Recreational System Optimization to Reduce Conflict on Public … · 2016-11-10 · Recreational...
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Recreational System Optimization to Reduce Conflicton Public Lands
Fraser Shilling • Jennifer Boggs • Sarah Reed
Received: 30 August 2011 / Accepted: 18 June 2012 / Published online: 8 July 2012
� Springer Science+Business Media, LLC 2012
Abstract In response to federal administrative rule, the
Tahoe National Forest (TNF), California, USA engaged in
trail-route prioritization for motorized recreation (e.g., off-
highway-vehicles) and other recreation types. The priori-
tization was intended to identify routes that were suitable
and ill-suited for maintenance in a transportation system. A
recreational user survey was conducted online (n = 813)
for user preferences for trail system characteristics, recre-
ational use patterns, and demographics. Motorized trail
users and non-motorized users displayed very clear and
contrasting preferences for the same system. As has been
found by previous investigators, non-motorized users
expressed antagonism to motorized use on the same rec-
reational travel system, whereas motorized users either
supported multiple-use routes or dismissed non-motorized
recreationists’ concerns. To help the TNF plan for reduced
conflict, a geographic information system (GIS) based
modeling approach was used to identify recreational
opportunities and potential environmental impacts of all
travel routes. This GIS-based approach was based on an
expert-derived rule set. The rules addressed particular
environmental and recreation concerns in the TNF. Route
segments were identified that could be incorporated into
minimal-impact networks to support various types of
recreation. The combination of potential impacts and user-
benefits supported an optimization approach for an
appropriate recreational travel network to minimize envi-
ronmental impacts and user-conflicts in a multi-purpose
system.
Keywords Off-highway vehicles � Recreation �Multiple-use � Optimization modeling � Conflict �Public lands
The [National Forest Management Act] NFMA
requires the provision of a broad spectrum of forest
and rangeland-related outdoor recreation opportuni-
ties that respond to current and anticipated user
demands. Specifically for ‘‘off-road vehicle’’ use, the
NFMA requires that these opportunities be planned
and implemented to protect land and other resources,
promote public safety, and minimize conflicts with
other uses of the National Forest System lands.
(Tahoe National Forest 2008)
Introduction
Motorized recreation on public lands has been steadily
increasing over the past 40 years and is a major use of most
public lands in the western U.S. Between 1993 and 2003, the
number of all-terrain vehicles and off-highway motorcycles
in use in the US almost tripled, from 2.9 million to 8 million
(Cordell and others 2005). Although potential impacts of
motorized recreation have been recognized in public policy
(E.O. 11644 1972; Carter 1977) and certain specific impacts
F. Shilling (&)
Departmenrt of Evironmental Science and Policy, University
of California, One Shields Avenue, Davis, CA 95616, USA
e-mail: [email protected]
J. Boggs
The Wilderness Society, Center for Landscape Analysis,
San Francisco, CA, USA
S. Reed
Human Dimensions of Natural Resources, Colorado State
University, Fort Collins, CO, USA
123
Environmental Management (2012) 50:381–395
DOI 10.1007/s00267-012-9906-6
have been well-studied (Adams and others 1982; Bolling and
Walker 2000; Havlick 2002; Iverson and others 1981; Prose
and others 1987), understanding of the cumulative and sys-
tematic impacts of motorized recreation is limited (reviewed
in: Ouren and others 2007). In addition, there are few
examples of the use of environmental impacts analysis in
planning and management of motorized recreation.
Recreational trails on public lands in the U.S. are man-
aged under the multiple-use paradigm (Multiple-Use Sus-
tained Yield Act) and the National Forest Management Act
(NFMA; 16 U.S.C. §§ 528–31, 1600–14). These Acts
require that all land uses, even competing ones, be accom-
modated on National Forests, while at the same time
maintaining the overall integrity of forest ecosystems and
associated human benefits. When applied to recreation, the
presumption for multiple-use management is often that
motorized and non-motorized users can be accommodated
on the same trail system on a given Forest. However, con-
flicts among users are possible, especially when many users
are restricted to a limited trail system. Recreational groups
may experience ‘‘asymmetric conflict’’, where one party
(i.e., non-motorized recreationists) receives greater impacts
and is more distressed by sharing trail systems than another
(i.e., motorized recreation; Adams and McCool 2009;
Knopp and Tyger 1973; Vaske and others 2007). These
conflicts include direct disturbance of non-motorized
recreationists by motorized vehicle users, disturbance of
wildlife by motorized recreation which reduces wildlife
viewing opportunities, the perception among motorized
recreationists that others want to limit their access to trails,
and the opinion of many non-motorized recreationists that
motorized vehicles should be banned from public lands that
they use. Conflict may also occur among motorized recre-
ation groups (Albritton and Stein 2011). Conflicts like these
are common under the multiple-use paradigm, leading to
legal action to restrict activities (e.g., Colorado Off-High-
way Vehicle Coalition vs. United States Forest Service and
others 2004) and ‘‘gridlock’’ among competing interests
(Cawley and others 1997). These conflicts can be situated
within a theoretical structure of recreational conflict, where
various individual attributes, values, and activity modes
combined with physical spaces that increase the likelihood
of inter-group interaction can result in varying potentials for
inter-individual and inter-group conflict (Jacob and Schre-
yer 1980). Overall conflict may be a result of interpersonal
conflict, or of social values conflict (Vaske and others 2007).
In addition to conflict, trail-space limitations can lead to
crowding and reduced recreational goal achievement both
within and among recreational group types. There have been
attempts to bring computational modeling to bear to aid in
crowding reduction (e.g., Lawson and others 2006), but so
far no spatial modeling approach has been broadly adopted
by public lands managers for recreational trail planning.
