“Figure 2. Relationship between the amount of illegal fishing (expressed as a proportion of the reported catch that is additionally taken as illegal and unreported catch) and an average of four World Bank indices of governance” from Agnew et al. (2009). This figure and other data from the article have given us a popular, but misinformed understanding of illegal fishing.
Author’s Note: I understand a few parts of this web essay may be provocative. I argue there is a major methodological failure in the field of fisheries management, and one example of this implies that the Obama administration may have been misinformed as to what we know scientifically about fisheries crime. My hope, however, is not to provoke, but perhaps encourage a little more discussion about the central issue.
A leading issue in the marine conservation arena is the global and large-scale nature of illegal fishing. Various NGOs have made Illegal, Unreported, and Unregulated (IUU) Fishing a key target of their campaigns, and indeed, you find that IUU is generally used as a proxy term for “illegal fishing”. Just off the top of my head, I can tell you that Pew, WWF, and Greenpeace all have global campaigns/programs dedicated to fighting “IUU” fishing but primarily focus on only the first “I”.
Further, governments have made the illegal fishing issue a priority. The EU is now actively blocking seafood imports from countries on suspicion that they were illegally produced, and this recently put Belize and Sri Lanka in the supra-state’s sights, among others. And in the U.S., President Obama recently issued a national task force to devise recommendations to combat seafood fraud and IUU fishing (though, staying par for course, the memorandum only discusses the term’s illegal component).
Because of this perceived problem, and my personal opinion that we needed a more scientific approach to engender fisher compliance than just getting governments to promise action and funds, I entered into a PhD program with the School of Criminal Justice at Michigan State University earlier this year. The program appealed to me because the School of Criminal Justice has a joint-research initiative with the MSU Department of Fisheries and Wildlife that examines issues of compliance with environmental law. In fact, this Conservation Criminology initiative makes MSU the leader in the field; no other university in the world has a formal program of research on environmental crime.
Though I am early into my work at the MSU School of Criminal Justice, I can say two things for certain:
- I made the right choice coming to MSU. There’s a ton of helpful theory, research methods, and empirically tested crime prevention strategies/tactics in the field of criminology that could be adapted to inform and upgrade fisheries enforcement.
- I’ve really got my work cut out for me. Now that I’m starting to think like a criminologist, I’m starting to understand that the dominant paradigm of fisheries enforcement is costly, unscientific, and quite likely ineffective, meaning that the field of fisheries management is going to need a major overhaul in its thinking.
Consider How We Measure Fisheries Crime
To best explain the rather bold statement (#2) above, let me provide you with a brief overview of our methods to estimate fisheries crime, which are quite “behind the times” from the perspective of criminology.
As I know from my own experience as a fisheries analyst, most fisheries management agencies in the world use law enforcement statistics, and law enforcement statistics alone, to assess rates of fishery rule violations, otherwise herein called ‘fisheries crime’. But most law enforcement experts (in the western world at least) would agree that for most crimes, these statistics can give a highly inaccurate picture of what’s really happening. This is because the nature of policing introduces bias (i.e., the “sampling” method is nonrandom), and also because for many types of violations, traditional policing generally fails to detect them.
For this reason, U.S. law enforcement agencies have long been trying to come up with other ways to measure the true rates of certain types of crime seen as most harmful to society. Perhaps most importantly, self-report surveys are now commonly employed to estimate the occurrence of often-unreported/detected crimes, like minor theft, sexual assault, and illegal drug use. Indeed, since 1972, the U.S. government has employed the National Crime Victimization Survey as one of its two primary measures of national crime rates (the other being traditional law enforcement statistics for certain major crimes compiled by the FBI). Other western countries commonly employ these self-report methods as well.
Generally, then, fisheries crime is monitored in a relatively archaic fashion. But is this to say that research scientists have not at all touched upon this crime estimation problem in fisheries management? Well…pretty much…yeah.
Consider the IUU fishing estimation methods that have been developed and deployed in the scientific literature. Virtually every method would fail to provide strategic information to the management agency. For instance, Agnew et al. (2009) – perhaps the most widely cited estimate of global illegal and unreported fishing – is in fact not based on observed behaviors, but instead draws upon a modeling exercise with highly suspect data and methods coming from other modeling exercises, trade press reports, and the expert opinion of fisheries biologists.
