Mountain biking is a well-established activity. It allows people to enjoy the outdoors, be active and reconnect with nature, but like all human activities, it also raises questions about the balance that needs to be struck between nature access and preservation.
A study carried out by the University of Zürich under the direction of Martin Wyttenbach looked at the impact of outdoor activities on the local deer population, and concluded that it was important to raise awareness of the need to respect wildlife, and to channel activities along well-defined trails to minimize impact. To find out more, read the full article on this subject.
The recent democratization of electric mountain biking has considerably broadened the potential user base and range, raising new questions about trail erosion, disturbance of flora and fauna, and potential user conflicts.
Among the questions opened up by this democratization :
A few studies mention differences in practices and profiles, but all acknowledge a current lack of robust data on the exact differences in ecological impact between these two types of mountain bike. The trend, therefore, is to stay cautious and limit pressure on natural environments, whatever the type of bike.
Nevertheless, here are a few studies carried out in the USA on the subject, to be extended with the help of ridership and behavior data made possible by our new solutions !
A study carried out in 2023 by a team of data scientists and Jim Wells, Park Manager for Dead Horse Point State Park (Moab, Utah) at Minuteman National Historical Park, gathered initial data on the behavior of mountain bike and eMTB users.
The results show little difference in behavior between conventional and assisted mountain bikers: average speed is only 2-3km/h (1-2mph) higher. Preliminary data show it is the type of ground used that is the main determinant of speed.
It was noted that conventional and electric bicycles slowed down in the same way in "high-risk" areas (such as junctions with roads used by vehicles). However, the study notes a lesser tendency for eMTB cyclists to direct their gaze towards high-risk areas.
In eastern California, reports came back from the field that mountain bikers tended to ride worse than before, and were more dangerous. This raised the question of whether it was relevant to open trails for e-mountain bikes.
A project has therefore been underway since 2017, with Sean Dougan, Trails Program Manager, to open up the practice on three specific trails, on a test basis, with an analysis of usage and behavior to identify relevance and assess possible conflicts.
Manual counts were therefore carried out, as well as an online and field survey. 244 manual counts were carried out on 20 trailheads. The figures showed that electric-assist mountain bike users represented a mere 2% of the total.
Distribution of users on the three trails studied
No conflicts of use were observed, with all types of cyclists having the same tendency to slow down when approaching intersections with motorized vehicles or pedestrians.
Surveys of local hospitals were also carried out, and concluded that there was no increase in accidents (alone or with third parties). These figures convinced the decision-makers to maintain the authorization for e-bikes to use the three trails, with the inclusion of prevention measures: signage to inform of the types of assisted bike authorized or trail access arrangements.
To carry out more comprehensive studies on the new uses of electric mountain bikes, and to obtain objective feedback on the preservation of natural areas, we are currently developing the CITIX AI Evo in Low Power version!
This multi-practice counter categorizes regular bikes from electric-assist bikes (thanks to the bike's morphology). This categorization enables a detailed analysis of usage and behavior (average speed, preferred routes by bike type and population).
This will enable managers of natural areas to provide objective elements for making the right decisions, and raising awareness among cyclists.
Possible installation of our CITIX-AI Evo camera in a natural environment
(powered with battery and/or solar panel)
Do you have a project in mind, or would you like to find out more about the behavioral and usage data that can be obtained by classifying eMTB and regular bikes with CITIX AI Evo ?