Major tree species of Central European forests differ in their proportion of positive, negative, and nonstationary growth trends.

Temperate forests are undergoing significant transformations due to the influence of climate change, including varying responses of different tree species to increasing temperature and drought severity. To comprehensively understand the full range of growth responses, representative datasets spanning extensive site and climatic gradients are essential. This study utilizes tree-ring data from 550 sites from the temperate forests of Czechia to assess growth trends of six dominant Central European tree species (European beech, Norway spruce, Scots pine, silver fir, sessile and pedunculate oak) over 1990-2014. By modeling mean growth series for each species and site, and employing principal component analysis, we identified the predominant growth trends. Over the study period, linear growth trends were evident across most sites (56% increasing, 32% decreasing, and 10% neutral). The proportion of sites with stationary positive trends increased from low toward high elevations, whereas the opposite was true for the stationary negative trends. Notably, within the middle range of their distribution (between 500 and 700 m a.s.l.), Norway spruce and European beech exhibited a mix of positive and negative growth trends. While Scots pine growth trends showed no clear elevation-based pattern, silver fir and oaks displayed consistent positive growth trends regardless of site elevation, indicating resilience to the ongoing warming. We demonstrate divergent growth trajectories across space and among species. These findings are particularly important as recent warming has triggered a gradual shift in the elevation range of optimal growth conditions for most tree species and has also led to a decoupling of growth trends between lowlands and mountain areas. As a result, further future shifts in the elevation range and changes in species diversity of European temperate forests can be expected.

Ecological and methodological drivers of non-stationarity in tree growth response to climate.

Radial tree growth is sensitive to environmental conditions, making observed growth increments an important indicator of climate change effects on forest growth. However, unprecedented climate variability could lead to non-stationarity, that is, a decoupling of tree growth responses from climate over time, potentially inducing biases in climate reconstructions and forest growth projections. Little is known about whether and to what extent environmental conditions, species, and model type and resolution affect the occurrence and magnitude of non-stationarity. To systematically assess potential drivers of non-stationarity, we compiled tree-ring width chronologies of two conifer species, Picea abies and Pinus sylvestris, distributed across cold, dry, and mixed climates. We analyzed 147 sites across the Europe including the distribution margins of these species as well as moderate sites. We calibrated four numerical models (linear vs. non-linear, daily vs. monthly resolution) to simulate growth chronologies based on temperature and soil moisture data. Climate-growth models were tested in independent verification periods to quantify their non-stationarity, which was assessed based on bootstrapped transfer function stability tests. The degree of non-stationarity varied between species, site climatic conditions, and models. Chronologies of P. sylvestris showed stronger non-stationarity compared with Picea abies stands with a high degree of stationarity. Sites with mixed climatic signals were most affected by non-stationarity compared with sites sampled at cold and dry species distribution margins. Moreover, linear models with daily resolution exhibited greater non-stationarity compared with monthly-resolved non-linear models. We conclude that non-stationarity in climate-growth responses is a multifactorial phenomenon driven by the interaction of site climatic conditions, tree species, and methodological features of the modeling approach. Given the existence of multiple drivers and the frequent occurrence of non-stationarity, we recommend that temporal non-stationarity rather than stationarity should be considered as the baseline model of climate-growth response for temperate forests.

Tree growth influenced by warming winter climate and summer moisture availability in northern temperate forests.

The role of future forests in global biogeochemical cycles will depend on how different tree species respond to climate. Interpreting the response of forest growth to climate change requires an understanding of the temporal and spatial patterns of seasonal climatic influences on the growth of common tree species. We constructed a new network of 310 tree-ring width chronologies from three common tree species (Quercus robur, Pinus sylvestris and Fagus sylvatica) collected for different ecological, management and climate purposes in the south Baltic Sea region at the border of three bioclimatic zones (temperate continental, oceanic, southern boreal). The major climate factors (temperature, precipitation, drought) affecting tree growth at monthly and seasonal scales were identified. Our analysis documents that 20th century Scots pine and deciduous species growth is generally controlled by different climate parameters, and that summer moisture availability is increasingly important for the growth of deciduous species examined. We report changes in the influence of winter climate variables over the last decades, where a decreasing influence of late winter temperature on deciduous tree growth and an increasing influence of winter temperature on Scots pine growth was found. By comparing climate-growth responses for the 1943-1972 and 1973-2002 periods and characterizing site-level growth response stability, a descriptive application of spatial segregation analysis distinguished sites with stable responses to dominant climate parameters (northeast of the study region), and sites that collectively showed unstable responses to winter climate (southeast of the study region). The findings presented here highlight the temporally unstable and nonuniform responses of tree growth to climate variability, and that there are geographical coherent regions where these changes are similar. Considering continued climate change in the future, our results provide important regional perspectives on recent broad-scale climate-growth relationships for trees across the temperate to boreal forest transition around the south Baltic Sea.

Incorporating high-resolution climate, remote sensing and topographic data to map annual forest growth in central and eastern Europe.