Perhaps most problematic is that the paper is based on data and data collection methods that appear to conflate ‘legal unreported’ catches with ‘illegal unreported catches’, and yet no discussion is provided on how the authors navigated this major problem and estimate only “illegal” AND “unreported” fishing. In fact, as best as I can tell, the problem can even be traced back to a misunderstanding of FAO definitions in the original MRAG consulting study that provided the framework for Agnew et al. (2009). Consider this quote from MRAG’s 2005 Review of Impacts of Illegal, Unreported and Unregulated Fishing on Developing Countries:
The FAO definition suggests that unreported fishing may not necessarily be illegal, although it is evident that it should also be considered illegal where reporting obligations form part of national laws and regulations or licence conditions. [bold added]
This is a completely incorrect reading of the agreed definition of IUU fishing. The FAO definition clearly states that unreported fishing can only occur with the ‘contravention’ of rules. Here’s the relevant definition from the FAO International Plan of Action to Prevent IUU Fishing, a document widely seen to be the authoritative “soft law” document on IUU fishing:
3.2. Unreported fishing refers to fishing activities:
3.2.1 which have not been reported, or have been misreported, to the relevant national authority, in contravention of national laws and regulations; or
3.2.2 undertaken in the area of competence of a relevant regional fisheries management organization which have not been reported or have been misreported, in contravention of the reporting procedures of that organization. [bold added]
The definitional problems of source data was avoided in Pitcher et al. (2002), the study which provided the analytical methodology of Agnew et al. (2009) and the MRAG report. Pitcher and his co-authors explicitly state they were use their own terminology, and that in order not to mix estimates of illegal unreported catches with estimates of legal unreported catches, they provide separate estimates for each type of unreported catch. Agnew et al. (2009), however, incorporated data that used the FAO definitions that conflate “illegal” with “unreported” and made no effort to separate the two categories of unreported fishing. Thus, we have just one set of numbers for “illegal and unreported” fishing in Agnew et al. (2009), and we can’t be sure how much of the amount was really associated with rule violations.
Really, once you look into the details of the Agnew et al. (2009) study, you begin to see that the original estimate was built on very limited data and a confused methodology. And yet, you have this estimate that – at no fault of the authors, mind you – has been cited all over the place as a proxy for “illegally caught fish”. Just consider this quote from President Obama’s Memorandum establishing a task force for seafood fraud and IUU fishing earlier this year:
Global losses attributable to the black market from IUU fishing are estimated to be $10-23 billion annually, weakening profitability for legally caught seafood, fueling illegal trafficking operations, and undermining economic opportunity for legitimate fishermen in the United States and around the world.
I know I’ve gotten into the weeds here, so let me just sum up the problem: the statement above, from the President’s office, is factually incorrect. The methodological issues with Agnew et al. (2009) mean that it is just not a well-reasoned estimate of illegal unreported fishing, and yet it is somehow cited by the U.S. Presidency as a reasonable quantification of “black market” seafood that harms legal fishers.
Filling the Data Gap
As a vast but useful oversimplification, you might say that fisheries agencies have recognized the problem of inferring true crime rates from law enforcement data, and have developed their own ways of filling the crime ‘data gap’. These ways can be divided into three strategy categories: increased police surveillance, technology solutions, and intelligence-led policing.
Let’s briefly consider each’s merits as a methodological fix then.
Traditional Police Surveillance
Generally speaking, the strategy of simply increasing police surveillance commonly consists of ramping up three “detection” tactics, each of which can be reasoned to be cost-prohibitive for most fisheries if the goal is representative crime rates.
- On-Board Observers. The introduction of on-board observers can be a very useful method of crime detection (as well as prevention), but it is generally cost-prohibitive in the majority of the world’s fisheries. Just consider that the FAO estimates that 2/3’s of the global fishing fleet’s vessels are un-decked and measure under 10 meters length. Also, as I’ve seen in Ecuador, it can be rather costly to obtain and maintain qualified observer personnel in the developing world.
- Additional At-Sea Patrols. Ramping up traditional patrols by sea and air to detect fisheries crime is still even more cost-prohibitive, if not also ineffective. For instance, King et al. (2009) found that the average cost-per-boarding of fishing vessels by US Coast Guard patrol vessels was between $61,700 and $97,100 for the 2003-2006 period, and as result, the Coast Guard’s estimated rate of fisher noncompliance likely underestimated the fishery crime rate by a significant margin due to the ability of illegal fishers to evade detection by patrols.
- Additional Dock-Side Inspections. Ramping up traditional inspections at the point where catches are landed are perhaps the most cost-friendly method to detect (and prevent) fisheries crime, but again, we might find reason to believe it is of limited utility for most of the world’s fisheries. A great many fisheries in the world have a large number of possible landings points, and many industrial fisheries are structured in a way that transhipments at-sea can be used to evade dockside inspectors. Further, while dockside inspections can detect illegal landing overages, illegal gears, and season violations, they can tell nothing about other violations, like illegal bycatch, discards, high-grading, area violations, or inappropriate temporary gear modifications (like tying closed/removing Turtle Excluder Devices in shrimp fisheries).
