Here we present a protocol outlining how to sample wooden specimens for the overall assessment of their growth structures. Macro- and microscopic preparation and visualization techniques necessary to generate well-replicated and highly resolved wood anatomical and dendroecological dataset, are described are described.
Dendroecological research uses information stored in tree rings to understand how single trees and even entire forest ecosystems responded to environmental changes and to finally reconstruct such changes. This is done by analyzing growth variations back in time and correlating various plant-specific parameters to (for example) temperature records. Integrating wood anatomical parameters in these analyses would strengthen reconstructions, even down to intra-annual resolution. We therefore present a protocol on how to sample, prepare, and analyze wooden specimen for common macroscopic analyses, but also for subsequent microscopic analyses. Furthermore we introduce a potential solution for analyzing digital images generated from common small and large specimens to support time-series analyses. The protocol presents the basic steps as they currently can be used. Beyond this, there is an ongoing need for the improvement of existing techniques, and development of new techniques, to record and quantify past and ongoing environmental processes. Traditional wood anatomical research needs to be expanded to include ecological information to this field of research. This would support dendro-scientists who intend to analyze new parameters and develop new methodologies to understand the short and long term effects of specific environmental factors on the anatomy of woody plants.
Trees, as well as shrubs, dwarf shrubs, and even herbs, show manifold response patterns related to changes in their environment. These patterns have been subject to botany and plant physiology since the mid-19th century. Back then, research on woody plants focused mostly on trees and a descriptive analysis of the structure and variability of annual rings in an ecological context1. When Andrew Ellicott Douglass invented the cross-dating technique for tree-ring research2, this ecological context was more or less suppressed by the new ability to accurately date wooden findings in archaeology. Cross-dating for the first time enabled the accurate dating of tree rings to the calendar year and is until now regarded as the backbone of tree-ring research in all fields of its application1.
In parallel, since the end of the 19th century, wood anatomy evolved into an important research discipline related to many other fields of natural and applied sciences3. Two main domains are established: the systematic wood anatomy, which is the basis for identifying wood in archaeology4, and the applied wood anatomy, related to wood technology, physiology, pathology, and ecology3,5.
In tree-ring research, dendroecology nowadays is defined as a topic encompassing tree-ring related studies focusing on environmental studies such as geomorphic processes (dendrogeomorphology), temperature and precipitation reconstructions (dendroclimatology), water level changes (dendrohydrology) or even glacier fluctuations (dendroglaciology)6. As this definition indicates, tree-ring analyses have become increasingly important in the field of dating and reconstructing environmental processes such as (i) past climate conditions by analyzing annual variations in ring-width7,8, wood density9 or isotopes10, or (ii) the recurrence intervals of geomorphic processes11. These very detailed studies about ring-width variations and their isotopic content demonstrate the need to analyze rings in more detail, i.e., to study the anatomical structure of the rings. However, detailed studies of wood anatomical features within the annual rings related to environmental changes are rare12,13. Although these microscopic features are known14, they have rarely been applied on a microscopic level to dendroecological research. Furthermore, the accurate timing of these growth reactions in naturally grown trees, essential for exact dating purposes, has rarely been documented recently15.
Regarding the effects of the global warming16, the improvement of existing and development of new techniques to record and quantify past and ongoing environmental processes is required, especially in terms of climate impact research11. By expanding traditional wood anatomical research to an ecologically based wood anatomy17, dendro-scientists can analyze new parameters and develop new methodologies to understand the short- and long-term effects of specific environmental factors on the anatomy of woody plants18. Detailed knowledge about variations in different cell parameters within individual rings related to specific drivers (e.g., mechanical forces, climate variations) is the basic requirement for understanding the variability in tree ring formation. Compared to common ring-width measurements, identifying wood anatomical variations requires more complex and expansive preparation techniques that require a lot of labor and time. Detailed procedures of sample cutting, staining, and embedding are manifold and are always dependent on the aim of the study19.
For macroscopic analysis of ring width in conifers or even structures for number, size or distribution of vessels in hardwoods, the surface of a sample is commonly polished using fine abrasive paper or special grinding machines20. A disadvantage of this procedure is the filling of the individual cells with dust that prevents further semiautomatic microscopic analysis21. The best results for macroscopic sample preparation are achieved when sample surface are cut using a razor blade or another sharp knife.
