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.

Dendrometers challenge the 'moon wood concept' by elucidating the absence of lunar cycles in tree stem radius oscillation.

Wood is a sustainable natural resource and an important global commodity. According to the 'moon wood theory', the properties of wood, including its growth and water content, are believed to oscillate with the lunar cycle. Despite contradicting our current understanding of plant functioning, this theory is commonly exploited for marketing wooden products. To examine the moon wood theory, we applied a wavelet power transformation to series of 2,000,000 hourly stem radius records from dendrometers. We separated the influence of 74 consecutive lunar cycles and meteorological conditions on the stem variation of 62 trees and six species. We show that the dynamics of stem radius consist of overlapping oscillations with periods of 1 day, 6 months, and 1 year. These oscillations in stem dimensions were tightly coupled to oscillations in the series of air temperature and vapour pressure deficit. By contrast, we revealed no imprint of the lunar cycle on the stem radius variation of any species. We call for scepticism towards the moon wood theory, at least as far as the stem water content and radial growth are concerned. We foresee that similar studies employing robust scientific approaches will be increasingly needed in the future to cope with misleading concepts.

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.

Tree ring segmentation using UNEt TRansformer neural network on stained microsections for quantitative wood anatomy.

Forests are critical in the terrestrial carbon cycle, and the knowledge of their response to ongoing climate change will be crucial for determining future carbon fluxes and climate trajectories. In areas with contrasting seasons, trees form discrete annual rings that can be assigned to calendar years, allowing to extract valuable information about how trees respond to the environment. The anatomical structure of wood provides highly-resolved information about the reaction and adaptation of trees to climate. Quantitative wood anatomy helps to retrieve this information by measuring wood at the cellular level using high-resolution images of wood micro-sections. However, whereas large advances have been made in identifying cellular structures, obtaining meaningful cellular information is still hampered by the correct annual tree ring delimitation on the images. This is a time-consuming task that requires experienced operators to manually delimit ring boundaries. Classic methods of automatic segmentation based on pixel values are being replaced by new approaches using neural networks which are capable of distinguishing structures, even when demarcations require a high level of expertise. Although neural networks have been used for tree ring segmentation on macroscopic images of wood, the complexity of cell patterns in stained microsections of broadleaved species requires adaptive models to accurately accomplish this task. We present an automatic tree ring boundary delineation using neural networks on stained cross-sectional microsection images from beech cores. We trained a UNETR, a combined neural network of UNET and the attention mechanisms of Visual Transformers, to automatically segment annual ring boundaries. Its accuracy was evaluated considering discrepancies with manual segmentation and the consequences of disparity for the goals of quantitative wood anatomy analyses. In most cases (91.8%), automatic segmentation matched or improved manual segmentation, and the rate of vessels assignment to annual rings was similar between the two categories, even when manual segmentation was considered better. The application of convolutional neural networks-based models outperforms human operator segmentations when confronting ring boundary delimitation using specific parameters for quantitative wood anatomy analysis. Current advances on segmentation models may reduce the cost of massive and accurate data collection for quantitative wood anatomy.

Genetic basis of growth reaction to drought stress differs in contrasting high-latitude treeline ecotones of a widespread conifer.

Climate change is increasing the frequency and intensity of drought events in many boreal forests. Trees are sessile organisms with a long generation time, which makes them vulnerable to fast climate change and hinders fast adaptations. Therefore, it is important to know how forests cope with drought stress and to explore the genetic basis of these reactions. We investigated three natural populations of white spruce (Picea glauca) in Alaska, located at one drought-limited and two cold-limited treelines with a paired plot design of one forest and one treeline plot. We obtained individual increment cores from 458 trees and climate data to assess dendrophenotypes, in particular the growth reaction to drought stress. To explore the genetic basis of these dendrophenotypes, we genotyped the individual trees at 3000 single nucleotide polymorphisms in candidate genes and performed genotype-phenotype association analysis using linear mixed models and Bayesian sparse linear mixed models. Growth reaction to drought stress differed in contrasting treeline populations. Therefore, the populations are likely to be unevenly affected by climate change. We identified 40 genes associated with dendrophenotypic traits that differed among the treeline populations. Most genes were identified in the drought-limited site, indicating comparatively strong selection pressure of drought-tolerant phenotypes. Contrasting patterns of drought-associated genes among sampled sites and in comparison to Canadian populations in a previous study suggest that drought adaptation acts on a local scale. Our results highlight genes that are associated with wood traits which in turn are critical for the establishment and persistence of future forests under climate change.

