Interactive Numeric & Spatial Information Data Engine

Idaho BLM Areas of Critical Environmental Concern (ACECs), Research Natural Areas (RNAs), and Outstanding Natural Areas (ONAs). ACECs are areas where special management is needed to protect important historical, cultural, or scenic values, fish and wildlife resources, or other natural systems or processes, or to identify areas hazardous to human life and property. Criteria for ACECs can be found at: BLM Manual 1613 and 43 CFR 1610.7-2(b). RNAs are areas where natural processes are allowed to predominate and which is preserved for the primary purposes of research and education. Under current BLM policy, RNAs must meet the relevance and importance criteria of ACECs and are designated as ACECs. Criteria for RNAs can be found at: BLM Manual 1613 and 43 CFR 1610.7-2(b). ONAs are areas with high scenic values that have been little altered by human impact. Under current BLM policy, ONAs must meet the relevance and importance criteria of ACECs and are designated as ACECs. Criteria for ONAs can be found at: BLM Manual 1613 and 43 CFR 1610.7-2(b).

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.

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

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.

Fencelines (pasture, allotment, exclosure etc) for Boise District(BD) and Twin Falls(TF) District. The BD data came from a seperate fence layer AND the new pasture_arc layer, the TF data came from the pasture_arc layer

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.

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.

This theme shows Herd Management Areas (HMAs). Wild horses are managed in accordance with the Wild Free-Roaming Horse and Burro Act of 1971, which gives BLM the responsibility to protect wild horses while ensuring their populations are in balance with the ecological capacity of public lands. Idaho's public lands are home to over 640 wild horses that occupy six herd management areas (HMAs). Five herd management areas are located in the Lower Snake River District and one HMA is located in the Challis Field Office. BLM studies each HMA to determine how many wild horses the area can support while providing for other land uses and resource values. The overall capacity of the HMA to support wild horses is called its Appropriate Management Level (AML).

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

This geodatabase of point, line and polygon features is an effort to consolidate all of the range improvement locations on BLM-managed land in Idaho into one database. Currently, the line feature class only has range improvements from Boise District (Four Rivers, Owyhee, and Bruneau Field Offices), Twin Falls District (Shoshone, Burley and Jarbidge Field Offices) and Idaho Falls District (Salmon, Challis and Upper Snake Field Offices). Range improvements are structures intended to enhance rangeland resources, including wildlife, watershed, and livestock management. Examples of range improvements include water troughs, spring headboxes, culverts, fences, water pipelines, gates, wildlife guzzlers, artificial nest structures, reservoirs, developed springs, corrals, exclosures, etc. These structures were first tracked by the Bureau of Land Management (BLM) in the Job Documentation Report (JDR) System in the early 1960s, which was predominately a paper-based tracking system. In 1988 the JDRs were migrated into and replaced by the automated Range Improvement Project System (RIPS), and version 2.0 is currently being used today. It tracks inventory, status, objectives, treatment, maintenance cycle, maintenance inspection, monetary contributions and reporting. Not all range improvements are documented in the RIPS database; there may be some older range improvements that were built before the JDR tracking system was established. There also may be unauthorized projects that are not in RIPS. Official project files of paper maps, reports, NEPA documents, checklists, etc., document the status of each project and are physically kept in the office with management authority for that project area. In addition, project data is entered into the RIPS system to enable managers to access the data to track progress, run reports, analyze the data, etc. Before Geographic Information System technology most offices kept paper atlases or overlay systems that mapped the locations of the range improvements. The objective of this geodatabase is to migrate the location of historic range improvement projects into a GIS for geospatial use with other data and to centralize the range improvement data for the state. This data set is a work in progress and does not have all range improvement projects that are on BLM lands. Some field offices have not migrated their data into this database, and others are partially completed. New projects may have been built but have not been entered into the system. Historic or unauthorized projects may not have case files and are being mapped and documented as they are found. Many field offices are trying to verify the locations and status of range improvements with GPS, and locations may change or projects that have been abandoned or removed on the ground may be deleted. Attributes may be incomplete or inaccurate. This data was created using the standard for range improvements set forth in Idaho IM 2009-044, dated 6/30/2009. However, it does not have all of the fields the standard requires. Fields that are missing from the line feature class that are in the standard are: ALLOT_NO, MGMT_AGCY, ADMIN_ST, ADMIN_OFF, SRCE_AGCY, MAX_PDOP, MAX_HDOP, CORR_TYPE, RCVR_TYPE, GPS_TIME, UPDATE_STA, UNFILT_POS, FILT_POS, DATA_DICTI, GPS_LENGTH, GPS_3DLGTH, AVE_VERT_P, AVE_HORZ_P, WORST_VERT, WORST_HORZ and CONF_LEVEL. Several additional fields have been added that are not part of the standard: top_fence, btm_fence, admin_fo_line and year_checked. There is no National BLM standard for GIS range improvement data at this time.

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.

