FHTET National Risk Mapping Approach

This approach is also a family of related approaches to predict tree mortality risk due to an invasive insect or pathogen based on expert opinion, forest inventory data, and other GIS data (Marsden and others 2005) , and also consult FHTET products web site: http://www.fs.fed.us/foresthealth/technology/products.shtml). Specifically, predictions are made of the potential basal area loss of susceptible tree species due to an invasive insect or pathogen. The location of suitable host species is interpolated using inverse-distance weighting based on forest inventory data. A multi-criteria risk ranking model is developed based on expert opinion about the factors that influence pest or pathogen establishment, spread, and tree mortality. An iterative process is used to develop risk maps, so the experts and analysts can alter the weighting of difference factors to adjust the maps to match expert opinion. This approach has been used to predict the potential effect of oak wilt in the North Central States and of wood wasp (Sirex noctilio Fabricius) throughout the conterminous United States: (http://www.fs.fed.us/foresthealth/technology/invasives_sirexnoctilio_riskmaps.shtml).

The following are the key required input data and their sources:

1. Principal United States ports - Army Corps of Engineers, Waterborne Commerce, Foreign Cargo Statistics
2. Markets for wood products - Federal Highway Administration, Freight Management and Operations, Freight Analysis Framework, Highway Truck Volume and Environmental Systems Research Institute's (ESRI) polygon data
3. Distribution centers - National Transportation Atlas Database
4. Species occurrence and basal area of individual tree species - USDA Forest Service, Forest Inventory and Analysis, National and New York State Christmas Tree Association websites
5. Road density and distance to road – United States Geological Survey, Heterogeneous Distribution Indicator

Use of this approach requires one or more experts on the pest or pathogen, expertise in the use of FIA data, and expertise in GIS software. The spatial scope is the conterminous Unites States for a single time period. Required software includes ArcView 3.x, Spatial Analyst ModelBuilder (ESRI, Inc.), and IDRISI 32 (a raster GIS software package). Model output includes maps of predicted occurrence based on: (1) hosts known to be susceptibleand (2) hosts suspected to be susceptible.

For regional and national risk analysis, the approach of mapping factors that influence a stressor and then combining these factors with weightings derived from expert opinion are intuitively appealing and fairly common. This flexible, iterative expert opinion-based approach can be used for virtually any pest or pathogen, and a risk map can be generated fairly quickly because the system is already in place. Other strengths of this approach include the use of national FIA data and the quantification of potential damage in terms of tree mortality. However, the flexible expert opinion-based approach is also a weakness because it is so open-ended, subjective, and difficult to validate. To date, it does not appear that an attempt has been made to determine which environmental factors were actually associated with pest presence, or to quantify uncertainties in GIS layers or predictions. In contrast, a statistical inference approach that made quantitative predictions of pest occurrence would be more useful because it could be better tested against validation data.