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Dendroclimatology offers the unique opportunity to reconstruct past climate at annual resolution and wood from historical buildings can be used to extend such information back in time up to several millennia. However, the varying and often unclear origin of timbers affects the climate sensitivity of individual tree‐ring samples. Here, we compare tree‐ring width and density of 143 living larch (Larix decidua Mill.) trees at seven sites along an elevational transect from 1400 to 2200 m asl and 99 historical tree‐ring series to parametrize state‐of‐the‐art classification models for the European Alps. To achieve geographical provenance of the historical series, nine different supervised machine learning algorithms are trained and tested in their capability to solve our classification problem. Based on this assessment, we consider a tree‐ring density‐based and a tree‐ring width‐based dataset for model building. For each of these datasets, a general not species‐related model and a larch‐specific model including the cyclic larch budmoth influence are built. From the nine tested machine learning algorithms, Extreme Gradient Boosting showed the best performance. The density‐based models outperform the ring‐width models with the larch‐specific density model reaching the highest skill (f1 score = 0.8). The performance metrics reveal that the larch‐specific density model also performs best within individual sites and particularly in sites above 2000 m asl, which show the highest temperature sensitivities. The application of the specific density model for larch allows the historical series to be assigned with high confidence to a particular elevation within the valley. The procedure can be applied to other provenance studies using multiple tree growth characteristics. The novel approach of building machine learning models based on tree‐ring density features allows to omit a common period between reference and historical data for finding the provenance of relict wood and will therefore help to improve millennium‐length climate reconstructions.

Pinus tabulaeformis ring widths were used to reconstruct mean Palmer Drought Severity Indices (PDSIs) from May to July for each of the past 283 years for Kongtong Mountain, China. A calibration model for the period from 1940 to 2005 explains 66.4% (or 65.9% after adjusting for the loss of the degrees of freedom) of the actual PDSI variance. The reconstructed Kongtong Mountain PDSIs could be representative of the moisture conditions of the entire Loess Plateau. The reconstruction captures a severe 1927–1930 drought event that was widespread across all of northern China. After 11‐year moving average, the reconstructed Kongtong PDSI was found to compare well with other tree ring‐based temperature reconstructions from both Huanglong (in the eastern part of the Chinese Loess Plateau) and Hokkaido, Japan. This result indicates that high temperatures may be a major contributor to the severity of dryness at low frequencies. Significant 93.33‐year and approximate 2‐year cycles were observed in the Kongtong tree ring chronology. Key Points May‐July PDSI was reconstructed for Kongtong, China using tree rings The ring‐width series can also be regarded as a temperature proxy It can be compared with tree‐ring‐based‐emperature reconstructions

Climatic change will affect elevational vegetation distribution because vegetation distribution is related to thermal conditions. However, how elevational species distributions are determined by biotic and abiotic factors is not clear. The long‐term plot census along an elevational gradient is indispensable to clarify mechanisms of elevational distribution of tree species. Two congeneric conifers, the less shade‐tolerant Abies veitchii and shade‐tolerant A. mariesii, dominate at low and high elevations, respectively, in the subalpine zone in Japan. This study investigated the population dynamics of the two species at three elevations (low, middle, high) for 13 years to examine why the two species dominated the different elevations from the viewpoints of competition and disturbance. This study showed that growth and survival rates were not highest at the most dominant elevations for each species. At the high elevation where A. mariesii dominated and small disturbances frequently occurred, the recruitment rate of A. mariesii was highest among the three elevations and that of A. veitchii was largely decreased by tree competition. However, A. veitchii was dominant earlier than A. mariesii at the low elevation after large disturbances by the high growth rate of individual trees. Therefore, A. mariesii was superior to A. veitchii at the high elevation because of its high recruitment rate and large reduction of recruitment of A. veitchii due to competition, while A. veitchii was superior to A. mariesii at the low elevation after large disturbances because of higher growth rate than A. mariesii. It is suggested that the elevational distributions of the two species were determined by elevational changes in population dynamics in relation to competition and disturbance. Long‐term observational studies of forest dynamics among various elevations are indispensable to predict the effects of climatic change on vegetation distribution. Climatic change will affect elevational vegetation distribution because vegetation distribution relates to thermal conditions. Two congeneric conifers, less shade‐tolerant Abies veitchii and shade‐tolerant A. mariesii dominate at low and high elevations, respectively, in the subalpine zone, Japan. This study showed that the elevational distributions of the two species were determined by elevational changes in regeneration traits in relation to competition and disturbance.

