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Based on the model results, we see that almost all the RBN scores for this planning unitwere calculated above 1. This indicates there is a high abundance of unique targetocc urrences/areas contained within this planning unit compared to the same target(s)occurring in the rest of the Tydixton Park watershed. Remember that these scores arerelative and their range of values can vary widely depending on the input data that isused. The highest two scores were for two rare bat species where there are very fewoccurrences throughout the watershed. Similarly, you will notice that Dry Alluvial Forestis a very rare habitat type and it occurs only in small amounts within the watershed ( totalof 38.8 hectares). If you look at planning unit 65, you will notice that a large majority ofwhat does exist for this habitat is located in that unit (approximately 28.79 hectares). Thiswas the highest individual RBN score in the entire watershed (73.87). Similarconclusions can be made for planning unit 65 where Wet_Alluvial_Forest andSmall_Rivers_Non_Karstic also scored relatively high RBN values (34.06 and 21.64,respectively). Please note that if you are only using point feature class targets, your RBIscores will be significantly lower, given the fact that there is no area to calculate forpoints.You can choose to symbolize the RBI values for a single Target using the“ your_output_name_RBI_ALL_TARGETS” feature class. To do this, go to the layer’sproperties dialog and select the “Definition Query” tab. Then use the query builder tocreate a query that will only display the information for the target you are interested in.See the example below.TNC Protected Area Tools (PAT) Version 3.0The Nature Conservancy, August 200938
Once this step is performed, you can symbolize this layer using the “symbology” tab in the layer properties.Classified RBI values based solely on the “Medium_River_Non_Karstic” streams target.TNC Protected Area Tools (PAT) Version 3.0The Nature Conservancy, August 200939
Page 1 and 2: Protected Area Tools (PAT)TMfor Arc
Page 3 and 4: AcknowledgementsThe idea for the de
Page 5 and 6: Mandatory Requirements Needed to Ru
Page 7 and 8: Installing the Protected Area Tools
Page 9 and 10: The majority of the work that goes
Page 11 and 12: data to spatially represent the spe
Page 13 and 14: 2003, Araújo et al. 2002). In some
Page 15 and 16: 1.1 Setting up the ERS TableSuccess
Page 17 and 18: 1.1.1 Overlay FunctionAnother item
Page 19 and 20: features have been added to the map
Page 21 and 22: the output will automatically defau
Page 23 and 24: Once you click OK in the previous m
Page 25 and 26: unit or feature (i.e. polygon) must
Page 27 and 28: higher elevations and ridges moving
Page 29 and 30: 1.3.4.2 Marine ERS ModelsDeveloping
Page 31 and 32: MODULE 2. Relative Biodiversity Ind
Page 33 and 34: Normalized relative biodiversity in
Page 35 and 36: EXERCISE 2. Calculating the Relativ
Page 37: the targets (polygons with lots of
Page 41 and 42: This selection routine will choose
Page 43 and 44: 3.0 The MARXAN AlgorithmOne of the
Page 45 and 46: 6. All input features must have the
Page 47 and 48: grid of squares or lattice of hexag
Page 49 and 50: • To make "area" and "length" com
Page 51 and 52: Sug gested steps for preparing inpu
Page 53 and 54: 2. Planning Unit File (pu.dat)This
Page 55 and 56: ‘id2’ are set but no value for
Page 57 and 58: conservation target files are alrea
Page 59 and 60: An example of what an attribute tab
Page 61 and 62: values. These values will be used i
Page 63 and 64: Occurrence (OCC), Minimum Clump (CL
Page 65 and 66: 3.2.4 Combining Marxan Input FilesI
Page 67 and 68: 2. Click onto the Run Options tab p
Page 69 and 70: This is the folder where the output
Page 71 and 72: 3.4 Joining and Displaying Marxan O
Page 73 and 74: Figure 12. Results of joining the t
Page 75: McPherson, M, S. Schill, G. Raber,

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