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Computers & Geosciences 32 (2006) 1259–1269 Coral Point Count with Excel extensions (CPCe): A Visual Basic program for the determination of coral and substrate coverage using random point count methodology $ Kevin E. Kohler , Shaun M. Gill National Coral Reef Institute, Nova Southeastern University Oceanographic Center, Dania Beach, FL 33004, USA Received 19 July 2005; received in revised form 17 November 2005; accepted 21 November 2005 Abstract Photographic and video methods are frequently used to increase the efficiency of coral reef monitoring efforts. The random point count method is commonly used on still images or frame-grabbed video to estimate the community statistics of benthos. A matrix of randomly distributed points is overlaid on an image, and the species or substrate-type lying beneath each point is visually identified. Coral Point Count with Excel extensions (CPCe) is a standalone Visual Basic program which automates, facilitates, and speeds the random point count analysis process. CPCe includes automatic frame-image sequencing, single-click species/substrate labeling, auto-advancement of data point focus, zoom in/out, zoom hold, and specification of random point number, distribution type, and frame border location. Customization options include user-specified coral/substrate codes and data point shape, size, and color. CPCe can also perform image calibration and planar area and length calculation of benthic features. The ability to automatically generate analysis spreadsheets in Microsoft Excel based upon the supplied species/substrate codes is a significant feature. Data from individual frames can be combined to produce both inter- and intra-site comparisons. Spreadsheet contents include header information, statistical parameters of each species/substrate type (relative abundance, mean, standard deviation, standard error) and the calculation of the Shannon–Weaver diversity index for each species. Additional information can be found at http:// www.nova.edu/ocean/cpce/. r 2005 Elsevier Ltd. All rights reserved. Keywords: Coral point count; Random point count; Coral reef assessment; Coral reef monitoring; Coral area measurement 1. Introduction and rationale Random point count methodology is commonly used in many population estimation applications, e.g. forestry vegetation (Stoyan and Penttinen, 2000), tree canopy cover (Thomas and Winner, 2000), bird population and diversity (Ralph et al., 1995; Thompson III et al., 2002; Young and Hutto, 2002). It is also commonly used on frame-grabbed video or still images to estimate the population statistics of marine benthic communities (Carleton and Done, 1995). Previous methods included over- laying underwater photographic images with trans- parent sheets containing randomly positioned ARTICLE IN PRESS www.elsevier.com/locate/cageo 0098-3004/$ - see front matter r 2005 Elsevier Ltd. All rights reserved. doi:10.1016/j.cageo.2005.11.009 $ Code available from server at http://www.iamg.org/CGEditor/ index.htm Corresponding author. Tel.: +1 954 262 3641; fax: +1 954 262 4158. E-mail address: [email protected] (K.E. Kohler).

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  • Computers & Geosciences 32 (2

    xteoco

    Kevin E. Kohler, Shaun M. Gill

    calculation of the ShannonWeaver diversity index for each species. Additional information can be found at http://

    www.nova.edu/ocean/cpce/.

    statistics of marine benthic communities (Carletonand Done, 1995). Previous methods included over-

    ARTICLE IN PRESS

    $Code available from server at http://www.iamg.org/CGEditor/

    index.htmCorresponding author. Tel.: +1954 262 3641;laying underwater photographic images with trans-parent sheets containing randomly positioned

    0098-3004/$ - see front matter r 2005 Elsevier Ltd. All rights reserved.

    doi:10.1016/j.cageo.2005.11.009

    fax: +1954 262 4158.

    E-mail address: [email protected] (K.E. Kohler).r 2005 Elsevier Ltd. All rights reserved.

    Keywords: Coral point count; Random point count; Coral reef assessment; Coral reef monitoring; Coral area measurement

    1. Introduction and rationale

    Random point count methodology is commonlyused in many population estimation applications,

    e.g. forestry vegetation (Stoyan and Penttinen,2000), tree canopy cover (Thomas and Winner,2000), bird population and diversity (Ralph et al.,1995; Thompson III et al., 2002; Young and Hutto,2002). It is also commonly used on frame-grabbedvideo or still images to estimate the populationNational Coral Reef Institute, Nova Southeastern University Oceanographic Center, Dania Beach, FL 33004, USA

    Received 19 July 2005; received in revised form 17 November 2005; accepted 21 November 2005

