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Full-Text Articles in Life Sciences
Input, Output And Complete Run Files For The Atlantis Ecosystem Model Deepwater Horizon Oil Spill Simulations Including Fish And Invertebrate Effects, Cameron Ainsworth, Lindsey N. Dornberger
Input, Output And Complete Run Files For The Atlantis Ecosystem Model Deepwater Horizon Oil Spill Simulations Including Fish And Invertebrate Effects, Cameron Ainsworth, Lindsey N. Dornberger
C-IMAGE data
These data include input and output files from the Gulf of Mexico Atlantis model. The simulations are published in Dornberger et al., 2019. The dataset includes every file needed to recreate the simulations: 1) the 18 spatial forcing files needed to recreate the sensitivity analysis; these vary the oil sensitivity threshold K, the fish oil threshold and the invertebrate oil threshold. The file naming scheme indicates parameter values used. 2) the three .prm files needed to recreate the different levels of fishing mortality (F=0.5, 1, 2.0, 10), The F rate indicates an increase in fishing mortality across all fishing sectors …
Hepatic Polycyclic Aromatic Hydrocarbons (Pahs) In Gulf And Southern Hake Collected Aboard Multiple R/V Weatherbird Ii Cruises In The Gulf Of Mexico From 2012-08-21 To 2015-09-24, Erin Pulster, Steven A. Murawski, Rachel Struch
Hepatic Polycyclic Aromatic Hydrocarbons (Pahs) In Gulf And Southern Hake Collected Aboard Multiple R/V Weatherbird Ii Cruises In The Gulf Of Mexico From 2012-08-21 To 2015-09-24, Erin Pulster, Steven A. Murawski, Rachel Struch
C-IMAGE data
This dataset contains hepatic polycyclic aromatic hydrocarbons (PAHs) in Gulf and Southern Hake collected aboard multiple R/V Weatherbird II cruises in the Gulf of Mexico from 2012-08-21 to 2015-09-24. PAH was extracted from liver samples using a modified QuEChERS (Bond Elut, Agilent Technologies, Santa Clara, CA, USA) method optimized specifically for these study species. Extracts were analyzed using Agilent’s 7890B gas chromatograph (GC) coupled to a 7010 tandem mass spectrometer (MS/MS) operating in multiple reactions mode (MRM). The dataset contains the location, date, biometrics, and the total concentration of polycyclic aromatic hydrocarbon (PAHs) in livers. The cruise documentation was provided …
Spectral Variability Of Oil Slicks Under Different Observing Conditions Derived From Satellite And Airborne Optical Remote Sensing, Chuanmin Hu
C-IMAGE data
In this dataset, we present the spectral variability of oil slicks under different observing conditions using MODIS (Moderate Resolution Imaging Spectroradiometer), MERIS (Medium Resolution Imaging Spectrometer), MISR (Multi-angle Imaging SpectroRadiometer), Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and AVIRIS (Airborne Visible/ Infrared Imaging Spectrometer). Optical remote sensing is commonly used to detect oil in the surface ocean due to the spectral differences between oil and water, allowing to modulate oil–water spatial and spectral contrasts. However, understanding these contrasts is challenging because of variable results from laboratory and field experiments, as well as different observing conditions and spatial/spectral resolutions of remote …
Input, Output And Complete Run Files For The Atlantis Ecosystem Model Deepwater Horizon Oil Spill Simulations, Cameron Ainsworth
Input, Output And Complete Run Files For The Atlantis Ecosystem Model Deepwater Horizon Oil Spill Simulations, Cameron Ainsworth
C-IMAGE data
Data are complete input, output, and executable model run files for Atlantis simulations of the Deepwater Horizon oil spill. The model outputs in these folders describe simulations from 2010 to 2035; the spatial domain is the entire Gulf of Mexico. Simulations are published as Ainsworth, C.H., Paris, C.B., Perlin, N., Dornberger, L.N., Patterson, W., Chancellor, E., Murawski, S., Hollander, D., Daly, K., Romero, I.C., Coleman, F. and Perryman, H. 2018. Impacts of the Deepwater Horizon oil spill evaluated using an end-to-end ecosystem model. PLoS One, 13(1): e0190840 doi: 10.1371/journal.pone.0190840
Dataset For: Tracking An Oil Tanker Collision And Spilled Oils In The East China Sea Using Multisensor Day And Night Satellite Imagery, Shaojie Sun
C-IMAGE data
In this dataset, we used a multi-sensor day and night satellite approach to track the SANCHI oil tanker collision and oil spill event in January 2018 in the East China Sea. The drifted on fire oil tanker was tracked by Visible Infrared Imaging Radiometer Suite (VIIRS) Nightfire product and Day/Night Band (DNB) imagery. Such pathway and locations were also reproduced with a numerical model, with RMS error of < 15 km. MultiSpectral Instrument (MSI) optical imagery during daytime shows smokes on 13 January 2018, further confirms the drifted tanker location. MSI imagery after 4 days of the tanker’s sinking (18 January 2018) reveals oil on the ocean surface to the east and northeast of the tanker sinking location. This combination of all available remote sensing and modeling techniques can provide effective means to monitor marine accidents and oil spills to assist event response.
