Dendrometer Data Research Articles

A machine learning approach to fill gaps in dendrometer data

Abstract Key message The machine learning algorithm extreme gradient boosting can be employed to address the issue of long data gaps in individual trees, without the need for additional tree-growth data or climatic variables. Abstract The susceptibility of dendrometer devices to technical failures often makes time-series analyses challenging. Resulting data gaps decrease sample size and complicate time-series comparison and integration. Existing methods either focus on bridging smaller gaps, are dependent on data from other trees or rely on climate parameters. In this study, we test eight machine learning (ML) algorithms to fill gaps in dendrometer data of individual trees in urban and non-urban environments. Among these algorithms, extreme gradient boosting (XGB) demonstrates the best skill to bridge artificially created gaps throughout the growing seasons of individual trees. The individual tree models are suited to fill gaps up to 30 consecutive days and perform particularly well at the start and end of the growing season. The method is independent of climate input variables or dendrometer data from neighbouring trees. The varying limitations among existing approaches call for cross-comparison of multiple methods and visual control. Our findings indicate that ML is a valid approach to fill gaps in individual trees, which can be of particular importance in situations of limited inter-tree co-variance, such as in urban environments.

Phylogenetic Effect on Tree Radial Growth Depends on Drought and Tree Sizes

AbstractTree radial growth is one of the most direct measures of tree performance and is also sensitive to climate. Growth performance is the consequence of the interplay between ecological and evolutionary processes. However, the effect of the evolutionary relatedness among species (i.e., phylogeny) on tree radial growth, especially under stressful conditions, remains largely unknown. Furthermore, there is still no ecological evidence for the influence of phylogeny on tree growth across different tree attributes (i.e., tree diameter variation and tree canopy height) and topographic habitat types. We used Blomberg's K to quantify the tree growth phylogenetic signal (TGPS) using two long‐term dendrometer data sets: one a continuous census of 225 tree species at 3‐month intervals in a tropical forest in southwest China from 2009 to 2017; the other, 12 tree species measured at 6‐month intervals in a temperate forest in Washington State, USA from 2013 to 2019. We found that TGPS values were higher in the temperate forest than in the tropical forest. Precipitation, tree diameter, canopy strata, and habitat types all influenced TGPS values. TGPS values were significantly (p < 0.05) and negatively related to precipitation in Xishuangbanna, and the three of four tree diameter classes in the temperate forest, respectively. Stressful growing conditions arose from either based on low precipitation or among large‐diameter trees competing with each other in the upper canopy led to phylogenetic conservatism in trees' radial growth performance. We conclude that phylogeny is pivotal to understanding the growth response differences among species and their responses to climate variability.

The timing of wood formation in peatland trees as obtained with different approaches

Dendrometers offer valuable insights into how tree growth responds to climatic variables and physiological processes over the course of a year. Yet, their applicability to extremely slow-growing trees, such as those in peatlands, has been limited due to the intricate and slow nature of growth, therefore rendering interpretation of results complex. In this study, we conducted a comprehensive monitoring of tree wood formation in both peatland and mineral soil ecosystems in southern Sweden (58.37 N, 12.17 E, 75 m asl) in 2021 and 2022, using both band and point dendrometers. To verify and validate the dendrometer data, we also sampled microcores every two weeks during both growing seasons. We find that peatland trees grow at approximately 30 % the rate of their neighbors on mineral soils. The onset of growth among peatland trees typically occurs between mid-May and early June, consistently lagging the start of the growing season in trees on mineral soils by one to three weeks. Notably, growth peaks are synchronized across peatland trees and coincide with the summer solstice. Both types of dendrometers exhibit varying degrees of accuracy depending on the phenological stages measured. They perform well in identifying growth onset and peak but are less effective at detecting growth cessation. Point dendrometers demonstrate superior accuracy as they better capture daily irreversible growth increments. In the case of band dendrometers, growth increments are obscured by greater reversible fluctuations in dead bark tissues. However, they remain valuable for tracking the wood phenology of trees with growth rates exceeding 2 mm/year. Based on our results, for an effective tree monitoring in peatlands, we strongly recommend (1) using point dendrometers and (2) removing the dead bark tissues on monitored trees.

