2010GradResearchSymposiumPoster yfx - Outdoor ...


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Research Purpose

A considerable amount of issues relating to mountain bike use impacts has surfaced in the last two decades. Social and
environmental impacts of the estimated 50 million mountain bike users in the United States as of 2008, has elicited concern
from resource managers and outdoor recreation resource
researchers (Outdoor Foundation, 2009: Shimano & International
Mountain Biking Association, 2008).
In response, mountain bikers have united together in large associations such as the
International Mountain Biking Association (IMBA), and Triangle Off
Road Cyclists (TORC). Mountain bike associations are
advocating and funding mountain bike trail construction projects all over the world, based on research showing mountain bike
impacts to be similar or less than traditional trail
activities (Webber, 2007).
Although literature confirms similar environmental
impact levels associated with mountain biking, hiking and horseback riding, it also references the fact there are no assessme
tools to measure mountain bike specific impacts. The purpose of this study was to develop a mountain bike specific, impact
tool (
, 1995; Pickering, Newsome, Hill, & Leung, 2010).
In order to understand specific mountain bike use
impacts we developed an assessment tool that measures environmental impacts related to technical trail features that exist
primarily for mountain bike use.

Specific Mountain Bike Impacts

Difficulties understanding mountain bike related impacts stem from the variety of rider types within mountain biking
itself. The International Mountain Biking Association (2006) references six different rider types: all
mountain, cross country,

downhill, free ride, racing and urban, each having different preferences, motivations, attitudes and skills. With such a div
user group the demand on resources and management have led to access and environmental impact issues. One specific rider
type called free riding, a combination of all other rider types, has been associated with high levels of environmental impact

the use of technical trail features (TTFs). In this study we have defined TTFs as
, natural features or built structures
that enhance mountain bike riding experiences through physical and mental challenges. These features are found
predominately in areas where natural terrain does not provide the physical and mental challenges riders desire. TTFs have
presented resource managers another challenge for protecting resources while providing desired outdoor recreation experiences

Current State of Literature

Previous studies have assessed mountain bike impacts through tools created for environmental assessment of traditional
trail recreation activities. This limited approach has found significant mountain biking impacts associated trail design, us
behavior and trail conditions but does not incorporate specific mountain bike elements. These studies have found high level
of environmental impact associated with steep slopes, curves, wet conditions, skidding and
braking (
, &
, 2000; Marion & Wimpey 2007; Thurston & Reader, 2001).
The consensus is that mountain bike impacts are similar
or less than other permitted trail uses. However, only two studies (
Newsome & Davies,
2009 and Pickering,

In Press)
incorporated technical trail features in their assessments. In essence this study provides two purposes; one to continue the

development of an assessment tool that measures mountain bike specific impacts and the attain a larger breadth of knowledge
about mountain bike


Study Site

Mountain biking in its short history has already become specialized and has its own terms that riders have construc
ted to describe their experiences and
features. To properly assess the features and ensure accuracy we constructed a feature identification guide that had picture
s a
nd technical terms for all known
mountain bike features. The field identification guide was used to survey several mountain biking sites within the Research
angle Area of North Carolina to see
what features were present here and to find an adequate research site. Potential study sites were found through a popular mo
ain biking website
(www.trianglemtb.com) and talking to local mountain bike users.

Legend park, a 24 acre heavy vegetated Urban park located in Clayton, North Carolina was selected as the study site

for it's variety and total number of
technical trail features (n=86). This site was also chosen for it's high visitation rate among Research Triangle Area mounta
bike riders. Legend park was
constructed by the Town of Clayton and local mountain biking advocates and is managed by the Town of Clayton. Legend park ha
s n
ine different trails that
combine to form over eight miles of trail with varying skill ratings. This site is known amongst Triangle Area riders for it

which are steep drop offs and
technical built structures.


The instrument chosen for this study was adapted from two Australian studies, Pickering
(In Press)
and Newsome (2009), to assess technical trail features
found in the United States. A field test of Pickering (2010) and Newsome (2009) found the presence or absence of certain fea
e, safety and managerial
components. The final instrument
used examined technical trail features and its proximate areas for environmental, safety, social and managerial issues.
In total there were 28 different elements that were used to assess the technical trail features. Comprehensive field procedu
and data forms were field tested and
finalized to ensure accuracy amongst the researchers.