While for small samples, razor blades are a perfect tool; bigger samples as cores require the cutting of plane surfaces over the whole extent of cores. In contrast to sanding, the cells are not filled with dust, which enables further preparation for the successive image analysis. Furthermore, the open cell lumen, the properly cut cell walls, and the plane surface of the entire sample enable the application of high frequency densitometry22 to the whole extent of the core. For image analyses, the surface of samples (cell walls) can be stained using dark ink and the open cell lumen can subsequently be filled with white chalk to enhance the contrast between the cell wall and the lumen area19,23. This rather simple technique enables a basic macroscopic assessment of larger cell structures for vessel size measurements.
These techniques for cutting plane surfaces are sufficient for macroscopic analyses. For a detailed wood anatomical (i.e., microscopic) analysis, transmitted light microscopy is the most common method applied in dendro sciences. Xylem cells differentiate through complex processes encompassing cell-type determination, cell division, cell differentiation, and programmed cell death24. Since the timing and rate at which these processes occur determine cell anatomical characteristics, environmental conditions affecting these processes can generate anatomical deviations in the ring structure. As an important precondition for these analyses, micro sections need to be prepared with a microtome19. When preparing samples for sectioning, the visibility of the tracheid or fiber direction is crucial. The use of hand driven sliding microtomes is recommended to cut micro sections because this technique facilitates high-quality sections as needed for image analyses19. Depending on the specific aim of a certain study, micro sections are cut perpendicular or parallel to the longitudinal extent of the cells. These sections are then photographed below a microscope and cell dimensions measured using specialized image analyses software.
Until recently, the ability to prepare micro sections was restricted to small sample sizes only (approximately 1 cm x 1 cm). This is acceptable to analyze single events as disturbances in specific years, but this technique does not allow the extended time series analysis needed for environmental reconstructions. This effort can only be realized through the development of new, efficient and economic preparation procedures and analytical techniques. In recent years, the members of the tree-ring lab at the Swiss Federal Research Institute WSL in Switzerland have started intensive work on this topic. As a result, new devices and analyzing techniques have been developed to support the idea of integrating wood anatomical features to a broad range of environmental research topics.
1. Sampling Techniques
2. Sample Preparation
3. Microslide Preparation
4. Visualizing Cell Contents
5. Preparing Digital Images of Anatomical Features
6. Quantifying Anatomical Features
All dendroecological analyses depend on accurate samples, no matter if discs, cores, or micro cores are taken. For this, the devices need to be in perfect shape (accurately sharpened) to avoid micro cracks within the wooden sample. When preparing surfaces on increment cores, the use of a core microtome is essential. The ability to have open cells, which can be further treated to enhance contrast for image analyses and vessel size measurements (Figure 1), is a first important step towards the adaption of anatomical structures into time series analyses. Sometimes the density of a hardwood sample prevents the use of a microtome. In that case a proper polishing and subsequent removal of excessive sawdust from the vessels with a compressor or vacuum is the best option.
For more detailed analyses of smaller cell structures as earlywood and latewood tracheids in conifers, high quality micro sections are needed. Here, potential artifacts such as secondary cell walls being stripped off the primary wall need to be avoided (Figure 2). If these artifacts occur in the digital images, an automated analysis of the cell dimensions is no longer possible. The artifacts then need to be manually corrected, which is time consuming and in most cases results in incorrect measurements of cell dimensions. The simple application of a Non-Newtonian fluid, i.e., a corn starch solution, to the top of the sample supports the stability of the structure while reducing the occurrence of artifacts to a minimum (Figure 2)26. This application of corn starch, suitable for all wooden samples including tropical species, makes the application of the embedding procedure to the samples before cutting redundant.
Micro sections enable a more secure determination of annual rings. This is especially the case for conifers growing on their natural limits, i.e., at the tree line in high alpine areas. Extremely narrow rings are frequent and hard to detect macroscopically (Figure 3). In extreme cases, the rings consist of one or two rows of earlywood cells and one row of flattened latewood cells, which lack (in contrast to common latewood cells) thickened cell walls. For this they are better or even only visible when using micro sections. Furthermore, density fluctuations can be differentiated from ring boundaries more clearly, which simplifies the detection of annual rings especially in the Mediterranean and the tropics (Figure 3).
When analyzing images at a magnification of 40X or higher, single cells are visible and the thickness of their cell walls is also detectable. Semi-automatic analysis software enables the measurement of specific parameters along defined paths following the direction of their temporal and spatial development (Figure 4). With this, changes of single parameters such as the cell lumen or cell wall thickness can be determined over the whole extent of an annual ring (Figure 4). This can be done for all rings visible within the image and this fully supports the need for an extended time series analysis.
