The usefulness of Unmanned Aerial Vehicles (UAV) in white stork censusing

Author:

Tobółka Marcin1,Aguirre José I.2,Dylewski Łukasz1,López-García Alejandro2,Martínez Rodrigo Gimeno3,Zbyryt Adam4

Affiliation:

1. Poznań University of Life Sciences

2. Complutense University of Madrid

3. Independent Researcher

4. University of Białystok

Abstract

Abstract Long-term bird monitoring brings vital information on the effects of environmental changes on wildlife. However, covering a large area with direct observations in the field is time-consuming and economically costly. New technologies, such as Unmanned Aerial Vehicles (UAV), are effective and often noninvasive tools successfully used in bird monitoring. However, the stability of the method is essential when handling long-term data in the context of population changes. We examined the efficiency and precision of data collected by UAV and human observers within two distinct populations of the white stork Ciconia ciconia, in Poland and Spain, presenting two different nesting patterns, solitary and colonial breeding. In Polish and Spanish populations, the number of fledglings was significantly lower when recorded by human observer than by UAV, i.e. 2.21 vs 2.60, and 1.35 vs 1.55. The mean time needed to record the number of fledglings was significantly longer when using a UAV than by a human observer. The number of detected nests in colonies differed significantly between the human observer and UAV, on average 13.1 vs 7.4, respectively. The difference number of recorded nests was linked with the type of nest substrates, i.e. on trees, the error was higher than in colonies located on human-made structures. The probability of mistake by the observer was significantly lower when recording the number of fledglings in colonial white storks in Spain than in solitary nesting in Poland. Although UAVs are a helpful tool in bird monitoring, in long-term studies, they must be used with caution and awareness that obtained results might differ from those obtained previously in a long-term monitoring framework.

Publisher

Research Square Platform LLC

Reference27 articles.

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