Suppr超能文献

利用单一物种复合体的全球远程相机数据来评估群体形成的驱动因素。

Using global remote camera data of a solitary species complex to evaluate the drivers of group formation.

作者信息

Twining Joshua P, Sutherland Chris, Zalewski Andrzej, Cove Michael V, Birks Johnny, Wearn Oliver R, Haysom Jessica, Wereszczuk Anna, Manzo Emiliano, Bartolommei Paola, Mortelliti Alessio, Evans Bryn, Gerber Brian D, McGreevy Thomas J, Ganoe Laken S, Masseloux Juliana, Mayer Amy E, Wierzbowska Izabela, Loch Jan, Akins Jocelyn, Drummey Donovan, McShea William, Manka Stephanie, Pardo Lain, Boyce Andy J, Li Sheng, Ragai Roslina Binti, Sukmasuang Ronglarp, Villafañe Trujillo Álvaro José, López-González Carlos, Lara-Díaz Nalleli Elvira, Cosby Olivia, Waggershauser Cristian N, Bamber Jack, Stewart Frances, Fisher Jason, Fuller Angela K, Perkins Kelly A, Powell Roger A

机构信息

New York Cooperative Fish and Wildlife Research Unit, Department of Natural Resources and the Environment, Cornell University, Ithaca, NY 14853.

Centre for Research into Ecological and Environmental Modelling, Schools of Mathematics and Statistics, Biology, and Computer Science, The Observatory Buchanan Gardens University of St. Andrews, St. Andrews, Fife KY16 9LZ, United Kingdom.

出版信息

Proc Natl Acad Sci U S A. 2024 Mar 19;121(12):e2312252121. doi: 10.1073/pnas.2312252121. Epub 2024 Mar 11.

Abstract

The social system of animals involves a complex interplay between physiology, natural history, and the environment. Long relied upon discrete categorizations of "social" and "solitary" inhibit our capacity to understand species and their interactions with the world around them. Here, we use a globally distributed camera trapping dataset to test the drivers of aggregating into groups in a species complex (martens and relatives, family , Order ) assumed to be obligately solitary. We use a simple quantification, the probability of being detected in a group, that was applied across our globally derived camera trap dataset. Using a series of binomial generalized mixed-effects models applied to a dataset of 16,483 independent detections across 17 countries on four continents we test explicit hypotheses about potential drivers of group formation. We observe a wide range of probabilities of being detected in groups within the solitary model system, with the probability of aggregating in groups varying by more than an order of magnitude. We demonstrate that a species' context-dependent proclivity toward aggregating in groups is underpinned by a range of resource-related factors, primarily the distribution of resources, with increasing patchiness of resources facilitating group formation, as well as interactions between environmental conditions (resource constancy/winter severity) and physiology (energy storage capabilities). The wide variation in propensities to aggregate with conspecifics observed here highlights how continued failure to recognize complexities in the social behaviors of apparently solitary species limits our understanding not only of the individual species but also the causes and consequences of group formation.

摘要

动物的社会系统涉及生理、自然史和环境之间复杂的相互作用。长期以来依赖于对“群居”和“独居”的离散分类,这限制了我们理解物种及其与周围世界相互作用的能力。在这里,我们使用一个全球分布的相机陷阱数据集,来测试一个被认为是 obligately solitary(此处原文有误,推测可能是“专性独居”)的物种复合体(貂类及其近亲,鼬科,食肉目)聚集成群的驱动因素。我们使用一种简单的量化方法,即在群体中被检测到的概率,将其应用于我们从全球范围获得的相机陷阱数据集。通过对来自四大洲17个国家的16483次独立检测数据应用一系列二项式广义混合效应模型,我们检验了关于群体形成潜在驱动因素的明确假设。我们在独居模型系统中观察到群体中被检测到的概率范围很广,聚集成群的概率相差超过一个数量级。我们证明,一个物种在群体中聚集的情境依赖性倾向是由一系列与资源相关的因素支撑的,主要是资源的分布,资源斑块性增加有利于群体形成,以及环境条件(资源稳定性/冬季严酷程度)和生理(能量储存能力)之间的相互作用。这里观察到的与同种个体聚集倾向的广泛差异凸显出,持续未能认识到明显独居物种社会行为的复杂性,不仅限制了我们对单个物种的理解,也限制了我们对群体形成的原因和后果的理解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b465/10962950/3996b6716739/pnas.2312252121fig01.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验