Beech Bark Disease in an Unmanaged Temperate Forest: Patterns, Predictors, and Impacts on Ecosystem Function

Beech Bark Disease (BBD) is a devastating threat to American beech (Fagus grandifolia), spreading through eastern mixed deciduous forests of North America at unprecedented rates. Understanding how and why some beech trees escape severe BBD effects is important; however, the biotic and abiotic factors that underpin the progression of BBD within unmanaged forests at local scales are not well explored. We surveyed 651 individual beech trees ≥ 10 cm diameter at breast height (DBH) for BBD, in a 13.5-ha unmanaged forest dynamics plot in Ontario, Canada, where >46,000 trees have been identified to species, mapped, and DBH measured at ∼5-year intervals. For each beech tree, BBD severity was ranked on a 5-point severity index, which was then evaluated as a function of tree characteristics including DBH and relative growth rate (RGR). Most beech trees were at either the insect or fungal stage of BBD, with only 22% of beech trees being free of symptoms. Ordinal logistic regression analysis indicated both DBH and RGR were significant predictors of BBD severity. These models, along with both randomization and Moran’s Eigenvector Maps (MEM) analyses, indicated that DBH and RGR and their spatial variation accounted for ∼44.6% of BBD severity in trees. Our MEMs also indicated ∼4.2% of variation in BBD severity was associated with unmeasured spatial variables, which may reflect either the spread of BBD through our study site, or the influence of abiotic variables on BBD severity. At our site, BBD is responsible for at least ∼6.0 Mg C ha–1, or ∼6.5% of the average 92.5 Mg of aboveground biomass C ha–1, transitioning from the live to dead biomass pool. Our study enhances the understanding of the factors predicting the severity of a major forest pathogen in North American temperate forests, assists the integration of BBD severity risk into forest C budget models, and provides insight into how large-scale forest inventories can inform screening for pest or pathogen resistance in trees.

Abstract licence: CC BY

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.