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by Natalie Springuel
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In the last 20 years, the lobster population model used by the federal government has consistently shown that the Gulf of Maine stock is overfished. Yet during this same period, lobster landings -- and by all indications, lobster populations -- have been increasing at record rates.
"Something is inconsistent here," said Yong Chen, professor of fisheries population dynamics at the University of Maine. "And many fishermen would like a second opinion."
Chen and Carl Wilson, chief lobster biologist with the Maine Department of Marine Resources (DMR), are working on a model they hope will provide that second opinion.
The two have received a $120,000 grant from the Maine Sea Grant Program and $50,000 from the DMR to develop the new model, as well as a lobster stock assessment framework for the Gulf of Maine.
Although the grant didn't become available until February 2002, Chen and Wilson began their work in 2001 with a Maine Sea Grant development fund award of $5,200. This award allowed the two researchers to assess uncertainty associated with the F10% estimate.
That preliminary study, the results of which will soon be published in the Canadian Journal of Fisheries and Aquatic Sciences, laid the foundation for the work to come.
Study objectives
The specific objectives of the Chen-Wilson project are to:
- Evaluate and identify problems associated with the approaches currently used in the lobster stock assessment;
- Develop alternative models to describe lobster population dynamics and assess current fisheries status;
- Develop a Bayesian stock-assessment framework to assess the Maine lobster fishery;
- Develop a stochastic (involving random variations) length-based stock assessment model to describe population dynamics of the lobster;
- Evaluate the population dynamics and current status of the lobster stocks;
- Develop a decision-making framework for risk analyses of alternative management strategies and provide management advice to government agencies and fishing industry; and
- Improve the understanding, utilization, and management of the fishery.
"This new lobster model will have more realistic assumptions about lobster biology, thus leading to a better description of lobster population dynamics," Chen said.
Landings disparity
Prior to the late 1980s, Maine lobster landings had averaged 20 million pounds a year. In 2000, landings were a record 57.2 million pounds with a value of $187.7 million. That was up from 1994 when landings hit 40 million pounds.
Many studies and field observations confirm that recruitment into the fishery, total potential egg production, and stock abundance all increased in recent years.
Despite all of this, the population model used by the federal government for two decades still shows that the lobster population is overfished.
As a result, the existing model has little credibility among fishermen in Maine, and it drives much of the tension between fishermen and fisheries managers.
Monitor population
The Atlantic States Marine Fisheries Commission (ASMFC) requires states to rebuild lobster stocks so that overfishing is no longer occuring by 2008.
In Maine, where lobster management is "bottom up," fishermen are in the difficult position of having to deal with coming up with management strategies to deal with a legally overfished population even though they believe the legal definition of "overfished" is wrong.
Many believe the time has come for the development of new models that more accurately reflect what actually happens in the lobster fishery.
"It is a much more fundamental question than simply wanting a new model that disproves the claim of an overfished lobster population," said Robin Alden, former commissioner of DMR.
"The question becomes, 'What do we need to monitor in order to predict and manage the lobster population if it does begin to drop?'" she explained. "Since we don't know why the population has increased, we are not prepared to track changes that might trigger decline."
Sea sampling is conducted the Maine Department of Marine Resources (DMR) from May through November. Each of the state's seven lobster zones is sampled three times monthly. The DMR hopes to integrate information collected on lobster boats into future stock assessment work. Top photo - DMR sea sampler Glenn Nutting during a November 2001 trip in Zone B. (DMR photo) Above - Brian McLain of Pemaquid readies to liberate an oversize lobster from a 1999 sea sampling day. (Jessica Stevens photo)
F10% goal
Federal law defines an overfished lobster population "as that stock level where the estimate of egg production per recruit (EPR) is 10% or less of that in an unharvested population."
In other words, if the number of eggs produced by the average female falls to less than 10% of what that same average female would have produced with no fishing, then the fishery is considered overfished.
The fishing mortality rate that produces this situation is considered a benchmark in lobster management and is commonly referred to as F10%.
"Think of F10% as a policy goal," said Geoff White, fisheries research specialist with the Atlantic States Marine Fisheries Commission (ASMFC).
"We think we need to have egg production at 10% of the virgin population to maintain a healthy biomass. It is like setting a goal that you want to build a building that is 110 stories high," White continued. "Models estimate the population that we currently have relative to that policy goal. In our example, a model might tell us that our building is only 58 stories high."
DMR sea sampler Erin Giggey during a sampling trip in lobster Zone F in November 2001. DMR photo.
