Jordi Bascompte is Professor of Ecology at the University of Zurich and Director of its Specialized Master on Quantitative Environmental Sciences. He is mostly well-known for having brought the interactions of mutual benefit between plants and animals into community ecology, at the time largely dominated by predation and competition. His application of network theory to the study of mutualism has identified general laws that determine the way in which species interactions shape biodiversity. Jordi is one of the most highly cited scientists according to Thompson Reuters. Among his distinctions are the European Young Investigator Award (2004), the Ecological Society of America's George Mercer Award (2007), the Spanish National Research Award (2011), and the British Ecological Society's Marsh Book of the Year Award (2016). Recipient of an ERC’s Advanced Grant, Jordi has served in the Board of Reviewing Editors of Science and has been the Ideas and Perspectives Editor at Ecology Letters. Among his books are Self-Organization in Complex Ecosystems (with R.V. Solé) and Mutualistic Networks (with P. Jordano), both published by Princeton University Press.

Jordi obtained a PhD in Biology by the University of Barcelona (1994), supervised by Ricard V. Solé. This was followed by a postdoctoral position in Steven Frank's laboratory at the University of California, Irvine (1996 and 1997). After that, he was awarded an independent postdoctoral fellowship at the National Center for Ecological Analysis and Synthesis (NCEAS, 1998 and 1999). In 2000, he became Associate Professor (Full Professor from 2008) at the Doñana Biological Station, a center of the Spanish Research Council, where he was based until moving to Zurich in 2015.

We combine mathematical models, simulations, and data set analyses to address fundamental and applied questions in ecology.

Our current major research interest focuses on the structure and dynamics of ecological networks. This complements main approaches to biodiversity research that neglect species interactions or assume these are homogeneously distributed.

As an example, our application of network theory to the study of mutualisms among free-living species has provided a quantitative framework to address mutualistic interactions at the community level. Our work has shown that these networks of mutual dependencies between plants and animals present general architectural patterns that maximize the number of coexisting species and increase the range of perturbations that can be withstood before one or more species goes extinct.