Interannual variability of wood density – an important plant functional trait and environmental proxy – in conifers is poorly understood. We therefore explored the anatomical basis of density. We hypothesized that earlywood density is determined by tracheid size and latewood density by wall dimensions, reflecting their different functional tasks. To determine general patterns of variability, density parameters from 27 species and 349 sites across the Northern Hemisphere were correlated to tree-ring width parameters and local climate. We performed the same analyses with density and width derived from anatomical data comprising two species and eight sites. The contributions of tracheid size and wall dimensions to density were disentangled with sensitivity analyses. Notably, correlations between density and width shifted from negative to positive moving from earlywood to latewood. Temperature responses of density varied intraseasonally in strength and sign. The sensitivity analyses revealed tracheid size as the main determinant of earlywood density, while wall dimensions become more influential for latewood density. Our novel approach of integrating detailed anatomical data with large-scale tree-ring data allowed us to contribute to an improved understanding of interannual variations of conifer growth and to illustrate how conifers balance investments in the competing xylem functions of hydraulics and mechanical support.

Land carbon cycle components in an Earth system model (ESM) play a crucial role in the projections of forest ecosystem responses to climate/environmental changes. Evaluating models from the viewpoint of observations is essential for an improved understanding of model performance and for identifying uncertainties in their outputs. Herein, we evaluated the land net primary production (NPP) for circumboreal forests simulated with 10 ESMs in Phase 5 of the Coupled Model Intercomparison Project by comparisons with observation‐based indexes for forest productivity, namely, the composite version 3G of the normalized difference vegetation index (NDVI3g) and tree‐ring width index (RWI). These indexes show similar patterns in response to past climate change over the forests, i.e., a one‐year time lag response and smaller positive responses to past climate changes in comparison with the land NPP simulated by the ESMs. The latter showed overly positive responses to past temperature and/or precipitation changes in comparison with the NDVI3g and RWI. These results indicate that ESMs may overestimate the future forest NPP of circumboreal forests (particularly for inland dry regions, such as inner Alaska and Canada, and eastern Siberia, and for hotter, southern regions, such as central Europe) under the expected increases in both average global temperature and precipitation, which are common to all current ESMs.

Tree-ring (TR) observations provide important data on long-term forest dynamics and their underlying ecophysiological mechanisms. To elucidate the seasonal link between photosynthetic carbon acquisition and TR growth, we analyzed the correlation between observed TR data (carbon sink) and model-estimated net primary production (NPP; carbon source). Temporal trends of the TR–NPP correlation over the last century were also analyzed to identify influences of past climate changes. We used TR data from Picea glehnii at seven sites on Hokkaido Island, Japan, which were obtained from the International Tree-Ring Data Bank. At each site, NPP was estimated using the Vegetation Integrative Simulator for Trace gases model, which was driven by long-term (1900–2010) meteorological data. Site-mean tree-ring width index (TRWI) chronologies were analyzed to reveal any relationship with the current or previous year’s annual or monthly NPP. We found moderate to strong correlations between TRWIs and model-estimated monthly NPP from April to June, especially in June of the current year, but no clear spatial trend was observed. During the twentieth century, the TRWI–NPP correlation increased for February, March, April, and July NPP of the current year and for October NPP of the previous year. Ecophysiologically, the period from April to June corresponds to the season when tree cambial cells are formed in the study area. Our findings suggest that photosynthate produced during this cambial growth season is allocated to stem growth and that this source allocation season has become longer due to past environmental changes.

