Attribute_Accuracy:
Attribute_Accuracy_Report:
A multi-stage error checking process is used to verify both attribute accuracy and logical consistency throughout data production. The process includes a standardized data entry methodology, data review by in-house and external resource experts, a final Quality Assurance/Quality Control (QA/QC) process, and multiple automated logical consistency checks. Quantitative data (such as densities, counts, abundances, or concentrations) provided by resource experts for inclusion in the data set may vary widely in attribute accuracy, depending upon the methodology used to collect and compile such data. For a more detailed evaluation of source data attribute accuracy, contact the sources listed in the Lineage section.
Logical_Consistency_Report:
A multi-stage error checking process, described in the above Attribute_Accuracy_Report, is used to verify both attribute accuracy and logical consistency throughout data production. This process includes multiple automated logical consistency checks that test the files for missing or duplicate data, rules for proper coding, GIS topological consistencies, and SQL SERVER(R) to ArcGIS(R) consistencies. A final review is made by the ESI manager, where the data are written to CD-ROM and the metadata are written. In the process of checking for topological and database consistencies, new ID's and RARNUM's or HUNUM's are also generated, while retaining the original RARNUM or HUNUM stored as MAPRAR and MAPHUN, respectively. The new ID's are a combination of atlas number, element number, and record number. In addition, the value used to represent the element is modified to reflect the type of feature being mapped. In the case of an element that is normally represented by a point or polygon, a value of 20 is added to the standard element value for mapping of linear features. In the case where an element usually mapped as a polygon is represented by a point, a value of 30 is added to the regular element value. The RARNUM's are also modified to include the atlas number, so multiple atlases can be combined and RARNUM's remain unique. RARNUM's are redefined on an element basis, so "resources at risk" groupings will contain only a single element. HUNUM's are also modified to include the atlas number.
Completeness_Report:
These data represent a synthesis of expert knowledge, available hardcopy documents, survey data, model data, and digital data on bird distribution, abundance, and PPO. These data do not necessarily represent all bird occurrences in BSEE Gulf of Mexico. The following species are included in this data set: (Species_ID, Common Name, Scientific Name [n/a if not applicable]): 1, Common loon, Gavia immer; 35, Parasitic jaeger, Stercorarius parasiticus; 38, Herring gull, Larus argentatus; 42, Bonaparte's gull, Larus philadelphia; 45, Common tern, Sterna hirundo; 98, Laughing gull, Leucophaeus atricilla; 118, Brown pelican, Pelecanus occidentalis; 119, Magnificent frigatebird, Fregata magnificens; 126, Brown noddy, Anous stolidus; 127, Sooty tern, Onychoprion fuscatus; 128, Masked booby, Sula dactylatra; 135, Sandwich tern, Thalasseus sandvicensis; 137, Royal tern, Thalasseus maximus; 167, Northern gannet, Morus bassanus; 193, Black tern, Chlidonias niger; 199, Pomarine jaeger, Stercorarius pomarinus; 261, Brown booby, Sula leucogaster; 283, Bridled tern, Onychoprion anaethetus; 287, Audubon's shearwater, Puffinus lherminieri; 339, Band-rumped storm-petrel, Oceanodroma castro; 445, Wilson's storm-petrel, Oceanites oceanicus; 529, Cory's shearwater, Calonectris diomedea; 603, Black-capped petrel, Pterodroma hasitata; 865, Great shearwater, Puffinus gravis; 1010, Pelagic birds, n/a; 1022, Seabirds, n/a.
Positional_Accuracy:
Horizontal_Positional_Accuracy:
Horizontal_Positional_Accuracy_Report:
Spatial components for biological data layers can come from expert interviews, hardcopy, or digital sources. Some of the spatial components of the biological data layers may have been developed using regional experts who estimate concentration areas. It is difficult to estimate the positional accuracy of such data, except to state that they are compiled on hardcopy base maps with a scale of 1:1,000,000. Some of the spatial components of the biological data sets are developed from pre-existing digital or hardcopy sources and reflect the positional accuracy of these original data. Note that biological resource data by their very nature are considered "fuzzy", and this should be understood when considering the positional accuracy of vector digital objects representing these resources. See the Lineage and Process_Description sections for more information on the original source data and how these data were integrated or manipulated to create the final data set.
