P-323 Application of Spatial-Temporal Analysis for the Efficient and Sustainable Development of a Commercial Fishery

Emma Posluns , Fisheries and Marine Institute, Memorial University of Newfoundland, St. John's, NF, Canada
Paul Winger , Fisheries and Marine Institute, Memorial University of Newfoundland, St. John's, NF, Canada
Randy Gillespie , Fisheries and Marine Institute, Memorial University of Newfoundland, St. John's, NF, Canada
The global collapse of innumerable fish stocks confirms that a robust management strategy is the key to sustainable and profitable fisheries.  In the 1960s, Geographic Information Science (GIS) emerged as a useful tool for decision makers in resource management.  As a result of increasing conservation needs in fisheries, considerable research has gone into the use of GIS in visualizing spatial patterns of fish stocks.  Yellowtail flounder (Limanda ferruginea) represent an important commercial fishery on the Grand Banks of Newfoundland, Canada, but industry lacks a comprehensive GIS showing catch rate location and distribution over space and time.  This study worked with the Atlantic Canadian company Ocean Choice International (OCI), a leader in the yellowtail flounder industry, to investigate correlation between ecosystem factors and spatial patterns of catch rate. 

In this project we tested the hypothesis that spatial and temporal distribution of commercial catch rate is impacted by environmental (i.e. bathymetry, sea state, surficial geology, and water temperature) and temporal variables (i.e. week, month, season).  To do this, we created a GIS in order to correlate logbook data from OCI vessels with environmental data from other sources such as Environment Canada and Natural Resources Canada.  Historical catch data of yellowtail flounder, taken from several commercial fishing vessels over the period 2007 to 2009, were examined using geostatistics and advanced spatial and temporal analysis tools.  The results of this study will improve understanding of yellowtail flounder commercial catch rate patterns.

The knowledge management system created in this project can help OCI to function in an efficient and sustainable manner by enabling the forecasting of future catch distribution.  By knowing where fish are likely to be caught at different times of the year, the company will decrease searching time and fuel use.  By spending less time at sea a higher net profit is gained which ensures the long-term sustainability of OCI and the continued employment of rural Newfoundlanders.  The results of this study have created a robust decision making tool for industry and provided a baseline of cultural and biological information concerning yellowtail flounder which may be used for future studies.