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基于红外相机技术的雷公山自然保护区白鹇生境选择研究

古定豪 吴必锋 余德会 李登江 李扬

安徽农业科学2025,Vol.53Issue(8):79-82,4.
安徽农业科学2025,Vol.53Issue(8):79-82,4.DOI:10.3969/j.issn.0517-6611.2025.08.017

基于红外相机技术的雷公山自然保护区白鹇生境选择研究

Research on Habitat Selection of Lophura nycthemera in Leigongshan Nature Reserve Based on Infrared Camera Technology

古定豪 1吴必锋 1余德会 1李登江 1李扬1

作者信息

  • 1. 贵州省雷公山自然保护区管理局,贵州雷山 557199
  • 折叠

摘要

Abstract

In order to understand the habitat selection characteristics of Lophura nycthemera in the Leigongshan Nature Reserve,100 infrared camera monitoring sites were randomly set up on a kilometer grid to monitor the activity of the white pheasant in key areas of Leigongshan.From January 2020 to December 2021,100 infrared cameras were collected for monitoring and investigating in the field for 18 074 camera days,ob-taining a total of 41 739 videos and photos.Among them,1 325 videos or photos of the white pheasant were detected,and 731 independent ef-fective photos(videos)of the white pheasant were analyzed and counted.A total of 37 monitoring points of the white pheasant were identified.The RAI statistical analysis of the white pheasant in the monitoring plot showed that the relative abundance index of the white pheasant in Leigongshan Nature Reserve was RAI=4.044,and its grid occupancy rate was 42.05%.After statistical analysis of the ecological factors affect-ing the habitat selection of the white pheasant,it was found that the habitat selected by the white pheasant is mainly in coniferous and broad-leaved mixed forests and broad-leaved forests near water sources,with abundant food resources,moderate terrain,and altitude gradients of grade Ⅲ-Ⅳ.There are fewer shrubs(<2 plants/m2)and moderate amounts of herbaceous plants(2-50 plants/m2)in the activity area.

关键词

红外触发相机技术/雷公山自然保护区/白鹇/生境选择

Key words

Infrared triggered camera technology/Leigongshan Nature Reserve/Lophura nycthemera/Habitat selection

分类

农业科技

引用本文复制引用

古定豪,吴必锋,余德会,李登江,李扬..基于红外相机技术的雷公山自然保护区白鹇生境选择研究[J].安徽农业科学,2025,53(8):79-82,4.

基金项目

黔东南州科技计划项目(黔东南科合[2020]063号) (黔东南科合[2020]063号)

贵州省林业科研课题(黔林科合[2020]16号). (黔林科合[2020]16号)

安徽农业科学

0517-6611

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