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Xylem Anatomical Variability in White Spruce at Treeline Is Largely Driven by Spatial Clustering
(2020)
The ecological function of boreal forests is challenged by drastically changing climate conditions. Although an increasing number of studies are investigating how climate change is influencing growth and distribution of boreal tree species, there is a lack of studies examining the potential of these species to genetically adapt or phenotypically adjust. Here, we sampled clonally and non-clonally growing white spruce trees (Picea glauca [Moench] Voss) to investigate spatial and genetic effects on tree ring width and on six xylem anatomical traits representing growth, water transport, mechanical support, and wood density. We compared different methods for estimating broad sense heritability (H2) of each trait and we evaluated the effects of spatial grouping and genetic grouping on the xylem anatomical traits with linear models. We found that the three different methods used to estimate H2 were quite robust, showing overall consistent patterns, while our analyses were unsuccessful at fully separating genetic from spatial effects. By evaluating the effect size, we found a significant effect of genetic grouping in latewood density and earlywood hydraulic diameter. However, evaluating model performances showed that spatial grouping was a better predictor than genetic grouping for variance in earlywood density, earlywood hydraulic diameter and growth. For cell wall thickness neither spatial nor genetic grouping was significant. Our findings imply that (1) the variance in the investigated xylem anatomical traits and growth is mainly influenced by spatial clustering (most probably caused by microhabitat conditions), which (2) makes it rather difficult to estimate the heritability of these traits in naturally grown trees in situ. Yet, (3) latewood density and earlywood hydraulic diameter qualified for further analysis on the genetic background of xylem traits and (4) cell wall thickness seems a useful trait to investigate large-scale climatic effects, decoupled from microclimatic, edaphic and genetic influences.
Abstract
The role of future forests in global biogeochemical cycles will depend on how different tree species respond to climate. Interpreting the response of forest growth to climate change requires an understanding of the temporal and spatial patterns of seasonal climatic influences on the growth of common tree species. We constructed a new network of 310 tree‐ring width chronologies from three common tree species (Quercus robur, Pinus sylvestris and Fagus sylvatica) collected for different ecological, management and climate purposes in the south Baltic Sea region at the border of three bioclimatic zones (temperate continental, oceanic, southern boreal). The major climate factors (temperature, precipitation, drought) affecting tree growth at monthly and seasonal scales were identified. Our analysis documents that 20th century Scots pine and deciduous species growth is generally controlled by different climate parameters, and that summer moisture availability is increasingly important for the growth of deciduous species examined. We report changes in the influence of winter climate variables over the last decades, where a decreasing influence of late winter temperature on deciduous tree growth and an increasing influence of winter temperature on Scots pine growth was found. By comparing climate–growth responses for the 1943–1972 and 1973–2002 periods and characterizing site‐level growth response stability, a descriptive application of spatial segregation analysis distinguished sites with stable responses to dominant climate parameters (northeast of the study region), and sites that collectively showed unstable responses to winter climate (southeast of the study region). The findings presented here highlight the temporally unstable and nonuniform responses of tree growth to climate variability, and that there are geographical coherent regions where these changes are similar. Considering continued climate change in the future, our results provide important regional perspectives on recent broad‐scale climate–growth relationships for trees across the temperate to boreal forest transition around the south Baltic Sea.
AbstractUsing measurements from high resolution monitoring of radial tree-growth we present new data of the growth reactions of four widespread broadleaved tree-species to the combined European drought years 2018 and 2019. We can show that, in contrast to field crops, trees could make better use of the winter soil moisture storage in 2018 which buffered them from severe drought stress and growth depressions in this year. Nevertheless, legacy effects of the 2018 drought accompanied by sustained low soil moisture conditions (missing recharge in winter) and again higher than average temperatures and low precipitation in spring/summer 2019 have resulted in severe growth reductions for all studied tree-species in this year. This highlights the pivotal role of soil water recharge in winter. Although short term resistance to hot summers can be high if sufficient winter precipitations buffers forest stands from drought damage, legacy effects will strongly impact tree growth in subsequent years if the drought persists. The two years 2018 and 2019 are extreme with regard to historical instrumental data but, according to regional climate models, resemble rather normal conditions of the climate in the second half of the 21st century. Therefore the observed strongly reduced growth rates can provide an outlook on future forest growth potential in northern Central Europe and beyond.
