satellite tracking – Uses of GIS in analysis of cetacean habitat use, behavior, and migratory patterns

Here, Lord-Castillo tailors a multi-dimensional ocean data model to be compatible with satellite telemetry tagging program through Oregon State University’s Marine Mammal Institute. This paper exemplifies the development of data sharing within ArcGIS with the intention that its associated analytical tools can be utilized by different shareholders. Here, authors developed non-spatial object classes and feature classes specific to Arc Marine, which was a data model originally written using Microsoft Visio software. Within this customization study, they found two concepts to help improve future uses of Arc Marine for animal tracking: increased multidimensionality and creating an expandable platform.

This concept is integral to improving spatial data storage, management, and analysis with the goal of investigating animal movements and implementing conservation strategies given migratory patterns and behaviors. This is similar to the data I am working with which incorporates point locations, genotypes, sex, telemetry tracks, and a host of other environmental variables that can be extracted using GIS.

Lord-Castillo, Brett K., et al. “A Customization of the Arc Marine Data Model to Support Whale Tracking via Satellite Telemetry.” Transactions in GIS, vol. 13, no. s1, 2009, pp. 63–83. Wiley Online Library, https://doi.org/10.1111/j.1467-9671.2009.01159.x.

Lydersen and colleagues set out to investigate fin whales and their migratory paths using satellite tracking. Tags were deployed on 25 fin whales and stayed attached for a range of 6 to 95 days with an average duration of 33. It was found that 10 of the 25 individuals stayed within the study region, and 15 individuals travelled out of the immediate study area and tracks varied among individuals. Environmental variables such as ocean depth, sea surface temperature, and distance to the nearest coast were extracted from geodatabases given the location of the whales. In this case, Lydersen extracted bathymetry data from the ETOPO 1 Arc-Minute global relief data set from the National Geophysical Data Center, NOAA, sea surface temperature from the Extended Reconstructed Sea Surface Temperature (ERSST) v5, and finally distance to the nearest coast from the land file (1:10 m) from www.naturalearthdata.com.

Track maps of whales are an incredible tool in both visualizing and analyzing whale movements. These tracks provide important information on foraging behavior, activity level, and migratory destinations or lack thereof. The locations that satellite tags transmit allow for extraction of environmental variables from a variety of geodatabases, such as those listed above, that can provide further insight into whale behavior and foraging strategies.

Lydersen, C., Vacquié-Garcia, J., Heide-Jørgensen, M.P., Øien, N., Guinet, C. & Kovacs, K.M. (2020) Autumn movements of fin whales (Balaenoptera physalus) from Svalbard, Norway, revealed by satellite tracking. Scientific Reports, 10, 16966.