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National Center for Ecological Analysis and Synthesis

Project Description

Overfishing threatens the health of many of the world's fish stocks and the millions of people who rely on fish for their food and livelihood. One challenge is that we lack regular assessment data for more than 90% of Earth's fisheries, and reliably assessed fisheries tend to be better managed, thus less overfished. Scientists have developed innovative, inexpensive approaches to assess data-limited fisheries. But there are still significant barriers to widespread implementation of these approaches. The Data-Limited Fisheries Management project, a project of the Science for Nature and People (SNAP) initiative, will convene fish stock assessors, social scientists, ecologists and marine conservation practitioners. Collectively they will: 1) develop a fisheries assessment and management framework that can be applied across geographies, fishery archetypes, data availability, and spatial scales; 2) provide risk-based guidance on the socio-economic and conservation value of improved data collection of stock status; and 3) implement adaptive assessment and management guidelines in collaboration with The Nature Conservancy and Wildlife Conservation Society field programs, and potentially other NGOs This project is supported by the Science for Nature and People (SNAP) initiative, generously funded through founding grants by Shirley and Harry Hagey, Steve and Roberta Denning, Seth Neiman, the Gordon and Betty Moore Foundation, Ward W. and Priscilla B. Woods, and the David and Lucile Packard Foundation.
Working Group Participants

Principal Investigator(s)

Jono R. Wilson, Carmen Revenga, Jeremy Rude

Project Dates

Start: November 1, 2013

End: November 30, 2016



Elizabeth A. Babcock
University of Miami
T. Douglas Beard
US Geological Survey (USGS)
Rich Bell
The Nature Conservancy Africa
Matias Caillaux
The Nature Conservancy
Stuart Campbell
Wildlife Conservation Society Indonesia
Keith Chanon
NOAA, National Marine Fisheries Service (NMFS)
Jason M. Cope
NOAA, Northwest Fisheries Science Center
Emily S. Darling
University of North Carolina, Chapel Hill
Dawn Dougherty
University of California, Santa Barbara
Natalie M. Dowling
Commonwealth Scientific and Industrial Research Organisation (CSIRO)
Sean P Fitzgerald
University of California, Santa Barbara
Rod M. Fujita
Environmental Defense Fund
Steven D. Gaines
University of California, Santa Barbara
Todd Gedamke
MER Consultants
Mary Gleason
The Nature Conservancy
Nicolas Gutierrez
Marine Stewardship Council
Adrian Hordyk
Murdoch University
Brandon Kuczenski
University of California, Santa Barbara
Catherine S. Longo
University of California, Santa Barbara
Katie Mandes
The Nature Conservancy
Peter Mous
The Nature Conservancy
Daniel Ovando
University of California, Santa Barbara
Ana Maria Parma
Centro Nacional Patag├│nico (CENPAT)
Jeremy Prince
Murdoch University
Carmen Revenga
The Nature Conservancy
Merrill Rudd
University of Washington
Jeremy Rude
The Nature Conservancy
Cody Szuwalski
University of California, Santa Barbara
Sarah R. Valencia
University of California, Santa Barbara
Steven Victor
The Nature Conservancy
George Waweru Maina
The Nature Conservancy
Jono R. Wilson
The Nature Conservancy


  1. Journal Article / 2015

    The fishery performance indicators: a management tool for triple bottom line outcomes

  2. Journal Article / 2016

    Market and design solutions to the short-term economic impacts of marine reserves

  3. Report or White Paper / 2017

    TNC's global coastal fisheries strategy

  4. Dissertation or Thesis / 2017

    Accounting for variability and biases in data-limited fisheries stock assessment

  5. Data Set / In prep

    Monitoring and enforcement cost estimates

  6. Journal Article / 2015

    Secure sustainable seafood from developing countries

  7. Journal Article / 2013

    Integration of no-take marine reserves in the assessment of data-limited fisheries

  8. Presentations / 2016

    FishPath: Co-development of a fisheries management framework for data limited fisheries

  9. Software / In Prep