In the late 1970’s, the USFS developed a system for land
managers, in part to balance sometimes competing recrea-
tional needs on limited public lands called the Recreational
Opportunity Spectrum (ROS, Clark and Stankey 1979). The
ROS defines recreational experience as being a combination
of the recreational activity and the setting. It further
decomposes the recreational experience into six activities,
with associated land classes: primitive; semi-primitive, non-
motorized; semi-primitive, motorized; roaded, natural;
rural; and urban (More and others 2003). Central to the
implementation of the ROS are two principles (1) its use of
the human experience of recreation and (2) impacts from
recreation on people and environment in rational and spa-
tially-explicit planning of activities, sometimes in restricted
locations and extents (Clark and Stankey 1979; More and
others 2003). The importance of the ROS to the USFS is
emphasized by the fact that its use is required for the
development and operation of trails (section 2353.14; For-
est Service Manual 2008), though historically, understand-
ing and acceptance of the ROS by field staff determines its
actual application (Stankey and others 1986). It is not clear
whether or not this situation has improved. In the current
project, the Tahoe National Forest used the language of the
ROS during planning of the optimization model, and we
applied ROS principles to frame our analyses of recreational
experiences and impacts to cover the spectrum of activities
in a spatially-explicit system.
Environmental effects of motorized and non-motorized
trail use are varied and include impacts to wildlife, plant
growth and succession, rates of erosion, weed invasion, and
archaeological sites (Adams and others 1982; Arp and
Simmons 2012; Brattstrom and Bondello 1983; Davidson
and Fox 1974; Iverson and others 1981; Ouren and others
2007; Wilshire 1983; Yarmoloy and others 1988). Motor-
ized vehicles include four-wheel drive automobiles (4WD),
all-terrain vehicles (ATVs or ‘‘quads’’), and motorcycles
(hereafter collectively called ‘‘off-highway vehicles’’,
OHV). These vehicles are rarely muffled and generally have
knobby tires. They produce more sound than street vehicles
and are thus thought to be a source of disturbance to wildlife
in forests and grasslands (Barton and Holmes 2007; Ouren
and others 2007). The combination of knobby tires and trail
position on steep slopes and near streams can result in
impacts to hydrologic connections to waterways, excess
compaction (Adams and others 1982), geomorphic impacts
to channels and wetlands (Arp and Simmons 2012), and
erosion (Iverson and others 1981). There are a variety of
other impacts that OHVs cause, including increased weed
invasion (Benninger-Traux and others 1992), degraded
habitat (Havlick 2002), and declines in the abundance
and survival of rodents, reptiles and birds (Brooks 1999;
Luckenbach and Bury 1983). Furthermore, OHVs allow
more visitors to travel further into the interior of public
382 Environmental Management (2012) 50:381–395
123
lands, thereby expanding the spatial extent of recreation
impacts. Non-motorized recreation also causes direct
impacts to trails and surrounding areas. For example, pro-
tected areas open to biking, hiking, and horseback riding
have fewer native carnivore species than areas closed to any
recreation (Reed and Merenlender 2008; Reed and Meren-
lender 2011). Behavioral responses (i.e., disturbance) by
wildlife to hikers and bikers can occur up to 400 m from
trails and is highly likely within 100 m of trails (Taylor and
Knight 2003). In addition, most recreation groups tend to
think that other groups are responsible for these kinds of
disturbance rather than their own group (Taylor and Knight
2003).
These environmental effects and others have led to
increased attention to and regulation of motorized recrea-
tion vehicle use on public lands, culminating in the federal
Travel Management Rule (TMR) of 2005 (36 CFR 212.55).
Prior to 2005, in most U.S. National Forests, off-trail or
‘‘cross-country’’ travel was permitted anywhere in a forest
that did not explicitly prohibit the use of motor vehicles.
The TMR requires USFS land managers to engage in a
planning process to designate an official motorized recre-
ation system in every National Forest, locating routes
suitable for motorized recreation so as to minimize envi-
ronmental impacts and conflicts among recreational users.
As pointed out in Vaske and others (2007), recreational
geographers and others have been studying conflict among
recreation group types for over 40 years, on trail systems
that have multiple uses. Recent advances in conflict
reduction have been made using GIS tools combined with
surveying of motorized recreationists in order to identify
geographic zones of conflict between groups that experi-
ence interference of their enjoyment by other motorized
groups (Albritton and Stein 2011). There have also been
suggestions that collaborative planning among stakeholders
could be used to find optimal solutions for recreational
system management (Asah and others 2012). This
approach is based on the premise that it is both necessary to
include all competing interests in policy implementation
(e.g., the TMR) and public lands management and suffi-
cient to include these interests if the goals are to reduce
conflict and improve system management. Asah and others
(2012) demonstrated that it is possible to find conceptual
agreement among competing interests within a structured
study, suggesting that conflict reduction can occur with
sufficient investment in process and careful implementa-
tion. However, when dealing with recreation across all
public lands units from a policy and analytical perspective,
it is worth considering spatial modeling of exclusive trail
systems on public lands as a strategy for conflict resolution,
during mandated route assessment and planning under the
TMR. The TMR planning process would also benefit from
evaluating and minimizing potential damage caused by
OHVs to natural systems.
