The California red-legged frog, once abundant in California, is now threatened due to habitat loss, overharvesting, and invasive species. Conservationists have translocated a population from northwestern Mexico to California, but monitoring their growth presents challenges. The frogs produce a distinctive low-pitched, creaky mating call, difficult to distinguish from other nighttime sounds. By employing machine learning models, scientists can efficiently analyze thousands of hours of audio recordings to identify these calls, ultimately facilitating successful conservation and future translocations of the species.
To monitor the California red-legged frog population's growth, conservationists translocated a group of these frogs and now utilize their distinctive mating call for tracking.
The California red-legged frog's mating call is low-pitched and creaky, making it distinct, yet challenging to listen for amid various nighttime sounds in Southern California.
Machine learning models assist scientists in analyzing thousands of hours of recordings to effectively identify California red-legged frog calls, aiding conservation efforts significantly.
The use of AI in monitoring these frogs is saving time and money for conservationists, allowing them to focus on translocating more frogs in the future.
#california-red-legged-frog #conservation #ai-in-wildlife-monitoring #endangered-species #habitat-loss
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