Climate-change-driven growth decline of European beech forests.

The growth of past, present, and future forests was, is and will be affected by climate variability. This multifaceted relationship has been assessed in several regional studies, but spatially resolved, large-scale analyses are largely missing so far. Here we estimate recent changes in growth of 5800 beech trees (Fagus sylvatica L.) from 324 sites, representing the full geographic and climatic range of species. Future growth trends were predicted considering state-of-the-art climate scenarios. The validated models indicate growth declines across large region of the distribution in recent decades, and project severe future growth declines ranging from -20% to more than -50% by 2090, depending on the region and climate change scenario (i.e. CMIP6 SSP1-2.6 and SSP5-8.5). Forecasted forest productivity losses are most striking towards the southern distribution limit of Fagus sylvatica, in regions where persisting atmospheric high-pressure systems are expected to increase drought severity. The projected 21st century growth changes across Europe indicate serious ecological and economic consequences that require immediate forest adaptation.

Limitation by vapour pressure deficit shapes different intra-annual growth patterns of diffuse- and ring-porous temperate broadleaves.

Understanding the effects of temperature and moisture on radial growth is vital for assessing the impacts of climate change on carbon and water cycles. However, studies observing growth at sub-daily temporal scales remain scarce. We analysed sub-daily growth dynamics and its climatic drivers recorded by point dendrometers for 35 trees of three temperate broadleaved species during the years 2015-2020. We isolated irreversible growth driven by cambial activity from the dendrometer records. Next, we compared the intra-annual growth patterns among species and delimited their climatic optima. The growth of all species peaked at air temperatures between 12 and 16°C and vapour pressure deficit (VPD) below 0.1 kPa. Acer pseudoplatanus and Fagus sylvatica, both diffuse-porous, sustained growth under suboptimal VPD. Ring-porous Quercus robur experienced a steep decline of growth rates with reduced air humidity. This resulted in multiple irregular growth peaks of Q. robur during the year. By contrast, the growth patterns of the diffuse-porous species were always right-skewed unimodal with a peak in June between day of the year 150-170. Intra-annual growth patterns are shaped more by VPD than temperature. The different sensitivity of radial growth to VPD is responsible for unimodal growth patterns in both diffuse-porous species and multimodal growth pattern in Q. robur.

Direct and Indirect Effects of Environmental Limitations on White Spruce Xylem Anatomy at Treeline.

Treeline ecosystems are of great scientific interest to study the effects of limiting environmental conditions on tree growth. However, tree growth is multidimensional, with complex interactions between height and radial growth. In this study, we aimed to disentangle effects of height and climate on xylem anatomy of white spruce [Picea glauca (Moench) Voss] at three treeline sites in Alaska; i.e., one warm and drought-limited, and two cold, temperature-limited. To analyze general growth differences between trees from different sites, we used data on annual ring width, diameter at breast height (DBH), and tree height. A representative subset of the samples was used to investigate xylem anatomical traits. We then used linear mixed-effects models to estimate the effects of height and climatic variables on our study traits. Our study showed that xylem anatomical traits in white spruce can be directly and indirectly controlled by environmental conditions: hydraulic-related traits seem to be mainly influenced by tree height, especially in the earlywood. Thus, they are indirectly driven by environmental conditions, through the environment's effects on tree height. Traits related to mechanical support show a direct response to environmental conditions, mainly temperature, especially in the latewood. These results highlight the importance of assessing tree growth in a multidimensional way by considering both direct and indirect effects of environmental forcing to better understand the complexity of tree growth responses to the environment.

Mask, Train, Repeat! Artificial Intelligence for Quantitative Wood Anatomy.

