Earth system models and various climate proxy sources indicate global warming is unprecedented during at least the Common Era
. However, tree-ring proxies often estimate temperatures during the ...Medieval Climate Anomaly (950-1250 CE) that are similar to, or exceed, those recorded for the past century
, in contrast to simulation experiments at regional scales
. This not only calls into question the reliability of models and proxies but also contributes to uncertainty in future climate projections
. Here we show that the current climate of the Fennoscandian Peninsula is substantially warmer than that of the medieval period. This highlights the dominant role of anthropogenic forcing in climate warming even at the regional scale, thereby reconciling inconsistencies between reconstructions and model simulations. We used an annually resolved 1,170-year-long tree-ring record that relies exclusively on tracheid anatomical measurements from Pinus sylvestris trees, providing high-fidelity measurements of instrumental temperature variability during the warm season. We therefore call for the construction of more such millennia-long records to further improve our understanding and reduce uncertainties around historical and future climate change at inter-regional and eventually global scales.
Many microdensitometric techniques are available for deriving maximum latewood density (MXD), which is the state-of-the-art proxy parameter for local to hemispheric-scale temperature reconstructions ...of the last millennium. Techniques based on X-ray radiation and visible light reflection, such as “blue intensity” (BI), integrate both the density/composition and the dimensions of the cell walls to derive microdensitometric data. In contrast, the dendroanatomical technique relies only on the dimensions of the cell walls. It is therefore possible to isolate cell wall variables by subtracting data derived using the dendroanatomical technique from data derived using X-ray and BI-based techniques.
In this study, we explore differences in well-replicated data from parallel X-ray, BI, and dendroanatomical measurements of temperature-sensitive Pinus sylvestris trees from northern Finland. We aim to determine whether cell wall density is critical to the success of X-ray-based MXD, and whether the BI-based parameter counterpart, here termed MXBI, contains useful information about the composition of the cell wall (specifically the lignin).
Our results indicate that cell wall density and cell wall BI have no relevant influence on MXD and MXBI measurements. Even in years with severely reduced lignification, identified as so-called “blue rings”, dendroanatomical MXD (aMXD) measurements do not deviate significantly from their MXD or MXBI counterparts. Moreover, derived chronologies of cell wall density and cell wall BI contain no significant climate signals when correlated with local climate. Maximum latewood density of conifers can thus be obtained without bias using the dendroanatomical technique. Because lignin content appears to play a negligible role for cell wall BI, the cell wall BI likely presents the biggest challenge when producing unbiased MXBI data. This is because BI data is notorious for cell wall color distortion across the heartwood and sapwood, and between living wood and dead wood, and may therefore distort the otherwise strong link with wood density on multidecadal scales.
Despite the spatially homogenous summer temperature pattern in Fennoscandia, there are large spreads among the many existing reconstructions, resulting in an uncertainty in the timing and amplitude ...of past changes. Also, there has been a general bias towards northernmost Fennoscandia. In an attempt to provide a more spatially coherent view of summer (June–August, JJA) temperature variability within the last millennium, we utilized seven density and three blue intensity Scots pine (
Pinus sylvestris
L.) chronologies collected from the altitudinal (Scandinavian Mountains) and latitudinal (northernmost part) treeline. To attain a JJA temperature signal as strong as possible, as well as preserving multicentury-scale variability, we used a new tree-ring parameter, where the earlywood information is removed from the maximum density and blue intensity, and a modified signal-free standardization method. Two skilful reconstructions for the period 1100–2006 CE were made, one regional reconstruction based on an average of the chronologies, and one field (gridded) reconstruction. The new reconstructions were shown to have much improved spatial representations compared to those based on data from only northern sites, thus making it more valid for the whole region. An examination of some of the forcings of JJA mean temperatures in the region shows an association with sea-surface temperature over the eastern North Atlantic, but also the subpolar and subtropical gyres. Moreover, using Superposed Epoch Analysis, a significant cooling in the year following a volcanic eruption was noted, and for the largest explosive eruptions, the effect could remain for up to 4 years. This new improved reconstruction provides a mean to reinforce our understanding of forcings on summer temperatures in the North European sector.
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.
