Software to Analyze Tree Rings. 'WinDENDRO is a semiautomatic image analysis system specifically designed for tree-ring measurement.' A comparison of two techniques for measuring and crossdating tree rings. These software programs serve as a sec.

• Dendrochronologia
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Non Technical Summary This proposal falls primarily within priority area 1 (foundation areas of knowledge) for McIntire-Stennis funding. To a lesser extent, it also falls within priority areas 2a (multi-state projects), 2b (forest ecosystem services), and 2d (uncertainty and decision making). Much research focuses on describing differences in species distributions, with a recent focus on distribution changes associated with a changing climate; (Shafer et al. 2001; Parmesan and Yohe 2003; Pearson et al. 2004; McKenney et al. Climate change will greatly affect the management of forest ecosystems, so understanding and predicting these changes is of significant practical concern (Millar et al.

This proposal uses Garry oak (Quercus garryana) as a model species to examine controls on species distribution. Garry oak is the most drought tolerant tree species in western Washington (Van Pelt 2007), allowing it to colonize areas that will not support more water-dependent conifers. Although it benefits from increased water availability, and can even tolerate periodic flooding, it is generally outcompeted on high productivity sites (Stein 1990). As a result, Garry oak is often found in narrow bands between areas with enough water to support conifers and areas with too little water to support trees, such as prairies and shrub steppe (Figure 1). This narrow ecotone suggests that changes in spatial distribution over time should be particularly detectable in Garry oak (Risser 1995). Project Methods During summer 2008, we obtained 400 cores from Garry oak trees in 4 stands in central Washington. Stands are located on a riparian bench and an upland slope at each of Swauk Creek valley and the Tieton River valley.

We will age these cores to quantify the stand age structures. Cores will be processed using conventional methods (Stokes and Smiley 1968) and scanned and analyzed using WinDendro software ($10,000 new; already owned by my lab). For cores that missed the pith, we will estimate the number of years between the inner ring of the core and the pith using Applequist's (1958) method. The height at which each core was taken was noted during sampling (average was 40 cm). To account for the time required for a Garry oak seedling to grow to this height, we will destructively sample five seedlings (1-1.4 m tall) per stand and age these seedlings at the root collar and in 5 cm height increments (Gutsell and Johnson 2002). Since we will be using a small sample size to establish these site-specific height-growth curves, we will adjust them based on curves developed for Garry oak in western Washington (Kertis 1986).

The WinDendro analyses will provide an age and a ring-width chronology for each tree. We will compare age distributions among stands to identify differences in stand history such as recruitment patterns (distinct cohorts vs continuous establishment). We will also integrate the age data with extant spatial data to analyze relationships between age and spatial pattern.

The spatial distribution of oaks will be compared to random, even and clumped distributions using a K statistic (Loosmore and Ford 2006); these comparisons will also be made for oaks within discrete age classes. We will use a spline correlogram to test for positive or negative spatial correlation between oaks of different ages (Bjornstad and Falck 2001).

We will use the ring-width chronology to identify release events, detected as increases in growth rates in spatially aggregated trees without simultaneous growth increases in other trees in the stand (Winter et al. Based on our findings concerning stand history and current stand health, we will develop recommendations regarding the spacing, density, and timing of planting during Garry oak restoration activities. We will also identify restoration treatments that are likely to promote tree growth, cavity formation, and use by wildlife species within maturing oak stands. Progress 10/01/08 to 09/30/09 Outputs OUTPUTS: We have prepared reports for most land managers summarizing our plot characteristic data, vegetation data, and Garry oak seedling density by size class.

The reports also include written and graphical information on how their stand compared with the others. Two undergraduate students received training in the implementation and analysis of research projects, presentation of research results, and report preparation. PARTICIPANTS: Key participants were Laura Blume (graduate student), Conor OMalley (undergraduate student), Scott Batiuk (undergraduate student), and Jonathan Bakker (faculty advisor). This project provided training in dendrochronology and implementation, analysis, and presentation of a research project to two undergraduates (OMalley and Batiuk). TARGET AUDIENCES: Our target audiences are those that are managing lands with existing Garry oak stands. We are interested in improving understanding of how to ensure continued regeneration of Garry oaks to replace older trees as they die, without developing overly dense stands. Our research is particularly useful to those managing the very lands where we did our research, including government agencies, a university, and an indigenous Nation.