    Abstract

    Photographic and video methods are frequently used to increase the efciency of coral reef monitoring efforts. The

    random point count method is commonly used on still images or frame-grabbed video to estimate the community statistics

    of benthos. A matrix of randomly distributed points is overlaid on an image, and the species or substrate-type lying

    beneath each point is visually identied. Coral Point Count with Excel extensions (CPCe) is a standalone Visual Basic

    program which automates, facilitates, and speeds the random point count analysis process. CPCe includes automatic

    frame-image sequencing, single-click species/substrate labeling, auto-advancement of data point focus, zoom in/out, zoom

    hold, and specication of random point number, distribution type, and frame border location. Customization options

    include user-specied coral/substrate codes and data point shape, size, and color. CPCe can also perform image calibration

    and planar area and length calculation of benthic features. The ability to automatically generate analysis spreadsheets in

    Microsoft Excel based upon the supplied species/substrate codes is a signicant feature. Data from individual frames can

    be combined to produce both inter- and intra-site comparisons. Spreadsheet contents include header information,

    statistical parameters of each species/substrate type (relative abundance, mean, standard deviation, standard error) and theCoral Point Count with Excel eprogram for the determination

    using random point006) 12591269

    nsions (CPCe): A Visual Basicf coral and substrate coverageunt methodology$

    www.elsevier.com/locate/cageo

  • points (Murdoch and Aronson, 1999). Later im-provements to this method included the use of

    identication required to provide meaningful popu-

    species/substrate type (relative abundance, meanthees.

    ify-der,oralof

    fterbefornedandof

    ARTICLE IN PRESSK.E. Kohler, S.M. Gill / Computers & Geosciences 32 (2006) 125912691260lation estimates. It includes many user-friendlydesign features, and provides a reliable means ofdata archiving. This paper describes the featuresand functionality of CPCe at the time of thiswriting, Version 3.3.

    2. Overview

    CPCe was designed specically to quickly andefciently calculate statistical coral coverage over aspecied area. Underwater photographic frames areoverlaid by a matrix of randomly distributed points,and the fauna/ora species or substrate type lyingbeneath each point is visually identied. The speciescode data for each frame is stored in a .cpc lewhich contains the image lename, point coordi-nates and the identied data codes. Data fromindividual frames can be combined to produce bothinter- and intra-site comparisons via automaticallygenerated Excel spreadsheets. The transect datasetscan then be statistically analyzed to give quantita-tive population estimates over the area of interest.In addition, CPCe has the ability to measure bothplanar length and area of selected benthic features.This capability allows the statistical comparison

    1Dustan, P., Leard, J., Meier, O., Brill, M., Kosmynin, V.,

    1999. PointCount99 software. University of Charleston, Southcomputer software to generate the random pointpatterns and to identify the underlying benthicfeatures. PointCount991 is one such computerprogram.Instead of requiring the counting of each speci-

    men, the random point method relies on statisticalpower analysis to estimate the actual populationusing the random point samples as a proxy (Lenth,2001). The technique consists of randomly distri-buting a number of points onto an underwaterphotographic image, and then visually identifyingthe features (e.g. coral, algae, rubble, etc.) lyingunder each point. The percentage of points over-lying each benthic category is calculated, andstatistics can be compiled to estimate the populationof biota such as stony coral, sponges, macroalgae,etc. over a region of interest. Coral Point Countwith Excel extensions (CPCe) was developed toincrease the efciency and ease of performing thelarge number of image analyses and featureCarolina, http://www.cofc.edu/coral/pc99/pc99.htm.3.1. Image and coral code file specification

    The user species a digital image in the form of a.jpg, .gif, or .bmp le by selecting File-Open-Rawtheimse operations is detailed below.

    to simplify and speed the processing effort. Each

    to ow logically from one operation to the next,

    statistical analysis. CPCe was specically desig

    automatically assembled into Excel spreadsheets

    the images have been processed, the data can

    the random points, and saving the data to le. A

    species and/or substrate-type lying beneath each

    overlaying random points, identifying the c

    ing a digital image, dening a frame bor

    The basic operations of CPCe consist of spec3. CPCe operationShannonWeaver diversity index for each speci

    and standard deviation), and the calculation ofbetween video quadrat analyses and in situ mea-surements, and also to determine growth trendsover time.The primary features of CPCe are:

    automatic frame-image sequencing, single-click species/substrate labeling, auto-advancement of data point focus, multiple point data assignment, user-specied coral/substrate codes, variable random point number/distribution, image scaling and calibration, planar area analysis, batch data input and output, automatic Excel spreadsheet generation, adjustable frame border dimensions, color-coded category boxes, zoom in/out and zoom hold, hide/show random points on image, customizable data point shape/color, code le integrity checker,A signicant feature of CPCe is the ability toautomatically generate analysis spreadsheets inMicrosoft Excel based upon the supplied species/substrate codes. Individual image frames can beanalyzed separately or multiple frames can becombined into a single transect datasheet containingheader information, statistical parameters of eachage le. Images smaller than the available screen

