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  • Jeffrey Maynard
    Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY
  • Ruben van Hooidonk
    NOAA Atlantic Oceanographic and Meteorological Laboratory, Miami, USA
  • C. Drew Harvell
    Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY
  • C. Mark Eakin
    NOAA Coral Reef Watch, NESDIS Center for Satellite Applications and Research, 5830 University Research Ct., College Park, USA
  • Gang Liu
    NOAA Coral Reef Watch, NESDIS Center for Satellite Applications and Research, 5830 University Research Ct., College Park, USA
  • Bette L. Willis
    Australian Research Council (ARC) Centre of Excellence for Coral Reef Studies, James Cook University, Townsville, Queensland
  • Gareth Williams
  • Maya L. Groner
    Centre for Veterinary Epidemiological Research, Atlantic Veterinary College, University of Prince Edward Island, Charlottetown, Prince Edward Island, Canada
  • Andrew Dobson
    Ecology and Evolutionary Biology, Princeton University
  • Scott F. Heron
    NOAA Coral Reef Watch, NESDIS Center for Satellite Applications and Research, 5830 University Research Ct., College Park, USA
  • Robert Glenn
    Energy and Environmental Affairs, Division of Marine Fisheries, Commonwealth of Massachusetts
  • Kathleen Reardon
    Department of Marine Resources, Maine
  • Jeffrey D. Shields
    College of William and Mary, Virginia
To forecast marine disease outbreaks as oceans warm requires new environmental surveillance tools. We describe an iterative process for developing these tools that combines research, development and deployment for suitable systems. The first step is to identify candidate host–pathogen systems. The 24 candidate systems we identified include sponges, corals, oysters, crustaceans, sea stars, fishes and sea grasses (among others). To illustrate the other steps, we present a case study of epizootic shell disease (ESD) in the American lobster. Increasing prevalence of ESD is a contributing factor to lobster fishery collapse in southern New England (SNE), raising concerns that disease prevalence will increase in the northern Gulf of Maine under climate change. The lowest maximum bottom temperature associated with ESD prevalence in SNE is 12°C. Our seasonal outlook for 2015 and long-term projections show bottom temperatures greater than or equal to 12°C may occur in this and coming years in the coastal bays of Maine. The tools presented will allow managers to target efforts to monitor the effects of ESD on fishery sustainability and will be iteratively refined. The approach and case example highlight that temperature-based surveillance tools can inform research, monitoring and management of emerging and continuing marine disease threats.
Original languageEnglish
JournalPhilosophical Transactions of The Royal Society B: Biological Sciences
Volume371
Issue number1689
Early online date15 Feb 2016
DOIs
Publication statusPublished - 5 Mar 2016

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