hilo-bird-study

Two ʻamakihi, a common honeycreeper, singing in the forest. UH Hilo ecologists have created an algorithm making automatic detection of particular bird songs much faster, more efficient and highly accurate. The researchers used the algorithm to confirm the existence of ʻamakihi in certain areas where species confirmation was previously unknown. Photo by Mark Kimura

Researchers at the bioacoustics lab at the University of Hawaiʻi at Hilo are quickly making great strides in advancing the field of ecology.

The lab was established last year by Patrick Hart, professor of biology, along with UH Hilo colleagues Donald Price, also a professor of biology, and Adam Pack, an associate professor of psychology who specializes in marine mammal behavior. Already the research and technology being developed at the lab are making a big impact, according to UH.

“We’re using sound in lots of different aspects of ecology,” explains Hart about the mission behind the lab and the research being conducted there. “We’re trying to use sound to better understand the distribution and abundance of animals and how the richness of their vocal repertoire changes with population size and across the landscape.”

The lab goes by the Hawaiian name LOHE, which means, “to perceive with the ear” and is an acronym for Listening Observatory for Hawaiian Ecosystems. The facility is made possible through a Centers of Research Excellence in Science and Technology grant awarded by the National Science Foundation and is currently home to several research projects.

A New and Innovative Algorithm

Esther Sebastián-González (with binoculars) and Ann Tanimoto record bird songs in the forest above Hilo. Photo courtesy of LOHE

Esther Sebastián-González (with binoculars) and Ann Tanimoto record bird songs in the forest above Hilo. Photo courtesy of LOHE

A new algorithm developed by a researcher at the LOHE lab — to identify the song of specific bird species — boasts efficiency and limitless potential for science.

A recent study undertaken by a research team at the lab, “Bioacoustics for Species Management: Two Case Studies with a Hawaiian Forest Bird” — published in the journal Ecology and Evolution — used the new algorithm to automatically detect native ʻamakihi bird songs out of the cacophony of sounds in the forest.