  • area are expanded to ll the available space, whilelarger images are reduced in size to t. A set ofmultiple image les can be specied at once andCPCe will process each le sequentially in alphabe-tical order. This eliminates the need to manuallyspecify each image le for analysis, and allows theuser to quickly switch back and forth betweenimages.

    3.2. Border designation

    The user then species the rectangular region ofthe image to be covered with random points. Theregion border can be specied in one of four ways

    ARTICLE IN PRESSK.E. Kohler, S.M. Gill / Computers & Geosciences 32 (2006) 12591269 1261(Fig. 1). The rst method is to click and drag tocreate a rectangular area on the digital image. Theborder can then be manually stretched and movedinto the desired size and position. The secondmethod is to use the entire image. Thirdly, the usercan specify a border offset (in pixels) in the x- andy-direction independently. The border is then drawnon the image using the appropriate offsets from theimage edges. Lastly, the user can specify thedimensions of the border region. For this method,the user must either specify the scaling resolution ofthe digital image, e.g. number of pixels percentimeter, or the image scaling can be calculatedwithin CPCe (see Section 6: Program tools). Afterthe image resolution is specied or calculated, aborder of specic dimensions can be drawn andpositioned.

    3.3. Random point specification

    The random points to be overlaid within theborder perimeter can be specied in one of fourFig. 1. Border boundary specication options.ways (Fig. 2). The rst way is the simple randommethod where every pixel within the marked borderboundary has an equal likelihood of being chosenfor the position of the random points. The x- andy-coordinates of the random points are generatedseparately and are calculated as follows. The VisualBasic random number generator is initialized withthe Randomize statement. An array newrand of sizenumrand is lled with random numbers in the range01. A random element of array newrand is chosenand the corresponding random number chosen. Therandom numbers are then scaled to producecoordinates which lie within the specied borderedarea. The chosen newrand element is then relledwith a new random number for the next iteration.The second border specication type is the

    stratied random method. In this case, the borderedregion is sub-divided into m rows and n columns,and each cell is populated with k random pointslying within the cell borders, using the techniquedescribed for the simple random method. Thisreduces the potential clumping of the randompoints using the simple random method, andensures that some random points are present ineach image cell region. The total number of points ism n k.The third and fourth border specication types

    allow the specication of a uniform grid over thebordered area. The third type asks for the numberof points in the x- and y- direction and creates thecorresponding matrix of point coordinates, ttingthe points exactly within the border boundaries. Inthis case, the x-spacing of the grid points does notnecessarily equal the y-spacing.The fourth specication type dictates that the

    x-spacing of the points equals the y-spacing, andthe user can specify the number of points in eitherthe x- or y-direction. The number of points that willt in the non-chosen direction (e.g. y-direction if thenumber of points in the x-direction is specied) iscalculated, and the point grid is centered in the non-chosen direction.In all the four methods, the maximum number of

    overlying points allowed is 500. After the pointdistribution method is specied, the random pointsare placed inside the bordered region of the image(Fig. 3).

    3.4. Point data assignment

    The random points are displayed and labeled

    either alphabetically or numerically. Data codes are

  • ARTICLE IN PRESSK.E. Kohler, S.M. Gill / Computers & Geosciences 32 (2006) 125912691262assigned by clicking the point label in the pointcodes box on the right side of the screen and thenthe appropriate species code identier at the bottomof the screen (Fig. 3). A sample species code le,shallow_coral_codes.txt, is supplied with CPCe andcontains common corals from the Caribbean region;however, a user can create a customized le withdata types most appropriate for a specic analysis.The appendix provides details for creating acustomized code le. The full name of the speciesor substrate corresponding to the displayed codecan be seen by allowing the cursor to hover over thecode box. After clicking on the appropriate codebox, the corresponding coral code is inserted in thepoint data table. Only data codes existing in thecode le may be entered for each point. The NOTEScolumn is used to further classify the data pointspertaining to disease, bleaching, etc. Points thathave been assigned data then change color to give a

    Fig. 2. Random point specication types: (a) simple random; (b) stvisual representation of points still requiring identi-cation. If the number of random points is greaterthan the number of data entry boxes that can beshown on the screen at once, arrow buttons areprovided to scroll up or down through the datapoint set.