The recent developments in artificial intelligence have the potential to facilitate new research methods in ecology. Especially Deep Convolutional Neural Networks (DCNNs) have been shown to outperform other approaches in automatic image analyses. Here we apply a DCNN to facilitate quantitative wood anatomical (QWA) analyses, where the main challenges reside in the detection of a high number of cells, in the intrinsic variability of wood anatomical features, and in the sample quality. To properly classify and interpret features within the images, DCNNs need to undergo a training stage. We performed the training with images from transversal wood anatomical sections, together with manually created optimal outputs of the target cell areas. The target species included an example for the most common wood anatomical structures: four conifer species; a diffuse-porous species, black alder (Alnus glutinosa L.); a diffuse to semi-diffuse-porous species, European beech (Fagus sylvatica L.); and a ring-porous species, sessile oak (Quercus petraea Liebl.). The DCNN was created in Python with Pytorch, and relies on a Mask-RCNN architecture. The developed algorithm detects and segments cells, and provides information on the measurement accuracy. To evaluate the performance of this tool we compared our Mask-RCNN outputs with U-Net, a model architecture employed in a similar study, and with ROXAS, a program based on traditional image analysis techniques. First, we evaluated how many target cells were correctly recognized. Next, we assessed the cell measurement accuracy by evaluating the number of pixels that were correctly assigned to each target cell. Overall, the "learning process" defining artificial intelligence plays a key role in overcoming the issues that are usually manually solved in QWA analyses. Mask-RCNN is the model that better detects which are the features characterizing a target cell when these issues occur. In general, U-Net did not attain the other algorithms' performance, while ROXAS performed best for conifers, and Mask-RCNN showed the highest accuracy in detecting target cells and segmenting lumen areas of angiosperms. Our research demonstrates that future software tools for QWA analyses would greatly benefit from using DCNNs, saving time during the analysis phase, and providing a flexible approach that allows model retraining.

Population structure and the influence of microenvironment and genetic similarity on individual growth at Alaskan white spruce treelines.

Knowledge on the adaptation of trees to rapid environmental changes is essential to preserve forests and their ecosystem services under climate change. Treeline populations are particularly suitable for studying adaptation processes in trees, as environmental stress together with reduced gene flow can enhance local adaptation. We investigated white spruce (Picea glauca) populations in Alaska on one moisture-limited and two cold-limited treeline sites with a paired plot design of one forest and one treeline population each, resulting in six plots. Additionally, one forest plot in the middle of the distribution range complements the study design. We combined spatial, climatic and dendrochronological data with neutral genetic marker of 2203 trees to investigate population genetic structure and drivers of tree growth. We used several individual-based approaches including random slope mixed-effects models to test the influence of genetic similarity and microenvironment on growth performance. A high degree of genetic diversity was found within each of the seven plots associated with high rates of gene flow. We discovered a low genetic differentiation between the three sites which was better explained by geographic distances than by environmental differences, indicating genetic drift as the main driver of population differentiation. Our findings indicated that microenvironmental features had an overall larger influence on growth performances than genetic similarity among individuals. The effects of climate on growth differed between sites but were smaller than the effect of tree size. Overall, our results suggest that the high genetic diversity of white spruce may result in a wider range of phenotypes which enhances the efficiency of selection when the species is facing rapid climatic changes. In addition, the large intra-individual variability in growth responses may indicate the high phenotypic plasticity of white spruce which can buffer short-term environmental changes and, thus, allow enduring the present changing climate conditions.

Global fading of the temperature-growth coupling at alpine and polar treelines.

Climate warming is expected to positively alter upward and poleward treelines which are controlled by low temperature and a short growing season. Despite the importance of treelines as a bioassay of climate change, a global field assessment and posterior forecasting of tree growth at annual scales is lacking. Using annually resolved tree-ring data located across Eurasia and the Americas, we quantified and modeled the relationship between temperature and radial growth at treeline during the 20th century. We then tested whether this temperature-growth association will remain stable during the 21st century using a forward model under two climate scenarios (RCP 4.5 and 8.5). During the 20th century, growth enhancements were common in most sites, and temperature and growth showed positive trends. Interestingly, the relationship between temperature and growth trends was contingent on tree age suggesting biogeographic patterns in treeline growth are contingent on local factors besides climate warming. Simulations forecast temperature-growth decoupling during the 21st century. The growing season at treeline is projected to lengthen and growth rates would increase and become less dependent on temperature rise. These forecasts illustrate how growth may decouple from climate warming in cold regions and near the margins of tree existence. Such projected temperature-growth decoupling could impact ecosystem processes in mountain and polar biomes, with feedbacks on climate warming.

