EFI 2019 Conference

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Ecological Forecasting Initiative 2019

May 13-15, 2019

AAAS Headquarters
1200 New York Ave, NW
Washington,DC 20005

@eco4cast  #efi2019

The Ecological Forecasting Initiative (EFI) is a broad, interdisciplinary effort aimed at promoting the use of forecasts to understand, manage, and conserve ecosystems and the services they provide. The EFI 2019 meeting is aimed at bringing together scientists, agencies, industry, and stakeholders to build a community of practice and advance research, applications, and collaboration around near-term (subdaily to decadal) ecological forecasts.

EFI2019 is sponsored by the Alfred P. Sloan Foundation, the Pardee Center for the Study of the Longer-Range Future, and the National Science Foundation’s Office of International Science and Engineering.

Invited Speakers

  • Theory & Synthesis: Dave Schimel, NASA JPL
  • Education: Jackie Matthes, Wellesley College
  • Diversity and Inclusion: Diana Dalbotten, University of Minnesota
  • Statistical Tools: Chris Wikle, U. Missouri
  • Decision Science: Yael Grushka-Cockayne, Harvard
    and Jason Merrick, VCU
  • Partnerships: Lonnie Gonsalves, NOAA
  • Cyberinfrastructure: Kenton McHenry, National Center for Supercomputing Applications

Conference Agenda

*agenda subject to change

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Background

Near-term ecological forecasting is an emerging interdisciplinary research area focused on accelerating environmental research and making it more relevant to society. EFI believes iterative near-term ecological forecasting is a paradigm-shifting win-win for accelerating environmental research and making it more relevant to society. Forecasts embody the scientific method, requiring that (i) all predictions be specific and quantitative, and (ii) all predictions be tested against future events (out-of-sample validation). Forecasts encourage robust, reproducible science, and their a priori specification provides natural protection against overfitting. Frequent, iterative forecasts provide constant feedback, through a combination of refuting hypotheses, analyzing patterns in errors, and identifying model components contributing the most to forecast uncertainty, which accelerates learning and helps prioritize future research. Societally, environmental decision makers rarely have access to the information they most need — our best scientific understanding of what will happen in the future (i.e. forecasts) under the status quo and different decision alternatives. It is precisely for this reason that effective, self-improving forecasting methodologies, are so desperately needed.

The goal of this conference, and its follow-on activities, is to expand the community of practice around ecological forecasting to include a wider, more interdisciplinary community that includes social, computational, and physical scientists, public health professionals, engineers, members of affected industries (natural resources, computing, environmental sensing), federal agencies, and other key stakeholders. The central questions of this conference — What are each of us doing in this area and what more could be done? — are aimed at fostering dialog, innovation, and new research directions.

There is much ecologists can learn about forecasting from our colleagues in other disciplines, and building these bridges is an explicit goal of this conference. However, forecasting the biological environmental sciences involves challenges that go beyond simply adopting techniques developed for the physical environmental sciences (e.g. meteorology), and requires a deep interdisciplinary synthesis. Lacking a forecast tradition, ecologists need to integrate with the decision, governance, and economic sciences, to better understand how ecological forecasts can influence decision making, and those studying coupled human-natural systems to better understand how human actions affect ecological predictions and projections. Because biological systems often lack the same governing equations present in the physical sciences, ecological forecasts are dominated by different uncertainties than weather forecasts and thus presents a range of different statistical challenges that are at the cutting edge of modern computational statistics, data science, and machine learning. The breadth and heterogeneity of ecological data also drive informatics challenges and will require close collaborations with computational scientists to take advantage of advances in cyberinfrastructure and workflow automation. The growth of near-term ecological forecasting will further increase demand for advances in environmental sensing and sensor engineering and create new opportunities for adaptive sensing driven by forecast projections. Finally, advancing ecological forecasting not only requires changes in how we train ecologists, but it presents new educational opportunities for how we teach society about nature and involve citizens in the co-production of science.

Ecological forecasting also requires direct ties between ecological forecasters and stakeholders in a range of industries, state and federal agencies, and non-profit organizations. Many of these stakeholders are not passive consumers, but need to play an active role in the co-production of ecological forecasts, as many are producers of both observations and the decision alternatives and management scenarios that forecasts need to evaluate.

Abstracts

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Registration

Registration is now closed. If you would like to be put on the waitlist, email eco4cast[dot]initiative[at]gmail[dot]com.

There is no registration fee for the conference, and conference attendance includes three lunches and one dinner. Registration is capped at 100 attendees and offered on a first-come basis. We are looking into opening up additional space, but this may involve a modest fee for late registrations. We will contact any late registrants directly to confirm.

UPDATE: travel scholarships are no longer available. 

A small number of travel scholarships were available. In particular, applicants from historically underrepresented groups in STEM and minority-serving institutions are particularly encouraged to apply. Early career applicants were also eligible. 

EFI2019 attendees are invited (but not required) to submit abstracts for contributed lightning talks, scientific posters, and organizational posters. See below for abstract submission.

 

Call for Abstracts

We invite submission of abstracts for both lightning presentations and posters for the 2019 Ecological Forecasting Initiative meeting. Abstracts should be written to appeal to a broad, interdisciplinary community of scientists, agencies, industry, and stakeholders and should highlight the state of the art within a discipline or a novel interdisciplinary collaboration.

Abstracts submission is conditional on meeting registration. Please register prior to submitting your abstract.

Deadline is March 11th for abstracts wanting to be considered for oral presentations

Abstract Guidelines

    • Abstract should be no more than 400 words
    • Title should be no more than 150 characters
    • For every author, list their name, institution, and email. Project names are permitted for projects that would otherwise have >6 authors.
    • Presenting author should be listed first
    • Abstracts must be clear and written in English following standard grammar and punctuation. To broaden access authors are also permitted to submit a second version of the abstract written in a non-English language, but the abstract will only be judged based on the English abstract.
    • Lightning presentation abstracts should articulate goals, questions, or hypotheses as well as specific results. Talks should be no more than 5 min in length, and will need to be submitted 24-hours in advance to allow presentations to be compiled.
    • Posters submissions come in two formats. Scientific posters follow the same scientific format as talks. Organizational posters may provide general information about an agency, NGO, company, or project.
    • Limit of ONE first-authored/presenter scientific abstract (talk or poster) per person and/or ONE organizational poster. Individuals may be coauthors on multiple abstracts.
  • Abstracts should indicate a primary cross-cutting theme (Theory & Synthesis; Methods & Tools; Cyberinfrastructure; Education and Diversity; Decision Science; Partnerships; Public Engagement) and the relevant scientific discipline(s) covered (BIO, GEO, PH, CISE, MPS, ENG, EDU)