    3.5. Saving the data

    At any time during the analysis, the data pointscan be saved to a .cpc data le. The .cpc le containsthe image lename, the name of the le containingthe species code identiers, the coordinates of theborder boundaries, the number of overlying points,the coordinates of the overlying points, andthe assigned code data for each point. By savingto a .cpc le, the image and point data can beretrieved at a later time for further analysis and/ormodication.

    ratied random; (c) uniform grid; and (d) equally spaced grid.

  • ARTICLE IN PRESSK.E. Kohler, S.M. Gill / Computers & Geosciences 32 (2006) 12591269 12633.6. Excel spreadsheet creation

    The data from one or more .cpc les can becombined in various ways to produce Excelspreadsheets. Individual frames can be analyzed toprovide intra-site comparisons. Alternatively, multi-ple image frames can be grouped together for singletransect evaluation. Additionally, multiple transectscan be analyzed together as a single site or samplingstation. To perform these analyses, the user speciesone or more .cpc les to process, and thecorresponding Excel spreadsheets are created. Thecoral categories and classes specied in the datacode le are inserted automatically into the spread-sheet. For each transect, two Excel worksheetsare createdone containing basic statistical ana-lyses of the data such as point frequency, percen-tage, ShannonWeaver diversity index for bothspecies and category group (Fig. 4a), and another

    Fig. 4. Example Excel spreadsheets generated by CPCe showing:

    (a) point frequency, percentage, and ShannonWeaver diversity

    index and (b) raw point code data of a single frame.

    Fig. 3. Screenshot of image with overlying random points. Available coral codes are shown underneath image. Data entry area is on right.

  • ARTICLE IN PRESSK.E. Kohler, S.M. Gill / Computers & Geosciences 32 (2006) 125912691264containing the raw point code data (Fig. 4b). Thissecond worksheet provides an archival record forthe point code data.Additional transects can be appended to existing

    Excel spreadsheets. A separate data summaryworksheet is created in each workbook whichcontains statistics among transects including mean,standard deviation, and standard error of categorygroups (Fig. 5).

    4. Program controls

    In the design of CPCe, an emphasis was placed onhaving the necessary tools accessible on a singlescreen window, while maximizing the screen areaallocated to the analysis image. Additionally, CPCewas designed to be a self-contained program,

    Fig. 5. Example Excel spreadsheet showing darequiring only Microsoft Excel for automated dataanalysis.There are several program controls designed to

    increase the efciency of assigning the data pointcodes (Fig. 6). In order to better view the underlyingimage features, all of the data points can betemporarily hidden. Isolation mode can be used toshow only the current point instead of all randompoints. Groups of points can be assigned with asingle click. Point groups are selected by using thetypical shift-click or ctrl-click combinations. Click-ing on the data code box assigns that code to allselected points. The data of the currently selectedpoints can be cleared by clicking on the Clearselected points icon. Additionally, all points havinga blank ID eld or blank Notes eld can be selectedat once, and lled with a single data code with oneclick.

    ta summary for four individual transects.

  • The image can be zoomed in or out by left-clicking or right-clicking on the image, respectively,with the zoom level increasing or decreasing by 50%with each click. If the Maintain zoom option ischecked in the Options menu, the current zoom levelis maintained when moving among data points.Buttons are provided to zoom to 100%, 300%, and600% with a single click. When the image is zoomedin, a border designating the visible region relative to

    the entire image is shown on an inset image at thelower right of the screen.

    5. Image enhancement

    CPCe includes the capability of basic imageenhancement within the program. The brightness,sharpness, and contrast of a selected area of theimage can be adjusted to aid in species identication(Fig. 7). This is very useful on indistinct object edgeswhen trying to determine random point position.Since it is rarely necessary to enhance an entireimage, the image enhancement is performed on onlya user-selected subset of the image to speed thecreation of the enhanced area display.To enhance an area of the image, the user selects

    the desired area by clicking and dragging. The typeand strength of image enhancement (brightness,sharpness, and contrast) desired is then specied,and the modied image area is displayed. Thebrightness and sharpen lters are accumulative,

    ARTICLE IN PRESS

    Fig. 6. CPCe program controls.