Image analyses can also be used to determine the developmental phases of annual rings within the vegetation period (Figure 5). When analyzing the image of a section stained with Safranin and Astra-blue using polarized light, even the different stages of lignification, beginning in the outermost corners of the cell walls until the full lignification of the secondary cell wall, become visible. This is because the lignified (mature) cell walls shine up in polarized light (Figure 5). Detailed information can be related to environmental data documented for the respective vegetation period to determine for example a more detailed climate-growth relationship.
Figure 1. Examples of a micro section and a prepared plane surface of an oak including ring-width and vessel size measurements. Left: outermost part of an oak increment core. The 5 mm diameter core was cut using a core microtome. The surface was then stained black using a felt marker and cells were filled with white chalk after the stain was dry. Right: the graph is indicating ring-width and vessel size measurements done on the surface of the core shown on the left. No micro sections were needed to do these measurements due to the clear surface created by the core microtome (modified after21). Bottom: Micro section cut off an increment core, stained, dehydrated and fixed in Canada balsam. Thickness: 20 µm, length: 25 cm. Please click here to view a larger version of this figure.
Figure 2. Images of micro sections cut without stabilization versus a section cut using the corn starch solution. Left: Micro section showing cutting artifacts in the earlywood tracheids of a conifer. The sample was cut without embedding and as a result the rather thin secondary walls of the earlywood cells were split off the primary wall (blue arrows). Right: Micro section without any artifacts in the earlywood tracheids of a conifer. This section (same sample as shown on the left) was cut after applying the cornstarch solution with a brush on top of the sample surface. Please click here to view a larger version of this figure.
Figure 3. Examples of hardly detectable annual ring boundaries. Left: Micro section of an increment core (here: Larix decidua) showing a ring boundary (black arrow) indicated by a single row of flattened latewood cells without any thickening of the cell walls. This ring would not be visible macroscopically. Right: Intra-annual density fluctuations (white arrow) are common in Mediterranean species (micro section: Quercus ilex). The gradual change of the cell structure towards latewood and back to earlywood structure (white arrow) allows for differentiating density fluctuations from real ring boundaries (black arrow). Please click here to view a larger version of this figure.
Figure 4. Illustration of lumen area and wall thickness measurements within an annual ring of a conifer. Top: Cut-out image showing an exemplary results of ROXAS analysis in a tree-ring of Pinus sylvestris (Scots pine). Ring borders are shown in yellow and outlines of tracheid lumina in cyan. For one radial file (blue tracheid lumina) the measured cell wall thicknesses is represented by red circles. Black scale bar = 100 µm. Bottom: The intra-annual changes in tracheid lumen area and tracheid cell-wall thickness for the entire annual ring. Please click here to view a larger version of this figure.
Figure 5. Example of a forming annual ring. The image has been captured under a light microscope with polarized light from a Safranin and Astra-blue stained micro-section obtained from a micro-core sampled on July 7th, 2007 from a Larix decidua growing in the Lötschental at 1,300 m above sea level. On this micro-section the cambial cells, the cells in the enlargement phase, the cells in the wall thickening phase and the mature cells are recognizable. The tangential width of the image covers ~1 mm of the xylem cross-section. Please click here to view a larger version of this figure.
The challenges of a successful and sustainable integration of wood anatomy into dendroecological research are, apart from manifold analytical problems, mostly due to technical aspects. These challenges range from principle sampling approaches to creating high quality micro sections and their subsequent analysis19.
At first glance, the sampling of cores or even discs is a simple procedure that has been known for many years now. There are many things that can be done wrong and a small inaccuracy in sampling can result in severe problems during the subsequent preparation and analysis phases. Small inaccuracies such as coring that is not exactly perpendicular to the stem axis or using an imperfectly sharpened corer are not an issue if the aim of the study is restricted to ring-width measurements. However, when aiming for microscopic analysis of the samples, an incorrect sampling direction might result in optical distortions of cell walls, while the use of blunt corers results in micro cracks within the core. As a result, when trying to cut micro sections of these cores, the thin sections just fall apart and an efficient preparation is no longer guaranteed. The same is true for micro-core sampling. A blunt tip will result in high pressure when the puncher is hammered into the stem wood. Consequently the cambial layer will be compressed. The cambial cells (Figure 5) are consequently squeezed and cannot be analyzed.
