Quantitative Wood Anatomy Research Articles

Indication of radioactive contamination of forest ecosystems in the zone of the east Ural radioactive trace using methods of quantitative wood anatomy

The anatomical structure of the annual rings of Scots pine, formed before and after the Kyshtym accident, is analyzed. In trees growing closer to the central axis of the East Ural radioactive trace (EURT), a decrease in the number of cells in the annual ring, as well as a decrease in the diameter of the lumens and the thickness of the cell walls, was noted. It is assumed that radiation-induced damage to the photo-assimilation apparatus of trees led to disturbances in physiological processes that were reflected in the anatomical structure of wood.

Indication of Radioactive Contamination of Forest Ecosystems in the Zone of the East Ural Radioactive Trace Using Methods of Quantitative Wood Anatomy

Indication of Radioactive Contamination of Forest Ecosystems in the Zone of the East Ural Radioactive Trace Using Methods of Quantitative Wood Anatomy

What signs of climate variability can be extracted from the quantitative wood anatomy of Cedrela fissilis Vell. rings?

What signs of climate variability can be extracted from the quantitative wood anatomy of Cedrela fissilis Vell. rings?

Traces of Local Adaptive Acclimatization Response in the Tracheid Anatomical Traits between Dry and Wet Mesic Norway Spruce (Picea abies) Forests in Moravia, Czech Republic?

Norway spruce (Picea abies) forests in temperate zones are already reacting to short-term extreme summer heatwaves, threatening the vitality of trees and forest productivity, and can even lead to local and regional dieback events. Examining quantitative wood anatomy can provide helpful information in terms of understanding the physiology mechanisms and related responses of conifer trees to local environmental interactions in relation to tracheid adaptive capacity. This study analysed the tracheid functional anatomical traits (FATs) plasticity of six young Norway spruce trees growing in two mesic research plots with high annual precipitation (~43%) and air temperature differences during 2010–2017. The research plots are located in the sub-mountainous (Rájec Němčice) and mountainous (Bílý Kříž) belts of the Moravia region, Czech Republic. Vapour pressure deficit and cell wall reinforcement index (CWRI) were shown to be the most representative environmental parameters as proxies of dry conditions. Tracheid FATs indicated latewood phenological plasticity sensitivity, with more pronounced variability in the warmer and drier plots. Latewood tracheids of Norway spruce trees grown in the RAJ formed significantly thicker cell walls than BK during the studied period. The observed differences between the two research plots indicate additional support for tracheid cells’ hydraulic safety against cavitation and potential traces of adaptive acclimatization response.

Tree-ring hydrological research in the Himalaya: State of the art and future directions

Recent developments in tree-ring research offer great potential for reconstructing past climate changes; determining the frequencies of natural hazards; and assessing the availability of freshwater resources over timescales that extend well into the pre-instrumental period. Here, we review the state of dendrochronological research in the Himalaya and outline future directions for tree-ring-based hydrological reconstructions in a region that has a pressing societal need to understand the causes and consequences of past, present and future changes in the hydrological cycle. We used ‘tree ring’ and ‘Himalaya’ as keywords to identify scholarly articles from the Web of Science that were published between 1994 and 2022. The resulting 173 publications were separated by their spatial coverage into the western, central and eastern Himalaya, as well as their scientific purpose (e.g. reconstructing growth-climate relationships, temperature, precipitation, streamflow, floods, droughts, etc.). Our analysis shows that dendrochronological research in the Himalaya primarily focused on understanding growth-climate relationships using annual tree-ring widths measurements obtained for coniferous species, and their application in climate reconstructions. Reconstructions of hydrological processes such as streamflows, and extremes such as glacial and landslide lake outburst floods, have received less attention. Recent advances in dendrochronology, including blue intensity (BI), quantitative wood anatomy (QWA), and tree-ring stable isotopes (TRSI) should be combined to improve the resolution and accuracy of hydrological reconstructions in all parts of the Himalaya. Such studies may allow us to better understand the effects of climate change and the Himalayan water resources for its lowland surroundings. They may also facilitate decision-making processes for mitigating the impacts of climate change on natural hazards, and for better managing water resources in the region.

