Interactive Numeric & Spatial Information Data Engine

This GIS digital data set portrays the average date when lilacs start bloom in Idaho. Information on dates when plants and animals reach various stages in their development is referred to as phenological data. The purple common lilac (Syringa vulgaris L.) was chosen as the indicator of plant development in western regional phenological studies because it is well adapted and widely distributed throughout the Western United States. Approximately 160 observers scattered throughout Idaho observed the dates of lilac bloom for the 10 years of data used as a base for this study (from 1957 to 1966). Without the unselfish dedication of these volunteers this study would not have been possible.

Aspect was used as a surrogate to characterize areas that are relatively drier, therefor have lower live/dead fuel moistures. If the effects of vegetation are ignored, it was assumed that fuel moisture varies according to aspect. That is, with all else being equal, fuels are typically drier on southwesterly aspects, and moister on northeasterly aspects. Relative fuel moisture was assigned to 3 aspect classes : Azimuth (degrees) Relative Solar Radiation Relative Fuel Moisture 1 to 80; 351 to 360 low high Flat; 81 to 170; 261 to 350 moderate moderate 171 to 260 high low Excluding the effects of real-time weather, fire behavior is dependent upon the structure, composition, and arrangement of fuels; fuel moisture, and slope.

At best, predicting surface and canopy fuel loads from mid-scale data is problematic at best. The structure, composition, and arrangement of fuels are dependent upon the disturbance history of any given stand. Disturbance history includes natural processes (e.g., fire, wind, insects, and pathogens), as well as anthropogenic processes (e.g., silvicultural treatments and grazing practices). The only available proxy to the disturbance history (and consequently fuel loadings) available at a mid-scale level is the current structure and composition of vegetation (e.g., cover type, canopy cover, and size class). Unfortunately, the current structure and composition of vegetation is a very poor predictor of stand history. For example, stands having the same cover type, canopy cover, and size class may have substantially different histories; one could have been logged and the fuels cleaned up, and the other could have been impacted by mountain pine beetles. Since the structure and composition of the current vegetation is a poor predictor of fuel loadings, we had Forest Service and BLM fuels specialist assign a very coarse qualitative ranking of "fuel hazard" (e.g., containment problems) to unique combinations of PVT and FBFM. The specific rule sets can be found in Table 24 of the "Idaho Interagency Assessment or Wildland Fire Risks to Communities: a Description of Methods". The specialists considered the following fire behavior attributes when making these assignments: ROS, fireline intensity, the potential for active crown fires, and the potential for spotting.

Anderson's (1982) fire-behavior fuel models were assigned to unique combinations of PVT, cover type, size class, and canopy density based upon field experience of U.S. Forest Service and Bureau of Land Management ecologists.

An ignition probability layer (fire density) was derived using an interpolation process (ArcInfo; pointinterp) of the fire start data. 2-km cells were used for the interpolation process because fire locations were commonly only reported to the nearest Public Land Survey Section (PLSS), approximately 1 square mile. Interpolation resulted in 2-km cells being attributed with the count of ignitions. Ignition probability was derived by classifying the density data into 5 classes (low to high) using the "natural break" algorithm included in ArcMap. The values represent relative values that have been standardized between 0.0 and 1.0

Slope steepness was used to reflect effects on relative fire behavior. It was assumed the steeper the slope, the higher the fire intensity, assuming other variables remain constant (weather; wind; structure, composition, and arrangement of fuels; fuel moisture, etc.). BehavePlus was used to model the relationship of fire intensity and slope. Slope Class Percent Slope Fire Intensity Rating 1 0-10% Low 2 10-30% Low 3 30-60% Moderate 4 >60% High

The Fire Restriction Areas represents a geographic location with similar timing for weather changes and resulting fire behavior potentials. Boundaries for each area generally follow county boundaries with some being placed along roadways, rivers, hydrologic divides or other known points that can be clearly described to the public and agency personnel. When a majority of land managers and agency administrators representing the jurisdictions within an area agree that the conditions warrant a restriction, the entire area will be placed in a restricted status. When land managers and agency administrators agree that the restrictions for that area can be removed, the entire area will rescind restrictions as a whole.

Sage-grouse core areas are habitats associated with 1) Montana's highest densities of sage-grouse (25% quartile), based on male counts and/or 2) sage-grouse lek complexes and associated habitat important to sage-grouse distribution.

Federal, state, and tribal fish hatcheries in the state of Idaho associated with fish distribution and abundance.

