Mapping drivers of change for biodiversity risk assessment to target conservation actions: Human frequentation in protected areas

Mapping the drivers of change that pose negative pressures or threats to biodiversity can help to identify where biodiversity is most threatened and can be used to determine priority sites to target conservation actions. Overlapping drivers of change maps with distribution maps of sensitive species provides valuable information to identify where and when it would be better to target actions to minimize the risk. The overall aim of this study was to develop a methodology for the integration of risk mapping associated with high human frequentation to guide conservation actions in two case study: the Kentish plover (Charadrius alexandrinus) and Posidonia meadows (Posidonia oceanica), both sensitive to human frequentation. To achieve this, we used two types of geolocated mobile phone information from the STRAVA platform: mapped paths and roads number of visitors at hourly precisions and a sporting activities heatmap representative of a wider period, together with species ecological information and complementary human frequentation data. The final, monthly risk maps identified the areas for Kentish plover with null, low, moderate, high, very high risk attributed to different aspects of the breeding biology of the species, nests, nestlings, and adults. The risk thresholds for nests are lower than for nestlings and adults, thought nestlings were generally less sensitive to human frequentation than adults. Visitors number ranges between 250 and 700 approximately suppose a moderate risk for the three assessed periods, and more than 1200 visitors appeared to prevent the nesting of the species completely. The final risk maps for Posidonia meadows determine the areas with low, moderate, hight and very high risk for human marine activities. Human frequentation values in this case study are scaled between 0 and 1, the results shows that values above 0.1 imply a high risk for the species. Both types of information can be used to target concrete, spatially explicit actions to minimize the risk caused by human frequentation. Furthermore, the first case study would allow to adapt the target actions to the species breeding phenology. The proposed risk assessment workflow is flexible and may be adjusted to match the available information and eventually could be adapted to other conservation objectives arising from different threats. In addition, data gathered from mobile mobility applications show great potential to accurately identify human frequentation, both spatially and temporally.