AutoCellRow (ACR) – A new tool for the automatic quantification of cell radial files in conifer images

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Siberian pine (Pinus sibirica Du Tour) is a widespread and long-lived species in the northern hemisphere, which makes it a good potential proxy for climatic data. However, the tree-ring growth of this species weakly correlates with climatic conditions, which prevents its use in dendroclimatic reconstruction. It was proposed to use the measurements of tracheid characteristics as model predictors to reconstruct the smoothed temperature of the key periods in tree growth. In this study, algorithms for preprocessing tracheids and temperature data, as well as for model cross-validation, were developed to produce reliable high-resolution (weekly-based) temperature reconstructions. Due to the developed algorithms, the key time periods of Siberian pine growth were identified during the growing season—early June (most active cell development) and mid-July (setting new buds for the next growing season). For these time periods, reliable long-term temperature reconstructions (R2 > 0.6, p < 10−8) were obtained over 1653–2018. The temperature reconstructions significantly correlated (p < 10−8) with independent reanalysis data for the 19th century. The developed approach, based on preprocessing tracheid and temperature data, shows new potential for Siberian pine in high-resolution climate reconstructions and can be applied to other tree species that weakly respond to climate forcing.

Section: Tree Data Collection and Processingmentioning

confidence: 99%

Tracheids vs. Tree Rings as Proxies for Dendroclimatic Reconstruction at High Altitude: The Case of Pinus sibirica Du Tour

Zharkov,

Yang,

Babushkina

et al. 2024

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“…Microphotographs of cross-sections were obtained using a digital camera (ProgResGryphax Subra, Jenoptik GmbH, Jena, Germany) mounted on an optical microscope with 200× magnification (BX43, Olympus, Tokyo, Japan). Anatomical traits of all the rings in the selected samples were measured using the semiautomatic program Lineyka 2.01 and ACR-software [47]. Wood anatomical traits, namely, the number of cells (N), their radial diameter (D), and cell wall thickness (CWT), were measured [48] for five radial cell rows per ring [49].…”

Section: Cell Data Processingmentioning

confidence: 99%

Tracheidogram’s Classification as a New Potential Proxy in High-Resolution Dendroclimatic Reconstructions

Zharkov

Huang

Yang

et al. 2022

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Quantitative wood anatomy (QWA) is widely used to resolve a fundamental problem of tree responses to past, ongoing and forecasted climate changes. Potentially, QWA data can be considered as a new proxy source for long-term climate reconstruction with higher temporal resolution than traditional dendroclimatic data. In this paper, we considered a tracheidogram as a set of two interconnected variables describing the dynamics of seasonal variability in the radial cell size and cell wall thickness in conifer trees. We used 1386 cell profiles (tracheidograms) obtained for seven Scots pine (Pinus sylvestris) trees growing in the cold semiarid conditions of Southern Siberia over the years 1813–2018. We developed a “deviation tracheidogram” approach for adequately describing the traits of tree-ring formation in different climate conditions over a long-term time span. Based on the NbClust approach and K-means method, the deviation tracheidograms were reliably split into four clusters (classes) with clear bio-ecological interpretations (from the most favorable growth conditions to worse ones) over the years 1813–2018. It has been shown that the obtained classes of tracheidograms can be directly associated with different levels of water deficit, for both the current and previous growing seasons. The tracheidogram cluster reconstruction shows that the entire 19th century was characterized by considerable water deficit, which has not been revealed by the climate-sensitive tree-ring chronology of the study site. Therefore, the proposed research offers new perspectives for better understanding how tree radial growth responds to changing seasonal climate and a new independent proxy for developing long-term detailed climatic reconstructions through the detailed analysis of long-term archives of QWA data for different conifer species and various forest ecosystems in future research.

“…Tree-ring width and wood anatomy data were analyzed for the periods 1970-2012, 1950-2010, and 1970-2013 in the case of P. halepensis, P. sylvestris and P. lumholtzii, respectively (see Table 1). Images of P. halepensis and P. sylvestris wood sections were processed using the ROXAS software [21], while images of P. lumholtzii wood sections were processed using the recently developed AutoCellRow software [36]. These analyses provided measurements of transversal conduit area and double cell-wall thickness of tracheids performed on radial direction within the dated annual ring.…”

Section: Tree-ring Width and Wood Anatomical Datamentioning

confidence: 99%

Wood Anatomical Traits Respond to Climate but More Individualistically as Compared to Radial Growth: Analyze Trees, Not Means

Rita

Camarero

Colangelo

et al. 2022

Wood encodes environmental information that can be recovered through the study of tree-ring width and wood anatomical variables such as lumen area or cell-wall thickness. Anatomical variables often provide a stronger hydroclimate signal than tree-ring width, but they show a low tree-to-tree coherence. We investigate the sources of variation in tree-ring width, lumen area, and cell-wall thickness in three pine species inhabiting sites with contrasting climate conditions: Pinus lumholtzii in wet-summer northern Mexico, and Pinus halepensis and Pinus sylvestris in dry-summer north-eastern Spain. We quantified the amount of variance of these three variables explained by spring and summer water balance and how it varied among trees. Wood anatomical variables accounted for a larger inter-individual variability than tree-ring width data. Anatomical traits responded to hydroclimate more individualistically than tree-ring width. This individualistic response represents an important issue in long-term studies on wood anatomical characteristics. We emphasized the degree of variation among individuals of the same population, which has far-reaching implications for understanding tree species’ responses to climate change. Dendroclimatic and wood anatomical studies should focus on trees rather than on the mean population series.