Advances in the monitoring of infrared cameras in southwest China.

In the face of increasing biodiversity loss, the United Nations adopted the Aichi Target of the Convention on Biological Diversity (Strategic Plan for Biodiversity 2011-2020) in 2010.
in order to implement the relevant provisions of the Convention, the former Ministry of Environmental Protection prepared the China Biodiversity Conservation Strategy and Action Plan (2011-2030), and the Chinese Academy of Sciences established the China Biodiversity Monitoring and Research Network (Sino BON).
, as one of the important members of the Sino BON Animal Special Network, the Animal Ecology and Evolution Discipline Group of Kunming Institute of Zoology of the Chinese Academy of Sciences carried out animal diversity monitoring and research in southwest China.
infrared camera technology has outstanding advantages in the investigation and monitoring research of large and medium-sized wild animals, easy to standardize technical standards, easy to manage and standardize statistical analysis of the obtained data, has become the main technical support of animal monitoring and research network at home and abroad.
in recent years, the Animal Ecology and Evolution Discipline Group has continuously expanded its monitoring scope, increased its monitoring efforts, and built an infrared camera monitoring and research network (Li et al., 2014) in protected areas representing different landscape types according to uniform sampling standards; Li et al., 2018).
based on previous monitoring data, the researchers used the hierarchical Bayesian model for three typical landscape types in southwestern China (alpine-sub-alpine regions ( 3500-4860 m), dry-hot valleys (2100-3500 m) and subtropical mountain forests .200 The richness and distribution of terrestrial and semi-terrestrial rare wildlife species are analyzed, and the species abundance and distribution of target groups in different landscapes are assessed by constructing hierarchical models, analyzing species occupancy and their associations with environmental variables from multiple levels, such as species, class groups and target species collections.
studies have found that the hierarchical occupancy model based on Poisson distribution fits the infrared camera data with high degree of dispersion, and the hierarchical model can integrate and analyze infrared camera data from several research sites, analyze species abundance and distribution patterns from different scales, and provide ideas for the integration and analysis of network data for regional collaborative infrared camera monitoring and research. The post-mortem distribution of the
model parameters (95% confidence interval) shows that, at the community level (target species collection), human interference shows strong negative effects on species diversity and occupancy, and the medium-peak pattern between species abundance and altitude is shown, and the medium-peak pattern of vertical distribution of species abundance corresponds to the high interference pressure at lower altitude and the low depression at higher altitude. Degrees: At the level of ecological groups, there is a clear parabolic relationship between the occupancy and altitude of various groups, and human interference has strong negative effects on the rest of the groups except ferns.
Although dry-hot valleys are often considered poor areas of biodiversity, studies have found that species of such landscape target groups are even richer than subtropical mountain forests and are ideal habitats for endangered species such as antelopes and rock sheep;
the research was based on the study of Using Large Spatial Scale Camera Trap Data and Sie-Si-s- and Sieus sr.
the research was supported by the National Key Research and Development Program (#2017YFC0505200), the National Natural Science Foundation of China (#31601874), the China Biodiversity Monitoring and Research Network (Sino BON) and the Ministry of Ecological Environment's Biodiversity Conservation (#2110404).
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