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• W2557652076 abstract "For the land managers of natural areas, knowledge of the location of the highest risk for visitors is required for the implementation of management measures that modify either the density of infected ticks (hazard) or the level of contact of the visitor with these ticks (exposure). We explore the possibilities to develop a simple, but informative reliable model to create local risk maps for land managers. In addition, we aim to disclose the most important parameters, based on literature study and expert opinion, in defining the risk on acquiring a tick bite from the deer tick Ixodes ricinus. We want to predict risk levels within the area of the land managers using these most important parameters and their knowledge of the area. By involving their knowledge, land managers are more likely to embrace the information risk maps can give them on, for example, vegetation structures, grazed pastures and touristic attractions. We developed a generally applicable model in ArcGIS to create the risk maps and based the model on the most important parameters (both hazard and exposure) explaining the risk of acquiring a tick bite for visitors of natural areas. We based the first part of the model on parameters explaining the hazard: vegetation type, absence/presence of wild ungulates, absence/presence of sandy soil and absence/presence of grazing leading to a hazard risk map with three risk levels (low, medium and high tick densities). In the next step, we included the exposure parameters in the model: accessibility, recreational quality, temporary exposure, and stationary exposure (crossroads and benches). This led to seven risk levels in total. We only validated the hazard part of the risk map in the field for a dune natural area: ‘Het Noord-Hollands Duinreservaat’. This pilot study presents a novel approach to disclose expert information to land managers to assist them with implementing management measures to prevent that visitors acquire tick bites. We view the results as promising and hope they will inspire additional investigation into the validation of the model and translation into a decision key for cost-effective and risk-based management." @default.
• W2557652076 created "2016-12-08" @default.
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• W2557652076 date "2016-11-30" @default.
• W2557652076 modified "2023-09-27" @default.
• W2557652076 title "26. From guessing to GIS-ing: empowering land managers" @default.
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• W2557652076 doi "https://doi.org/10.3920/978-90-8686-838-4_26" @default.
• W2557652076 hasPublicationYear "2016" @default.
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