Perhaps if you had all of these tactics in place, you would have a very effective surveillance system, not to mention an incredible crime deterrent, but most fisheries just would not merit the costly government investment. I would also speculate that most of these fisheries would stopping turning a profit if industry had to fund these measures.
Technology Solutions
Some fishery agencies have implemented new technologies to operationalize new detection activities. These technologies offer meaningful new information, but their utility is limited to a narrow range of offenses.
- Vessel-Monitoring Systems (VMS). In many countries, industrial fishing vessels are tracked according to their spatial position, but this technology itself can be easily deactivated. Further, many protected areas still allow entry for transit while prohibiting fishing; in these cases, VMS often fails to detect illegal fishing as presence would not inherently imply wrong-doing. Because of these problems, a huge amount of illegal fishing in protected areas goes undetected.
- Electronic Monitoring Systems (EMS). Another technology-based measurement (and prevention) solution that has rarely been employed is that of just putting cameras on boats. Such Electronic Monitoring Systems are employed in the British Columbia Groundfish Fishery and some Alaskan fisheries, but rarely elsewhere due to the costs, technical operating requirements, and inapplicability to small vessels (i.e. most of the world’s fishing fleet).
- Auditing Analyses. An indirect method to measure illegal fishing volumes is to conduct accounting audits of reported seafood sales volumes with reported seafood landings. For example, auditing tools have now been institutionalized into the management processes of ICCAT for the high-value Atlantic Bluefin tuna industry, so much so that some NGOs are even conducting alternative auditing analyses to show how the ICCAT auditing tool is failing. But again, even if the kinks are worked out, we have a problem. The method can say nothing about those catches that were reported, but made illegal due to other types of violations, like using prohibited gears or fishing in protected areas. Thus again, a meaningful component of fishery rule violations go unconsidered. Plus, you could imagine that this method requires a level of bookkeeping that is impractical, if not impossible, for most fisheries and their governments.
- Hotlines and Cell Phone Applications. Fisheries crime hotlines and, to a lesser extent, mobile phone fisheries crime reporting apps can be used to collect additional data from voluntary informants. Though these technological solutions may provide meaningful actionable evidence for the authorities, it can generally be inferred that they offer data of an unknown bias/representativeness.
Intelligence-Led Policing
Intelligence-led Policing (ILP) is yet a third strategy that at least one fisheries agency has implemented to improve its understanding of fisheries crime.
The irony here is that intelligence-led policing isn’t really helpful for estimating crime rates. Instead, you might describe ILP as a management strategy that directs policing efforts on the basis of three principles: 1) the use of all available information, 2) expert analysis, and 3) holistic intelligence gathering through discussions with key stakeholders (i.e. informants).
The leading, and quite possibly only, country to serve as an exemplar of this management strategy is that of Australia. On a biennial basis, Australia conducts an National Compliance Assessment that identifies key risks that will be prioritized for police targeting in the following period. I’d guess this process is one of the reasons why Australian fisheries are so well-managed relative to the rest of the world, but that still doesn’t mean it gives an accurate picture of fisheries crime in Australia. The management strategy simply does not offer any methodology to structure its holistic intelligence gathering with stakeholders. Therefore all the biases and limitations of traditional police surveillance and technology strategies remain, and they interact with the unexplored and largely unknown biases of cooperative stakeholders.
ILP in fisheries, then, is not focused on scientific identification of crime problems, but instead upon subjective risk management from the perspective of fisheries managers.
Why Don’t We Just Ask? Fisheries Crime Self-Reports for Fisheries Management
Ultimately, every fishery is going to need some combination of traditional surveillance tactics, technology solutions, and intelligence-led policing. But having considered what we know about the biases and costs of these crime detection/estimation strategies, do we really think we will ever deploy them to a sufficient extent that the crimes most harmful to the fishery are made known to policymakers? I sure don’t. Just consider how very little we really know about the prevalence, frequency, or harm of different types of fisheries crime associated with that supposed “$10-23 billion seafood black market” mentioned above by the White House.
So here’s an easy fix…why don’t we just ask fishers about what they are doing or what they have seen?
