Solitude or Primitive and Unconfined Recreation Quality Indicators

Monitoring the Solitude or Primitive and Unconfined Recreation Quality assesses whether management of a wilderness is trending over time towards protecting outstanding opportunities for specific unique recreational experiences. Key indicators and measures monitor solitude (from activities occurring both inside and outside of wilderness), primitive recreation, and unconfined recreation. This section provides detailed guidance for monitoring the following indicators and measures:

• 5.2 Indicator: Remoteness from Sights and Sounds of Human Activity Inside

Wilderness

• • 5.2.1 Measure: Index of Encounters
  • 5.2.2 Measure: Index of Recreation Sites Within Primary Use Areas
  • 5.2.3 Measure: Acres of Wilderness Away From Access, Travel Routes and Developments Inside Wilderness
  • 5.2.4 Measure: Miles of Unauthorized Trails
• 5.3 Indicator: Remoteness from Sights and Sounds of Human Activity Outside

the Wilderness

• • 5.3.1 Measure: Acres of Wilderness Away From Adjacent Travel Routes and Developments Outside the Wilderness
• 5.4 Indicator: Facilities That Decrease Self-Reliant Recreation
  • 5.4.1 Measure: Index of NFS Developed Trails
  • 5.4.2 Measure: Number of Authorized Constructed Recreation Features
• 5.5 Indicator: Management Restrictions on Visitor Behavior
  • 5.5.1 Measure: Index of Visitor Management Restrictions

5.2 Indicator: Remoteness from Sights and Sounds of Human Activity Inside Wilderness

This indicator focuses on wilderness visitation and the capacity of the wilderness setting to allow for escape from the sights and sounds of human activity. There are four measures under this indicator: one required measure on encounters and three measures on other aspects of remoteness from human activity inside wilderness from which units are required to select at least one.

5.2.1 Measure: Index of Encounters

This measure monitors encounters by assessing one of the following, listed in order of preference: (1) an index evaluating traveling and camp encounters; (2) the number of traveling encounters or camp encounters (but not both); (3) the number of visitors; or (4) the trend in visitation. Local units may select the appropriate protocol option as described in step 1 below. Local data are compiled and stored in local archives. Local staff calculate the measure value. Table 2.5.1 describes key features for this measure.

Table 2.5.1—Summary of measure type, protocol options, local tasks, national tasks, and frequency of data reporting for measure “Index of Encounters.”

Protocol

Step 1: Determine which protocol option is appropriate for the wilderness. The four protocol options for this measure are summarized below, listed in order of preference from highest to lowest data adequacy.

Protocol Option 1—Index of Traveling and Camp Encounters. This protocol option requires encounter data on both traveling encounters and camp encounters. The mean number of traveling encounters per hour and the mean number of camps seen from occupied sites are combined in an index to derive the measure value.

Protocol Option 2—Number of Traveling or Camp Encounters. This protocol option only requires one type of encounter data—either traveling encounters or camp encounters—but not both. The measure value is either the mean number of traveling encounters per hour or the mean number of camps seen from occupied sites.

Protocol Option 3—Number of Visitors. If direct data on encounters are not available, indirect (proxy) data on visitation may be used instead. For this protocol option, the measure value is the number of visitors.

Protocol Option 4—Trend in Visitation. If there are no direct data on encounters or data on visitation, professional judgment may be used to determine the trend in this measure. For this protocol option, the measure value is the perceived trend in visitation, reported as increasing, stable, or decreasing.

To determine which protocol option is most appropriate, local units must first identify which types of data sources (encounter data, visitation data, or professional judgment) are available for a wilderness. Given the great amount of local variability in data collection, there is no strict formula for selecting the preferred data source. If a wilderness has multiple types of data (e.g., traffic counter data for some areas, traveling encounter data for other areas), select the best source, taking into account the geographical coverage, amount of data collected (i.e., number of days of monitoring), and accuracy of the method. In some cases the local unit may choose one of the options as the required measure and then one of the other options as a locally developed measure. And in some cases, it may be that combining different data sources generates the best overall assessment; if so, this should be considered professional judgment and the Protocol Option 4–Trend in Visitation, should be selected. Additional considerations for determining the most appropriate data source are described below by data type.

Encounter data (for Protocol Options 1 and 2). Valid traveling or camp encounter data should follow the Forest Service national minimum protocol for monitoring outstanding opportunities for solitude, or should be compiled using a locally defined protocol that provides data quality and quantity comparable to, or better than, the national minimum protocol. The national minimum protocol, available online at http://www.wilderness.net/toolboxes/documents/WC/National_Minimum_ Protocol_Solitude.pdf, was used in the 10-year Wilderness Stewardship Challenge, and it provides detailed instructions for sampling, collecting data, standardizing data, and reporting results for WSP.

Use of informal encounter data collected opportunistically is not recommended unless these records include the basic data fields required in the national minimum protocol to standardize encounter rates across locations and dates. Specifically, information for each observation session must include the interval of time when data were collected and the location of data collection. If such information is not collected, it is not possible to track trends over time with confidence, and the data should not be used for this measure. If encounter data are used to evaluate this measure, local units must be confident that data from each monitoring period are comparable, meaning data come from the same location and use season.

Visitation data (Protocol Option 3). Visitation data may be collected under locally developed protocols through a variety of data sources, including permits, trailhead registers, traffic counters, or other means. To determine whether visitation data are appropriate to use for this measure, or to choose the best visitation data from multiple potential sources, consider two primary factors:

1. Data accuracy—Data accuracy is similar to data adequacy (see section 1.2.3

of part 2). Monitoring systems vary considerably in the accuracy of the data collected. For instance, mechanical counters (e.g., car counters, TRAFx trail counters) can be highly accurate with complete 24/7 coverage, while self-issue permits can have low and variable compliance rates, resulting in poor data accuracy. The data source with the highest accuracy should be chosen. Traffic count data are often more accurate and complete than ranger reports, so if both types of data are available, it is advisable to use the traffic count data.

1. Geographical coverage—Many units collect visitation data for limited locations.

This is not necessarily a problem if data for the same locations are collected in subsequent years, and if the protocols provide at least as complete coverage as required in the national minimum protocol. Ideally, data from more locations would be preferable, but coverage will often be less of a concern than data accuracy.

Professional Judgment (Protocol Option 4). If data for encounters or visitation are not available, professional judgment may be used to determine the trend in visitation. Local units would not be expected to report actual estimates of encounters or visitation; instead they would report the perceived trend at 5-year intervals. If a wilderness has multiple types of data (e.g., visitation data for some areas, encounter data for others), the best decision might be to combine these sources through professional judgment.

Step 2: Document the data compilation strategy. To ensure confidence in tracking trends, data must be compiled consistently over time. Given the amount of variability in data sources and protocol options for this measure, it is essential that local units document the data compilation strategy (including the unit of measure as well as the timing, location, and intensity of data collection) for each wilderness. From year to year, local units should also document any special circumstances that may have affected data collection (e.g., equipment failures, gaps in data, or weather events that may have affected visitor use). Documentation may consist of a brief narrative or detailed instructions, and may be stored locally, on shared drives, or uploaded to the WCMD.