During the field tests it became apparent that a circular observation zone (COZ) would be the most efficient, syst
ematic way to assess the features and their
respective impact. The COZ consisted of a flagged circle around the feature that had a radius half the size of the technical

ial feature. This observation method
allowed for a more complete assessment that included all trail features and their proximate areas. Standard trial measuremen
t t
ools were used for the assessment
procedure including a metric wheel, metric rulers, a SUUNTO Tandem
/compass combo, and a Garmin GPS Unit (Oregon 550 with digital camera).
Research teams were organized into two teams of two where one member took measurements while the other entered data onto the
ld data form. The
observation period lasted one month during the fall season of 2009.


A total of 86 technical trail features we identified and assessed at Legend Park. Of the 86 TTF's forty
two features
were built
technical features, 23 were natural trail features and 21 were built enhanced features. The experience grouping had 39 trave

features, 32 aerial features and 15 ground features. The frequency of features (feature per unit area) was one for every 149

There were no significant differences for environmental, safety, social and managerial components found between the compositi
(BTF, BE, NTF) groups. However, there were significant differences found between the experience (aerial, ground, traverse)
groupings and amongst the technical trail features within the experience groups.

Results from the one
way ANOVA, shown in

Table 2
found significant differences at the 0.05 level among the experience
groups for the following variables: TTF length, TTF maximum height, trail incision, trail slope and landscape slope. Aerial
(Figure 3)
were associated with higher maximum height, trail incision and larger trail slope. Ground features

( Figure 2) were
associated with longer feature length and larger landscape slope. Traverse
features (Figures 1 & 4)
had the smallest mean feature
length, maximum height, trail incision, trail slope and landscape slope.

Group differences using the chi
square analysis found several trends in the data. Aerial features were more likely t
o be in
cleared areas than traverse or ground features that were predominately on trail. Ground features were almost always found by

vegetation and a closed canopy while traverse and aerial groups were found near light vegetation and moderate canopy openness

The traverse groups had much less root exposure around features than either aerial or groups group features which were heavil
associated with root exposure.

The Chi
square analysis within experience groups found significant differences at the 0.05 level amongst the features

each group. The traverse group had the most variance among features with four significantly different variables while the g
group had the least variance with only one significantly different variable. Two variables, root exposure and canopy opennes
found to be significantly different amongst the aerial group. Drop
off features had one hundred percent of features showing roo
exposure while the other features had a mixture of presence and absence of root exposure. The drop
off features were also assoc
with open canopy more than the other features. The ground group had only one variable, native vegetation removed to construc
feature, showing significant difference among its' features.

were heavily associated with the presence of removed native
vegetation while rock gardens and whoop

were more naturally existing. The final group, traverse, had the most variance
amongst the highest total number of features in any group. Trail feature condition, native vegetation removed to construct

trail type and root exposure differences were all significant at the 0.05 level. Bridge, boardwalk and skinny features had
condition scores and were not associated with removal of native vegetation. Log ride and boardwalk features were associated
less root exposure than the other technical trail features within the traverse group.


The adapted framework based on experience categorization proved to be an efficient way to assess and understand technical tra
features found on mountain bike sites. This conceptual model allows for the assessment of mountain bike specific impacts tha
t c
be added to the traditional trail assessments to gain an overall understanding of mountain bike impacts. The composition
categorization does provide information about how features are built but it does not provide a clear image for the assessment


environmental, social and managerial elements. However, the categorization based on experience does provide useful insight o
n t
environmental, social and managerial issues that are debated today. Using the experience group categorizations can provide s
mountain bike assessments, specific feature assessment and comparison, areas where certain features may not be suitable, and
possible substitution of features.

It is plausible that groups have differences among them since they have been constructed to provide different
Previous research has shown that riders prefer variability among trails and experiences. That has been one of the major iss

managers as they struggle to provide all the experiences that several rider types prefer. This adapted model shows the f var
amongst features and groups and incorporates that into the assessment tool. The length and height of features vary between
as does trail and landscape slopes. These variables have been heavily studied components of trail elements that are found on

mountain bike sites but have not been examined in the form of technical trail features.