Disc sampling is indeed the best strategy when analyzing growth variations to relate them to environmental changes. Unfortunately it is simply impossible to take discs from all trees intended to be sampled for further analyses. Nevertheless, especially in case of tropical dendrochronology, a certain amount of stem disks is needed in combination with increment cores. The disks are used as a base to define ring boundaries and for this to support the boundaries defined based on analyzing increment cores12,27,28.
The pros and cons of sanding versus cutting are frequently discussed1,11,21. As it is mentioned above, the best procedure always depends on the research question and the parameters to be analyzed (macroscopic or microscopic). If isotopic or chemical analyses are projected in a further working step, it is of utmost importance that the abrasive dust created by sanding that may fill into cell lumina over the entire sample, is carefully removed by vacuuming or pressure air.
Cutting micro sections is for all microscopic analyses the most appropriate way of preparing samples for further analyses. First of all, the section is cut off the sample, which then can be kept without any contamination for potential further analyses. Second these sections allow for high resolution measurements of single cell parameters. Furthermore, avoiding the time consuming embedding technique by using a cornstarch solution26 to stabilize the cells is a big advantage in micro sectioning.
A disadvantage of micro sectioning is still the limited sample size resulting in long preparation times. For real time series analyses going back in time over centuries or even millennia, there is a need to further develop existing cutting devices17,19, but also image processing and analysis18. A first step into this direction is the development of the core microtome21, initially manufactured to cut plane surfaces on cores (Figure 1). Recent tests revealed the ability to cut micro sections of entire cores using this device (Figure 1).
High quality micro sections provide the basic principle for an effective image analysis. Taking the images under a microscope is a common procedure19, but their effective analysis is still a task that needs to be further developed17. All existing image analysis systems are semi-automatic, i.e., they need to be more or less intensely controlled by the technician. In many cases, the images need to be corrected or even new images have to be done to enhance contrast for a better registration of the structures by the software without changing cell wall thickness within the image.
Specialized image analysis tools such as ROXAS18, WinCell or specific scripts for ImageJ29 are able to provide basic anatomical data such as cell number, cell dimension, cell wall thickness and cell position within the annual ring. Many additional anatomical metrics that are relevant in a dendroecological context can be calculated from these basic measurements such as size of the largest conduits, size distribution of conduits, size of earlywood or the first row of conduits, (optical) wood density, intra-annual profiles of conduit size and cell wall thickness, and grouping patterns of conduits (solitary, multiples, etc.).
Using the software ROXAS18, the outlines of conduit lumina (i.e., water conducting cell) and annual ring borders are automatically recognized and visually represented as overlays over the original image. Detection algorithms for conduits are based on color, size and shape information, detection algorithms for ring borders on the local context of each conduit. A toolbox allows us to manually improve these results by directly editing the overlay features, i.e., deleting, adding and modifying ring borders and conduit outlines. After editing, the final data output, including cell wall thickness (conifers), is automatically generated and saved into a spreadsheet. Fully automated systems are currently not available, not even for conifers showing a relatively simple structure, but this is a goal for future developments. This would strongly support the full integration of wood anatomical parameters in time series analyses.
The authors have nothing to disclose.
The authors would like to acknowledge the effort of Sandro Lucchinetti (Schenkung Dapples, Zürich) for constructing the devices needed to guarantee progress in sample preparation.
Increment corer | http://www.haglofinc.com/index.php?option=com_content&view=article &id=57&Itemid=88&lang=en |
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Core-Microtome | http://www.wsl.ch/dendro/products/microtomes/index_EN | ||
Laboratory microtome | http://www.wsl.ch/dendro/products/microtomes/index_EN | ||
Trephor micro corer | http://intra.tesaf.unipd.it/Sanvito/trephorEn.asp | ||
Nawashin solution | Ten parts 1% chromic acid, four parts 4% formaldehyde and one part acetic acid | ||
Picric-Anilin blue | One part saturated aniline blue and four parts Trinitrophenol dissolved in 95% ethanol | ||
Safranin | Empirical Formula (Hill Notation) C20H19ClN4 | ||
Astra-blue | Empirical Formula (Hill Notation) C47H52CuN14O6S3 | ||
Ethanol | Linear Formula CH3CH2OH | ||
Xylol (Xylene) | Linear Formula C6H4(CH3)2 | ||
Canada Balsam | Embedding solution for microscopy | ||
Roxas Software | http://www.wsl.ch/dienstleistungen/produkte/software/roxas/index_EN | ||
ImageJ Software | http://imagej.nih.gov/ij/ | ||
WinCell | http://imagej.nih.gov/ij/ |