If encounter or visitation data are used, local units must document the unit of measure as “people,” “vehicles,” or “groups” (see table 2.5.2). The specific choice of unit of measure is not critical as long as each monitoring cycle uses the same units over time to assess trends. For some data sources (e.g., permits or trail registers), it is simpler to use “groups” as the unit of analysis, rather than “people,” because this requires only counting the total number of entries rather than summing the number of people in each group.

Table 2.5.2—Choices for units of measure for encounters and visitation.

To be able to track change over time, data must be collected in the same places and during the same seasons each monitoring cycle. Documentation for each wilderness should include a map that clearly identifies locations of data collection (e.g., zones monitored for encounters or trailheads where traffic counters are placed). Given the extreme variation of visitor use across the year, it is advised only to collect and report data for the primary use season (additional guidance on this is provided in the national minimum protocol). The primary use season will vary depending on where a wilderness is and the type of visitor use it receives. If National Visitor Use Monitoring (NVUM) data are used (see Caveats and Cautions for concerns about using NVUM), document specific sampling sites and dates from each monitoring cycle. This information provides context for inferring whether differences in NVUM’s visitor use estimates are due to actual changes in use, or whether they are an artifact of changes in sampling times or locations.

Documentation for this measure should also include information on the sampling intensity and data accuracy. Because visitor use is highly dependent on weather, fire, publicity about specific locations, and other factors, measures based on a small sample of dates in any given year may be a poor indicator of overall visitor use or encounter rates. The more dates included in sampling, the greater the likelihood of drawing correct interpretations about trends over time. Similarly, including assessments of data accuracy (e.g., documenting compliance rates for self-issue permits) allows for more confidence in interpreting trends over time. If traffic counters are used, local units also need to perform calibration tests to ensure the accuracy of the data. TRAFx provides links to various studies and documents to help local units design calibration studies (https://www.trafx.net/counting_methodology.htm).

If professional judgment is used to assess trends in visitation, local units must document who made the assessment and the basis for their determination. For example, if informal encounter data were combined with self-issue permit data to derive the trend in visitation, those data sources and the data adequacy of each should be recorded.

Step 3: Compile and process the data. Data may be collected over a span of multiple years within the 5-year reporting period for this measure. For example, encounter data may be collected in different locations in different years, with a full cycle of monitoring (all identified monitoring areas) completed after 5 years. Or, partial data may be collected for a single area across multiple years. Data are considered complete when a sufficient amount of data (per the national minimum protocol) have been collected for all monitoring areas. Ideally, it would be better to collect encounter or visitation data annually (i.e., more frequently than the minimum 5-year frequency required for this measure) because wilderness visitation can be quite variable and can depend on many factors, such as snowpack, weather conditions, fire events, and economic conditions. It is recognized, however, that most wildernesses will not be able to collect complete data for all locations every year.

Once all data have been compiled, the data are processed to derive the measure value. Data processing requirements are described below for each protocol option.

Protocol Option 1—Index of Traveling and Camp Encounters. Traveling encounters are generally reported as the number of encounters (people or groups) per hour, while camp encounters are generally reported as the number of camps (i.e., the number of groups) seen from occupied sites. While traveling and camp encounter data may be processed in a variety of ways, the national minimum protocol suggests recording the mean number of encounters per hour (i.e., the mean encounter rate) separately for each monitoring area. For this protocol option, local units must compute the grand mean (i.e., the mean of means) for a wilderness for both traveling and camp encounters by averaging the mean encounter rate across all monitoring areas within a wilderness, as illustrated in tables 2.5.3 and 2.5.4.

Table 2.5.3—Example of computing the grand mean number of traveling encounters per hour based on data collected using the national minimum protocol.

Table 2.5.4—Example of computing the grand mean number of camp encounters based on data collected using the national minimum protocol.

Local units then combine the grand means for traveling encounters and camp encounters into an index using the following formula:

Traveling encounters + (2 × Camp encounters) = Index of encounters

For example, using the grand means from tables 2.5.3 and 2.5.4, the calculation for the index of encounters would be:

10 + (2 × 2) = 10 + 4 = 14

This index weights camp encounters twice as heavily as traveling encounters because research has shown that seeing or hearing other campers is substantially more impactful on visitors’ experiences than encountering people on the trail. The measure value reported for this protocol option is the index value.

Protocol Option 2—Number of Traveling or Camp Encounters. This protocol option follows the same initial steps described above for the Index of Traveling and Camp Encounters protocol option using whichever encounter data are available for a wilderness. Once the grand mean of either traveling or camp encounters has been calculated, however, no further data processing is required. The measure value reported for this protocol option is either the grand mean of traveling encounters or the grand mean of camp encounters.

Protocol Option 3—Number of Visitors. If visitation data are used, sum the total number of people, groups, or vehicles across all trailheads or access points monitored for a wilderness. If traffic counters are used, the data may need to be corrected to account for entries and exits and ensure visitors are only counted once. This would be the case whenever vehicles must travel both in and out over the sensor. (If the site layout and counters are arranged so that each vehicle is only counted once, correction is not needed.) To correct the data, divide traffic counter totals by two. The measure value reported for this protocol option is the total number of people, groups, or vehicles. Table 2.5.5 shows variations of the measure value based on the data source.

Table 2.5.5—Values to report for various data sources used for indirect measures for the index of encounters

Protocol Option 4—Trend in Visitation. If professional judgment is used, consult with individuals with the best knowledge of on-the-ground conditions (e.g., lead wilderness rangers) to assign an applicable trend category from the following options:

• Decreasing visitation—visitation levels appear to be trending over time towards

fewer visitors.

• Stable visitation—visitation levels appear to be remaining about the same.
• Increasing visitation—visitation levels appear to be trending over time towards

more visitors.

For the measure baseline year, the stable visitation category should be selected. In subsequent monitoring cycles, trends in visitation should be assessed by comparing current perceptions of visitation levels with perceptions from the measure baseline year. Given the subjective nature of professional judgments, it is important to include additional documentation (e.g., a brief narrative) for each monitoring period that explains who assigned the trend category and the basis for their determination. The measure value reported for this protocol option is the selected trend category.

Step 4: Enter data in the WCMD. Enter the appropriate measure value for the selected protocol option in the WCMD. The measure value is either the index value, the grand mean of encounters, the number of visitors, or the trend category for visitation.

As described above, it would be ideal if complete encounter or visitation data were collected annually for this measure, although it is recognized that most units will be unable to do this. If a wilderness using protocol options 1, 2, or 3 (but not protocol option 4) does have complete data collection each year, however, the measure value is instead calculated as a 3-year rolling average. With annual (complete) data collection, local units must still enter the values described above in the WCMD, but the WCMD then automatically calculates 3-year rolling averages from those data.

Caveats and Cautions

Encounter and visitation monitoring protocols tend to change frequently. For example, local unit managers decide to monitor different areas, collect different data, or implement (or discontinue) self-registration systems. Because of such changes, units should not simply assume that differences over time reflect real change. Before drawing conclusions about meaningful change, verify that the data collected in different time periods are in fact comparable.

