Skip to main content
SLU publication database (SLUpub)

Research article2020Peer reviewedOpen access

The Mostela: an adjusted camera trapping device as a promising non-invasive tool to study and monitor small mustelids

Mos, Jeroen; Hofmeester, Tim Ragnvald


In spite of their potential important role in shaping small mammal population dynamics, weasel (Mustela nivalis) and stoat (Mustela erminea) are understudied due to the difficulty of detecting these species. Furthermore, their conservation status in many countries is unknown due to lack of monitoring techniques. There is thus an important need for a method to detect these small mustelids. In this study, we tested the efficiency of a recently developed camera trapping device, the Mostela, as a new technique to detect mustelids in a study area near Dieren, the Netherlands. We placed Mostelas in linear landscape features, and other microhabitats thought to be frequently visited by weasels, from March to October 2017 and February to October 2018. We tested for yearly and monthly differences in site use and detectability, as well as the effect of entrance tube size, using an occupancy modelling framework. We found large seasonal differences in site use and detectability of weasels with the highest site use in June to October and highest detection probability in August and September. Detection probability was approximately two times higher for Mostelas with a 10-cm entrance tube compared with 8-cm. Furthermore, we were able to estimate activity patterns based on the time of detection, identify the sex in most detections (69.5%), and distinguish several individuals. Concluding, the Mostela seems promising as a non-invasive monitoring tool to study the occurrence and ecology of small mustelids. Further development of individual recognition from images would enable using the Mostela for density estimates applying capture-recapture models.


Mustelidae; Wildlife monitoring; Bayesian occupancy model; Hierarchical analysis; Trail camera; Camera trap

Published in

Mammal Research
2020, Volume: 65, number: 4, pages: 843-853 Publisher: SPRINGER HEIDELBERG