Author 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
Document Type
Journal Article
Publication Title
ICES Journal of Marine Science
Publisher
Oxford Academic
School
School of Science
RAS ID
32435
Funders
Edith Cowan University - Open Access Support Scheme 2020
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.
DOI
10.1093/icesjms/fsaa180
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
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