The suitability of the NVUM program (https://www.fs.fed.us/recreation/programs/ nvum/) to generate wilderness visitation data should be addressed. NVUM provides a measure of wilderness visits for each national forest, along with the 90-percent confidence interval. Because NVUM was designed to generate estimates for the NFS as a whole, some features of the methodology make it problematic to use for estimating use of a specific wilderness. Using NVUM as a proxy for the number of encounters in a wilderness is not recommended for the following reasons:

• All wildernesses in a single Forest Service unit are combined in a single

sampling stratum so only a few sites may represent data for any given wilderness. Professional judgment would have to be used to apportion visits across the different wildernesses.

• Sampling intensity is low, with as few as eight sample days for wilderness for

any given Forest Service unit.

• Confidence intervals for visitation tend to be wide.
• If a wilderness is shared across units, it is not possible to assemble data for an

individual wilderness.

The current NVUM report (USDA Forest Service 2013b) (http://www.fs.fed.us/ recreation/programs/nvum/2012%20National_Summary_Report_061413.pdf) states that data “currently cannot be used to identify trends or make assumptions about changing use patterns.” Changes have been made in the NVUM protocols concerning reclassification of wilderness sampling sites as high, medium, or low use. This means that data in some cases will not be comparable, or will produce questionable trends. For example, table 2.5.6 shows data for two rounds or cycles of data collection for the Deschutes, Mt. Hood, and Willamette National Forests in Oregon. The wide confidence intervals around the estimated number of visits (± 50 to 60%) make it extremely difficult to detect trends. Moreover, the data suggest that wilderness use in the Deschutes and Willamette National Forests decreased during a time in which the local population grew considerably and local permit data show increased use, calling into question the validity of the NVUM data.

Table 2.5.6—NVUM estimates of wilderness visits for three Region 6 National Forests (Deschutes, Mt. Hood, and Willamette) for years 2005–2009 and 2010–2014.

Despite these limitations, there may be a few situations when NVUM is appropriate for documenting visitation, such as if a local unit has only one wilderness or if a forest conducted additional data collection in conjunction with the standard NVUM surveying. If NVUM data are used the measure value is the total annual number of wilderness visits.

Data Adequacy

Data adequacy must be assessed for each wilderness individually based on the quality and quantity of local data. A general overview of data adequacy for various data sources is provided below as a starting point for local data adequacy assessments.

Data on the number of encounters collected in accordance with the national minimum protocol should be of good quality, but in most cases will only be available for selected monitoring zones, so data quantity will usually be partial. In some wildernesses, such as a small wilderness with only two or three primary use areas, data from the national minimum protocol will capture overall encounter conditions and can confidently be used for assessing trends. However, in large wildernesses with variable use across different locations, the data only reflect conditions within the areas monitored, which may or may not be representative of a wilderness as a whole. Even if not representative, trends in those selected areas could be very informative in terms of suggesting the need for more intensive monitoring. Thus, the overall data adequacy is medium.

Data on visitation collected by traffic or trail counters are generally of good data quality, and depending on coverage will range from insufficient to complete data quantity. Data are usually complete for each location because counters record continuously, but only a few locations may have counters installed. Overall data adequacy is therefore medium to high.

Data on visitation collected by trail registers or self-issue permits can have significant limitations. For example, compliance rates with self-issue permits tend to be low and variable (Cole and Hall 2008), and if observational data are not collected to calibrate the counts generated, accuracy may be low. Moreover, self-issue stations may run out of forms or pens, leading to gaps in data, particularly during high use times. However, mandatory registration systems can provide good coverage, and public contact reports or other observations can generate correction factors to adjust for non-compliance and improve confidence in data quality. Thus, data adequacy can range from medium to high.

The other widely available data source, NVUM, is not designed to monitor individual wildernesses separately, and therefore should be used cautiously, if at all. While consistent protocols and a trained workforce ensure moderate to good quality data, representation of individual wildernesses is poor, making data quantity insufficient unless additional sampling has been conducted. NVUM reports provide a 90-percent confidence interval for wilderness visits, which gives local units information about the precision of the estimates. Data accuracy is usually low to medium.

Professional judgment about trends in visitor use can be good in some cases, if it is based on multiple years of on-the-ground experience. However, professional judgment is not acceptable for estimating actual encounter rates or visitation levels.

Additionally, natural human tendencies to focus on anomalies may call into question the validity of professional judgment. Thus, data adequacy can range from low to high depending on the sources of data used.

Frequency

Every 5 years, data on encounters or visitation are compiled and the index of encounters, number of encounters, number of visitors, or trend category is then entered in the WCMD. Field data collection may span multiple years within the 5-year reporting interval. Although the minimum frequency for this measure is every 5 years, data compilation, analysis, and entry may occur more frequently if so desired for the Index of Traveling and Camp Encounters, Number of Traveling or Camp Encounters, or Number of Visitors protocol options.

Threshold for Change

The threshold for meaningful change differs depending on the protocol option used. If Protocol Option 1—Index of Traveling and Camp Encounters, Protocol Option 2—Number of Traveling or Camp Encounters, or Protocol Option 3— Number of Visitors are used, the threshold is a 10-percent change in the measure value or number of encounters or visitors. Once there are five measure values, the threshold for meaningful change will switch to regression analysis for these three protocol options. (If a wilderness has annual data collection for any of these protocol options, the threshold would be a 10-percent change in the 3-year rolling average or, once there are five measure values, switching to regression analysis of the rolling averages). If Protocol Option 4—Trend in Visitation is used, the threshold is any change in categories. A decrease in the encounter or visitation measure value beyond the threshold for meaningful change, or a change in categories towards decreasing visitation, results in an improving trend in the measure.

5.2.2 Measure: Index of Recreation Sites Within Primary Use Areas

This measure is an index that assesses the number of recreation sites and their condition, based on the national minimum protocol for recreation site monitoring. Local data are compiled and stored in local archives. Local staff calculate the measure value. Table 2.5.7 describes key features for this measure.

Table 2.5.7—Summary of measure type, protocol options, local tasks, national tasks, and frequency of data reporting for measure “Index of Recreation Sites within Primary Use Areas.”

Protocol

Step 1: Ensure users understand what types of recreation sites are counted under this measure and compile data. A recreation site is defined as a place where visible impacts to vegetation or soil are documented as a result of recreational use. For this measure, recreation sites may include both designated sites and user-created sites. Recreation sites are often campsites (both designated and user-created), but may also include viewpoints and day use areas. Locally-unique recreation sites, such as impacts at the base of climbing routes, may be included at the discretion of local units. If locally-defined recreation sites are included in this measure, the types of additional sites being monitored must be documented to ensure consistency from year to year. Recreation sites do not include travel routes, such as trails or portages, because those are captured under different measures: user-created trails are counted under the measure Miles of Unauthorized Trails (section 5.2.4 in part 2) and designated trails are counted under the measure Index of NFS Developed Trails (section 5.4.1 in part 2). Viewpoints along trails where vegetation is trampled may be considered recreation sites. Similarly, administrative facilities associated with recreation sites, such as toilets or fire grates, are not monitored under this measure because they are captured under the measure Number of Authorized Constructed Recreation Features (section 5.4.2 in part 2).

