to a specific dataset. The table can be accessed by clicking ""View dataset as HTML" and downloaded in "Download dataset as tab-delimited text". 3) Individual Excel files for each dataset can be manually chosen from the summary table, corresponding to the complete ²³⁴Th dataset and metadata from a specific publication or program. This option is available by clicking "View dataset as HTML". Furthermore, all files referred to can be downloaded in one go as ZIP or TAR.
    Keywords: 234Th; Author(s); Binary Object; biological carbon pump; Carbon, organic, particulate/Thorium-234 ratio; carbon export; Chief scientist(s); Cruise/expedition; DATE/TIME; ELEVATION; Gear; GEOTRACES; Global marine biogeochemical cycles of trace elements and their isotopes; JGOFS; Joint Global Ocean Flux Study; Journal/report title; LATITUDE; LONGITUDE; Multiple cruises/expeditions; Ocean; Ocean and sea region; Period; POC flux; Project; Reference of data; Thorium-234, dissolved; Thorium-234, particulate; Thorium-234, total; Uniform resource locator/link to reference; Uranium-238; Vessel; Year of publication
    Type: Dataset
    Format: text/tab-separated-values, 4056 data points
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  • 4
    Publication Date: 2024-04-27
    Description: There is a growing need for past weather and climate data to support science and decision-making. This paper describes the compilation and the construction of a global multivariable (air temperature, pressure, precipitation sum, number of precipitation days) monthly instrumental climate database that encompasses a substantial body of the known early instrumental time series. The dataset contains series compiled from existing databases that start before 1890 (though continuing to the present) as well as a large amount of newly rescued data. All series underwent a quality control procedure and subdaily series were processed to monthly mean values. An inventory was compiled, and the collection was deduplicated based on coordinates and mutual correlations. The data are provided in a common format accompanied by the inventory. The collection totals 12452 meteorological records in 118 countries. The data has been merged from 18250 original data files. The data can be used for climate reconstructions and analyses. It is the most comprehensive global monthly climate data set for the preindustrial period.
    Keywords: A Palaeoreanalysis To Understand Decadal Climate Variability; de-duplication; early instrumental; GlobCover; PALAEO-RA; paleoclimatology; Paleometeorology; quality control; Time series
    Type: Dataset
    Format: application/zip, 24 datasets
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  • 5
    Publication Date: 2024-01-16
    Description: Data on infauna and sediment characteristics were collected as part of an extensive research program on the effects of offshore wind turbines on the marine environment funded by the German Federal Maritime and Hydrographic Agency. The investigations were performed in the first German offshore wind farm alpha ventus in the German Bight (North Sea). The overall aim of the program was to evaluate the German national standard concept for environmental impact assessments for offshore wind farms. Specifically, our study addressed the potential changes of the infauna communities in different distances from single turbines in an early stage of the operational phase of the wind farm. The data were collected during the cruises HE296 (2008), HE313 (2009), HE340 (2010) and HE369 (2000) of the German research vessel RV Heincke. Infauna samples were taken with van Veen grab samples (sampling area: 0.1 m2, weight: 95 kg) inside the wind farm and in two reference sites outside the wind farm. Three replicate samples were taken at each station. The samples were sieved through a 1 mm mesh and species of the macro-infauna were determined to the lowest taxonomic level possible. Sub-samples of the sediments were fractionated in a cascade of sieves of different mesh sizes to determine the grain size distributions. The organic contents of the sediments were determined as weight loss on ignition. The dataset comprises 11,400 count and biomass records for 103 infaunal taxa (89 % on species level, 11 % others) from 528 samples. Sediments were characterised for 176 van Veen grabs.