Growth and Wood Trait Relationships of Alnus glutinosa in Peatland Forest Stands With Contrasting Water Regimes.

Human-driven peatland drainage has occurred in Europe for centuries, causing habitat degradation and leading to the emission of greenhouse gases. As such, in the last decades, there has been an increase in policies aiming at restoring these habitats through rewetting. Alder (Alnus glutinosa L.) is a widespread species in temperate forest peatlands with a seemingly high waterlogging tolerance. Yet, little is known about its specific response in growth and wood traits relevant for tree functioning when dealing with changing water table levels. In this study, we investigated the effects of rewetting and extreme flooding on alder growth and wood traits in a peatland forest in northern Germany. We took increment cores from several trees at a drained and a rewetted stand and analyzed changes in ring width, wood density, and xylem anatomical traits related to the hydraulic functioning, growth, and mechanical support for the period 1994-2018. This period included both the rewetting action and an extreme flooding event. We additionally used climate-growth and climate-density correlations to identify the stand-specific responses to climatic conditions. Our results showed that alder growth declined after an extreme flooding in the rewetted stand, whereas the opposite occurred in the drained stand. These changes were accompanied by changes in wood traits related to growth (i.e., number of vessels), but not in wood density and hydraulic-related traits. We found poor climate-growth and climate-density correlations, indicating that water table fluctuations have a stronger effect than climate on alder growth. Our results show detrimental effects on the growth of sudden water table changes leading to permanent waterlogging, but little implications for its wood density and hydraulic architecture. Rewetting actions should thus account for the loss of carbon allocation into wood and ensure suitable conditions for alder growth in temperate peatland forests.

Species-specific effects of thermal stress on the expression of genetic variation across a diverse group of plant and animal taxa under experimental conditions.

Assessing the genetic adaptive potential of populations and species is essential for better understanding evolutionary processes. However, the expression of genetic variation may depend on environmental conditions, which may speed up or slow down evolutionary responses. Thus, the same selection pressure may lead to different responses. Against this background, we here investigate the effects of thermal stress on genetic variation, mainly under controlled laboratory conditions. We estimated additive genetic variance (VA), narrow-sense heritability (h2) and the coefficient of genetic variation (CVA) under both benign control and stressful thermal conditions. We included six species spanning a diverse range of plant and animal taxa, and a total of 25 morphological and life-history traits. Our results show that (1) thermal stress reduced fitness components, (2) the majority of traits showed significant genetic variation and that (3) thermal stress affected the expression of genetic variation (VA, h2 or CVA) in only one-third of the cases (25 of 75 analyses, mostly in one clonal species). Moreover, the effects were highly species-specific, with genetic variation increasing in 11 and decreasing in 14 cases under stress. Our results hence indicate that thermal stress does not generally affect the expression of genetic variation under laboratory conditions but, nevertheless, increases or decreases genetic variation in specific cases. Consequently, predicting the rate of genetic adaptation might not be generally complicated by environmental variation, but requires a careful case-by-case consideration.

Xylem Anatomical Variability in White Spruce at Treeline Is Largely Driven by Spatial Clustering.

