Empirical and process-based models predict enhanced beech growth in European mountains under climate change scenarios: A multimodel approach.

Process-based models and empirical modelling techniques are frequently used to (i) explore the sensitivity of tree growth to environmental variables, and (ii) predict the future growth of trees and forest stands under climate change scenarios. However, modelling approaches substantially influence predictions of the sensitivity of trees to environmental factors. Here, we used tree-ring width (TRW) data from 1630 beech trees from a network of 70 plots established across European mountains to build empirical predictive growth models using various modelling approaches. In addition, we used 3-PG and Biome-BGCMuSo process-based models to compare growth predictions with derived empirical models. Results revealed similar prediction errors (RMSE) across models ranging between 3.71 and 7.54 cm2 of basal area increment (BAI). The models explained most of the variability in BAI ranging from 54 % to 87 %. Selected explanatory variables (despite being statistically highly significant) and the pattern of the growth sensitivity differed between models substantially. We identified only five factors with the same effect and the same sensitivity pattern in all empirical models: tree DBH, competition index, elevation, Gini index of DBH, and soil silt content. However, the sensitivity to most of the climate variables was low and inconsistent among the empirical models. Both empirical and process-based models suggest that beech in European mountains will, on average, likely experience better growth conditions under both 4.5 and 8.5 RCP scenarios. The process-based models indicated that beech may grow better across European mountains by 1.05 to 1.4 times in warmer conditions. The empirical models identified several drivers of tree growth that are not included in the current process-based models (e.g., different nutrients) but may have a substantial effect on final results, particularly if they are limiting factors. Hence, future development of process-based models may build upon our findings to increase their ability to correctly capture ecosystem dynamics.

Soil respiration variation along an altitudinal gradient in the Italian Alps: Disentangling forest structure and temperature effects.

On the mountains, along an elevation gradient, we generally observe an ample variation in temperature, with the associated difference in vegetation structure and composition and soil properties. With the aim of quantifying the relative importance of temperature, vegetation and edaphic properties on soil respiration (SR), we investigated changes in SR along an elevation gradient (404 to 2101 m a.s.l) in the southern slopes of the Alps in Northern Italy. We also analysed soil physicochemical properties, including soil organic carbon (SOC) and nitrogen (N) stocks, fine root C and N, litter C and N, soil bulk densities and soil pH at five forest sites, and also stand structural properties, including vegetation height, age and basal area. Our results indicated that SR rates increased with temperature in all sites, and 55-76% of SR variability was explained by temperature. Annual cumulative SR, ranging between 0.65-1.40 kg C m-2 yr-1, decreased along the elevation gradient, while temperature sensitivity (Q10) of SR increased with elevation. However, a high SR rate (1.27 kg C m-2 yr-1) and low Q10 were recorded in the mature conifer forest stand at 1731 m a.s.l., characterized by an uneven-aged structure and high dominant tree height, resulting in a nonlinear relationship between elevation and temperature. Reference SR at 10°C (SRref) was unrelated to elevation, but was related to tree height. A significant negative linear relationship was found between bulk density and elevation. Conversely, SOC, root C and N stock, pH, and litter mass were best fitted by nonlinear relationships with elevation. However, these parameters were not significantly correlated with SR when the effect of temperature was removed (SRref). These results demonstrate that the main factor affecting SR in forest ecosystems along this Alpine elevation gradient is temperature, but its regulating role can be strongly influenced by site biological characteristics, particularly vegetation type and structure, affecting litter quality and microclimate. This study also confirms that high elevation sites are rich in SOC and more sensitive to climate change, being prone to high C losses as CO2. Furthermore, our data indicate a positive relationship between Q10 and dominant tree height, suggesting that mature forest ecosystems characterized by an uneven-age structure, high SRref and moderate Q10, may be more resilient.

Do Aerial Nitrogen Depositions Affect Fungal and Bacterial Communities of Oak Leaves?

The amount of nitrogen (N) deposition onto forests has globally increased and is expected to double by 2050, mostly because of fertilizer production and fossil fuel burning. Several studies have already investigated the effects of N depositions in forest soils, highlighting negative consequences on plant biodiversity and the associated biota. Nevertheless, the impact of N aerial inputs deposited directly on the tree canopy is still unexplored. This study aimed to investigate the influence of increased N deposition on the leaf-associated fungal and bacterial communities in a temperate forest dominated by Sessile oak [Quercus petraea (Matt.) Liebl.]. The study area was located in the Monticolo forest (South Tyrol, Italy), where an ecosystem experiment simulating an increased N deposition has been established. The results highlighted that N deposition affected the fungal beta-diversity and bacterial alpha-diversity without affecting leaf total N and C contents. We found several indicator genera of both fertilized and natural conditions within bacteria and fungi, suggesting a highly specific response to altered N inputs. Moreover, we found an increase of symbiotrophic fungi in N-treated, samples which are commonly represented by lichen-forming mycobionts. Overall, our results indicated that N-deposition, by increasing the level of bioavailable nutrients in leaves, could directly influence the bacterial and fungal community diversity.

Nitrogen deposition outweighs climatic variability in driving annual growth rate of canopy beech trees: Evidence from long-term growth reconstruction across a geographic gradient.

In this study, we investigated the role of climatic variability and atmospheric nitrogen deposition in driving long-term tree growth in canopy beech trees along a geographic gradient in the montane belt of the Italian peninsula, from the Alps to the southern Apennines. We sampled dominant trees at different developmental stages (from young to mature tree cohorts, with tree ages spanning from 35 to 160 years) and used stem analysis to infer historic reconstruction of tree volume and dominant height. Annual growth volume (GV ) and height (GH ) variability were related to annual variability in model simulated atmospheric nitrogen deposition and site-specific climatic variables, (i.e. mean annual temperature, total annual precipitation, mean growing period temperature, total growing period precipitation, and standard precipitation evapotranspiration index) and atmospheric CO2 concentration, including tree cambial age among growth predictors. Generalized additive models (GAM), linear mixed-effects models (LMM), and Bayesian regression models (BRM) were independently employed to assess explanatory variables. The main results from our study were as follows: (i) tree age was the main explanatory variable for long-term growth variability; (ii) GAM, LMM, and BRM results consistently indicated climatic variables and CO2 effects on GV and GH were weak, therefore evidence of recent climatic variability influence on beech annual growth rates was limited in the montane belt of the Italian peninsula; (iii) instead, significant positive nitrogen deposition (Ndep ) effects were repeatedly observed in GV and GH ; the positive effects of Ndep on canopy height growth rates, which tended to level off at Ndep values greater than approximately 1.0 g m-2  y-1 , were interpreted as positive impacts on forest stand above-ground net productivity at the selected study sites.