ZEF Colloquium on Towards robust data and models for addressing global sustainability trade-offs

April 29, 2021 | 15:30 h - 16:30 h

ZEF colloquium on Thursday 29 April at 1:30 pm (CEST)

Speaker: Carsten Meyer (German Centre for Integrative Biodiversity Research (iDiv))

Title: Towards robust data and models for addressing global sustainability trade-offs

 

Abstract:

The sustainability challenges surrounding trade-offs between food security, biodiversity conservation, and economic development are typically vast, urgent, and complex. Confronted with such problems, we are often tempted to act fast by pulling together little bits and pieces from different fields and simply adding these to pre-existent models or frameworks. Seldom, though, do we pause long enough to consider how best to draw on these fields, in order to build sustainable data and modelling structures that will remain powerful for addressing human-environmental challenges over the long term. In this talk, I will discuss some structural limitations in current interdisciplinary model-building efforts and outline a research agenda for addressing this status quo. A vision of a socio-technological 'infrastructure' that integrates and regularly updates best-available data, theory, and methods from multiple fields to facilitate an empirically robust causal and predictive understanding of the major human-environment relationships governing food-biodiversity-development trade-offs. In doing so, it may enable more robust scenario modelling pipelines that are better capable of addressing some of the major sustainability challenges of the 2020s and beyond. Here and there, I will also showcase some of my lab's efforts in advancing parts of this agenda.

Dr. Carsten Meyer is head of the junior research group "Macroecology and Society" at the German Centre for Integrative Biodiversity Research (iDiv). His research focuses on global land-use changes, their environmental consequences, and their socioeconomic drivers using modern digital technology as a way of addressing theoretical, data, and modelling challenges in interdisciplinary science.

 

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