Biodiversity is crucial for maintaining ecosystem stability and achieving sustainable development. However, global biodiversity loss is a common challenge faced by most countries. Therefore, based on the data from the International Union for Conservation of Nature (IUCN) Red List of Threatened Species and the Eora database, we used the multi-regional input-output (MRIO) model to calculate biodiversity loss in 188 countries. We constructed a global biodiversity loss transfer network from the binary and weighted perspectives and deconstructed the evolution characteristics and the factors influencing the network from the "relationship" perspective using social network analysis (SNA) and quadratic assignment procedure (QAP) method. The global biodiversity loss transfer network had a typical network structure with dense connections, demonstrating spatial correlation characteristics. The countries with top in- and out-degree centrality rankings were developed and large-scale emerging economies and developing countries in Africa, respectively, implying that the former are responsible for "importing" large amounts of biodiversity and transferring biodiversity loss to the latter. The block model analysis indicated that the transfer network was divided into different functional blocks, with biodiversity spillover effects. The QAP analysis revealed that the differences in geographical adjacency, per capita GDP, urbanization rate, environmental regulation, and agricultural land proportion explained 3.627% of the changes in the global biodiversity loss transfer network. Our results suggested that the relationships of biodiversity loss transfer among countries should be considered by policymakers to address biodiversity challenges. Therefore, governments should recognize the remote responsibility, reduce unsustainable consumption and production, develop sustainable trade, and make trade policies considering the transfer of biodiversity impacts.
Keywords: Biodiversity loss transfer; International trade; Quadratic assignment procedure analysis; Social network analysis.
© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.