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A timesaving, accurate method for locating and re-locating plants in ecological field studies Lotta Wallin , Hamish R.D. Avery Department of Plant Ecology, Evolutionary Biology Centre, Uppsala University, Villavägen 14, SE-752 36 Uppsala, Sweden ARTICLE INFO ABSTRACT Article history: Received 29 September 2006 Received in revised form 5 March 2007 Accepted 6 March 2007 We present a method for increasing the accuracy and acquisition rate of the initial location data of plants within fixed areas. Using a personal digital assistant (PDA) to create a link between various electronic measurement devices (pantograph, micrometers etc.) and a database of the study individual's location information, has significantly increased measurement reliability and speed in a demographic field study. The method also provides a means to quickly and accurately re-identify the same individuals during subsequent visits to the study plot. Application of the same method can be used in all ecological field studies with sessile organisms in permanent plots, increasing speed and accuracy of coordinate measurement. © 2007 Elsevier B.V. All rights reserved. Keywords: Database Demographic study Pantograph Permanent plot Coordinate measuring 1. Introduction For studies that track individual plants over time and within fixed plots, for example, demographic studies of perennial plants (Morris and Doak, 2002), the location of the individuals needs to be recorded. Traditionally, different forms of mapping techniques have been used to acquire the location data. A common method involves dividing the plot into smaller sub-plots, or a grid, and then mapping the studied individuals within these smaller sectors (Lennartsson and Oostermeijer, 2001; Brys et al., 2004; Nordbakken et al., 2004). Mechanical mapping instruments, such as a pantograph, (a device that transfers coordinates directly to paper via a mechanical arm with a reduction mechanism; Jerling, 1984; Sutherland, 1996) automate the coordinate measurement, reducing the risk of human error. When studying individuals that are either large, or in a relatively undisturbed system, permanent tagging can be a good way to ensure that you locate the correct individuals at every census. This method has been used both for vascular plants, trees and bryophytes (Condit et al., 1995; Rydgren and Økland, 2002; Fröborg and Eriksson, 2003). Many studies do not specify the technique that was used, simply reporting that individuals were mapped. For cases where all markers indicating the individual plants must be removed between measurements, or when permanent marking is impossible for other reasons, the measurement process must be repeated in reverse to locate the individuals in subsequent visits. This process is often difficult and time-consuming, furthermore, errors in the initial location data can result in the wrong individual being studied, creating erroneous conclusions to the study. Regardless of the measurement technique, once the position data has been determined, the information is usually transferred from the field data to a database or electronic dataset on a computer for analysis (Fig. 1). This transferal process takes time and introduces another source of errors. 1.1. New technologies Traditional measurement techniques can in many cases be replaced by new technologies. These range from global ECOLOGICAL INFORMATICS 2 (2007) 367 372 Corresponding author. E-mail address: [email protected] (L. Wallin). 1574-9541/$ - see front matter © 2007 Elsevier B.V. All rights reserved. doi:10.1016/j.ecoinf.2007.03.003 available at www.sciencedirect.com www.elsevier.com/locate/ecolinf

A timesaving, accurate method for locating and re-locating plants in ecological field studies

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A timesaving, accurate method for locating and re-locatingplants in ecological field studies

Lotta Wallin⁎, Hamish R.D. AveryDepartment of Plant Ecology, Evolutionary Biology Centre, Uppsala University, Villavägen 14, SE-752 36 Uppsala, Sweden

A R T I C L E I N F O

⁎ Corresponding author.E-mail address: [email protected] (L. W

1574-9541/$ - see front matter © 2007 Elsevidoi:10.1016/j.ecoinf.2007.03.003

A B S T R A C T

Article history:Received 29 September 2006Received in revised form5 March 2007Accepted 6 March 2007

We present a method for increasing the accuracy and acquisition rate of the initial locationdata of plants within fixed areas. Using a personal digital assistant (PDA) to create a linkbetween various electronic measurement devices (pantograph, micrometers etc.) and adatabase of the study individual's location information, has significantly increasedmeasurement reliability and speed in a demographic field study. The method alsoprovides a means to quickly and accurately re-identify the same individuals duringsubsequent visits to the study plot. Application of the same method can be used in allecological field studies with sessile organisms in permanent plots, increasing speed andaccuracy of coordinate measurement.