The recommended approach for collecting data for this measure is to follow the Forest Service national minimum protocol for recreation site monitoring. The national minimum protocol (available online at http://www.wilderness.net/toolboxes/ documents/recsitemonitor/National%20Minimum%20Recreation%20Site%20 Monitoring%20Protocol.pdf) was used in the 10-year Wilderness Stewardship Challenge, and it provides detailed information on sampling, collecting data, standardizing data, and reporting results for WSP. It describes how to search for and identify sites within primary use areas and provides instructions for assessing site condition by measuring impacts to groundcover, documenting damage to trees, and estimating the spatial extent of the disturbed area. These variables are then summed to generate a condition rating of 1 (least impacted) to 8 (most impacted) for each recreation site.

A locally defined protocol that provides data quality and quantity comparable to, or better than, the national minimum protocol may also be used to compile data for this measure if it too generates a condition rating for each recreation site. Locally defined condition rating values may extend beyond the 1–8 scale described in the national minimum protocol as long as higher condition ratings still correspond with greater site impacts. If a local protocol is used instead of the national minimum protocol, document the process for searching for and identifying sites, assessing site condition, and deriving a condition rating for each site.

Recreation site monitoring data may be collected over a span of multiple years within the 5-year reporting period for this measure. For example, recreation site data may be collected in different locations in different years, with a full cycle of monitoring (all identified monitoring areas) completed after 5 years. Regardless of whether the national minimum protocol or a local protocol is used, it is important to train field staff to properly measure site impacts and, ideally, to use the same staff over time to conduct the monitoring. Different observers may be more or less thorough in searching for recreation sites, and people can judge the same conditions in different ways. When this happens, it is possible that what appear to be changes from one monitoring cycle to another may simply be a reflection of different judgments made by different observers. To ensure data are compiled consistently over time, documentation for each wilderness should also include a map that clearly identifies the areas surveyed for recreation sites for each monitoring cycle.

Step 2: Calculate the index value and enter data in the WCMD. Once recreation site data have been collected, calculate the total sum of recreation site condition ratings to derive the measure value. There are two possible methods for calculating this value. The first method is to simply sum the condition ratings for all recreation sites in a wilderness. The second method is to use an index in which users multiply the numerical condition rating (1 to 8) by the number of sites with that rating, and then sum the results (the component scores) for all condition ratings. Table 2.5.8 provides an example of the second method. Once the total sum is calculated, enter the measure value in the WCMD. The measure value is the index value.

Table 2.5.8—An example of how to calculate the index of recreation sites for a wilderness.

Caveats and Cautions

If conducted by well-trained staff, recreation site monitoring should accurately document increases and decreases in the number of recreation sites. Detecting meaningful change in the condition of recreation sites is more difficult due to some inherent subjectivity and because heavily impacted sites can undergo deterioration that will not be captured during subsequent monitoring. For example, sites that were assigned the highest impact categories during the initial inventory may deteriorate further without showing an increase in the condition rating.

Data Adequacy

If the national minimum protocol is used to compile data for this measure, the overall data adequacy is medium. Data quantity for the total number of sites should be complete, as long as all likely locations are surveyed, and if all types of recreation sites are included (and not just campsites). Data quality is moderate due to subjectivity in identifying the edges of the disturbed area and in estimating the area of impact, as well as differences associated with observers using different approaches to search for sites and impacted trees. Data adequacy must be assessed for each wilderness individually based on the quality and quantity of local data.

If locally developed protocols are used, data quantity will likely range from partial to complete, and data quality will be moderate to good. The determination of data adequacy will have to be made at the local level, based on quality and quantity of data.

Frequency

Every 5 years, recreation sites are surveyed and assigned a condition rating. An index value is calculated for all sites, and that value is then entered in the WCMD. Field data collection may span multiple years within the 5-year reporting interval.

Threshold for Change

The threshold for meaningful change is a 5-percent change in the recreation site measure value. Once there are five measure values, the threshold for meaningful change will switch to regression analysis. A decrease in the measure value beyond the threshold for meaningful change results in an improving trend in this measure.

5.2.3 Measure: Acres of Wilderness Away From Access and Travel Routes and Developments Inside Wilderness

This measure assesses the total number of wilderness acres located more than ½ mile from access points, travel routes (e.g., authorized trails and roads, aircraft landing sites), and developments inside wilderness. Unless stated otherwise, the protocol steps are intended to be completed by the central data analyst. Data are compiled from the EDW, or other local or national data sources, and validated locally. The central data analyst calculates the measure value. Table 2.5.9 describes key features for this measure.

Table 2.5.9—Summary of measure type, protocol options, local tasks, national tasks, and frequency of data reporting for measure “Acres of Wilderness Away from Access and Travel Routes and Developments Inside Wilderness.”

Protocol

Step 1: Ensure users understand what types of routes and developments are counted under this measure and retrieve spatial data. Only those access and travel routes and developments inside wilderness for which there are existing spatial data are included in this measure. Locally unique or less common types of routes and developments that affect this indicator, such as travel routes on water, are not tracked under this measure due to the lack of nationally available data. Table 2.5.10 lists the types of routes and developments that are and are not included in this measure.

Table 2.5.10—Specific access points, travel routes, and developments used in this measure.

There is the possibility of confusion about whether to include travel routes and developments that are on the boundary of a wilderness (including cherry-stemmed roads) under this measure or under the related measure Acres of Wilderness Away from Adjacent Travel Routes and Developments Outside the Wilderness (section 5.3.1 in part 2). Travel routes and developments should only be included in one of the measures, not both. Features located on the boundary should only be included in the measure Acres of Wilderness Away from Adjacent Travel Routes and Developments Outside the Wilderness.

The spatial data used for this measure come from a variety of data sources. Contact a GIS specialist to assist with this measure, if necessary. Finding data may require searching forest Spatial Data Engine (SDE) GIS libraries, the EDW, NRM, or contacting the local unit. All local units maintain roads, motorized routes, and NFS trails data in a GIS, and some data are stored in NRM, but data are not necessarily linked together or validated. Some units have made their road and trail data available in the EDW and on websites like the Forest Service Interactive Travel Map. Spatial data on small-scale developments may be challenging to find; while some units maintain spatial data on developments in a GIS, others do not. FSTOPO feature classes (available from the EDW) may depict some developments inside wilderness as well. Data sources for this measure include:

• The EDW
• Forest GIS data in SDE data linked to NRM
• Other local GIS
• Forest Service Interactive Travel Map (https://apps.fs.usda.gov/TravelAccess/)
• Forest Service Interactive Visitor Map (https://www.fs.fed.us/ivm/)

A recommended starting point in the compilation of data for this measure is to retrieve the following FSTOPO feature classes and additional “RoadCore” transportation feature classes from the EDW.