    Type: Dataset
    Format: application/zip, 2 datasets
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  • 6
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    Unknown
    PANGAEA
    In:  Supplement to: Hiller, Anna E; Koo, Michelle S; Goodman, Kari R; Shaw, Kerry L; O'Grady, Patrick M; Gillespie, Rosemary G (2019): Niche conservatism predominates in adaptive radiation: comparing the diversification of Hawaiian arthropods using ecological niche modelling. Biological Journal of the Linnean Society, https://doi.org/10.1093/biolinnean/blz023
    Publication Date: 2024-02-17
    Description: Focal Taxa: Laupala, AMC Clade Drosophila, Tetragnatha, and Nesosydne. We assembled comprehensive occurrence datasets of all known records for each of the four lineages (included here), modeled their distributions using Maxent across the entire archipelago, and quantified niche overlap. Final base layers Mean Annual Air Temperature (°C), Mean Annual Rainfall (mm), Vegetation Height (m), and Normalized Difference Vegetation Index (NDVI) were selected based on optimum AUC values of trial models run. Rasters were obtained for the Rainfall Atlas of Hawaii, Climate of Hawaii, and USGS and resampled to a ~1km by ~1km resolution using smoothing for quantitative variables and nearest neighbor resampling for categorical variables (Giambelluca et al. 2013, Giambelluca et al. 2014, Hawaii Soil Survey 2000). Data presented here are the full set of georeferenced occurrence records, the filtered model inputs, and the final SDM models in ASCII format for each species. See the supplementary material in the corresponding publication (Hiller et al. 2017) for details on the georeferencing protocols used and a list of museum specimen numbers. Note that not all models were included in subsequent analyses due to poor quality (〈3 records as model input or low AUC score).
    Keywords: File content; File format; File size; Hawaii; Hawaiian Islands, North Central Pacific; Species; Uniform resource locator/link to file
    Type: Dataset
    Format: text/tab-separated-values, 659 data points
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  • 7
    Publication Date: 2024-01-16
    Description: Data on infauna and sediment characteristics were collected as part of an extensive research program on the effects of offshore wind turbines on the marine environment funded by the German Federal Maritime and Hydrographic Agency. The investigations were performed in the first German offshore wind farm alpha ventus in the German Bight (North Sea). The overall aim of the program was to evaluate the German national standard concept for environmental impact assessments for offshore wind farms. Specifically, our study addressed the potential changes of the infauna communities in different distances from single turbines in an early stage of the operational phase of the wind farm. The data were collected during the cruises HE296 (2008), HE313 (2009), HE340 (2010) and HE369 (2011) of the German research vessel RV HEINCKE. Infauna samples were taken with van Veen grab samples (sampling area: 0.1 m2, weight: 95 kg) inside the wind farm and in two reference sites outside the wind farm. Three replicate samples were taken at each station. The samples were sieved through a 1 mm mesh and species of the macro-infauna were determined to the lowest taxonomic level possible. Sub-samples of the sediments were fractionated in a cascade of sieves of different mesh sizes to determine the grain size distributions. The organic contents of the sediments were determined as weight loss on ignition. The dataset comprises 11,400 count and biomass records for 103 infaunal taxa (89 % on species level, 11 % others) from 528 samples. Sediments were characterised for 176 van Veen grabs.