© 2007 Elsevier B.V. All rights reserved.

Keywords:DatabaseDemographic studyPantographPermanent plotCoordinate measuring

1. Introduction

For studies that track individual plants over time and withinfixed plots, for example, demographic studies of perennialplants (Morris and Doak, 2002), the location of the individualsneeds to be recorded. Traditionally, different forms ofmapping techniques have been used to acquire the locationdata. A common method involves dividing the plot intosmaller sub-plots, or a grid, and then mapping the studiedindividuals within these smaller sectors (Lennartsson andOostermeijer, 2001; Brys et al., 2004; Nordbakken et al., 2004).Mechanical mapping instruments, such as a pantograph, (adevice that transfers coordinates directly to paper via amechanical arm with a reduction mechanism; Jerling, 1984;Sutherland, 1996) automate the coordinate measurement,reducing the risk of human error.

When studying individuals that are either large, or in arelatively undisturbed system, permanent tagging can be agood way to ensure that you locate the correct individuals atevery census. This method has been used both for vascularplants, trees and bryophytes (Condit et al., 1995; Rydgren and

allin).

er B.V. All rights reserved

Økland, 2002; Fröborg and Eriksson, 2003). Many studies do notspecify the technique that was used, simply reporting thatindividuals were mapped.

For cases where all markers indicating the individualplants must be removed between measurements, or whenpermanent marking is impossible for other reasons, themeasurement process must be repeated in reverse to locatethe individuals in subsequent visits. This process is oftendifficult and time-consuming, furthermore, errors in theinitial location data can result in the wrong individual beingstudied, creating erroneous conclusions to the study.

Regardless of the measurement technique, once theposition data has been determined, the information is usuallytransferred from the field data to a database or electronicdataset on a computer for analysis (Fig. 1). This transferalprocess takes time and introduces another source of errors.

1.1. New technologies

Traditional measurement techniques can in many cases bereplaced by new technologies. These range from global

.

Fig. 1 –Typical process of initial measurement where location/re-location is performed with any conventional measurementdevice such as ruler or calipers, followed by measurements recorded on paper datasheets and later transferred to electronicform.

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positioning systems (GPS) in the large scale to digital caliperson the small scale. Wired and wireless 2D and 3D mappingsystems, once too expensive for most ecological studies, arenow becoming cheap and readily available thanks to thevirtual reality industry, for example, miniBIRD 800 (AscensionTechnology Corporation), PATRIOT (Polhemus) and Inertia-Cube2 (InterSense). Along with displayed measurements,these new technologies often provide measurement storagefacilities and a means to transfer this data directly to acomputer, via, for example, USB or serial ports.

1.2. A new method

When using a measurement device with an output (position)available in electronic format, and when storing the locationdata in an electronic format, the advantages in linking the twoare obvious. Because most personal computers used for dataanalysis are physically large and operate for a limited timeunder battery power, the approach presented in this paper isto use a low-cost generic personal digital assistant (PDA) tolink the database of coordinates and the measurementsrecorded by the electronic measurement device (Fig. 2).

By making use of the PDA's processing capabilities, this linkcan work both to store the data from the measurement devicebefore loading it into a database and to work backwards,providing a ‘seek’ function to re-locate previously knownindividuals. The ‘seek’ function uses the graphical display topresent, in amap form, the locations of individuals already in thedatabase, along with the position of the measurement device.

As an additional benefit, the PDA can also function as abasic field datasheet, with which the user can enter datadirectly into excel or other spreadsheet/database programs.

Fig. 2 –Electronic method of traditional techniques, using a persothe dataset.

1.3. Motivation

The results of this paper were motivated by an ecologicalstudy looking at the effects of differing management regimeson three perennial species commonly occurring in woodedhay-meadows on the Baltic island of Gotland, Sweden. Withinthe three studied meadows there were 156 0.5 m2 permanentplots containing, in total, some 3500 tracked plant individuals.Because the meadows were grazed in late summer, the plotshad to be completely cleared from aboveground plantmarkersafter the last census of each field season (Wallin andSvensson, manuscript).

