Reut Vardi, Andrea Soriano-Redondo, Jorge S Gutiérrez, Łukasz Dylewski, Zuzanna Jagiello, Peter Mikula, Oded Berger-Tal, Daniel T Blumstein, Ivan Jarić, Valerio Sbragaglia
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引用次数: 0
Abstract
The widespread sharing of information on the Internet has given rise to ecological studies that use data from digital sources including digitized museum records and social media posts. Most of these studies have focused on understanding species occurrences and distributions. In this essay, we argue that data from digital sources also offer many opportunities to study animal behavior including long-term and large-scale comparisons within and between species. Following Nikko Tinbergen's classical roadmap for behavioral investigation, we show how using videos, photos, text, and audio posted on social media and other digital platforms can shed new light on known behaviors, particularly in a changing world, and lead to the discovery of new ones.
期刊介绍：
PLOS Biology is the flagship journal of the Public Library of Science (PLOS) and focuses on publishing groundbreaking and relevant research in all areas of biological science. The journal features works at various scales, ranging from molecules to ecosystems, and also encourages interdisciplinary studies. PLOS Biology publishes articles that demonstrate exceptional significance, originality, and relevance, with a high standard of scientific rigor in methodology, reporting, and conclusions.
The journal aims to advance science and serve the research community by transforming research communication to align with the research process. It offers evolving article types and policies that empower authors to share the complete story behind their scientific findings with a diverse global audience of researchers, educators, policymakers, patient advocacy groups, and the general public.
PLOS Biology, along with other PLOS journals, is widely indexed by major services such as Crossref, Dimensions, DOAJ, Google Scholar, PubMed, PubMed Central, Scopus, and Web of Science. Additionally, PLOS Biology is indexed by various other services including AGRICOLA, Biological Abstracts, BIOSYS Previews, CABI CAB Abstracts, CABI Global Health, CAPES, CAS, CNKI, Embase, Journal Guide, MEDLINE, and Zoological Record, ensuring that the research content is easily accessible and discoverable by a wide range of audiences.
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