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71 results for “Coastal modelling”
Data from: Phylogeography, population genetics, and distribution modeling reveal vulnerability of Scirpus longii (Cyperaceae) and the Atlantic Coastal Plain Flora to climate change.
A proactive approach to conservation must be predictive, anticipating how habitats will change and which species are likely to decline or prosper. We use composite species distribution modeling to identify suitable habitats for 18 members of the North American Atlantic Coastal Plain Flora (ACPF) since the Last Glacial Maximum and project these into the future. We then use Scirpus longii (Cyperaceae), a globally imperiled ACPF sedge with many of the characteristics of extinction vulnerability, as a case study. We integrate phylogeographic and population genetic analyses and species distribution modeling to develop a broad view of its current condition and prognosis for conservation. We use genotyping-by-sequencing to characterize the genomes of 142 S. longii individuals from twenty populations distributed throughout its range (New Jersey to Nova Scotia). We measure the distribution of genetic diversity in the species and reconstruct its phylogeographic history using SNAPP and RASE. Extant populations of S. longii originated from a single refugium south of the Laurentide ice sheet around 25 thousand years ago. The genetic diversity of S. longii is exceedingly low, populations exhibit little genetic structure, and the species is slightly inbred. Projected climate scenarios indicate that nearly half of extant populations of S. longii will be exposed to unsuitable climate by 2070. Similar changes in suitable habitat will occur for many other northern ACPF species – centers of diversity will shift northward and Nova Scotia may become the last refuges for those species not extinguished.
ICON-Coast model output for a study on the impact of Arctic coastal erosion on sea water carbonate saturation.
<p>Primary output of the ocean-biogeochemistry model ICON-Coast that has been used to create the figures in a manuscript on the impact of Arctic coastal erosion on sea water carbonate saturation.</p>
Supporting materials for 'Building quantitative skills with a simplified physical model of coastal storm deposition'
<p>Supporting Materials for Lazarus (2024): "Building quantitative skills with a simplified physical model of coastal storm deposition" (preprint <a href="https://doi.org/10.31223/X56H5B">here</a>).</p> <p>Files include:</p> <ul> <li><strong>DEM_washover_final_demo.tif </strong>– "final" DEM for a bare back-barrier floodplain in a physical laboratory experiment of coastal barrier overwash</li> <li><strong>Lazarus_2024_experimental_washover_exercise_instructions_Zenodo_release.pdf</strong> – step-by-step instructions for a classroom exercise that guides students through using the 'DEM_washover_final_demo' file to digitise, measure, and plot washover deposits with QGIS and Python</li> <li><strong>experiments_plotting_simple.ipynb</strong> – Python notebook for plotting results from classroom exercise</li> <li><strong>Lazarus_2024_washover_exercise_figs.ipynb</strong> – Python notebook for plotting Figs. 3 & 4 in the accompanying manuscript (Lazarus, 2024)</li> <li><strong>GGES2021_S24_data_all_release.csv</strong> – dataset of morphometric measurements presented and discussed in the accompanying manuscript (<a href="https://doi.org/10.31223/X56H5B">Lazarus, 2024</a>)</li> </ul>
Groundwater model outputs for coastal aquifer system
<p>Model outputs for 9 predevelopment coastal groundwater models, and one development scenario for each of these models. This data has been used to generate results for a manuscript which has been submitted for publication.</p>
Multiple-model stock assessment frameworks for precautionary management and conservation on fishery-targeted coastal dolphin populations off Japan
<p>1. Stock assessment approaches are often oversimplified due to lack of biological knowledge and insufficient data. In spite of worldwide attention, fishery-targeted coastal dolphin species in Japan have lacked in-depth quantitative stock assessments because of limited time-series of population size and an absence of associated biological information. We consequently developed integrated population models that analyzed multiple sources of data simultaneously with published biological information within a Bayesian framework.<br> 2. We estimate population status and trends for three main species targeted by fisheries, bottlenose dolphins <em>Tursiops truncatus</em>, Risso's dolphins <em>Grampus griseus</em>, and short-finned pilot whales <em>Globicephala macrorhynchus</em>, using single-species age-aggregated and age-structured population dynamics models. Models were fit to absolute abundance estimates from systematic line-transect surveys, four series of abundance indices calculated from fisher's logbooks, and historical catch records. Published biological information was used to develop prior distributions for the biological parameters. We assessed the possible effects of ecological disturbance and competition using state-space and multispecies models.<br> 3. The multispecies model was selected by the model selection both for the age-aggregated and the age-structured approaches.<br> 4. Single-species assessments found that population size declined 4.2% (Risso's dolphin) to 8.0% (bottlenose dolphin) for three species since the late 1800s based on median posterior values, while the state-space and multispecies models found that environmental disturbance and an interaction among species could have reduced population size more substantially.<br> 5. '<em>Policy implications</em>' Simple single-species models are often used to provide conservation and management advice for wild animals but, in this case, results from such models are overly optimistic because they overlook important ecological process. In contrast, current population status could be less favorable if environmental disturbance and interspecific competition actually control population dynamics. Even if that is not the case, considering ecological process in the model will provide more precautionary ways. Our approach of combining multiple modelling frameworks is applicable to many other management systems, and offers increased confidence in estimated status and trends over assessments that consider only a single model.</p>