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.

An open-source machine-learning approach for obtaining high-quality quantitative wood anatomy data from E. grandis and P. radiata xylem

Quantitative wood anatomy is a subfield in dendrochronology that requires effective open-source image analysis tools. In this research, the bioimage analysis software QuPath (v0.4.4) is introduced as a candidate for accurately quantifying the cellular properties of the xylem in an automated manner. Additionally, the potential of QuPath to detect the transition of early- to latewood tracheids over the growing season was evaluated to assess a potential application in dendroecological studies. Various algorithms in QuPath were optimized to quantify different xylem cell types in Eucalyptus grandis and the transition of early- to latewood tracheids in Pinus radiata. These algorithms were coded into cell detection scripts for automatic quantification of stem microsections and compared to a manually curated method to assess the accuracy of the cell detections. The automatic cell detection approach, using QuPath, has been validated to be reproducible with an acceptable error when assessing fibers, vessels, early- and latewood tracheids. However, further optimization for parenchyma is still required. This proposed method developed in QuPath provides a scalable and accurate approach for quantifying anatomical features in stem microsections. With minor amendments to the detection and classification algorithms, this strategy is likely to be viable in other plant species.

Ultra-high-resolution reflected-light imaging for dendrochronology

Dendroclimatic reconstructions play a key role in contextualizing recent climate change by improving our understanding of past climate variability. The Blue Intensity (BI) measurement technique is gaining prominence as a more accessible alternative to X-ray densitometry for producing climatically highly-sensitive tree-ring predictors. Nevertheless, accurately representing low-frequency trends and high-frequency extremes using scanner-based BI remains a challenge due to color biases and resolution limitations. Herein we introduce several methodological advances in sample surfacing, imaging, and image processing which yield measurement series analogous to BI from ultra-high-resolution (UHR; ∼74 700 dpi) images. Such series capture changes in tree-ring anatomical density by representing wood anatomical structure using binary (i.e., black-white) segmentation of sample images. We refer to this novel technique as Binary Surface Intensity (BSI). By utilizing a UHR system and entirely eliminating color and light intensity as variables, the most substantial drawbacks of scanner BI (i.e., discoloration and resolution biases) are bypassed, resulting in more accurate representations of low-frequency climatic trends and high-frequency extremes. Comparisons of several chronologies developed with the BSI and BI techniques, including a multiparameter dataset from Björklund et al. (2019), showed that BSI datasets outperform BI in terms of common signal (r-bar), but also contain strong climatic signals that can exceed those obtained from BI and X-ray density, and even match density datasets based on quantitative wood anatomy. However, measurement software advancements are still required to unlock the full potential of tree-ring parameters produced using the BSI technique. Ongoing development of this new technique will not only aid the attainment of long unbiased chronologies by overcoming color biases and resolution limitations, but also holds promise for unlocking UHR analyses of surface anatomical (sQWA) parameter datasets from reflected-light images. These advances will lead to more accurate tree-ring-based paleoclimatic reconstructions and could also serve a wider range of dendrochronological applications.

Impact of intra-annual wood density fluctuation on tree hydraulic function: insights from a continuous monitoring approach.

Climate change significantly impacts global forests, leading to tree decline and dieback. To cope with climate change, trees develop several functional traits, such as intra-annual density fluctuations (IADFs) in tree rings. The formation of these traits facilitates trees to optimize resource allocation, allowing them to withstand periods of stress and eventually recover when the conditions become favourable again. This study focuses on a Pinus pinaster Aiton forest in a warm, drought-prone Mediterranean area, comparing two growing seasons with different weather patterns. The innovative continuous monitoring approach used in this study combines high-resolution monitoring of sap flow (SF), analysis of xylogenesis and quantitative wood anatomy. Our results revealed the high plasticity of P. pinaster in water use and wood formation, shedding light on the link between IADFs and tree conductance. Indeed, the capacity to form large cells in autumn (as IADFs) improves the total xylem hydraulic conductivity of this species. For the first time, a continuous SF measurement system captured the dynamics of bimodal SF during the 2022 growing season in conjunction with the bimodal growth pattern observed through xylogenesis monitoring. These results highlight the intricate interplay between environmental conditions, water use, wood formation and tree physiology, providing valuable insights into the acclimation mechanisms employed by P. pinaster to cope with weather fluctuations.

