使用大规模的社区科学数据和计算机视觉来评估温度调节作为Anolis carolinensis生理色彩变化的自适应驱动器
Serena Price1, Robert Guralnick2, Coleman M Sheehy3
1Division of Biodiversity Informatics, Florida Museum of Natural History, University of Florida, Gainesville, FL, 32611, USA. serenabprice2003@gmail.com.
Frontiers in zoology
|October 10, 2025
概括
绿色 (Anolis carolinensis) 在冬季改变颜色以进行温度调节,并在夏季进行社会信号. 这项研究使用了公民科学数据和计算机视觉来分析这些颜色变化,揭示了表型可塑性的多个驱动因素.
科学领域:
- 动物行为 动物行为
- 生理生态生态学生理生态学
- 计算机视觉在生物学中的应用.
背景情况:
- 在Anolis carolinensis的选择性颜色变化服务于潜在的适应性功能.
- 假设包括伪装,社会信号和温度调节.
- 了解这些颜色变化是理解表型可塑性的关键.
研究的目的:
- 为了研究绿色 (Anolis carolinensis) 变色的驱动因素.
- 为了测试伪装,社会信号和温度调节假设.
- 展示计算机视觉在分析公民科学数据以获得生态洞察的有用性.
主要方法:
- 利用计算机视觉管道从公民科学图像中分类色 (绿色与棕色).
- 集成的色彩数据与气候,季节和背景信息.
- 分析了颜色形态,温度和一年中的时间之间的相关性.
主要成果:
- 在冬季的低温下,棕色的鱼更常见.
- 在夏季繁殖季节,颜色和温度之间的相关性是不存在的.
- 没有发现背景颜色匹配的有力证据.
结论:
- 支持了温度调节 (冬季) 和社会信号 (夏季) 假设.
- 表示多个,时间依赖的驱动因素影响Anolis carolinensis颜色变化.
- 强调了机器学习和数字图像在生态研究中的力量.
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