The two foundation ideas or concepts that are of vital importance in GIS work (in my humble opinion) are:

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1 HOME RANGE ESTIMATION AND HABITAT SELECTION USING G.I.S. During this workshop, you will be introduced to ArcGIS 9 software and some of the analytical tools available to go with this software. This workshop evolved from an assignment taught at UC Berkeley in Spring 2006 in an upper level wildlife ecology class, which was open to all majors. It assumes that you have never used ArcView/ArcGIS and have only heard or read about GIS at a basic level. If you have used ArcView 3.x and are hoping to make the scary transition, this may be a good way to do it, however, you may get bored during the introductory parts. Feel free to use this time to just get familiar with the different software and functionalities. Importantly, feel free to ask me questions. I m not an expert, but I have just made this fun-filled transition in platforms (ArcView 3.x to ArcGIS) from the perspective of a novice wildlife ecologist. A geographic information system (GIS) is a system for the management, analysis, and display of geographic information. GIS software, such as ESRIs ArcGIS, is a primary tool used for the spatial management and study of wildlife. In this exercise, you will use GIS to construct home ranges, using pre-existing tools incorporated into ArcGIS. You will then use some simple operations to create habitat selection data to manipulate and explore in Excel. You can work with a partner at your computer during this workshop but make sure you both get to explore the program equally. In order to be comfortable in ArcGIS 9, you will want to be clicking the mouse a lot, changing layers in the view, and have good grip on a couple of foundation ideas and how that translates into the mouse clicking and moving layers around. In this outline I will use the to denote pull-down and choose the next option in a menu. You will see that some terms in the text are in bold this suggests that they are GIS specific jargon and might need defining. [I will put bracketed comments in the text for extra information that may be of use to people upgrading from ArcView 3.x or those who want to know more about how I derived some of these data models] The two foundation ideas or concepts that are of vital importance in GIS work (in my humble opinion) are: 1. OVERLAY OPERATIONS this means you literally stack layers of spatially explicit, georeferenced data, and perform operations on them. 2. ANCILLARY DATA this is data or information associated with a specific location. By performing overlay operations or map math, if you will, you can add more ancillary data to specific locations. This allows you to then manipulate the data into models or simply express novel properties in maps. 1

2 In this workshop, you will use some data from Sadie s field site in South Africa. In Part II, you will replicate some methods used in Sadie s dissertation work to describe the home range and habitat selection of African buffalo (Syncerus caffer) in the Klaserie Private Nature Reserve, South Africa [1]. In Part III of the assignment, you will use species of wildlife from the general census data (unpublished) collected in the dry season in 1999 in Klaserie and learn habitat selection tools similarly to the first section to describe their use of this landscape. PART I: INTRODUCTION, GETTING AND UNDERSTANDING THE DATA, PLAYING WITH ARCGIS 9 LOADING THE DATA Unzip all the data for this workshop into a folder which will serve as your working folder. The data you will be using in this workshop is vector data. You will notice that each of the files has 5-6 parts associated with it. These are shapefiles and it is important that all the pieces stay together. [These are outmoded files from ArcView 3.x with an additional projection file; ArcGIS is backward format friendly, in that it will read shapefiles, but ArcView 3.x will not read layer files.] ArcMap will load shapefiles as layer files, and when you look at them from ArcMap, you will only see one file. The data source for this file is the shapefile, so they are not completely interchangeable. The multiple parts contain various information such as the data table associated with the picture you see, the graphics, and some georeferencing information. All of this data has been projected in UTM WGS84 Zone 36S. You can use the internet to find out what this means, but for the workshop, it s good to know that this means that the units are in meters. You will see coordinates at the bottom of ArcMap with numbers such as , these are x,y coordinates for your data. The locations of three buffalo herds during the time period of are shown as points. These herds are known as N, F and S a Northern herd, a Focal central herd and a Southern herd. In addition, a polygon describing the total reserve Klaserie is kept in another file. There are two more files, Vegetation and Water, which are both a series of polygons. Vegetation describes the reserve in 8 vegetation types. These are classifications of woody vegetation created in 1984 for more information, either ask me, or check out my pubs. The water file is a series of bands or buffers that have been created around water sources (rivers, pans, boreholes, troughs) that are available to wildlife in the dry season. These buffers are at 1km 2