Quantitative wood anatomy and stable carbon isotopes indicate pronounced drought exposure of Scots pine when growing at the forest edge

Climate change poses a major threat to global forest ecosystems. In particular, rising temperatures and prolonged drought spells have led to increased rates of forest decline and dieback in recent decades. Under this framework, forest edges are particularly prone to drought-induced decline since they are characterized by warmer and drier micro-climatic conditions amplifying impacts of drought on tree growth and survival. Previous research indicated that forest-edge Scots pine trees have a higher growth sensitivity to water availability compared to the forest interior with consequent reduction of canopy greenness (remotely sensed NDVI) and higher mortality rates. Yet, the underlying physiological mechanisms remain largely unknown. Here, we address this knowledge gap by comparing stable carbon isotope signatures and wood anatomical traits in annual rings of trees growing at the forest edge vs. the forest interior and between trees that either survived or died during the extreme drought of 2015. Our analyses suggest that the exposure to drought of forest-edge Scots pine likely results in a reduction of stomatal conductance, as reflected by a higher δ13C of stem wood, thinner cell walls, and lower mean ring density. Moreover, we found dead trees to feature larger mean hydraulic lumen diameters and a lower cell-wall reinforcement, indicating a higher risk to suffer from cavitation. In conclusion, the typically drier micro-climatic conditions at the forest edge seem to have triggered a larger reduction of stomatal conductance of Scots pine trees, resulting in a lower carbon availability and significantly altered wood anatomical properties under an increasingly drier climate.

Tree Core Analysis with X-ray Computed Tomography.

An X-ray computed tomography (CT) toolchain is presented to obtain tree-ring width (TRW), maximum latewood density (MXD), other density parameters, and quantitative wood anatomy (QWA) data without the need for labor-intensive surface treatment or any physical sample preparation. The focus here is on increment cores and scanning procedures at resolutions ranging from 60 µm down to 4 µm. Three scales are defined at which wood should be looked at: (i) inter-ring scale, (ii) ring scale, i.e., tree-ring analysis and densitometry scale, as well as (iii) anatomical scale, the latter approaching the conventional thin-section quality. Custom-designed sample holders for each of these scales enable high-throughput scanning of multiple increment cores. A series of software routines were specifically developed to efficiently treat three-dimensional X-ray CT images of the tree cores for TRW and densitometry. This work briefly explains the basic principles of CT, which are needed for a proper understanding of the protocol. The protocol is presented for some known species that are commonly used in dendrochronology. The combination of rough density estimates, TRW and MXD data, as well as quantitative anatomy data, allows us to broaden and deepen current analyses for climate reconstructions or tree response, as well as further develop the field of dendroecology/climatology and archeology.

Towards ROXAS AI: Deep learning for faster and more accurate conifer cell analysis

