PhD Research - Laura Urbisci

MA Applied Stastics, University of California, Santa Barbara; BS Environmental Science and Management, University of California, Davis

Laura is a PhD candidate at the University of California, Santa Barbara with a MA in Applied Statistics. Prior to graduate school, Laura interned at NOAA’s Southwest Fisheries Science Center in La Jolla, CA, where she worked on population assessments of swordfish, short fin mako sharks, blue sharks, and common thresher sharks. During her time at UCSB, Laura received the Dr. Vapnek Fellowship and Award and the NMFS-Sea Grant Fellowship in Population and Ecosystem Dynamics. She has been very active in the UCSB community – in the Bren PhD community she ran coffee hour her first year and planned multiple retreats and barbecues. She has also been a statistics tutor for the Probability and Statistics Department for over three years and was the Bren Quantitative Consultant. She has been a mentor for a Bren masters student group project, the Women in Stem Program, and the Graduate Scholars Program (GSP). Through her involvement in the GSP, Laura has been recognized by Dean Carol Genetti for contribution to UCSB's Diversity Initiative. After completing her PhD, Laura will participate in the Insight Data Science Fellowship Program in San Francisco, CA.

Dissertation Abstract:
My dissertation is an interdisciplinary approach that combines fisheries science, ecological theory, and applied statistics. My first chapter is a meta-analysis on transfer efficiency that describes and quantifies the variation in transfer efficiency. My second chapter assesses uncertainty in food web models by creating multiple Monte Carlo simulations to test various ecological assumptions about net primary production and transfer efficiency. My final chapter is a comparative analysis of two Bayesian models: a classic Bayesian surplus production model and a Bayesian surplus production model that incorporates ecological information. This chapter examines if the inclusion of ecological information informs and alters fisheries assessment models, with a focus on data-limited fisheries. Ultimately, my work bridges the gap between applied statistics and ecological theory and encourages the use of uncertainty analysis to make more robust predictions in food web models.

Year Admitted: 2013
Research Areas: Fisheries, statistics
Faculty Advisor: Steve Gaines



Urbisci, L. C., Stohs, S. M., and Piner, K. P. 2015. From sunrise to sunset in the California drift gillnet fishery: An examination of the effects of time and area closures on the catch and catch rates of four key pelagic species: thresher shark (Alopias vulpinus), swordfish (Xiphias gladius), blue shark (Prionace glauca), and shortfin mako (Isurus oxyrinchus). Marine Fisheries Review. In progress.

Urbisci, L. C., Sippel, T., Teo, L. H., Piner, K. R., and Kohin, S. 2013 Size composition and spatial distribution of shortfin mako sharks by size and sex in U.S. West Coast fisheries. Submitted to ISC Shark Working Group Workshop July 6-11, 2013.

Urbisci, L. C., Runcie, R., Sippel, T., Piner, K., Dewar, H., and Kohin, S. 2012 Examining size-sex segregation among blue sharks (Prionace glauca) from the Eastern Pacific Ocean using drift gillnet fishery and satellite tagging data. Submitted to ISC Shark Working Group Workshop January 7-14, 2013.

Urbisci, L. C. 2011. Testing the unknown: the distribution, size and abundance of intertidal Haliotis rufescens (red abalone) and Haliotis cracherodii (black abalone) within Marine Protected Areas. (Unpublished student report. On file at the Cadet Hand Library, U.C. Davis Bodega Marine Laboratory).


NMFS – Sea Grant Fellowship in population dynamics (2014-2017)

ERI Summer Fellowship, 2014

Dr. Daniel Vapnek Fellowship and Award 2013 – 2014