    Keywords: Area/locality; Biomass, wet mass; Counts; DATE/TIME; DEPTH, water; Event label; Gear; HE296; HE296/865-1; HE296/865-2; HE296/865-3; HE296/866-2; HE296/866-3; HE296/866-4; HE296/867-2; HE296/867-3; HE296/867-4; HE296/868-1; HE296/868-2; HE296/868-3; HE296/903-1; HE296/903-2; HE296/904-1; HE296/905-1; HE296/905-2; HE296/905-4; HE296/906-2; HE296/906-3; HE296/906-4; HE296/907-2; HE296/907-3; HE296/907-4; HE296/908-2; HE296/908-3; HE296/908-4; HE296/912-1; HE296/912-3; HE296/912-4; HE296/913-1; HE296/913-3; HE296/913-4; HE296/914-1; HE296/914-3; HE296/914-4; HE296/915-2; HE296/915-3; HE296/915-4; HE296/916-2; HE296/916-3; HE296/916-4; HE296/917-1; HE296/917-2; HE296/917-3; HE296/918-1; HE296/918-2; HE296/918-4; HE296/919-1; HE296/919-3; HE296/919-4; HE296/920-1; HE296/920-2; HE296/920-3; HE296/921-1; HE296/921-3; HE296/921-4; HE296/923-1; HE296/923-2; HE296/923-3; HE296/924-1; HE296/924-2; HE296/924-3; HE296/925-1; HE296/925-2; HE296/925-3; HE296/926-1; HE296/926-3; HE296/926-4; HE296/927-2; HE296/927-3; HE296/927-4; HE296/928-1; HE296/928-3; HE296/928-4; HE296/929-1; HE296/929-2; HE296/929-3; HE296/930-1; HE296/930-2; HE296/930-3; HE296/931-1; HE296/931-2; HE296/931-3; HE296/932-1; HE296/932-3; HE296/932-4; HE296/933-1; HE296/933-2; HE296/933-4; HE296/934-1; HE296/934-2; HE296/934-3; HE296/935-1; HE296/935-2; HE296/935-4; HE296/936-1; HE296/936-2; HE296/936-3; HE296/949-1; HE296/949-2; HE296/949-3; HE296/950-1; HE296/950-2; HE296/950-4; HE296/951-1; HE296/951-3; HE296/951-4; HE296/952-1; HE296/952-3; HE296/952-4; HE296/953-1; HE296/953-2; HE296/953-3; HE296/954-1; HE296/954-2; HE296/954-3; HE296/955-1; HE296/955-2; HE296/955-4; HE296/956-1; HE296/956-2; HE296/956-3; HE296/965-1; HE296/965-2; HE296/965-3; HE296/992-1; HE296/992-3; HE296/992-4; HE296/993-2; HE296/993-3; HE296/993-4; HE313; HE313/916-2; HE313/916-3; HE313/916-4; HE313/917-2; HE313/917-3; HE313/917-4; HE313/918-2; HE313/918-3; HE313/918-4; HE313/919-2; HE313/919-3; HE313/919-4; HE313/920-2; HE313/920-3; HE313/920-4; HE313/921-1; HE313/921-4; HE313/922-2; HE313/922-3; HE313/922-4; HE313/923-2; HE313/923-3; HE313/923-4; HE313/924-2; HE313/924-3; HE313/924-4; HE313/925-2; HE313/925-3; HE313/925-4; HE313/926-2; HE313/926-3; HE313/926-4; HE313/927-2; HE313/927-3; HE313/927-4; HE313/928-2; HE313/928-3; HE313/928-4; HE313/929-2; HE313/929-3; HE313/929-4; HE313/930-2; HE313/930-3; HE313/930-4; HE313/931-2; HE313/931-3; HE313/931-4; HE313/932-2; HE313/932-3; HE313/932-4; HE313/933-2; HE313/933-3; HE313/933-4; HE313/934-2; HE313/934-3; HE313/934-4; HE313/935-2; HE313/935-3; HE313/935-4; HE313/936-2; HE313/936-3; HE313/936-4; HE313/941-2; HE313/941-3; HE313/941-4; HE313/942-2; HE313/942-3; HE313/942-4; HE313/943-2; HE313/943-3; HE313/943-4; HE313/944-2; HE313/944-3; HE313/944-4; HE313/945-2; HE313/945-3; HE313/945-4; HE313/946-2; HE313/946-3; HE313/946-4; HE313/947-2; HE313/947-3; HE313/947-4; HE313/948-2; HE313/948-3; HE313/948-4; HE313/955-2; HE313/955-3; HE313/955-4; HE313/956-2; HE313/956-3; HE313/956-4; HE313/957-2; HE313/957-3; HE313/957-4; HE313/958-2; HE313/958-3; HE313/958-4; HE313/959-2; HE313/959-3; HE313/959-4; HE313/960-2; HE313/960-3; HE313/960-4; HE313/961-2; HE313/961-3; HE313/961-4; HE313/962-2; HE313/962-3; HE313/962-4; HE313/963-2; HE313/963-3; HE313/963-4; HE313/964-2; HE313/964-3; HE313/964-4; HE313/965-2; HE313/965-3; HE313/965-4; HE313/966-2; HE313/966-3; HE313/966-4; HE313/967-2; HE313/967-3; HE313/967-4; HE313/968-2; HE313/968-3; HE313/968-4; HE313/969-2; HE313/969-3; HE313/969-4; HE340; HE340/03-2; HE340/03-3; HE340/03-4; HE340/04-2; HE340/04-3; HE340/04-4; HE340/05-2; HE340/05-3; HE340/05-4; HE340/06-2; HE340/06-3; HE340/06-4; HE340/07-2; HE340/07-3; HE340/07-4; HE340/08-2; HE340/08-3; HE340/08-4; HE340/09-2; HE340/09-3; HE340/09-4; HE340/10-2; HE340/10-3; HE340/10-4; HE340/11-2; HE340/11-3; HE340/11-