Our understanding of fish ecology and ability to manage populations require accurate data on species occurrence, abundance, body-size distribution and behaviour. Remote video-based sampling methods are increasingly being adopted due to: (i) their non-destructive nature, (ii) ability to sample rare species (Harvey et al. 2018; Goetze et al. 2019), over broad depth ranges (Heyns-Veale et al. 2016; Wellington et al. 2018), (iii) provision of a permanent record that can be reviewed to reduce interobserver variability (Cappo et al. 2009), (iv) ability to collect concomitant data on habitat (Bennett et al. 2016; e.g. epibenthic cover and substrate, Collins et al. 2017), and (v) provision of images for science communication. Remote underwater video sampling methods are not subject to diver safety restrictions, nor do they suffer from the behavioural biases resulting from diver presence (Lindfield et al. 2014; Gray et al. 2016). Multiple remote systems can be deployed in the field consecutively to make efficient use of field time and enable spatially-extensive sampling (Langlois et al. 2012c).
The use of bait with remote underwater video (BRUV) systems increases the relative abundance and diversity of fishes observed, particularly species targeted by fisheries, without precluding the sampling of fishes not attracted to bait (Harvey et al. 2007; Coghlan et al. 2017; Speed et al. 2019). Biases associated with bait use have been discussed in various studies (Dorman, Harvey & Newman 2012; Hardinge et al. 2013; Goetze et al. 2015; Coghlan et al. 2017). Variation in bait plume dispersal and the sensitivity of different fish species to bait is unknown (Harvey et al. 2007), and likely species-specific, with cryptic and sedentary species potentially under-represented (Watson et al. 2005; Stat et al. 2019). Despite these limitations, BRUVs have been shown to provide relative measures of species richness and abundance for a range of species in a diverse array of conditions and habitats (Cappo, Harvey & Shortis 2006).