No abstract

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

With climate change, natural disturbances such as storm or fire are reshuffled, inducing pervasive shifts in forest dynamics. To predict how it will impact forest structure and composition, it is crucial to understand how tree species differ in their sensitivity to disturbances. In this study, we investigated how functional traits and species mean climate affect their sensitivity to disturbances while controlling for tree size and stand structure. With data on 130,594 trees located on 7617 plots that were disturbed by storm, fire, snow, biotic or other disturbances from the French, Spanish, and Finnish National Forest Inventory, we modeled annual mortality probability for 40 European tree species as a function of tree size, dominance status, disturbance type, and intensity. We tested the correlation of our estimated species probability of disturbance mortality with their traits and their mean climate niches. We found that different trait combinations controlled species sensitivity to disturbances. Storm‐sensitive species had a high height‐dbh ratio, low wood density and high maximum growth, while fire‐sensitive species had low bark thickness and high P50. Species from warmer and drier climates, where fires are more frequent, were more resistant to fire. The ranking in disturbance sensitivity between species was overall consistent across disturbance types. Productive conifer species were the most disturbance sensitive, while Mediterranean oaks were the least disturbance sensitive. Our study identified key relations between species functional traits and disturbance sensitivity, that allows more reliable predictions of how changing climate and disturbance regimes will impact future forest structure and species composition at large spatial scales.

23Identifying the scales of variation in forest structures and the underlying processes are fundamental 24 for understanding forest dynamics. Here, we studied these scale-dependencies in forest structure in 25 naturally dynamic boreal forests on two continents. We identified the spatial scales at which forest 26 structures varied, and analyzed how the scales of variation and the underlying drivers differed 27 among the regions and at particular scales. 28 29We studied three 2 km × 2 km landscapes in northeastern Finland and two in eastern Canada. We 30 estimated canopy cover in contiguous 0.1-ha cells from aerial photographs and used scale-31 derivative analysis to identify characteristic scales of variation in the canopy cover data. We 32 analyzed the patterns of variation at these scales using Bayesian scale space analysis. 33 34We identified structural variation at three spatial scales in each landscape. Among landscapes, the 35 largest scale of variation showed greatest variability (20.1 -321.4 ha), related to topography, soil 36 variability, and long-term disturbance history. Superimposed on this large-scale variation, forest 37 structure varied at similar scales (1.3 -2.8 ha) in all landscapes. This variation correlated with 38 recent disturbances, soil variability, and topographic position. We also detected intense variation at 39 the smallest scale analyzed (0.1 ha, grain of our data), partly driven by recent disturbances. 40 41The distinct scales of variation indicated hierarchical structure in the landscapes studied. Except for 42 the large-scale variation, these scales were remarkably similar among the landscapes. This suggests 43 that boreal forests may display characteristic scales of variation that occur somewhat independent of 44 the tree species characteristics or the disturbance regime. 45