4; HE340/12-2; HE340/12-3; HE340/12-4; HE340/13-2; HE340/13-3; HE340/13-4; HE340/14-2; HE340/14-3; HE340/14-4; HE340/15-2; HE340/15-3; HE340/15-4; HE340/16-2; HE340/16-3; HE340/16-4; HE340/17-2; HE340/17-3; HE340/17-4; HE340/18-2; HE340/18-3; HE340/18-4; HE340/19-2; HE340/19-3; HE340/19-4; HE340/20-2; HE340/20-3; HE340/20-4; HE340/21-2; HE340/21-3; HE340/21-4; HE340/22-2; HE340/22-3; HE340/22-4; HE340/23-2; HE340/23-3; HE340/23-4; HE340/24-2; HE340/24-3; HE340/24-4; HE340/25-2; HE340/25-3; HE340/25-4; HE340/26-2; HE340/26-3; HE340/26-4; HE340/27-2; HE340/27-3; HE340/27-4; HE340/47-2; HE340/47-3; HE340/47-4; HE340/48-2; HE340/48-3; HE340/48-4; HE340/49-2; HE340/49-3; HE340/49-4; HE340/50-2; HE340/50-3; HE340/50-4; HE340/51-2; HE340/51-3; HE340/51-4; HE340/56-2; HE340/56-3; HE340/56-4; HE340/57-2; HE340/57-3; HE340/57-4; HE340/58-2; HE340/58-3; HE340/58-4; HE340/59-2; HE340/59-3; HE340/59-4; HE340/60-2; HE340/60-3; HE340/60-4; HE340/61-2; HE340/61-3; HE340/61-4; HE340/62-2; HE340/62-3; HE340/62-4; HE340/63-2; HE340/63-3; HE340/63-4; HE340/64-2; HE340/64-3; HE340/64-4; HE340/65-2; HE340/65-3; HE340/65-4; HE340/66-2; HE340/66-3; HE340/66-4; HE340/67-2; HE340/67-3; HE340/67-4; HE340/73-2; HE340/73-3; HE340/73-4; HE340/74-2; HE340/74-3; HE340/74-4; HE369; HE369/001-2; HE369/001-3; HE369/001-4; HE369/002-1; HE369/003-1; HE369/004-1; HE369/005-1; HE369/006-1; HE369/007-1; HE369/008-1; HE369/009-1; HE369/010-1; HE369/011-1; HE369/012-1; HE369/015-1; HE369/016-1; HE369/017-1; HE369/018-1; HE369/023-2; HE369/023-3; HE369/023-4; HE369/024-1; HE369/025-1; HE369/026-1; HE369/027-1; HE369/028-1; HE369/029-1; HE369/030-1; HE369/031-1; HE369/032-1; HE369/033-1; HE369/034-1; HE369/035-1; HE369/036-1; HE369/058-1; HE369/059-1; HE369/060-1; HE369/061-1; HE369/062-1; HE369/063-1; HE369/064-1; HE369/065-1; HE369/066-1; HE369/067-1; HE369/068-1; HE369/069-1; HE369/070-1; HE369/071-1; Heincke; LATITUDE; LONGITUDE; North Sea; Penetration depth; Project; Replicate; Scientific name; van Veen Grab; VGRAB
    Type: Dataset
    Format: text/tab-separated-values, 90465 data points
    Location Call Number Limitation Availability
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  • 8
    Publication Date: 2024-01-16
    Description: Data on infauna and sediment characteristics were collected as part of an extensive research program on the effects of offshore wind turbines on the marine environment funded by the German Federal Maritime and Hydrographic Agency. The investigations were performed in the first German offshore wind farm alpha ventus in the German Bight (North Sea). The overall aim of the program was to evaluate the German national standard concept for environmental impact assessments for offshore wind farms. Specifically, our study addressed the potential changes of the infauna communities in different distances from single turbines in an early stage of the operational phase of the wind farm. The data were collected during the cruises HE296 (2008), HE313 (2009), HE340 (2010) and HE369 (2011) of the German research vessel RV HEINCKE. Infauna samples were taken with van Veen grab samples (sampling area: 0.1 m2, weight: 95 kg) inside the wind farm and in two reference sites outside the wind farm. Three replicate samples were taken at each station. The samples were sieved through a 1 mm mesh and species of the macro-infauna were determined to the lowest taxonomic level possible. Sub-samples of the sediments were fractionated in a cascade of sieves of different mesh sizes to determine the grain size distributions. The organic contents of the sediments were determined as weight loss on ignition. The dataset comprises 11,400 count and biomass records for 103 infaunal taxa (89 % on species level, 11 % others) from 528 samples. Sediments were characterised for 176 van Veen grabs.
