NVCS

This Python project is Stage 1 of an effort to populate a new condition attribute, NVCS_CD, to NIMS and FIADB condition tables. NVCS_CD is a classification variable describing the present vegetative community (very similar to forest type). NVCS stands for National Vegetation Classification Standard.

This initial version contains separate code bases for different FIA regional groups. For additional information see the relevant README in the regional codebase folders: * NVCS-EAST

Dependencies

• Python 3
• Cx_Oracle Python module

Set-Up (Windows)

1. Download and install Python 3.*:

   • Go to python.org and download the "Windows x86 executable installer"

   • Run the installer.

2. Download and install cx_Oracle:

   • Go to pypi.python.org

   • Open a command prompt and type:

   python -m pip install cx_Oracle
   

3. Extract the attached zip file. I extracted it to %userprofile%\NVCS.

4. Make sure your Windows ORACLE_HOME environment variable is set or appears on the PATH environment variable. Otherwise cx_Oracle may fail to resolve the net service name, for example ORACLE_HOME=C:\oracle64\product\12.2.0\client\bin

5. Test the database connection:

   • Open a python command prompt.

   import cx_Oracle
   con = cx_Oracle.connect('/@FIADB01P')
   #If you get the >>> back then it worked and you can close the connection:
   con.close()

Background

The U.S. National Vegetation Classification (USNVC) Standard was adopted by the Federal Geographic Data Committee as a federal standard for reporting vegetation information. NatureServe and the U.S. Forest Service (USFS) are collaborating to implement the USNVC in the USFS Forest Inventory and Analysis (FIA) Program. The USNVC uses an ecological vegetation approach that integrates ecological and human factors with all vegetation layers into separate 8-level hierarchy of types for both natural and cultural (plantation) forests. The goal of our project is to classify conditions on FIA "Phase 2" (P2) plots across the U.S. to the macrogroup level for natural forests and to type for plantation forests. In this first phase, for eastern U.S. forests, NatureServe scientists first completed a narrative-based key that used available FIA attributes, including tree and environmental data, tree life-history data (nativity, wetland indicator status, ruderality), and ecoregional information, to assign P2 plot conditions to 27 macrogroup and 11 plantation types. The process of computerizing the key was iterative. NRS-FIA staff (Kevin Nimerfro) developed a computer algorithm based on this key, then produced summary outputs of macrogroup and plantation types and distributions, which NatureServe staff compared with published descriptions of the types. The final version of the key was validated for natural forests using P2 FIA plots previously assigned to USNVC groups and macrogroups by experts working with the LandFire program. By assigning a macrogroup and plantation type to each forested condition, FIA can report forest type data for eastern U.S. forests using the USNVC standard.　 This information will facilitate collaborations with other agencies using the USNVC.　FIA data also improve the USNVC by providing valuable quantitative data on macrogroup tree composition and distribution.

As the first phase of a national strategy, this project developed and documented an approach for attributing FIA P2 forested conditions with the USNVC macrogroups in the eastern half of the US (US Forest Service Regions 8 and 9), from Minnesota to Maine, south to Louisiana and eastern Texas to Florida. The region extends as far west as the tallgrass prairie ecoregion (Ecoregions 250, 255), including a small eastern portion of the Great Plains states of Kansas, Nebraska, North Dakota, and South Dakota; the prairie province extends further west in Oklahoma and Texas, so larger proportions of these two states are included. FIA plots in ecoregions of western portions of these six plains states do not yet have Macrogroup classification keys. A future goal is to develop keys and code for attributing macrogroup to the western half of the US, at which time those western portion of NRS-FIA and SRS-FIA states will also be completed.

NatureServe scientists Don Faber Langendoen and Shannon Menard first completed a narrative-based key that used available FIA attributes and tree species and life-history data to assign P2 plot conditions to 27 macrogroup types and 11 plantation types in eastern US. The process of computerizing the key was conducted primarily by Kevin Nimerfro. Once the first iteration of the key was completed, it was translated into a Python program (by Kevin Nimerfro), which is used to assign macrogroup codes to plot conditions. The Python program was generated from a set of configuration files that describe the logic and flow of the couplets in the key hierarchy. These configuration files allow for frequent code changes including restructuring of the hierarchy. Likewise, it will be easy to extend the key (e.g. include the Western U.S.) or develop a separate key for another region of interest (e.g. a single state) – once NatureServe develops new keys for the West.