    K.E. Kohler, S.M. Gill / Computers & Geosciences 32 (2006) 12591269 1265Fig. 7. Image enhancintegrity checks.whereas the contrast lter is not.

    6. Program tools

    Several program tools are provided to performtasks such as area measurements and various dataement interface.

  • 6.1. Image calibration and planar area analysis

    CPCe includes the ability to calibrate an imageand to calculate a planar area or length of adisplayed object. This is useful to document the sizeand area of bottom features, and to aid in theinvestigation of growth trends of a coral colonyover time.The rst step in area or length analysis is to

    determine the scaling resolution of the image, e.g.number of pixels per centimeter. To determinethe scaling, an image is selected, and two pointsthat are a known distance apart are marked onthe image (Fig. 8). The user enters the distancespanned by the points, and the scaling resolution iscalculated.Once the image calibration is known, areas and

    lengths on the image can be determined. Tocalculate a length, points at the beginning and endof a linear segment are clicked, and the distancebetween them is calculated and displayed. To

    outlined by pressing shift-right-click. Instructions toaccess these capabilities are displayed on the rightside of the screen. An example of traced andcalculated areas is seen in Fig. 9.The image including the traced area(s) can be

    saved to an image (.bmp) le, either with or withoutthe area information labels. Also, the traced area(s)information can be saved to an .ara le which canbe retrieved for later re-analysis in CPCe.

    6.2. Data check and species search in .cpc files

    This option searches a selected set of .cpc les forunassigned points or the occurrence of a speciedspecies code. It provides the ability to identifyframes with incomplete data entries, and to locateframes containing possibly misidentied species.This is very useful for analysis involving largenumbers of image frames as it eliminates the need tomanually inspect each data le to ensure complete

    code or image les into other folder locations

    ARTICLE IN PRESSK.E. Kohler, S.M. Gill / Computers & Geosciences 32 (2006) 125912691266calculate an area, a trace is performed by left-clicking the mouse, moving the mouse around theperiphery of the desired area, and then right-clicking the mouse which connects the rst and lastpoints and closes the path. The area of the enclosedregion is calculated and displayed. Other featuresinclude the ability to temporarily stop a trace, andto erase partial traces. Once an area is traced, theuser can toggle between having the area lled orFig. 8. Screenshot of image scalipost-analysis.data point assignments.

    6.3. Change code file/image file directory location

    This option changes the directory location ofeither the coral code le or image le in a selectedset of .cpc les. This allows the user to move theng and calibration process.

  • ARTICLE IN PRESSK.E. Kohler, S.M. Gill / Computers & Geosciences 32 (2006) 12591269 12676.4. Code file check

    This option nds any obvious errors in a user-customized species code le such as incorrectsyntax, missing required category elds, and dupli-cate species codes.

    7. Program options

    There are several user-customizable programoptions available. CPCe uses a conguration leto hold the current setting of the various settingsand options. Each setting/option change is writtento the conguration le, and the current setting/option conguration is recalled each time theprogram starts. The program options are listedbelow.

    Fig. 9. Screenshot showing traced areas and lengths, outlined area, a

    bitmapped images.7.1. Data point graphical parameters

    This option customizes the shape, size, and colorof the data point objects. The available shapes arecircle, circle with crosshairs, box, triangle, cross-hairs, all either lled (solid) or outlined. The colorsof unassigned points, assigned points, the currentfocus point, and the frame border can also bespecied, which makes it easier to determine whichpoints remain to be identied. Also, the size of thefont in the coral code boxes can be specied.

    7.2. Color-coded code category boxes

    This option allows the user to specify customcolors for each of the species and substrate codecategories appearing under the analysis image. Thishelps in quickly nding a particular code box whenusing many codes. Blank boxes can also be inserted

    nd movable text boxes. Areas of traced regions can be saved as

  • Walker, and Dr. Ivor Williams for their helpfulcomments which signicantly improved the useful-

    species identiers. The format of the coral code leis as follows:

    ARTICLE IN PRESSK.E. Kohler, S.M. Gill / Computers & Geosciences 32 (2006) 125912691268in the coral code le to separate the coral codes forenhanced visual recognition.

