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本文引用的文献

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Accounting for individual-specific variation in habitat-selection studies: Efficient estimation of mixed-effects models using Bayesian or frequentist computation.在栖息地选择研究中考虑个体特有变异:使用贝叶斯或频率派计算有效估计混合效应模型。
J Anim Ecol. 2020 Jan;89(1):80-92. doi: 10.1111/1365-2656.13087. Epub 2019 Sep 9.
2
Optimizing the use of biologgers for movement ecology research.优化生物标记物在运动生态学研究中的应用。
J Anim Ecol. 2020 Jan;89(1):186-206. doi: 10.1111/1365-2656.13094. Epub 2019 Oct 1.
3
Linking behaviour to dynamics of populations and communities: application of novel approaches in behavioural ecology to conservation.将行为与种群和群落动态联系起来:行为生态学中新颖方法在保护中的应用。
Philos Trans R Soc Lond B Biol Sci. 2019 Sep 16;374(1781):20190008. doi: 10.1098/rstb.2019.0008. Epub 2019 Jul 29.
4
Animal movement tools (amt): R package for managing tracking data and conducting habitat selection analyses.动物运动工具(amt):用于管理跟踪数据和进行栖息地选择分析的R包。
Ecol Evol. 2019 Feb 5;9(2):880-890. doi: 10.1002/ece3.4823. eCollection 2019 Jan.
5
Central place foragers and moving stimuli: A hidden-state model to discriminate the processes affecting movement.中央位置觅食者和移动刺激:用于区分影响运动过程的隐状态模型。
J Anim Ecol. 2018 Jul;87(4):1116-1125. doi: 10.1111/1365-2656.12830. Epub 2018 Apr 19.
6
Tree-centric mapping of forest carbon density from airborne laser scanning and hyperspectral data.基于机载激光扫描和高光谱数据的森林碳密度树状中心映射
Methods Ecol Evol. 2016 Oct;7(10):1236-1245. doi: 10.1111/2041-210X.12575. Epub 2016 May 14.
7
The sensory ecology of adaptive landscapes.适应性景观的感官生态学。
Biol Lett. 2015 May;11(5):20141054. doi: 10.1098/rsbl.2014.1054.
8
Space-use behaviour of woodland caribou based on a cognitive movement model.基于认知运动模型的林地驯鹿空间利用行为
J Anim Ecol. 2015 Jul;84(4):1059-70. doi: 10.1111/1365-2656.12357. Epub 2015 Mar 20.
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Patch size, functional isolation, visibility and matrix permeability influences neotropical primate occurrence within highly fragmented landscapes.斑块大小、功能隔离、可见性和基质渗透性影响新热带灵长类动物在高度破碎化景观中的出现情况。
PLoS One. 2015 Feb 6;10(2):e0114025. doi: 10.1371/journal.pone.0114025. eCollection 2015.
10
Applications of step-selection functions in ecology and conservation.步选择函数在生态学和保护中的应用。
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所见即所得:在三维结构的林冠层中,可视性影响鸟类的运动决策。

What you see is where you go: visibility influences movement decisions of a forest bird navigating a three-dimensional-structured matrix.

机构信息

Department of Biology, University of Antwerp, Wilrijk, Belgium.

Wildlife Sciences, University of Goettingen, Göttingen, Germany.

出版信息

Biol Lett. 2021 Jan;17(1):20200478. doi: 10.1098/rsbl.2020.0478. Epub 2021 Jan 27.

DOI:10.1098/rsbl.2020.0478
PMID:33497591
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7876602/
Abstract

Animal spatial behaviour is often presumed to reflect responses to visual cues. However, inference of behaviour in relation to the environment is challenged by the lack of objective methods to identify the information that effectively is available to an animal from a given location. In general, animals are assumed to have unconstrained information on the environment within a detection circle of a certain radius (the perceptual range; PR). However, visual cues are only available up to the first physical obstruction within an animal's PR, making information availability a function of an animal's location within the physical environment (the effective visual perceptual range; EVPR). By using LiDAR data and viewshed analysis, we modelled forest birds' EVPRs at each step along a movement path. We found that the EVPR was on average 0.063% that of an unconstrained PR and, by applying a step-selection analysis, that individuals are 1.55 times more likely to move to a tree within their EVPR than to an equivalent tree outside it. This demonstrates that behavioural choices can be substantially impacted by the characteristics of an individual's EVPR and highlights that inferences made from movement data may be improved by accounting for the EVPR.

摘要

动物的空间行为通常被认为是对视觉线索的反应。然而,由于缺乏客观的方法来确定动物从特定位置有效获取的信息,因此对环境的行为推断受到了挑战。一般来说,动物被认为在一定半径的检测圆(感知范围;PR)内对环境具有不受限制的信息。然而,只有在动物 PR 内的第一个物理障碍物之前才能获得视觉线索,这使得信息的可用性成为动物在物理环境中位置的函数(有效视觉感知范围;EVPR)。通过使用激光雷达数据和视线分析,我们在运动路径的每个步骤上模拟了森林鸟类的 EVPR。我们发现,EVPR 平均为无约束 PR 的 0.063%,并且通过应用步长选择分析,个体在 EVPR 内移动到一棵树的可能性是在其外部移动到等效树的可能性的 1.55 倍。这表明行为选择可能会受到个体 EVPR 特征的重大影响,并强调了通过考虑 EVPR,可以提高从运动数据中得出的推断。