Wildlife Conservation: A Bibliometric Analysis

Abstract

This study presents a bibliometric analysis of wildlife conservation research to identify its intellectual structure, thematic evolution, influential publications, and collaboration patterns. A total of 1,997 documents published between 2000 and 2026 were retrieved from the Scopus database and analyzed using VOSviewer through keyword co-occurrence, overlay, and density visualizations, as well as co-authorship analysis at the author, institution, and country levels. The results show that the field is organized around three main thematic clusters: ecological and biodiversity assessment, conservation management and human dimensions, and animal biology and health. Core themes such as conservation, wildlife conservation, nature conservation, and biodiversity dominate the literature, while recent studies increasingly focus on artificial intelligence, learning systems, local livelihoods, and less-studied taxa such as invertebrates. The most cited documents address machine learning, climate-change adaptation, population genomics, and human–wildlife relationships. Co-authorship networks among authors and institutions display chain-like and partially fragmented structures, whereas the United States, the United Kingdom, Australia, India, and China emerge as the main hubs of international collaboration. The study highlights a transition from species- and habitat-oriented research toward interdisciplinary, technology-supported, and socially informed approaches to wildlife conservation.