Performance of Baited Underwater Video: Does It Underestimate Abundance at High Population Densities?

Abstract

Video survey techniques are now commonly used to estimate animal abundance under the assumption that estimates relate to true abundance, a key property needed to make video a valid survey tool. Using the spiny lobster Palinurus elephas as our model organism, we evaluate the effectiveness of baited underwater video (BUV) for estimating abundance in areas with widely different population density. We test three BUV abundance metrics and compare the results with an independently obtained abundance index from trammel-net surveys (Trammel). Video metrics used to estimate relative abundance include a value for total number of individuals per recording (TotN), the traditional maximum number of fish observed in a single video frame (MaxN), and the recently suggested alternative, the average of the mean MaxN from 5-minute periods throughout the duration of the recording (MeanN). This is the first video study of a wild population to include an estimate for TotN. Comparison of TotN with the other two BUV relative abundance metrics demonstrates that both of the latter lack resolution at high population densities. In spite of this, the three BUV metrics tested, as well as the independent estimate Trammel, distinguished high density areas from low density areas. Thus they could all be used to identify areas of differing population density, but MaxN and MeanN would not be appropriate metrics for studies aimed at documenting increases in abundance, such as those conducted to assess marine protected area effectiveness, as they are prone to sampling saturation. We also demonstrate that time of first arrival (T1) is highly correlated with all of the abundance indices; suggesting T1 may be a potentially useful index of abundance. However, these relationships require further investigation as our data suggests T1 may not adequately represent lobster abundance in areas of high density.

Estimating the density of resident coastal fish using underwater cameras: accounting for individual detectability

“…However, RUV recording has also some disadvantages as a limited field of vision, the need for good visibility and the cost related with image processing (Pita et al 2014, Struthers et al 2015. In most cases, bait is used for attracting fish around the camera (Whitmarsh et al 2017).…”

The use of video-techniques for monitoring and quantification of mobile fauna in marine cultivation systems

“…When comparing different studies on video techniques, authors seem to disagree on the best method to present the data (Stobart et al 2015). MaxN is a traditionally used and very conservative value which reports the maximal number of fish observed in a single video frame.…”

“…Additionally, the first time of arrival of an individual (t1) is a value that seems to be correlated to the total species abundance and may therefore also be worth reporting (Stobart et al 2015). For a comparison of the main advantages and shortcomings of each observation technique see Table 2.…”

Is seeing believing? Diver and video-based censuses reveal inconsistencies in roving predator estimates between regions

“…Similarly, BRUVS are often preferred for predator surveys, although BRUVS may underestimate predator populations in very high-density locations as a result of count saturation within space-limited fields of view , Cappo et al 2004, Watson et al 2005, Watson & Harvey 2007, Wraith 2007, Stobart et al 2015. Additional considerations include the potential inflation of density estimates due to fish being drawn from outside visible sampling areas, unknown areas of attraction as a byproduct of variable bait plume dispersion, alteration of fish behaviors, competitive exclusion, and/or preferential sampling of predator and scavenger populations with corresponding reductions to other functional groups (Harvey et al 2007, Colton & Swearer 2010, Dorman et al 2012.…”