  Spatial memory plays a role in the way animals perceive their environments,
resulting in memory-informed movement patterns that are observable to
ecologists. Developing mathematical techniques to understand how animals use
memory in their environments allows for an increased understanding of animal
cognition. Here we describe a model that accounts for the memory of seasonal or
ephemeral qualities of an animal's environment. The model captures multiple
behaviors at once by allowing for resource selection in the present time as
well as long-distance navigations to previously visited locations within an
animal's home range. We performed a set of analyses on simulated data to test
our model, determining that it can provide informative results from as little
as one year of discrete-time location data. We also show that the accuracy of
model selection and parameter estimation increases with more location data.
This model has potential to identify cognitive mechanisms for memory in a
variety of ecological systems where periodic or seasonal revisitation patterns
within a home range may take place.
