i-CONN has been a rich and diverse experience, although much of phase 1 of the network was delivered online due to COVID-19 (with the addition of an online seminar series that featured external speakers and was open to all). The second phase of i-CONN focused on strengthening wider networking, with two annual meetings, a final meeting, and two datathon events that created space for further collaborations between ESRs, as well as helping the curation of network datasets and the application of diverse connectivity methods to these datasets. These activities enabled us to achieve our goals, with all deliverables and milestones completed. In addition to the dissemination of results via conferences and publications, we have disseminated summaries of the research via 3-minute TEDx-style presentations, and via links with non-academic stakeholders, e.g. the UK Environment Agency and the Donau-Auen National Parks.
We created a training network for ESRs, focused on research and transferable skills, alongside advanced training courses, that benefited all members of the network. As a result, alongside secondments and training at host beneficiary institutions, we have trained a highly skilled cohort of 15 ESRs who now have exceptional skills spanning the theory, methods, and applications of connectivity.
We developed the theoretical underpinning of connectivity science (WP1), including understanding the diversity of relationships between structural and functional connectivities via simple mathematical models, and understanding collective behaviours in networks, and the development of a taxonomy of structural and functional connectivities in complex systems. We assessed the commonalities and uniqueness of properties, structures, techniques and the methods utilized across the network (Fig 2), and from this explored the application of these methods across disciplines, which culminated in a “Synthesis of methods” (WP2). This work underpinned the application of connectivity science methods within i-CONN (WP3), largely supported by secondments, and led to detailed applications within disciplines of geomorphology, ecology, neuroscience, and social-ecological systems.
We took the opportunity to explore how an innovative training network can create transdisciplinary capacity, via the work of an ESR, who studied the evolution of the i-CONN network. Through this longitudinal study, we have been able to reflect on the effectiveness and inclusiveness of collaborations and evaluate the types of interactions that help to facilitate knowledge exchange and learning between network members (Fig 3).
