Small mammal cycles have been studied for 100 years, but the field still lacks consensus on their underlaying causes. Time-series analyses are a key approach to the study of cycles, with monitoring methods arguably limiting the understanding that is possible to gain. During the last decade, camera traps have been tested and implemented as a method for long-term monitoring, with the potential for new avenues. Here, we identify key aspects of camera trapping for future research; i) the possibility to provide data at a temporal scale that matches the fast life-histories of small mammals, ii) the indiscriminatory monitoring of the entire small mammal community, iii) the possibility to match population dynamics data with simultaneously collected data on climatic events, and iv) the potential for spatially spread monitoring designs enabling research on large-scale spatial aspects of population dynamics. We further highlight necessary developments, namely i) developing automatic image annotation models with species-level detection, ii) advancing the methodology of calculating abundance estimates from unidentified individuals, and iii) finding the adequate analytical tools to analyse high-resolution time-series. In summary, camera trapping methodology has the potential to expand the limits of achievable knowledge, but focused, collaborative research on key methodological challenges is still needed.
Soininen et al. (2026) studied this question.
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