A team of experts in artificial intelligence and animal ecology have put forward a new, cross-disciplinary approach intended to enhance research on wildlife species and make more effective use of the vast amounts of data now being collected thanks to new technology. Their study appears in Nature Communications. The field of animal ecology has entered the era of big data and the Internet of Things. Unprecedented amounts of data are now being collected on wildlife populations, thanks to sophisticated technology such as satellites, drones and terrestrial devices like automatic cameras and sensors placed on animals or in their surroundings. These data have become so easy to acquire and share that they have shortened distances and time requirements for researchers while minimizing the disrupting presence of humans in natural habitats.

Inexpensive and accessible sensors are accelerating data acquisition in animal ecology. These technologies hold great potential for large-scale ecological understanding, but are limited by current processing approaches which inefficiently distill data into relevant information. We argue that animal ecologists can capitalize on large datasets generated by modern sensors by combining machine learning approaches with domain knowledge. Incorporating machine learning into ecological workflows could improve inputs for ecological models and lead to integrated hybrid modeling tools. This approach will require close interdisciplinary collaboration to ensure the quality of novel approaches and train a new generation of data scientists in ecology and conservation. Animal ecologists are increasingly limited by constraints in data processing. Here, Tuia and colleagues discuss how collaboration between ecologists and data scientists can harness machine learning to capitalize on the data generated from technological advances and lead to novel modeling approaches.

A team of experts in artificial intelligence and animal ecology has put forth a new, cross-disciplinary approach intended to enhance research on wildlife species and make more effective use of the vast amounts of data now being collected thanks to new technology, as announced in a press release by École Polytechnique Fédérale de Lausanne (EPFL), a Swiss technology institute, which contributed to the study. The results were published in Nature Communications. The field of animal ecology has entered the era of big data and the Internet of Things. Unprecedented amounts of data are now being collected on wildlife populations, thanks to sophisticated technology such as satellites, drones and terrestrial devices like automatic cameras and sensors placed on animals or in their surroundings. These data have become so easy to acquire and share that they have shortened distances and time requirements for researchers while minimizing the disrupting presence of humans in natural habitats.