An oceanic manta ray outfitted with a satellite tag at the Revillagigedo Islands, Mexico

I am a quantitative conservation ecologist. I use a combination of battle-tested and novel approaches to fill ecological knowledge gaps that are preventing the effective conservation or management of marine systems and species. I use quantitative modeling and analytical tools to combine multiple data sources in order to better understand important ecological parameters. I tend to prefer Bayesian methods because of their ability to include expert knowledge into models (especially useful in data-poor scenarios) and their utility in projecting future population conditions under various possible management scenarios. That said, I’ll use whatever is the best tool for the job at hand. 

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Broadly speaking, I am interested in understanding how large, mobile marine species move through and interact with their environments, and how that information can be used to improve management. Determining the conditions that drive movement patterns—such as foraging, mating, competition, etc.—can help us predict future movements and how species will respond to environmental change. Identifying the movements themselves allows us to better understand critical habitat use, gene flow, how populations might be impacted by fisheries and other human activities, and the susceptibility of certain populations to local extinction events. Understanding how and why animals move in marine systems is often a prerequisite for effective conservation action.​​​​​​​

Good thing I have a nice view to distract me from all of that R code...

I’m especially interested in using and developing integrative population models to reduce uncertainty when studying data-poor systems/species/fisheries, which are common in the developing countries where I typically work. Examples of this might include combining capture-recapture and fisheries catch data; tagging data and density estimates; or two different databases with the same type of data (e.g. two independent photo ID databases from the same region). In the same vein, I use many different field and laboratory methods to address any one research question, providing improved spatial and temporal resolution that is more useful in a management context than any single method. In a recent example, I used a combination of satellite tagging, stable isotope analysis, and next-generation genetic sequencing methods to study the short- and long-term connectivity of oceanic manta ray populations. This allowed us to identify relevant ecological units, and make suggestions about what spatial scale would be most effective for management efforts. 
This type of work is almost always international in scale, and requires a dedicated network of passionate researchers. I am constantly indebted to and in awe of the many amazing collaborators that I work with around the world, who both collect critical data in challenging conditions, and ensure that the results of our work help inform local management efforts. I am always excited to collaborate on new projects, work with new threatened species or systems, and meet the many dedicated conservation scientists working to improve the future prospects of our wild planet.
Current projects that... 

I'm leading: (1) Understanding habitat use and foraging behavior of mantas using animal-mounted Crittercams; (2) Describing environmental drivers of habitat use by juvenile manta rays in the Gulf of Mexico; (3) Estimating the survival probability of manta and mobula rays incidentally captured and released in tuna fisheries.

I'm collaborating on: (1) Estimating the total catch, catch trends, and population impacts of gill net fisheries for mobulid rays in Sri Lanka; (2) Estimating abundance and population trends of oceanic manta rays in the Western Pacific; (3) Estimating the abundance and spatial dynamics of transient Orcas in the Pacific Northwest; (4) Describing fertilization rates and survival of eggs from a Nassau Grouper spawning aggregation in the Caribbean.

My students are leading: (1) Identifying seasonal visitation of mantas and relationships to El Niño and other environmental drivers in the Eastern Pacific; (2) Acoustic tagging of oceanic manta rays in the Eastern Pacific; (3) Describing variable risk of injury (anthropogenic and natural/predatory) to protected and unprotected oceanic manta populations in the Eastern Pacific.

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