Exploring the dispersal patterns of insects at the SAMSI Ecology Transition workshop

Erin Schliep

Erin Schliep attended the SAMSI Ecology Transition workshop and wrote this blog post.

The following was written by Erin M. Schliep, PhD, Postdoctoral Fellow, Department of Statistical Science at Duke University

During the first week of May, the Ecology Transition Workshop was held at SAMSI, once again bringing together statisticians, mathematicians, and ecologists from around the country. This workshop marked the conclusion of the the Statistical/Mathematical Ecology Program that began in August, 2014.

At the beginning of the program, interdisciplinary working groups were established, each focusing on a different research area within mathematical and statistical ecology. The working groups held both in-person and virtual group research meetings throughout the year. At the Transition Workshop, members of the different working groups presented on current research projects that stemmed from the year-long program as well as exciting directions for on-going collaborations. Some of the main themes from the workshop included networks, infectious disease, dispersal patterns of insects, joint species modeling, and data fusion of multiple data sources.

woman checking her cell phone

Checking messages during a break.

As a statistician focusing on ecological and environmental applications, I thoroughly enjoyed the meeting that combined technical statistical methodology and detailed information on the ecological processes of interest. The diverse scientific backgrounds of participants in the program led to interesting discussions, including the behavior of ant colonies, the distance at which scientists aboard ships can accurately identify birds, and the polygamous mating patterns of the North American barn swallow.

Speaking on behalf of the multivariate models working group focusing predominantly on statistical methodology, the workshop was a great opportunity for us to present our current research and to learn of new and exciting ecological datasets to apply our new methods. Our current aim is developing computationally feasible joint models for species distributions that allow for multiple types of data, such as continuous, count, or composition data. Even though the program is completed, our group continues to meet and has established research goals for the coming months.  I know that many of the other working groups within the Statistical/Mathematical Ecology Program also have on-going research and I am excited to learn of their future progress.

 

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