Lineage:
Source_Information:
Source_Citation:
Citation_Information:
Originator:
BUREAU OF OCEAN ENERGY MANAGEMENT, NOAA SOUTHEAST FISHERIES SCIENCE CENTER, US FISH AND WILDLIFE SERVICE, US GEOLOGICAL SURVEY
Publication_Date: 2022
Title:
GULF OF MEXICO MARINE ASSESSMENT PROGRAM FOR PROTECTED SPECIES (GOMMAPPS) PELAGIC SEABIRD SURVEYS - CUMULATIVE HABITAT SUITABILITY INDEX MODEL
Geospatial_Data_Presentation_Form: RASTER DIGITAL DATA
Other_Citation_Details: UNPUBLISHED
Type_of_Source_Media: ONLINE
Source_Time_Period_of_Content:
Time_Period_Information:
Range_of_Dates/Times:
Beginning_Date: 2017
Ending_Date: 2019
Source_Currentness_Reference: DATE OF SURVEY
Source_Citation_Abbreviation: NONE
Source_Contribution: BIRDS INFORMATION
Source_Information:
Source_Citation:
Citation_Information:
Originator:
GULF OF MEXICO MARINE ASSESSMENT PROGRAM FOR PROTECTED SPECIES (GOMMAPPS)
Publication_Date: 2022
Title: SUMMER MARINE BIRD PREDICTIONS
Geospatial_Data_Presentation_Form: VECTOR DIGITAL DATA
Other_Citation_Details: UNPUBLISHED
Type_of_Source_Media: ONLINE
Source_Time_Period_of_Content:
Time_Period_Information:
Range_of_Dates/Times:
Beginning_Date: 2018
Ending_Date: 2020
Source_Currentness_Reference: DATE OF SURVEY
Source_Citation_Abbreviation: NONE
Source_Contribution: BIRDS INFORMATION
Source_Information:
Source_Citation:
Citation_Information:
Originator:
GULF OF MEXICO MARINE ASSESSMENT PROGRAM FOR PROTECTED SPECIES (GOMMAPPS)
Publication_Date: 2022
Title: WINTER MARINE BIRD PREDICTIONS
Geospatial_Data_Presentation_Form: VECTOR DIGITAL DATA
Other_Citation_Details: UNPUBLISHED
Type_of_Source_Media: ONLINE
Source_Time_Period_of_Content:
Time_Period_Information:
Range_of_Dates/Times:
Beginning_Date: 2018
Ending_Date: 2020
Source_Currentness_Reference: DATE OF SURVEY
Source_Citation_Abbreviation: NONE
Source_Contribution: BIRDS INFORMATION
Source_Information:
Source_Citation:
Citation_Information:
Originator:
GULF OF MEXICO MARINE ASSESSMENT PROGRAM FOR PROTECTED SPECIES (GOMMAPPS) - JEFF GLEASON
Publication_Date: 2022
Title:
BIRDS BY SEASON DETECTED ON VESSEL SURVEYS, DRAFT SUMMARY TABLE FROM DRAFT GOMMAPPS FINAL REPORT
Geospatial_Data_Presentation_Form: DOCUMENT
Other_Citation_Details: UNPUBLISHED
Type_of_Source_Media: EMAIL
Source_Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 2022
Source_Currentness_Reference: DATE OF ACCESS
Source_Citation_Abbreviation: NONE
Source_Contribution: BIRDS INFORMATION
Source_Information:
Source_Citation:
Citation_Information:
Originator:
PAT JODICE (US GEOLOGICAL SURVEY) AND PAM MICHAEL (CLEMSON UNIVERSITY)
Publication_Date: 2022
Title:
PREDICTED PROBABILITY OF OCCURRENCE OF BLACK-CAPPED PETREL IN THE NORTHERN GULF OF MEXICO
Geospatial_Data_Presentation_Form: RASTER DIGITAL DATA
Other_Citation_Details: UNPUBLISHED
Type_of_Source_Media: EMAIL
Source_Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 2022
Source_Currentness_Reference: DATE OF ACCESS
Source_Citation_Abbreviation: NONE
Source_Contribution: BIRDS INFORMATION
Process_Step:
Process_Description:
Two main sources of data were used to depict bird distribution and seasonality for this data layer: 1) personal interviews with resource experts from the U.S. Fish and Wildlife Service (USFWS), U.S. Geological Survey (USGS) and Clemson University and 2) published and unpublished data and reports. Nearshore birds – Nearshore marine birds were mapped using model data provided by the Gulf of Mexico Marine Assessment Program for Protected Species (GOMMAPPS). GOMMAPPS used aerial survey data collected from the shoreline to 50 nm offshore during winter and summer survey seasons, along with environmental data, to model winter and summer abundances of marine birds in this area. Model output data were divided into three quantiles to designate high, medium, and low ESI concentrations of marine birds throughout the study area. The survey platform was also included in the ESI concentration field to emphasize the difference in data collection and modeling protocols between the GOMMAPPS aerial (nearshore) surveys and vessel (nearshore and offshore) surveys. Thus, ESI concentrations used for nearshore marine birds are: ‘High-Aerial Survey’, ‘Medium-Aerial Survey’, and ‘Low-Aerial Survey’. Data were available for ‘marine birds’ as a group, so these aerial survey data were mapped in the ESI with the common name ‘Marine birds’; data on individual species were not