The purpose of the present study was to provide a case
study for recreational system planning on public lands
combining: (1) spatial analysis of potential damage to
specific environmental values with (2) spatially optimizing
a trail system to provide reduced-conflict recreational
opportunities for both non-motorized and motorized users,
using the Tahoe National Forest (TNF), California, as a
model system. Our modeling approach was based on a
comprehensive trail-user survey, TNF staff’s collective
expertise about locations and types of recreational uses and
associated effects, and published studies of recreation
impacts on the environment. The trail-user survey provided
useful information about recreational groups’ opinions
about both the recreation system and other recreational
users, and it revealed important conflicts between motor-
ized and non-motorized recreationists. Finally, we present
an optimized system of trails designed to meet the recre-
ational needs of motorized users, while limiting both
environmental impacts and conflict with non-motorized
users. This method is a model for implementing the TMR
in a way that designates routes to minimize environmental
impact and reduce conflict among recreation types.
Methods
Study Area
The Tahoe National Forest stretches from the foothills of the
western slope of the Sierra Nevada (California, USA) to the
high desert ecosystem of the eastern slope of the range. Land
cover is primarily mixed hardwood conifer, closed-cone
conifer, alpine, and barren. Hundreds of native vertebrates
have habitat in the Forest, including many species with legal
protection. The Forest includes 522,359 Ha of land and
8,233 km of roads, of which 333,954 Ha of land and
4,249 km are public lands and roads and the remainder pri-
vate in-holdings and roads (Fig. 1). It also contains 1,223 km
of authorized and 2,253 km of unauthorized motorized rec-
reation trails. Recreational users often make use of both
unpaved roads and trails within an excursion, and hereafter
we refer to trails and roads used for recreation as ‘‘routes.’’
There are approximately 1.6 million person-visits to the
Forest each year for recreation, 35% of which are for skiing
and 8% for snowmobile riding (USDA Forest Service 2006).
Survey of Recreational Users
An online survey was used to query trail users in the TNF
about their route system preferences, experiences, and
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123
feedback about overall recreational route management.
They were asked which of 6 main types of activities they
engaged in: Four-wheel drive passenger vehicle (henceforth
‘‘4WD’’), four-wheel motorcycle (henceforth ‘‘quad’’), two-
wheel motorcycle (henceforth ‘‘motorcycle’’), bicycling
(primarily mountain biking), hiking, and horseback riding.
The questionnaire addressed the following concepts: where,
how often, and what type of recreation was preferred; what
physical route and environmental properties were preferred;
how they would rank their experience and what could be
done to improve their experience; and their age, gender, and
zip code. An example of a key question for developing the
‘‘trail benefits’’ analysis in GIS was: ‘‘When occupied with
your favorite recreation on the Tahoe National Forest, rank
from 1 to 4 (1 = highest) which of the following qualities of
the trail system you think are the most important?’’, which
was followed by a list of 9 factors. TNF hosted the survey for
30 days (April, 2006) using an online service and advertised
its availability to recreational users via contact lists of
people interested in Forest management, recreational inter-
est and environmental groups, and others. Because there was
no attempt to develop a random survey design and control
responses to the survey, the results should be viewed as an
opportunistic sampling of opinions about the recreation
system within recreational-user groups. The primary appli-
cation of the survey results in this study was in developing
the ‘‘route benefits’’ component of the GIS-based route
optimization model (Fig. 2b).
Environmental Impacts Knowledge Base
A knowledge base is a representation of our knowledge
about how a system works, or the interaction among ideas
that together compose a larger idea or goal. The software
Netweaver (http://rules-of-thumb.com) was used here to
generate a hierarchical knowledge base based on the con-
cept ‘‘route segments sustainably meet recreational goals
while minimizing environmental impact’’, which was
developed by the TNF-Inter Disciplinary Team (IDT,
Fig. 2) and was similar to that used by the TNF for roads
analysis (Girvetz and Shilling 2003). Netweaver is an
object- and network-based modeling system, which uses
fuzzy logic to evaluate evidence for propositions repre-
sented in its network structure. The goal statement was di-
saggregated in the knowledge base into two main concepts
– potential environmental impact and potential benefits to
recreation (Fig. 2). Each of these concepts was in turn
broken down into sub-concepts until each could be linked
to spatial data. The ‘‘environmental impacts’’ concept
(Fig. 2a) was populated with sub-concepts from the scien-
tific literature on recreational impacts. The ‘‘route benefits’’
concept (Fig. 2b) was populated with sub-concepts drawn
from the results of the trail-user survey. The knowledge
base was used to combine spatial data corresponding to
specific environmental features and potential impacts and to
balance potential environmental impacts with recreational
planning objectives.
Fig. 1 Study area map. The
Tahoe National Forest,
including highways, roads, and
trails. Inset: The position of the
Tahoe National Forest in
California
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123
Fig. 2 a Knowledge base of contributions of various environmental
conditions to the concept ‘‘environmental impact’’. Rectanglesindicate concepts, circles indicate Boolean logic operators, and
rounded rectangles indicate sources of environmental data. b Knowl-
edge base of contributions of various trail conditions to the concept
‘‘trail benefits’’
Environmental Management (2012) 50:381–395 385
123
Spatial Data and Data Processing
Spatial data representing natural and infrastructural fea-
tures were obtained from TNF and the California Depart-
ment of Forestry and Fire Protection-Forest Resource
Assessment Program (FRAP). The data types are indicated
in the knowledge base (Fig. 2). A transportation database
developed by TNF GIS staff in 2006 included the locations
of all authorized and unauthorized roads and trails
(1:24,000; hereafter, routes), descriptions of route status
(open or closed), and route width. Unauthorized routes are
also called ‘‘user-created’’ routes and are features created
by unknown users of the TNF without authorization from
the US Forest Service. TNF staff provided zone and route-
specific recreational-use information from Ranger District
recreation managers. This information was collected using
a standardized questionnaire and set of maps. Managers
were asked to indicate areas and routes that had low,
medium, or high use for each of the following types of
recreation: 4WD, quad, motorcycle, bicycle, hiking, and
horseback. Their feedback was included as route-specific
attribute information in the routes database.