    7.3. Specify coral code file

    The user can specify different data code les forindividual analyses.

    7.4. Letters/numbers

    The user has the option of using either numbersor letters to identify the data points on the image.

    7.5. Maintain zoom

    If this option in the control box is checked, thecurrent zoom level is maintained after assigningeach data point.

    7.6. Auto-advance and auto-follow

    If the auto-advance option is checked, after apoint is assigned a category, the next point insequence becomes the current point, and the cursoris positioned at the corresponding data entry label.This eliminates the need to manually click each datapoint before assigning it a category value.If the auto-follow option is checked, and main-

    tain zoom is checked, the image shifts to center thecurrent point in the display area, while maintainingthe same zoom level.

    8. Summary

    Coral Point Count with Excel extensions (CPCe)is a standalone Visual Basic program which auto-mates the random point count method for thestatistical analysis of marine benthic communities.Features such as group point selection, auto-follow,auto-advance, isolation mode, batch processing ofboth input and output datasets, and image enhance-ment are specically designed to speed the analysisof photo-quadrats. In order to ensure data integrity,the data are saved separately in .cpc format whichcan then be automatically assembled into MicrosoftExcel spreadsheets. By saving the individual .cpcles, the resultant Excel spreadsheets can be easilyregenerated at any time. CPCe also provides thecapability to perform planar area and lengthanalyses on individual coral colonies and other

    benthic features.The number of general coral categoriesFor each coral category: category symbol,category nameFor each coral type: coral code, coraldescription, category nameNOTES, NOTES, NOTES (this line separatesthe coral names from the notes descriptors).For each notes descriptor: notes code,ness and functionality of CPCe. We also thank Drs.Bernhard Riegl and Richard Dodge for their helpfulmanuscript suggestions. Thanks are also extendedto the many researchers at the National Coral ReefInstitute, Florida Fish and Wildlife ConservationCommission Fish and Wildlife Research Institute,University of Miami Rosenstiel School of Marineand Atmospheric Science, and the University ofHawaii for providing feedback on the programsoperation and effectiveness.This work is a result of research funded by the

    National Oceanic and Atmospheric AdministrationCoastal Ocean Program under award #NA03-NOS4260046 to Nova Southeastern University forthe National Coral Reef Institute (NCRI). This isNCRI contribution No. 75.

    Appendix A. Coral code le creation

    A coral code le is an ASCII text le containinggeneral coral categories and individual codes andCPCe is continually updated, and the authors arereceptive to suggestions from other researchers. Thefeatures described in this paper are found in thecurrent version of CPCe, Version 3.3. CPCe is beingmade available free of charge to interested research-ers afliated with scientic institutions. Moreinformation, as well as instructions for downloadingthe software, can be found at http://www.nova.edu/ocean/cpce/index.html.

    Acknowledgments

    The authors thank in alphabetical order Dr. JeanKenyon, Ryan Moyer, Dr. James Stoddart, Briandescription, NA (not applicable)

  • Example:

    categories, as well as the category Coral. Addi-tionally, every category must contain at least onemember.Blank boxes can be inserted within the coral code

    list to separate groups of coral codes. This is doneby entering Blank,Blank,Blank. These boxesappear solid black on the screen.

    Appendix B. Supplementary material

    Supplementary data associated with this articlecan be found in the online version at doi:10.1016/j.cageo.2005.11.009

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    Coral Reefs 18, 341351.

    ARTICLE IN PRESSK.E. Kohler, S.M. Gill / Computers & Geosciences 32 (2006) 12591269 1269Due to the requirements of the associated Excelspreadsheets, the category TWS (Tape, wand,shadow) must be included as one of the coralMonitoring bird populations by point counts. US Forest

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    Coral Point Count with Excel extensions (CPCe): A Visual Basic program for the determination of coral and substrate coverage using random point count methodologyIntroduction and rationaleOverviewCPCe operationImage and coral code file specificationBorder designationRandom point specificationPoint data assignmentSaving the dataExcel spreadsheet creation

    Program controlsImage enhancementProgram toolsImage calibration and planar area analysisData check and species search in .cpc filesChange code file/image file directory locationCode file check

    Program optionsData point graphical parametersColor-coded code category boxesSpecify coral code fileLetters/numbersMaintain zoomAuto-advance and auto-follow

    SummaryAcknowledgmentsCoral code file creationSupplementary materialReferences