  With the recent increase in deforestation, forest fires, and regional
temperatures, the concerns around the rapid and complete collapse of the Amazon
rainforest ecosystem have heightened. The thresholds of deforestation and the
temperature increase required for such a catastrophic event are still
uncertain. However, our analysis presented here shows that signatures of
changing Amazon are already apparent in historical climate data sets. Here, we
extend the methods of climate network analysis and apply them to study the
temporal evolution of the connectivity between the Amazon rainforest and the
global climate system. We observe that the Amazon rainforest is losing
short-range connectivity and gaining more long-range connections, indicating
shifts in regional-scale processes. Using embeddings inspired by manifold
learning, we show that Amazon connectivity patterns have become more variable
in the twenty-first century. By investigating edge-based network metrics on
similar regions to the Amazon we see the changing properties of the Amazon are
significant in comparison. Furthermore, we simulate diffusion and random walks
on these networks and observe a faster spread of perturbations from the Amazon
in recent decades. Our methodology innovations can act as a template for
examining the spatiotemporal patterns of regional climate change and its impact
on global climate using the toolbox of climate network analysis.