We present two new millennium-long tree-ring oxygen isotope chronologies for central and northern Japan, based on 9693 annually resolved measurements of tree-ring oxygen isotopes from 39 unearthed samples consisting mainly of Japanese cedar (Cryptomeria japonica). These chronologies were developed through cross-dating of tree-ring widths and δ18O data from multiple samples covering the periods 2349–1009 BCE (1341 yr) and 1412–466 BCE (947 yr) for central and northern Japan, respectively. In combination with our published chronology for central Japan, the tree-ring δ18O dataset currently available covers the past 4354 yr (2349 BCE to 2005 CE), which represents the longest annually resolved tree-ring δ18O dataset for Asia. Furthermore, the high-resolution temporal record of 14C contents independently developed by Sakurai et al. (2020) was reproduced by our 14C measurements of earlywood and latewood in annual rings for the period 667–660 BCE.

Tree‐ring‐width chronology of Betula ermanii was developed at the timberline (2,400 m a.s.l.) on Mount Norikura in central Japan, and climatic factors affecting the tree‐ring width of B. ermanii were examined. Three monthly climatic data (mean temperature, insolation duration, and sum of precipitation) were used for the analysis. The tree‐ring width of B. ermanii was negatively correlated with the December and January temperatures and with the January precipitation prior to the growth. However, why high temperatures and heavy snow in winter had negative effects on the growth of B. ermanii is unknown. The tree‐ring width was positively correlated with summer temperatures during June–August of the current year. The tree‐ring width was also positively correlated with the insolation duration in July of the current year. In contrast, the tree‐ring width was negatively correlated with summer precipitation during July–September of the current year. However, these negative correlations of summer precipitation do not seem to be independent of temperature and insolation duration, i.e., substantial precipitation reduces the insolation duration and temperature. Therefore, it is suggested that significant insolation duration and high temperature due to less precipitation in summer of the current year increase the radial growth of B. ermanii at the timberline. The results were also compared with those of our previous study conducted at the lower altitudinal limit of B. ermanii (approximately 1,600 m a.s.l.) on Mount Norikura. This study suggests that the climatic factors that increase the radial growth of B. ermanii differ between its upper and lower altitudinal limits.

The long-term relationship between temperature and hydroclimate has remained uncertain due to the short length of instrumental measurements and inconsistent results from climate model simulations. This lack of understanding is particularly critical with regard to projected drought and flood risks. Here we assess warm-season co-variability patterns between temperature and hydroclimate over Europe back to 850 CE using instrumental measurements, tree-ring based reconstructions, and climate model simulations. We find that the temperature-hydroclimate relationship in both the instrumental and reconstructed data turns more positive at lower frequencies, but less so in model simulations, with a dipole emerging between positive (warm and wet) and negative (warm and dry) associations in northern and southern Europe, respectively. Compared to instrumental data, models reveal a more negative co-variability across all timescales, while reconstructions exhibit a more positive co-variability. Despite the observed differences in the temperature-hydroclimate co-variability patterns in instrumental, reconstructed and model simulated data, we find that all data types share relatively similar phase-relationships between temperature and hydroclimate, indicating the common influence of external forcing. The co-variability between temperature and soil moisture in the model simulations is overestimated, implying a possible overestimation of temperature-driven future drought risks.

Key Message The automatic detection of tree-ring boundaries and other anatomical features using image analysis has progressed substantially over the past decade with advances in machine learning and imagery technology, as well as increasing demands from the dendrochronology community. This paper presents a publicly available dataset of 64 annotated images of transverse sections of commercially grown Pinus taeda L. trees from northern Uruguay, presenting 17 to 24 annual rings. The collection contains several challenging features for automatic ring detection, including illumination and surface preparation variation, fungal infection (blue stains), knot formation, missing bark or interruptions in outer rings, and radial cracking. This dataset can be used to develop and test automatic tree ring detection algorithms. The dataset presented here was used to develop the Cross-Section Tree-Ring Detection (CS-TRD) method, an open-source automated ring-detection algorithm for cross-sectioned images. Dataset access at https://doi.org/10.5281/zenodo.15110647 . Access to the metadata describing the data set:  https://metadata-afs.nancy.inra.fr/geonetwork/srv/fre/catalog.search#/metadata/5fdbd411-9ae1-4ce6-8ef0-cdfa2fbd7a6a .