Four main types of geo-processing were conducted to mea-
sure environmental conditions associated with route segments:
Distance to Feature
Many of the rules developed by the TNF staff related to
distance from routes to valued cultural and environmental
features. Valued features included heritage sites (archaeo-
logical, historical, cultural), streams and riparian areas;
wetlands; bald eagle, goshawk, and California Spotted Owl
nests and activity centers; old-forest areas; Lahontan cut-
throat trout streams; roadless areas; and deer wintering and
fawning areas. Raster datasets (10 m cell size) of Euclidean
distance were calculated from each type of feature.
Landscape Attribute
Certain of the rules developed by the TNF staff related
directly to a landscape attribute (e.g., slope, or land-slide).
Digital maps composed of polygons representing different
attributes of the landscape were converted to grid maps
using ArcGIS 9.1. The attributes converted to grid maps
were weed occurrences, route density, patch density, rare
plant occurrences, adjacent vegetation, route slope posi-
tion, precipitation, and slides and mass-wasting.
Route Segmentation
The original routes database contained line segments ranging
from*0.1 m to more than 50 km in length. Because this range
was too large to effectively attribute environmental conditions
to individual segments, all route segments were divided into
smaller segments with a maximum length of 300 m.
Data Attribution
The average value of each distance or landscape attribute
grid was attributed to each route segment. The resulting
routes database included a field for each potential envi-
ronmental impact and other concern and this was used as
the basis for the Ecosystem Management Decision-Support
(EMDS) model.
Spatially-Explicit Goal Modeling
We combined geographic data using the software program
EMDS (Reynolds and others 1996; Reynolds 1999a, b;
http://www.institute.redlands.edu/emds/) to evaluate the
contribution of individual route segments to recreational
and environmental goals. The routes database containing
fields for each environmental and cultural resource concern
was used as the base data for the knowledge base. Each
data link in the knowledge base was associated with a
corresponding field in the route map attribute table. EMDS
helps resource managers make informed decisions about
landscape processes and land management (Girvetz and
Shilling 2003; Reynolds and others 2000; Shilling and
Girvetz 2007). The system is based on principles of fuzzy-
set membership, meaning that it can account for interme-
diate values relating to assertions about states and pro-
cesses in nature, thus better reflecting how natural systems
work.
EMDS interprets and synthesizes ecological attributes,
condition, risk, etc., from geographic maps using a logic
model that translates observed data into continuous mea-
sures of strength of evidence (hereafter, just evidence).
EMDS 3.1 links the GIS program ArcGIS8.3 (ESRI) with
the logic-modeling program Netweaver (Saunders and
others 1990). EMDS provides Netweaver with the neces-
sary GIS base data for combining together, based upon
user-defined logical rules to determine evidence for prop-
ositions, also called a ‘‘truth value’’ (Reynolds and others
1996; Reynolds 1999a, b). Propositions are statements to
be tested by topics in the network structure (that is, a topic
is a network object responsible for testing a proposition).
An example of a proposition is ‘‘the slope is erodible’’;
examples of topics for this proposition include slope
steepness, slope length, soil type, vegetation type, and
precipitation. Evidence for propositions and their topics are
combined using OR and AND Boolean logic operators.
The OR operator returns the evidence for its strongest
premise. Thus, for the OR operator, if only one topic within
a proposition is fully satisfied (evidence = 1.0), the entire
386 Environmental Management (2012) 50:381–395
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proposition is considered satisfied, even if all its other
premises provide no evidence (evidence = -1.0). The
AND operator is used to combine topics, when all topics
must be fully satisfied to fully support the proposition. The
AND operator combines the evidence of multiple premises
based on the formula:
AND t1; . . .; tnð Þ ¼ min t1; . . .; tnð Þ þ�average t1; . . .; tnð Þ
�min t1; . . .; tnð Þ �� ½min t1; . . .; tnð Þ þ 1�=2
where t1 to tn are the evidence of n premises being com-
bined. Thus, an AND-based proposition is completely
unsatisfied (evidence = -1) if any of its topics are com-
pletely unsatisfied and only completely satisfied (evi-
dence = 1) if all of its topics are true. A useful way to
understand the AND operator is that it treats its underlying
set of topics as limiting factors.
After the EMDS model run, truth values for environ-
mental conditions were associated with the routes database
attribute table. Each feature or landscape attribute in the
knowledge base had a corresponding truth value field, and
truth values were calculated for each route segment. These
values were used in later calculations of environmental
impact and to create optimized route networks. Truth val-
ues for environmental impact were composed of multiple
attributes, combined using the model’s logic rules.
Scenarios
Model scenarios were run for each of the 6 types of rec-
reation opportunities: 4WD, quad, motorcycle, bicycle,
horse, and hiking. Each scenario run resulted in a different
recreation opportunity truth value finding for route seg-
ments. In each scenario, the potential environmental
impacts were assumed to be similar. Within each recrea-
tional scenario, route benefits were combined with poten-
tial environmental impacts using the Boolean AND
operator. This calculation provided a direct objective
measure of the ability of each route segment to meet the
combined requirements of maximizing recreational
opportunity, while minimizing environmental impact.
