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Exploring spatiotemporal trends in commercial fishing effort of an abalone fishing zone: a GIS-based hotspot model
Citation
Jalali, MA and Ierodiaconou, D and Gorfine, H and Monk, J and Rattray, A, Exploring spatiotemporal trends in commercial fishing effort of an abalone fishing zone: a GIS-based hotspot model, PLoS ONE, 10, (5) Article 0122995. ISSN 1932-6203 (2015) [Refereed Article]
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Copyright Statement
Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0) http://creativecommons.org/licenses/by/4.0/
DOI: doi:10.1371/journal.pone.0122995
Abstract
Assessing 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.
Item Details
Item Type: | Refereed Article |
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Keywords: | LiDAR, abalone, commercial fishing, suitable habitat |
Research Division: | Agricultural, Veterinary and Food Sciences |
Research Group: | Fisheries sciences |
Research Field: | Aquaculture and fisheries stock assessment |
Objective Division: | Environmental Management |
Objective Group: | Marine systems and management |
Objective Field: | Marine biodiversity |
UTAS Author: | Monk, J (Dr Jacquomo Monk) |
ID Code: | 100808 |
Year Published: | 2015 |
Web of Science® Times Cited: | 17 |
Deposited By: | IMAS Research and Education Centre |
Deposited On: | 2015-05-29 |
Last Modified: | 2022-12-06 |
Downloads: | 255 View Download Statistics |
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