Jong Hwan Lim

TL;DR: In this paper, the authors present the first global assessment of recent tree mortality attributed to drought and heat stress and identify key information gaps and scientific uncertainties that currently hinder our ability to predict tree mortality in response to climate change and emphasizes the need for a globally coordinated observation system.

TL;DR: In this article , a machine learning model was developed to explain tree mortality and growth reduction in terms of the key parameters of climate and tree ecophysiology in temperate forests of Korea, where various ecophysiological parameters with a process-based vegetation model were used as inputs to multiple machine learning algorithms and the conventional multiple linear regression (MLR).