Mapping Tree Water Deficit with UAV Thermal Imaging and Meteorological Data

The mapping of forest stands and individual trees affected by drought stress is a crucial step in targeted forest management, aimed at fostering resilient and diverse forests. Unoccupied aerial vehicle (UAV)-based thermal sensing is a promising method for obtaining high-resolution thermal data. However, the reliability of typical low-cost sensors adapted for UAVs is compromised due to various factors, such as internal sensor dynamics and environmental variables, including solar radiation intensity, relative humidity, object emissivity and wind. Additionally, accurately assessing drought stress in trees is a complex task that usually requires laborious and cost-intensive methods, particularly in field settings. In this study, we investigated the feasibility of using the thermal band of the Micasense Altum multispectral sensor, while also assessing the potential for modelling tree water deficit (TWD) through point dendrometers and UAV-derived canopy temperature. Our indoor tests indicated that using a limited number of pixels (< 3) could result in temperature errors exceeding 1 K. However, enlarging the spot-size substantially reduced the mean difference to 0.02 K, validated against leaf temperature sensors. Interestingly, drought-treated (unwatered) leaves exhibited a higher root mean squared error (RMSE) (RMSE = 0.66 K and 0.73 K) than watered leaves (RMSE = 0.55 K and 0.53 K), likely due to lower emissivity of the dry leaves. Comparing field acquisition methods, the mean standard deviation (SD) for tree crown temperature obtained from typical gridded flights was 0.25 K with a maximum SD of 0.59 K (n = 12). In contrast, a close-range hovering method produced a mean SD of 0.09 K and a maximum SD of 0.1 K (n = 8). Modelling the TWD from meteorological and point dendrometer data for the 2021 growth season (n = 2928) yielded an R2 = 0.667 using a generalised additive model (GAM) with vapor pressure deficit (VPD), wind speed, and solar radiation as input features. A point dendrometer lag of one hour was also implemented. When predicting individual tree TWD with UAV-derived tree canopy temperature, relative humidity, and air temperature, an RMSE of 4.92 (μm) and R2 of 0.87 were achieved using a GAM. Implementing leaf-to-air pressure deficit (LVPD) as an input feature resulted in an RMSE of 6.87 (μm) and an R2 of 0.71. This novel single-shot approach demonstrates a promising method to acquire thermal data for the purpose of mapping TWD of beech trees on an individual basis. Further testing and development are imperative, and additional data from drought periods, point dendrometers, and high-resolution meteorological sources are required.

INTRAGRO: A machine learning approach to predict future growth of trees under climate change.

The escalating impact of climate change on global terrestrial ecosystems demands a robust prediction of the trees' growth patterns and physiological adaptation for sustainable forestry and successful conservation efforts. Understanding these dynamics at an intra-annual resolution can offer deeper insights into tree responses under various future climate scenarios. However, the existing approaches to infer cambial or leaf phenological change are mainly focused on certain climatic zones (such as higher latitudes) or species with foliage discolouration during the fall season. In this study, we demonstrated a novel approach (INTRAGRO) to combine intra-annual circumference records generated by dendrometers coupled to the output of climate models to predict future tree growth at intra-annual resolution using a series of supervised and unsupervised machine learning algorithms. INTRAGRO performed well using our dataset, that is dendrometer data of P. roxburghii Sarg. from the subtropical mid-elevation belt of Nepal, with robust test statistics. Our growth prediction shows enhanced tree growth at our study site for the middle and end of the 21st century. This result is remarkable since the predicted growing season by INTRAGRO is expected to shorten due to changes in seasonal precipitation. INTRAGRO's key advantage is the opportunity to analyse changes in trees' intra-annual growth dynamics on a global scale, regardless of the investigated tree species, regional climate and geographical conditions. Such information is important to assess tree species' growth performance and physiological adaptation to growing season change under different climate scenarios.

