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评价日本东北部不同分析方法下肉食动物的时间和时空生态位分割。

Evaluating the temporal and spatio-temporal niche partitioning between carnivores by different analytical method in northeastern Japan.

机构信息

Graduate School of Agricultural Sciences, Yamagata University, 1-23, Wakaba-machi, Tsuruoka-shi, Yamagata, 997-8555, Japan.

Center for Environmental Science in Saitama, 914, Kamitanadare, Kazo-shi, Saitama, 347-0115, Japan.

出版信息

Sci Rep. 2022 Jul 14;12(1):11987. doi: 10.1038/s41598-022-16020-w.

Abstract

Temporal and spatio-temporal niche partitioning is an important strategy for carnivore coexistence. Camera-trap data has been analyzed through several methods to assess the temporal and spatio-temporal niche partitioning. However, different analytical approaches used to may evaluate niche partitioning detect different results. In this study, we evaluated the temporal or spatio-temporal partitioning among sympatric medium-sized carnivores, red foxes, raccoon dogs, and Japanese martens, based on three analytical methods-the temporal overlap, temporal co-occurrence, and time-to-encounter analysis-to evaluate. From May to October 2019 and 2020, we obtained the activity of the target species using camera-traps in northeastern Japan. We analyzed the data with the coefficient of temporal overlap, probabilistic co-occurrence analysis, checkerboard score, and multi-response permutation procedures. The results of the assessment of the niche partitioning differed depending on the analytical methods based on temporal and spatio-temporal partitioning. Therefore, we conclude that the choice of analytical approach is important for evaluating the temporal and spatio-temporal niche partitioning.

摘要

时间和时空生态位分离是肉食动物共存的一种重要策略。已经通过几种方法对相机陷阱数据进行了分析,以评估时间和时空生态位分离。然而,用于评估生态位分离的不同分析方法可能会检测到不同的结果。在这项研究中,我们基于三种分析方法(时间重叠、时间共存和遭遇时间分析)评估了在日本东北部的同一地区共存的中型肉食动物(赤狐、貉和日本貂)之间的时间或时空生态位分离。我们在 2019 年 5 月至 10 月和 2020 年期间使用相机陷阱获取了目标物种的活动数据。我们使用时间重叠系数、概率共存分析、棋盘得分和多响应置换程序对数据进行了分析。基于时间和时空分离的生态位分离评估结果因分析方法而异。因此,我们得出结论,选择分析方法对于评估时间和时空生态位分离非常重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/55d1/9283404/8b7ed463e5d9/41598_2022_16020_Fig1_HTML.jpg

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