Hydroclimatological extremes, such as droughts and floods, are expected to increase in frequency and intensity with global climate change. An improved knowledge of its natural variability and the ...underlying physical mechanisms for changes in the hydrological cycle will help understand the response of extreme hydroclimatic events to climate warming. This study presents the first gridded hydroclimatic reconstruction (0.5° × 0.5° grid resolution), as expressed by the warm season Standardized Precipitation Evapotranspiration Index (SPEI), for most of Fennoscandia. A point-by-point regression approach is used to develop the reconstruction from a network of moisture sensitive tree-ring chronologies spanning over the past millennium. The reconstruction gives a unique opportunity to examine the frequency, severity, persistence, and spatial characteristics of Fennoscandian hydroclimatic variability in the context of the last 1,000 years. The full SPEI reconstruction highlights the seventeenth century as a period of frequent severe and widespread hydroclimatic anomalies. Although some severe extremes have occurred locally throughout the domain over the fifteenth and sixteenth centuries, the period is surprisingly free from any spatially extensive anomalies. The twentieth century is not anomalous in terms of the number of severe and spatially extensive hydro climatic extremes in the context of the last millennium. Principle component analysis reveals that there are two dominant modes of spatial moisture variability across Fennoscandia. The same patterns are evident in the observational record and in the reconstructed dataset over the instrumental era and two paleoperiods. The 500 mb pressure patterns associated with the two modes suggests the importance of the summer North Atlantic Oscillation.
The inexpensive Blue Intensity proxy has been considered a complement or surrogate to maximum latewood density (MXD), but is associated with biases from differential staining between sapwood and ...heartwood and also between deadwood samples and living-wood samples that compromise centennial-scale information. Here, we show that, with some minor adjustments, ΔBlue Intensity (ΔBI) is comparable with MXD or ΔDensity (Δ = the difference or contrast between latewood and earlywood density) in dendroclimatological reconstructions of summer temperatures in the Central Scandinavian region, using Pinus sylvestris L. (Scots pine), on annual and multi-centennial timescales. By using ΔBI, this bias is significantly reduced, but the contrast between earlywood and latewood in BI is altered with degree of staining, while for density it is not. Darker deadwood samples have a reduced contrast compared with the lighter living-wood samples that make ΔBI and ΔDensity chronologies diverge. Here, we quantify this behaviour in BI and offer an adjustment that can reduce this bias. The adjustment can be derived on independent samples, so in future work on BI, parallel density measurements are not necessary. We apply this methodology to two Central Scandinavian Scots pine chronologies that averaged into a composite is able to reconstruct summer temperatures with an explained variance in excess of 60% in each verification period using a split sample calibration verification procedure. Although the amount of data used to derive this contrast adjustment produces desirable results, more tests are needed to confirm its performance, and we suggest that future work on the BI proxy should aim for a small subset of parallel BI and density measurements while the bulk of the data is only measured with the BI technique. This is to ensure that the adjustment is continuously updated with new data and that the conclusions derived here are robust.
Blue intensity (BI) from tree rings is a technique that has been widely explored for temperature reconstruction purposes in middle and high latitudes. However, it is still rather untested at lower ...latitudes and in drier climates, particularly in subtropical areas. Here, we develop the first series of BI-based tree-ring parameters (earlywood BI, EWBI; latewood BI, LWBI and ΔBI, the difference between LWBI and EWBI) in humid subtropical China from the species Pinus massiniana. Although the BI parameters have weaker inter-series correlations than do ring widths, they are generally better correlated with climate parameters. Our study shows a positive temperature response in the EWBI parameter and negative responses in the LWBI and ΔBI parameters. Interestingly, the correlation pattern is almost the opposite of that observed at high latitudes, where there is a pronounced positive sensitivity of the LWBI/ΔBI/MXBI parameters to temperature.
We find the EWBI to be the most robust parameter for reconstruction purposes. The positive March–May average temperature signal of EWBI is stable across frequencies and shows consistent interdecadal variations with other temperature proxy series from the region. The compilation of new tree-ring records using the BI technique will ultimately support our understanding of climate history. For this reason, we encourage similar attempts to push the boundaries of the BI technique even further.