3 intervals from water [2]. You can also add the layer file H20 to see the dry season perennial water sources (parts of river courses, boreholes and pans) used in this file. [In ArcGIS 9, buffers are all integrated into Arc Toolbox. You can find a wizard GUI for the multiple ring buffer in the Arc Toolbox Analysis Proximity Multiple ring buffer. Caution!! It took a very long time to process anything.] GETTING TO KNOW ARCGIS 9 Start ArcMap in the start menu, go to programs ArcGIS ArcMap. It will load an empty map screen and ask you if you want to start a new map. Yes you do. Add the data files. You can use the + in the toolbar at the top. Once added, you will see them listed at the side of the map screen as layers; you can drag them around and turn them on and off, so that you can see the points on the vegetation layers and so on. Explore the files within ArcMap. Look at the attribute table. (hint: right click on the mouse). See if you can change the color of the points (hint: look at Symbology in the Properties, or doubleclick the color square for the layer). See if you can figure out how to color each vegetation type separately, and the different water bands (hint: make categories based on NZ_NUMBER and DISTANCE). Try zooming in and out of your map, see if you can figure out distances on the map what does 10m look like? What does 10km look like? If you had to guess, how big is Klaserie? Now you want to load Hawth s tools. If you don t already see a Hawth s tools pull-down menu at the top of your map, go to View toolbars Hawth s tools. You should then see a pulldown menu if it is floating, you can anchor it to the toolbar. Look at the pull-down menu and see what tools are in there do you recognize any of the names or calculations? PART II: USING HERD LOCATION DATA FOR HOME RANGE AND HABITAT SELECTION ANALYSES HOME RANGE CALCULATIONS The first type of home range in this workshop is the Minimum Convex Polygon (MCP). In ArcGIS, under Hawth s tools, choose Animal Movements Create Minimum Convex Polygons. It will ask you to choose a point file; using the pull-down menu, choose one of the three herds, n, f, s. Then you will need to name the file I use a convention that is easily recognized, such as n_mcp. Make sure you save this in your working folder, so that you can find it again. Do this for all three herds. The layer created will be added to your map. If you right click on the filename and go to Open Attribute Table, you will see an area estimate for the shape. This is in square meters (m 2 ). Calculate what this is in km 2 and fill in the value on the worksheet. 3

4 Kernel methods Use the Hawth s tools to create kernel home ranges; this version of a kernel density estimator is clearly designed for visualizing and does not readily provide an area estimate. However, if you select the Fixed Kernel Density under Kernel Tools and create both the raster (grid) and the volume contours (polylines), you can see the areas of probability density on the map view. [This is as far as you can go with kernel estimators in Hawth s tools, at present. In order to calculate the areas generated under this method, I developed a work-around as follows (this refers to an extension, Xtools, which you can download and buy): Use the extension XTools to convert the polylines into polygons Use Hawth s Tools Table Tools to calculate the area of the polygons Subtract the area of internal polygons from external ones If you find a way to do this that doesn t involve another extension, or is a free download, please let me know] In order to provide you with a comparison of home range areas using different estimators, I simply created the kernel files separately in ArcView 3.x. You will notice that these are not exactly the same as the contours you can generate using Hawth s tools. Without getting derailed in mathematics, this is because a different smoothing parameter was used to generate the kernels in ArcView. You can read about kernel methods and choosing the smoothing parameter, H in [3], for example. Load the kernel files for each of the three buffalo herds Nkernel, Fkernel, and Skernel. You will see that the 50% probability density and the 95% probability density are shown. Once again, if you right click on the files, you can see the area in square meters for each of these probability kernels. Try making the 95% and 50% density kernels different colors. HOMERANGE QUESTIONS What is the size of the Minimum Convex Polygon in km 2 for each of the three herds? N F S What is the size of the 95% and 50 % kernel for each of the three herds? N 95% 50% F 95% 50% S 95% 50% Which method tells you more about the use of the area by buffalo? 4

5 If you look at the vegetation map and the water map with the 50% density kernels overlaid, can you tell anything about how the herds are distributed on the landscape? (hint: change the colors of the file to let you look through them) HABITAT SELECTION In this part, you will create a new column in the table associated with the water and vegetation layers for the point set you use. Under Hawth s tools Analysis Tools Count Points in Polygons. For the Polygon layer, you will choose either Vegetation or Water. For the point layer choose f, n, or s. In order to keep your columns clear, name your output column in a recognizable way. For example, if I were adding the f herd to the Vegetation layer, I might call the column fveg. Once you have assigned the points to the polygons, open up the polygon layer s table (right click on Vegetation or Water and choose Open Attribute Table). Hopefully you will see the new column you created. You can repeat this procedure to create several new columns of data. There are many ways to examine habitat selection in analytical frameworks. At this point, you have herd locations and their associated habitats or distance to water at the locations. If you want to export this data for analyses, click on the Options tab and choose export. You will create a dbf file that you can open in Excel easily or import into other software. What follows is the first stages of habitat selection analyses based on the Neu [4] method, which uses a χ 2 (Chi-Square) analysis of proportional occurrence in a contingency table (with Bonferroni corrected statistics). This is essentially the method I used in my dissertation [5]. To create a table for export, we first want to summarize the data by habitat either distance to water, or the vegetation type. To do this, open the attribute table for the polygon layer, and click on the column you want to summarize, highlighting it. In the water layer, this will be DISTANCE, in the vegetation layer this will be your choice of NZ_NUMBER, LANDSCAPE or VEGTYPE. Right click Summarize this puts you in the summarize tool, which allows you to select which fields will be summarized by the category you have chosen. For this exercise, choose Area sum, and the sum of each field of points you have assigned to the habitat. In the file location string, create a name for your output table that you will recognize, such as Veg_out or watersumm. The tool window will ask you if you want to add the table to your map yes. The table will appear under your layer files (if you don t see it automagically, click on the Source tab). Open the table and make sure you understand what you see. Next, click the Options tab and choose export. Again, name the output file as something you will recognize and save it in your working folder. If you save it as a dbase file, you will be able to open it in Excel to work with. Open these exported tables in Excel. First, calculate the total area) and the proportion of that area occurring in each habitat category (DISTANCE or VEGTYPE). Then perform the same sums on the points (proportion of points occurring in each category as a proportion of the total number of 5