The model output consisted of normally-distributed
values for the higher order primary knowledge base con-
cept: ‘‘Route segments sustainably meet recreational goals
while minimizing environmental impact’’. This concept
was the product of an AND relationship between the sub-
concepts: ‘‘Environmental impact’’; and ‘‘Trail benefits’’
(Fig. 2). The high values in all cases corresponded to a low
environmental impact and high-value recreational route,
the low values corresponded to a high environmental
impact and low-value recreational route. ‘‘High value’’
recreational routes are defined as meeting user preferences
as found in the recreational use survey and from TNF
staff’s expert opinion. The higher order concepts contain
multiple sub-concepts and can guide larger decisions about
route systems. Because each higher order concept is an
aggregate of lower order concepts (Fig. 2), the recreation
planner or land manager can use the knowledge base to
‘‘drill down’’ in the model output attribute table to find out
why a particular segment received a relatively high or low
score. The combination of mapped potential environmental
impacts and trail user preferences for each recreation
activity type was then used to develop guidelines for
overall system planning and to make recommendations to
TNF route designation staff.
Route System Optimization
There is no software currently available to automate the
selection of recreation routes on a landscape in order to
optimize recreational experience opportunities, while
minimizing environmental impact. In particular, the desire
expressed by motorized and non-motorized visitors for
looping paths makes automated optimization difficult for
multiple starting and end points. Here, we demonstrate two
methods for approximating an optimized route system that
maximize recreation opportunity and minimize potential
environmental impact. In both cases, the goal was to derive
an optimized route system that met recreational demand for
motorized recreation, while minimizing conflict with
impacts on the environment and potential for conflict with
non-motorized recreationists.
Data collected for the USFS National Visitor Use
Monitoring program (NVUM) indicates that between 3.7
and 7.3 % of visitors to the TNF were engaged in ‘‘OHV
Use’’ as a primary activity or ‘‘Motorized Trail Activity’’
as a general activity, respectively (USDA Forest Service
2006). The NVUM also describes 26.9 % of visitors using
routes in non-motorized recreation as a primary activity
and 50.3 % of visitors engaged in hiking, biking, fishing,
wildlife viewing, backpacking, camping, and other non-
motorized recreation in general. Because, at most, 7% of
recreationists in the TNF use wheeled, motor-powered
vehicles (e.g., 4WD, quads, motorcycles; USDA Forest
Service 2006), we constructed each motorized recreation
route system on a corresponding proportion of the TNF
transportation system: specifically, 7% of the existing trail
and dirt road network. We chose this approach because it
was the most parsimonious way to determine a threshold
for sharing a system where there is conflict among groups,
although we acknowledge that other factors could be
considered (e.g., average distance of trail traveled by a
visitor in each recreational user group).
Manual Selection: Because there was no suitable auto-
mated alternative available to optimize a route network
Environmental Management (2012) 50:381–395 387
123
with multiple loops, routes were selected by hand within
the GIS—‘‘manual selection’’. The output from the mod-
eling of potential environmental impact was used as the
basis for manually selecting routes that had the lowest
environmental impact in contained, looping networks
around six motorized recreation trail-head facilities in the
TNF: China Wall/Parker Flats, Big Trees, Prosser, Sterling
Lake, Washington Overlook, and Eureka Diggins. By
selecting motorized recreation trail-heads as the core of the
optimized system, we made the assumption that concen-
trating motorized recreation use in certain areas that were
familiar to users and that were not near non-motorized
recreational areas, conflict could be minimized.
For each trail-head area, route segments were manually-
selected on-screen at 1:24,000 from the TNF route network
that had the lowest potential environmental impact. The
segments were selected so that they avoided environmental
harm and provided for looping routes and routes that
accessed more remote areas. The final systems were ana-
lyzed for minimization of environmental harm relative to
the entire set of roads and trails.
Cost-Distance Modeling: This consisted of automated
calculation for each route segment of the combined dis-
tance from the same six motorized recreation trailheads and
environmental impact of all route segments. These values
were used to illustrate routes that could meet combined
needs of trailhead access and minimized environmental
impact. We used Path Distance analysis in ArcGIS Spatial
Analyst and converted the path distance value back to the
poly-line route network file. Path Distance calculates the
least accumulative cost to the nearest point from a given
source taking into account surface distance, and the cost of
traveling across that point, modeled as the environmental
impact value (range 0.5–1.5) multiplied by the travel
distance.
Results
Survey of Recreational Users
During the one month the online survey was available, 813
recreational trail users responded. Of these, 49 were from
outside California and 40 did not provide zip codes. The
respondents were asked to describe their recreational
preferences and other uses of the route system. Not all
respondents answered all questions. Based on their indi-
cation of their ‘‘favorite type of recreation’’, respondents
were roughly split between motorized (n = 444) and non-
motorized (n = 325) recreation types, with the largest
groups being 4WD vehicle drivers (n = 294) and hikers
(n = 209).
Recreation frequency varied slightly by type of recrea-
tional activity, and among all respondents, monthly recre-
ation was the highest (54 % of respondents), with weekly
(21 %), annually (19 %), and daily (6 %) frequencies
ranking lower. Age distributions were different among
recreation types, with a greater representation of older age
classes for hikers and horseback riders and a greater rep-
resentation of younger and middle age classes for motor-
ized recreation. Similarly, gender distributions varied by
recreation groups, with horseback riders and hikers having
greater proportions female respondents than motorized
recreation.
Conflict Among User Groups
None of the survey questions asked explicitly whether or
not the respondents were opposed to multiple recreation
types using the same route system. However, two open-
ended questions in the survey provided an opportunity for
respondents to indicate ways that the TNF could improve
the route system. Seventy six percent of non-motorized and
79% of motorized recreationists responded with text com-
ments. Of those respondents including text comments, 63%
of non-motorized recreationists reported conflict with
motorized recreationists, and 4% of motorized recreation-
ists reported conflict. Hikers and horseback riders reported
conflict at higher rates than all other recreation types.
