EGU22-9340
https://doi.org/10.5194/egusphere-egu22-9340
EGU General Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Measuring Amazon rainforest resilience from remotely sensed data

Da Nian1, Lana Blaschke1, Yayun Zheng2, and Niklas Boers1,3,4
Da Nian et al.
  • 1Potsdam Institute for Climate Impact Research, Potsdam, 14412, Germany
  • 2School of Mathematical Sciences, Jiangsu University, Zhenjiang 212013, China
  • 3School of Engineering & Desin, Earth System Modelling, Technical University of Munich, Germany;
  • 4Department of Mathematics and Global Systems Institute, University of Exeter, United Kingdom

The Amazon rainforest has a major contribution to the bio-geochemical functioning of the Earth system and has been projected to be at risk of large-scale, potentially irreversible, dieback to a savanna state. Measuring the resilience of the Amazon rainforest empirically is critical to helping us understand the magnitude and frequency of disturbances that the rainforest can still recover from. Different means to quantify resilience in practice have been proposed. Here we determine the Amazon rainforest resilience based on a space-for-time replacement, and then estimating the average residence time in the forest state. This 'global' notion of resilience is different from local measures based on variance or autocorrelation and thus provides complementary information. We study the dependence of the exit-time-base resilience on total rainfall and, in order to study the evolution of the Amazon rainforest, we also estimate changes in their resilience over the years.

How to cite: Nian, D., Blaschke, L., Zheng, Y., and Boers, N.: Measuring Amazon rainforest resilience from remotely sensed data, EGU General Assembly 2022, Vienna, Austria, 23–27 May 2022, EGU22-9340, https://doi.org/10.5194/egusphere-egu22-9340, 2022.

Corresponding presentation materials formerly uploaded have been withdrawn.