Introduction to Management Strategy Evaluation (MSE): Conversations with Blue Matter Science’s Dr. Tom Carruthers

August 23, 2024

AuthorDr. Tom Carruthers
CEO, Blue Matter Science

Blue Matter Science, led by CEO Dr. Tom Carruthers, is a leading organization dedicated to advancing marine science and sustainable fisheries management. With a background in marine biology, experimental ecology, and a PhD in applied mathematics from Imperial College, Tom is also an Adjunct Professor of Fisheries Science at the University of British Columbia. His passion for problem-solving in marine science drives his current focus on developing tools that support robust fisheries management.

In this two-part blog series, we delve into the nuanced landscape of MSE with Tom, unpacking the fundamental components that render MSE indispensable in our collective pursuit of ecologically responsible and economically viable fisheries management.

Part 1: The Fundamentals and Challenges of Management Strategy Evaluation (MSE)

Introduction to MSE

HS.org:  In 50 words or less, can you explain what Management Strategy Evaluation (MSE) is and why it is an important tool in international fisheries management?

Tom:  International fishery managers are tasked with implementing a harvest strategy that meets the objectives of diverse stakeholders, often in the face of large scientific uncertainties. MSE is a computer simulation approach that tests candidate harvest strategies across various scenarios for the fishery to identify those that can robustly achieve management objectives.   

A common analogy for MSE is the testing of pilots using a flight simulator. In the MSE context, harvest strategies are the pilots being tested. Instead of flying conditions, MSE simulates a plausible range of biological, ecological, and exploitation scenarios for the fishery. Like a flight simulator, MSE can provide us with confidence that a harvest strategy (the pilot) will perform well over a wide range of conditions.  

Key Components

HS.org: What are the key components of an effective MSE process, and how do they interact to ensure the long-term sustainability of fisheries?

Tom: MSEs are pursued for various reasons, so ‘effective’ is somewhat case-specific. In the case of Atlantic bluefin tuna, there were difficulties in establishing a scientifically defensible assessment of the resource for use in decision-making. Essentially, there were many hypotheses for biology, ecology, and behavior that were similar to the data. For Bluefin, MSE was all about establishing a simple harvest strategy that was demonstrated to work robustly across all those hypotheses. The challenge in the South African sardine and anchovy fishery was establishing a harvest strategy that could allow for fishing without serious overexploitation of either species. In the case of the Bay of Fundy herring, MSE was used as a sort of ‘due diligence’ for a harvest strategy that had already been adopted and was in use. This might sound like a rather pedantic start of an answer to your question, but it goes to a point: arguably, the most important part of an MSE process is identifying a clear problem statement. Why MSE in this context?

There are three main parts to an MSE that interact in the adoption of a sustainable, robust harvest strategy:

• 1) Performance indicators
• 2) System uncertainties
• 3) Harvest strategies

Performance indicators are the basis for the scoring and comparison of harvest strategies. They are the lens through which all participants will view results. The performance aims of managers will be revealed when a harvest strategy is adopted. An effective MSE is one built around participation and communication. It should include a comprehensive consultation process with a range of stakeholders to ensure that their perspectives and values are communicated in results. Any legal requirements for fishery managers should also be expressed as performance indicators. Once established, the set of performance indicators provides a transparent account of harvest strategy strengths and weaknesses. It allows managers to explicitly consider trade-offs between, for example, extraction and conservation objectives. If the performance indicators part is done right, when a harvest strategy is adopted, it is clear why it was selected.

An effective MSE is one where managers have confidence in the adopted harvest strategy. That confidence arises from testing candidate harvest strategies against a wide range of plausible uncertainties (hypotheses) in current and future fishery conditions. Although science is usually the primary basis for developing these hypotheses, an effective MSE process includes stakeholder knowledge and experience, allowing a range of perspectives on the fishery to inform the selection of an appropriate harvest strategy.

Now that we have established how to score them and the conditions by which they will be tested, it is vital to focus on the harvest strategies – the pilots in the flight simulator analogy. An effective MSE is an open process that allows for testing a diverse range of harvest strategies developed by multiple development teams. These teams engage in a collaborative competition where harvest strategies are compared and refined. This diversity, friendly competition, and ingenuity process extracts every possible ounce of performance from a harvest strategy. Within the constraints specified by managers, anything goes. For me, it’s the most fun part of MSE!

If I’ve answered this correctly, it should be clear why MSE is such a powerful tool in establishing a long-term sustainable harvest strategy for a fishery. MSE is 1) inclusive, open, and transparent. 2) accounts for economic and biological definitions of sustainability in performance indicators, and 3) selects a harvest strategy that has been shown to provide sustainability across a range of hypotheses for the system. 

Challenges and Solutions

HS.Org: Despite the proven benefits of harvest strategies and MSE, widespread adoption has been slow in some areas. What are the primary barriers to the broader adoption of these management approaches, and how can they be addressed?

Tom: Technical overhead. Previously, a serious impediment to MSE adoption was developing all the code to do the simulation work. Today, MSE packages like FLR and OpenMSE take much of this burden away from the process, allowing it to refocus on performance indicators, uncertainties, and harvest strategy design – the things that matter. However, the false perception of MSE as an expensive, burdensome, complicated techno-rats-nest persists. A big part of our collaboration with www.harveststrategies.org and The Ocean Foundation has been about showing people that this is no longer the case. We have been to management settings with OpenMSE, where managers and stakeholders were very organized, and harvest strategies were adopted in less than six months. A lot of managers and scientists don’t realize what is now possible.  

Getting stuck in ‘Assessment mode’. The conventional approach to fisheries management is to develop a ‘best’ model of the fishery that is empirically validated by fitting to data and then used in management decision-making. Yes, you can look at alternative models and assumptions via so-called sensitivity analyses, but fundamentally the focus of stock assessment modelling is scientific veracity. That is not the focus of MSE, which is all about harvest strategy robustness. ‘Assessment mode’ is a condition that is a serious threat to the health of any MSE process. Scientists can get bogged down in the details of the models and data, which may affect perceptions of the stock but are often inconsequential to harvest strategy performance. Managers want to see stock assessments in their harvest strategies instead of simpler approaches that perform similarly. MSE projections are viewed as forecasts, not scenarios, for testing harvest strategies and so on. As is the case for many MSE problems, the solution is to do a thorough introduction to MSE and then get a demo MSE framework up and running as soon as possible so that all participants can see it in action and hopefully interact with it.

Indecision. MSE necessarily requires many decisions to be made, including who to include, when to hold meetings, when to draw a line on developing hypotheses, what performance indicators, what diagnostics, and what types of harvest strategies. 

The list is enormous. This can drag out an MSE into an arduous process where momentum is lost to a point where new data and hypotheses emerge, and the process is stalled in a constant update loop. The best way to solve this is to employ an experienced chair of the process who can develop an MSE roadmap and maintain discipline on timelines. 

HS.Org: How do you balance short-term economic interests with long-term fishery goals in MSE?

Tom: For most MSEs, the principal performance trade-off among harvest strategies is between what you take and what is left over in the water. Managers must navigate this trade-off between catches in the short term and biomass/catch outcomes over the longer term based on their established objectives and legal requirements. As a mere analyst, this is above my pay grade! Things are not as clear-cut as you might expect, however. I’m currently working on a harvest strategy for an invasive species.

Stay tuned for Part 2: Advanced Perspectives and Future Directions in Management Strategy Evaluation (MSE), where we dive deeper into the challenges, technological advances, and future directions of Management Strategy Evaluation in international fisheries management. Don’t miss the opportunity to learn more about how these modern approaches are shaping the sustainable future of our global ocean.