FSTOPO feature classes:

• S_USA.FSTopo_Building_PT
• S_USA.FSTopo_Culture_LN
• S_USA.FSTopo_Culture_PT

• S_USA.FSTopo_Culture_PL • S_USA.FSTopo_RecFacility_PT • S_USA.FSTopo_BuiltupArea_PL • S_USA.FSTopo_LargeTank_PT • S_USA.FSTopo_Airfield_LN • S_USA.FSTopo_Airfield_PT • S_USA.FSTopo_Railroad_LN • S_USA.FSTopo_Transport_LN • S_USA.FSTopo_Transport_PT

Additional “RoadCore” transportation feature classes:

• S_USA.RoadCore_Existing • S_USA.RoadCore_FS

Note that some routes may be depicted in both FSTOPO’s S_USA.FSTopo_ Transport_LN feature class and one or both of the “RoadCore” transportation feature classes. Where there are multiple depictions of the same route, data from either of the “RoadCore” transportation feature classes are likely to be more accurate, and are therefore preferred over transportation data from FSTOPO.

Given questions about the completeness and accuracy of national spatial data, a map must be sent to the local unit for validation once all data have been located. Local wilderness specialists and other relevant local resource specialists must review the map for accuracy and completeness and identify any routes or developments that are missing or incorrect. (Corrections to these components in the corporate GIS will have to be made through appropriate channels.) The iterative process of evaluating and correcting the map of routes and developments inside wilderness is most critical for the measure baseline year.

Step 2: Perform the spatial analysis to calculate the acres of wilderness away from access and travel routes and developments inside wilderness. To complete the spatial analysis, first buffer all identified routes and developments inside wilderness by ½ mile on all sides. Subtract the buffered area from the wilderness polygon and then calculate the remaining area to determine the acres of wilderness away from internal routes and developments.

Step 3: Enter data in the WCMD. Enter the acres of wilderness away from access and travel routes and developments inside wilderness in the WCMD. The measure value is the number of acres.

Caveats and Cautions

One major limitation to this measure is that it is unlikely to change because trails, roads, and developments are rarely built or removed in wilderness (although conversion of a user-created trail to a NFS system trail would increase the total route mileage included in this measure). However, if initial spatial data have errors or omissions corrected later, the baseline measure can be updated (recalculated) prior to computing trends over time.

Data Adequacy

Wilderness boundary spatial data are complete and accurate. Currently, however, the quality and quantity of data in travel route layers varies. Centerline data for system trails should be complete and accurate by the end of 2017. Data on cartographic features are presumed to be complete and accurate (see www.fs.fed.us/database/ cff.htm). They are maintained at the Geospatial Technology and Application Center (GTAC) and are updated on a 7-year cycle. Overall, data adequacy is considered to be medium to high, because data quantity is likely to be partial to complete and data quality is likely to be moderate to good.

Frequency

Every 5 years, the acres of wilderness away from access and travel routes and developments inside wilderness are assessed, and the total acres are then entered in the WCMD.

Threshold for Change

The threshold for meaningful change is a 3-percent change in the acres of wilderness away from access and travel routes and developments inside wilderness. Once there are five measure values, the threshold for meaningful change will switch to regression analysis. An increase in the number of wilderness acres beyond the threshold for meaningful change results in an improving trend in this measure.

5.2.4 Measure: Miles of Unauthorized Trails

This measure assesses the number of linear miles of unauthorized (non-system) trails inside wilderness. Local data are compiled and are either stored in local archives or entered in NRM-Trails. Local staff or NRM-WCM calculate the measure value. Table 2.5.11 describes key features for this measure.

Table 2.5.11—Summary of measure type, protocol options, local tasks, national tasks, and frequency of data reporting for measure “Miles of Unauthorized Trails.”

Protocol

Step 1: Ensure users understand what types of trails are counted under this measure and compile data. For this measure, unauthorized trails include user-created trails as well as other unauthorized routes (e.g., decommissioned roads or trails) that are currently in use. It may also include climbing routes. If a wilderness collects data on unauthorized trails, it is strongly recommended that they select this measure as it is relatively more sensitive to change than the other two measures in this “required to select at least one” suite of measures. As the ability to monitor social trails improves (e.g., with new types of technology and imagery), local units will need to verify that apparent change over time reflects the creation of new trails, and not simply the level of effort applied to detect trails.

The recommended approach for collecting data for this measure is to follow the Forest Service national minimum protocol for monitoring user-created trails. The national minimum protocol, available online at http://www.wilderness.net/ toolboxes/documents/recsitemonitor/National%20Minimum%20Recreation%20 Site%20Monitoring%20Protocol.pdf, provides detailed information on sampling, collecting data, standardizing data, and reporting results for WSP. A locally defined protocol that provides data quality and quantity comparable to, or better than, the national minimum protocol may also be used to compile data for this measure. Use of professional judgment to identify the routes of known unauthorized trails is not recommended without validation of trail locations through objective data (e.g., field reconnaissance or imagery). If a local protocol is used instead of the national minimum protocol, document the process for searching for and identifying unauthorized trails.

For monitoring trends over time, it is important that the same areas are searched for trails each monitoring cycle—although it is not required that the entire wilderness be monitored. To ensure data are compiled consistently over time, documentation for each wilderness should include a map that clearly identifies the areas surveyed for unauthorized trails for each monitoring cycle. Data on unauthorized trails may be also collected over a span of multiple years within the 5-year reporting period for this measure. For example, unauthorized data may be collected in different locations in different years, with a full cycle of monitoring (all identified monitoring areas) completed after 5 years.

Step 2: Calculate the total miles and enter data in the WCMD. Once unauthorized trails data have been collected, calculate the total miles of trails to derive the measure value. While many units are likely to archive unauthorized trails data in local spreadsheets or geospatial databases, some may enter the data in NRM-Trails. If data are stored in NRM-Trails, the NRM-WCM application will calculate the measure value automatically. Local units must then validate the value generated by NRM-WCM and correct records in NRM-Trails as necessary. Enter the total miles in the WCMD. The measure value is the miles of unauthorized trails.

Caveats and Cautions

If local units choose to use data stored in NRM-Trails for this measure, it should not be assumed that the data currently recorded in NRM are accurate or complete. Records from NRM-Trails must be scrutinized carefully for both mileage errors and missing unauthorized trails. If data from NRM-Trails are insufficient, local units must either: (1) update and improve the data in NRM, (2) use other data sources to complete the measure protocol, or (3) choose not to use this measure. Note that unauthorized trail segments less than 0.5 miles are rounded down to 0 in NRM-WCM and are not included in the total mileage calculation.

Data Adequacy

Most units do not have data for unauthorized trails. Data quantity is insufficient to partial, and quality will vary from poor to good, depending on the level of effort made and the ability to locate unauthorized trails. Overall, data adequacy at this time is low. Data adequacy must be assessed for each wilderness individually based on the quality and quantity of local data.

Frequency

Every 5 years, unauthorized trails are assessed, and the total number of miles is then entered in the WCMD. Field data collection may span multiple years within the 5-year reporting interval.

Threshold for Change

The threshold for meaningful change is a 3-percent change in the miles of unauthorized trails. Once there are five measure values, the threshold for meaningful change will switch to regression analysis. A decrease in the miles of unauthorized trails beyond the threshold for meaningful change results in an improving trend in this measure.

== 5.3 Indicator: Remoteness from Sights and Sounds of Human Activity Outside the Wilderness ==

This indicator focuses on human activity occurring outside or on the boundary of a wilderness that is visible or audible from within wilderness. There is one required measure for this indicator.

