Classification and analysis of VMS data in vertical line fisheries: incorporating uncertainty into spatial distributions

Commercial fishing fleets play a critical role in the population dynamics of exploited stocks. Understanding the spatial distribution of fleets allows managers to anticipate how fishing pressure on exploited stocks changes in response to fishing regulations or to large-scale perturbations. By antici...

Full description

Saved in:
Bibliographic Details
Published in:Canadian journal of fisheries and aquatic sciences 2017-11, Vol.74 (11), p.1749-1764
Main Authors: Ducharme-Barth, Nicholas D, Ahrens, Robert N.M
Format: Article
Language:English
Subjects:
Acoustic equipment
Case studies
Catch per unit effort
Classification
Commercial fishing
Data analysis
Data processing
Distribution
Environmental aspects
Exploitation
Fish
Fisheries
Fishing
Fishing effort
Fishing fleets
Fishing pressure
Fishing vessels
Marine
Methods
Model accuracy
Modelling
Monitoring
Monitoring systems
Oil spills
Overfishing
Pressure
Radar
Reef fish
Reef fisheries
Remote sensors
Sonar
Spatial analysis
Spatial data
Spatial distribution
Stock assessment (Wildlife management)
Studies
Uncertainty
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Commercial fishing fleets play a critical role in the population dynamics of exploited stocks. Understanding the spatial distribution of fleets allows managers to anticipate how fishing pressure on exploited stocks changes in response to fishing regulations or to large-scale perturbations. By anticipating how fishing pressure changes, managers can develop proactive responses to better protect stocks that are vulnerable to overfishing. Modern fisheries monitoring techniques, including vessel monitoring systems (VMS), have advanced this endeavor. This paper presents a framework for using VMS data to develop spatial distributions of catch, fishing effort, and catch per unit of effort (CPUE) as well as associated estimates of uncertainty in a vertical line fishery. VMS data are classified as fishing using a random forest (RF) model. Uncertainty is calculated using a two-step approach to account for uncertainty arising from the RF modeling process and the classification accuracy of the model. This framework is applied to investigate changes in the Gulf of Mexico reef fish fishery during a period of 6 years, including the 2010 Deepwater Horizon oil spill.
ISSN:0706-652X
1205-7533
DOI:10.1139/cjfas-2016-0181