Sea turtle sightings in Taiwan | 台灣海龜目擊紀錄

Daphne Hoh1, Chia-Ling Fong1

1 TurtleSpot Taiwan, , Taiwan

Corresponding author(s): Daphne Hoh (daphnehohzhiwei@gmail.com)Chia-Ling Fong

Received {date}; Revised {date}; Accepted {date}; Published {date}

Citation: Combination of authors, year of data paper publication (in parentheses), Title, Journal Name, Volume, Issue number (in parentheses), and doi of the data paper.

Resource Citation

Hoh D, Fong C (2022): Sea turtle sightings in Taiwan. v1.9. TurtleSpot Taiwan. Dataset/Occurrence. https://ipt.taibif.tw/resource?r=turtlespot&amp;v=1.9

Abstract

A more detailed description of the dataset in this data paper: https://doi.org/10.3897/BDJ.10.e90196. The data paper content described the dataset version 1.9 and before. Several edits were made, and new records (n=125) were added.
We describe a dataset of sea turtle sightings around the coast of Taiwan and its islands. This data collection was initiated by TurtleSpot Taiwan, a citizen-science project that collects sea turtle sighting data. This dataset includes 3,515 sighting data dated from March 2010, except most of the data (n = 3,128; 89%) were collected between June 2017 to December 2021. Sightings were reported by citizen scientists to the Facebook Group of TurtleSpot Taiwan (https://www.facebook.com/groups/turtlespotintw) by providing occurrence information. We also requested photos and videos for species identification and to record any physical abnormality of the turtle, if observable. In addition to recording data often associated with an occurrence, TurtleSpot aims to identify each sea turtle up to the individual level using the Photo Identification (Photo ID) method. Hence, if photos of left facial scutes were available, the sighted individual can be identified and given a unique turtle ID. In total, 762 individuals were assigned a turtle ID, comprising 723 Greens (Chelonia mydas), 38 Hawksbills (Eretmochelys imbricata) and one Olive Ridley (Lepidochelys olivacea) turtle. It is hoped that the data may assist in future ecological studies and the development of conservation measures.
This dataset is currently the largest public dataset of sea turtle sighting records in Taiwan. Post-publication of this dataset to the GBIF platform demonstrated that the number of Green sea turtle Chelonia mydas records in Taiwan is one of the largest in the world (last accessed date: 15-10-2022).
The dataset contains data of two major categories: data associated with the occurrence and data related to the biological characteristics of the sighted turtle individual. The former category consists of information during the sighting event such as date, time, location, geographical coordinates, observation method and species. The latter category characterised the observed turtle individual using our controlled vocabulary during the sighting, including data such as living status, life stage, sex, physical abnormality and associated organism. The data allowed future research studies, such as biogeography, sea turtle foraging ecology that includes habitat use, sex ratio, abnormalities encountered and intra- and interspecies interaction. The data may also potentially guide any policy-making process through the assessment of species conservation status and diversity in the area of occurrences.

Keywords: Occurrence; Observation; Sighting data; Citizen science, Facebook group; Sea turtle; Coastal waters; Photo identification, Occurrence, Observation

Project details

Project title: TurtleSpot Taiwan
Personnel: Daphne Hoh, Chia-Ling Fong, Huai Su, Pengyu Chen, Chia-Chen Tsai

Data published through GBIF: https://ipt.taibif.tw/resource?r=turtlespot

Taxonomic coverage

General taxonomic coverage description: Four species of sea turtles were recorded in the dataset, including Green turtle (Chelonia mydas), Hawksbill (Eretmochelys imbricata), Olive Ridley (Lepidochelys olivacea) and Kemp's Ridley (Lepidochelys kempii). Most of the sea turtle sightings in the dataset were of Green and Hawksbill turtles (97.3% and 2.4%). Occurrences that failed to assign species (n = 11) were recorded as Cheloniidae.
Taxonomic ranks
Family: Cheloniidae
Species: Chelonia mydas, Eretmochelys imbricata, Lepidochelys olivacea, Lepidochelys kempii, Caretta caretta
Common names: Green sea turtle, Hawksbill turtle, Olive ridley turtle, Kemp's ridley, Sea turtle, Loggerhead turtle

