Preprints
https://doi.org/10.5194/bg-2022-159
https://doi.org/10.5194/bg-2022-159
 
27 Jul 2022
27 Jul 2022
Status: this preprint is currently under review for the journal BG.

Physical parameters beneficial for grouping of western barbastelle bats into clusters during hibernation

Grzegorz Kłys1, Zbigniew Ziembik2, and Joanna Makuchowska-Fryc2 Grzegorz Kłys et al.
  • 1Institute of Biology. University of Opole. Oleska Street 22. 45-052 Opole. Poland
  • 2Institute of Environmental Engineering and Biotechnology. University of Opole Kardynała B. KominkaStreet 6. 6a. 45-032 Opole. Poland

Abstract. Social hibernation of animals is one of the most important physiological and ecological behaviours. The purpose of the study was the investigation of the influence of the roostsite climate parameters: temperature (T), humidity (Rh) and air flow velocity (v) on the clustering of the Barbastella barbastellus (western barbastelle) during hibernation. The research was carried out in the underground systems of Poland (Central Europe) over a period of 6 years. The range of air parameters changes ranged for T from 6.0 to 12.4 °C, for Rh from 56.4 to 91.8 % and for v from 0.01 to 1.17 m/s. The quantile linear regression method was used for the statistical analysis of the results. The study indicated that the increase in the number of individuals in the hibernaculum occurs with an increase in the product (correlation result) T and v, while a decrease in the size of the group occurs with an increase in the products T and Rh, v and Rh as well as T, v and Rh.

Grzegorz Kłys et al.

Status: open (until 07 Sep 2022)

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Grzegorz Kłys et al.

Grzegorz Kłys et al.

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Short summary
Social hibernation of animals is one of the most important physiological and ecological behaviours. The purpose of the study was the investigation of the influence of the roostsite climate parameters: temperature (T), humidity (Rh) and air flow velocity (v) on the clustering of the Barbastella barbastellus (western barbastelle) during hibernation. The quantile linear regression method was used for the statistical analysis of the results.
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