Recent work suggests that episodes of drought and heat can bring forests across climate zones to a threshold for massive tree mortality. Across complex systems, the vicinity of a threshold for collapse tends to come with a loss of resilience as reflected in declining recovery rates from perturbations. Trees may be no exception, as at the verge of drought induced death, trees are found to be weakened in multiple ways affecting their ability to recover from stress. Here we use world-wide time series of satellite images to show that temporal autocorrelation, an indicator of slow recovery rates, rises steeply as mean annual precipitation declines to levels known to be critical for tropical forests. This implies independent support for the idea that such forests may have a tipping point for collapse at drying conditions. Moreover, the demonstration that slowing down may be detected from satellite data suggests a novel way to monitor resilience of tropical forests, as well as other ecosystems known to be vulnerable to collapse. With the advent of Sentinel-1 and 2 satellites new opportunities arise to derive accurate and near operational forest resilience measures.

Jan Verbesselt @janverbesselt is associate professor in remote sensing at Wageningen University, Laboratory of Geo-information Science and Remote Sensing. He focuses on measuring and understanding ecosystem dynamics by developing novel spatio-temporal methods to detect, monitor and forecast changes using remotely sensed data from in-situ, terrestrial- and airborne LiDAR, and satellite sensors. The application of remotely sensed images for ecological modelling, and collaborative earth science for assessing vegetation, climate, and human impacts take a central place. He is the author of an open-source toolkit, BFAST, providing functionality to detect, monitor and characterise change within satellite image time series (http://bfast.r-forge.r-project.org/).

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