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1. Available underwater visual census methods such as line transects or
point count observations are widely used to obtain community data of
underwater species assemblages, despite their known pit-falls. As interest
in the community structure of aquatic life is growing, there is need for
more standardized and replicable methods for acquiring underwater census
data. 2. Here, we propose a novel approach, Point-Combination Transect
(PCT), which makes use of automated image recording by small digital
cameras to eliminate observer and identification biases associated with
available underwater visual census methods. We conducted a pilot study at
Lake Tanganyika, demonstrating the applicability of PCT on a taxonomically
and phenotypically highly diverse assemblage of fishes, the Tanganyikan
cichlid species-flock. 3. We conducted 17 PCTs consisting of five GoPro
cameras each and identified 22'867 individual cichlids belonging to
61 species on the recorded images. This data was then used to evaluate our
method and to compare it to traditional line transect studies conducted in
close proximity to our study site at Lake Tanganyika. 4. We show that the
analysis of the second hour of PCT image recordings (equivalent to 360
images per camera) leads to reliable estimates of the benthic cichlid
community composition in Lake Tanganyika according to species accumulation
curves, while minimizing the effect of disturbance of the fish through
SCUBA divers. We further show that PCT is robust against observer biases
and outperforms traditional line transect methods.
202 views reported since publication in 2019.