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For decades, researchers have employed sound to study the biology of wildlife, with the aim to better understand their ecology and behaviour. By utilizing on‐animal recorders to capture audio from freely moving animals, scientists can decipher the vocalizations and glean insights into their behaviour and ecosystem dynamics through advanced signal processing. However, the laborious task of sorting through extensive audio recordings has been a major bottleneck. To expedite this process, researchers have turned to machine learning techniques, specifically neural networks, to streamline the analysis of data. Nevertheless, much of the existing research has focused predominantly on stationary recording devices, overlooking the potential benefits of employing on‐animal recorders in conjunction with machine learning. To showcase the synergy of on‐animal recorders and machine learning, we conducted a study at the Kutuharju research station in Kaamanen, Finland, where the vocalizations of rutting reindeer were recorded during their mating season. By attaching recorders to seven male reindeer during the rutting periods of 2019 and 2020, we trained convolutional neural networks to distinguish reindeer grunts with a 95% accuracy rate. This high level of accuracy allowed us to examine the reindeers' grunting behaviour, revealing patterns indicating that older, heavier males vocalized more compared to their younger, lighter counterparts. The success of this study underscores the potential of on‐animal acoustic recorders coupled with machine learning techniques as powerful tools for wildlife research, hinting at their broader applications with further advancement and optimization. [ABSTRACT FROM AUTHOR]

In polygynous systems, such as that exhibited by reindeer Rangifer tarandus , mate choice can be difficult to disentangle from male intrasexual competition because male behavior may constrain female choice. Multiple mating may provide an avenue for female mate choice, though it is difficult to identify using behavioral estimators alone. Molecular techniques address this issue by affording ecologists an opportunity to reassess mating systems from a genetic perspective. We assessed the frequency and possible explanations for multiple mating in reindeer using a genetic approach to determine the success of observed copulations in a semi-domesticated herd in Kaamanen, Finland. Behavioral and genetic data were synthesized with population characteristics over a 7-year period to test the hypothesis that, if present, polyandry in reindeer is driven by sexual harassment from sub-dominant males. We observed multiple mating in 42% of females, with as many as 60% exhibiting multiple mating in certain years. We found no evidence that multiple mating resulted from sexual harassment by sub-dominant males, suggesting that it is likely a deliberate strategy among females. Conversion rate of copulations into paternities varied with male size, with smaller males more likely to experience mismatch than larger males. Female preference for larger males persisted despite the occurrence of multiple mating, possibly suggesting a mechanism for cryptic post-copulatory selection. We suggest further research to delineate the possible influence of cryptic post-copulatory selection and multiple mating to defend against infertility in exhausted males. [ABSTRACT FROM AUTHOR]