Lunch and Learn with Dr. Jennifer Miller

Date and Time
Phelps 3512
Jackal in Field
Jackal in Field
Jennifer A. Miller

Please RSVP HERE by Thursday, May 11th at 5 p.m. if you will be attending as we will be providing lunch.

The Center for Spatial Studies would like to invite you to a Lunch and Learn with Dr. Jennifer Miller on Tuesday, May 16th at 12:00 p.m. in Phelps 3512. We will be having a paper discussion with Dr. Miller about her paper titled: "Exploring the utility of movement parameters to make inferences about dynamic interactions in moving objects". Read below about Dr. Miller as well as an abstract on the paper we will be discussing.

Bio: Jennifer A Miller is a Professor of GIScience and the Chair of the Department of Geography and the Environment at the University of Texas at Austin. She joined the faculty at UT-Austin in 2007 after four years at West Virginia University. Dr. Miller's general research interests lie at the confluence of GIScience, spatial analysis, and biogeography. Her specific research focus is in the application area of species distribution modeling (SDM), and much of her previous work has addressed explicitly spatial issues associated with SDM, such as incorporating spatial autocorrelation and representing spatial accuracy and uncertainty. Current research investigates the effects that spatial structure, scale and sampling strategies have on SDM using simulated data; using SDM to investigate the effects of climate change; and using spatial simulation to analyze (animal) species movement and interaction.

Abstract: " Dynamic interactions” in animals are inter-individual interactions defined by proximity in both space and time and are important for understanding spatial behaviors such as mating, predation, and territoriality, as well as phenomena such as disease spread. Dynamic interactions are typically quantified by analyzing GPS locations as points or by examining the paths that are inferred as trajectories between subsequent points. Current path-based approaches measure movement similarity in terms of step length and azimuth, which is associated with a relatively narrow conceptualization of interaction (e.g., traveling together). This research explores how other, more complex movement parameters may differ with proximity to another individual; if proximity-related movement differences can be detected, this information can be used to generate new dynamic interaction metrics. This approach was first tested using simulated movement data with known interaction properties, then applied to 10 black-backed jackal (Canis mesomelus) dyads in Etosha National Park, Namibia. In general, an individual's movement was often different when it was close to another individual, suggesting that dynamic interaction can potentially be inferred by analyzing movement parameters. Movement parameters that describe directional persistence, speed, and change performed better, but there was considerable variation across movement parameters, proximity, and individuals.