To ensure comparable spatial and temporal coverage with similar historic datasets, we flew 32 east-west-oriented uniform transects (spaced at 15' latitude [27.8-km] intervals) when possible to the 2000-m isobath (includes shelf, slope, and rise waters). At the request of BOEM, we included six focal-area surveys nested within the overall broad transect survey area. Each focal-area survey consisted of ten 25-km, parallel transect lines targeting shelf waters and spaced at 6-km intervals. This pattern (broad survey lines and Focal Area survey lines) was surveyed during each oceanographic season: summer (June-July), fall (September-October), and winter (January-February) during 2011 and 2012. Aerial survey methods follow Mason et al. (2007) with slight modifications. Specifically, we recorded all sightings of marine animals, vessels, and floating objects from twin-engine, high wing aircraft (Partenavia P-68, Aspen Helicopters, Oxnard, CA, or Commander AC-500, GoldAero, Arlington, WA) along pre-determined 150-m (75 m per side) strip transects at 60-m above sea level. Surveys were flown at 160 km/h, and we used a Global Positioning System (GPS) unit linked to a laptop computer that allowed us to simultaneously collect coordinates (WGS-84 map datum), sea surface temperature (SST, degrees Celcius [°C]) determined via a belly-mounted pyrometer, and ocean color data via an onboard radiometer (see Remote sensing methods). We maintained the same two trained observers throughout the study. During individual surveys, observers frequently verified strip widths using hand-held clinometers. Observations generally were discontinued when glare exceeded >25% of the field-of-view or if sea state exceeded Beaufort 5 (29-38 km/h wind speed). Observations were recorded into hand-held digital audio recorders. The third (non-dedicated) observer assisted the pilot with navigation, monitored sensor data, and maintained the onboard computer. Observations of species or individuals identified to nearest taxon included number of individuals, time, pre-coded behaviors, flight direction, and interspecies or vessel associations. Digital recordings of observations were archived and used by observers after surveys to enter data into a customized Graphical User Interface in ACCESS (Microsoft). Observation data were proofed after transcription to ensure accuracy or to resolve inconsistencies. Species observations were linked with GPS-based tracklines generated at 1 to 3 second intervals. Based on variations in the lag-time between sightings and recordings, we estimate that observations have a nominal along-trackline spatial accuracy of 222 m, based on a five-second lag at 160 km/hr survey speed.Tracklines and associated observations were mapped and analyzed using ArcMap (ESRI, Redlands, CA). GPS data were recorded in WGS-84 map datum and projected to a USGS Albers Equal Area Conic map projection for presentation and subsequent density analyses. Concatenated GPS and observation data were then used to generate point and line coverages in ArcMap. We designed a custom analytic tool using ArcMap Model Builder that allows for the construction and export of user-specified and effort-adjusted spatial binning of species observations along continuous tracklines. We calculated density estimates along continuous 6.8-km (~ 5 min longitude) trackline segments (i.e., 6.8-km bins). Therefore, marine bird densities are based on a composite strip area ranging from 0.225 square km (one observer; 50-m strip width) to 0.450 square km (two observers; 150-m total strip width). We made no effort to adjust densities such that they would be proportional to variations in the area of buffered transect (i.e., weighted offset variable). An interval of 6.8 km (approximating 5 minutes of longitude in our study area) was chosen to calculate densities in order to be comparable to historical aerial seabird survey data that were summarized in arbitrary 5 min X 5 min grid cells.This file geodatabase feature dataset contains marine bird density data by 6.8-km bins for 35 species and 10 groupings of species. References:Bonnel, M.L., C.E. Bowlby, and G.A. Green. 1992. Chapter 2: Pinniped Distribution and Abundance off Oregon and Washington, 1989 – 1990. In: J.J. Brueggeman (Ed.) Oregon and Washington Marine Mammal and Seabirds Surveys. Final Report, OCS Study MMS 91-0093, Pacific OCS Region, Minerals Management Service, US Department of the Interior, Los Angeles, CA. Briggs, K.T., W.M. Breck Tyler, D.B. Lewis, and D.R. Carlson. 1987. Bird Communities at Sea Off California 1975 to 1983. Studies in Avian Biology No. 11. The Cooper Ornithological Society. 74 pp.Briggs, K.T., D.H. Varoujean, W.W. Williams, R.G. Ford, M.L. Bonnel, and J.L. Casey. 1992, Chapter 3: Seabirds of the Oregon and Washington OCS, 1989 – 1990. In: J.J. Brueggeman (Ed.) Oregon and Washington Marine Mammal and Seabirds Surveys. Final Report, OCS Study MMS 91-0093, Pacific OCS Region, Minerals Management Service, US Department of the Interior, Los Angeles, CA. Green, G.A., J.J. Brueggeman, R.A. Grotefendt, and C.E. Bowlby. 1992, Chapter 1: Cetacean Distribution and Abundance off Oregon and Washington, 1989 – 1990. In: J.J. Brueggeman (Ed.) Oregon and Washington Marine Mammal and Seabirds Surveys. Final Report, OCS Study MMS 91-0093, Pacific OCS Region, Minerals Management Service, US Department of the Interior, Los Angeles, CA.A full description of methods and results are available in the following report (please note that results in the report are presented at a different scale than data in this feature class):Adams, J., J. Felis, J. W. Mason, and J. Y. Takekawa. 2014. Pacific Continental Shelf Environmental Assessment (PaCSEA): aerial seabird and marine mammal surveys off northern California, Oregon, and Washington, 2011-2012. U.S. Dept. of the Interior, Bureau of Ocean Energy Management, Pacific OCS Region, Camarillo, CA. OCS Study BOEM 2014-003. 266 pages.
These data were edited in January 2017: attribute labels for species name have been converted to species code.
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