Cross-Disciplinary Stats

Full Title

Cross-disciplinary statistical applications in the Anthropocene


The objective of this workshop is to enhance collaboration among ecologists, environmental scientists, applied statisticians, and economists to promote the sharing and development of analytical methods across disciplines in an effort to tackle wicked problems in an era of big data. The transfer of methods across disciplines will provide novel ways of addressing longstanding questions in both basic ecological and economic research, while interdisciplinary collaborations to develop analytical methods will lead to transformative approaches for solving complex socio-environmental problems. Within the workshop, participants will compare statistical techniques used to determine causality by the different disciplines, and identify their comparative advantages and drawbacks. The workshop will address: What novel socio-environmental research opportunities exist at the interface of ecology and economics that are facilitated by sharing statistical methods across disciplines, as well as rapid advances in high spatial and temporal resolution datasets on social and ecological systems.

Project Type
Team Synthesis Project
Michael Bonsall, University of Oxford
Tamma Carleton, University of California, Berkeley
Sathya Gopalakrishnan, Ohio State University
Giovanni Rapacciuolo, UC Merced
Kathleen Patricia Bell, University of Maine
Joshua Abbott, Arizona State University
Samuel Edward Wills, University of Sydney
Cory Merow, Yale
Leah Johnson, Virginia Tech
Robert Scholes, University of the Witwatersrand
Charles Towe, University of Connecticut
Juan Carlos Rocha, Stockholm University
Alexander Pigot, University College London
Heather Ann Kropp, Colgate University
David Allen Newburn, UMD
Shinichi Nakagawa, UNSW
Eric Sodja, Utah State University
Alexander Pfaff, Duke University
Juan Gutierrez, University of Georgia
Camilo Mora, University of Hawaii