Abstract

ABSTRACT Forest resilience, the ecosystem’s capacity to withstand perturbations and retain primary functions and characteristics, is an essential indicator in evaluating the fate of an ecosystem under rapid climate change. Detailed information about forest resilience change, such as number of changes, direction (reduced vs increased), timing (start/end year), or duration of the change, is critical but is often not well demonstrated at the global scale. Here, we applied lag-one autocorrelation (AC1) as a forest resilience indicator on time series MODIS vegetation index images from 2001 to 2022 and employed LandTrendr spectral-temporal segmentation algorithms to track forest resilience change. Our results showed that the resilience of global forests changed nearly 3 times on average, and over 50% of global forests had an overall downward trend from the early 2000s up to recently. However, the current condition is changing for the better globally with approximately 53% of global forests currently showing an increased resilience during the recent change, and average patches of reduced resilience becoming smaller and more scattered. Over half of the forests in arid and temperate domains still show decreased resilience recently, which highlights the need for improved management practices.

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