Biological Oceanography
Joshua Kilborn
Research Assistant Professor, College of Marine Science
Ph.D. Marine Science – Concentration in Marine Resource Assessment, University of
South Florida, College of Marine Science (2017)
Office Phone: 727-553-3358
Email: jpk@usf.edu
CV: View PDF
MATLAB Resources
Research Priorities
Fishery Ecosystems; Dynamical Systems Theory and Ecological Regime Shifts; Ecosystem-based Fisheries Management; Fish Ecology; Applied Multivariate Statistics; Methods Development in Numerical Ecology; Spatiotemporal Analyses
In ecology, the problem of “pattern and scale” (Levin, 1992) persists where, in systems with many interacting factors and processes, the mechanisms that control the structure, function, and health of the system’s resources exist at multiple temporal and spatial scales that may change over the lifetime of the resource. Dr. Kilborn’s research focuses on describing large marine ecosystems and their associated fisheries in terms of the biological and non-biological aspects relevant to management and for moderating competing stakeholder interests. He uses parametric and non-parametric, uni/multivariate statistical methods to develop decision-support products, such as the Gulf of Mexico fisheries ecosystem model implemented using the Ecosystem-Level, Management-Indicator Selection Tool (Kilborn et al., 2018), that distill the multiple, dynamic interactions and trade-offs within an ecosystem into a more manageable format for managers and stakeholders. Dr. Kilborn also uses, and develops (Kilborn et al., 2017), state-of-the-art methods in numerical ecology to determine (1) what spatiotemporal scales are most relevant to different marine ecosystem resources, (2) what internal or external factors most affect the organization of resources over time and space, and (3) what large or small scale influences may account for, or predict, shifts in those organizational states. Ultimately, the results of his work are meant to provide necessary context and perspective for those that are investigating which of the complex ecosystem dynamics should be monitored and managed, and for fostering practical and sustainable long-term use of the variety of important services that large marine ecosystems provide. Finally, Dr. Kilborn also enjoys working and mentoring students through teaching the College’s Biometry (Fall; CRN: 88449) and Applied Multivariate Statistics (Spring; CRN: 18230) courses annually.
Relevant Publications & Works Cited
Kilborn, J. P. 2018. The Darkside Toolbox for MATLAB. ±«Óătv, College of Marine
Science, St. Petersburg, FL.
Kilborn, J. P., Drexler, M., and Jones, D. L. 2018. Fluctuating fishing intensities and climate
dynamics reorganize the Gulf of Mexico’s fisheries resources. Ecosphere, 9: e02487.
Kilborn, J. P., Jones, D. L., Peebles, E. B., and Naar, D. F. 2017. Resemblance profiles as clustering
decision criteria: Estimating statistical power, error, and correspondence for a hypothesis
test for multivariate structure. Ecology and Evolution, 7: 2039-2057.
Levin, S. A. 1992. The Problem of Pattern and Scale in Ecology. Ecology, 73: 1943-1967.
Tzadik, O. E., Kilborn, J. P., and Appeldoorn, R. S. 2017. Differential habitat use of reef fishes on a shelf-edge
reef off La Parguera, Puerto Rico. Bulletin of Marine Science, 93: 893-914.