Current nest box designs may not be optimal for the larger forest dormice: Pre‐hibernation increase in body mass might lead to sampling bias in ecological data

Autor: Hesamaddin Farhadi
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Ecology and Evolution, Vol 11, Iss 24, Pp 18460-18466 (2021)
Druh dokumentu: article
ISSN: 2045-7758
DOI: 10.1002/ece3.8437
Popis: Abstract Biologists commonly use nest boxes to study small arboreal mammals, including the forest dormouse (Dryomys nitedula). Hibernating dormouse species often experience pronounced seasonal variations in body mass, which might lead to sampling biases if it is not taken into account when designing nest boxes. In my study of the forest dormouse, I noticed that the entrance hole of nest boxes had been gnawed. I hypothesized that this behavior was exhibited by the individual dormice of higher body mass, who were unable to pass through the entrance holes. To test my hypothesis, I categorized the individual dormice present inside nest boxes based on their body mass and then compared the seasonal body mass dynamics with the timing of the gnawing behavior. I also compared nest box occupancy by the forest dormouse before and after the gnawing behavior. Interestingly, I found that the gnawing behavior was displayed exclusively when part of the dormouse population increased considerably in body mass, which supports my hypothesis. Additionally, nest box occupancy decreased significantly from 20% before to 4.6% after the gnawing behavior. I suggest that researchers include nest boxes with entrance holes larger than 4 cm in future studies of the forest dormouse to prevent the possible exclusion of the conspecifics that have higher body mass before hibernation. This type of sampling bias might also concern studies of other species, such as the fat dormouse, that similarly show pronounced seasonal variations in body mass. I recommend that biologists consider the seasonal body mass dynamics of the target species when designing nest boxes to minimize bias in ecological data and improve management actions.
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