Sophie Pierszalowski

Master’s student

sophie.pierszalowski@oregonstate.edu

In this class, I will be looking at spatial trends in sighting data of humpback whales in southeastern Alaska from 2004-2005 summer field seasons. This sighting data was collected under the auspices of SPLASH (Structure of Populations, Levels of Abundance, and Status of Humpbacks), a massive collaboration of agencies and independent researchers from the U.S., Mexico, Canada, Russia and Japan. While this explorations isn’t directly related to my current research questions, I hope that being exposed to techniques in spatial statistics will allow me to integrate some of these tools into my research to better visualize the habitat use of humpback whales in southeastern Alaska.

I am especially interested in correlating habitat use with different bathymetric features such as depth, SST, and distance to shore. The main problem that I face when statistically analyzing these sighting records is that field efforts were not random and sightings reflect locations of predictable habitat use rather than sightings along survey transects. Thus, what appear to be hot spots or patterns of habitat use within southeastern Alaska, might actually be areas of increased field effort. This will undoubtedly complicate my analyses and I continue to turn to the Arc Blog for answers. Julia suggesting focusing on different spatial scales within southeastern Alaska to see if we could somehow show that the field effort within Glacier Bay, for example, covered the entire area.

Here are images of the three spatial scales:

1) southeastern Alaska

2) Glacier Bay

3) Point Adolphus

Students

Jennifer Bauer

OSU Courtesy Faculty

contact me: bauerj@geo.oregonstate.edu

My Spatial Problem

My current research is focused on assessing risks associated with energy production throughout the U.S. For this class, I am focusing on my work associated with offshore hydrocarbon production in the deep and ultra-deep waters of the Gulf of Mexico to interpret subsurface geologic characteristics throughout the Gulf to assist with modeling the characteristics and behavior of an oil spill or blowout. To interpret subsurface geologic characteristics we are leveraging data available from the Bureau of Ocean Energy Management (BOEM) and the Bureau of Safety and Environmental Enforcement (BSEE) that contain subsurface geologic data collected from the thousands of wells and boreholes drilled throughout the Gulf of Mexico (available online at data.boem.gov or data.bsee.gov).

The main problem or challenge we face with these datasets is that they are three dimensional. Subsurface geologic characteristics, such as temperature, pressure, and porosity vary both horizontally (x and y) and vertically (z). Therefore, spatial patterns and trends in our dataset need to be assessed both horizontally and vertically to effectively identify correlations between subsurface characteristics and allow us to create more accurate inputs for modeling the characteristics and behavior of an oil spill or blowout.