Conflict statements from non-motorized recreation respon-
dents often included sentiments like: ‘‘No motorized vehi-
cles allowed period’’. Conflict statements from motorized
recreation respondents were similar, but rarely suggested
banning non-motorized recreation: ‘‘Seperate [sic] the
hikers from the off highway adventures’’.
Respondents also used the open-ended questions to
voluntarily report their positive or negative feelings about
multiple-uses of recreational route systems. Almost half of
hikers and almost two-thirds of horseback riders were
opposed to multiple uses of the route system by motorized
and non-motorized recreation (Fig. 3). In contrast, very
few motorized recreationists opposed multiple-uses of the
route system. For the 9 % of all respondents who supported
multiple-uses, motorized recreation respondents were twice
as likely to support multiple-uses as non-motorized
(Fig. 3). Older recreationists were more likely to report
conflict and oppose multiple uses of the route system than
younger respondents.
There were several ‘‘cut-and-paste’’ comments in the
survey, exclusively from respondents who identified them-
selves as motorized users. This indicates that the online
survey URL was likely passed along among groups with
access to a common set of responses. The following are the
more prevalent among the survey responses, quoted verba-
tim: ‘‘Develop new OHV and 4x4 trails’’ (n = 21);
388 Environmental Management (2012) 50:381–395
123
‘‘Increase dispersed camping opportunities’’ (n = 29);
‘‘Provide additional structure parking for OHV [and/or]
equestrian support vehicles’’ (n = 45); and ‘‘Balance use by
trail miles, not just by acreage. A healthy forest acre has huge
opportunity for campers, hikers, bird watchers’’ (n = 17).
Model Outputs
The EMDS model provided 3 main findings that can be
applied to design an optimal recreation system for TNF. The
first was an estimate of the potential recreational opportunity
for each of the 6 recreation types. The second was an esti-
mate of the potential environmental impact of each segment
in the route network, including dirt roads, authorized trails,
and unauthorized trails. The third provided an estimate of
management sustainability from the combined potential
environmental impacts and recreation benefits. This com-
bined cost-benefit output (where cost = environmental
impact) would allow a recreation planner to design a route
system that meets the combined social and statutory
requirements of accommodating forest users’ needs while
minimizing environmental impacts. Because one of these
outputs was developed for each recreation type, recreational
planners could develop an overall system that also mini-
mized conflict among user groups through sub-sets of trails
for recreation groups. In each case of modeling environ-
mental impacts or recreational benefits, the values provided
in this section are relative to each other. In other words
‘‘high impact’’ of a trail segment means high relative impact
compared to potential impacts of other segments of the trail
system. Because of the wide range of benefits and impacts in
the system, we suggest that low and high relative model-
values are similar to actual values.
Benefits for recreational use were modeled based on 8
spatial data sources for all 6 non-winter recreational user
types and results are shown separately for motorized and
non-motorized uses (Fig. 4a, b). The values are normally
distributed across the range from 0 (low use) to 1.0 (high
use). However, there was a strong spatial concentration of
high recreation benefit values on the eastern side of the
Forest, where route systems and facilities have been more
developed for motorized recreational use.
Based on the 22 datasets of environmental conditions
and the knowledge base defining their contributions to
environmental impact (Fig. 2a), the potential environ-
mental impact of each dirt road and trail segment was
modeled (Fig. 4c). The distribution of values was normal
across the range from 0 (high impact) to 0.87 (low impact),
and the low and high values were relatively evenly dis-
tributed across different parts of the Forest.
The outputs of the models for potential environmental
impacts and recreational benefits were combined to iden-
tify routes that had low potential environmental impact and
high recreational benefits and were thus more sustainable
and preferable in the long-term. Results are shown for the
top quartile of routes for all motorized recreation combined
(Fig. 4d). The truth values for the combined output were
normally distributed across the range from 0 to 0.90. There
was some spatial concentration of preferable routes across
the Forest, with higher values—indicating a lower envi-
ronmental impact and greater recreation opportunity—
more concentrated in the eastern side of the Forest.
Optimizing Route Systems to Minimize Impact
and Maximize Recreation
Manual Selection
Six optimal networks were delineated for the TNF, one for
each OHV staging area (Fig. 5a). Each proposed network
Fig. 3 Proportions of
participants engaged in different
recreation types reporting
conflict and support or
opposition to multiple-use of
trails
Environmental Management (2012) 50:381–395 389
123
was analyzed for the potential environmental impact of its
component route segments. On a per-segment basis, the
recommended routes had overall lower environmental
impact than the existing system (Fig. 5b). In addition,
because the recommended route network had only 7 % of
the total distance of the existing transportation system—
603 km of routes compared to 8,713 km of authorized and
unauthorized roads and trails available for recreation—the
net environmental impact of the combined recommended
route systems was much lower than that of the existing
system (Fig. 5c).
Cost-Distance Modeling
An alternative approach that can further assist in the
manual selection of looped networks to meet route
Fig. 4 a Trail benefits of routes for mixed non-motorized recreation and b mixed motorized recreation. c Environmental impact of routes
according to the EMDS model. d Management sustainability of routes for motorized recreation according to the EMDS model
390 Environmental Management (2012) 50:381–395
123
optimization goals is the use of ‘‘cost-distance’’ modeling,
where cost is the product of travel distance and potential
environmental impact (Fig. 6). Using an OHV staging area
as a starting point, the combined cost-distance was calcu-
lated for each route segment around each of 7 trail-heads
and staging areas in the TNF. This allows a manual selec-
tion of routes based on the efficiency of the system through
a combination of travel distance from the trail-head (indi-
cated with a circle) and potential environmental impact.
