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粟通萍,霍娟,陈光平,杨灿朝,梁伟.2017.野外使用红外热成像仪搜寻鸟巢实验.动物学杂志,52(1):108-114.
野外使用红外热成像仪搜寻鸟巢实验
A Test for Using Thermal Image by Infrared Thermography to Search Bird Nests
投稿时间:2016-06-23  修订日期:2016-12-28
DOI:10.13859/j.cjz.201701012
中文关键词:  红外热成像仪  鸟巢  野外调查  宽阔水国家级自然保护区
英文关键词:Infrared thermography  Bird nest  Field survey  Kuankuoshui National Nature Reserve
基金项目:国家自然科学基金项目(No. 31260514,31272328,31472013),教育部新世纪优秀人才支持计划项目(No. NCET-13-0761);
作者单位E-mail
粟通萍 热带动植物生态学省部共建教育部重点实验室 sutongping007@126.com 
霍娟 热带动植物生态学省部共建教育部重点实验室  
陈光平 贵州宽阔水国家级自然保护区管理局  
杨灿朝 热带动植物生态学省部共建教育部重点实验室  
梁伟* 热带动植物生态学省部共建教育部重点实验室 liangw@hainan.net 
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中文摘要:
      红外热成像仪是一种非接触、无损伤性的温度测量仪,它可通过接收被测物体表面的热辐射形成热谱图,对研究对象进行定性观察或定量分析。热成像仪在野生动物调查和实验研究等领域均有应用。我们于2015年4 ~ 8月的鸟类繁殖季,使用手持便携式红外热成像仪,对贵州宽阔水国家级自然保护区内4种生境的鸟巢进行系统搜索。共找到鸟巢54个,其中7巢可在红外热成像仪中清晰显示。使用红外热成像仪搜寻鸟巢的成功率为13.0%(7/54)。其中,搜寻地面巢的成功率最大(27.3%,3/11),树上巢的成功率最低(0%,0/5)。在热谱图中所显示的巢,其植被郁闭度显著小于红外热成像仪搜寻不到的巢(t = 2.837,df = 16,P < 0.01);而其温差则显著大于红外热成像仪搜寻不到的巢(t =﹣2.476,df = 19,P < 0.05)。这表明,使用红外热成像仪搜寻鸟巢主要受巢上植被郁闭度及巢周围环境温度的影响。巢上植被郁闭度越小,与周围环境的温差越大,则搜寻成功率越高。
英文摘要:
      Infrared thermography (IRT) is a non-invasive and non-contact method for measuring surface temperature by absorbing the radiation heat from the surface of objects and transferring into thermogram (Fig. 1). Thermography has numerous practical applications in animal thermal physiology and wildlife monitoring. During the breeding season from April to August 2015, we searched for bird nests across four types of habitat in Kuankuoshui National Nature Reserve, southwestern Guizhou, China. During our work, we first used portable thermal image by IRT to scan for the nests within 5 m along the paths with possible nests been shown obviously (Fig. 1), then we carefully searched for the nests again by eyesights in the same area. A total of 54 bird nests were found, of which only 7 nests were recorded in thermal image and the searching success rate by IRT was 13.0% (7/54, Table 1). The highest searching success rate by IRT was for ground nests (27.3%, 3/11) and the lowest for tree nests (0%, 0/5). The vegetation coverage of nests found by IRT was significantly lower than that by traditional searching method (t = 2.837, df = 16, P < 0.01), and there was also significant difference in nesting site temperature D-value (t =﹣2.476, df = 19, P < 0.05) between them. Our results showed that vegetation density and temperature D-value of nesting site had important effects on searching success rate by IRT, with better searching success rate under lower vegetation cover and higher temperature D-value.
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