Mundy, C, Fine scale assessment of small vessel fisheries: application of GIS to spatial performance measures, 4th International Symposium in GIS/Spatial analysis in Fisheries and Aquatic Sciences, 25-28 August 2008, Rio de Janeiro, Brazil (2008) [Conference Extract]
Fisheries operating out of small vessels (<7m) typically target spatially structured stocks distributed over large geographic scales in remote areas. The nature of these fishing operations means precise recording of fishery dependent data is challenging, and fishery independent data collection is cost prohibitive. Assessments of these fisheries are typically done over large reporting units, with low-level precision data, thus the spatial structure and pattern of stock productivity and resilience to fishing, and the dynamics of the fleet, are lost.
As spatially structured stocks rebuild or improve, Fisher Ecological Knowledge (FEK) leads to rapid increases in catch rates, potentially over-stating the state of stocks. As stock levels decline, changes in fisher strategies lead to hyper-stable catch rates, masking evidence of change. This creates a lag between stock decline and detection, resulting in management actions that are too late and large, leading to conflict between fishers and managers. It is essential therefore to identify assessment methods that enable timely, accurate identification of change, and capture fine-scale spatial dynamics of the fishery.
For several years, a combination of GPS and depth/time dataloggers has been trialled in several Australian abalone fisheries. Access to this high-resolution, high-quality data has enabled the development of spatial performance measures to assess abalone stocks at fine scales, and to quantify fleet dynamics and fisher behaviour. Using ArcGIS 9.2 and Hawths Analysis Tools, and Repeating Shapes tool (Jenness), we have created a grid of 1 Ha cells around the coastline of Tasmania to a distance of 2km offshore. The effort and catch reported from each diver, and the number of active divers are then quantified within each grid cell. These data then enable computation of a range of measures of fishery performance, identify productive areas of the fishery (or changes in productivity) at a local scale, and the extent of overlap, and change in activity patterns of fishers. Overlap in space by divers varied substantially among regions. Unexpected differences in fishing strategies were also apparent among relatively experience divers working in the same areas.
|Item Type:||Conference Extract|
|Keywords:||GIS, abalone, GPS, assessment|
|Research Division:||Agricultural, Veterinary and Food Sciences|
|Research Group:||Fisheries sciences|
|Research Field:||Fisheries management|
|Objective Division:||Animal Production and Animal Primary Products|
|Objective Group:||Fisheries - wild caught|
|Objective Field:||Fisheries - wild caught not elsewhere classified|
|UTAS Author:||Mundy, C (Dr Craig Mundy)|
|Deposited By:||IMAS Research and Education Centre|
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