Estimating roe deer density using motion‐sensitive cameras in Switzerland. Issue 8 (2nd September 2022)

• Record Type: Journal Article
• Authors: Hinojo, Amael; Christe, Philippe; Moreno, Inès; Hofmeister, Robin J.; Dandliker, Gottlieb; Zimmermann, Fridolin
• Is Part Of: Journal of wildlife management. Volume 86:Issue 8(2022)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2022-09-02
• Subjects: Capreolus capreolus -- density estimation -- motion‐sensitive cameras -- photo‐identification -- sex ratio estimate -- spatially explicit capture‐recapture models -- sub‐sampling; Wildlife management -- Periodicals; Zoology -- Periodicals; 333.954
• DOI: 10.1002/jwmg.22307
• Languages: English
• ISSNs: 0022-541X

Abstract

Abstract: Wildlife conservation and management need accurate methods for population survey and monitoring. Absolute counts of roe deer populations ( Capreolus capreolus ) are not possible, but the rapid advancement of motion‐sensitive camera technologies and new analytical approaches might potentially lead to more precise estimates at lower costs compared to traditional survey methods. We applied spatially explicit photographic capture–recapture models (SCR) in the Lake Geneva basin, Switzerland, from 25 April to 20 September 2018 to estimate roe deer densities in a pilot survey. We investigated the effect of survey duration and camera density on male roe deer density estimates to select the sampling design that produced density estimates with sufficient accuracy and precision at lower costs (i.e., material, fieldwork, data processing, and analyses). Males could be identified based on their antlers, which allowed us to apply SCR to estimate their density. Because females could not be identified individually, we inferred the overall roe deer density (adult and sub‐adult roe deer) based on the sex ratio estimated from motion‐sensitive camera photos. According to the results of sub‐sampling simulations and by taking into account the financial costs associated with fieldwork and analyses, we conclude that 20 motion‐sensitive cameras set over 20 nights (i.e., the 20/20 method) is a good compromise to provide reliable estimates of male roe deer density. Furthermore, studies estimating overall roe deer density using SCR and sex ratio estimates should be conducted from mid‐August to the end of October just after rutting season and the peak of yearling dispersal, when the movement rates of males and females, and hence their detection probabilities, are similar and when males are still carrying their antlers. This approach was successfully applied in 4 selected study areas with contrasting roe deer management regimes, resulting in overall roe deer density estimates ranging from 3.9 ± 1.3 (SE) deer/km 2 forest to 22.5 ± 6.1 deer/km 2 forest. Our study provides a valuable and cost‐effective approach using photographic SCR methodology and sex ratio information to calculate roe deer density estimates that can be used in management measures such as defining hunting quotas. Abstract : We conducted a pilot survey to investigate the effect of survey duration and motion‐sensitive camera density on male roe deer density estimates in spatially explicit capture‐recapture (SCR) models to select the least costly sampling design that produces density estimates with sufficient accuracy and precision. Subsequently, we applied this design in selected study areas with contrasting roe deer management regimes to estimate overall roe deer densities based on SCR and sex ratio information resulting from camera photographs. Taken together our study provides a valuable and cost‐efficient approach for roe deer density estimates by means of photographic SCR methodology and sex ratio estimate allowing a better management of roe deer populations.