The ecological function of boreal forests is challenged by drastically changing climate conditions. Although an increasing number of studies are investigating how climate change is influencing growth and distribution of boreal tree species, there is a lack of studies examining the potential of these species to genetically adapt or phenotypically adjust. Here, we sampled clonally and non-clonally growing white spruce trees (Picea glauca [Moench] Voss) to investigate spatial and genetic effects on tree ring width and on six xylem anatomical traits representing growth, water transport, mechanical support, and wood density. We compared different methods for estimating broad sense heritability (H2) of each trait and we evaluated the effects of spatial grouping and genetic grouping on the xylem anatomical traits with linear models. We found that the three different methods used to estimate H2 were quite robust, showing overall consistent patterns, while our analyses were unsuccessful at fully separating genetic from spatial effects. By evaluating the effect size, we found a significant effect of genetic grouping in latewood density and earlywood hydraulic diameter. However, evaluating model performances showed that spatial grouping was a better predictor than genetic grouping for variance in earlywood density, earlywood hydraulic diameter and growth. For cell wall thickness neither spatial nor genetic grouping was significant. Our findings imply that (1) the variance in the investigated xylem anatomical traits and growth is mainly influenced by spatial clustering (most probably caused by microhabitat conditions), which (2) makes it rather difficult to estimate the heritability of these traits in naturally grown trees in situ. Yet, (3) latewood density and earlywood hydraulic diameter qualified for further analysis on the genetic background of xylem traits and (4) cell wall thickness seems a useful trait to investigate large-scale climatic effects, decoupled from microclimatic, edaphic and genetic influences.

Global assessment of relationships between climate and tree growth.

Tree-ring records provide global high-resolution information on tree-species responses to global change, forest carbon and water dynamics, and past climate variability and extremes. The underlying assumption is a stationary (time-stable), quasi-linear relationship between tree growth and environment, which however conflicts with basic ecological and evolutionary theory. Indeed, our global assessment of the relevant tree-ring literature demonstrates non-stationarity in the majority of tested cases, not limited to specific proxies, environmental parameters, regions or species. Non-stationarity likely represents the general nature of the relationship between tree-growth proxies and environment. Studies assuming stationarity however score two times more citations influencing other fields of science and the science-policy interface. To reconcile ecological reality with the application of tree-ring proxies for climate or environmental estimates, we provide a clarification of the stationarity concept, propose a simple confidence framework for the re-evaluation of existing studies and recommend the use of a new statistical tool to detect non-stationarity in tree-ring proxies. Our contribution is meant to stimulate and facilitate discussion in light of our results to help increase confidence in tree-ring-based climate and environmental estimates for science, the public and policymakers.

Reduced above-ground growth and wood density but increased wood chemical concentrations of Scots pine on relict charcoal hearths.

Deciphering the drivers of tree growth is a central aim of dendroecology. In this context, soil conditions may play a crucial role, since they determine the availability of water and nutrients for trees. Yet, effects of systematically differing soil conditions on tree growth render a marginally studied topic. In this context, relict charcoal hearths (RCH) - a widespread legacy of anthropogenic charcoal production - render a valuable 'natural' experiment to study possible effects of artificially altered soil conditions on tree growth. We hypothesize, that the differing physico-chemical properties of RCH result in differing wood properties if compared to trees growing on unmodified soils. To test this hypothesis, we analyzed tree-growth, wood density, and wood elemental concentrations of Scots pine as well as physico-chemical soil properties. We applied a classic control-treatment design to compare RCH with unmodified soils. Our analyses identified significantly lower above-ground wood production but systematically higher wood elemental concentrations in RCH-trees compared to control trees. Since we could not identify treatment-specific growth patterns, we hypothesize the observed lower above-ground productivity of Scots pine to indicate an increased root-shoot ratio to compensate for a potentially lower plant water availability on RCH-sites. The observed higher wood elemental concentrations likely reflect higher soil elemental concentrations of Fe, Ca, K, and Mn in RCH soils. In conclusion, our study highlights diverse effects of RCH on tree growth and wood properties and strengthens the value of dendro-chemistry to use the tree-ring archive as proxy for soil conditions within a dendro-ecological context.

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.

Moisture-driven shift in the climate sensitivity of white spruce xylem anatomical traits is coupled to large-scale oscillation patterns across northern treeline in northwest North America.

