Francesco Minunno

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, a steady-state model integrating xylem and phloem transport, leaf-level gas exchange and plant carbohydrate consumption during drought development is presented, and the possible modes of plant failure at steady state are identified.

TL;DR: In this paper, the authors used six models, ranging from simple parameter-sparse models to complex process-based models: 3PG, 4C, ANAFORE, BASFOR, BRIDGING and FORMIND, to predict forest growth in Austria, Belgium, Estonia and Finland.

TL;DR: The calibrated model suggests that the response of forest productivity to climate extremes is more complex than simple shift toward higher elevation, and robust estimates of NPP are key for increasing the understanding of forests ecosystems carbon dynamics under climate extremes.

TL;DR: The present study accounts for the main sampling-related biases to determine reliable species-specific growth-mortality relationships using logistic mixed-effects regression models and highlights the importance of using a sampling strategy that is consistent with the research question.