Arachnids, it turns out, are natural-born dancers. Over millions of years of evolution, many spider species have developed intricate footwork to convey messages ranging from courtship rituals to territorial disputes and hunting strategies. Traditionally, researchers have relied on laser vibrometers in laboratory settings to observe these movements. However, the high cost and limited field deployment capabilities of such systems have posed significant challenges.

Enter Noori Choi, a PhD student at the University of Nebraska-Lincoln, who set out to address this longstanding issue. Choi devised a novel solution by combining an array of inexpensive contact microphones with a machine learning program for sound processing. Venturing into the forests of north Mississippi, Choi conducted field tests to capture spiders’ elusive movements across woodland substrates.

Published in Communications Biology, Choi’s results represent a pioneering approach to collecting data on spiders’ movements, a task notoriously difficult due to the subtlety of vibrations. Over two sweltering summer months, Choi strategically placed 25 microphones and pitfall traps across 1,000-square-foot sections of forest floor, yielding a wealth of data encompassing over 39,000 hours, including more than 17,000 series of vibrations.

Yet, amidst the cacophony of forest sounds—from buzzing insects to chirping birds and human-made disturbances—filtering out the desired arachnid signals posed a formidable challenge. Choi’s innovative machine learning program proved instrumental in isolating vibrations from three wolf spider species: Schizocosa stridulans, S. uetzi, and S. duplex.

The analysis unveiled intriguing insights into arachnid behaviors, including a nuanced understanding of communication dynamics among the wolf spider species. Choi discovered an overlap in acoustic frequency and signaling space between S. stridulans and S. uetzi, suggesting a strategic allocation of signaling locations atop leaf litter versus pine debris.

Moreover, Choi’s findings shed light on how wolf spiders adapt their communication strategies based on proximity to conspecifics and interspecies interactions. Notably, S. stridulans adjusted their courtship dances when encountering same-species males or neighboring S. uetzi, highlighting the spiders’ sophisticated social dynamics.

Beyond enriching our understanding of spider behavior, Choi’s innovative methodology holds promise for ecosystem monitoring. By providing a non-invasive and highly effective means of tracking spider populations, it offers a valuable tool for assessing ecosystem health and resilience.

In the words of Choi, now a postdoctoral researcher at Germany’s Max Planck Institute of Animal Behavior, “Arthropods play a crucial role in ecosystem functioning, but monitoring changes in arthropod populations remains a challenge. With this new approach, we have the potential to revolutionize our ability to observe and understand spider behavior, paving the way for comprehensive ecosystem monitoring.”

By Impact Lab