Abstract

Bark beetle outbreaks damage forests and kill trees worldwide, but many aspects of their dynamics remain unexplained. Our aim was to identify predictors for individual tree deaths within the small (0.7 km2) Plešné Lake catchment in the Šumava National Park in southwestern Czechia. Within this area, >60,000 trees were geo-referenced and categorized from ten aerial images (20 cm spatial resolution) between 2000 and 2015. For each year for which aerial images were available, we calculated tree densities of different categories and diameters. Tree height was evaluated by means of LiDAR in two terrestrial campaigns (2010 and 2011). A machine learning technique was then used to evaluate the most important variables. The resulting relationships were largely nonlinear and differed among years; however, individual trait tree height proved to be the most influential variable in each year. Higher trees were more likely to have died during either the undisturbed phase (2000 and 2003), the disturbed phase (2005–2011), or the recovery phase (2013). Our results indicate that salvage logging may not be the most effective measure for protecting trees in small catchments.

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