This geodatabase of point, line and polygon features is an effort to consolidate all of the range improvement locations on BLM-managed land in Idaho into one database. Currently, the polygon feature class only has range improvements from Boise District (Four Rivers, Owyhee, and Bruneau Field Offices), Twin Falls District (Shoshone, Burley and Jarbidge Field Offices) and the Salmon Field Office of the Idaho Falls District. Range improvements are structures intended to enhance rangeland resources, including wildlife, watershed, and livestock management. Examples of range improvements include water troughs, spring headboxes, culverts, fences, water pipelines, gates, wildlife guzzlers, artificial nest structures, reservoirs, developed springs, corrals, exclosures, etc. These structures were first tracked by the Bureau of Land Management (BLM) in the Job Documentation Report (JDR) System in the early 1960s, which was predominately a paper-based tracking system. In 1988 the JDRs were migrated into and replaced by the automated Range Improvement Project System (RIPS), and version 2.0 is currently being used today. It tracks inventory, status, objectives, treatment, maintenance cycle, maintenance inspection, monetary contributions and reporting. Not all range improvements are documented in the RIPS database; there may be some older range improvements that were built before the JDR tracking system was established. There also may be unauthorized projects that are not in RIPS. Official project files of paper maps, reports, NEPA documents, checklists, etc., document the status of each project and are physically kept in the office with management authority for that project area. In addition, project data is entered into the RIPS system to enable managers to access the data to track progress, run reports, analyze the data, etc. Before Geographic Information System technology most offices kept paper atlases or overlay systems that mapped the locations of the range improvements. The objective of this geodatabase is to migrate the location of historic range improvement projects into a GIS for geospatial use with other data and to centralize the range improvement data for the state. This data set is a work in progress and does not have all range improvement projects that are on BLM lands. Some field offices have not migrated their data into this database, and others are partially completed. New projects may have been built but have not been entered into the system. Historic or unauthorized projects may not have case files and are being mapped and documented as they are found. Many field offices are trying to verify the locations and status of range improvements with GPS, and locations may change or projects that have been abandoned or removed on the ground may be deleted. Attributes may be incomplete or inaccurate. This data was created using the standard for range improvements set forth in Idaho IM 2009-044, dated 6/30/2009. However, it does not have all of the fields the standard requires. Fields that are missing from the polygon feature class that are in the standard are: ALLOT_NO, POLY_TYPE, MGMT_AGCY, ADMIN_ST, and ADMIN_OFF. The polygon feature class also does not have a coincident line feature class, so some of the fields from the polygon arc feature class are included in the polygon feature class: COORD_SRC, COORD_SRC2, DEF_FET, DEF_FEAT2, ACCURACY, CREATE_DT, CREATE_BY, MODIFY_DT, MODIFY_BY, GPS_DATE, and DATAFILE. There is no National BLM standard for GIS range improvement data at this time.

This geodatabase of point, line and polygon features is an effort to consolidate all of the range improvement locations on BLM-managed land in Idaho into one database. Currently, the point feature class only has range improvements from Boise District (Four Rivers, Owyhee, and Bruneau Field Offices), Twin Falls District (Shoshone, Burley and Jarbidge Field Offices) and Idaho Falls District (Salmon, Challis and Upper Snake Field Offices). Range improvements are structures intended to enhance rangeland resources, including wildlife, watershed, and livestock management. Examples of range improvements include water troughs, spring headboxes, culverts, fences, water pipelines, gates, wildlife guzzlers, artificial nest structures, reservoirs, developed springs, corrals, exclosures, etc. These structures were first tracked by the Bureau of Land Management (BLM) in the Job Documentation Report (JDR) System in the early 1960s, which was predominately a paper-based tracking system. In 1988 the JDRs were migrated into and replaced by the automated Range Improvement Project System (RIPS), and version 2.0 is currently being used today. It tracks inventory, status, objectives, treatment, maintenance cycle, maintenance inspection, monetary contributions and reporting. Not all range improvements are documented in the RIPS database; there may be some older range improvements that were built before the JDR tracking system was established. There also may be unauthorized projects that are not in RIPS. Official project files of paper maps, reports, NEPA documents, checklists, etc., document the status of each project and are physically kept in the office with management authority for that project area. In addition, project data is entered into the RIPS system to enable managers to access the data to track progress, run reports, analyze the data, etc. Before Geographic Information System technology most offices kept paper atlases or overlay systems that mapped the locations of the range improvements. The objective of this geodatabase is to migrate the location of historic range improvement projects into a GIS for geospatial use with other data and to centralize the range improvement data for the state. This data set is a work in progress and does not have all range improvement projects that are on BLM lands. Some field offices have not migrated their data into this database, and others are partially completed. New projects may have been built but have not been entered into the system. Historic or unauthorized projects may not have case files and are being mapped and documented as they are found. Many field offices are trying to verify the locations and status of range improvements with GPS, and locations may change or projects that have been abandoned or removed on the ground may be deleted. Attributes may be incomplete or inaccurate. This data was created using the standard for range improvements set forth in Idaho IM 2009-044, dated 6/30/2009. However, it does not have all of the fields the standard requires. Fields that are missing from the point feature class that are in the standard are: ALLOT_NO, MGMT_AGCY, ADMIN_ST, ADMIN_OFF, SRCE_AGCY, MAX_PDOP, MAX_HDOP, CORR_TYPE, RCVR_TYPE, GPS_TIME, UPDATE_STA, UNFILT_POS, FILT_POS, DATA_DICTI, GPS_HEIGHT, VERT_PREC, HORZ_PREC, and CONF_LEVEL. Several additional fields have been added that are not part of the standard: wrpt_idwrn, bird_laddr, and year_checked. There is no National BLM standard for GIS range improvement data at this time.

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 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.

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.

This file contains data for riparian areas in the state of Idaho. The data for the Challis Field Office area was derived from Idaho GAP data by selecting all vegetation classes considered to fall under riparian area. This dataset has not been verified.

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