X-ray CT scanning can boost tree-ring research

A new technique to scan tree rings offers to yield precious new data on past climates.

You may have learned as a child that each year a tree grows a new ring around its core, and you can age a tree stump by counting the rings. There’s much more data in a tree ring than that. The size and properties of that ring can provide data on the climate that year. Effectively trees can be climate recorders, keeping a literal log of data. A new technique based on advanced X-ray CT scanning developed by Professor Jan Van den Bulcke and colleagues could provide better access to that data than ever.

CT, in this case, stands for computed tomography. Scientists scan a sample at different angles and then put the results together to create 3D images, that can also be visualised as cross-section slices through the sample. It’s as if someone could ‘fly’ through the digital volume. Van den Bulcke and colleagues have created a better imaging system by producing a scanning system that works at multiple scales and at a higher resolution than before.

It might seem that multiple scales is a peculiar approach. Why not scan at the highest resolution? As Van den Bulcke explained, this is not a practical solution. “Obviously, scanning everything at the finest resolution is what everyone wants. However, the time to scan an entire object and the final data volumes scale when you increase the resolution. Furthermore, resolution is also limited by object size: it is not possible to have a large object, let us say 10 cm in diameter, scanned at submicron resolution. Scanning everything at the finest resolution might also be inefficient. It is beneficial to scan at a lower resolution, for instance for tree-ring analysis, and then zoom in on interesting anatomical details on sections of cores, such as specific years, based on this first analysis.”

Scan of a Scots pine increment core, from core to rings down into individual earlywood cell level. Image by Van den Bulcke et al. 2019.

The technique has been honed on a variety species. “We took a variety of species that are commonly studied in paleoclimatology such as Scots pine (Pinus sylvestris), with the Maximum Latewood Density (MXD) as the most sensitive proxy for climate reconstructions,” Van den Bulcke said. “We also examined species where anatomy can serve as a proxy for climate or reveal ecological information on the tree, or species where tree rings are being studied in forest management, such as oak species (Quercus sp.), common beech (Fagus sylvatica) and European white birch (Betula pendula). The main idea was to show that any type of woody species can be handled and to relate to well-known and commonly studied species.”

Being able to look at any species with rings is vital, as not all trees produce rings the same way. Van den Bulcke’s team have been scanning difficult samples to test their system. “We originally applied X-ray CT on tropical angiosperm trees from the Congo Basin, which have a challenging tree ring structure due to lower seasonality. Any sample is possible, moving from the tropics all the way up to regions where trees or shrubs grow at their outermost limits: Rhododendron samples from the Tibetan Plateau, for instance, could be scanned as well. Of course, whether or not tree-ring boundaries (i.e. the zone in the wood where the ring of that year ends and a new ring of the next year begins) can be discerned, depends on the species, more specifically the type of anatomical feature that is determining this boundary and which resolution that is needed to visualize that boundary. Further, the actual time series will depend on the cross-dating quality, and that is dependent on the region/site where the samples were scanned.”

Tackling cross-dating is a problem that the team have already been working on. A pattern of a series of years could be like a barcode in the tree ring. Find a match in barcodes for two samples, and you can put them together to build a longer climate record. However, width data is just part of the sample. The X-ray CT scanning also allows measurements of density in order to build more secure matches between samples.

Van den Bulcke is looking forward to the new research multiscale X-ray CT scanning can make possible. “Currently, MXD data are quite tedious to generate. A large part of the current MXD-based temperature reconstructions end around the 1980’s and 1990’s and are not sufficiently updated yet. It would be most interesting to revisit some of the trees that were sampled in that era and update them with the last 20-30 years, an era with significant climatic change. Moreover, while there is a dense network of tree-ring width chronologies in the International Tree-Ring Databank, the number of MXD chronologies is lower, partly due to the limited number of classic densitometry facilities and the sample preparation steps. Especially, the Southern Hemisphere has very few MXD series to date. X-ray CT allows to indicate tree ring boundaries and derive MXD series in a very fast way.”

“As our current set-up allows for anatomical measurements on subsections, machine learning algorithms that are used on sanded or micro sections can help to semi-automatically indicate tissue fractions on 3D images, thus also reducing the time spent in the lab, while increasing sample size. It would be very much complementary to the conventional approach, since X-ray CT volumes allow to exploit the 3D nature of the virtual volume, which has not been exploited much so far. Nevertheless, to have an efficient workflow from sample to data, there is still work to be done.”

Another advantage of this method is that the data that comes in depends on how the sample has been prepared. “Our original aim was to avoid difficulties such as preparing samples for scanning and to increase the sample size.” Van den Bulcke said. “Traditionally, cores for tree-ring analysis are mounted on a support. Small diameter cores are therefore difficult to use in a classic densitometry set-up because they need to be precisely sawn to a thin section, perpendicular to the grain, which causes the sample to be somewhat destroyed thereafter.”