In the first field season, each tracked individual's locationwas measured with a tape-measure referenced from theclosest x and y edges of a frame marking the plots perimeter.The coordinates and measurement reference used wereverbally relayed to a field assistant who recorded them onpaper for later entry into a database. This data was then to beused to re-locate the individuals at the beginning of the nextfield season, and the same measurement technique used torecord all new seedlings of the study species that werediscovered. Because this process would take a long time —during the period of rapid seedling and cover foliage growth—the dataset risked becoming skewed when comparing thesurveys of the plots visited first to those visited last in thespring survey, suggesting a need for rapid re-location andmeasurement.

At the end of the first field-season, three major problemswere identified when using this technique for this study;

• Slow initial location measurement,• errors in coordinate recording, and

nal digital assistant (PDA) to link the measurement device to

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• slow re-identification of individuals that had been previ-ously identified.

At this time the method presented in this paper wasdeveloped. We now present a solution to the three problemsmentioned above, which, while being too specific for wideruse, serves to illustrate the application of the method.

2. Materials and methods

Because we could not find any low-cost readily availablesolutions for measuring coordinates within a small plot, wedeveloped a customised electronic pantograph device thatcould accurately measure the location of a measurementstylus within a defined boundary, by measuring ultra-soundtravel times. This instrument displayed the position of thestylus on a small display, as well as providing the stylusposition in an electronic format (Fig. 3).

A Microsoft Access 2000 (Microsoft Corporation, Washing-ton, USA) database containing the details of each individualplant was created. This included each individual's parameterssuch as species and age as well as its home meadow, thetransect and plot it was located within and it's coordinateswithin that plot. Each individual plant specimenwas providedwith a unique number that was used to identify it. Becauseeach individual's specific location was available in electronicformat (species, meadow, transect, plot, and coordinateswithin the plot), it was a straightforward process to extractthis data for use by the PDA.

Fig. 3 –The frame ismade of carbon-fiber-rods (for lightweightrigidity) and the transmitting stylus is a plastic rod thatcontains a small transmittingdevice sendingout anultrasonicwave that is recorded by receivers positioned in the corners ofthe frame. In our example the size of the area is 0.5 m2.

Fig. 4 –Typical display of the personal digital assistant (PDA)screen, showing all individuals present in a selected plot ofthe size of 0.5m2 (a), and close-up of screen, after zoom-in to a10×10 cmarea in searchmode, in this case, showing a clusterof seedlings (b).

The PDA chosen for linking the database of the coordinatesto themeasurement device was a Compaq IPAQ. The PDAwasprogrammed with Embedded Visual Basic (Microsoft Corpo-ration, Washington, USA) to store a cut-down version of thefull dataset, in this case, a text file containing the basicinformation needed to identify each individual. The programwas also configured such that once one selected a species,meadow, transect and plot, all the known individuals insideeach plot were displayed graphically as a map (Fig. 4a). Byoverlaying the stylus's position on the map it was possible touse the location measurement apparatus ‘in reverse’ to homein a specific individual. In operation, when a target individualis selected, the PDA displays the individual as a flashing targetwithin the plot, alongwith all the other known individuals as areference. The position of the stylus is also shown. When thestylus is moved, and it's coordinates approach the coordinatesof the target individual, the map ‘zooms-in’ to allow moreprecise location (Fig. 4b). When the stylus coordinates finallymatch the database coordinates, the individual must then bebeneath the stylus. Once the individual is identified, a buttonon the stylus is triggered and the target coordinates areautomatically incremented to identify the next individual.

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This process results in rapid and accurate re-identification.The entire process is shown in the context of the motivatingstudy schematically in Fig. 5.

Due to time and budget limitations, this example systemdid not fully implement the system presented in the “A newmethod” section. The measurements taken by the electronicmeasurement device were not stored electronically, but reliedon transcription to a paper datasheet by a field assistant. Theaccuracy of this process was increased by providing a displaythat was clipped onto the field assistant's datasheet. Thisdisplay showed the coordinates of the stylus for ten secondswhenever the stylus's button was pressed.

