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. 2020 Oct 21;10(1):17886.
doi: 10.1038/s41598-020-74933-w.

Long-term capture and handling effects on body condition, reproduction and survival in a semi-aquatic mammal

Affiliations

Long-term capture and handling effects on body condition, reproduction and survival in a semi-aquatic mammal

Rasmus M Mortensen et al. Sci Rep. .

Abstract

In long-term individual-based field studies, several parameters need to be assessed repeatedly to fully understand the potential fitness effects on individuals. Often studies only evaluate capture stress that appears in the immediate weeks or breeding season and even long-term studies fail to evaluate the long-term effects of their capture procedures. We investigated effects of long-term repeated capture and handling of individuals in a large semi-aquatic rodent using more than 20 years of monitoring data from a beaver population in Norway. To investigate the effects, we corrected for ecological factors and analysed the importance of total capture and handling events, years of monitoring and deployment of telemetry devices on measures related to body condition, reproduction and survival of individual beavers. Body mass of dominant individuals decreased considerably with number of capture events (107 g per capture), but we found no statistically clear short or long-term effects of capture and handling on survival or other body condition indices. Annual litter size decreased with increasing number of captures among older individuals. Number of captures furthermore negatively affected reproduction in the beginning of the monitoring, but the effect decreased over the years, indicating habituation to repeated capture and handling. By assessing potential impacts on several fitness-related parameters at multiple times, we can secure the welfare of wild animal populations when planning and executing future conservation studies as well as ensure ecologically reliable research data.

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Conflict of interest statement

The authors declare no competing interests.

Figures

Figure 1
Figure 1
The predicted relationship ± 95% confidence interval between age, sex and tail fat index (a) and age, sex, season and tail fat index (b) in a Eurasian beaver population in south-eastern Norway between 1998 and 2018.
Figure 2
Figure 2
The predicted relationship ± 95% confidence interval between age, territory size and body mass in young beavers (a), between season, sex and body mass in adult beavers (b), between age, and body mass in adult beavers (c) and between number of captures, social status and body mass in adult beavers (d) in a Eurasian beaver population in south-eastern Norway between 1998 and 2018.
Figure 3
Figure 3
The predicted relationship ± 95% confidence interval between age, territory size and body length in young beavers (a) and between age, season and body length in adult beavers (b) in a Eurasian beaver population in south-eastern Norway between 1998 and 2018.
Figure 4
Figure 4
The predicted relationship ± 95% confidence interval between number of captures, years of monitoring and probability of reproducing (a) and annual litter size (b), and between number of captures, age and probability of reproducing (c) in a Eurasian beaver population in south-eastern Norway between 1998 and 2018. Points represent the actual observations with small random variation for better visualisation. Darker colours increase with (a,b) increasing years of monitoring and (c) increasing number of captures.
Figure 5
Figure 5
The predicted relationship ± 95% confidence interval between age, social status and survival probability (a) and between family group size and survival probability (b) in a Eurasian beaver population in south-eastern Norway between 1998 and 2018. Points represent the actual observations with small random variation for better visualisation.
Figure 6
Figure 6
The predicted relationship ± 95% confidence interval between age (a), family group size (b) and probability of keeping dominance in a Eurasian beaver population in south-eastern Norway between 1998 and 2018. Points represent the actual observations with small random variation for better visualisation.

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