ECCO-Darwin ED-SBS model and running instructions for "Biogeochemical river runoff drives intense coastal Arctic Ocean outgassing"
<p>Here is the model code and instructions file to run the ED-SBS simulations of "Biogeochemical river runoff drives intense Arctic Ocean outgassing" article.</p> <p>For more informations follow the instructions in the README.md file.</p>
Exploring controls on coastal dune growth through a simplified model [Dataset]
<p>This dataset contains the Duna model output data, included in the article “Exploring controls on coastal dune growth through a simplified model” published in the <em>Journal of Geophysical Research - Earth Surface</em>.</p> <p>The data is provided as “Fig*.mat” files, processed in MatLab (R2023a), and organised following the structure of the figures presented in the manuscript (e.g., Fig1.mat corresponds to data shown in Fig.1). </p> <p>'Dataset.docx' provides information on the individual files contained in the dataset.</p>
A Multi-algorithm Approach for Modeling Coastal Wetland Eco-geomorphology
<p>This dataset includes the input data for MACES to run simulations on three representative coastal wetland sites: two saltmarsh wetland (Venice Lagoon and Plum Island Estuary) and a mangrove wetland (Hunter Estuary).</p>
Data from: Phylogeography, population genetics, and distribution modeling reveal vulnerability of Scirpus longii (Cyperaceae) and the Atlantic Coastal Plain Flora to climate change.
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Global coastal wind hazard maps from the CHAZ tropical cyclone model
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High-resolution species distribution modelling of two coastal biogenic habitat-forming species in an Ecologically and Biologically Significant Area of the Bay of Fundy, Canada
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Modelling coastal connectivity in the Mediterranean Sea: Similar effects of changes in hydrodynamics and reduction in planktonic duration
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Multiple-model stock assessment frameworks for precautionary management and conservation on fishery-targeted coastal dolphin populations off Japan
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Modeling and Monitoring Submerged Prehistoric Sites during Offshore Sand Dredging and Implications for the Study of Early Holocene Coastal Occupation of Southern California
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Datatset from "Coastal flooding in the Maldives induced by mean sea-level rise and wind-waves: from global to local coastal modelling"
<p>Resulting downscaled wave fields from the WaveWatch III simulations for the four main wave directions identified and six return periods (10, 20, 50, 100, 500, and 1000 years).</p>
Dynamic Load Balancing for Predictions of Storm Surge and Coastal Flooding-Model setup and source code
<p>Source code and model setup/inputs for the paper titled "Dynamic Load Balancing for Predictions of Storm Surge and Coastal Flooding" article. Simulations were conducted using a modified version of ADCIRC+DLB (ADCIRC + Dynamic Load Balancing) on unstructured triangular meshes.</p> <p>Contains:</p> <ol> <li>Model input files. <ol> <li>ADCIRC model input files for the ideal channel setup and Hurricane Irene simulation (*.13, *.14, *.15)</li> </ol> </li> <li>Zipped archive of the ADCIRC code (adcirc-cg-DLB.zip) used to produce the simulations for the paper.</li> <li>Step-by-step compilation and usage instructions for ADCIRC+DLB. <ol> <li>Installation.html </li> <li>Usage.html</li> </ol> </li> </ol>
Figure 3 in Natural history and ecological niche modelling of coastal Atyphella Olliff Larvae (Lampyridae: Luciolinae) in Vanuatu
Figure 3. Distributions of pronotal widths and resulting predicted instars in two species of coastal Atyphella.
Figure 2 in Natural history and ecological niche modelling of coastal Atyphella Olliff Larvae (Lampyridae: Luciolinae) in Vanuatu
Figure 2. (a) Collection site of coastal Atyphella. Yellow dots indicate locations specimens were collected in 2018. (b) Predictive model for possible localities of coastal Atyphella in Vanuatu. White squares indicate locations Atyphella was collected in 2018.
Figure 1 in Natural history and ecological niche modelling of coastal Atyphella Olliff Larvae (Lampyridae: Luciolinae) in Vanuatu
Figure 1. (a) Typical habitat of coastal Atyphella (Efate, Vanuatu). (b) Typical habitat of coastal Atyphella (Malekula, Vanuatu). (c) Experimental setup of submersion experiment. (d) Captive coastal Atyphella feeding on snail.
Data from: Where consumers control plant reproduction in coastal wetlands: the environmental stress model in plants' versus consumers' perspectives
<p>This is the data set for the paper entitled "Where consumers control plant reproduction in coastal wetlands: the environmental stress model in plants’ versus consumers’ perspectives" upcoming in the Journal of Ecology.</p> <p>The metadata for interpreting the data set are included in the Excel file. </p>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.