The continuous development of new proxies as well as a refinement of
existing tools are key to advances in paleoclimate research and improvements
in the accuracy of existing climate reconstructions. ...Herein, we build on
recent methodological progress in dendroanatomy, the analyses of wood
anatomical parameters in dated tree rings, and introduce the longest (1585–2014 CE) dendroanatomical dataset currently developed for North America.
We explore the potential of dendroanatomy of high-elevation Engelmann spruce
(Picea engelmannii) as a proxy of past temperatures by measuring anatomical cell dimensions
of 15 living trees from the Columbia Icefield area. X-ray maximum latewood
density (MXD) and its blue intensity counterpart (MXBI) have previously been
measured, allowing comparison between the different parameters. Our findings
highlight anatomical MXD and maximum radial cell wall thickness as the two
most promising wood anatomical proxy parameters for past temperatures, each
explaining 46 % and 49 %, respectively, of detrended instrumental
July–August maximum temperatures over the 1901–1994 period. While both
parameters display comparable climatic imprinting at higher frequencies to
X-ray derived MXD, the anatomical dataset distinguishes itself from its
predecessors by providing the most temporally stable warm season temperature signal. Further studies, including samples from more diverse age cohorts and the adaptation of the regional curve standardization method, are needed to disentangle the ontogenetic and climatic components of long-term signals stored in the wood anatomical traits and to more comprehensively evaluate the potential contribution of this new dataset to paleoclimate research.
Despite the emergence of new high-resolution temperature reconstructions around the world, only a few cover the Medieval Climate Anomaly (MCA). Here we present C-Scan, a new Scots pine tree-ring ...density-based reconstruction of warm-season (April–September) temperatures for central Scandinavia back to 850 CE, extending the previous reconstruction by 250 years. C-Scan is based on samples collected in a confined mountain region, adjusted for their differences in altitude and local environment, and standardised using the new RSFi algorithm to preserve low-frequency signals. In C-Scan, the warm peak of MCA occurs ca. 1000–1100 CE, and the Little Ice Age (LIA) between 1550 and 1900 CE. Moreover, during the last millennium the coldest decades are found around 1600 CE, and the warmest 10 and 30 years occur in the most recent century. By comparing C-Scan with other millennium-long temperature reconstructions from Fennoscandia, regional differences in multi-decadal temperature variability, especially during the warm period of the last millennium are revealed. Although these differences could be due to methodological reasons, they may indicate asynchronous warming patterns across Fennoscandia. Further investigation of these regional differences and the reasons and mechanisms behind them are needed.
Bulk wood density measurements are recognized for their utility in ecology, industry, and biomass estimations. In tree-ring research, microdensitometric techniques are widely used, but their ability ...to determine the correct central tendency has been questioned. Though rarely used, it may be possible to use bulk wood density as a tool to check the accuracy of and even correct microdensitometric measurements. Since measuring bulk wood density in parallel with X-ray densitometry is quickly and easily done, we suspect that its omission is largely due to a lack of awareness of the procedure and/or its importance. In this study, we describe a simple protocol for measuring bulk wood density tailored for tree-ring researchers and demonstrate a few possible applications. To implement real-world examples of the applications, we used a sample of existing X-ray and Blue Intensity (BI) measurements from 127 living and dead Pinus sylvestris trees from northern Sweden to produce new measurements of bulk wood density.
We can confirm that the central tendency in this sample material is offset using X-ray densitometry and that the diagnosis and correction of X-ray density is easily done using bulk wood density in linear transfer functions. However, this approach was not suitable for our BI measurements due to heavy discoloration. Nevertheless, we were able to use bulk wood density to diagnose and improve the use of deltaBI (latewood BI – earlywood BI) with regard to its overall trends and multi-centennial variability in a dendroclimatological application. Moreover, we experimented with percent of latewood width, scaled with bulk wood density, as a time- and cost-effective proxy for annual ring density. Although our reconstruction only explains about half of the variation in ring density, it is most likely superior to using fixed literature values of density in allometric equations aimed at biomass estimations.
With this study, we hope to raise new awareness regarding the versatility and importance of bulk wood density for dendrochronology by demonstrating its simplicity, relevance, and applicability.
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