PROJECT MODIFICATIONS: Although we initially intended to select sites that were similar to each other, controlling variables such as slope, elevation, and vegetative cover, we found that the typical Garry oak stand characteristics varied substantially throughout the state of Washington, and we were unable to fully control for these variables. This left us with about as many predictive variables as experimental units, and little power to test variables independently. We also found our proposed methods to be overly time consuming, and therefore only collected and aged seedlings at a subset of sites so we could assess seedling densities at more sites. With regard to seedling densities, this project served as a pilot study identifying possible trends which may best be further addressed individually or even experimentally on smaller geographic scales.

Dendrochronologia

Impacts We collected data on Garry oak (Quercus garryana) regeneration in 16 Garry oak stands throughout Washington state. We sampled 2-4 plots per stand. We also aged trees and destructively sampled seedlings at a subset of the stands. This project increased our understanding of the complex interactions among factors affecting regeneration. Unfortunately, the small sample size together with the high variability in seedling densities resulted in few statistically significant findings. Garry oak seedling densities were significantly higher east of the Cascades than west of the Cascades; this broadly agrees with the predicted bioclimatic envelope for future conditions favoring Garry oak. Seedling densities were higher in southern parts of the state.

Small seedlings (under 1 m tall) were most abundant at mid elevations, while large individuals (over 1 m tall and under 4 cm dbh) were most abundant at the highest elevations. Slope gradient limited seedling density; plots on slopes over 40% never had over about 15,000 small seedlings per hectare or over about 1,000 large seedlings per hectare. Small seedlings were more likely to be found at high densities with high canopy cover, but large individuals were more dense at low canopy cover. This finding suggests that although Garry oak seedlings can establish more easily under a canopy where there is relatively low herb and shrub cover, in order to persist and grow, they do best without an overtopping tree canopy. Dendrochronological analyses demonstrated that age and dbh were correlated at some sites but not at others.

Seedling height and tree radial growth rates are much greater west than east of the Cascades, but regeneration has occurred more recently in stands east of the Cascades. Trees in riparian areas had faster radial growth rates than those in upslope areas. Seedling age and height are correlated, though the strength of this correlation varied among sites. Publications. Batiuk, S. Analysis of the relationship between age and diameter at breast height of Garry oak (Quercus garryana) in Washington state. Environmental Science and Resource Management capstone senior thesis, School of Forest Resources, University of Washington, Seattle, WA.

OMalley, C. Using stem analysis to evaluate seedling dynamics in Quercus garryana. Unpublished research paper. School of Forest Resources, University of Washington, Seattle, WA.

The first step of tree-ring analysis is image acquisition. WinDENDRO has been designed and is optimised for optical scanners but can also analyse images from cameras and digital filmless x-ray systems. It can open image files produced by these hardware manufacturers programs (provided they are saved in a standard format such as jpeg or tiff), but most of the time WinDENDRO is used to acquire images directly from such devices (when they are TWAIN compatible.). Optical scanners are particularly well adapted for tree-rings analysis. They produce high quality images over large areas.

WinDENDRO deals with scanners in a very efficient way. It has two methods of image acquisition for them, one is optimised for ease of use and requires just a mouse click to get an image.

Time is saved in bypassing the standard 'Preview' step (which can take tens of seconds per sample) and by using positioning accessories which allows to repetitively place the samples at the right place on the scanner. The other scanning method is more complex and powerful, it uses the Preview step to optimise the scanning parameters. Regent’s optional core holder and positioning system eases and accelerates cores scanning by allowing the operator to rapidly position the samples at the same place on the scanner glass (thus eliminating the need to preview before a scan) and allows manipulation of cores during their preparation.

This system can be rapidly added or removed at any time. Disks are placed face down on the scanner for image acquisition.