We tested the measurement device in two ways. To assessthe impact on measurement error frequency in the datamaterial, we counted the number of errors in coordinate datawithin the season when using only the tape measure method,and the within-season errors when using only the newmethod. The absolute error (in cm) between the recordedand actual locations was compared between these points.Only errors exceeding 2 cm were considered because this wasconsidered to be sufficiently accurate to identify the indivi-duals, given that the movement of the soil during the winterand the movements of the plants themselves were estimatedto be of this magnitude.

The accuracy of the measurement instrument itself wasdetermined by recording the location of the stylus whenplacedwithin a 0.5m2 plot, using a gridwith 10×10 points. Therecordings were taken on meadow grass with an averageheight of five cm. Four measurements at each grid point weretaken by two operators, in a total of 400 measurements.

Fig. 5 –Measurement process showing the integration of the coorda field season for a demographical study.

3. Results

The two censuses performed with the tape-measure systemcontained 293 measurements with coordinate differencesexceeding 2 cm, from a total number of 2496 individuals(∼12%). The distribution of these errors was roughly even overthe size of the plot (Fig. 6a). The same comparison wasperformed on two censuses measured with the electronicsystem presented in this paper. There were 72 measurementswith coordinate differences exceeding 2 cm from a total of2927 individuals (∼2.5%). Of these errors, over half occurredwith a difference less than 6 cm (Fig. 6b).

The error of the measurement device was maximum±1.8 cm (Fig. 7).

4. Discussion

For study systems similar to the one described in themotivation section, the method presented in this paper hasshown itself to be effective at reducing the time taken to mapindividuals, and to re-identify them in subsequent visits. Thereduced census time both saved money by reducing the timespent in the field and also increased data fidelity by reducingthe time each census took. Performing a census within a shortperiod results in a more consistent image of the data becausefactors affecting the data gathering process (foliage density,sizes of seedlings etc.) are equal throughout the data acqui-sition period.

inate measuring system, in the context of a one-year cycle of

Fig. 6 –The distribution ofmeasurement errors for two subsequent visitswith a) tapemeasurer, not including errors under 2 cm.(Nerrors=293) and b) using the new method of data measuring with a link between database and field plot, not including errorsunder 2 cm. (Nerrors=72).

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The test results showed the advantages of automating themeasurements process. Removing the confusion arising fromusing the tape measure from different reference points, theaddition of the visual coordinate display, and the removal oferrors in re-locating the plantsmarkedly reduced the numbersof errors in the coordinate database. The errors remaining inthe measurements show two important points:

The concentration of errors below 6 cm indicates that themovement of the plants may be larger than estimated.

The remaining errors above 6 cm must be due to transcrip-tionerrors; thisprovidesanerrorbaseline that canbe subtracted

from the tape-measure results to determine the errors directlyarising from the manual measurement process.

Fully implementing the systempresented, so that it directlytransfers themeasurements from the electronicmeasurementdevice to the database, will remove the transcription errors.

The method presented could be applied to other purposes.For example, when doing follow-up field surveys of biodiver-sity, a permanent plot could be re-surveyed at different timeintervalswith the species plotted in the last survey being easilymonitored. It could also be useful in studies of spatial patternsin plants. A plant individual is usually strongly affected by its

Fig. 7 –Magnitude error surface of measured versus knowncoordinates in field conditions with a maximum error of1.8 cm.

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neighbouring plants as it is sessile and the available resourcesare limited (Crawley, 1997). Therefore, the spatial distributionof individuals is inmany cases not random, but determined bywhich neighbours each plant has and how close they stand.The new system reduces the effort of the data acquisition forspatial analysis, allowing the tracking of much greaternumbers of individuals within neighbourhoods.

5. Conclusion

The method of linking an electronic measurement device to adatabase of location information allows 1) rapid and accurategathering of the initial location data and 2) rapid and accuratere-locating of the known individuals in subsequent visits.

R E F E R E N C E S

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