Effects of competition reduction on intra-annual radial growth of European beech (Fagus sylvatica L.) at stem base and crown base

Key messageIn beech stands, thinning affects growth differently along tree stems, with higher and longer duration increment at stem base than at crown base while unmanaged stands depict opposite patterns.Forest management affects individual tree growth dynamics at different levels of the tree bole. Here, we assessed stem-growth patterns as a function of bole height (stem base and crown base) and competition reduction using high-resolution dendrometer records. We measured radial increments throughout the vegetation periods of 2015 and 2016 in two differently managed European beech (Fagus sylvatica L.) stands in central Germany. In one stand, trees had been repeatedly released from competition while the other had remained unmanaged for about 40 years. To assess different temporal phases of diameter increment, we fitted Weibull growth curves to dendrometer data. Stem basal area and crown base area increments of trees in the managed stand were always higher than in the unmanaged stand. In the managed stand, crown base and stem base monthly diameter increments were highly correlated until July when diameter increment at stem base surpassed the diameter increment at crown base. Conversely, in the unmanaged stand, monthly diameter increment at the stem base was often lower than at crown base. In both stands, diameter growth started earlier at crown base than at stem base. However, stem base growth in the managed stand began earlier and lasted longer than in the unmanaged stand. Our results confirm that competition reduction affects diameter increment along the stem differently than in unmanaged stands and increases growth duration. Future research is needed to test whether different growth patterns and tapers of residual trees in managed and unmanaged stands have implications for biomass and carbon storage modeling.

Why Intra-Annual Density Fluctuations Should Be Formed at Night? Implications for Climate–Growth Relationships in Seasonally Dry Conifer Forests

Trees grow at night, when the vapor pressure deficit (VPD) is low enough. Therefore, intra-annual density fluctuations (IADFs) should be formed when the VPD drops below a certain threshold. This idea is tested by assessing climate-latewood IADF relationships in six conifer species under Mediterranean climate conditions. Hourly climate and dendrometer data were analyzed for years with elevated IADF production in two species (Pinus halepensis, Juniperus thurifera). Lastly, climate–growth relationships were evaluated in two drought-prone sites to assess the relative role of minimum vs. maximum temperatures as growth drivers. Latewood IADF production was positively related to growth rate. IADFs were more abundant when monthly or 10-day long precipitation was high in the late growing season (August and September). According to dendrometer data, growth mainly occurred in early night (20–2 h) and early morning (6–8 h). This growth window corresponded to rainy periods with VPD below a minimum threshold associated with summer storms. Latewood IADFs are produced in response to these wet late-summer conditions, which could be related to bimodal growth. These associations are in line with correlations showing that high minimum (night) rather than maximum (day) temperatures reduce growth. This last idea should be further checked in drought-prone forests using global tree-ring databases.

Climatic influences on intra-annual stem radial variations and xylem formation of Toona ciliata at two Asian tropical forest sites with contrasting soil water availability

Climate extremes will increasingly influence ecosystem productivity of tropical forests, but little is known about their effects on tree stem radial growth, a major component of forest productivity. To analyze the role of climatic drivers and local site differences on tree growth at sub-annual timescales, we studied the timing, magnitude and climatic drivers of stem growth and xylem formation at two tropical forest sites with contrasting soil water availability in southwestern China. We combined high-resolution point dendrometer recordings and microcoring to investigate intra-annual stem radius variation and xylem formation of Toona ciliata over three consecutive years (2018–2020). Stem radial increment of T. ciliata derived from dendrometer data showed distinct seasonal patterns, with growth mainly occurring during March to October. The start day of stem radial growth coincided with the occurrence of the cell enlarging phase, and its end day occurred concomitantly with the cessation of cell enlarging as identified from microcores. Toona ciliata trees at the tropical ravine rainforest site with higher soil water availability showed higher mean annual stem radial increment, higher daily growth rates, and longer duration of xylem productivity than that at the tropical karst forest site. Weekly stem radial growth rates increased with precipitation and air temperature at the wetter ravine rainforest site, while relative humidity had a positive effect at the drier karst forest site. Our findings indicate that drought stress advances and shortens the growing season for T. ciliata. Our study highlights the strong influence of soil water capacity mediating the impact of climate, so response to drought is site-specific, which should be considered in growth models.