Within the groups there is also variability amongst the features that provide similar experiences. The diffe
rences here are
due to composition differences between features. More variability was found within the traverse group because it had the mos
features providing the same experience. These features are providing the same function but are made of different materials,
and foreign, which have different levels of impact and construction needs. All of the groups had variability with levels of
environmental impact which suggests that certain features may be more harmful to the environment than others. If there are
multiple features providing the same experience and one has less environmental impact then management may substitute one feat

for another.


This assessment tool has many management implications including site design, social rules and feature manage
Proposed mountain bike sites can be designed with trail features that have known environmental, social, safety and managerial

components that will increase resource sustainability and user satisfaction. The GPS tool allows management to monitor the s
condition and number of technical trail features under their control. The geo
tagged photos can also be used to make paper maps

online maps that users can view before riding the trail for the first
time (Figure 5).


, G. R. (1995). Off
road mountain biking: A profile of riders and their recreation setting and experience preferences.
, (92).

Chiu, L., &
, L. (2003). Managing recreational mountain biking in wellington park,
Annals of Leisure Research
(4), 339

Davies, C., & Newsome, D. (2009).
Mountain bike activity in natural areas: impacts, assessment and implications for management: a case study from John

Forrest National Park, Western Australia
: Sustainable Tourism.

, S.,
, M., Olson, D., & Chavez, D. (1995). An examination of the characteristics, preferences, and attitudes of mountain bike user
s o
f the

national forests.
Journal of park and recreation administration
(3), 41

Marion, J., & Wimpey, J. (2007). Environmental impacts of mountain biking: Science review and best practices. In
Managing mountain biking: IMBA's guide

to providing great riding

(pp. 94
111). Boulder, CO: International Mountain Biking Association.

Foundation. (2009).
Outdoor recreation participation report

(pp. 1
48). Boulder, CO: Outdoor Foundation. Retrieved from outdoorfoundation.org

Pickering, C. (In Press). Environmental, Social and Management Issues of

Mountain Bicycling Trail Technical Features in an Australian

urban Forest.

, C. M., Newsome, D., Hill, W., & Leung, Y. (2010). Comparing hiking, mountain biking and horse riding impacts on vegetation

soils in

Australia and the United States of America.
Journal of environmental management
(3), 551

Shimano, & International Mountain Bicycling Association. (2008).
Outdoor freedom: As natural as riding a bike
. The economic benefits of mountain biking

(pp. 1

, M.,
, W., &
, V. (2000). Managing Recreational Trial Environments for Mountain Bike User Preferences.
Journal of

Environmental Management
(5), 549

Thurston, E., & Reader, R. (2001). Impacts of experimentally applied mountain biking and hiking on vegetation and soil of a d
duous forest.

(3), 397.

Webber, P., & International Mountain Bicycling Association. (2007).
Managing mountain biking : IMBA's guide to providing great riding
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Mountain bike picture: ww
w. www.pinedaleonline.com/scr

Figure 4: Skinny

Figure 3: Drop

Figure 2: Rock

Figure 1: A


5: Geo
tagged Trail Features

Figure 2

In an effort to understand mountain biking and its' impacts the
technical trail features were initially categorized into natural,
enhanced and built features. Natural features are technical terrain
that provides challenge to the riders but has not been changed by
humans. Built enhanced features are features that are comprised of
natural, native material but have been moved or changed by
humans to provide challenge. Built features are predominately
structures that are made of foreign materials that have brought to
the site and constructed by humans to provide an element of
challenge. Although this categorization has implications for
management it was not found to be an effective way to assess
technical trail features. Instead a categorization of features based
on the experiences they provided was more effective for assessment
and future application. Three categories (aerial, ground and
traverse) were designed to encompass the physical and mental
experiences provided by all technical trail features. Aerial features
allow riders to challenge themselves through the air and gravity.
Ground features allow riders to

technical terrain on the
ground. Traverse features allow riders to go from point a to point b
on a structure that takes the rider off the natural trail of surface.
The challenge presented and skill required can change based on the
dimension of the feature but the provided type of experience
remains constant.

Statistical Analysis

SPSS 18 was used for the statistical analysis of features and
categories for the 28 different assessment components. Data trends
showed a skew to the right hand side which required data
transformations (inverse and log) on several variables. A one
ANOVA was used to determine variance at the .05 level between the
three different experience groups. Due to the low sample size a
parametric Chi
square analysis was used to examine variance
among technical trail features within the experience group.

Table 2
: One
way ANOVA for Experience Groups

Table 1: Assessment Variables