DOI: 10.5061/dryad.ncjsxkt4v
title: Data from: Utilization patterns and optimization suggestions for wildlife passages in Xinjiang nature reserves

description: The expansion of linear infrastructure significantly threatens
 biodiversity, necessitating comprehensive multi-species research and
 studies on regional differences. We surveyed and monitored wildlife
 passages in eight nature reserves in Xinjiang, assessing their
 construction status, utilization patterns, and key factors influencing
 utilization rates, and proposing optimization suggestions. Our results
 showed that dedicated wildlife passages were rare, except in large
 reserves, which mostly relied on small bridges and culverts for water
 passage. Strengthening passage construction in these areas is recommended.
 We recorded 32 wildlife species, including 13 bird species and 19 mammal
 species. The relative abundance index of Cetartiodactyla and
 Perissodactyla, such as bharal, goitered gazelle, and Asian wild ass, was
 notably high. Utilization rates of passages were lowest in winter,
 increased in spring, and peaked in summer and autumn. In July, all
 monitoring sites showed positive selection, indicating a universal trend.
 Passage utilization rates were significantly higher at night. At sunrise,
 86.96% of monitoring sites showed positive selection, while at sunset,
 91.30% did. Seasonal variations and time differences should be considered
 in passage design and management, particularly by reducing human
 activities during nighttime and dawn/dusk periods to improve utilization
 and protect wildlife migration and survival needs. The density of linear
 infrastructure and human activity intensity were the main factors
 influencing utilization rates. Lower infrastructure density leads to
 higher utilization rates, while high-intensity human activity areas, due
 to more food resources and reduced interspecific competition, increase
 utilization rates. Minimizing habitat fragmentation and strengthening
 passage construction and management in high human activity areas is
 suggested. Our study emphasizes tailored passage design and management
 based on species-specific and seasonal behaviors, contributing to better
 conservation practices and policies. These findings can be applied to
 other regions, offering principles in conservation biology to reduce
 habitat fragmentation and strategically place passages to facilitate
 wildlife movement and survival.
description: (1) Monitoring data Infrared camera monitoring
 technology widely applied in wildlife passage utilization studies was used
 here. Cameras were set at 0.5-1 meters above the ground, angled slightly
 downward, avoiding direct sunlight or reflective objects. Camera
 performance and settings are shown in Table 2. Data was collected for at
 least three months per monitoring point to account for animal activity
 variations and ensure comprehensive data collection. Species
 identification referenced the " List of Biological Species of China
 (2023 Edition)," " Vertebrate Volume of the Red List of
 Biodiversity of China," and " List of Birds of China (4th
 Edition, 2023)." Photos with accurately identifiable species recorded
 species names and numbers.  (2) RDA analysis
 data Traffic volume refers to the annual average
 traffic volume of motor vehicles, measured in vehicles per day. Underpass
 and overpass types of passages were assigned values of 1 and 2,
 respectively. Passage size refers to the volume of the passage (deck width
 of the bridge × clearance height × span) and the width of the passage
 reserved in the fence. Linear infrastructure density refers to the ratio
 of the total length of highways, railways, and fences within a 1-kilometer
 radius of the sample sites to the area of that region. Human activity
 intensity refers to the total number of independent valid photos of humans
 and livestock within the sample site divided by the total number of
 effective working days at all monitoring points. RAI stands for relative
 abundance index, and SWI stands for Shannon-Wiener index.
description: # Data from: Utilization patterns and optimization suggestions for
 wildlife passages in Xinjiang nature reserves
 [https://doi.org/10.5061/dryad.ncjsxkt4v](https://doi.org/10.5061/dryad.ncjsxkt4v) ## Description of the data and file structure The expansion of linear infrastructure significantly threatens biodiversity, necessitating comprehensive multi-species research and studies on regional differences. We surveyed and monitored wildlife passages in eight nature reserves in Xinjiang, assessing their construction status, utilization patterns, and key factors influencing utilization rates, and proposing optimization suggestions. Infrared camera monitoring technology widely applied in wildlife passage utilization studies was used here. Cameras were set at 0.5-1 meters above the ground, angled slightly downward, avoiding direct sunlight or reflective objects. Camera performance and settings are shown in Table 2. Data was collected for at least three months per monitoring point to account for animal activity variations and ensure comprehensive data collection. Species identification referenced the " List of Biological Species of China (2023 Edition)," " Vertebrate Volume of the Red List of Biodiversity of China," and " List of Birds of China (4th Edition, 2023)." Photos with accurately identifiable species recorded species names and numbers.  Key factors considered for influencing wildlife passage utilization rates included: Traffic volume refered to the annual average traffic volume of motor vehicles, measured in vehicles per day. Underpass and overpass types of passages were assigned values of 1 and 2, respectively. Passage size refered to the volume of the passage (deck width of the bridge × clearance height × span) and the width of the passage reserved in the fence. Linear infrastructure density refered to the ratio of the total length of highways, railways, and fences within a 1-kilometer radius of the sample sites to the area of that region. Human activity intensity refered to the total number of independent valid photos of humans and livestock within the sample site divided by the total number of effective working days at all monitoring points. RAI stands for relative abundance index, and SWI stands for Shannon-Wiener index. ### Files and variables #### File: RDA\_analysis\_data.xlsx **Description:** Redundancy analysis (RDA) was performed using Canoco 5 software to analyze the relationship between the utilization rate of wildlife passages and their influencing factors. ##### Variables * Traffic volume refered to the annual average traffic volume of motor vehicles, measured in vehicles per day. Underpass and overpass types of passages were assigned values of 1 and 2, respectively. Passage size refered to the volume of the passage (deck width of the bridge × clearance height × span) and the width of the passage reserved in the fence. Linear infrastructure density refered to the ratio of the total length of highways, railways, and fences within a 1-kilometer radius of the sample sites to the area of that region. Human activity intensity refered to the total number of independent valid photos of humans and livestock within the sample site divided by the total number of effective working days at all monitoring points. RAI stands for relative abundance index, and SWI stands for Shannon-Wiener index. #### File: Monitoring\_data.xlsx **Description:** Data monitored by infrared cameras. ##### Variables * The date and time of the infrared camera of each monitoring site, as well as the name and number of species.