Dendrometer measurements of Mediterranean-alpine dwarf shrubs and micro-environmental drivers of plant growth – Dataset from long-term alpine ecosystem research in the Sierra Nevada, Spain (LTAER-ES)

Here, we present measurement data of stem diameter variability of three common woody plants, monitored in the Mediterranean-alpine biome for six consecutive years (2015–2020). These focal species (Astragalus granatensis, Cytisus galianoi, and Genista versicolor) are abundant across the Sierra Nevada mountain chain (Southern Spain) and will potentially be affected by severe future climatic changes predicted for the region, including increased aridification in a warming environment. Understanding their fine-scale radial growth-patterns in relation to local environmental parameters might gain further insights into future vegetational shifts. We therefore used 139 high-resolution dendrometers to continuously monitor specimens along a steep elevational gradient and at varying topographical positions within the heterogeneous topography of the region. Additionally, we measured on-site environmental conditions at each studied site, including soil moisture and soil temperature within the root zone. All data were recorded at hourly resolution and are presented as daily mean values. The dataset was collected as a part of our long-term alpine ecosystem research program (LTAER), which functions as the basis for our recent projects on the use of dendrometer data to better understand the physiological mechanisms and the environmental drivers of the ongoing alpine greening.

A methodological framework to optimize models predicting critical dates of xylem phenology based on dendrometer data

Dendrometer measurements are a frequently used alternative to the laborious and time consuming microcoring to investigate intra-annual growth dynamics of trees. However, since dendrometer data not only comprise cambial growth, but also hydrological fluctuations, both signals need to be disentangled to derive critical dates of xylem phenology from dendrometer data. For this purpose, various approaches can be found in the literature, however a systematic comparison of the different options is still missing. In this study we present a methodological framework to evaluate the accuracy of different mathematical fittings to derive tree-ring phenology from dendrometer data and apply this approach to a data set comprised of three conifer species where high-resolution band dendrometer measurements and microcore sampling have been done in parallel. Based on our study we provide evidence that the most common approaches to derive onset and cessation of xylem cell enlargement from dendrometer data, i.e. applying absolute and relative thresholds to deterministic models fitted to dendrometer data, caused systematic deviations from the reference of xylogenesis observations, but could be improved by small adaptations. The most precise and unbiased predictions of xylem growth phenology were obtained by fitting the three-parameter Gompertz model to the dendrometer data and applying a relative threshold of 3.5% of annual increment to the model predictions for growth onset and an absolute threshold of 4.5 µm day-1 based on the first model derivative for growth cessation. Our framework enables an improved usage of dendrometer data for the prediction of the onset and cessation of xylem cell enlargement, which are important ecological indicators to quantify the effects environmental changes on forest growth and the terrestrial carbon cycle.

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.

Processing and Extraction of Seasonal Tree Physiological Parameters from Stem Radius Time Series

Radial stem size changes, measured with automated dendrometers at intra-daily resolution, offer great potential to link environmental conditions with tree physiology at the seasonal scale. Such measurements need to be time-aligned, cleaned of outliers and shifts, gap-filled and analysed for reversible (water-related) and irreversible (growth-related) fractions to obtain physiologically meaningful data. Therefore, comprehensive tools are needed for reproducible data processing and analytics of dendrometer data. Here we present a transparent method, compiled in the R package treenetproc, to turn raw dendrometer data into clean, physiologically interpretable information, i.e., stem growth, tree water deficit, growth phenological phases, mean daily shrinkage and their respective timings. The removal of errors is facilitated by additional functions and supported with graphical visualizations. To ensure reproducible data handling, the processing parameters and induced changes to the raw data are documented in the output and, thus, are a step towards a standardized processing of automatically measured stem radius time series. We discuss examples, such as the seasonality of growth or the dependence of growth on atmospheric and soil drought. The presented growth and water-related physiological variables at high temporal resolution offer novel physiological insights into the seasonally varying responses of trees to changing environmental conditions.

