Michael Dorman

TL;DR: The results imply that growth-based mortality algorithms may be a powerful tool for predicting gymnosperm mortality induced by chronic stress, but not necessarily so for angiosperms and in case of intense drought or bark-beetle outbreaks.

TL;DR: In this paper, the authors estimate the potential for electricity generation by building-integrated PV in typical residential building types in dense urban locations, accounting for shading by adjacent structures using 3D modeling of the shadows cast by buildings.

TL;DR: In this article, the authors examined how rainfall amount affects forest performance and found that forest performance response was not spatially homogeneous, and three response types could be identified along the rainfall gradient: stable performance with low correlation to rainfall pattern in the humid region (>500mm), moderate performance decline with high correlated to rainfall in the intermediate region (350-500mm) and steep performance decline in the arid region (

TL;DR: It is demonstrated how machine learning with quality control and spatial features substantially improves satellite-derived AOD products for air pollution modeling, with XGBoost outperformed the other machine-learning approaches.

TL;DR: The observed insensitivity of slow-growing trees to competition implies that mortality risk may be density independent, when even any potential for higher soil moisture availability in open stands is lost to evapotranspiration before it can benefit tree growth.