Spatial coverage

General spatial coverage: Most of the sighting data were from Taiwan and its islands and only a few (n = 35) were from other countries which include Indonesia, Philippines, Malaysia, Palau, the Mariana Islands, Japan, Maldives and United States.
Coordinates: 90°0'0''S and 90°0'0''N Latitude; 180°0'0''W and 180°0'0''E Longitude 

Temporal coverage: March 23, 2010 - May 31, 2022

Methods

Method step description: 
- . 	Data collection: Citizens who encountered sea turtles reported their sightings to us via our Facebook Group. Reporters post a regular post to the Group following our reporting format to contribute sighting information including sighting location, date, time, depth, observation method, photographs of the whole body and left- and right faces of the turtle individual.
- . 	Quality control of sighting report received: Each sighting reported to the Group was first checked by the group administration prior to approval. The group administration checked if the post followed the reporting format mentioned above and the sighting provider will be requested to provide any of the missing information unless unavailable. Once the submitted post passed the quality check, the post will be approved by the group administration to be visible in the Facebook Group.
- . 	Data transcription: Sighting information contained in the post/report was transcribed into Google Sheets as raw data.
- . 	Determine additional information from the sighting report: We recorded additional information about the occurrence through the sighting reporter’s notes of onsite observation and our identification through the provided photos and videos. Additional information included the biological characteristics of the sighted individual turtle (sex, life stage, behaviour, associated taxa) and physical abnormality of the turtle (e.g. fishing line entanglement, tumour and others).
- . 	Sea turtle individual identification: If clear photos of the left face of the sighted turtle were provided in the report, we use the Photo Identification (Photo ID) method to identify the turtle individual. Currently, we use two methods to perform Photo ID: (1) compare the facial scute pattern manually and (2) HotSpotter (Crall et al. 2013, Dunbar et al. 2021), open-source software for pattern recognition in wildlife research. Each sea turtle individual was assigned a unique turtle ID. The turtle ID was assigned as follows: Country code, site code, species code and sequence number. For example, in TW01G0082, “TW”, “01”, “G” and “0082” stands for Taiwan, island or county label, green turtle and unique number for the individual, respectively.
- . 	Open data preparation: The language used in most of the recorded data is Traditional Chinese. Nevertheless, valuable information including sighting location, method, common name and life stages which allowed future data use was translated into English. We converted the occurrence data into Darwin Core Archive standard in Google Sheets, an online spreadsheet tool, using the Darwin Core Archive Assitant Add-on (Salim and Saraiva 2020). Refer to the Data resources section for a detailed description of each column. We then validated the occurrence dataset using the Data Validator developed by GBIF (Global Biodiversity Information Facility 2017). Lastly, we uploaded, stored and published the dataset using The Integrated Publishing Toolkit (IPT) of GBIF installed under the Taiwan Biodiversity Information Facility. The data is then opened on the IPT and GBIF for the public to access.
Study extent description: We collect sighting reports of all sea turtle sightings from any region, which is included in the dataset. But our current research focus is on the sighting data around the coasts of Taiwan and its islands.
Sampling description: See the step description below for more detail.

Datasets

Dataset description
Object name: Darwin Core Archive Sea turtle sightings in Taiwan | 台灣海龜目擊紀錄
Character encoding: UTF-8
Format name: Darwin Core Archive format
Format version: 1.0
Distribution: https://ipt.taibif.tw/archive.do?r=turtlespot
Publication date of data: 2024-05-16
Language: English
Licences of use: Creative Commons Attribution (CC-BY) 4.0 License

Metadata language: English
Date of metadata creation: 2021-04-22
Hierarchy level: Dataset

References
Crall JP, Stewart CV, Berger-Wolf TY, Rubenstein DI, Sundaresan SR (2013) Hotspotter—patterned species instance recognition. 2013 IEEE workshop on applications of computer vision (WACV). IEEE. https://doi.org/10.1109/WACV.2013.6475023
Salim JA, Saraiva AM (2020) A Google Sheet Add-on for Biodiversity Data Standardization and Sharing. Biodiversity Information Science and Standards. 4:e59228. https://doi.org/10.3897/biss.4.59228
Dunbar S, Anger E, Parham J, Kingen C, Wright M, Hayes C, Safi S, Holmberg J, Salinas L, Baumbach D (2021)
HotSpotter: Using a computer-driven photo-id application to identify sea turtles. Journal of Experimental Marine Biology and Ecology 535 https://doi.org/10.1016/j.jembe.2020.151490