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Cross-disciplinary approaches are needed to make major leaps forward on large societal issues. But the application of such an approach often proves challenging. In this panel, we propose to discuss the use of trans-disciplinary approaches to address global changes, including how to combine the needs and knowledge to respond effectively to the fast-changing climate. Participants will propose through short presentations a given perspective from within their respective discipline(s) (environment and natural sciences, health, social sciences and humanities) on the panel’s central question: “What are the major challenges of cross-disciplinary data and service integration technically, scientifically and socially to face global changes?”. The discussion will then be centered around lessons learned and experiences, as well as technical and conceptual solutions already explored for integrating diverse data types from a variety of sources within inter-, multi- or trans-disciplinary projects. In addition, bearing in mind that global changes concern a large variety of stakeholders, acting within rather than among systems and procedures, the specific added-value of integrating citizen science techniques and other participatory methodologies from social sciences and humanities into these cross-cutting projects will also be explored. This panel aims to identify the most valuable theoretical and practical collaboration perspectives among disciplines as an efficient way for the analysis and the comprehension of global changes. Audience participation in the discussions will be actively encouraged, ideally using one of the techniques discussed as a demonstration., The TRIPLE project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 863420 Disclaimer. The content of this publication is the sole responsibility of the authors and can in no way be taken to reflect the views of the European Commission. The European Commission is not responsible for any use that may be made of the information it contains.

Density-dependence function (f) with respect to varying strength of the Allee effect (a). Where KÂ =Â 600, 200, 100 and a vary from 0 to 100. High a reduces the population reproductive function and represents notably the difficulty to locate a mate when the population density is low. (PDF 48Â kb)