Abstract

While remote camera surveys have the potential to improve the accuracy of recreational fishing estimates, missing data are common and require robust analytical techniques to impute. Time-lapse cameras are being used in Western Australia to monitor recreational boating activities, but outages have occurred. Generalized linear mixed effect models formulated in a fully conditional specification multiple imputation framework were used to reconstruct missing data, with climatic and some temporal classifications as covariates. Using a complete 12-month camera record of hourly counts of recreational powerboat retrievals, data were simulated based on ten observed camera outage patterns, with a missing proportion of between 0.06 and 0.61. Nine models were evaluated, including Poisson and negative binomial models, and their associated zero-inflated variants. The imputed values were cross-validated against actual observations using percent bias, mean absolute error, root mean square error, and skill score as performance measures. In 90% of the cases, 95% confidence intervals for the total imputed estimates from at least one of the models contained the total actual counts. With no systematic trends in performance among the models, zero-inflated Poisson and its bootstrapping variant models consistently ranked among the top 3 models and possessed the narrowest confidence intervals. The robustness and generality of the imputation framework were demonstrated using other camera datasets with distinct characteristics. The results provide reliable estimates of the number of boat retrievals for subsequent estimates of fishing effort and provide time series data on boat-based activity.

RAS ID

32435

Document Type

Journal Article

Date of Publication

2020

Funding Information

Edith Cowan University - Open Access Support Scheme 2020

School

School of Science

Creative Commons License

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

Publisher

Oxford Academic

Identifier

Ebenezer Afrifa-Yamoah
ORCID: https://orcid.org/0000-0003-1741-9249

Aiden Fisher
ORCID: https://orcid.org/0000-0002-5826-6800

Ute Mueller
ORCID: https://orcid.org/0000-0002-8670-2120

Comments

Afrifa-Yamoah, E., Taylor, S. M., Fisher, A., & Mueller, U. (2020). Imputation of missing data from time-lapse cameras used in recreational fishing surveys. ICES Journal of Marine Science, 77(7-8), 2984–2994. https://doi.org/10.1093/icesjms/fsaa180

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Link to publisher version (DOI)

10.1093/icesjms/fsaa180