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Quantifying exaptation in scientific evolution

About the book:


This book explores the role of exaptation in diverse areas of life, with examples ranging from biology to economics, social sciences and architecture. The concept of exaptation, introduced in evolutionary biology by Gould and Vrba in 1982, describes the possibility that already existing traits can be exploited for new purposes throughout the evolutionary process.

Edited by three active scholars in the fields of biology, physics and economics, the book presents an interdisciplinary collection of expert viewpoints illustrating the importance of exaptation for interpreting current reality in various fields of investigation. Using the lenses of exaptation, the contributing authors show how to view the overall macroscopic landscape as comprising many disciplines, all working in unity within a single complex system.

This book is the first to discuss exaptation in both hard and soft disciplines and highlights the role of this concept in understanding the birth of innovation by identifying key elements and ideas. It also offers a comprehensive guide to the emerging interdisciplinary field of exaptation, provides didactic explanations of the basic concepts, and avoids excessive jargon and heavy formalism. Its target audience includes graduate students in physics, biology, mathematics, economics, psychology and architecture; it will also appeal to established researchers in the humanities who wish to explore or enter this new science-driven interdisciplinary field.



M. Ferreira, N. Reisz, W. Schueller, V.D.P. Servedio, S. Thurner, V. Loreto, Quantifying exaptation in scientific evolution, in: in: C. La Porta, S. Zapperi, L. Pilotti (eds.), Understanding Innovation Through Exaptation (2020) Springer 55–68

Willliam Schueller © Verena Ahne

William Schueller

Niklas Reisz © Verena Ahne

Niklas Reisz

Vito D. P. Servedio

Stefan Thurner @ Franziska Liehl, President of the Complexity Science Hub

Stefan Thurner

Vittorio Loreto, External Faculty member at the Complexity Science Hub

Vittorio Loreto

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