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* Metric Name: Goldspotted Oak Borer *  

* Tier: 2  

* Data Vintage: 2010 to 2021  

* Unit Of Measure: Count, trees per acre  

* Represent element and pillar: Yes  

* Type and distribution of data: Asymmetric distribution representing count values. The raw data range from 26 to 345630.  

* Translation: Where is goldspotted oak borer mortality low?  

* Translation method and outcome: Raw data values translated to range from +1 to -1 representing more favorable to less favorable conditions, respectively. **** The proposition of more favorable is based on the objective of goldspotted oak borer mortality low (negative linear slope). More favorable (translated to +1) set at 345630, less favorable (translated to -1) set at > 26\. Alternative approaches could be to set -1 at the top value, but that would result in a more favorable interpretation of goldspotted oak borer mortality. 

Figure . Histogram and scoring of goldspotted oak borer in Southern California

Figure . Histogram of translated goldspotted oak borer in Southern California

Figure 152. Maps displaying raw metric and translated metric goldspotted oak
borer in Southern California

  

* Metric Definition and Relevance: Tree mortality and other forest damage is detected by annual aerial surveys over forested lands by state and federal agency staff. The primary purpose of the aerial survey is to create sketch maps of areas containing current year conifer and hardwood mortality, defoliation, and other damage. Number of trees and acres with damage are calculated for areas surveyed and reported annually using the methodology described below. Aerial surveys have been recognized for over fifty years as an efficient and economical method of detecting and monitoring forest change events over large forested areas. As with all remotely sensed data, some amount of ground-truthing is required before the data can be considered reliable. The goldspotted oak borer was identified based on field surveys starting in 2006, and coded as goldspotted oak borer during aerial detection surveys beginning in 2010.  

* Credits: R5 Aerial Detection Monitoring \--USDA Forest Service, Forest Health Monitoring (FHM)