Background:

Animal behavior and ecology research has long relied on the presence of artificial and/or natural markings to distinguish between individuals within populations. Identification of individuals allows researchers to assess population dynamics, movement and behavior. For bottlenose dolphin (Tursiops truncatus), individuals can often be discerned using characteristic blemishes, nicks, notches, and/or scars on their dorsal fins. There are currently a number of active bottlenose dolphin photo-identification programs that rely on the use of dorsal fin markings. Depending on the intensity of survey efforts and size of study area, photo-identification catalogs can grow at a rapid pace. As catalogs grow, the process of matching individuals can become very time-consuming.

Photo-identification methodology has recently been advanced by the advent of digital photography. The use of digital images has allowed researchers to take advantage of commercially available image analysis software as well as develop computer-assisted image analysis techniques to facilitate the matching process. While database management systems (DBMS) have been increasingly employed to store and manage textual and numerical data associated with photo-identification research, the management and analysis of images is often performed manually outside of the DBMS. FinBase is a customized Microsoft Access database that not only stores and manages textual and numerical data from photo-identification surveys, but also performs many of the tasks associated with image management and analysis. A companion ArcGIS™ Extension called the FinBase Mapping Tool was also developed to allow users to easily query FinBase while in a GIS environment and spatially display output.