Optimising sampling of fish assemblages on intertidal reefs using remote underwater video

Katherine R Erickson; Ana B Bugnot; Will F Figueira

doi:10.7717/peerj.15426

Optimising sampling of fish assemblages on intertidal reefs using remote underwater video

PeerJ. 2023 May 22:11:e15426. doi: 10.7717/peerj.15426. eCollection 2023.

Authors

Katherine R Erickson^{1

2}, Ana B Bugnot^{2

3}, Will F Figueira^{2

4}

Affiliations

¹ Centre for Marine Science and Innovation, University of New South Wales, Sydney, NSW, Australia.
² School of Life and Environmental Sciences, University of Sydney, Sydney, NSW, Australia.
³ Oceans and Atmosphere, Commonwealth Scientific and Industrial Research Organisation, Brisbane, QLD, Australia.
⁴ Sydney Institute of Marine Science, Sydney, NSW, Australia.

Abstract

Background: Assessing fish assemblages in subtidal and intertidal habitats is challenging due to the structural complexity of many of these systems. Trapping and collecting are regarded as optimal ways to sample these assemblages, but this method is costly and destructive, so researchers also use video techniques. Underwater visual census and baited remote underwater video stations are commonly used to characterise fish communities in these systems. More passive techniques such as remote underwater video (RUV) may be more appropriate for behavioural studies, or for comparing proximal habitats where the broad attraction caused by bait plumes could be an issue. However, data processing for RUVs can be time consuming and create processing bottlenecks.

Methods: Here, we identified the optimal subsampling method to assess fish assemblages on intertidal oyster reefs using RUV footage and bootstrapping techniques. We quantified how video subsampling effort and method (systematic vs random) affect the accuracy and precision of three different fish assemblage metrics; species richness and two proxies for the total abundance of fish, MaxN_T and MeanCount_T, which have not been evaluated previously for complex intertidal habitats.

Results: Results suggest that MaxN_T and species richness should be recorded in real time, whereas optimal sampling for MeanCount_T is every 60 s. Systematic sampling proved to be more accurate and precise than random sampling. This study provides valuable methodology recommendations which are relevant for the use of RUV to assess fish assemblages in a variety of shallow intertidal habitats.

Keywords: Cryptic fish; Intertidal reef; Sampling effort; Unbaited underwater camera.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Animals
Censuses
Coral Reefs*
Ecosystem
Fishes*

Grants and funding

This project was funded by an Australian Research Council Linkage Project LP180100732 with partners Sydney Institute of Marine Science, Department of Primary Industries, and the Nature Conservancy. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.