In micro-densitometry of wood it is standard procedure to extract resin and other soluble compounds before X-ray analysis to eliminate the influence of these extractives on wood-density. Dendrochemical studies using X-ray fluorescence analysis on the other hand are commonly conducted without previous extraction. However, it is well known that translocation processes of elements during heartwood formation in trees or (temporal) differences in sap content of wood samples can influence dendrochemical element profiles. This might bias environmental signals stored in time series of element concentrations in wood proxies. We hypothesize that metals tightly bound to cell walls show a more robust proxy potential for environmental conditions than easily translocated ones. To eliminate the noise of these soluble substances in wood elemental time series, their extraction prior to analysis might be necessary. In our study we tested the effect of different solvents (water, alcohol, and acetone) and different extraction times on elemental time series of three tree species with differing wood structure (Pinus sylvestris; Quercus robur and Populus tremula). Micro-XRF analysis was conducted on nine replicates per species using an ITRAX-Multiscanner. A set of elements commonly detected in wood (S, Cl, K, Ca, Ti, Mn, Fe, and Ni) was analysed at high resolution before and after several extraction runs. Besides lowering their levels, extraction did not significantly change the temporal trends for most elements. However, for some elements, e.g., Potassium, Chlorine or Manganese, especially the water extraction led to significant decreases in concentrations and altered temporal trends. Apparently the dipole effect of water produced the strongest extraction power of all three solvents. In addition we observed a dependency of extraction intensity from wood density which differed between wood types. Our results help in interpreting and evaluating element profiles and mark a step forward in establishing dendrochemistry as a robust proxy in dendro-environmental research.
Coastal dunes near the Baltic Sea are often stabilized by Scots pine forests and are characterized by a mild climate. These ecosystems are affected by water shortages and might be influenced by climate extremes. Considering future climate change, utilizing tree rings could help assess the role of climate extremes on coastal forest growth. We used superposed epoch analysis to study Scots pine responses to droughts and cold winters, with focus on frequency, timing, and duration. We measured ring widths (RW) and latewood blue intensity (LBI) on samples extracted from trees growing at dune ridge and bottom microsites at the south Baltic Sea. At the regional scale, we observed some similarities in tree responses to both extremes between RW and LBI within the same microsite type and region. At the local scale, RW and LBI were more frequently influenced by cold winters than droughts. RW and LBI from dune ridges were more frequently influenced by droughts than RW and LBI from dune bottoms. LBI from both microsites was more often influenced by droughts than RW. RW and LBI from both microsites were similarly often influenced by cold winters. At both scales, the response time of RW and LBI after droughts predominantly lagged by one year, while cold winters were recorded in the same year. The typical duration of growth reductions after both extremes was one year for both RW and LBI. Our study indicates that Scots pine from the Baltic Sea region is sensitive to climate extremes, especially cold winters.
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.
Abstract
Aim
Climate limits the potential distribution ranges of species. Establishment and growth of individuals at range margins is assumed to be more limited by extreme events such as drought or frost events than in the centre of their range. We explore whether the growth of beech is more sensitive to drought towards the dry distribution margin and more sensitive to frost towards the cold distribution margin. Furthermore, we aim to gain insight into the adaptive potential of beech towards both the dry and cold distribution margins.
Location
European gradient from the dry (Spain) to the cold (Poland, Sweden) distribution margin of beech.
Taxon
European beech (Fagus sylvatica L.).