Quantitative wood anatomy (QWA) has proven to be a powerful method for extracting relevant environmental information from tree-rings. Although classical image-analysis tools such as ROXAS have greatly improved and facilitated measurements of anatomical features, producing QWA datasets remains challenging and time-consuming. In recent years, deep learning techniques have drastically improved the performance of most computer vision tasks. We, therefore, investigate three different deep learning models (U-Net, Mask-RCNN, Panoptic Deeplab) to improve the main bottleneck, cell detection. Therefore, we create a Conifer Lumen Segmentation (CoLuS) dataset for training and evaluation. It consists of manual outlines of each cell lumen from anatomical images of several conifer species that cover a wide range of sample qualities. We furthermore apply our deep learning model to a previously published high-quality QWA chronology from Northern Finland to compare the warm-season (AMJJAS) temperature reconstruction skill of our deep learning method with that of the current ROXAS implementation, which is based on classical image analysis. Based on our evaluation dataset we show improvements of 7.6% and 8.1% for our best performing deep learning model (U-Net) for the computer vision metrics mean Intersection over Union (mIoU) and Panoptic Quality (PQ) compared to automatic ROXAS segmentation, in addition to being much faster. Furthermore, U-Net reduces the percentage error compared to automatic ROXAS analysis - which tends to systematically underestimate lumen area - by 57.8% for lumen area, 63.2% for average cell wall thickness, and 54.1% for cell count. In addition, we show higher performance for the U-Net compared to the Mask-RCNN previously used for tree cell segmentation. These improvements are independent of sample quality. For the Northern Finland QWA chronology, our U-Net model matches or outperforms ROXAS with and without manual post-processing, showing a common signal (Rbar) of 0.72 and a AMJJAS temperature correlation of 0.81 for maximum radial cell wall thickness. A clear improvement is especially visible for the anatomical latewood density, likely due to the better detection of small cell lumina. Our results demonstrate the potential of deep learning for higher-quality segmentation with lower manual post-processing time, saving weeks to months of tedious work without compromising data quality. We thus plan to implement deep learning in a future version of ROXAS.

Conifer quantitative wood anatomy as proxy data: application in agricultural yield reconstruction

Conifer quantitative wood anatomy as proxy data: application in agricultural yield reconstruction

Dendroanatomy of xylem hydraulics in two pine species: Efficiency prevails on safety for basal area growth in drought-prone conditions

Xylem structure optimizes water conductivity while preventing hydraulic failure via embolism resistance, but how this process is modulated by climate variability and how it affects secondary growth in mature trees is still not fully understood, particularly in water-limited environments. Using quantitative wood anatomy techniques, we estimated xylem anatomical proxies for hydraulic efficiency (xylem specific conductivity, Ks) and safety (cell wall reinforcement, wrein) in two western US conifers, Pinus flexilis and Pinus longaeva, at a montane and subalpine location respectively. We built two large datasets (570 rings for P. flexilis, 635 rings for P. longaeva) to investigate 1) the variability of anatomical parameters (i.e lumen diameter, cell wall thickness) and hydraulic proxies along the stem in the five outermost rings (2009–2013); 2) the response of hydraulic proxies to daily climate over a period of 24 years (1990–2013); and 3) the relationship between xylem hydraulic architecture and basal area increment (BAI). Lumen diameter scaled along the stem following a power function, but the scaling patterns of cell wall thickness and hydraulic proxies differed significantly between species. From 1990–2013, Ks decreased in both species, whereas wrein increased only in P. longaeva, while no trends were observed in BAI. Climate sensitivity of Ks peaked over a longer period (84–102 days) compared to wrein (20–55 days), responding to increasing minimum temperature. In both species, Ks was a better predictor of BAI than wrein, indicating that, even under severely water-limited conditions, radial growth is linked to hydraulic efficiency rather than safety. Based on the variability of cell density along the stem, the trade-off between hydraulic efficiency and safety in P. longaeva appeared to be controlled by a strategy of space occupation. Characterizing the mechanistic relationship between xylem anatomy, plant hydraulic functioning, and stem growth is necessary to better understand climate-growth relationships in the western US and species’ growth plasticity under future climate change scenarios.