This apparent fourth “Self-Report” strategy for fisheries crime estimation is what mainstream law enforcement and criminologists have been employing elsewhere for decades, and they’ve produced plenty of evidence to show that self-reports can be used to obtain representative data. If you don’t believe me, consider this quotes from a Workshop Summary from a National Science Foundation (NSF) Workshop on Measurement Problems in Criminal Justice held in 2003:
Early studies (Porterfield, 1943; Wallerstein and Wylie, 1947) found that not only were respondents willing to self-report their delinquency and criminal behavior, they did so in surprising numbers…The self-report methodology continues to advance in terms of both its application to new substantive areas and the improvement of its design. Gibbons’s (1979) suggestion that self-reports were just a fad, likely to disappear, is clearly wrong. Rather, with improvements in question design, administration technique, reliability and validity, and sample selection, this technique is being used in the most innovative research on crime and delinquency. [bold added]
The value of self-reports for estimating crime rates can be conceptualized in five ways:
- Versatile. Self-reports can easily be designed for any fishery context to evaluate compliance with fishery rules, either in part or whole. Numerous methods are also available to encourage the respondent to provide accurate information, such as by asking the respondent to speak only about the behavior of others, or by guaranteeing anonymity through methods like randomized response.
- Opportunity for Triangulation. A single survey of self-reported non-compliance can be immediately used to “triangulate” the true rates of crime occurrence and magnitude with technological monitoring and police surveillance data. For instance, if self-report data indicated that fishing in closed areas is a problem, and VMS data indicated regular transiting through fishing areas, managers could quickly prioritize area enforcement. Further, if self-report data conflicted with law enforcement data, at a minimum, further investigation would be warranted. For instance, in one of the rare examples of a self-report survey being used in a fishery, King et al. (2009) found that fishers in the Northeast Groundfish Fishery believed fisheries crime was a far greater problem than indicated by official US Coast Guard law enforcement data – a finding that likely did not surprised those people familiar with the fishery in the mid-00’s.
- Opportunity for Trend Identification. Repeat surveys of self-reported non-compliance employing the same methodology can also be used to infer trends in fisheries crime. Thus, while the true underlying crime rates might not be known, the measurement tool can be used to detect increases or declines of certain types of violations, like the utilization of prohibited gears, catch of prohibited species, and illegal high-grading.
- Opportunity for Prediction. The field of behavioral economics also indicates that self-reports, in particular those used to gauge respondents’ perceptions of non-compliance, can be used to predict future fisheries crime. This is because of two well-documented psychological “biases” in human decision-making. The first is our tendency to structure our decision-making around internalization of norms of behavior; that is, our perceptions of what other people are typically doing can greatly effect our own behavior (i.e. “if everybody is doing it, why don’t I?”). The second is our tendency to assume what is called a “false consensus”; that is, when we are asked to estimate other peoples’ behavior, we assume that they behave much like we do (i.e. perception can reveal actual behavior).
- Cost-Effective. Self-reports are relatively inexpensive compared to traditional surveillance measures like at-sea patrols and on-board observers, so to the extent that they are designed to limit nonresponse and improve recall, they can be considered to be highly cost-effective.
Is There an Illegal Fishing Crisis?
This quick consideration of fisheries crime estimation methods leads me to ask the headline question: Is there really a global illegal fishing crisis?
Honestly, I just can’t tell you ‘yes’ or ‘no’. One one hand, the popular estimate of a $10-23 billion “black market” for illegal and unreported fishing is highly suspect and should not be used as a proxy for illegal fishing. But on the other, it is also pretty clear that there are or have been some “problem fisheries” (e.g., abalone, bluefin tuna), and anecdotal information provided by fisheries management professionals suggests that enforcement is significantly underfunded outside of high value fisheries. Given this uncertainty, I think it is best to apply the precautionary principle and assume that there is a widespread compliance problem until proven otherwise.
Looking forward, I’d argue that what is needed is a cost-effective way to evaluate fisheries crime. For if we can’t identify the problems, how can we appropriately target them? And if we can’t measure rates of crime over time, can we ever really determine if our “solutions” for the supposed illegal fishing crisis are working? Thankfully, self-reports offer a world of cost-effective opportunity.
Cited References:
Agnew, D.J., J. Pearce, G. Pramod, T. Peatman, R. Watson, J.R. Beddington, & T.J. Pitcher (2009). Estimating the worldwide extent of illegal fishing. PloS ONE, 4 (2).
King, D., R.D. Porter & E.W. Price (2009). Reassessing the Value of U.S. Coast Guard At-Sea Fishery Enforcement. Ocean Development and International Law 40:350-372.
Pitcher, T.J., R. Watson, R. Forrest, H. Valtýsson, & S. Guénette (2002) Estimating Illegal and Unreported Catches From Marine Ecosystems: A Basis For Change. Fish and Fisheries 3: 317–339 (2002).
