Habitat is recognized as crucial to the survival and recovery of exploited species. Climate change, environmental variability, and increased anthropogenic modification of the oceans add a sense of urgency to the correct identification, monitoring and conservation of essential fish habitat. Identifying essential habitat in three dimensions is the first step in being able to react to changes in environment caused by any of these drivers. Extending tools for essential fish habitat (EFH) analysis to higher dimensions would greatly enhance the ability of scientists to evaluate and respond to climate change. The ability to create these types of analyses for pelagic species will improve our ability to support integrated ecosystem analyses (IEA).

Geographic information systems (GIS) have provided many of the tools used to delineate EFH. These tools work very well for the characterization of benthic EFH, but are less usable for identifying pelagic EFH. HabitatSpace extends the 2-D tools used for EFH to a suite of 3-D tools by integrating new and existing analysis routines. Tools include creating a convex hull for calculating habitat volumes, calculating volume on volume intersections, and calculating the intersection of path taken by larvae through in situ data to create predicted temperature histories. The tools will also be generalized to the path of anything through a temperature volume stored as a netCDF file – e.g. path through atmosphere. For summarizing the data we investigate the implementation of 3-D statistics. The aim is to create equivalents to the traditional landscape metrics for 3-D.