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Forecasting Anchovy and Sardine Transitions
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Successful ecological forecasting of fishery yields in the face of climate variability has eluded resource managers for decades. However, recent advances in observing systems, computational power and understanding of ecosystem function offer credible evidence that the variability of the ocean ecosystem and its impact on fishery yield can be forecast accurately enough and with enough lead time to be useful to society. The tools are now in place to provide ocean managers the capability to both protect and wisely use living marine resources. Advances in space-based real time sensors, high performance computing, very high-resolution physical models, and robust ecosystem theory make possible operational forecasts of both fish availability and ecosystem health. Accurate and timely forecasts can provide the information needed to maintain the longterm sustainability of fish stocks and protect the ecosystem of which the fish are an integral part, while maximizing social and economic benefits and preventing wasteful overinvestment of economic resources. We propose to enhance the current decision support system for the small pelagic fishery and upwelling ecosystem in the coastal ocean off Peru with remote sensing information and state-of-the-art coupled physical-biogeochemical three dimensional ocean models to provide operational forecasting and improve ecosystem management. This region is the best in the world for this implementation because it has the world’s largest single-species fishery, the Peruvian anchovy, which is supported by the world’s most variable ocean ecosystem. This variability is forced mainly by well understood climate variability. Because of the global importance of both the climate variability and the anchovy fishery, there are in place in this region well developed monitoring and decision support systems. No other ocean region has this combination of environmental observations, fish resources, fisheries monitoring and well validated climate forecast models for forcing high-resolution operational ecosystem models. Once implemented for the Peruvian anchovy fishery, these tools will be ported to decision support systems for fisheries along the US West Coast and made available to others working in similar environments of the world ocean. Proposal

Table 1 Participant Information. FAST Email List                                                      top


Roles and Tasks


F. Chavez, D. Kolber ,M. Messie, R.Michisaki,
MBARI Non-profit

Project management, biological & chemical oceanography

Yi Chao,
Remote Sensing Solutions Inc.

Basin-scale models, data assimilation

Hongchun Zhang,
Xiaochun Wang
NASA JPL Government

Basin-scale models, data assimilation

Fei Chai
Lei Shi
Yi Xu

U of Maine Educational

Ecosystem modeling
Alec MacCall
Kevin Hill

Dave. Foley
Sam McClatchie
NOAA Southwest Fisheries Science Center, Environmental Research Division, NMFS, SWFSC

R. Barber
T. Sakagami
Duke Educational

Ecosystem modeling
Renato Guevara,
Miquel Ñiquen
Instituto del Mar del Peru
Instituto del Mar del Perú

 topProposed meeting schedule:   top

FAST Proposal
 Ecosystem Modeling:
Yi Chao
Modeling the Central California Coastal Upwelling System: Physics, Ecosystems and Resource Management
Fei Chai NOPP Ecosystem
Physical Oceanography:Dave Foley NOAA/ERD
Biological and Chemical Oceanography:
Renato Guevara,
Miquel Ñiquen

Francisco Chavez,
Dorota Kolber,
Monique Messie,
Reiko Michisaki

Forecasting Anchovy and Sardine Transitions

A ten-year time series from Monterey Bay, California:Seasonal, 
interannual and long-term patterns

Analysis along CalCOFI Line 67: SECRET Cruises (1997-2000)

Time series summary from Monterey Bay


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Last updated: Oct. 17, 2013

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