Population survey and habitat selection of Sus scrofa in Hunan Gaowangjie National Nature Reserve by infrared camera
Based on the investigation of the current status of the Sus scrofa population and their habitat selection preferences within the Hunan Gaowangjie Nature Reserve,with the aim of providing scientific evidence and decision support for wildlife conservation and disease prevention and control.From January 2021 to May 2022,87 cameras were strategically placed within the Hunan Gaowangjie Nature Reserve using a combination of grid and transect sampling methods.Correlating population status and habitat of S.scrofa usingrelative abundance(shooting rate),cluster analysis and principal component analysis.During the study period,the occurrence rate of S.scrofa in the infrared camera monitoring sites reached 76.92%,and the relative abundance index RAI was 4.43,estimating the population size to be about 1 561 animals.Monthly relative abundance index analysis revealed that July was the peak of S.scrofa activity,while activity was relatively low in March.The analysis of daily activity rhythms revealed that S.scrofa activities were mainly concentrated from 6:00 to 8:00 a.m.and from 16:00 to 18:00 p.m.In terms of habitat selection,S.scrofa preferred to move in mixed coniferous and broad forests(66.1%of the total),with tree heights of 11～20 m(61%ofthe total),with a degree of depression of more than 50%(84.1%ofthe total),and with shrub heightsranging2～4 m(69.5%ofthe total).The S.scrofa population in the Hunan Gaowangjie Nature Reserve was relatively abundant and widely distributed,and showed obvious seasonal activity patterns and preference for specific habitat types.In this study,the S.scrofa population was effectively monitored by infrared camera technology,and its activity pattern and habitat preference were analyzed in depth,which provided an important reference for subsequent S.scrofa ecological research and conservation management.
Sus scrofainfrared camerapopulation statushabitat selectionGaowangjie Nature Reserve
NETL
NSTL
万方数据
