Our 2 Cents

It Takes Two: Economics + Ecology Can Improve Fishery Outcomes

Wednesday, April 3, 2019
ByDan Ovando

Dan Ovando, emLab collaborator, is a postdoctoral scholar at the University of Washington. 

Various forms of rights-based fisheries management (RBFM) have been used across the globe for centuries, but the majority of the world's fisheries have historically existed in a state of open access, delivering sub-optimal outcomes for ecosystems and people. Over the last few decades though, the widespread implementation of market-based solutions has fundamentally transformed the way we manage global fisheries. More and more fisheries have begun implementing RBFM strategies--including individual transferable quotas (ITQs), cooperatives, and territorial user right fisheries (TURFs)--and fish caught in rights-based fisheries now account for about 22% of global landings. 

Market-based solutions rely on incentives to produce improved and equitable outcomes for fisheries, but their sustained success depends on our ability to effectively monitor the health of global fish stocks. Even the most well-designed and well-managed ITQ fishery might fail if the science underpinning its quotas falls short. 

Typical inputs for stock assessments include a close-to-complete catch history, an index of relative abundance, such as catch-per-unit-effort (CPUE), and information on the age or length composition of the catch. These intensive data requirements are a major hurdle for unassessed fisheries interested in getting a better understanding of their resources. For example, if catch records have not been kept in the past, it can be very difficult, if not impossible, to accurately recreate them. The same is true for recreating length compositions. And even if a fishery begins collecting data today, it may still take decades to gather enough catch and CPUE data to perform a reliable assessment. Given the challenges associated with traditional stock assessments, we must bring greater innovation to stock assessments, and develop accurate ways for communities with limited data and resources to effectively monitor and learn something about the health of their fisheries. 

This is where my research comes in. With support from the National Marine Fisheries Service- Sea Grant Population and Ecosystem Dynamics Fellowship, my team and I have been testing new ways to leverage economic data--information that is commonly available, even in data-limited fishery contexts--to conduct stock assessments. The benefits of doing so are two-fold. First, these data serve as critical inputs for stock assessments, and second, using fishers' knowledge on the economic history of their profession provides a tangible way to bring their valuable expertise into the assessment process.

Our team's work was inspired by recent experiences in Peru, where conversations with local stakeholders revealed a wealth of information about the ways fishing practices and fish prices have responded to skyrocketing seafood demand from local restaurants. Though this kind of information has no home in standard stock assessment methods, we have been able to demonstrate how pairing this kind of economic data with more commonly-collected biological information (like fish sizes) can help reduce uncertainty and bias in estimates of fishing mortality rates. 

Using this principal at a much larger scale, our team is also exploring what the behavioral patterns revealed by Global Fishing Watch can tell us about the health of stocks being targeted by industrial fleets. Global Fishing Watch provides near-real time data on fishing behavior all around the globe. We've paired data from Global Fishing Watch with estimates of fish densities to train models that use fishing effort to predict fish abundance. We found that fishing behavior can indeed predict fish abundance, but that these relationships are highly location-specific. 

Tools like Global Fishing Watch are facilitating new learning on how we can use information about fishing behavior to inform fisheries management--both in terms of conducting assessments and designing policy. Integrating economics and ecology shows how new data like GFW can be used for enforcement and for advancing our understanding of stock status, potentially improving buy-in for transparency by fishing fleets. 

Infusing scientific ideas and economic insights into fisheries assessment can help reduce uncertainty and empower communities to effectively manage their marine resources. Unfortunately, research agendas are often separated into economic and ecological questions, limiting our ability to jointly leverage insights from both fields to generate new knowledge and improve management outcomes. Thus, developing research programs--like emLab at UC Santa Barbara--that seek to collect and leverage interdisciplinary data are critical for making research more cost effective, inclusive, and impactful. 

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