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.

Networking the forest infrastructure towards near real-time monitoring - A white paper.

Forests account for nearly 90 % of the world's terrestrial biomass in the form of carbon and they support 80 % of the global biodiversity. To understand the underlying forest dynamics, we need a long-term but also relatively high-frequency, networked monitoring system, as traditionally used in meteorology or hydrology. While there are numerous existing forest monitoring sites, particularly in temperate regions, the resulting data streams are rarely connected and do not provide information promptly, which hampers real-time assessments of forest responses to extreme climate events. The technology to build a better global forest monitoring network now exists. This white paper addresses the key structural components needed to achieve a novel meta-network. We propose to complement - rather than replace or unify - the existing heterogeneous infrastructure with standardized, quality-assured linking methods and interacting data processing centers to create an integrated forest monitoring network. These automated (research topic-dependent) linking methods in atmosphere, biosphere, and pedosphere play a key role in scaling site-specific results and processing them in a timely manner. To ensure broad participation from existing monitoring sites and to establish new sites, these linking methods must be as informative, reliable, affordable, and maintainable as possible, and should be supplemented by near real-time remote sensing data. The proposed novel meta-network will enable the detection of emergent patterns that would not be visible from isolated analyses of individual sites. In addition, the near real-time availability of data will facilitate predictions of current forest conditions (nowcasts), which are urgently needed for research and decision making in the face of rapid climate change. We call for international and interdisciplinary efforts in this direction.

Accuracy, realism and general applicability of European forest models.

Forest models are instrumental for understanding and projecting the impact of climate change on forests. A considerable number of forest models have been developed in the last decades. However, few systematic and comprehensive model comparisons have been performed in Europe that combine an evaluation of modelled carbon and water fluxes and forest structure. We evaluate 13 widely used, state-of-the-art, stand-scale forest models against field measurements of forest structure and eddy-covariance data of carbon and water fluxes over multiple decades across an environmental gradient at nine typical European forest stands. We test the models' performance in three dimensions: accuracy of local predictions (agreement of modelled and observed annual data), realism of environmental responses (agreement of modelled and observed responses of daily gross primary productivity to temperature, radiation and vapour pressure deficit) and general applicability (proportion of European tree species covered). We find that multiple models are available that excel according to our three dimensions of model performance. For the accuracy of local predictions, variables related to forest structure have lower random and systematic errors than annual carbon and water flux variables. Moreover, the multi-model ensemble mean provided overall more realistic daily productivity responses to environmental drivers across all sites than any single individual model. The general applicability of the models is high, as almost all models are currently able to cover Europe's common tree species. We show that forest models complement each other in their response to environmental drivers and that there are several cases in which individual models outperform the model ensemble. Our framework provides a first step to capturing essential differences between forest models that go beyond the most commonly used accuracy of predictions. Overall, this study provides a point of reference for future model work aimed at predicting climate impacts and supporting climate mitigation and adaptation measures in forests.

The 2018 European heatwave led to stem dehydration but not to consistent growth reductions in forests.

Heatwaves exert disproportionately strong and sometimes irreversible impacts on forest ecosystems. These impacts remain poorly understood at the tree and species level and across large spatial scales. Here, we investigate the effects of the record-breaking 2018 European heatwave on tree growth and tree water status using a collection of high-temporal resolution dendrometer data from 21 species across 53 sites. Relative to the two preceding years, annual stem growth was not consistently reduced by the 2018 heatwave but stems experienced twice the temporary shrinkage due to depletion of water reserves. Conifer species were less capable of rehydrating overnight than broadleaves across gradients of soil and atmospheric drought, suggesting less resilience toward transient stress. In particular, Norway spruce and Scots pine experienced extensive stem dehydration. Our high-resolution dendrometer network was suitable to disentangle the effects of a severe heatwave on tree growth and desiccation at large-spatial scales in situ, and provided insights on which species may be more vulnerable to climate extremes.

Increased wood biomass growth is associated with lower wood density in Quercus petraea (Matt.) Liebl. saplings growing under elevated CO2.

Atmospheric carbon dioxide (CO2) has increased substantially since the industrial revolution began, and physiological responses to elevated atmospheric CO2 concentrations reportedly alter the biometry and wood structure of trees. Additionally, soil nutrient availability may play an important role in regulating these responses. Therefore, in this study, we grew 288 two-year-old saplings of sessile oak (Quercus petraea (Matt.) Liebl.) in lamellar glass domes for three years to evaluate the effects of CO2 concentrations and nutrient supply on above- and belowground biomass, wood density, and wood structure. Elevated CO2 increased above- and belowground biomass by 44.3% and 46.9%, respectively. However, under elevated CO2 treatment, sapling wood density was markedly lower (approximately 1.7%), and notably wider growth rings-and larger, more efficient conduits leading to increased hydraulic conductance-were observed. Moreover, despite the vessels being larger in saplings under elevated CO2, the vessels were significantly fewer (p = 0.023). No direct effects of nutrient supply were observed on biomass growth, wood density, or wood structure, except for a notable decrease in specific leaf area. These results suggest that, although fewer and larger conduits may render the xylem more vulnerable to embolism formation under drought conditions, the high growth rate in sessile oak saplings under elevated CO2 is supported by an efficient vascular system and may increase biomass production in this tree species. Nevertheless, the decreased mechanical strength, indicated by low density and xylem vulnerability to drought, may lead to earlier mortality, offsetting the positive effects of elevated CO2 levels in the future.

