Predicting state shifts in energetic food webs under climate change

Global environmental changes are driving biodiversity loss at unprecedented rates. By providing ecosystem services, biodiversity contributes up to 50% of the GNP internationally every year. Simply put, the loss of biodiversity constitutes a global threat to both human welfare and global stability. This realization has led to a growing interest in forecasting biological responses from local to global scales and from genes to ecosystems. Yet, our ability to predict the long-​term consequences of global environmental changes on biodiversity and the associated ecosystem services remains severely limited.

StateShift propose a novel approach to forecasting changes in biodiversity that overcomes some of the limitations of current approaches: modelling stable states and shifts in the architecture of food webs.

PI: Miguel Araújo

Duration: 36 months