Reference Document 6-2
Appendix 6
Detailed mapping steps Note: For more details on the mapping steps, code used to create this layer is also provided. The code is an .ipynb file that can be opened and run in ArcPro. Prepare the intact habitat cores data • From the TIGER/Line shapefile, make a layer of the NC state boundary. • Reproject all inputs to a common equal area projection and limit the extent to the area near North Carolina, to speed up analysis time. • In the intact habitat cores data, make a copy of the Unique Core Identifier. In the geodatabase, the field name is "Value", and the alias is "Unique Core Identifier." Since we are exporting as a shapefile, choose a shorter and more descriptive name for the new field. Here, we choose "Core_UID". • Delete all the other fields from the cores layer, keeping the “"Core_UID" (formerly "Value") that could be used to join back to the larger attribute if desired. Prepare the plant Heritage data • Start the plant analysis using the distributed EO dataset. Only keep records that are plants, with an accuracy of low or better, and with a status that includes only Endangered, Threatened, Special Concern-Vulnerable, Special Concern-Historical. o Use a select and the following query: ACCURACY IN ('1-Very High', '2-High', '3- Medium', '4-Low') And NC_STATUS IN ('E', 'T','SC-V','SC-H') And NAME_CATGY = 'Plant' • Further limit the plant records to those with a last observed date of the year 2000 or more recent by making a new numeric field from the Last_Obs field. This is a text field, but for the records that we want to keep, the text field always starts with the year. By calculating this new numeric field from the text field, it will throw an error for those fields that do not start with a number, which will allow us to keep the rows that have the desired dates. From the new field, retain records with a year of 2000 or more recent. • Dissolve by both scientific name and "ELEMENT_ID". Judy Ratcliffe and Suzanne Mason with NC Heritage asked to keep the "ELEMENT_ID" field, in addition to scientific name, because scientific names can change over time. • Since we are dissolving on both, we need to check to see if there are duplicates. It is hard to evaluate if we have any double species due to name changes, so do a second dissolve just on the "ELEMENT_ID". Compare the two different dissolve outputs. They have the same number of records, which confirms that keeping the species names isn’t causing double counting (which could happen if the name had changed and both versions were used in the dataset).
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2025 NC Wildlife Action Plan
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