Dendrometer measurements of arctic-alpine dwarf shrubs and micro-environmental drivers of plant growth - Dataset from long-term alpine ecosystem research in central Norway

Here, we present fine-scale measurements of stem diameter variation from three common arctic-alpine dwarf-shrub species monitored in two mountain regions of Central Norway. All three species (Betula nana, Empetrum nigrum ssp. hermaphroditum, and Phyllodoce caerulea) are abundant within the studied regions and highly important contributors to potential future arctic-alpine vegetation shifts. A profound understanding of their radial growth patterns therefore has the potential to yield crucial information regarding climate-growth relations within these ecosystems. We used high-resolution dendrometers (type DRO) to monitor 120 specimens, taking measurements near the shoot base of one major horizontal stem. Along with the shrub growth measurements, we measured on-site micro-environmental data at each studied site, including shoot zone and root zone temperatures as well as soil moisture. All data were recorded at an hourly scale and are presented as daily mean values. The monitoring period spanned five full years (2015 - 2019), with additional data from 2014 and 2020. Data were collected within one of the most continental climate regions of Europe, the Vågå/Innlandet region, and in the oceanic climate region Geiranger/Møre og Romsdal, spanning a steep climate gradient over just ~100 km horizontal distance. Both study regions are characterized by steep elevational gradients and highly heterogeneous micro-topography. The studied sites were chosen to represent these natural conditions using the transect principle. The collection of our original data is subject of our long-term alpine ecosystem monitoring program since 1991, from which numerous publications function as the basis for a recent project on the use of dendrometer data in alpine ecosystem studies.

Intra-annual diameter growth variation of six common European tree species in pure and mixed stands

Studies of intra-annual growth are particularly useful for understanding tree growth because of their high temporal resolution. This study was performed in Austria and included hourly band dendrometer data of 244 annual tree recordings from six tree species ( (L.) Karst., L., Mill., Mill., L., spp. ( (Matt.) Liebl., L.) sampled on five sites with contrasting site conditions in pure and mixed stands and on trees of different social position. Measurements encompassed 1–7 years. Cumulative diameter increment was modelled by logistic mixed-effects models with random effects at the tree and year level. The results showed large differences in seasonal growth patterns between sites, with a clearly shorter growing season at the drier sites. Species specific response on dry sites could be linked to drought characteristics, whereas response on more humid sites was related to light requirements or successional status. The deciduous trees showed earlier growth culmination and shorter growing periods than the evergreen species. Individual tree growth of spp., , and was positively affected by mixture whereas , and showed no or adverse mixture effects. Mixture effects differed between years and social position. Furthermore, increment culmination was earlier in mixed stands, but shifts were minor. Tree growth differed by social position with dominant trees showing the largest increment and the longest growth duration, with shifts in tree growth patterns due to social position being as large as those between different sites.Picea abiesPinus sylvestrisLarix deciduaAbies albaFagus sylvaticaQuercusQuercus petraeaQuercus roburQuercusP. abiesF. sylvaticaL. deciduaP. sylvestrisA. alba

“dendRoAnalyst”: A tool for processing and analysing dendrometer data

Dendrometers are vital tools for studying the response of trees to intra-annual environmental changes in different temporal resolutions, ranging from hourly, daily to weekly time resolution. Dendrometers are increasingly used in forest management and tree physiological studies. Besides the data analysis, data processing is also challenging, time-consuming and potentially error-prone due to the immense number of measurements generated by self-registering electronic dendrometers. We present the package ‘dendRoAnalyst’ based on R statistical software to process and analyse dendrometer data using various approaches. This package offers algorithms for handling and pre-cleaning of dendrometer data before the application of subsequent data analytical steps. This includes identifying and erasing artefacts in dendrometer datasets not related to actual stem circumference change, identifying data gaps within records, and the possibility of change(s) in temporal resolution. Furthermore, the package can calculate different daily statistics of dendrometer data, including the daily amplitude of tree growth. The package dendRoAnalyst is therefore intended to facilitate researchers with a collection of functions for handling and analysing dendrometer data.