Seasonally varying relationship between stem respiration, increment and carbon allocation of Norway spruce trees.

Stem respiration is an important component of an ecosystem's carbon budget. Beside environmental factors, it depends highly on tree energy demands for stem growth. Determination of the relationship between stem growth and stem respiration would help to reveal the response of stem respiration to changing climate, which is expected to substantially affect tree growth. Common measurement of stem radial increment does not record all aspects of stem growth processes, especially those connected with cell wall thickening; therefore, the relationship between stem respiration and stem radial increment may vary depending on the wood cell growth differentiation phase. This study presents results from measurements of stem respiration and increment carried out for seven growing seasons in a young Norway spruce forest. Moreover, rates of carbon allocation to stems were modeled for these years. Stem respiration was divided into maintenance (Rm) and growth respiration (Rg) based upon the mature tissue method. There was a close relationship between Rg and daily stem radial increment (dSRI), and this relationship differed before and after dSRI seasonal maximum, which was around 19 June. Before this date, Rg increased exponentially with dSRI, while after this date logarithmically. This is a result of later maxima of Rg and its slower decrease when compared with dSRI, which is connected with energy demands for cell wall thickening. Rg reached a maxima at the end of June or in July. The maximum of carbon allocation to stem peaked in late summer, when Rg mostly tended to decrease. The overall contribution of Rg to stem CO2 efflux amounted to 46.9% for the growing period from May to September and 38.2% for the year as a whole. This study shows that further deeper analysis of in situ stem growth and stem respiration dynamics is greatly needed, especially with a focus on wood formation on a cell level.

Forest carbon allocation modelling under climate change.

Carbon allocation plays a key role in ecosystem dynamics and plant adaptation to changing environmental conditions. Hence, proper description of this process in vegetation models is crucial for the simulations of the impact of climate change on carbon cycling in forests. Here we review how carbon allocation modelling is currently implemented in 31 contrasting models to identify the main gaps compared with our theoretical and empirical understanding of carbon allocation. A hybrid approach based on combining several principles and/or types of carbon allocation modelling prevailed in the examined models, while physiologically more sophisticated approaches were used less often than empirical ones. The analysis revealed that, although the number of carbon allocation studies over the past 10 years has substantially increased, some background processes are still insufficiently understood and some issues in models are frequently poorly represented, oversimplified or even omitted. Hence, current challenges for carbon allocation modelling in forest ecosystems are (i) to overcome remaining limits in process understanding, particularly regarding the impact of disturbances on carbon allocation, accumulation and utilization of nonstructural carbohydrates, and carbon use by symbionts, and (ii) to implement existing knowledge of carbon allocation into defence, regeneration and improved resource uptake in order to better account for changing environmental conditions.

Ultraviolet radiation modulates C:N stoichiometry and biomass allocation in Fagus sylvatica saplings cultivated under elevated CO2 concentration.

Under the conditions of ongoing climate change, terrestrial ecosystems will be simultaneously exposed to a permanent rise in atmospheric CO2 concentration and increasing variability of such environmental factors as temperature, precipitation, and UV radiation. This will result in numerous interactions. The interactive effects caused by exposure to such multiple environmental factors are not yet well understood. We tested the hypotheses that enhanced UV radiation reduces the stimulatory effect of elevated CO2 concentration on plant biomass production and that it alters biomass allocation in broadleaved European beech (Fagus sylvatica L.) saplings. Our results after 2 years of exposure confirmed interactive effects of CO2 concentration and UV radiation on biomass production, and particularly on biomass allocation to roots and aboveground biomass. The strongest stimulatory effect of elevated CO2 on aboveground biomass and roots was found under ambient UV radiation, while both low and high UV doses reduced this stimulation. Nitrogen content in the roots and the distribution of nitrogen among leaves and roots were also significantly affected by interaction of CO2 concentration and UV radiation. The observed changes in leaf and root C:N stoichiometry were associated with altered morphological traits, and particularly with a change in the proportion of fine roots. As the biomass allocation and especially the proportion of fine roots can play an important role in effective water and nutrient use and acclimation to future climates, it is essential to obtain a deeper understanding of the links between C:N stoichiometry and biomass accumulation.