Consistency of spatio‐temporal patterns of avian migration across the Swiss lowlands

Abstract

AbstractEach year, billions of birds migrate across the continents by day and night through airspaces increasingly altered by human activity, resulting in the deaths of millions of birds every year through collisions with man‐made structures. To reduce these negative impacts on wildlife, forecasts of high migration intensities are needed to apply mitigation actions. While existing weather radar networks offer a unique possibility to monitor and forecast bird migration at large spatial scales, forecasts at the fine spatial scale within a complex terrain, such as the mountainous Swiss landscape, require a small‐scale network of ornithological radars. Before attempting to build such a network, it is crucial to first investigate the consistency of the migratory flow across space and time. In this study, we simultaneously operated three ornithological radar systems across the Swiss lowlands to assess the spatio‐temporal consistency of diurnal and nocturnal bird movements during the spring and autumn migration season. The relative temporal course of migration intensities was generally consistent between sites during peak migration, in particular for nocturnal movements in autumn, but absolute intensities differed greatly between sites. Outside peak migration, bird movement patterns were much less consistent and, unexpectedly, some presumably non‐migratory bird activity achieved intensities close to peak migration intensities, but without spatial correlations. Only nocturnal migration intensity in autumn could be predicted with consistently high accuracy, but including parameters of atmospheric conditions in the model improved predictability of diurnal movements considerably. Predictions for spring were less reliable, probably because we missed an important part of the migration season. Our results show that reliable forecasts of bird movements within a complex terrain call for a network of year‐round bird monitoring systems, whereas accurate information of atmospheric conditions can help to limit the number of measurement points.