Underwater video and still-image dataset of fishes and other aquatic animals in Lake Biwa, Japan, observed via carp-mounted video loggers

This is the first large dataset of underwater videos from which species occurrence and behavioral records of aquatic organisms were identified in Lake Biwa, the largest lake in Japan. We compiled 109 videos and 122 still-images of fishes, diving birds and shrimps. The images were cropped from videos taken underwater with animal-borne video cameras which were mounted on the backs of common carp (Cyprinus carpio). The attribute of each image and its occurrence of organisms were formatted according to the Darwin Core Archive which was developed by the Biodiversity Information Standards (TDWG), and the dataset is available via the Global Biodiversity Information Facility (GBIF). Our dataset includes records of 10 species, 4 genera, 2 families and 1 infraorder which includes mostly fishes, several birds, and a crustacean. The fish records include a threatened endemic fish, the “gengorou-buna” crucian carp (Carassius cuvieri), and two alien fishes, largemouth bass (Micropterus salmoides), and bluegill sunfish (Lepomis macrochirus). We confirmed several types of intra- and inter-specific relationships between video-mounted carp and other organisms; for example, most video-mounted carp frequently approached or chased conspecifics upon encountering, which sometimes led to two carp feeding side by side. At least three avian species also appeared in the dataset: Eurasian coot (Fulica atra), little grebe (Tachybaptus ruficollis), great crested grebe (Podiceps cristatus); but there was no apparent interaction between carp and these birds. Our underwater videos reveal and showcase the rich biodiversity of the lake today, providing clear evidence for behavior of aquatic organisms under natural conditions. The complete data set for this abstract published in the Data Paper section of the journal is available in electronic format in Ecological Research Data Paper Archives at http://db.cger.nies.go.jp/JaLTER/ER_DataPapers/archives/2020/ERDP-2020-18