Dendrochronology in the tropics using tree-rings of Pinus kesiya

The recent decade has witnessed considerable progress in the number of tree-ring studies using the tropical conifer taxa, Pinus kesiya. Several tree-ring networks have been established in less explored regions in Northeast India, Southwest China and Vietnam. The seasonal climate response of P. kesiya tree-rings has been examined and used to reconstruct temperature and soil moisture variability over the past century and augment the short instrumental records in South and Southeast Asia. In addition to standard approaches, the application of stable isotope, wood density, and blue intensity measurements indicates a significant development in P. kesiya studies. This review elaborates the future prospects of using multiple tree-ring parameters to establish discrete proxies besides tree-ring width. We recommend blue intensity as a cost-effective alternative to quantitative wood anatomy in tropical pines, and call for routine assessments of the temporal stability of climate-growth responses to identify and study potentially non-stationary climate signals. Efforts should be made towards developing extensive networks of long P. kesiya tree-ring chronologies to extend regional climate reconstructions.

Is there Chornobyl nuclear accident signature in Scots pine radial growth and its climate sensitivity?

The extensive radioactive fallout resulting from the 1986 Chornobyl accident caused tree death near the nuclear power plant and perturbed trees communities throughout the whole Chornobyl exclusion zone. Thirty years into the post-accident period, the radiation continues to exert its fatal effects on the surviving trees. However, to what extent the continuous multi-decadal radiation exposure has affected the radial tree growth and its sensitivity to climate variation remains unascertained. In this comparative study, we measure the Scots pine radial growth and quantify its response to climate at two sites along the western track of the nuclear fallout that received significantly different doses of radiation in 1986. The common features of the two sites allow us to disentangle and intercompare the effects of sub-lethal and moderate radiation doses on the pine's growth and climatic sensitivity. We extend the response function analysis by making the first use of the Full-Duration at Half-Maximum FDHM method in dendrochronology and apply the double-moving window approach to detect the main patterns of the growth-to-climate relationships and their temporal evolution. The stand exposed to sub-lethal radiation shows a significant radial growth reduction in 1986 with a deflection period of one year. The stand exposed to moderate radiation, in contrast, demonstrates no significant decrease in growth either in 1986 or in the following years. Beyond the radiation effects, the moving response function and FDHM enabled us to detect several mutual patterns in the growth-to-climate relationships, which are seemingly unrelated to the nuclear accident. To advance our predictive understanding of the response of forest ecosystems to a massive radioactive contamination, future studies should include quantitative wood anatomy techniques.

Combined tree-ring width and wood anatomy chronologies provide insights into the radial growth and hydraulic strategies in response to an extreme drought in plantation-grown Mongolian pine trees

Mongolian pine (Pinus sylvestris var. Mongolica) is among the most commonly used coniferous afforestation tree species for building shelter forests in vast areas of northern China, yet it is at a high risk of mortality in the context of increased frequency of extreme drought events associated with anticipative climate change. Understanding the long-term ecophysiological response to climate extremes is of great relevance for taking appropriate practices for the sustainability-oriented management of Mongolian pine plantations in drought-prone environments. Here, the hydraulic strategy behind the response of the radial growth of Mongolian pine trees planted in a water-limited area of northern China to the extreme drought event from 2001 to 2004 was retrospectively investigated by combining standard dendrochronological methods and quantitative wood anatomy. We found that water-related climatic variables acted as the main factors regulating the radial growth and xylem tracheid size of the Mongolian pine trees at the study site, and the extreme drought significantly reduced xylem theoretical hydraulic conductivity and almost stagnated the trunk radial increment. Immediately after this climatic extreme, the stem growth sharply increased to a level substantially higher than that preceding the extreme drought, which was probably attributable to the reduction of inter-tree competitions for resources due to the mortality of a large number of trees caused by the extreme drought event. Around the extreme drought event, tree ring width was significantly proportional to the number of earlywood tracheid cell layers but was uncorrelated with tracheid size metrics, alongside a clear hydraulic safety-efficiency trade-off among the stem xylem traits obtained from tree ring series. This study stresses the role that xylem hydraulics play in modulating the radial growth of plantation-grown Mongolian pine trees during extreme droughts by adjusting xylem structural characteristics and hence hydraulic transport functions.