available. For more detailed information about how to interpret the model data, please contact the resource experts listed in the atlas Introduction. Nearshore and offshore birds – Birds throughout the northern Gulf of Mexico were mapped using model data provided by GOMMAPPS. GOMMAPPS used vessel survey data collected from throughout the northern Gulf, along with environmental data, to model predicted probability of occurrence (PPO) of seabirds using a MaxEnt model. “MaxEnt is a machine learning technique that uses the maximum entropy approach to estimate the probability of occurrence of a species across a specified area based on occurrence (presence only) observations and a set of covariates (i.e., predictor variables that represent habitat conditions)” (J. Gleason, pers. comm.). Model output data (PPO) were divided into three quantiles to designate high, medium, and low ESI concentrations of seabirds throughout the study area. The survey platform and resulting model metric (PPO) were also included in the ESI concentration field to emphasize the difference in data collection and modeling protocols between the GOMMAPPS aerial (nearshore) surveys and vessel (nearshore and offshore) surveys. Thus, ESI concentrations used for seabird vessel survey modeled data are: ‘High-Vessel Srvy PPO’, ‘Med-Vessel Srvy PPO’, and ‘Low-Vessel Srvy PPO’. Modeled data were available for a cumulative group of 24 species of seabirds, so this dataset shows PPO of seabirds as a general group. Therefore, concentrations were assigned only to the ‘Seabirds’ records in the ESI data. The individual species that comprised the cumulative model were included in the ESI data without concentration values. Individual species model data were not available at the time of ESI atlas publication, but will be available by late 2023. For more detailed information about how to interpret the model data and for further information on individual seabird species, please contact the resource experts listed in the atlas Introduction. Conservation priority species – Black-capped petrel is proposed federally threatened at the time of publication of this atlas. As a conservation priority, this species has been modeled individually using a combination of GOMMAPPS survey data and Natural Resource Damage Assessment survey data collected to support post-spill injury assessment following the Deepwater Horizon oil spill. Similar to the vessel survey GOMMAPPS data described above, a MaxEnt model was developed to estimate PPO of black-capped petrel in the northern Gulf of Mexico. Model output data were divided into three quantiles to designate high, medium, and low concentrations as described above. For more detailed information about how to interpret the model data for black-capped petrel, please contact the resource experts listed in the atlas Introduction.
The above digital and/or hardcopy sources were compiled by the project biologist to create the BIRDS data layer. Depending on the type of source data, three general approaches are used for compiling the data layer: 1) information gathered during initial interviews and from hardcopy sources are compiled onto U.S. Geological Survey 1:1,000,000 topographic quadrangles and digitized; 2) hardcopy maps are digitized at their source scale; 3) digital data layers are evaluated and used "as is" or integrated with the hardcopy data sources. See the Lineage section for additional information on the type of source data for this data layer. The ESI, biology, and human-use data are compiled into the standard ESI digital data format. A second set of interviews with participating resource experts are conducted to review the compiled data. If necessary, edits to the BIRDS data layer are made based on the recommendations of the resource experts, and final hardcopy maps and digital data are created.
Process_Date: 202302
Process_Contact:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization:
Bureau of Safety and Environmental Enforcement (BSEE), U.S. Department of the Interior
Contact_Person:
Bureau of Safety and Environmental Enforcement (BSEE), U.S. Department of the Interior Gulf of Mexico OCS Region Program Manager
Contact_Address:
Address_Type: Physical address
Address: 1201 Elmwood Park Blvd
City: New Orleans
State_or_Province: Louisiana
Postal_Code: 70123-2394
Contact_Voice_Telephone: (504) 736-0557
Contact_Electronic_Mail_Address: eugene.oberry@bsee.gov