    Keywords: Area/locality; Campaign; DATE/TIME; Event label; HE296; HE296/865-1; HE296/866-1; HE296/867-1; HE296/868-1; HE296/904-1; HE296/905-1; HE296/906-1; HE296/907-1; HE296/908-1; HE296/912-1; HE296/913-1; HE296/914-1; HE296/915-1; HE296/916-1; HE296/917-1; HE296/918-1; HE296/919-1; HE296/920-1; HE296/921-1; HE296/923-1; HE296/924-1; HE296/925-1; HE296/926-1; HE296/927-1; HE296/928-1; HE296/929-2; HE296/930-1; HE296/931-1; HE296/932-1; HE296/933-1; HE296/934-1; HE296/935-1; HE296/936-1; HE296/949-1; HE296/950-1; HE296/951-1; HE296/952-3; HE296/953-1; HE296/954-1; HE296/955-1; HE296/956-2; HE296/965-1; HE296/992-1; HE296/993-1; HE313; HE313/916-1; HE313/917-1; HE313/918-1; HE313/919-1; HE313/920-1; HE313/921-1; HE313/922-1; HE313/924-1; HE313/925-1; HE313/926-1; HE313/927-1; HE313/928-1; HE313/929-1; HE313/930-1; HE313/931-1; HE313/932-1; HE313/933-1; HE313/934-1; HE313/935-1; HE313/936-1; HE313/941-1; HE313/942-1; HE313/943-1; HE313/944-1; HE313/945-1; HE313/946-1; HE313/947-1; HE313/948-1; HE313/955-1; HE313/956-1; HE313/957-1; HE313/958-1; HE313/959-1; HE313/960-1; HE313/961-1; HE313/962-1; HE313/963-1; HE313/964-1; HE313/965-1; HE313/966-1; HE313/967-1; HE313/968-1; HE313/969-1; HE340; HE340/03-1; HE340/04-1; HE340/05-1; HE340/06-1; HE340/07-1; HE340/08-1; HE340/09-1; HE340/10-1; HE340/11-1; HE340/12-1; HE340/13-1; HE340/14-1; HE340/15-1; HE340/16-1; HE340/17-1; HE340/18-1; HE340/19-1; HE340/20-1; HE340/21-1; HE340/22-1; HE340/23-1; HE340/24-1; HE340/25-1; HE340/26-1; HE340/27-1; HE340/47-1; HE340/48-1; HE340/49-1; HE340/50-1; HE340/51-1; HE340/56-1; HE340/57-1; HE340/58-1; HE340/59-1; HE340/60-1; HE340/61-1; HE340/62-1; HE340/63-1; HE340/64-1; HE340/65-1; HE340/66-1; HE340/67-1; HE340/73-1; HE340/74-1; HE369; HE369/001-1; HE369/002-1; HE369/003-1; HE369/004-1; HE369/005-1; HE369/006-1; HE369/007-1; HE369/008-1; HE369/009-1; HE369/010-1; HE369/011-1; HE369/012-1; HE369/015-1; HE369/016-1; HE369/017-1; HE369/018-1; HE369/023-1; HE369/024-1; HE369/025-1; HE369/026-1; HE369/027-1; HE369/028-1; HE369/029-1; HE369/030-1; HE369/031-1; HE369/032-1; HE369/033-1; HE369/034-1; HE369/035-1; HE369/036-1; HE369/058-1; HE369/059-1; HE369/060-1; HE369/061-1; HE369/062-1; HE369/063-1; HE369/064-1; HE369/065-1; HE369/066-1; HE369/067-1; HE369/068-1; HE369/069-1; HE369/070-1; HE369/071-1; Heincke; LATITUDE; LONGITUDE; Loss on ignition; mesh sieved; North Sea; Project; Replicate; Sample mass; Sample method; Size fraction 〈 0.063 mm, mud, silt+clay; Size fraction 〉 0.063 mm, sand; Size fraction 〉 0.125 mm; Size fraction 〉 0.250 mm; Size fraction 〉 0.500 mm, gravel; Size fraction 〉 1 mm, gravel; Size fraction 〉 2 mm, gravel; Station label; van Veen Grab; VGRAB
    Type: Dataset
    Format: text/tab-separated-values, 2640 data points
    Location Call Number Limitation Availability
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