Tiny sensor used to track the migratory patterns of monarch butterflies
Date:
May 2, 2022
Source:
University of Pittsburgh
Summary:
Scientists have developed a tracking system that can be attached
to monarch butterflies and transmit data about their location all
throughout their three-month migratory journey south.
FULL STORY ========================================================================== Millions of monarch butterflies migrate each fall to a specific cluster
of mountain peaks in central Mexico. How exactly they navigate to their
winter home, and the way they choose their path, is a topic of great
interest to scientists -- especially as climate change redirects their
chosen path.
========================================================================== Inhee Lee, assistant professor of electrical and computer engineering at
the University of Pittsburgh, is part of a team developing a tracking
system that could be attached to monarch butterflies and transmit data
about their location all throughout the three month journey south. A
paper detailing these findings recently won the Best Paper Award at the
MobiCom 2021 Conference.
"Tracking animal migration is a critical ecosystem indicator," said Lee.
"Migrators travel long distances across entire continents, and it
can give us unprecedented insight into their migratory paths, how the environment around them is changing, and how species interactions are
impacted by changing movements and distributions." Previously, only
larger animal migrators can be tracked for significant portions of their migration. Insect migrators, however, make up an enormous portion of the
total migrators across the world. To track them, researchers have created
a new wireless sensing platform called mSAIL, specifically designed for
monarch migration.
The tiny, 62 mg, 8x8x2.6 mm chip is attached to the butterfly's
back and can simultaneously measure light intensity and temperature,
wirelessly communicating that information back to researchers once
the butterflies reach their destination. The system will use a deep learning-based localization algorithm to reconstruct the butterfly's
migration trajectory after it has made the journey.
To test the potential of mSAIL, researchers attached the system to a
live monarch butterfly in a botanical garden. The chip was glued to the butterfly; it had no issue flying, opening and closing its wings, or
engaging in any other normal butterfly behaviors with the chip in place.
mSAIL is an extension of work that Lee completed while an assistant
research scientist at the University of Michigan. mSAIL integrates
previously developed integrated circuits within a 3D-stacked form factor
and demonstrates, for the first time, the feasibility of individual
butterfly localization and tracking using the novel embedded system.
The next step of the project is to mass produce over 100 mSAIL sensors
that can reliably operate during the three-month monarch migration
period. The researchers will release the mSAIL-equipped butterflies at
various locations in the U.S. and will check in with the sensors at the butterflies' well- established resting spots -- such as in the western
Lake Erie archipelago - - and at the final overwintering site in central Mexico. Eventually, the team hopes to add an air pressure sensor to
mSAIL, which will allow it to determine altitude and more accurately
assess the butterflies' path.
The paper, "mSAIL: Milligram-Scale Multi-Modal Sensor Platform for Monarch Butterfly Migration Tracking," was led by Lee and Roger Hsiao, who was
an undergraduate student at the University of Michigan and currently a
graduate student at UC Berkeley. Additional co-authors are from Pitt, University of Michigan, the University of Nebraska and the University
of Delaware.
========================================================================== Story Source: Materials provided by University_of_Pittsburgh. Original
written by Maggie Lindenberg. Note: Content may be edited for style
and length.
==========================================================================
Link to news story:
https://www.sciencedaily.com/releases/2022/05/220502120508.htm
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