Quantifying terminal white bands in Salix from the Yenisei river, Siberia and their relationship to late-season flooding

Key MessageWood fiber cell wall thickness best characterizes white bands found at the end of certain growth rings in Salix alba. Evidence suggests these features are related to late-season hydrology.Recent, record-breaking discharge in the Yenisei River, Siberia, is part of a larger trend of increasing river flow in the Arctic driven by Arctic Amplification. These changes in magnitude and timing of discharge can lead to increased risk of extreme flood events, with implications for infrastructure, ecosystems, and climate. To better understand the effect of these changes on riparian tree growth along the lower reaches of the Yenisei River, we collected white willow (Salix alba) cross sections from a fluvial fill flat terrace that occasionally floods when water levels are extremely high. These samples displayed bands of lighter colored wood at the end of certain annual growth rings that we hypothesized were related to flood events. To identify the characteristics and causes of these features, we use an approach known as quantitative wood anatomy (QWA) to measure variation in fiber cell dimensions across tree rings, particularly fiber lumen area (LA) and cell wall thickness (CWT). We investigate (1) which cell parameters and method to extract intra-annual data from annual tree rings best capture terminal white bands identified in Salix, and (2) if these patterns are related to flood magnitude and/or duration. We find that fiber CWT best captures terminal white bands found in Salix rings. Time series derived from CWT measurements correlate with July water-level durations, but at levels too low to be labeled flooding. Although both terminal white bands and July flooding have reduced since 1980, questions remain as to the cause of terminal white bands. Understanding how riparian vegetation responds to changes in hydrology can help us better manage riparian ecosystems and understand the impacts of a changing Arctic hydrological regime.

Investigation of Trees' Sensitivity to Drought: A Case Study in the Opole Region, Poland

<i>Pinus sylvestris</i> L. is the most common tree species growing in Poland. Trees of this species are considered to be resistant to difficult meteorological conditions; however, in the past decades, many of them have died and been cut down by foresters. The measurements of the annual tree ring width can provide information on how trees respond to drought events. This study aimed to investigate the potential differences between healthy and declining trees (identified as trees to be cut down by foresters). For this purpose, we collected samples of five trees from each group and analysed them using dendrochronological and quantitative wood anatomy approaches. We measured ring width index (RWI) chronologies for healthy and declining trees and compared them with climate data. Additionally, we compared some anatomical features of trees from both groups as cell wall thickness (CWT) and lumen area (LA). The conducted analyses showed significant differences between healthy and declining trees. In particular, declining trees were characterised by lower RWI, LA and CWT values, especially in the past 20 years, and showed greater sensitivity to changes in temperature and humidity than healthy trees.

Practical guidelines for quantitative wood anatomy on Ginkgo biloba L.

Summary Ginkgo biloba L., a long-lived relict species, has high ecological, cultural and economic value. Studying the quantitative wood anatomy of G. biloba is important to understand the relationships between their tree-growth and climate change, which could help in the protection of old G. biloba trees. Preparing high-quality wood thin sections is the premise of quantitative wood anatomy analysis. In addition, manual correction of image analysis is a time-consuming process. We therefore present a protocol on how to make G. biloba high-quality xylem thin sections, from sample preparation, sample embedding, blade selection to thickness selection. We also present a method to determine the necessary sample width and number of cores to establish reliable wood anatomical time series that both can capture climate signals and reduce the time used for image analysis. For microsection preparation, it is optimal to cut 20–30-μm-thick sections using Leica DB80 blades after applying the cornstarch solution on top of the sample surface. For image analysis, the reliable wood anatomical time series can be established when measuring six cores (trees) or above, and the environmental signals are captured when analyzing a 1.2-mm-wide radial strip along the increment core (deviation <2%) for the parameters cell density, mean lumen area, potential hydraulic conductivity and percentage of the conductive area. This paper provides practical guidance to successfully use quantitative wood anatomy methods on G. biloba. We hope our study will be helpful for future research on the quantitative wood anatomy of G. biloba and similar tree species.