Combining Dendrometer Series and Xylogenesis Imagery—DevX, a Simple Visualization Tool to Explore Plant Secondary Growth Phenology

Determining the effect of a changing climate on tree growth will ultimately depend on our understanding of wood formation processes and how they can be affected by environmental conditions. In this context, monitoring intra-annual radial growth with high temporal resolution through point dendrometers has often been used. Another widespread approach is the microcoring method to follow xylem and phloem formation at the cellular level. Although both register the same biological process (secondary growth), given the limitations of each method, each delivers specific insights that can be combined to obtain a better picture of the process as a whole. To explore the potential of visualizing combined dendrometer and histological monitoring data and scrutinize intra-annual growth data on both dimensions (dendrometer → continuous; microcoring → discrete), we developed DevX (Dendrometer versus Xylogenesis), a visualization application using the “Shiny” package in the R programming language. The interactive visualization allows the display of dendrometer curves and the overlay of commonly used growth model fits (Gompertz and Weibull) as well as the calculation of wood phenology estimates based on these fits (growth onset, growth cessation and duration). Furthermore, the growth curves have interactive points to show the corresponding histological section, where the amount and development stage of the tissues at that particular time point can be observed. This allows to see the agreement of dendrometer derived phenology and the development status at the cellular level, and by this help disentangle shrinkage and swelling due to water uptake from actual radial growth. We present a case study with monitoring data for Acer pseudoplatanus L., Fagus sylvatica L. and Quercus robur L. trees growing in a mixed stand in northeastern Germany. The presented application is an example of the innovative and easy to access use of programming languages as basis for data visualization, and can be further used as a learning tool in the topic of wood formation and its ecology. Combining continuous dendrometer data with the discrete information from histological-sections provides a tool to identify active periods of wood formation from dendrometer series (calibrate) and explore monitoring datasets.

Patterns and drivers in spring and autumn phenology differ above- and belowground in four ecosystems under the same macroclimatic conditions

Start and end of the growing season determine important ecosystem processes, but their drivers may differ above-and belowground, between autumn and spring, and between ecosystems. Here, we compare above-and belowground spring and autumn phenology, and their abiotic drivers (temperature, water level, and soil moisture) in four temperate ecosystems (beech forest, alder carr, phragmites reed, and sedge reed). Root growth was measured in-situ with minirhizotrons and compared with aboveground phenology assessed with dendrometer data and NDVI. Synchrony of above- and belowground phenology depended on ecosystem. Onset of root growth was later than shoot growth in all three peatlands (12–33 days), but similar in the beech forest. The growing season ended earlier belowground in the two forested ecosystems (beech forest: 27 days, understory of the alder carr: 55 days), but did not differ in the phragmites reed. Generally, root production was correlated with soil temperature (especially in spring) and water level in the peatlands, while abiotic factors were less correlated with leaf activity or root production in either spring or autumn in the beech forest. Root production on organic soils was ten times higher compared to the zonal broadleaf deciduous forest on mineral soils, highlighting the importance of peatlands. Belowground phenology cannot be projected from aboveground phenology and measuring root phenology is crucial to understand temporal dynamics of production and carbon fluxes.

Growth and Tree Water Deficit of Mixed Norway Spruce and European Beech at Different Heights in a Tree and under Heavy Drought

