Fisheries management decisions are often based on population models. However, those models need quality data to be effective. It's that caliber and volume of data that is lacking in fisheries science, according to Milo Adkison, an associate professor in the School of Fisheries and Ocean Sciences at the University of Alaska Fairbanks.
"Many fisheries scientists spend a lot of time and effort doing complicated analyses using complex models of their data," said Adkison. "This effort might be better spent collecting more and better data."
Adkison is one of several scientists who spoke during a session on improving fishery sustainability Feb. 19 at the American Association for the Advancement of Science annual meeting, which begins today in San Francisco. The session, moderated by UAF fisheries professor Terrance Quinn, focused on whether advances in science and technology can produce a spectrum of sustainable fisheries and minimize environmental degradation within an ecosystem.
Adkison's presentation centered on why collecting data is important to accurately assess the health and population of various fisheries. His presentation is called "Model Complexity vs. Data Quality: Are Our Models Too Complex?" The primary limitation in fisheries management decisions is the absence of quality data, Adkison says. He says that scientists and fishery managers would be better served with simpler modeling analyses and improved data.
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