You can scan the whole disk (although this takes huge amounts of memory) or you can scan narrow paths, a few millimeters or centimeters in width, from pith to bark. A scan typically takes between 10 and 60 seconds to complete depending on the image size (scan area and resolution). Note that scanning whole disks or using very high dpi (such as 2400 or more) will take more time (and a fast computer with plenty of memory). Right after scanning, the image is displayed on screen.

Most scanners on the market have their scan area glass lower than the plastic surrounding it. Large samples are not in contact with the glass everywhere. Although WinDENDRO can work with most TWAIN compatible scanners, we do not guarantee it will support all functionalities for all models. Our simple interface is guaranteed to work only with the models we sell. Our scanners also come with a calibration for higher precision.

To learn more about sample preparation required for scanning and WinDENDRO see the note next. After image acquisition, you indicate WinDENDRO where to measure rings in the image.

This is done by tracing paths interactively. Straight line paths (such as those extending from a disk pith to bark) can be created automatically with a single mouse click (up to a few hundreds in a single click). More complex shape paths (see below) are created manually by clicking at different places. In its simplest form a path can run across a sample (core or disk radius) on a straight line. Hundreds of paths can be created with a single mouse click in pre-defined directions around the clicked position. Paths can also be created by clicking at their beginning and ending points.

You can trace paths with a perpendicular trajectory to ring boundaries (as in manual dendrochronological measurement methods). Paths may contain discontinuities to avoid damaged areas in order to move perpendicular to ring boundaries. Ring-widths can be measured taking into account their boundary orientation relative to the path. This allows to increase the precision when using straight paths (to achieve similar results as to path made perpendicular to ring widths). One or more cores can be analysed per image.

In this example multiple cores have been scanned side by side to save scanning time. They are then analysed in the same image by clicking their respective beginning and ending (for curved cores intermediary clicks are required). After paths have been created, rings are automatically detected by WinDENDRO and their presence is indicated over the image with lines and text. Lines indicate the rings boundary position and orientation and the text indicates the year and ring number. Earlywood width can also be displayed along with other ring features (explained next). Close to the image, a profile of the light variations inside the path is also displayed along with ring and earlywood widths. This region is also used to adjust the sensitivity of the automatic ring detection.

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The sensitivity of this initial detection can be adjusted in function of the rings appearance. Narrow and low contrasts rings require more attention.

One or two methods of ring detection are provided in function of the WinDENDRO software model. The first method is based on light intensity differences. It is simple, efficient and works fine for contrasted rings like those of conifers. The other ring detection method is called Teach & Show and is a method where you show to WinDENDRO what a tree ring is in the image so that it can automatically detect them after. This method is more computer intensive and is well adapted for low contrasted rings like those of deciduous trees. There are limits however and minimal contrast is required in order to get a good level of automatic detection. When contrast is too low, you can work in manual mode where you indicate the position of rings in the image by clicking them.

All the image content inside the path (not only the central line) is used to calculate the intensity profile displayed parallel to the path. The path width is adjustable so that you can choose what the profile is made of (paths should only contain valid tree-rings information, they should not encompass the core holder for example). The WinDENDRO Density version also uses ring orientation to produce more precise profiles.

Each time a ring is moved or reoriented, the intensity profile is recalculated using a virtual slit that matches the rings boundary. Light variations transitions are less sharp for rings with a wrong orientation. Regarding Wood Species, Narrow Rings & Ring Contrasts When rings are well contrasted, such as with medium to large rings (0.5 mm and over) of coniferous species, the automatic detection rate is in the range of 85 to 100% requiring little modifications from the operator so the productivity gain over manual methods is very high. Rings with lower contrasts such as those from deciduous (hardwood) species or narrow rings, require more attention to preparation, scanning and analysis settings.

The more time is spent on obtaining a good image, the less time is spent on their analysis (this is true for manual methods also). Low contrast samples can be analysed with WinDENDRO but the productivity gain over manual methods is lower than with conifers because more operator corrections are needed. Low contrasted rings requires paying attention to: 1) Sample preparation. It has a great influence on the automatic detection rate. As rings get narrower, the finer the preparation has to be (0.01 mm rings require a finer method than 1.0 cm rings).

