Category: Conservation

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Co-occurrence of gray whales and vessel traffic in the North Pacific Ocean

With increasing vessel traffic, whales are becoming more susceptible to vessel strikes. In order to measure the extent and risk of these vessel strikes on gray whales of the North Pacific, Silber and colleagues used published range data from gray whales (in polygonal data format) to help inform management reform. ArcGIS was used to convert Keyhole Markup Language (KML) data into vector format and the Buffer tool was used to transform linear features to vectors. The Clip Tool was used to extract vessel traffic data that was derived from Automatic Identification Systems (AIS).

Silber identified the risk of not only large tankers to fatal vessel strikes, but also the potential risk of strikes from fishing vessels due to the sheer amount of commercial fishery activity in this region. Maps generated within GIS using both vessel and gray whale range data were used to identify areas of high vessel-strike risk. This type of data can be applied to a number of whale species to help manage vessel traffic in a way that can reduce the risk for whale fatality.

Silber G, Weller D, Reeves R, et al (2021) Co-occurrence of gray whales and vessel traffic in the North Pacific Ocean. Endang Species Res 44:177–201. https://doi.org/10.3354/esr01093

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Suitability Analysis of Acoustic Refugia for Endangered Killer Whales (Orcinus Orca) Using the GIS-Based Logic Scoring of Preference Method

Much of the world’s cetacean species rely on calls, clicks, and song to communicate and hunt. A species most susceptible to the growing amount of ocean noise are killer whales. Drackett and Dragićević aimed to increase the ability for GIS and spatial multicriterion evaluation (MCE) methods to represent the complex relationships between ocean noise in relation to the detection of acoustic refugia alongside other habitat criteria.

The GIS based Logistic Scoring of Preference (LSP)-MCE analysis is composed of input values, such as industrial sites, ports, aquaculture, kelp beds, and shipping traffic, that are weighed according to suitability which are represented within a raster layer within GIS. This suitability raster layer is superimposed on the area of interest (the Salish Sea), where this endangered population frequents. This study represents the use of spatial analysis and scoring to identify areas of most concern in regard to habitat suitability based on several criteria, including ocean noise. These maps can then be used to inform management decisions surrounding this population and area of concern.

Such use of spatial analysis can be expanded to include a host of new variables that can inform management decisions of other cetacean species.

Drackett, Logan, and Suzana Dragićević. “Suitability Analysis of Acoustic Refugia for Endangered Killer Whales (Orcinus Orca) Using the GIS-Based Logic Scoring of Preference Method.” Environmental Management, vol. 68, no. 2, Aug. 2021, pp. 262–78. DOI.org (Crossref), https://doi.org/10.1007/s00267-021-01481-y.

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Behavior and social structure of the sperm whales of Dominica, West Indies

This long-term study took place during the years 2005 to 2012 and focused on data collection on Caribbean sperm whales with the goal of general investigation of this understudied population. Through use of photo ID and behavioral observations, social units of sperm whales were identified, and locations of encounters were recorded. Using Spatial Analyst Tools in ArcGIS10, the researchers were able to determine the distance from shore, and from a 100 by100 m resolution bathymetric model (IFREMER), the researchers were able to estimate the depth of ocean that the whales were sighted.

Although this study focused primarily on individual identification through photo ID and determination of social units, this study exemplified the simple yet effective use of GIS to extract pertinent information such as distance from shore and ocean depth from simple lat/long coordinates. My own dataset does not include depth or distance from shore but may benefit from these metrics by providing additional clues to identify potential foraging behavior and prey preferences based on depth of occurrence and location.

Gero, S., Milligan, M., Rinaldi, C., Francis, P., Gordon, J., Carlson, C., Steffen, A., Tyack, P., Evans, P. & Whitehead, H. (2014) Behavior and social structure of the sperm whales of Dominica, West Indies. Marine Mammal Science, 30, 905–922.

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The Application of GIS and Spatiotemporal Analyses to Investigations of Unusual Marine Mammal Strandings and Mortality Events

This study investigated unusual mortality events (UME) of marine mammals using harbor porpoises as a model. An unusually high number of porpoise strandings within the Pacific Northwest, later classified as a UME, occurred in the years 2007-2008. Upon investigation of the stranded carcasses, location data was taken (lat/long) and a spatiotemporal cluster detection test (Knox test) was performed. The study found interesting patterns when investigating the age class, as there were a higher proportion of stranded calves relative to more mature individuals. This study exemplifies the use of spatiotemporal analyses on marine mammals to study stranding events and tracking of disease and other health related metrics.

Using location data to investigate stranding events can help researchers perform impact assessments of events such as oil spills. With events such as Deepwater Horizon, we may be interested in investigating the spatial patterns of stranded individuals and the populations from which they originate. The ability to analyze location data along with data such as sex and age class could help to understand the geographic patterns in strandings.

Norman, Stephanie A., et al. “The Application of GIS and Spatiotemporal Analyses to Investigations of Unusual Marine Mammal Strandings and Mortality Events.” Marine Mammal Science, vol. 28, no. 3, July 2012, pp. E251–66. DOI.org (Crossref), https://doi.org/10.1111/j.1748-7692.2011.00507.x.