TY - GEN A1 - Hirschl, Bernd A1 - Ruppert-Winkel, Chantal A1 - Arlinghaus, Robert A1 - Deppisch, Sonja A1 - Eisenack, Klaus A1 - Gottschlich, Daniela A1 - Matzdorf, Bettina A1 - Mölders, Tanja A1 - Padmanabhan, Martina A1 - Selbmann, Kirsten A1 - Ziegler, Rafael A1 - Plieninger, Tobias T1 - Characteristics, emerging needs, and challenges of transdisciplinary sustainability science: experiences from the German Social-Ecological Research Program T2 - Ecology and Society N2 - Transdisciplinary sustainability science (TSS) is a prominent way of scientifically contributing to the solution of sustainability problems. Little is known, however, about the practice of scientists in TSS, especially those early in their career. Our objectives were to identify these practices and to outline the needs and challenges for early career scientists in TSS. Three major challenges were identified: (1) TSS demands openness to a plurality of research designs, theories, and methods, while also requiring shared, explicit, and recursive use of TSS characteristics; (2) researchers in TSS teams must make decisions about trade-offs between achievements of societal and scientific impact, acknowledging that focusing on the time-consuming former aspect is difficult to integrate into a scientific career path; and (3) although generalist researchers are increasingly becoming involved in such TSS research projects, supporting the integration of social, natural, and engineering sciences, specialized knowledge is also required. KW - Social-Ecological Research Program KW - Nachhaltigkeit KW - Transdisciplinary sustainability science (TSS) Y1 - 2015 U6 - https://doi.org/10.5751/ES-07739-200313 SN - 1708-3087 VL - 20 IS - 3 SP - 13 ER - TY - GEN A1 - Jeltsch, Florian A1 - Roeleke, Manuel A1 - Abdelfattah, Ahmed A1 - Arlinghaus, Robert A1 - Berg, Gabriele A1 - Blaum, Niels A1 - De Meester, Luc A1 - Dittmann, Elke A1 - Eccard, Jana Anja A1 - Fournier, Bertrand A1 - Gaedke, Ursula A1 - Gallagher, Cara A1 - Govaert, Lynn A1 - Hauber, Mark A1 - Jeschke, Jonathan M. A1 - Kramer-Schadt, Stephanie A1 - Linstädter, Anja A1 - Lucke, Ulrike A1 - Mazza, Valeria A1 - Metzler, Ralf A1 - Nendel, Claas A1 - Radchuk, Viktoriia A1 - Rillig, Matthias C. A1 - Ryo, Masahiro A1 - Scheiter, Katharina A1 - Tiedemann, Ralph A1 - Tietjen, Britta A1 - Voigt, Christian C. A1 - Weithoff, Guntram A1 - Wolinska, Justyna A1 - Zurell, Damaris T1 - The need for an individual-based global change ecology T2 - Individual-based ecology N2 - 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. KW - Agent-based KW - Biodiversity crisis KW - Climate change KW - Ecological theory KW - Individual trait variation KW - Predictions KW - Scaling up Y1 - 2025 U6 - https://doi.org/10.3897/ibe.1.148200 SN - 3033-0947 VL - 1 SP - 1 EP - 18 PB - Pensoft Publishers CY - Sofia ER -