Mountain data collection and modelling efforts are still often conducted in narrow disciplinary silos and short-term projects. Systematically gathered and comprehensive long-term data are scarce, with socio-economic data often especially lacking. Consequently, key interactions and feedbacks operating across mountain socio-ecological systems may remain poorly understood and/or represented in models. We encourage contributions that, a priori, take highly interdisciplinary/holistic and/or long-term approaches to (in situ and/or remotely sensed) data collection, collation, or integration across spatial and elevational gradients, and modelling studies that capitalize on a broad range of observations to deliver improved decision-relevant predictions. Pathways towards sustainably and permanently obtaining Standard Observations / Essential Mountain Variables, ideally following open science principles, should be explored (e.g. the emerging eLTER RI). We anticipate a rich discussion on the challenges of working across traditional disciplinary and methodological boundaries.

A new research aims to identify the main changes in mountain transhumance over the past decades as perceived by the breeders and stakeholders. This research is currently based on twelve contrasted case studies located in diverse mountain areas and climatic-ecological zones. Several topics of changes are identified, especially in terms of governance, presence of other users, herd and pasture management practices and technologies, transportation. Climate change is an ever-increasing reality that will strongly affect transhumance and the entire livestock sector. Differences and similarities between the case studies suggest that appropriated policies based on collective approaches can enable breeders to be more involved in mountains’ sustainable development. We invite the different case studies to present in 10-12 pages or 20-25000 characters their respective papers, focusing on the diversity of occurred changes, trying to prioritize them. We are also very interested in other case studies. We suggest that they also present their respective papers in 10-12 pages or 20-25000 characters.