Dan

You ask an important question. The answer lies in MISmanagement. Who manages the fisheries? Its a political process that depends on the science we do. Do politicians actually understand the science and the risks we quantify? From my experience they do not! Come election year they will increase the TAC...they angling for votes.

Read some of Prof Doug Butterworths papers on Operational Management Plans (OMP)...published in the South African journal of Marine Science...now called African journal of Marine Science.

An OMP developed properly:

1. Stipulates what data is to be collected (fisheries dependent or independent) (This is science)

2. What models to be applied to set the TAC (This is science)

3. How to divide the TAC into quotas (this is management)

4.Law enforcement of fishing regulations (this is management)

5. The process repeats itself

In a nutshell Dan dont lump the science we do with management. There is a clear distinction. We practice science for decades...Fisheries Ministers lifespans are just 5 years.

Best regards

Anesh

2J3KL northern cod though a fishery dependent index. Lots of good paper by Myers, Hutchings, Walters and others on it. You could argue that almost all assessment use poor indexes since we do not actually know if they are proportional to abundance. There are a few salmon cases where we actually know. I think the P. hake acoustic time series was thrown out due to poor ground-truthing but it would be tricky to connect the index in the assessment to the management decisions made. There are a number of issues with the indexes used in the tuna assessment due to standardization problems. Would also be difficult to make the connection between these and the management advice.

I've always wondered about the follow-up assessment of management decisions. I hear a LOT about planning, but very very little about 'how well did the plan work?' good luck, sorry I don't have any suggestions

Hi Anesh....I agree with you that more than just science determines management and unfortunately sometimes it may come down to fishing for votes :). But I'm not ready to accept that science plays no role (not yet). There are many fisheries where the stock assessments strongly influence the management decisions.  A great example is the 1990s North Atlantic cod fishery crash due to strongly influential and (incorrect) stock assessment. Admittedly, its not my favorite example of management using science. Is the glass half full or half empty?.....Its interesting to hear your perspective, and I will take a look at Butterwwoths' papers....Thanks!

Hi Rob....Really great to hear from you. I guess this isn't the right forum to ask how the family is....I'll save that for later. Right now the cod fishery collapse is my only example. The literature is dense with papers about the need for fisheries independent data, index standardization, accounting for variable catchability. And agencies like NOAA invest a lot of money into developing and improving indices. But actually determining mismanagement and assigning blame to something specific seems nearly out of reach. I think the cod example is available because it was such a tragedy and people wanted to know what went wrong.

I'll keep digging to see what I come up with. If I find any more examples, I'll post them (Rachel).

Thanks! 

Hake provides a good example of an error prone index but on the whole, the management has been pretty good. Some of the simulations in http://www.westcoast.fisheries.noaa.gov/publications/fishery_management/groundfish/whiting/2014-stock-assess.pdf illustrate how the combination of both an error prone index and high recruitment variability can be buffered against with non-assessment/index modifications to the harvest control rule (i.e. catch caps).

It's an interesting problem but I'm not sure the argument that you're contemplating. I'd be happy to talk further if you like and could probably thing of a couple other examples.

Dan

Check out this publication

Age, growth and retrospective stock assessment of an economically extinct sparid fish, Polysteganus undulosus, from South Africa

Article in Fisheries Research 51(1):87-92 · April 2001

DOI: 10.1016/S0165-7836(00)00235-6

Anesh

Fisheries managers often rely upon commercial landings data in stock assessments even when the accuracy of the data is unknown.  I seem to recall there being a conclusion several years ago that the assessment of bluefin tuna in the Atlantic Ocean being severely affected by errors and incomplete reporting of commercial landings from at least one country.  I'm not sure this is the kind of information you are seeking, but if it is, would suggest you contact ICCAT to get more information.

I really appreciate everybody contributing to this discussion. It’s a real treat to hear from you Nathan…I’m familiar with your work. And really good to hear from you, Gary.

What is motivating my question is a contract I have with NOAA in collaboration with Nate Bacheler and Kyle Shertzer at the Beaufort lab.  I have been working to develop analytical methods to combine video and chevron trap data into a single index by explicitly modeling the observation process of each gear. The statement that I am looking to support is simply, “Within the fisheries management and conservation context, the ability to disentangle the abundance and detection processes carries significant value, and failing to do so can carry substantial costs due to mismanagement.”

And so I’m looking for documented costs (or evidence of costs) due to mismanagement as a result of indices not being proportional to abundance.

I imagine that there are situations where an error prone index simply does not matter because the management may not be refined enough for it to matter (or for the reasons Anesh mentioned). But I’m sure in many cases there is a cost due to harvesting at sub optimal levels. Those are the examples I'm digging for.

Thanks again for contributing, and please let me know if any examples come to mind. 

Cheers, Dan

Nathan, 

It sounds like the simulations you mentioned may demonstrate the cost of an error prone index if they found that a more conservative harvest control rule buffers against potential for overfishing. In this case the cost of the poor index would be forgone harvest. Is this the case? I'll have a look at the report you linked. 

Thanks again,

Dan

As for Chinook salmon, usage of so called "Sacramento Index" or "Jack Index" to predict the annual Sacramento River fall-run Chinook abundance led to overfishing of this stock and contributed to the failure to achieve the escapement goal in 2007. You can read about all circumstances in comprehensive report by Lindley ST, Grimes CB, Mohr MS, Peterson WT and others (2009) What caused the Sacramento River fall Chinook stock collapse? U. S. Department of Commerce, NOAA Technical Memorandum NMFS, NOAA-TM-NMFS-SWFSC, 121 pp (available online). 

This is a good example Vladimir. thanks for this. 

d

I do agree with explanation given by Robert N M Ahrens ·

Hi,

I'm thinking northern Atlantic cod crisis, especially in Atlantic Canada (NFL, QC, ...)

More recently, there have been debates about the shrimp quotas mismanagement in NFL. Research have been conducted in MUN University (see Mather, for example) but I'm not sure in which extent it'll help you ...

 The RFAMS method is an very helpful tool for recording catches at fish landing sites in tropical developing countries where the catches are highly diverse with many fishing types involved. on the other hand, a potentially main issue is whether a large portion of the catches is being missed for any particular reason, e.g. catches by-passing the surveyed part of the landing site, sale direct from boats prior to catches entering landing site, etc. This needs to be determined on a case by case basis depending on the landing site being surveyed. Thus, one of the critical first steps of using this method is to develop a good understanding of the dynamics of the landing site or sites being surveyed. Using this method without understanding how a landing site operates can lead to significant underestimation of landings and potentially erroneous data being collected