Cheng Wan-Hwa, Chan Ying-Tin, Hong Haisen, Johnson Benjamin, Cheng I-Jiunn
Masters of Advanced Study in Geographic Information Systems, Arizona State University, Tempe Campus, Arizona, 85281, USA.
Institute of Marine Biology, National Taiwan Ocean University, Keelung 202-24, Taiwan.
Zool Stud. 2019 Aug 1;58:e18. doi: 10.6620/ZS.2019.58-18. eCollection 2019.
Facial photo identification (ID) has proven to be a non-invasive method for identifying individual wild animals, and in recent years it has been effective on megafauna such as sea turtles. However, when processing hundreds of photos over a long period of time, variation in facial scale patterns makes identifying individuals complicated. This means that there is a high possibility that the individual is misidentified, which results in incorrectly determining population sizes. This study used the programming languages Python and SQL to determine green turtle foraging population size in the nearshore waters of a coral island, Liuchiu Island, from 2011 to 2017. The programs determined that the foraging population was 432 turtles, approximately 90% of which resided there one year or less and selected only one foraging site. Those that stayed for more than two years selected two foraging sites. Less than 3% stayed throughout the 7 years. The core residence area was from Beauty Cave to Vase Rock. This study found that the nearshore waters of Liuchiu Island are a temporary development/foraging site for immature green turtles. This is the first study to use Python analysis to determine a foraging sea turtle population in the field.
面部照片识别已被证明是一种识别野生个体动物的非侵入性方法,近年来,它在诸如海龟等大型动物身上很有效。然而,在长时间处理数百张照片时,面部鳞片图案的变化使得识别个体变得复杂。这意味着个体被误识别的可能性很高,从而导致错误地确定种群规模。本研究使用编程语言Python和SQL来确定2011年至2017年绿海龟在珊瑚岛琉球岛近岸水域的觅食种群规模。程序确定觅食种群有432只海龟,其中约90%在那里停留一年或更短时间,并且只选择一个觅食地点。那些停留超过两年的海龟选择了两个觅食地点。不到3%的海龟在7年中一直停留。核心居住区域是从美人洞到花瓶岩。本研究发现,琉球岛近岸水域是未成熟绿海龟的临时发育/觅食地点。这是第一项使用Python分析来确定野外觅食海龟种群的研究。