Marine Geospatial Ecology Tools: An integrated framework for ecological geoprocessing with ArcGIS, Python, R, MATLAB, and C++

With the arrival of GPS, satellite remote sensing, and personal computers, the last two decades have
witnessed rapid advances in the field of spatially-explicit marine ecological modeling. But with this
innovation has come complexity. To keep up, ecologists must master multiple specialized software
packages, such as ArcGIS for display and manipulation of geospatial data, R for statistical analysis, and
MATLAB for matrix processing. This requires a costly investment of time and energy learning computer
programming, a high hurdle for many ecologists. To provide easier access to advanced analytic methods,
we developed Marine Geospatial Ecology Tools (MGET), an extensible collection of powerful, easy-to-use,
open-source geoprocessing tools that ecologists can invoke from ArcGIS without resorting to computer
programming. Internally, MGET integrates Python, R, MATLAB, and Cþþ, bringing the power of these
specialized platforms to tool developers without requiring developers to orchestrate the interoperability
between them.

In this paper, we describe MGET’s software architecture and the tools in the collection. Next, we
present an example application: a habitat model for Atlantic spotted dolphin (Stenella frontalis) that
predicts dolphin presence using a statistical model fitted with oceanographic predictor variables. We
conclude by discussing the lessons we learned engineering a highly integrated tool framework.