Using GPS tracking to understand the impact of management interventions on visitor densities and bird populations

To manage the potential conflict between outdoor recreation and nature conservation, managers of nature areas need information to select effective interventions. For large nature areas information on visitor use is often lacking and managers often make decisions based on expert judgement. In this paper we use monitoring data gathered with GPS devices to develop a tool and derive rules of thumb managers can use to estimate the impact of management actions on visitor densities. Using a dataset of 1563 tracks from the New Forest, UK, we developed a random forest model and identified which landscape and environmental features account for the spatial variation in visitor densities. The random forest model shows that distance to car park, distance to roads and openness are the most important factors for predicting visitor densities. The model was used as a tool to assess the impact of potential management interventions on the population of Nightjar. As developing this type of tool requires a lot of data we also derived rules of thumb and a simple algorithm that managers of other nature areas can use to estimate the impact of their interventions on visitor densities. The derived rules of thumb show that changing the location of car parks in relation to tarmac roads can help managers to reduce local visitor densities by 80%. Further research in other nature areas should verify the feasibility of these rules of thumb and the simple algorithm. •GPS data provides information to understand what drives visitor densities.•Random forest models can be used as tool to assess the impact of interventions.•Current recreational use lowers the Nightjar population by 38% in the New Forest, UK.•Changing the location of car parks in relation to roads is an effective intervention.•Managers might use a simple algorithm for a first estimation of visitor densities.