To enhance our understanding of forest carbon sequestration, climate change mitigation and drought impact on forest ecosystems, the availability of high-resolution annual forest growth maps based on tree-ring width (TRW) would provide a significant advancement to the field. Site-specific characteristics, which can be approximated by high-resolution Earth observation by satellites (EOS), emerge as crucial drivers of forest growth, influencing how climate translates into tree growth. EOS provides information on surface reflectance related to forest characteristics and thus can potentially improve the accuracy of forest growth models based on TRW. Through the modelling of TRW using EOS, climate and topography data, we showed that species-specific models can explain up to 52 % of model variance (Quercus petraea), while combining different species results in relatively poor model performance (R2 = 13 %). The integration of EOS into models based solely on climate and elevation data improved the explained variance by 6 % on average. Leveraging these insights, we successfully generated a map of annual TRW for the year 2021. We employed the area of applicability (AOA) approach to delineate the range in which our models are deemed valid. The calculated AOA for the established forest-type models was 73 % of the study region, indicating robust spatial applicability. Notably, unreliable predictions predominantly occurred in the climate margins of our dataset. In conclusion, our large-scale assessment underscores the efficacy of combining climate, EOS and topographic data to develop robust models for mapping annual TRW. This research not only fills a critical void in the current understanding of forest growth dynamics but also highlights the potential of integrated data sources for comprehensive ecosystem assessments.

Compression wood has a minor effect on the climate signal in tree-ring stable isotope records of montane Norway spruce.

Compression wood (CW) is a common tissue present in the trunk, branches and roots of mechanically stressed coniferous trees. Its main role is to increase the mechanical strength and regain the vertical orientation of a leaning stem. Compression wood is thought to influence the climate signal in different tree-ring measures. Hence trees containing CW are mostly excluded from tree-ring studies reconstructing past climate variability. There is a large gap of systematic work testing the potential effect of CW on the strength of the climate signal in different tree-ring parameters, especially stable isotope records. Here we test for the first time the effect of CW contained in montane Norway spruce (Picea abies L. Karst) on both δ13C and δ18O tree-ring cellulose records by analyzing compression and opposite wood radii from several disturbed trees together with samples from undisturbed reference trees. We selected four trees tilted by geomorphic processes that were felled by wind and four undisturbed reference trees in the Tatra Mountains, Poland. We qualitatively classified the strength of CW using wood cell anatomical characteristics (tracheid shape, cell wall thickness and presence of intercellular spaces). Then we developed tree-ring width and δ13C and δ18O chronologies from the CW radii, from the opposite radii of the tilted trees and from the reference radii. We tested the effect of CW on tree-ring cellulose δ13C and δ18O variability and on the climate signal strength. We found only minor differences in the means of δ13C and δ18O of compression (δ13C: -22.81‰, δ18O: 28.29‰), opposite (δ13C: -23.02‰; δ18O: 28.05‰) and reference (δ13C: -22.78‰; δ18O: 27.61‰) radii. The statistical relationships between climate variables, δ13C and δ18O, remained consistent among all chronologies. Our findings suggest that moderately tilted trees containing CW can be used to reconstruct past geomorphic activity and for stable isotope-based dendroclimatology.

Growth responses to climate in a multi-species tree-ring network in the Western Carpathian Tatra Mountains, Poland and Slovakia.

We analyzed growth responses to climate of 24 tree-ring width and four maximum latewood density chronologies from the greater Tatra region in Poland and Slovakia. This network comprises 1183 ring-width and 153 density measurement series from four conifer species (Picea abies (L.) Karst., Larix decidua Mill., Abies alba (L.) Karst., and Pinus mugo (L.)) between 800 and 1550 m a.s.l. Individual spline detrending was used to retain annual to multi-decadal scale climate information in the data. Twentieth century temperature and precipitation data from 16 grid-boxes covering the 48-50 degrees N and 19-21 degrees E region were used for comparison. The network was analyzed to assess growth responses to climate as a function of species, elevation, parameter, frequency and site ecology. Twenty ring-width chronologies significantly correlated (P<0.05) with June-July temperatures, whereas the latewood density chronologies were correlated with the April-September temperatures. Climatic effects of the previous-year summer generally did not significantly influence ring formation, whereas site elevation and frequency of growth variations (i.e., inter-annual and decadal) were significant variables in explaining growth response to climate. Response to precipitation increased with decreasing elevation. Correlations between summer temperatures and annual growth rates were lower for Larix decidua than for Picea abies. Principal component analysis identified five dominant eigenvectors that express somewhat contrasting climatic signals. The first principal component contained highest loadings from 11 Picea abies ring-width chronologies and one Pinus mugo ring-width chronology and explained 42% of the network's variance. The mean of these 12 high-elevation chronologies was significantly correlated at 0.62 with June-July temperatures, whereas the mean of three latewood density chronologies, which loaded most strongly on the fourth principal component, significantly correlated at 0.69 with April-September temperatures (P<0.001 over the 1901-2002 period in both cases). These groupings allow for a robust estimation of June-July (1661-2004) and April-September (1709-2004) temperatures, respectively. Comparison with reconstructions from the Alps and Central Europe supports the general rule of the dominant influence of growing season temperature on high-elevation forest growth.