5.3.1 Measure: Acres of Wilderness Away From Adjacent Travel Routes and Developments Outside the Wilderness

This measure assesses the total number of wilderness acres more than ½ mile from roads, structures, and other developments that are located outside a wilderness or on the boundary, including cherry-stemmed access road corridors and developed inholdings. Unless stated otherwise, the protocol steps are intended to be completed by the central data analyst. Data are compiled from the EDW, or other local or national data sources, and validated locally. The central data analyst calculates the measure value. Table 2.5.12 describes key features for this measure.

Table 2.5.12—Summary of measure type, protocol options, local tasks, national tasks, and frequency of data reporting for the measure “Acres of Wilderness Away from Adjacent Travel Routes and Developments Outside the Wilderness.”

Protocol

Step 1: Ensure users understand what types of routes and developments are counted under this measure and retrieve spatial data. Only those travel routes and developments outside wilderness for which there are existing spatial data are included in this measure. Locally unique or less common types of routes and developments that affect this indicator, such as travel routes on water, are not tracked under this measure due to the lack of nationally available data. Table 2.5.13 lists the travel routes and developments that are and are not included in this measure.

Table 2.5.13—Specific access points, travel routes, and developments used in this measure.

There is the possibility of confusion about whether to include travel routes and developments that are on the boundary of a wilderness (including cherry-stemmed roads) under this measure or under the related measure Acres of Wilderness Away From Adjacent Travel Routes and Developments Inside Wilderness (see section 5.2.3 in part 2). Travel routes and developments should only be included in one of the measures, not both. Features located on a wilderness boundary should be included in this measure. Likewise, travel routes and developments on inholdings should also be included in this measure because inholdings are, by definition, not part of a wilderness.

The spatial data used for this measure come from a variety of data sources. Contact a GIS specialist to assist with this measure, if necessary. Finding data may require searching forest SDE GIS libraries, the EDW, NRM, or contacting the local unit. All local units maintain roads, motorized routes, and NFS trails data in a GIS, and some data are stored in NRM, but data are not necessarily linked together or validated. Some units have made their road and trail data available in the EDW and on websites like the Forest Service Interactive Travel Map. FSTOPO feature classes (available from the EDW) depict both Forest Service and non-Forest Service developments and travel routes. Spatial data on small-scale developments, however, may be challenging to find; while some units maintain spatial data on local developments in a GIS, others do not. Data sources for this measure include:

• The EDW • Forest GIS data in SDE data linked to NRM • Other local GIS • Forest Service Interactive Travel Map (https://apps.fs.usda.gov/TravelAccess/) • Forest Service Interactive Visitor Map (https://www.fs.fed.us/ivm/)

A recommended starting point in the compilation of data for this measure is to retrieve the following FSTOPO feature classes and additional “RoadCore” transportation feature classes from the EDW:

FSTOPO feature classes:

• S_USA.FSTopo_Building_PT • S_USA.FSTopo_Culture_LN • S_USA.FSTopo_Culture_PT • S_USA.FSTopo_Culture_PL • S_USA.FSTopo_RecFacility_PT • S_USA.FSTopo_BuiltupArea_PL • S_USA.FSTopo_LargeTank_PT • S_USA.FSTopo_Airfield_LN • S_USA.FSTopo_Airfield_PT • S_USA.FSTopo_Railroad_LN • S_USA.FSTopo_Transport_LN • S_USA.FSTopo_Transport_PT

Additional “RoadCore” transportation feature classes:

• S_USA.RoadCore_Existing • S_USA.RoadCore_FS

Note that some routes may be depicted in both FSTOPO’s S_USA.FSTopo_ Transport_LN feature class and one or both of the “RoadCore” transportation feature classes. Where there are multiple depictions of the same route, data from either of the “RoadCore” transportation feature classes are likely to be more accurate, and are therefore preferred over transportation data from FSTOPO.

Given questions about the completeness and accuracy of national spatial data, a map must be sent to the local unit for validation once all data have been located. Local wilderness specialists and other relevant local units review the map for accuracy and completeness and identify any routes or developments that are missing or incorrect. (Corrections to these components in the corporate GIS will have to be made through appropriate channels.) The iterative process of evaluating and correcting the map of routes and developments outside wilderness is most critical for the measure baseline year.

Step 2: Perform the spatial analysis to calculate the acres of wilderness away from travel routes and developments outside the wilderness. To complete the spatial analysis, first buffer all identified routes and developments outside wilderness by ½ mile on all sides. Subtract the buffered area from the wilderness polygon and then calculate the remaining area to determine the acres of wilderness away from external routes and developments.

Step 3: Enter data in the WCMD. Enter the acres of wilderness away from travel routes and developments outside wilderness in the WCMD. The measure value is the number of acres.

Caveats and Cautions

This measure will not capture all important impacts on the visitor experience from sources outside wilderness, such as impacts from nearby urban areas or overflights. To some extent, such impacts could be captured locally through tailoring the national minimum protocol for solitude monitoring. If initial spatial data have errors or omissions corrected later, the baseline measure can be updated (recalculated) prior to computing trends over time.

Data Adequacy

Wilderness boundary spatial data are complete and accurate. Currently, however, the quality and quantity of data in travel route layers varies. NRM anticipates that the centerline data for system trails should be complete and accurate by 2017. Data on cartographic features are presumed to be complete and accurate (see www.fs.fed. us/database/cff.htm). These data are maintained at the Geographic Technology Applications Center and are updated on a 7-year cycle. Data on non-Forest Service roads, trails, and developments outside wilderness will vary in quantity and quality. Overall, data adequacy is considered to be medium to high, because data quantity is likely to be partial to complete, and data quality is likely to be moderate to good.

Frequency

Every 5 years, the acres of wilderness away from travel routes and developments outside wilderness are assessed, and the total acres are then entered in the WCMD.

Threshold for Change

The threshold for meaningful change is a 3-percent change in the acres of wilderness away from travel routes and developments outside wilderness. Once there are five measure values, the threshold for meaningful change will switch to regression analysis. An increase in the number of wilderness acres beyond the threshold for meaningful change results in an improving trend in this measure.

5.4 Indicator: Facilities That Decrease Self-Reliant Recreation

This indicator focuses on the presence of facilities in wilderness that decrease opportunities for self-reliant recreation. There are two measures for this indicator and units are required to select at least one.

5.4.1 Measure: Index of NFS Developed Trails

This measure is an index that assesses the miles of NFS trails and their trail classes. Local data are compiled and periodically entered in NRM-Trails. NRM-WCM calculates the measure value. Table 2.5.14 describes key features for this measure.

Table 2.5.14—Summary of measure type, protocol options, local tasks, national tasks, and frequency of data reporting for measure “Index of NFS Developed Trails.”

Protocol

Step 1: Retrieve NFS trail data from NRM. This measure uses data on both the miles and trail classes of NFS trails within wilderness to derive the measure value. Note that designated trail classes are used rather than actual trail conditions. Trail classes range from trail class 1 (minimally developed) to trail class 5 (fully developed) and describe the prescribed scale of development for a trail (i.e., its intended design and management standards).

