Forest growth in Europe shows diverging large regional trends.

Forests cover about one-third of Europe's surface and their growth is essential for climate protection through carbon sequestration and many other economic, environmental, and sociocultural ecosystem services. However, reports on how climate change affects forest growth are contradictory, even for same regions. We used 415 unique long-term experiments including 642 plots across Europe covering seven tree species and surveys from 1878 to 2016, and showed that on average forest growth strongly accelerated since the earliest surveys. Based on a subset of 189 plots in Scots pine (the most widespread tree species in Europe) and high-resolution climate data, we identified clear large-regional differences; growth is strongly increasing in Northern Europe and decreasing in the Southwest. A less pronounced increase, which is probably not mainly driven by climate, prevails on large areas of Western, Central and Eastern Europe. The identified regional growth trends suggest adaptive management on regional level for achieving climate-smart forests.

Climatic water availability modifies tree functional diversity effects on soil organic carbon storage in European forests.

Forest stand and environmental factors influence soil organic carbon (SOC) storage, but little is known about their relative impacts in different soil layers. Moreover, how environmental factors modulate the impact of stand factors, particularly species mixing, on SOC storage, is largely unexplored. In this study, conducted in 21 forest triplets (two monocultures of different species and their mixture on the same site) distributed in Europe, we tested the hypothesis that stand factors (functional identity and diversity) have stronger effects on topsoil (FF + 0-10 cm) C storage than environmental factors (climatic water availability, clay + silt content, oxalate-extractable Al-Alox) but that the opposite occurs in the subsoil (10-40 cm). We also tested the hypothesis that functional diversity improves SOC storage under high climatic water availability, clay + silt contents, and Alox. We characterized functional identity as the basal area proportion of broadleaved species (beech and/or oak), and functional diversity as the product of broadleaved and conifer (pine) proportions. The results show that functional identity was the main driver of topsoil C storage, while climatic water availability had the largest control on subsoil C storage. Functional diversity decreased topsoil C storage under increasing climatic water availability, but the opposite was observed in the subsoil. Functional diversity effects on topsoil C increased with increasing clay + silt content, while its effects on subsoil C were negative at increasing Alox content. This suggests that functional diversity effect on SOC storage changes along gradients in environmental factors and the direction of effects depends on soil depth.

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.

The distribution of carbon stocks between tree woody biomass and soil differs between Scots pine and broadleaved species (beech, oak) in European forests.

While the impacts of forest management options on carbon (C) storage are well documented, the way they affect C distribution among ecosystem components remains poorly investigated. Yet, partitioning of total forest C stocks, particularly between aboveground woody biomass and the soil, greatly impacts the stability of C stocks against disturbances in forest ecosystems. This study assessed the impact of species composition and stand density on C storage in aboveground woody biomass (stem + branches), coarse roots, and soil, and their partitioning in pure and mixed forests in Europe. We used 21 triplets (5 beech-oak, 8 pine-beech, 8 pine-oak mixed stands, and their respective monocultures at the same sites) in seven European countries. We computed biomass C stocks from total stand inventories and species-specific allometric equations, and soil organic C data down to 40 cm depth. On average, the broadleaved species stored more C in aboveground woody biomass than soil, while C storage in pine was equally distributed between both components. Stand density had a strong effect on C storage in tree woody biomass but not in the soil. After controlling for stand basal area, the mixed stands had, on average, similar total C stocks (in aboveground woody biomass + coarse roots + soil) to the most performing monocultures. Although species composition and stand density affect total C stocks and its partitioning between aboveground woody biomass and soil, a large part of variability in soil C storage was unrelated to stand characteristics. Supplementary Information: The online version contains supplementary material available at 10.1007/s10342-022-01453-9.

Modelos del tamaño de copa del pinus sylvestris L en bosques del centro de España / Models of crown size in the scots pine pinus sylvestris L in forests of central Spain

Las ecuaciones de perfil de copa pueden ser usadas para caracterizar la apertura de la copa, el perfil del área de la copa, el volumen de la copa y la porosidad de la copa de un rodal, para predecir el crecimiento en altura de los árboles individuales, el crecimiento en área basal y la probabilidad de mortalidad en modelos de desarrollo del rodal, lo cual es importante para tomar decisiones de manejo. El objetivo de este estudio es construir ecuaciones para predecir los parámetros de la copa de pino silvestre en un bosque de montaña. Han sido ensayados diferentes modelos para estimar la relación de copa, la máxima anchura de copa, la altura a la base de la copa y la altura al punto de máxima anchura de copa usando regresión no lineal. La validación de los modelos da como resultado que son adecuados para estimar el tamaño de copa de pino silvestre y la importancia que tiene su estudio en los bosques de montaña