Methods
We applied a range‐wide dendroecological study to analyse spatial and temporal trends in climate–growth relationships. We further investigated negative growth anomalies and growth synchrony towards the range margins.
Results
We found beech to be drought sensitive across its whole range, except at the dry distribution margin. Furthermore, sensitivity to winter temperature was not found in the centre or at the cold distribution margin, but at the southern distribution margin. Growth synchrony was lower at the dry than at the cold distribution margin.
Main conclusions
Beech seems to be adapted to drought at the dry distribution margin with a high adaptive potential indicated by the lowest growth synchrony along the gradient. At the cold distribution margin, cold events in winter and spring were less important for growth than drought. Still, the importance of spring frost for beech growth appears to increase in recent decades. Considering a projected north‐eastward shift of the distribution range, beech is likely facing drought stress in combination with spring frost risk at the cold margin which could lead to a hampered range expansion.
Understanding the effects of temperature and moisture on radial growth is vital for assessing the impacts of climate change on carbon and water cycles. However, studies observing growth at sub-daily temporal scales remain scarce.
We analysed sub-daily growth dynamics and its climatic drivers recorded by point dendrometers for 35 trees of three temperate broadleaved species during the years 2015–2020. We isolated irreversible growth driven by cambial activity from the dendrometer records. Next, we compared the intra-annual growth patterns among species and delimited their climatic optima.
The growth of all species peaked at air temperatures between 12 and 16°C and vapour pressure deficit (VPD) below 0.1 kPa. Acer pseudoplatanus and Fagus sylvatica, both diffuse-porous, sustained growth under suboptimal VPD. Ring-porous Quercus robur experienced a steep decline of growth rates with reduced air humidity. This resulted in multiple irregular growth peaks of Q. robur during the year. By contrast, the growth patterns of the diffuse-porous species were always right-skewed unimodal with a peak in June between day of the year 150–170.
Intra-annual growth patterns are shaped more by VPD than temperature. The different sensitivity of radial growth to VPD is responsible for unimodal growth patterns in both diffuse-porous species and multimodal growth pattern in Q. robur.
Coastal sand dunes near the Baltic Sea are a dynamic environment marking the boundary between land and sea and oftentimes covered by Scots pine (Pinus sylvestris L.) forests. Complex climate-environmental interactions characterize these ecosystems and largely determine the productivity and state of these coastal forests. In the face of future climate change, understanding interactions between coastal tree growth and climate variability is important to promote sustainable coastal forests. In this study, we assessed the effect of microsite conditions on tree growth and the temporal and spatial variability of the relationship between climate and Scots pine growth at nine coastal sand dune sites located around the south Baltic Sea. At each site, we studied the growth of Scots pine growing at microsites located at the ridge and bottom of a dune and built a network of 18 ring-width and 18 latewood blue intensity chronologies. Across this network, we found that microsite has a minor influence on ring-width variability, basal area increment, latewood blue intensity, and climate sensitivity. However, at the local scale, microsite effects turned out to be important for growth and climate sensitivity at some sites. Correlation analysis indicated that the strength and direction of climate-growth responses for the ring-width and blue intensity chronologies were similar for climate variables over the 1903–2016 period. A strong and positive relationship between ring-width and latewood blue intensity chronologies with winter-spring temperature was detected at local and regional scales. We identified a relatively strong, positive influence of winter-spring/summer moisture availability on both tree-ring proxies. When climate-growth responses between two intervals (1903–1959, 1960–2016) were compared, the strength of growth responses to temperature and moisture availability for both proxies varied. More specifically, for the ring-width network, we identified decreasing temperature-growth responses, which is in contrast to the latewood blue intensity network, where we documented decreasing and increasing temperature-growth relationships in the north and south respectively. We conclude that coastal Scots pine forests are primarily limited by winter-spring temperature and winter-spring/summer drought despite differing microsite conditions. We detected some spatial and temporal variability in climate-growth relationships that warrant further investigation.