Data Types Requested
For Data Call 1, there are different data types that are being collected for this NWPRP effort: spatial layers and plot data. Spatial layers include GIS layers of whitebark pine distribution and abundance. Plot data are georeferenced plot-based field measurements of whitebark pine abundance and health across its range. We are asking that plot-level data be submitted using the Hi5DB format as explained below. In addition, if agencies have GPS coordinates of whitebark pine stands with no other information, polygons enclosing whitebark pine communities, or presence/absence data, all data types should be submitted to us as well.
Note: We recognize that agencies recently sent the U.S. Fish & Wildlife Service (F&WS) their whitebark pine distribution GIS layers and health data in response to the F&WS data call in connection with their on-going whitebark pine status review. F&WS will share with us these distributional data, unless an agency placed a restriction on data sharing. If your agency provided data to F&WS with restrictions, we would be grateful if you would send us these data directly. We will reach out and contact you if we do not hear from you.
Please submit data to Whitebark Pine Ecosystem Foundation Executive Assistant, Julee Shamhart ([email protected]) as either geotiff or zipped shapefiles. Data can be submitted in the Forest Service T: drive folder (T:\FS\RD\RMRS\Science\FFS\Projects\NWPR\data_depository) or placed in the Whitebark Pine Ecosystem Foundation Dropbox. To access the WPEF Dropbox, please send an email to Julee Shamhart requesting a shared Dropbox folder in which to place your data. You will receive a link to a folder shared only with you. Include all available location and health data attributes in the format provided in the attached example (DataSubmissionEx.xls).
Attributes requested include:
• Date: the date the data were collected
• Potential: 0 or 1 describing whether there is potential for WBP (if you do not know how to evaluate, please omit)
• Existing: 0 or 1 describing whether WBP has been observed (even 1 tree)
• Abundance: We accept two measures of the abundance of whitebark pine – living trees per acre and live basal area (square feet per acre). Please note that these are for trees that are above 4.5 feet tall– no seedlings
• Mountain Pine Beetle: We accept two measures of the impact of mountain pine beetles on whitebark pine – the percent of living whitebark pine trees (>4.5 ft tall) that have evidence of mountain pine beetle occurrence and the percent of the trees (>4.5 ft tall) that were killed by mountain pine beetle.
• White pine blister rust: We accept two measures of the impact of blister rust on whitebark pine – the percent of living whitebark pine trees (>4.5 ft tall) that have evidence of blister rust occurrence and the percent of the trees (>4.5 ft tall) that were killed by blister rust.
*Whenever possible, please submit data in the requested format; however, data existing in other formats will also be accepted. We do not currently have the funding or resources to extensively reformat or digitize data, but we will attempt to standardize unformatted data if the resources become available. Maps can be scanned and submitted for potential digitizing if that is the only data you have available.
Efforts by the Rocky Mountain Research Station (RMRS) are currently underway to collect all data on whitebark pine in the U.S. to augment an existing database. This includes data on distribution, health condition, regeneration, wildlife, or any other aspect that includes whitebark pine information. Any data that describe whitebark pine are being requested. Examples include stand inventories, research plots, or other field studies. The RMRS has assumed oversight for the Hi5DB database (formally WLIS). We are using this modified database to collect and serve the data to those who need it to prioritize core areas. In addition, we will make use of distributional and health data in the course of developing the National Whitebark Pine Restoration Plan and to improve existing spatial data layers.