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Existing model
The existing model indicates that the current fishing mortality rate in the Gulf of Maine results in a lobster population that is capable of producing only 3.2% of the eggs compared to an unharvested population. Therefore, it is considered overfished.
How was this rate calculated? To drastically simplify, ASMFC determines if the lobster population is overfished using these four steps.
In Step 1, catch data are obtained in two ways: as fisheries-dependent data collected by government agencies through various reporting and sampling systems; and by the National Marine Fisheries Service in fisheries-independent bottom trawl surveys that are used to generate an estimated stock-abundance index.
In Step 2, both sets of data are then entered into a mathematical model called the DeLury model to provide estimates of fishing mortality for female lobsters.
In Step 3, the F10% benchmark goal for the typical female in that population is estimated from the egg-per-recruit model using information about lobster growth, natural mortality, fecundity, maturation, molting frequency, trap retaining rate, seasonal variation in fishing effort, and v-notching rates.
Finally, in Step 4, the fishing mortality estimated in Step 2 is compared with the F10% benchmark estimated in Step 3 to determine if the population is overfished.
For a given year in a given stock area, if the fishing mortality rate estimated in Step 2 is higher than F10% estimated in Step 3, resulting in an egg-per-recruit rate lower than the F10% benchmark, then the stock is defined as overfished.
Complex. controversial
Population models are complex, and this contributes to their controversy. From a scientific perspective, potential problems with the approach above lie in the quality of data put into the models, and the assumptions made about the models.
Chen and Wilson stated in their grant proposal to develop the new model that problems with the current EPR model include its "inability to systematically incorporate data of different sources that have been increasingly available in the fishery and (its) inability for risk analyses of alternative management strategies."
Other problems include unrealistic assumptions in dynamic models, unrealistic assumptions about the statistical property of data, and inappropriate statistical estimators, and the fact that the model's results cannot be validated against real world fisheries data.
And, according to Chen, the current model is highly limiting in terms of the data sources that can be incorporated into the assessment.
"The concept itself -- that you need to maintain a certain level of egg production to maintain the fishery -- may seem logical on the surface, but there is no way of verifying if it is right," said Jim Wilson, University of Maine professor of Marine Science.
"If you had many different indicators giving a consistent result, then you would have a more justified conclusion, but the current estimate from the model is the only indicator used," he continued. "The chances for a false-positive reading are high in these circumstances. Economists, for example, have learned that they need 20 or 30 separate indicators to get a firm sense of the state of the economy."
"The question becomes, 'What do we need to monitor in order to predict and manage the lobster population if it does begin to drop?' Since we don't know why the population has increased, we are not prepared to track changes that might trigger decline." —Robin Alden
New model alternative
The Chen-Wilson study, which is titled "Developing a Bayesian Stock Assessment Framework for the American Lobster," focuses on a type of probability model increasingly used throughout the world to assess and manage fisheries stocks.
Chen himself has successfully applied similar models to fisheries in Australia, New Zealand and, much closer to home, the green sea urchin fishery in Maine.
Due to its flexibility, a Bayesian framework can handle a variety of different data from a range of sources in order to come up with various models showing the effects of diverse fishery management options.
Unlike the current stock assessment framework, which only allows for catch and survey data to be modeled, the Bayesian stock assessment framework allows for assimilation of data from different sources.
These sources include prior knowledge of the fishery derived from previous ecological studies, as well as scientists' and fishermen's observations and experiences. It also allows for risk analyses of different options.
What it will do
The ability to assimilate data from different sources will increase spatial and temporal understanding of the lobster fishery and allow for greater industry input in the stock assessment. This could provide a better picture about the status of the lobster stock.
With this more accurate information in hand, the new model will enable analysis of the risks involved in different management options and compare potential outcomes associated with such options. This could lead to the development of better management plans.
In their proposal, Chen and Wilson asserted, "The new stock assessment approach ... can overcome many problems associated with the traditional methods, improve the quality of the lobster stock assessment, and will provide fisheries scientists, managers, and ... industry an alternative approach for lobster stock assessment."
This could greatly advance the understanding and management of this important resource in Maine and other parts of the Northeast, they predicted.
"The new stock assessment framework will bring the stock assessment techniques for the lobster fishery up to date and to the standard that has been widely adopted for many fisheries on the West Coast and internationally," Chen said.
Since Chen is committed to testing the model vigorously first, it may be a few years before this new model can be used in any official stock assessment.