Discussion
Spatial Optimization
According to Executive Order, designated routes under the
TMR must meet the following requirements: ‘‘the
responsible official shall consider effects on National
Forest System natural and cultural resources, public
safety, provision of recreational opportunities, access
Fig. 5 a Selected route networks around motorized recreation access
points in the TNF. The background is the TNF administrative lands in
gray, with private in-holdings shown in white. b Proportion of all
routes and selected routes in each environmental impact category
from high impact (0.00) to low impact (1.00). c Combined lengths of
all routes and selected routes in each environmental impact category
from high impact (0.00) to low impact (1.00)
Environmental Management (2012) 50:381–395 391
123
needs, conflicts among uses of National Forest System
lands, the need for maintenance and administration of
roads, trails, and areas that would arise if the uses under
consideration are designated; and the availability of
resources for that maintenance and administration.’’
(TMR, § 212.55(a)) The main finding from the present
study was that collaborative modeling with a USFS Rec-
reation Inter-Disciplinary Team could provide a National
Forest with the tools to develop a potential environmental
impacts analysis for the entire route network, a recrea-
tional benefits analysis, and an optimized recreational
route system that could reduce conflict. We were also able
to combine the impacts and benefits into a whole recrea-
tion system analysis that was effectively a cost-benefit
accounting, consistent with requirements of both the
federal Travel Management Rule (TMR) and the National
Environmental Policy Act. This approach also allowed
for estimation of cumulative effects and through optimi-
zation of the network, a demonstration of cumulative
effects minimization and minimization of user-conflict.
Previous studies have used the least-cost path analysis
approach for forest road system optimization (Girvetz
and Shilling 2003) and for single motorized recreation
route optimization (Snyder and others 2008). An impor-
tant advance in this area would be the development of a
recreational route-network optimization approach in GIS
that minimized environmental impact and user conflict,
while providing some reasonable level of recreation
opportunities.
The important contribution that this analysis makes is that
it is possible to minimize environmental impact and provide
mixed recreational opportunities within the same overall
system. If the recommended motorized route networks were
implemented, the net result should be an efficient system in a
compact area to limit impacts to surrounding natural systems
and non-motorized recreation. The recommended, opti-
mized system is also more manageable from a maintenance,
administrative, and law enforcement point of view because it
is limited to * 600 km of trails and dirt roads, which seems
appropriate, based on the dollar values for cost per mile of
trails and dirt roads ($1,500-$5,770/mile) and the amounts of
funding available for at least roads maintenance described in
the TNF-DEIS (Vol. 3, 2008). The TNF estimated that
motorized recreation costs approximately $23–$28 million
annually in terms of road and trail maintenance, whereas the
roads-maintenance budget for 2007 fiscal year was $1.2
million,*5 % of the amount needed. Management action to
resolve conflict has not been forthcoming in the TNF and
other Forests, possibly because, federal agency officials
reported that they ‘‘cannot sustainably manage their OHV
route systems’’ (GAO 2009). A reduced motorized routes
system would be more sustainably managed and reduce
conflict between motorized and non-motorized user groups.
User Conflict
Conflict among out-door recreational groups can take many
forms; Jacob and Schreyer (1980) posited that there are 4
Fig. 6 Least-cost paths
originating from motorized
recreation trail-head and staging
area (‘‘Parker Flat’’), where cost
is a combination of
environmental impact and
distance
392 Environmental Management (2012) 50:381–395
123
main classes of factors that could produce conflict: activity
style, recreational resource specificity, mode of recrea-
tional experience, and lifestyle tolerance. The potential for
these factors to result in conflict increases as the rate of
encounter among recreation group type increases (Jacob
and Schreyer 1980). The recognition that conflict among
uses be considered and presumably kept to a minimum
through spatial separation of activities has a long history in
recreational management by the US Forest Service (Clark
and Stankey 1979). This philosophy derives from the
highly varied patterns of recreational behavior and recre-
ationist demographics in National Forests (Chavez 2001).
One assumption of the public and land managers is that
these varied patterns and activities can co-occur under a
multiple-use model. This may be true, but if conflict occurs
or is perceived, then land managers have a responsibility to
minimize it through system and activity management.
As demonstrated here, conflict among users of the Tahoe
National Forest is perceived to be high by non-motorized
route users, but not by motorized users. Approximately
one-quarter to half of all hikers and horseback riders
reported significant conflict with motorized recreation and
about half opposed multiple-use of route systems. In con-
trast, very few motorized recreationists reported conflict or
opposed multiple-use. Although users were not asked the
reason for the perception of conflict, it seems likely that
interactions between motorized and non-motorized users
on the same route will have a greater effect on the non-
motorized users. These findings are critical for 3 reasons:
(1) According to the National Vehicle Use Monitoring
study conducted by the US Forest Service (USDA Forest
Service 2006), the vast majority of TNF recreationists are
not motorized recreationists, but instead are hikers, walk-
ers, bird-watchers, campers, anglers, and equestrians. (2)
People engaging in non-motorized recreation are signifi-
cantly impacted by motorized recreation because of sound
and safety issues, whereas motorized recreationists repor-
ted no impacts and may suffer few disadvantages from a
mixed use system. (3) Multiple-use at the route-scale (as
opposed to whole Forest scale) is a management option that
conflicts with the needs of the majority of users of the
Forest. If this option is failing, then other options should be
explored to meet the requirements of the National Forest
Management Act, the Travel Management Rule, and the
National Environmental Policy Act. One such option is the
establishment of defined ‘‘Motorized Recreation Areas’’
that can be managed to reduce conflict with non-motorized
recreation, allow multiple-use of the Forest, but not each
route, allow effective law enforcement, be affordable with
current maintenance allocations, and reduce overall envi-
ronmental impact. The proposed networks in the present
study would be one way to effectively reduce conflict,
while also providing sufficient motorized recreational
opportunities and minimizing environmental harm. By
decreasing the likelihood of encounters among recreation
groups, Jacob and Schreyer’s (1980) conflict factors are
less likely to result in actual conflict.
