Browsing by Author "Halpin, Patrick N"

Primary production regulates fisheries yield, but testing the degree to which it is so is complicated by our limited ability to measure and model net primary production in the ocean. Herein, I analyze primary production and fisheries yields in the tropical Pacific Ocean, and how uncertainties in physiology parameterizations and in field primary production measurements used in the models’ formulations limit model skill. I find that primary production model choice has an effect on designating sustainable fisheries levels, that model parameterizations are not tuned to the tropical Pacific systems, and that model skill assessment is highly dependent on our understanding of local biomass-productivity dynamics. Moving forward, improving the primary production estimates in the tropical Pacific can be done incorporating understanding of local ocean dynamics into model skill assessments.

Infusing models for animal movement with more behavioral realism has been a goal of movement ecologists for several years. As ecologists have begun to collect more and more data on animal distribution and abundance, a clear need has arisen for more sophisticated analysis. Such analysis could include more realistic movement behavior, more information on the organism-environment interaction, and more ways to separate observation error from process error. Because landscape ecologists and behavioral ecologists typically study these same themes at very different scales, it has been proposed that their union could be productive for all (Lima and Zollner, 1996).

By understanding how animals interact with their land- and seascapes, we can better understand how species partition up resources are large spatial scales. Accordingly I begin this dissertation with a large spatial scale analysis of distribution data for marine mammals from Nova Scotia through the Gulf of Mexico. I analyzed these data in three separate regions, and in the two data-rich regions, find compelling separation between the different communities. In the northernmost region, this separation is broadly along diet based partitions. This research provides a baseline for future study of marine mammal systems, and more importantly highlights several gaps in current data collections.

In the last 6 years several movement ecologists have begun to imbue sophisticated statistical analyses with increasing amounts of movement behavior. This has changed the way movement ecologists think about movement data and movement processes. In this dissertation I focus my research on continuing this trend. I reviewed the state of movement modeling and then proposed a new Bayesian movement model that builds on three questions of: behavior; organism-environment interaction; and process-based inference with noisy data.

Application of this model to two different datasets, migrating right whales in the NW Atlantic, and foraging monk seals in the Northwest Hawaiian Islands, provides for the first time estimates of how moving animals make choices about the suitability of patches within their perceptual range. By estimating parameters governing this suitability I provide right whale managers a clear depiction of the gaps in their protection in this vulnerable and understudied migratory corridor. For monk seals I provide a behaviorally based view into how animals in different colonies and age and sex groups move throughout their range. This information is crucial for managers who translocate individuals to new habitat as it provides them a quantitative glimpse of how members of certain groups perceive their landscape.

This model provides critical information about the behaviorally based movement choices animals make. Results can be used to understand the ecology of these patterns, and can be used to help inform conservation actions. Finally this modeling framework provides a way to unite fields of movement ecology and graph theory.