{"title":"利用相机陷阱估算中央森林国家自然保护区(俄罗斯欧洲部分西部)棕熊的种群密度和数量","authors":"S. Ogurtsov","doi":"10.24189/ncr.2023.008","DOIUrl":null,"url":null,"abstract":"This paper presents the results of estimating the population density and abundance of Ursus arctos (hereinafter – brown bear) in the Southern Forestry of the Central Forest State Nature Biosphere Reserve (CFNR), West of European Russia, in 2021 based on the Random Encounter Model (REM) based upon data obtained from camera traps. Methods for obtaining parameters necessary for building a model are demonstrated. A total of 7970 camera trap nights were worked out at 46 stations, and 502 independent trap events were obtained. The average relative abundance index (RAI) was 6.28 ± 1.59. The total average brown bear population density was 0.086 ± 0.034 individuals per 1 km2. The approximate estimated abundance was 18.98 ± 7.54 individuals. The coefficient of variation was 38%. Population density estimates had a pronounced seasonal dynamics. The minimum value was recorded for the period from 24 June to 23 July (individuals feeding on meadows and ants outside the CFNR core area), and the maximum for the period from 24 July to 22 August (brown bears feeding by berries in the CFNR core area). We found a strong significant correlation between brown bear population density and its relative abundance index (r = 0.81, p < 0.05). It was found that with an increase in the sampling period duration, the estimate of the population density noticeably decreases (r = -0.53, p < 0.05). Parameters of the average travel speed and activity level are a subject to the greatest variability, which determines the significant variability of the day range. In general, the method of population density estimation using REM is highly promising to carry out the brown bear population size estimation in forests and mountain forests, where visual estimations are difficult or impossible.","PeriodicalId":54166,"journal":{"name":"Nature Conservation Research","volume":null,"pages":null},"PeriodicalIF":1.2000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Estimating brown bear population density and abundance using camera traps in the Central Forest State Nature Reserve (west of European Russia)\",\"authors\":\"S. 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The minimum value was recorded for the period from 24 June to 23 July (individuals feeding on meadows and ants outside the CFNR core area), and the maximum for the period from 24 July to 22 August (brown bears feeding by berries in the CFNR core area). We found a strong significant correlation between brown bear population density and its relative abundance index (r = 0.81, p < 0.05). It was found that with an increase in the sampling period duration, the estimate of the population density noticeably decreases (r = -0.53, p < 0.05). Parameters of the average travel speed and activity level are a subject to the greatest variability, which determines the significant variability of the day range. In general, the method of population density estimation using REM is highly promising to carry out the brown bear population size estimation in forests and mountain forests, where visual estimations are difficult or impossible.\",\"PeriodicalId\":54166,\"journal\":{\"name\":\"Nature Conservation Research\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":1.2000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nature Conservation Research\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.24189/ncr.2023.008\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"BIODIVERSITY CONSERVATION\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature Conservation Research","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.24189/ncr.2023.008","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"BIODIVERSITY CONSERVATION","Score":null,"Total":0}
引用次数: 0
摘要
本文介绍了基于相机陷阱数据的随机相遇模型(REM)对俄罗斯西部中央森林国家自然生物圈保护区(CFNR)南部森林地区2021年熊(以下简称棕熊)种群密度和丰度的估算结果。演示了获取建立模型所需参数的方法。在46个站点共计算了7970个相机陷阱夜,获得了502个独立陷阱事件。平均相对丰度指数(RAI)为6.28±1.59。棕熊总平均种群密度为0.086±0.034只/ 1 km2。估计丰度为18.98±7.54只。变异系数为38%。人口密度估计具有明显的季节性动态。最小值出现在6月24日至7月23日(以草地和蚂蚁为食),最大值出现在7月24日至8月22日(棕熊以浆果为食)。棕熊种群密度与其相对丰度指数呈极显著相关(r = 0.81, p < 0.05)。随着采样周期的延长,种群密度估计值显著降低(r = -0.53, p < 0.05)。平均旅行速度和活动水平的参数是变化最大的一个主题,这决定了日范围的显著变化。总体而言,利用REM估算种群密度的方法在森林和山林中进行棕熊种群规模估算是很有希望的,因为目测估算是困难或不可能的。
Estimating brown bear population density and abundance using camera traps in the Central Forest State Nature Reserve (west of European Russia)
This paper presents the results of estimating the population density and abundance of Ursus arctos (hereinafter – brown bear) in the Southern Forestry of the Central Forest State Nature Biosphere Reserve (CFNR), West of European Russia, in 2021 based on the Random Encounter Model (REM) based upon data obtained from camera traps. Methods for obtaining parameters necessary for building a model are demonstrated. A total of 7970 camera trap nights were worked out at 46 stations, and 502 independent trap events were obtained. The average relative abundance index (RAI) was 6.28 ± 1.59. The total average brown bear population density was 0.086 ± 0.034 individuals per 1 km2. The approximate estimated abundance was 18.98 ± 7.54 individuals. The coefficient of variation was 38%. Population density estimates had a pronounced seasonal dynamics. The minimum value was recorded for the period from 24 June to 23 July (individuals feeding on meadows and ants outside the CFNR core area), and the maximum for the period from 24 July to 22 August (brown bears feeding by berries in the CFNR core area). We found a strong significant correlation between brown bear population density and its relative abundance index (r = 0.81, p < 0.05). It was found that with an increase in the sampling period duration, the estimate of the population density noticeably decreases (r = -0.53, p < 0.05). Parameters of the average travel speed and activity level are a subject to the greatest variability, which determines the significant variability of the day range. In general, the method of population density estimation using REM is highly promising to carry out the brown bear population size estimation in forests and mountain forests, where visual estimations are difficult or impossible.