This measure is designed to take advantage of currently collected and reported data on NFS trails. In NRM-WCM, retrieve existing data by running a report that displays all wilderness trails and trail classes. (Data for this report are pulled from existing records in NRM-Trails; only records where the “Jurisdiction” is “Forest Service,” the “Trail status” is “Existing,” and the “Trail system” is “NFST,” are retrieved.) The following attributes will be displayed for all wilderness trails:

• Trail class • Total miles (note that this refers to the total miles of trail inside wilderness)

Local wilderness staff must review the miles and trail classes of wilderness trails retrieved through NRM-WCM for accuracy and completeness. If discrepancies are found (e.g., if the trail condition on the ground does not match the assigned trail class), corrections to these attributes will have to be made through appropriate channels in NRM-Trails.

Step 2: Calculate the index value and enter data in the WCMD. The measure value is derived through an index combining the miles and trail classes for all wilderness trails. The NRM-WCM application will automatically calculate the index value for this measure. Local units must review and validate the value generated by NRM-WCM and correct records as necessary. Once validated, enter the index value in the WCMD. The method NRM-WCM uses to calculate these values is described below for reference. The measure value is the index value.

For each trail class, NRM-WCM multiplies the numerical trail class value (1 to 5) by the miles of wilderness trails in that class. NRM-WCM then sums all the component scores (the scores for all trail classes) to calculate the index value for a wilderness. Table 2.5.15 provides an example showing how to calculate the index value for this measure.

Table 2.5.15—An example of how to calculate the index of NFS trails for a wilderness.

Caveats and Cautions

Trail classes are established at the time of trail construction and may be updated infrequently. Conditions of many trails are likely to be more primitive than the official trail class because of declining maintenance. Hence, this is a conservative measure that is unlikely to show increases in opportunities for primitive recreation should they actually occur.

Note that if the total miles are less than 0.5 miles for a given trail class, NRM-WCM rounds the value down to 0 and it is not included in the final index value calculation.

Data Adequacy

Information about trail classes are considered relatively good in NRM-Trails because of the agency’s focus on travel management as well as the need for interagency common standards. Data are also fairly complete, making data adequacy high. Data adequacy must be assessed for each wilderness individually based on well the national data reflect local conditions.

Frequency

Every 5 years, NFS trails are assessed and the index value is calculated. The index value is then entered in the WCMD.

Threshold for Change

The threshold for meaningful change is a 3-percent change in the measure value for NFS trails. Once there are five measure values, the threshold for meaningful change will switch to regression analysis. A decrease in the measure value beyond the threshold for meaningful change results in an improving trend in this measure.

5.4.2 Measure: Number of Authorized Constructed Recreation Features

This measure assesses the total number of authorized constructed recreation features. Local data are compiled and are either stored in local archives or entered in NRMWilderness. Local staff or NRM-WCM calculate the measure value. Table 2.5.16 describes key features for this measure.

Table 2.5.16—Summary of measure type, protocol options, local tasks, national tasks, and frequency of data reporting for measure “Number of Authorized Constructed Recreation Features.”

Protocol

Step 1: Ensure users understand what types of recreation features are counted under this measure and compile data. This measure counts authorized constructed recreation features located within wilderness, such as bridges, toilets, fire grates, and bear boxes. General guidelines for what features to include and exclude from this measure are described below.

• This measure records authorized features (i.e., installed and maintained by the Forest Service, or historical structures used by visitors). It may also include user-created structures (e.g., tent pads or outfitter camp structures) that managers maintain or permit to exist, but it does not include unauthorized user-created features that are routinely removed when found. • To avoid double counting, non-recreational developments are not counted under this measure because they are monitored for the measure Index of Authorized Non-Recreational Physical Development under the Undeveloped Quality (see section 4.2.1 in part 2). • System trails are not included in this measure because they are monitored under the measure Index of NFS Developed Trails (see section 5.4.1 in part 2). • Campsites (including designated campsites) that have natural rock fire pits or user-flattened tent pads are captured under the measure Index of Recreation Sites Within Primary Use Areas (section 5.2.2 in part 2), and not this measure; however, recreation features associated with designated campsites (e.g., toilets, fire grates) are counted here. • Several types of trail-related features (e.g., trail turnpikes, trail signs, or blazes) are not included because they may have minimal impact on the sense of primitive recreation (relative to major facilities) or because local units are unlikely to maintain accurate counts of those features. Likewise, climbing anchors (e.g., bolts) are not included because it is presumed difficult to obtain accurate counts.

Existing data on recreation features are generally archived locally in spreadsheets or geospatial databases. Some local units, however, may enter and store these data in NRM-Wilderness. The recommended approach for this measure is to use data on recreation features collected as part of the Forest Service national minimum protocol for recreation site monitoring (available online at http://www.wilderness.net/ toolboxes/documents/recsitemonitor/National%20Minimum%20Recreation%20 Site%20Monitoring%20Protocol.pdf). Provide counts of each of the following types of authorized constructed recreation features:

• Toilets and toilet buildings • Forest Service-constructed tent pads or tent platforms (fabricated with wood, cement, or other material and designed to be permanent installations) • Picnic tables • Benches • Bear poles or other food storage structures • Permanent fire rings, grills, fireplaces, or wood stoves • Shelters and cabins • Developed recreational water sources (if not counted under the Undeveloped Quality) • Corrals or hitchrails for recreational stock holding • Large bridges (bridges with railings or decking) • Airstrips

Step 2: Count the number of features and enter data in the WCMD. Each feature included in this measure is weighted equally, and all recreation features at a site are counted separately. For example, a toilet and a fire ring at one site are counted as two features. Likewise, a bear box attached to a shelter would count as two features. Sum the total number of recreation features to derive the measure value. Alternatively, if data are stored in NRM-Wilderness, the NRM-WCM application will calculate the total number of recreation features automatically. Local units must then validate the value generated by NRM-WCM and correct records in NRM-Wilderness as necessary. Enter the measure value in the WCMD. The measure value is the total number of recreation features.

Caveats and Cautions

If local units choose to use data stored in NRM-Wilderness for this measure, it should not be assumed that the data currently recorded in NRM are accurate or complete. Records from NRM-Wilderness must be scrutinized carefully for missing recreation features. If data from NRM-Wilderness are insufficient, local units must either: (1) update and improve the data in NRM, (2) use other data sources to complete the measure protocol, or (3) choose not to use this measure.

Data Adequacy

Units should be able to accurately report these features with minimal effort and without the need for new field data collection. Therefore, it is assumed that data quality will be good, data quantity is complete, and overall data adequacy is high. Data adequacy must be assessed for each wilderness individually based on the quality and quantity of local data.

Frequency

Every 5 years, changes to the number of authorized constructed recreation features are assessed, and the total number of features is then entered in the WCMD.

Threshold for Change

The threshold for meaningful change is any change in the total number of authorized constructed recreation features. A decrease in the number of features beyond the threshold for meaningful change results in an improving trend in this measure.

5.5 Indicator: Management Restrictions on Visitor Behavior

This indicator focuses on management restrictions that degrade opportunities for unconfined recreation. There is one required measure for this indicator.