As you can prevent samples from being damaged, then many more samples become feasible for study, Van den Bulcke said. “Unlike traditional densitometry, an X-ray CT scanner can scan mounted samples from collections thus would be very well suited for scanning old samples. Of course, it is still better to have samples that haven’t been mounted at all.”

One of the interesting comments in the paper is that there would be advantages to the plant science community as a whole, if there were a centralised scanning facility. “With an optimized system, a high number of cores could be scanned on a yearly basis,” Van den Bulcke said. “Although in the future several X-ray CT systems could exist for this purpose, we can imagine that still groups would like to rely on an existing facility rather than having to acquire an X-ray CT machine themselves. It should be noted that if in the near future this kind of scanning would become a routine business, of course one single X-ray CT machine could not handle all requests.” Van den Bulcke also believes that having a few facilities would aid reproducibility in scanning, by having ongoing routines for scans. It would also enable reliable access to essential expertise. “Close collaboration with a team of X-ray physicists allows proper control of all steps of the toolchain,” he added.

Van den Bulcke sees many opportunities for the use of X-ray CT scanning in current studies. “X-ray CT scanning has been used in many different research domains for 3D analysis. 4D, time-resolved scanning, is very much in focus as well nowadays, for instance in cavitation research. Basically any researcher interested in the 3D hierarchical structure of a material in need for non-destructive imaging, could take some valuable information from this research, especially when it is plant-based. In some cases, e.g. for non-woody plants, like Arabidopsis the biological material under study should be pre-treated properly.”

While there are plenty of potential new discoveries to be made, there is still plenty of data to refine, Van den Bulcke said. “Among others, there is a need to update current MXD chronologies, both spatially and temporally. This requires new field campaigns. However, also current collections around the world that have samples, can be re-analyzed for MXD in a non-destructive way. Furthermore, the opportunities to exploit X-ray CT imagery at an anatomical level offer new perspectives in wood anatomy, for ecological studies in tree mortality, cavitation etc.”

“While the technique has existed for several decades, X-ray CT machines are now capable of contributing to the era of large data with a resolution and flexibility that is only feasible since the last decade or so. Still, work needs to be done to optimize toolchains tailored to tree-ring/wood anatomical research and especially efficient data handling is a challenge. Considering non-tree materials, there are also marine proxies such as sea shells that can be treated similarly as we present in this paper.”

Further reading

Black, B. A., Andersson, C., Butler, P. G., Carroll, M. L., DeLong, K. L., Reynolds, D. J., … Witbaard, R. (2019). The revolution of crossdating in marine palaeoecology and palaeoclimatology. Biology Letters, 15(1), 20180665. https://doi.org/10.1098/rsbl.2018.0665

De Mil, T., Vannoppen, A., Beeckman, H., Van Acker, J., & Van den Bulcke, J. (2016). A field-to-desktop toolchain for X-ray CT densitometry enables tree ring analysis. Annals of Botany, 117(7), 1187–1196. https://doi.org/10.1093/aob/mcw063

De Mil, T., Tarelkin, Y., Hahn, S., Hubau, W., Deklerck, V., Debeir, O., … Van den Bulcke, J. (2018). Wood Density Profiles and Their Corresponding Tissue Fractions in Tropical Angiosperm Trees. Forests, 9(12), 763. https://doi.org/10.3390/f9120763

Dhondt, S., Vanhaeren, H., Van Loo, D., Cnudde, V., & Inzé, D. (2010). Plant structure visualization by high-resolution X-ray computed tomography. Trends in Plant Science, 15(8), 419–422. https://doi.org/10.1016/j.tplants.2010.05.002

Lamarque, L. J., Corso, D., Torres-Ruiz, J. M., Badel, E., Brodribb, T. J., Burlett, R., … Delzon, S. (2018). An inconvenient truth about xylem resistance to embolism in the model species for refilling Laurus nobilis L. Annals of Forest Science, 75(3). https://doi.org/10.1007/s13595-018-0768-9

St. George, S., & Esper, J. (2019). Concord and discord among Northern Hemisphere paleotemperature reconstructions from tree rings. Quaternary Science Reviews, 203, 278–281. https://doi.org/10.1016/j.quascirev.2018.11.013

Van den Bulcke, J., Boone, M. A., Dhaene, J., Loo, D. V., Hoorebeke, L. V., Boone, M. N., … De Mil, T. (2019). Advanced X-ray CT scanning can boost tree-ring research for earth-system sciences. Annals of Botany. https://doi.org/10.1093/aob/mcz126