Daphne Z. Hoh‡, Chia-Ling Fong§|¶, Huai Su§, Pengyu Chen§, Chia-Chen Tsai§, Kelly W. H. Tseng#, Melissa J. Y. Liu¤Corresponding author: Daphne Z. Hoh ( daphnehohzhiwei@gmail.com ) © Daphne Z. Hoh, Chia-Ling Fong, Huai Su, Pengyu Chen, Chia-Chen Tsai, Kelly W. H. Tseng, Melissa J. Y. Liu. This is an open access preprint distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Citation:
Hoh DZ, Fong C-L, Su H, Chen P, Tsai C-C, Tseng KWH, Liu MJY (2022) A dataset of sea turtle occurrences around the Taiwan coast. ARPHA Preprints. https://doi.org/10.3897/arphapreprints.e90210 |  |
We describe a dataset of sea turtle sightings around the coast of Taiwan and its islands. The data was collected by citizen scientists and reported to TurtleSpot Taiwan, a citizen science initiative that collects sea turtle sighting data mainly through the Facebook group. This dataset includes 3,515 sighting data dated from March 2010, except most of the data (n=3,128; 89%) falls were between June 2017 to December 2021. A standardized format of basic sighting information was suggested to anyone who wishes to report the occurrence. We also request photos and videos for turtle species identification and to record any physical abnormality. In addition to the basic data often associated with an occurrence, TurtleSpot aims to identify each sea turtle up to the individual level using the Photo ID method. Hence, if a good quality photo of left- and right-facial scutes were available, the sighted individual can be identified and given a unique Turtle ID. In total, 762 turtle individuals were assigned a turtle ID, comprising 723 green, 38 hawksbill, and 1 olive ridley turtles. The data of TurtleSpot Taiwan has allowed some ecological observations of sea turtles in the wild, such as witnessing the recovery of some injured turtles, behaviours, intra- and inter-species interactions, and physical abnormality. These data will offer essential information that helps to understand the foraging ecology of sea turtles and assists in the development of conservation measures.
This dataset contains 3,515 occurrence records of sea turtles and is currently the largest public dataset of sea turtle sighting records in Taiwan. Post-publication of this dataset to the Global Biodiversity Information Facility (GBIF) demonstrated that the number of green sea turtle Chelonia mydas occurrence records is few of the top in the world. The data served as the foundation for understanding sea turtle ecology in Taiwan's coastal waters.