MacaqueNet: Advancing comparative behavioural research through large-scale collaboration

IF 3.7 1区环境科学与生态学 Q1 ECOLOGY Journal of Animal Ecology Pub Date : 2025-02-11 DOI:10.1111/1365-2656.14223

Delphine De Moor, Macaela Skelton, MacaqueNet, Federica Amici, Malgorzata E. Arlet, Krishna N. Balasubramaniam, Sébastien Ballesta, Andreas Berghänel, Carol M. Berman, Sofia K. Bernstein, Debottam Bhattacharjee, Eliza Bliss-Moreau, Fany Brotcorne, Marina Butovskaya, Liz A. D. Campbell, Monica Carosi, Mayukh Chatterjee, Matthew A. Cooper, Veronica B. Cowl, Claudio De la O, Arianna De Marco, Amanda M. Dettmer, Ashni K. Dhawale, Joseph J. Erinjery, Cara L. Evans, Julia Fischer, Iván García-Nisa, Gwennan Giraud, Roy Hammer, Malene F. Hansen, Anna Holzner, Stefano Kaburu, Martina Konečná, Honnavalli N. Kumara, Marine Larrivaz, Jean-Baptiste Leca, Mathieu Legrand, Julia Lehmann, Jin-Hua Li, Anne-Sophie Lezé, Andrew MacIntosh, Bonaventura Majolo, Laëtitia Maréchal, Pascal R. Marty, Jorg J. M. Massen, Risma Illa Maulany, Brenda McCowan, Richard McFarland, Pierre Merieau, Hélène Meunier, Jérôme Micheletta, Partha S. Mishra, Shahrul A. M. Sah, Sandra Molesti, Kristen S. Morrow, Nadine Müller-Klein, Putu Oka Ngakan, Elisabetta Palagi, Odile Petit, Lena S. Pflüger, Eugenia Polizzi di Sorrentino, Roopali Raghaven, Gaël Raimbault, Sunita Ram, Ulrich H. Reichard, Erin P. Riley, Alan V. Rincon, Nadine Ruppert, Baptiste Sadoughi, Kumar Santhosh, Gabriele Schino, Lori K. Sheeran, Joan B. Silk, Mewa Singh, Anindya Sinha, Sebastian Sosa, Mathieu S. Stribos, Cédric Sueur, Barbara Tiddi, Patrick J. Tkaczynski, Florian Trebouet, Anja Widdig, Jamie Whitehouse, Lauren J. Wooddell, Dong-Po Xia, Lorenzo von Fersen, Christopher Young, Oliver Schülke, Julia Ostner, Christof Neumann, Julie Duboscq, Lauren J. N. Brent

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猕猴：通过大规模合作推进比较行为研究。

有大量的、不断积累的关于个体识别动物的行为数据，这是揭示动物行为变化的生态和进化驱动因素的不可思议的资源。然而，这些数据的全部潜力在于具有不同生活史和生态的分类群之间的比较研究。实质性的挑战阻碍了系统的比较，其中之一是缺乏持久的、可获得的和标准化的数据库。建立标准化数据库的大团队方法为促进可靠的跨物种比较提供了一种解决方案。通过在研究人员之间共享数据和专业知识，这些方法确保了有价值的数据变得更容易被发现、重新利用和合成，否则这些数据可能会被闲置。此外，这种大规模的合作促进了研究社区内的共享文化，通过确保通过明确的共享指导方针考虑他们的利益来激励研究人员贡献他们的数据。在标准化过程中与数据提供者的积极沟通也有助于避免对数据的误解，最终提高比较数据库的可靠性。在这里，我们介绍MacaqueNet，一个由100多名研究人员组成的全球合作项目（https://macaquenet.github.io/），旨在为猕猴社会行为研究解锁丰富的跨物种数据。猕猴数据库包含了从1981年到现在的14个物种的61个种群的数据，是第一个公开搜索和标准化的关于亲和和敌对动物社会行为的数据库。我们描述了猕猴的建立，从我们开始大规模集体的步骤，到跨物种协作数据库的创建，以及数据输入和检索协议的实现。我们共享macquenet的组件资源：用于数据标准化的R包、网站代码、关系数据库结构、术语表和数据共享使用条款。由于所有这些组件都可以公开访问，macquenet可以作为未来建立大规模协作比较数据库的完全可复制的模板。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Animal Ecology 环境科学-动物学

CiteScore

9.10

自引率

4.20%

发文量

188

审稿时长

3 months

期刊介绍： Journal of Animal Ecology publishes the best original research on all aspects of animal ecology, ranging from the molecular to the ecosystem level. These may be field, laboratory and theoretical studies utilising terrestrial, freshwater or marine systems.