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NIMBioS Investigative Workshop

Next Generation Genetic Monitoring

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Topic: Conserving genes for the future: Improving statistical approaches for genetic resource monitoring

Meeting dates: November 7-9, 2016

Location: NIMBioS at the University of Tennessee, Knoxville

Organizers:
Sean Hoban, Tree Conservation Biologist, Morton Arboretum, Lisle, IL
Michael W. Bruford, Biosciences, Cardiff Univ., Wales, UK
Louis Bernatchez, Biology, Univ. Laval, Canada
Erin Landguth, Computational Ecology Laboratory, Univ. of Montana

Objectives: Genetic variation underlies key ecological processes and economic activities, and is thus a collective resource for sustaining future species, ecosystems and human society. As biodiversity loss accelerates and environmental challenges mount, there is need for quantitative evaluation of the status and trends of genetic biodiversity. However, appropriate mathematical tools for this evaluation are lacking. Despite major recent advances in obtaining genetic data, current genetic metrics are piecemeal, may be incomparable across studies and data types, and are often collected and presented in an ad hoc manner.

There is an urgent need to conceive and develop standard, summary-level genetic indices that are robust, easily interpretable and tractable across diverse datasets. In this workshop we developed a framework for constructing these mathematical tools. Specifically, we: identified key attributes of successful indices in biodiversity science, surveyed and critiqued existing genetic metrics, and identified potential statistical approaches suitable for summarizing the highly dimensional nature of genetic data. We hope the workshop inspired several synthesis papers, new collaborations, and research funding proposals for developing, evaluating and distributing new genetic indices.

The inherent challenges of our aims require integration of mathematical and computational approaches with ecology, genetics, and biodiversity science. Our workshop was designed to help unlock the conservation potential of genomics research, and ensure that genetic and non-genetic factors are considered in quantitative fashion when evaluating and managing wild and cultivated species. More broadly, we laid a foundation for developing new theory and approaches for describing, quantifying, and interpreting the complex, multidimensional information contained in biodiversity datasets.

Descriptive flyer

Evaluation Report

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Next Generation Genetic Monitoring WordPress Site

Live-stream icon. Live Stream. Presentations were available for viewing via live streaming during the workshop. A live chat took place via Twitter with the hashtag #nextgenWS.

Playlist of online videos

photo. Summary Report. Genetic variation underlies key ecological processes and economic activities and is a collective resource for sustaining human society. As biodiversity loss accelerates and environmental challenges mount, there is need for quantitative evaluation of the status and trends of genetic biodiversity. However, appropriate mathematical tools for this evaluation are lacking, even as genetic datasets and genetic studies are larger and more complex than ever. Our group formed around the recognition that there is an urgent need to summarize and integrate genetic data in ways that are easily interpretable and tractable across diverse datasets. We also recognized that other fields of biodiversity science and ecological statistics may have solutions to this need or may face similar challenges. In this workshop we had 10 speakers, and critical discussion following the speakers, in which we identified key attributes of successful data analysis in biodiversity science, and surveyed and critiqued existing genetic metrics. As a large group we then brainstormed potential, feasible approaches for summarizing, representing and translating the highly dimensional nature of genetic data. We then formed five groups, each tackling a different approach at a different scale. Each group focused on different elements of the main topic, from theoretical to practical, from mathematical developments to review articles. Our workshop led to plans for synthesis papers, new collaborations, and research proposals for developing, evaluating and distributing new mathematical and statistical approaches. We accomplished our workshop aims: to help unlock the conservation potential of genomics research, ensure that genetic and non-genetic factors can be considered in quantitative fashion, and lay a foundation for new theory and approaches for describing, quantifying, and interpreting the complex, multidimensional information contained in biodiversity datasets.


NIMBioS Investigative Workshops focus on broad topics or a set of related topics, summarizing/synthesizing the state of the art and identifying future directions. Workshops have up to 35 participants. Organizers and key invited researchers make up half the participants; the remaining participants are filled through open application from the scientific community. Open applicants selected to attend are notified by NIMBioS within two weeks of the application deadline. Investigative Workshops have the potential for leading to one or more future Working Groups. Individuals with a strong interest in the topic, including post-docs and graduate students, are encouraged to apply. If needed, NIMBioS can provide support (travel, meals, lodging) for Workshop attendees, whether from a non-profit or for-profit organization.

A goal of NIMBioS is to enhance the cadre of researchers capable of interdisciplinary efforts across mathematics and biology. As part of this goal, NIMBioS is committed to promoting diversity in all its activities. Diversity is considered in all its aspects, social and scientific, including gender, ethnicity, scientific field, career stage, geography and type of home institution. Questions regarding diversity issues should be directed to Dr. Ernest Brothers, the NIMBioS Associate Director for Diversity Enhancement (diversity@nimbios.org). You can read more about our Diversity Plan on our NIMBioS Policies web page. The NIMBioS building is fully handicapped accessible.


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NSF logo. NIMBioS is sponsored by the National Science Foundation through NSF Award #DBI-1300426, with additional support from The University of Tennessee, Knoxville. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
 
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