Although several studies suggest that tree species in mixed stands resist drought events better than in pure stands, little is known about the impact on growth and the tree water deficit (TWD) in different tree heights at heavy drought. With dendrometer data at the upper and lower stem and coarse roots, we calculated the TWD and growth (ZGmax) (referring to the stem/root basal area) to show (1) the relationship of TWD in different tree heights (50% tree height (H50), breast height (BH), and roots) and the corresponding leaf water potential and (2) how mixture and drought influence the partitioning of growth and tree water. The analyses were made in a mature temperate forest of Norway spruce (Picea abies (L.) Karst.) and European beech (Fagus sylvatica (L.)). Half of the plots were placed under conditions of extreme drought through automatic closing roof systems within the stand. We found a tight relationship of leaf water potentials and TWD at all tree compartments. Through this proven correlation at all tree heights we were also able to study the differences of TWD in all tree compartments next to the growth allocation. Whereas at the beginning of the growing period, trees prioritized growth of the upper stem, during the course of the year the growth of lower stem became a greater priority. Growth allocation of mixed spruces showed a tendency of a higher growth of the roots compared to the BH. However, spruces in interspecific neighborhoods exhibited a lesser TWD in the roots as spruces in intraspecific neighborhood. Beeches in intraspecific neighborhoods showed a higher TWD in BH compared to H50 as beeches in interspecific neighborhoods. Mixture seems to enhance the water supply of spruce trees, which should increase the stability of this species in a time of climatic warming.

Seasonal radial growth of black pine (Pinus nigra Arnold) from Bosnia and Herzegovina, monitored by the pinning method and manual band dendrometers

Despite numerous dendroclimatological investigations into different tree species from Bosnia and Herzegovina, information is lacking on intra-annual wood formation patterns, which would help us to interpret the climate signal in tree rings better. Using the pinning method and manual band dendrometers, we investigated the seasonal dynamics of radial growth of black pine (Pinus nigra Arnold) trees in two successive growing seasons: 2011 and 2012. The up to 60-year-old trees grew in a stand at the base of a hill in the western, mountainous part of the Balkan Peninsula. The seasonal dynamics of wood formation and final number of cells differed between the studied years. Wood formation started in both years in early to mid-March. Differences were noticed in the wood production culmination; in 2011 it occurred at the end of May and beginning of June in 2012 and 2011, respectively. Xylem growth finished in 2012 in the middle of August and in 2011 in the middle of September. Based on the first derivative of the Gompertz function calculated rate of xylem growth was lowest in 2011. The dendrometers recorded a slow increment rate in spring, higher in summer and a decreasing rate again in the late summer in both growing seasons. In comparison with pinning, dendrometers showed a delay in the start of radial growth of up to 20 days in 2012. Additionally, dendrometers showed an increase in stem girth after the end of both growing seasons, when wood formation was already completed. Deviations between the two methods could be ascribed to the influence of water storage dynamics in the main stem and numerous structural processes in bark tissue, which are captured in dendrometer data. The influence of weather conditions on xylem phenology is also indicated by differences between the two studied years, although it is difficult to identify the influence of particular short-term weather events.

Comparative Analysis of the Effects of Stem Height and Artificial Pruning on Seasonal Radial Growth Dynamics of Wild Cherry (Prunus avium L.) and Sycamore (Acer pseudoplatanus L.) in a Widely Spaced System

Intensive artificial pruning of trees increases the proportion of high-value timber but simultaneously reduces the crown and consequently the capacity to assimilate photosynthates. Here, midterm effects of two intensive pruning treatments, a classical and a selective approach, on radial growth dynamics at different stem heights is comparatively analyzed for the broadleaved tree species sycamore (Acer pseudoplatanus L.) and wild cherry (Prunus avium L.) at a site in the upper Rhine valley in southwest Germany using high-resolution point-dendrometers starting three years after pruning. We fitted shape-constrained additive models to the dendrometer data and derived estimates of growth phenology and performance of individual trees over the 2010–2016 observation period. The statistical analysis based on linear mixed-effects models showed significantly later growth cessation and in individual years also higher rates of radial growth in sycamore compared to wild cherry. Growth onset for both tree species initiated systematically earlier at the higher dendrometer location compared to breast height. While no main effects of treatment or interactions of treatment with year were detected, we found significantly higher average daily growth rates and annual radial growth of wild cherry at the top dendrometer location compared to breast height in the selective pruning treatment. Our results provide new insights into seasonal growth patterns of sycamore and wild cherry in a widely spaced system and contribute to a better understanding of the effects of stem height, pruning treatment and climate on radial growth dynamics of valuable broadleaved tree species.