jalali-exploringspatiotemporal-2015.pdf (7.4 MB)
Exploring spatiotemporal trends in commercial fishing effort of an abalone fishing zone: a GIS-based hotspot model
journal contribution
posted on 2015-01-01, 00:00 authored by Mohammad Ali Jalali, Daniel IerodiaconouDaniel Ierodiaconou, H Gorfine, J Monk, Alexander RattrayAssessing patterns of fisheries activity at a scale related to resource exploitation has received particular attention in recent times. However, acquiring data about the distribution and spatiotemporal allocation of catch and fishing effort in small scale benthic fisheries remains challenging. Here, we used GIS-based spatio-statistical models to investigate the footprint of commercial diving events on blacklip abalone (Haliotis rubra) stocks along the south-west coast of Victoria, Australia from 2008 to 2011. Using abalone catch data matched with GPS location we found catch per unit of fishing effort (CPUE) was not uniformly spatially and temporally distributed across the study area. Spatial autocorrelation and hotspot analysis revealed significant spatiotemporal clusters of CPUE (with distance thresholds of 100's of meters) among years, indicating the presence of CPUE hotspots focused on specific reefs. Cumulative hotspot maps indicated that certain reef complexes were consistently targeted across years but with varying intensity, however often a relatively small proportion of the full reef extent was targeted. Integrating CPUE with remotely-sensed light detection and ranging (LiDAR) derived bathymetry data using generalized additive mixed model corroborated that fishing pressure primarily coincided with shallow, rugose and complex components of reef structures. This study demonstrates that a geospatial approach is efficient in detecting patterns and trends in commercial fishing effort and its association with seafloor characteristics.
History
Journal
PLoS OneVolume
10Issue
5Season
Article Number : e0122995Article number
e0122995Pagination
1 - 20Publisher
Public Library of Science (PLOS)Location
San Francisco, Calif.Publisher DOI
eISSN
1932-6203Language
engPublication classification
C Journal article; C1 Refereed article in a scholarly journalCopyright notice
2015, The AuthorsUsage metrics
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