Evaluation Of Diet Matrix Uncertainty For The Atlantis Model, Cameron Ainsworth
Evaluation Of Diet Matrix Uncertainty For The Atlantis Model, Cameron Ainsworth
C-IMAGE data
We conducted 1000 Atlantis simulations, using permutated diet matrices created by drawing from a beta distribution that represented uncertainty in predator diet. We also employed a statistical emulator which simulates the production of many more Atlantis runs than could be achieved through numerical simulation. This dataset includes 3 products: statistical emulator output, diet matrices, and Atlantis simulations. These are each contained in their own zip file.
Remote Sensing Estimation Of Surface Oil Volume During The 2010 Deepwater Horizon Oil Blowout In The Gulf Of Mexico: Scaling Up Aviris Observation With Modis Measurements, Chuanmin Hu, Lian Feng
Remote Sensing Estimation Of Surface Oil Volume During The 2010 Deepwater Horizon Oil Blowout In The Gulf Of Mexico: Scaling Up Aviris Observation With Modis Measurements, Chuanmin Hu, Lian Feng
C-IMAGE data
This dataset contains Rayleigh corrected reflectance data from 19 MODIS images collected between April and July 2010, along with their corresponding maps of surface oil volume, maps of relative oil thickness of different classes, and maps of probability distributions of different thicknesses. Surface oil was estimated by spatially scaling up AVIRIS observations to synoptic MODIS measurements, which were the used to derived oil classification and probability maps.
Ixtoc-I Oil Spill Footprints Derived From Coastal Zone Color Scanner And Landsat/Mss Imagery, Shaojie Sun
Ixtoc-I Oil Spill Footprints Derived From Coastal Zone Color Scanner And Landsat/Mss Imagery, Shaojie Sun
C-IMAGE data
This dataset contains Coastal Zone Color Scanner (CZCS) and Landsat/MSS images used to identify the surface oil footprints created by the Ixtoc-I oil spill in 1979. There are two periods of imagery: June 1979-March 1980 is the oil spill period; and Jan. 1981-Dec. 1982 is the reference period. Oil slick surface footprints derived from the images are also included in the dataset. They are either in the format of shapefile or ArcGIS personal geodatabase.
Dataset For: Sun Glint Requirement For The Remote Detection Of Surface Oil Films, Mengqiu Wang
Dataset For: Sun Glint Requirement For The Remote Detection Of Surface Oil Films, Mengqiu Wang
C-IMAGE data
This dataset includes selected points and their sun glint strength values of image pairs which were used in determining the sun glint threshold required for remotely sensing oil films in the northern Gulf of Mexico. The satellite imagery used in the analyses were collected by Moderate Resolution Imaging Spectroradiometer (MODIS) Terra (MODIST), MODIS Aqua (MODISA), and Visible Infrared Imaging Radiometer Suite (VIIRS) instruments. The dataset includes original raw file lists of the imagery used and information about how they can accessed can be found in the Supplemental Information section of the metadata. Post processing MODIS Rayleigh corrected reflectance (Rrc) data, …
Land Cover Data For The Mississippi-Alabama Barrier Islands, 2010-2011 Arcgis V10.3 Geodatabase, Gregory A. Carter, Carlton P. Anderson, Kelly L. Lucas, Nathan L. Hopper
Land Cover Data For The Mississippi-Alabama Barrier Islands, 2010-2011 Arcgis V10.3 Geodatabase, Gregory A. Carter, Carlton P. Anderson, Kelly L. Lucas, Nathan L. Hopper
Land Cover Data for the Mississippi-Alabama Barrier Islands, 2010-2011
Land cover on the Mississippi-Alabama barrier islands was surveyed in 2010-2011 as part of continuing research on island geomorphic and vegetation dynamics following the 2005 impact of Hurricane Katrina. Results of the survey include sub-meter GPS location, a listing of dominant vegetation species and field photographs recorded at 375 sampling locations distributed among Cat, West Ship, East Ship, Horn, Sand, Petit Bois and West Dauphin Islands. The survey was conducted in a period of intensive remote sensing data acquisition over the northern Gulf of Mexico by federal, state and commercial organizations in response to the 2010 Macondo Well (Deepwater Horizon) …
Spatial Distributions Of Fish And Invertebrates In The Gulf Of Mexico For 2010-01-01 Estimated Using A Statistical Model, Michael Drexler
Spatial Distributions Of Fish And Invertebrates In The Gulf Of Mexico For 2010-01-01 Estimated Using A Statistical Model, Michael Drexler
C-IMAGE data
A generalized additive modelling (GAM) approach is used to describe the abundance of 40 species groups (i.e. functional groups) across the Gulf of Mexico (GoM) using a large fisheries independent data set (SEAMAP) and climate scale oceanographic conditions. Predictor variables included in the model are chlorophyll a, sediment type, dissolved oxygen, temperature, and depth. The GAM approach was shown to be robust despite zero-inflated data. article: http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0064458