5.5.1 Measure: Index of Visitor Management Restrictions

This measure is an index that assesses the relative degree of imposition or inconvenience of certain visitor management restrictions as well as the geographic extent of those restrictions. Local data are compiled and entered in NRM-Wilderness and NRM-WCM annually. NRM-WCM calculates the measure value. Table 2.5.17 describes key features for this measure.

Table 2.5.17—Summary of measure type, protocol options, local tasks, national tasks, and frequency of data reporting for measure “Index of Visitor Management Restrictions.”

Protocol

Step 1: Ensure users understand what types of visitor management restrictions are counted under this measure and retrieve data from NRM. Management restrictions are put in place through the implementation of wilderness regulations authorized by regional or forest special orders. Restrictions may be national, regional, or local in scope, and may apply to the entire wilderness or just certain areas within a wilderness. This measure monitors the following 11 categories of regulations deemed most likely to affect the perception of unconfined recreation:

1. Area closure 2. Campfire restrictions 3. Camping restrictions 4. Dogs and domesticated animals 5. Fees 6. Group size limits 7. Human waste 8. Length of stay 9. Permits 10. Stock use 11. Swimming/bathing

Although these categories are not exhaustive, they represent a selected group of more common types of visitor management restrictions (forest or regional regulations) and should reliably track changes in the measure. Other types of Forest Service regulations are not tracked for this measure because they either do not present significant confinement of the visitor (e.g., anti-littering regulations) or they are uncommon. In addition, regulations or restrictions imposed by other agencies (e.g., state park fees) as well as common practices (e.g., Leave No Trace guidelines) are not monitored under this measure. Seasonal restrictions are only included in this measure for restrictions that occur at the same time each year.

The data on visitor management restrictions that are used for this measure are already reported through NRM-Wilderness by local units during annual upward reporting. Run a report in NRM-WCM to display relevant data for this measure. (Data for this report are pulled from existing records entered in the Wilderness Regulations module in NRM-Wilderness.)

NRM-WCM automatically assigns an impact rating of 0 to 3 for each regulation category based on the relative restrictiveness of a wilderness’s regulations entered in NRM-Wilderness. A higher impact rating indicates a greater degree of restriction on visitor behavior, with the highest rating of 3 reserved for regulations that cause substantial imposition on visitors. For example, mandatory use-limiting permits (an impact rating of 3) require advance planning and may require visitors to change their planned trip dates or make a special trip to a permitting office. Similarly, requiring visitors to pack out their human waste (an impact rating of 3) likewise necessitates advance planning as well as considerable inconvenience during the trip. General guidelines for impact ratings are described in table 2.5.18, while table 2.5.19 shows the specific impact rating scales used by NRM-WCM for each category of regulation. If a wilderness has more than one type of regulation within a given category, NRMWCM will use the most restrictive regulation in place to assign the impact rating. For example, if there are mandatory use-limited permits required in summer (an impact rating of 3) but mandatory non-use-limiting permits required in winter (an impact rating of 2), NRM-WCM will assign an impact rating of 3 for the permits regulation category.

Table 2.5.18—Guidelines for assigning impact ratings to regulations.

Table 2.5.19—A list of categories, impact ratings, and types of restrictions for computing the visitor restriction index.

Table 2.5.19—A list of categories, impact ratings, and types of restrictions for computing the visitor restriction index.

Local units must validate the impact ratings displayed in NRM-WCM and, if necessary, correct records in NRM-Wilderness. It may be necessary to check records in NRM-Wilderness directly to ensure that all visitor management restrictions have been entered and that NRM-WCM has retrieved the most restrictive regulation (with the highest impact rating) for each category.

For each regulation category, local units must also enter the geographic weight— that is, whether the restriction applies to a subarea of a wilderness or to the entire wilderness. This is a new attribute that must be entered in NRM-WCM and cannot be entered in NRM-Wilderness. If local units set the geographic extent as the entire wilderness, NRM-WCM will automatically assign a weight of 2 to that regulation category; if local units set the geographic extent as only part of the wilderness, NRM-WCM will assign a weight of 1. If there is more than one type of restriction within a given regulation category, use the restriction with the highest impact rating to determine the geographic weight. For example, if there is a wilderness-wide requirement to use weed-free feed for stock (an impact rating of 2, geographic weight of 2), but a specific riparian area is also closed to all stock use (an impact rating of 3, geographic weight of 1), NRM-WCM will use the riparian area closure restriction to assign the higher impact rating for the stock use regulation category, and local units should assign a corresponding geographic weight of 1 (part of the wilderness) for that restriction.

Each regulation category is then assigned a weight for geographic extent based on whether restrictions apply to a subarea of a wilderness (a weight of 1) or to the entire wilderness (a weight of 2). NRM-WCM automatically determines the appropriate weight for a restriction by using the new geographic extent attribute local units entered in step 1. If there is more than one type of regulation within a given category, NRM-WCM will use the geographic extent for the restriction with the highest impact rating. For example, if there is a wilderness-wide requirement to use weed-free feed for stock (an impact rating of 2, geographic extent weight of 2), but a specific riparian area is also closed to all stock use (an impact rating of 3, geographic extent weight of 1), NRM-WCM will use the area closure restriction, with the higher impact rating, to assign a geographic extent weight of 1 for the stock use regulation category.

Step 2: Calculate the index value. The index used for this measure combines impact ratings and geographic weights for each of the 11 regulation categories. The NRM-WCM application will automatically calculate the index value for this measure. Local units must review and validate the value generated by NRM-WCM and correct records as necessary. The method NRM-WCM uses to calculate these values is described below for reference.

Once an impact rating and a geographic weight are assigned for each regulation category, NRM-WCM calculates the visitor management restrictions index in two basic steps. First, a component score is generated for each regulation category by multiplying the impact rating by its geographic weight. Second, the component scores for all categories are summed to produce the final index value. Table 2.5.20 provides an example showing how NRM-WCM calculates the index value for this measure.

Table 2.5.20—An example of how to calculate the visitor management restrictions index value. A dash (-) in the column means that geographic weight is not applicable because there is no restriction for the regulation category (impact rating = 0). If there is no restriction, there can be no geographic extent and no geographic extent weight.

Step 3: Enter data in the WCMD. Local units must validate the visitor management restrictions index value generated by NRM-WCM and correct records in NRM-WCM or NRM-Wilderness as necessary. Once validated, enter the index value in the WCMD. The measure value is the index value.

Caveats and Cautions

Regulations entered in NRM-Wilderness must be accurate to apply the proper geographic weight and provide a component score. Missing regulations in NRMWilderness or the use of an inaccurate regulation type could provide an incorrect component score.

Data Adequacy

Data are of reasonably good quality and data quantity is complete. Efforts have been made recently to ensure that regulations are correctly reported through NRM because the website www.wilderness.net publishes these data. Therefore, data adequacy is high. Data adequacy must be assessed for each wilderness individually based on the quality and quantity of local data.

Frequency

Every 5 years, data on visitor restrictions are retrieved and the index value is calculated. The index value is then entered in the WCMD.

Threshold for Change

The threshold for meaningful change is any change in the measure value. A decrease in the measure value beyond the threshold for meaningful change results in an improving trend in this measure.