Towards Sustainable Fisheries: State Space Assessment Models for Complex Fisheries and Biological Data

Expansive oceans cover much of the Earth’s surface and are teeming with diverse ecosystems. Humans have long seen the oceans as a source of food and around the world, more than 200 million people are employed in the fishing industry. As our appetite for fish and other seafood continues to grow, we invenitbily put more stress on these delicate ecosystems. The math behind overfishing is simple: we are taking out fish from the ocean faster than it can be replenished. Even in Canada, overfishing is a growing problem.

Fisheries have formed the backbone of the economy in many parts of Canada throughout history and currently contributes over $3 billion dollars to Canada annually. Globally, overfishing is threatening fish stocks and jobs with serious social, economic, and environmental consequences with recent assessments reporting that the general state of global fish stocks is poor and declining. Of the 4,714 fisheries assessed in 2012, only 32% remained at or above the biomass target that supports maximum sustainable yield and 68% have slipped below that critical threshold. 29% of assessed major stocks are currently overexploited or depleted. Fisheries scientists are working on innovative solutions for overfishing, which are needed now more than ever.

Fisheries scientists collect biological and fisheries data to perform stock assessments that provide resource managers with information needed to regulate fish stocks. The key goals of fisheries management are to eliminate overfishing and restore stocks that have been previously overfished. Joanna Mills Flemming, Professor of Mathematics and Statistics at Dalhousie University, along with her Collaborative Research Team (CRT) are tackling this problem by combining statistical and data science approaches to uncover new insights that can help better manage overfishing.

Currently, fisheries management uses State Space Models for stock assessment, which play an important role in the process of predicting future stock sizes. Joanna and her team are advancing these models through goodness-of-fit statistics, residual analysis, and other statistical techniques and approaches that empower fisheries management to better asses, predict and uncover solutions to overfishing in Canada and internationally. 

Assembling a Diverse Team

Addressing these problems require complex and multi-faceted solutions, which is why Joanna’s CRT is multidisciplinary and diverse. “My team is scientifically diverse. It includes statisticians, fisheries scientists and applied ecologists working in academia, industry and government across Canada and abroad,” Joanna says. This project is not only improving tools for accurate stock assessment, but also addresses the need for developing Highly Qualified Personnel (HQP) in Canada.

The Canadian Statistical Sciences Institute’s (CANSSI) CRT program is a catalyst to engage the scientific community, government and industry by bringing the statistical and data science community together to tackle difficult and important problems. “CANSSI has supported us by giving us a seat at the table. We’re able to bring our own funding and HQP to address pressing problems in multidisciplinary research environments” Joanna says. “This allows us to become effective collaborators instead of being incorrectly viewed as consultants. This makes all of the difference.”

Training HQP

One of these HQPs is William Aeberhard, who worked closely with Joanna as part of this CRT. Participating on this team allowed him to develop expertise in programming for state-of-the-art statistical software such as the R package Template Model Builder, and also develop a deeper understanding of the connection between science and society from collaborating with scientists at Fisheries and Oceans Canada. 

By being a part of this CRT, William rapidly honed a variety of important and relevant skills, from collaborating with marine biologists and fisheries scientists, to serving as an external reviewer for Fisheries and Oceans Canada’s framework assessment meetings, to developing relevant technical skills. William also found academic success, publishing two papers with various collaborators, with a third one in the works.

This CRT acted as a springboard for William, helping contribute to his success in his field. He leveraged the skills and experience from his time with Joanna’s team and is now an Assistant Professor of Statistics in the Department of Mathematical Sciences at Stevens Institute of Technology. There he is conducting research in statistics that extends current established models and methods and is involved in cross-disciplinary collaborations—such as volcanology and public health, among others—where this class of models is becoming a standard.

William is just one example of the HQP trained as part of CANSSI’s CRT program, which provides hands-on experience that accelerates the careers and personal development of HQPs. “I am applying what I learned with this CRT on a daily basis”, says William. “It was a fantastic and valuable experience to be part of this amazing CRT”.

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