Visible mechanical marks (like scratches) should be avoided as they tend to be more visible in digitized images than to the naked eye. They can trigger false ring detections or wrong orientations. There are no universal method accepted for preparation but sanding is very popular for dry samples. Contrasts enhancements done during scanning or after in WinDENDRO allows to see the rings more easily. Narrow rings require higher resolution (DPI) than large rings. As a rule the practical minimum number of pixels per ring is four and this number increases (up to ten typically) as ring contrasts lower. A good quality scanner is also mandatory.

Good quality is not only related to the theoretical dpi claimed by its manufacturer, it is also a matter of good optics and electronics. Regent Instruments tests and compares all scanner models it sells. It also ensures they are compatible with WinDENDRO and its accessories.

Regent Instruments can take the time to look at your samples before recommending a system, so do not hesitate to contact us. 3) Analysis settings. They must also be fine tuned for low contrasts rings.

You can experiment with the two methods of ring detection provided and adjust their parameters to optimise the automatic detection. Some samples are better done in the complete manual mode. Rings can be tagged with observations that you define (you choose their name, meaning and the symbol used to indicate their presence close to a ring). For example you could define two features called 'narrow' and 'frost' and select which rings have these characteristics.

These ring features are then displayed on the graphic and in the image close to rings which have these features. No modifications are made to the original image which is always available for future reference or analyses. The images can also be exported to other software programs (to create a report for example). They can also be saved with their analyses and later be retrieved and edited or validated by WinDENDRO.

Rings Validation After the initial automatic rings detection, a validation must be done to consider the possibility of the presence of false, frost, locally absent rings or simply misclassification done by WinDENDRO. In this regard we say WinDENDRO is a semi-automatic rather than an automatic system. This is done by browsing the image and looking for missing or false rings.

Contrary to systems based on positioning tables, you can switch back and forth along the ring paths without precision loss (due to gears backlash). Previously identified rings can be reviewed at any moment even years later. Adding or deleting rings is easily done interactively.

When the mouse is held over a ring, the latter is highlighted (in yellow as illustrated). Clicking it deletes the ring, clicking at a place there is no ring adds one. Rings can be deleted in groups, moved or reoriented. Earlywood-latewood boundaries position can also be overriden. As modifications are done, the rings number and year are automatically updated in the image and the ring-widths graphic. Detected rings can be reoriented to match the ring boundary for more precise measurement.

Rings can be moved. Rings can be deleted (or added) by clicking them one by one or by using an image selection.

The Ring-Widths Graphic & Cross-Dating A graphic of ring-widths in function of the year is displayed during the analysis and is automatically updated as rings are edited during the validation phase (Reg and Density versions). This graphic is also used for visual and numerical cross-dating. It can display simultaneously master chronologies and the ring widths of the sample under analysis and correlate some of them to help find mistakes in the analysis. Ring-width series can be detrended (converted to indices) using the smoothing spline method.

A graphic of ring-widths in function of the year is displayed during the analysis and is automatically updated as rings are edited during the validation phase (Reg and Density versions). This graphic is also used for visual and numerical cross-dating. It can display simultaneously master chronologies and the ring widths of the sample under analysis and correlate some of them to help find mistakes in the analysis. Ring-width series can be detrended (converted to indices) using the smoothing spline method.

The smoothing spline can be displayed to help determine its filtering strength. Skeleton plots can be displayed during the measurements of one or more series simultaneously with master chronologies. These are used by dendrochronologists to identify rings that are smaller or larger than their neighbors for visual cross-dating.

Ring widths can be displayed unmodified (as measured in millimeters) or as index values (ring widths for which long term non-climatic variations such as those due to tree aging have been removed) and can also be converted to a logarithm scale to increase the effects of narrow rings variations. There are many interactive commands associated with the graphic. For example, when you click a year on it, the image is scrolled to display the part of the image where that ring is.

The ring-width series can be splitted and shifted at different places (and the correlation updated) to help find missing or false rings. Modifications done by adding rings at splits points can be ported to the analysed sample by activating a command. Three split points where the data series can be independently shifted. More points can be added or removed. Density Analysis WinDENDRO is available with or without density analysis capability. The principles behind WinDENDRO’s density analyses are well known and have been applied for years in tree ring analysis.

