Higher Winter-Spring Temperature and Winter-Spring/Summer Moisture Availability Increase Scots Pine Growth on Coastal Dune Microsites Around the South Baltic Sea

Janecka, Karolina; Harvey, Jill E.; Trouillier, Mario; Kaczka, Ryszard J.; Metslaid, Sandra; Metslaid, Marek; Buras, Allan; Wilmking, Martin

doi:10.3389/ffgc.2020.578912

Cited by 15 publications

(9 citation statements)

References 97 publications

(152 reference statements)

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“…contorta and P . banksiana growth are similar to other studies of freeze effects on pine in Canada and Europe ( 25 , 26 , 42 ). Furthermore, P. menziesii , an important timber species in western North America, is notoriously sensitive to freezing conditions ( 29 ).…”

Section: Discussionsupporting

confidence: 89%

Cold-season freeze frequency is a pervasive driver of subcontinental forest growth

Girardin

Guo

Gervais

et al. 2022

Proc. Natl. Acad. Sci. U.S.A.

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Significance The reduction of freeze exposure with winter warming has consequences for carbon sequestration by northern forests. Quantifying the impact of these changes on tree growth is, however, challenging because of among- and within-tree species variability in freeze tolerance and phenological cues. Here, we provide a comprehensive assessment of tree growth response to the cold-season frequency of freeze days using an extensive tree-ring dataset covering Canada’s forests. Our study shows that tree growth responses to freeze exposure vary in direction and magnitude by clade and species but also with leaf-out strategy, tree age and size, and environmental factors. Such quantification can help predict terrestrial carbon dynamics under climate change.

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Section: Discussionsupporting

confidence: 89%

Cold-season freeze frequency is a pervasive driver of subcontinental forest growth

Girardin

Guo

Gervais

et al. 2022

Proc. Natl. Acad. Sci. U.S.A.

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“…Conifers, beech, and oak are some of the most used species for tree ring studies in general ( Scharnweber et al, 2013 ; Príncipe et al, 2017 ; Lange et al, 2018 ; Janecka et al, 2020 ) and specifically for wood anatomical analyses ( Björklund et al, 2020 ; Pampuch et al, 2020 ; Peters et al, 2020 ). Images were collected from several sources, to ensure variability in the image quality and within the sample processing ( Supplementary Table 1 ).…”

Section: Methodsmentioning

confidence: 99%

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

et al. 2021

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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.

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“…Late winter and early spring temperature is the dominant climatic factor shaping tree-ring widths in Scots pine on the Southern and Eastern Baltic coasts [4,8,11,22,25,26,58,59]. The lack of strong frost in January, and especially in February, and an early and warm spring (March) result in good health of the trees, and the formation of broad tree-rings.…”

Section: Discussionmentioning

confidence: 99%

“…An early onset of spring (temperature increase in March, lack of frost) extends the vegetation season and favors an acceleration of metabolic processes and cambial activity [6,27,60]. At numerous sites, Scots pines (especially those growing on sands) also display sensitivity to rainfall sums in summer (June-August) [20,26,59]. During summer droughts, sandy soils, which are characterized by high permeability and most frequently There are, however, considerable changes in the growth-climate response depending on the type/age of the dune.…”

Section: Discussionmentioning

confidence: 99%

“…In the Southern and Eastern Baltic coast regions, Scots pine is also the main focus of dendrochronological studies, e.g., [12,13,[20][21][22][23], apart from the native oak species (Quercus robur and Q. petrea). Numerous studies point to late winter and early spring air temperatures (February and March) as the dominant factor shaping tree-ring width in Scots pine [4,8,9,11,[24][25][26]. Climate warming observed in recent decades (especially affecting the winter-spring transition) causes the vegetation season to become extended, and results in improved pine growth…”

Section: Introductionmentioning

confidence: 99%

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Differences in Growth–Climate Relationships among Scots Pines Growing on Various Dune Generations on the Southern Baltic Coast

Cedro

Podlasiński

2022

Forests

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This study focuses on analyzing the growth rate and growth–climate relationship in Scots pine (Pinus sylvestris L.) growing on coastal dunes of different ages on the Southern Baltic coast. Podzols have developed on these dunes. Depending on dune age, however, podzols are characterized by a different degree of development and richness, which represents the main factor differentiating the studied habitats: the oldest brown dunes (BD), younger yellow dunes (YD), and the youngest white dunes (WD). Samples were taken from 68 trees using Pressler borers. Using classic cross-dating methods, local chronologies were compiled that served as the basis for further analyses. Basic analyses of soil properties were also performed. Trees growing on brown dunes display the widest tree-rings and the highest rate of cumulative radial growth. Both rates are the lowest for trees growing on white dunes (WD). The dominant meteorological factor shaping tree-ring widths is late winter/early spring air temperature (February/March). However, in poorer habitats with inferior soil air–water conditions, rainfall sums and rainfall distribution through the year become progressively more significant factors. On white dunes (WD), the strongest growth–climate correlations are obtained for summer precipitation. These results identify habitat richness as the main factor shaping growth dynamics in Scots pines growing on dunes. Due to the protective function of the studied tree stands (coast protection), and in light of the rising sea levels and increasing storm intensities, further studies are required, aiming at understanding all interrelationships occurring in these valuable ecosystems.

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Higher Winter-Spring Temperature and Winter-Spring/Summer Moisture Availability Increase Scots Pine Growth on Coastal Dune Microsites Around the South Baltic Sea

Cited by 15 publications

References 97 publications

Cold-season freeze frequency is a pervasive driver of subcontinental forest growth

Cold-season freeze frequency is a pervasive driver of subcontinental forest growth

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

Differences in Growth–Climate Relationships among Scots Pines Growing on Various Dune Generations on the Southern Baltic Coast

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