Author Identifier

Ebenezer Afrifa-Yamoah

https://orcid.org/0000-0003-1741-9249

Ute Mueller

https://orcid.org/0000-0002-8670-2120

Document Type

Journal Article

Publication Title

Fisheries Research

Publisher

Elsevier

School

School of Science

RAS ID

32434

Funders

Edith Cowan University - Open Access Support Scheme 2020

Comments

Afrifa-Yamoah, E. Taylor, S., & Mueller, U. (2020). Trade-off assessments between reading cost and accuracy measures for digital camera monitoring of recreational boating effort. Fisheries Research, 233, Article 105757.

https://doi.org/10.1016/j.fishres.2020.105757

Abstract

Digital camera monitoring is increasingly being used to monitor recreational fisheries. The manual interpretation of video imagery can be costly and time consuming. In an a posteriori analysis, we investigated trade-offs between the reading cost and accuracy measures of estimates of boat retrievals obtained at various sampling proportions for low, moderate and high traffic boat ramps in Western Australia. Simple random sampling, systematic sampling and stratified sampling designs with proportional and weighted allocation were evaluated to assess trade-offs in terms of bias, accuracy, precision, coverage rate and cost in estimating the annual total number of powerboat retrievals in 10,000 jackknife resampling draws. The relative standard error (RSE ± standard deviations) obtained by the sampling designs for sampling proportions from 0.4 onwards were below a 20 % threshold for three of the sampling designs across the three boat ramps. Coverage rates of over 90 % were observed for the confidence intervals for the estimated annual number of powerboat retrievals, with low relative standard errors (RSE < 20 %). Interpreting 40 % of camera footage within a year provided the minimum level to obtain sufficient accuracy measures for all sampling designs considered. The stratified random sampling design with weighted allocation consistently resulted in the smallest variance for estimates of annual powerboat retrievals across the various sampled proportions. These findings have the potential to considerably reduce the cost of manual data interpretation, since operating cost increased linearly with increasing sampling proportion.

DOI

10.1016/j.fishres.2020.105757

Creative Commons License

Creative Commons Attribution 4.0 License
This work is licensed under a Creative Commons Attribution 4.0 License.

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