This data series contains 22 map layers for the University of Idaho Main Campus Moscow, Idaho. Map layers include building footprints, automobile, motorcycle and bike parking, curbs, land use, pedestrian lights, tree health, walkways, and sidewalk as well as others. Most data are not being updated on a regular basis and are current only to 2005.

Weed presence in Idaho, consolidated from datasets provided by BLM Boise District, BLM Twin Falls District, BLM Idaho Falls District, BLM Coeur d'Alene District, and the Idaho Department of Agriculture, from December 2005. Many errors noted. Users must review attributes before using. No corrections to any errors or inconsistencies have been made. See supplementary information.

For this analysis, it was assumed that a relative measure of the risks to communities from wildland fire could be characterized by integrating relative wildland fire risk, relative wildland fire hazard, and wildland urban interface. That is, within the wildland urban interface, risks are directly associated with the probability that an area will burn, as well as the likely fire behavior that would occur if that area did in fact burn. It was assumed that burn probability and likely fire behavior would contribute equally to the risks to communities. Agriculture, rock, urban, and water were not assigned a burn probability or relative fire behavior. Consequently, by definition, communities within these cover classes would not be at risk from wildland fires. For those communities occurring within burnable areas, a community’s risk to wildland fire could be characterized as follows: CAR = (WUI + Relative WildlandFireRiskstd + Relative WildlandFireHazardstd)/3 Using the three components mentioned above, RelFireRiskCommunities_ID_BLM, "Relative Risk to Communities from Wildland Fire in Idaho" was derived.

Idaho communities at risk from wildfire, as listed in the Federal Register (August 17,2001).

To determine the relative wildland fire hazard for this analysis, fuel hazard, expected fuel moisture (aspect), and slope effect on fire behavior were used. Fire behavior is dependent upon fuels (arrangement, composition, and structure - relatively constant), weather (variable), and topography (aspect/slope constant). For this analysis, relative fire hazard was analyzed excluding the effects of real-time weather condition. A rating of high displays areas where fires may be more difficult to control. Relative Wildland Fire Hazard was then derived using the standardize values for fuel hazard, fuel moisture (aspect), and fire intensity (slope): Relative Wildland Fire Hazard = Fuel Hazard + Fuel Moisture + Fire Intensity/3

Relative Wildland Fire Risk (i.e., the likelihood that a given area will burn) was analyzed by integrating fire ignition data, fire weather data (e.g., temperature, humidity, wind), and potential rate-of-spread considering the dominant surface fuel model. It was assumed that areas were more likely to experience wildland fire if they were in locations having: (1) a higher ignition probability; (2) a higher frequency of extreme fire weather; and (3) fuels having higher rates-of-spread (ROS). All three variables contribute equally to burn probability. Also it was assumed that wildland fires do not occur on the following land cover classes; agriculture, rock, urban, and water. There were five classes rating relative wildland fire risk in Idaho from "low" to "high". Areas rated as "high" are likely to have more fire ignitions, higher rates of spread, and are relatively hotter, drier, and windier in August. Relative Wildland Fire Risk = (Potential Fire Weather+Ignition Probability+ROS)/3 The derivation of each of these components to generate Relative Wildland Fire Risk is described in the metadata for each of those components.

Relative rate of spread was determined based on the estimated predominate surface fuel model as described in Anderson’s "Aids to Determining Fuel Models for Estimating Fire Behavior (1982)". These models (1-13) are representative of surface fuels only and key in on fuels that would be the primary carriers of wildland fire (i.e., grass, brush, timber, and logging slash). ROS values were then standardized between 0.0 and 1.0. The table below depicts how areas were rated based on fuel model FBFM Rate of Spread (Chains/hour) 1 78 2 35 5 18 6 32 8 2 9 7 10 8

For the purposes of this analysis, Wildland Urban Interface is mapped using 2000 Census data and the communities listed in Idaho as "at risk" in the 2001 Federal Register (Vol. 66, Number 160, August 17, 2001), buffered by 1 mile. There were weaknesses with both data sets; data representing "urban wildland communities" are commonly not incorporated communities, nor are they areas that can be precisely located from a geographic standpoint. The Census data accounts for permanent residences only; it does not account for seasonal residences (e.g., summer cabins and ski area condominiums), or residences occurring on public lands (e.g. leased cabin sites).

This spatial data contains a combination of data that was published in a map of South Central Idaho in the late 1990s from submissions from the Bureau of Land Management and the Bureau of Reclamation and data that was added from the Bureau of Land Management Boise District.