The need for an individual-based global change ecology
Florian Jeltsch, Manuel Roeleke, Ahmed Abdelfattah, Robert Arlinghaus, Gabriele Berg, Niels Blaum, Luc De Meester, Elke Dittmann, Jana A. Eccard, Bertrand Fournier, Ursula Gaedke, Cara A. Gallagher, Lynn Govaert, Márk E. Hauber, Jonathan M. Jeschke, Stephanie Kramer‐Schadt, Anja Linstädter, Ulrike Lucke, Valeria Mazza, Ralf Metzler, Claas Nendel, Viktoriia Radchuk, Matthias C. Rillig, Masahiro Ryo, Katharina Scheiter, Ralph Tiedemann, Britta Tietjen, Christian C. Voigt, Guntram Weithoff, Justyna Wolinska, Damaris Zurell
Abstract
Biodiversity loss and widespread ecosystem degradation are among the most pressing challenges of our time, requiring urgent action. Yet our understanding of their causes remains limited because prevailing ecological concepts and approaches often overlook the underlying complex interactions of individuals of the same or different species, interacting with each other and with their environment. We propose a paradigm shift in ecological science, moving from simplifying frameworks that use species, population or community averages to an integrative approach that recognizes individual organisms as fundamental agents of ecological change. The urgency of the biodiversity crisis requires such a paradigm shift to advance ecology towards a predictive science by elucidating the causal mechanisms linking individual variation and adaptive behaviour to emergent properties of populations, communities, ecosystems, and ecological interactions with human interventions. Recent advances in computational technologies, sensors, and analytical tools now offer unprecedented opportunities to overcome past challenges and lay the foundation for a truly integrated Individual-Based Global Change Ecology (IBGCE). Unravelling the potential role of individual variability in global change impact analyses will require a systematic combination of empirical, experimental and modelling studies across systems, while taking into account multiple drivers of global change and their interactions. Key priorities include refining theoretical frameworks, developing benchmark models and standardized toolsets, and systematically incorporating individual variation and adaptive behaviour into empirical field work, experiments and predictive models. The emerging synergies between individual-based modelling, big data approaches, and machine learning hold great promise for addressing the inherent complexity of ecosystems. Each step in the development of IBGCE must systematically balance the complexity of the individual perspective with parsimony, computational efficiency, and experimental feasibility. IBGCE aims to unravel and predict the dynamics of biodiversity in the Anthropocene through a comprehensive study of individual organisms, their variability and their interactions. It will provide a critical foundation for considering individual variation and behaviour for future conservation and sustainability management, taking into account individual-to-ecosystem pathways and feedbacks.