Space oddity: The mission for spatial integration

Author:

Berger Aaron M.1,Goethel Daniel R.2,Lynch Patrick D.3,Quinn Terrance4,Mormede Sophie5,McKenzie Jeremy6,Dunn Alistair57

Affiliation:

1. Fisheries Resource and Monitoring Division, Northwest Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, 2032 S.E. OSU Drive, Newport, OR 97365, USA.

2. Sustainable Fisheries Division, Southeast Fisheries Science Center, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, 75 Virginia Beach Drive, Miami, FL 33133, USA.

3. Office of Science and Technology, National Marine Fisheries Service, National Oceanic and Atmospheric Administration, 1325 East-West Hwy, Silver Springs, MD 20910, USA.

4. College of Fisheries and Oceans Sciences, University of Alaska Fairbanks, 17101 Point Lena Road, Juneau, AK 99801, USA.

5. National Institute of Water and Atmospheric Research, 301 Evans Bay Parade, Wellington, New Zealand.

6. National Institute of Water and Atmospheric Research, 41 Market Place, Auckland, New Zealand.

7. New Zealand Ministry for Primary Industries, Pastoral House, 25 the Terrace, Wellington, New Zealand.

Abstract

Fishery management decisions are commonly guided by stock assessment models that aggregate outputs across the spatial domain of the species. With refined understanding of spatial population structures, scientists have begun to address how spatiotemporal mismatches among the scale of ecological processes, data collection programs, and stock assessment methods (or assumptions) influence the reliability and, ultimately, appropriateness of regional fishery management (e.g., assigning regional quotas). Development and evaluation of spatial modeling techniques to improve fisheries assessment and management have increased rapidly in recent years. We overview the historical context of spatial models in fisheries science, highlight recent advances in spatial modeling, and discuss how spatial models have been incorporated into the management process. Despite limited examples where spatial assessment models are used as the basis for management advice, continued investment in fine-scale data collection and associated spatial analyses will improve integration of spatial dynamics and ecosystem-level interactions in stock assessment. In the near future, spatiotemporal fisheries management advice will increasingly rely on fine-scale outputs from spatial analyses.

Publisher

Canadian Science Publishing

Subject

Aquatic Science,Ecology, Evolution, Behavior and Systematics

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