Tiny mammals are sending warning signs scientists can finally read

Researchers have now developed a new way to identify and monitor these animals by analyzing their footprints. The method was tested on two nearly indistinguishable species of sengi and achieved accuracy rates as high as 96 percent, offering a promising new tool for conservation science.

"We had two key motivations for undertaking this study," said Dr. Zoë Jewell of Duke University Nicholas School of the Environment, co-author of the article in Frontiers in Ecology and Evolution. "Firstly, to find a better, more ethical, and more scientifically robust way to monitor even the tiniest species, and secondly, to provide a reliable and broad metric for ecosystem integrity that can be applied routinely and regularly -- a new pulse on the planet."

Why Small Mammals Matter

Despite their size, small mammals play essential roles in ecosystems and respond quickly to environmental change. Because of this sensitivity, shifts in their populations can serve as early warning signs of ecological disruption. Monitoring them accurately, however, is difficult. Many are what scientists call cryptic species, meaning they are visually almost impossible to tell apart.

This challenge is illustrated by the two species used to test the new footprint technique: Eastern Rock sengis and Bushveld sengis. Although they appear nearly identical, they live in different habitats and face different environmental pressures.

"It's often only possible to distinguish between cryptic species using DNA, which can be slow, invasive, and costly," explained Jewell. "It's really important to know which is which, because although these species might look the same, they face different environmental threats and play different roles in the environment. For example, in our study, one of the sengis lives exclusively in rocky habitats and the other on sand, and each can act independently as an indicator in those environments."

How Footprints Reveal Species Identity

While the two sengi species look alike, their feet are not exactly the same. Subtle differences in foot shape leave distinct patterns in the tracks they make. The research team focused on capturing and analyzing these differences, training a computer model to recognize which footprints belonged to which species.

By treating footprint identification like a digital tracking problem, the scientists aimed to replace invasive and expensive monitoring methods with a faster and more practical alternative.

Fieldwork in South Africa

The researchers collected sengis from two locations in South Africa: Telperion Nature Reserve and Tswalu Kalahari Reserve. All 18 Bushveld sengis were found at Tswalu, while 19 Eastern Rock sengis were identified across both sites. Some of the Eastern Rock sengis were living very close to Bushveld sengis, a surprising result since Tswalu Kalahari Reserve lies outside the species' expected range.

This unexpected overlap underscored the importance of better monitoring tools, as species may be expanding or shifting their ranges without being detected.

The animals were captured using specially-designed traps filled with soft bedding and food, including oats, peanut butter, and Marmite -- which they find particularly delicious -- before being transferred to a footprint collection box. Inside the box, special paper and charcoal dust encouraged the sengis to walk across the surface, leaving clear tracks behind. Each animal was then released unharmed at its original capture site.

Turning Tracks Into Data

High-resolution images of the footprints were analyzed using morphometry software that measured shape and size characteristics. The researchers focused on front footprints, which consistently provided the clearest and most distinctive features. More than 100 potential measurements were initially identified.

Statistical testing was then used to determine which combination of features most effectively separated the two species.

Accuracy Without Invasive Methods

From this analysis, nine key footprint features were selected and tested against previously unseen images and sets of tracks. Across all trials, the system correctly identified the species 94 percent to 96 percent of the time.

The results show that footprint analysis can offer a simple, affordable, and non-invasive way to confirm species presence and track changes in population size and geographic range. The research team plans to expand the approach to other species by training new models with additional datasets. They also hope to compare footprint analysis with other non-invasive monitoring techniques to see how different tools can work together.

"Small mammals exist in almost every ecosystem on the planet, and our tech is flexible enough to adapt to every one," said Jewell.