Climatic factors controlling stem growth of alien tree species at a mesic forest site: a multispecies approach

Abstract

The introduction of non-native species with various ecological and functional traits to European forests may be a potential tool for mitigating climate risks. We analyzed the growth sensitivity to climate of seven alien (Acer rubrum, Betula maximowicziana, Castanea sativa, Cryptomeria japonica, Metasequoia glyptostroboides, Thuja plicata and Tsuga heterophylla) and two native (Fagus sylvatica and Picea abies) tree species on a productive forest site in western Germany in order to assess their potential suitability in light of climate change. Retrospective basal area increment at breast height (BAI) and total stem volume increment (VI) were statistically related to a total of 11 multiscale climatic variables showing minor discrepancies between BAI and VI in climatic sensitivity. Across the tree species, the strongest climate signals were found for the standardized precipitation evapotranspiration index (spei), vapor pressure deficit (vpd) and the number of frost days (nfr) representing water availability, heat and coldness, respectively. Growth of most species was positively affected by mild winters and growing season spei. Importance of the investigated variables differed among tree species with, e.g., C. sativa and T. plicata being mainly driven by winter vpd and A. rubrum, C. japonica and P. abies by water availability in the growing seasons. We conclude that particularly more anisohydric species (e.g., C. sativa) may profit from their low sensitivity to drier conditions. Highly sensitive and isohydric species (e.g., A. rubrum) will undergo significant growth reductions when climate becomes more variable.

Tree functional traits, forest biomass, and tree species diversity interact with site properties to drive forest soil carbon

“…To enable comparisons, when possible we calculated the different stand metrics (e.g., missing values of basal area were calculated from stand density and stem diameter). Then, when possible (25% of data), we estimated the missing values of stand biomass using linear regressions with other stand metrics (i.e., based on tree height [n = 37; P < 0.001; r 2 = 0.51] or stem diameter [n = 50; P < 0.001; r 2 = 0.45]), relying on the strong allometric relationships that exist among tree compartments [103][104][105] . We applied the same rationale to estimate the stand litterfall flux using the fine root production as predictor (3% of data; [n = 13; P = 0.017; r 2 = 0.42]).…”