Tree growth at northern treelines is generally temperature-limited due to cold and short growing seasons. However, temperature-induced drought stress was repeatedly reported for certain regions of the boreal forest in northwestern North America, provoked by a significant increase in temperature and possibly reinforced by a regime shift of the pacific decadal oscillation (PDO). The aim of this study is to better understand physiological growth reactions of white spruce, a dominant species of the North American boreal forest, to PDO regime shifts using quantitative wood anatomy and traditional tree-ring width (TRW) analysis. We investigated white spruce growth at latitudinal treeline across a >1,000 km gradient in northwestern North America. Functionally important xylem anatomical traits (lumen area, cell-wall thickness, cell number) and TRW were correlated with the drought-sensitive standardized precipitation-evapotranspiration index of the growing season. Correlations were computed separately for complete phases of the PDO in the 20th century, representing alternating warm/dry (1925-1946), cool/wet (1947-1976) and again warm/dry (1977-1998) climate regimes. Xylem anatomical traits revealed water-limiting conditions in both warm/dry PDO regimes, while no or spatially contrasting associations were found for the cool/wet regime, indicating a moisture-driven shift in growth-limiting factors between PDO periods. TRW reflected only the last shift of 1976/1977, suggesting different climate thresholds and a higher sensitivity to moisture availability of xylem anatomical traits compared to TRW. This high sensitivity of xylem anatomical traits permits to identify first signs of moisture-driven growth in treeline white spruce at an early stage, suggesting quantitative wood anatomy being a powerful tool to study climate change effects in the northwestern North American treeline ecotone. Projected temperature increase might challenge growth performance of white spruce as a key component of the North American boreal forest biome in the future, when drier conditions are likely to occur with higher frequency and intensity.

Removing the no-analogue bias in modern accelerated tree growth leads to stronger medieval drought.

In many parts of the world, especially in the temperate regions of Europe and North-America, accelerated tree growth rates have been observed over the last decades. This widespread phenomenon is presumably caused by a combination of factors like atmospheric fertilization or changes in forest structure and/or management. If not properly acknowledged in the calibration of tree-ring based climate reconstructions, considerable bias concerning amplitudes and trends of reconstructed climatic parameters might emerge or low frequency information is lost. Here we present a simple but effective, data-driven approach to remove the recent non-climatic growth increase in tree-ring data. Accounting for the no-analogue calibration problem, a new hydroclimatic reconstruction for northern-central Europe revealed considerably drier conditions during the medieval climate anomaly (MCA) compared with standard reconstruction methods and other existing reconstructions. This demonstrates the necessity to account for fertilization effects in modern tree-ring data from affected regions before calibrating reconstruction models, to avoid biased results.

Stand basal area and solar radiation amplify white spruce climate sensitivity in interior Alaska: Evidence from carbon isotopes and tree rings.

The negative growth response of North American boreal forest trees to warm summers is well documented and the constraint of competition on tree growth widely reported, but the potential interaction between climate and competition in the boreal forest is not well studied. Because competition may amplify or mute tree climate-growth responses, understanding the role current forest structure plays in tree growth responses to climate is critical in assessing and managing future forest productivity in a warming climate. Using white spruce tree ring and carbon isotope data from a long-term vegetation monitoring program in Denali National Park and Preserve, we investigated the hypotheses that (a) competition and site moisture characteristics mediate white spruce radial growth response to climate and (b) moisture limitation is the mechanism for reduced growth. We further examined the impact of large reproductive events (mast years) on white spruce radial growth and stomatal regulation. We found that competition and site moisture characteristics mediated white spruce climate-growth response. The negative radial growth response to warm and dry early- to mid-summer and dry late summer conditions intensified in high competition stands and in areas receiving high potential solar radiation. Discrimination against 13 C was reduced in warm, dry summers and further diminished on south-facing hillslopes and in high competition stands, but was unaffected by climate in open floodplain stands, supporting the hypothesis that competition for moisture limits growth. Finally, during mast years, we found a shift in current year's carbon resources from radial growth to reproduction, reduced 13 C discrimination, and increased intrinsic water-use efficiency. Our findings highlight the importance of temporally variable and confounded factors, such as forest structure and climate, on the observed climate-growth response of white spruce. Thus, white spruce growth trends and productivity in a warming climate will likely depend on landscape position and current forest structure.