NSF Postdoctoral Fellowship in Biology FY 2013

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Linking early growth and survival with population dynamics, using hierarchical Bayesian models and a global database of fish life-history traits Studying the processes that regulate population demography, such as density dependent growth and survival, provides knowledge that is critical to understanding how species coexist and thrive in their environment. Marine populations, in particular, are very difficult to study because parts of their life cycle, such as larval or juvenile stages, remain a mystery. The objective of this research is to develop a life-history model that can be parameterized with public data from marine stock assessments of fished populations. These data on the population dynamics of hundreds of marine species are collected by international and federal agencies around the globe. With recently developed statistical methods, these data can be used to indirectly infer the relationship between life-history traits (including egg size and number) and population resilience for many species. This was previously almost impossible to do, because of the limitations of prior statistical methods and available data. This comparative approach will provide new perspectives on the key life-history traits that determine species? resilience to environmental change.In addition to these impacts, this research allows for the training of an early career scientist in novel statistical techniques. It also provides opportunities to teach and work with others tackling problems in conservation, including ecologists, resource managers, and policy makers. With the training received as an NSF postdoctoral fellow, the PI will be able to continue developing interdisciplinary approaches to the current challenges facing marine organisms.