6 points). You will either want to insert columns next to the original summary data, or create a table below it with the proportions. Next, create column graphs in excel showing the proportion of area in each vegetation type and the proportion of herd points in each vegetation type. At a quick glance, you can guesstimate whether the buffalo prefer certain habitat types if the proportion of locations in the area is higher than the proportion of the area. For those of you familiar with χ 2 analyses, this is the Observed and Expected. It is thus easy to see how this can be expanded to a cross tab table and analyzed appropriately. HABITAT SELECTION QUESTIONS Which vegetation types were preferred by each of the three herds? F N S Which were avoided? F N S What about their distance to water? Do buffalo like water? PART II In the data files provided for this workshop is some census data. There are point files for 8 species: Giraffe, Kudu, Impala, Wildebeest, Warthogs, Waterbuck, Zebra. The points represent occurrences of the species. Load all of the species onto your map. Does it look crowded? This reserve is FULL of wildlife. Look at the attribute table for these point files. You will see that some of the points have multiple animals associated with them. Now that you know how big the reserve is, calculate the density of each species per km 2. This is a standard wildlife statistic that practitioners report. However, it s not always straightforward from this type of data. Make sure that you are using the number of individual animals, not the number of groups. You can, for example, highlight the entire attribute table and then use Selection Statistics to find the sum of the Number of animals. 6

7 [The density calculator ArcToolbox Spatial Analyst Tools point density will give you a raster, or grid of densities across the whole map the mean of this would be the same estimate, but it seems more laborious to me] Densities of 8 species Giraffe Impala Kudu Rhino Waterbuck Wildebeest Warthog Zebra Pick two of the species and perform habitat selection analyses on them for vegetation and water preferences. The method you will use for this is slightly different than before. To understand why, we need to step back from the machine and go back to biological mechanism. The data we used before is a sequence of locations for single herds. For this part, we are looking at a census of multiple groups simultaneously. Thus, we want to know if we are asking the question where do more groups occur or where do more individuals occur. I presume the latter for most habitat selection analyses, so we want to make use of the Number column in the attribute data for the census species. This means, instead of assigning the animals to the vegetation type or water distance, we want to assign the vegetation type or water distance to the animal groups. Under Hawth s Tools Analysis Tools Intersect Point Tool this allows you to select the point file, the polygons you are assigning to them, and which field within the file. [This is similar to assigning data by location in geoprocessing in ArcView 3.x, only nicely automated so that you can select the right columns of data for your analyses]. Once again, you can create summaries based on habitat category make sure you sum the number of individuals and export the data from the attribute table into a nice excel file and use it to look at proportions and run χ 2 analyses. Congratulations you have reached the end of this exercise. 7

8 REFERENCES CITED IN THIS HANDOUT 1. Ryan, S.J., Spatial ecology of African buffalo (Syncerus caffer) and their resources in a savanna landscape, in Environmental Science, Policy, and Management. PhD thesis. 2006, University of California at Berkeley: Berkeley, CA. p Ryan, S.J. and W.M. Getz, A spatial location allocation GIS framework for managing water sources in an exemplar savanna nature reserve. South African Journal of Wildlife Research, (2): p Seaman, D.E. and R.A. Powell, An evaluation of the accuracy of kernel density estimators for home range analysis. Ecology, (7): p Neu, C.W., C.R. Byers, and J.M. Peek, A technique for analysis of utilization-availability data. Journal of Wildlife Management, : p Ryan, S.J., C.U. Knechtel, and W.M. Getz, Range and habitat selection of African buffalo in South Africa. Journal of Wildlife Management, (3). 8