New publication

Challenges of transferring models of fish abundance between coral reefs

Jessica Meeuwig | Apr 17, 2018
Jessica Meeuwig
Apr 17, 2018

CITATION

Sequeira AMM, Mellin C, Lozano-Montes HM, Meeuwig JJ, Vanderklift MA, Haywood MDE, Babcock RC, Caley MJ. 2018. Challenges of transferring models of fish abundance between coral reefs. PeerJ, 6: e4566.

ABSTRACT

Reliable abundance estimates for species are fundamental in ecology, fisheries, and conservation. Consequently, predictive models able to provide reliable estimates for un- or poorly-surveyed locations would prove a valuable tool for management. Based on commonly used environmental and physical predictors, we developed predictive models of total fish abundance and of abundance by fish family for ten representative taxonomic families for the Great Barrier Reef (GBR) using multiple temporal scenarios. We then tested if models developed for the GBR (reference system) could predict fish abundances at Ningaloo Reef (NR; target system), i.e., if these GBR models could be successfully transferred to NR. Models of abundance by fish family resulted in improved performance (e.g., 44.1% 0.05). High spatio-temporal variability of patterns in fish abundance at the family and population levels in both reef systems likely affected the transferability of these models. Inclusion of additional predictors with potential direct effects on abundance, such as local fishing effort or topographic complexity, may improve transferability of fish abundance models. However, observations of these local-scale predictors are often not available, and might thereby hinder studies on model transferability and its usefulness for conservation planning and management.

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TRANSFERRING MODELS

Prediction of total fish abundance (Ntotal) and fish abundance by fish family to Ningaloo Reef (NR) by the transferred models from the Great Barrier Reef (GBR). Figure: Sequeira et al. 2018.

FUNDING & ACKNOWLEDGEMENTS

We are grateful to R Pitcher and M Case for providing access to the environmental variables used as predictors in this work, and to all participants in the fish data collection both at NR and the GBR. CSIRO Ningaloo work in 2013 was funded by the Australian Government’s Caring For Our Country Program.