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Different methods can be applied to perform density analysis in WinDENDRO:. The conventional film-based method This method is the oldest and most widely used for tree ring density analysis by dendrochronologists. It is well documented in Dr. Schweingruber book Basic and Applications of Dendrochronology. Wood samples are cut into thin slices (1 to 2 mm thick), brought to a predetermined humidity level and exposed to x-rays over a film.

The film is then developed. In WinDENDRO, the conventional analog densitometer is replaced by a digital method that consists of scanning the x-ray film and then measuring light that passes through a virtual slit scanned over the rings.

Unlike the analog densitometer, parameters such as slit size can easily be changed. When computing density, WinDENDRO automatically sets the slit angle tangent to the ring boundary in order to produce accurate measurements.

The slit angle linearly changes its orientation gradually between rings so that it is tangent to all rings boundaries. The operator can interactively override the slit angle estimated by WinDENDRO. The reflected-light method This method does not produce true density measurements but estimates density based on the assumption that wood color is related to density. When the wood surface is carefully prepared, it makes sense to think that the reflected light profile measured by WinDENDRO can be calibrated to procure density related measurements. This calibration is not simple, however, and we are not aware of a successful calibration method. In recent years however some researchers obtained interesting results using the blue channel of color images. Most of the time the reflected-light method is used for relative measurements instead.

One major advantage of the reflected-light method is that it does not require costly radiation equipment. It requires a good understanding of its limitations however. The filmless digital x-ray imaging method It is possible to use the newest filmless digital x-ray cameras or scanners (not sold by Regent) to acquire x-ray images of pieces of wood and then measure their density.

Some systems require that the pieces of wood still be prepared as described above. Density is measured in WinDENDRO from these images exactly as it is from digitized films (except for calibration). Multiple density measurements can be saved on a ring or pixel basis. Available per ring: ring width, earlywood and latewood width (in mm or percentage of ring width), ring maximum density, ring minimum density, ring mean density, earlywood mean density, latewood mean density and ring boundary orientation.

Available per pixel along a ring path: pixel density or light intensity (calibrated or not) and slit orientation. Data When an analysed image is saved to a file, the analysis is automatically saved with it. This analysis can later be retrieved,validated or modified simply by loading the image in WinDENDRO. The analysis data such as ring width, minimum density etc, are also saved to standard text files that can be read by many programs including spreadsheet style software like Microsoft’s Excel. WinDENDRO has its own format (documented in its user guide) to store these data but can also convert files to the decadal (Tucson) format used by dendrochronologists (at 1/100 or 1/1000 of a mm precision). Unlike the decadal format, the WinDENDRO format allows to store the analysis settings, date and time, image information along with the rings measurements. Stem Analysis XLSTEM is an optional stem analysis program that runs within Microsoft Excel.

It allows to visualize data produced by WinDENDRO and to do standard stem analysis (like reconstituting tree growth as a function of age, measuring tree volume.). Calculations can be done interactively on selected trees or in batch. XLSTEM calculates the following information from ring width data produced by WinDENDRO:. Mean radius (quadratic method), diameter and area per disk (cumulative or incremental).

Tree height and volume as a function of age or year (cumulative or incremental). Basal and summary information about the tree It has three height interpolation methods: Linear, Carmean and Newberry. Miscellaneous WinDENDRO comes with a printed color illustrated manual and prompt and competent technical support (via e-mail).

Although it is done by e-mail it is as responsive as telephone could be. The typical answering time is within one hour. It is also done by competent persons, people close to and which can rely on WinDENDRO programmers for technical advices. WinDENDRO is a member of a family of related products for plant science research and production. Among them you will find: WinCELL for wood anatomical cell analysis (free with WinDENDRO Reg and Density) WinRHIZO & WinRHIZO Tron for root analysis (extracted and in-soil) WinSCANOPY for canopy and radiation analyses from fisheye hemispherical images WinCAM for color analysis WinFOLIA for broad leaf analysis WinSEEDLE for seed and needle analysis The steep increase in scanner and computer performances and prices decrease over the last years have made WinDENDRO systems more than an affordable solution to set up a tree-ring facility. Its cost compares favorably with binocular and positioning table based manual systems.