Success of Application of the Travel Management Rule
In an exhaustive review of the social and legal aspects of
TMR implementation, Adams and McCool (2009) suggest
that ‘‘the agencies need to do their best to imagine the best
possible arrangement of ORV routes, rather than simply
tinkering around the edges of the current allocations.’’ The
Tahoe National Forest has been preparing a management
response to the federal TMR since 2006 by designating
routes and preparing a ‘‘Motor Vehicle Use Map’’. It was
once one of the leading forests in California in this effort,
but was the last to complete its Final EIS (http://www.fs.fed.
us/r5/routedesignation/statusreport/report042010.html), partially
in response to receiving [3,000 scoping comments and
[7,000 comments on the draft EIS. A possible cause for the
delays and comments is that, contrary to the goals and
requirements of the TMR, the plan for motorized recreation
management available for public input (Tahoe National
Forest 2008) failed fundamentally to deliver a low-impact
motorized route alternative. One reason for this is that under
the proposal analyzed in the DEIS, the existing route system
remains substantially un-modified, motorized recreation
routes were added in almost all alternatives, and the DEIS did
not consider the individual and cumulative effects of routes
used for motorized recreational and other vehicular travel.
For example, under DEIS preferred alternative B, routes pass
through streams, wildlife nesting and foraging areas, and
meadow areas. In addition, despite impacts to wildlife being
one of the primary concerns about motorized recreation
management, only two routes were identified as needing any
mitigation activity from the use of OHVs (Tahoe National
Forest, Vol. 2, 2008) and no significant analysis of noise
impacts were conducted, despite motorized-recreation noise
being one of the most obvious impacts to wildlife. This is in
contrast to the optimized system proposed in the current
study, based upon TNF staff rules, the literature on impacts
of motorized recreation, the results of the user survey, and the
principles of the Recreation Opportunity Spectrum (ROS).
There is no reason to think that the Tahoe National
Forest is any different from many other Forests in its
designation and environmental analysis of routes under the
TMR. For example, the neighboring Eldorado National
Forest (http://www.fs.fed.us/r5/eldorado/projects/route/index.
shtml) and the more distant Six Rivers National Forest
(http://fs.usda.gov/srnf) also maintained or increased the
available length of routes for motorized recreation and did
not base route designation decisions on minimizing envi-
ronmental impacts. This conclusion is based on the fact
Environmental Management (2012) 50:381–395 393
123
that, although the Forests comprehensively describe
potential impacts, these impacts were not explicitly used as
part of decision-support for designation of individual or
networks of routes, or what was the ultimate selection of
the most environmentally-harmful alternative (Eldorado
National Forest 2008; Six Rivers National Forest 2010). In
addition, neither Forest developed a system to minimize
conflict among user groups, despite a requirement under
the TMR to minimize conflict (TMR, § 212.55(a)).
Although evidence of conflict is provided by the present
study and close reading of responses from the public to
National Forest environmental analyses, the Forests largely
ignored conflict in their route designation process. Essen-
tially, all 3 Forests ‘‘tinkered around the edges of current
allocations’’ (Adams and McCool 2009) and failed to
design an effective and manageable recreational system
based on requirements under the TMR.
Optimization and Resolution
We present here one way to resolve possible conflicts that
arise among recreational user groups and address trade-offs
between recreation opportunities and environmental val-
ues. This approach is consistent with current recommen-
dations for policy and management directions that the US
government and its constituent agencies, the US Forest
Service and Bureau of Land Management should take to
minimize conflict and environmental impacts from
motorized uses (Adams and McCool 2009). At the same
time we recognize that the land management agencies may
not have the ability or desire to resolve conflict in this way,
by segmenting competing uses in a way that limits
motorized recreation (Wilson 2008).
By selecting environmentally optimized roads and trails
for motorized recreation around existing staging areas, both
environmental harm and potential conflict between
motorized recreationists and non-motorized can be mini-
mized. One important step in the proposed approach is to
estimate potential environmental impact for the recrea-
tional routes, as required by the TMR and NEPA. This
estimate of harm can be combined with recreation prefer-
ences to develop an environmentally-optimized road and
trail system that provides motorized recreation while
minimizing environmental harm. We chose the approach of
selecting route system length for a group (i.e., motorized
users) based on proportion of total number of users,
because it was the most parsimonious way to determine a
threshold for sharing a system where there is conflict
among groups. This approach also does not favor one
group over another in that each group is allocated a pro-
portion of the system according to the group’s size. Finally,
this approach has the secondary benefit of limiting the
degree and spatial extent of cumulative environmental
impacts from motorized recreation. The approach descri-
bed could be used to implement the ROS approach in a way
that has not previously been available. Specifically,
developing a recreational system that deals with conflict,
environmental impacts, and system limits is more likely to
be sustainable and manageable on public lands. We pro-
pose this approach as a way forward for public lands
managers attempting to resolve differences over transpor-
tation system management.
Acknowledgments Funding for this work was provided by the US
Forest Service, Tahoe National Forest (TAH-OHV-02-05) and the
Recreation Planning Program of The Wilderness Society. Particular
thanks are given to Carol Kennedy and other members of the Tahoe
National Forest-Inter-Disciplinary Team for recreational routes
analysis and planning and for helping to develop the optimization
model. Thanks also to Mark Lubell, UC Davis, for advice on
designing the survey instrument and analyzing survey data. The
article benefited from the insightful comments of the editor and 3
anonymous reviewers.
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