By Dana Sackett

The old adage, “there are plenty of fish in the sea” begs the question, how many fish are actually in the sea? Many fisheries scientists have worked tirelessly to answer this question. Estimating the size of a fish population (which can range from largemouth bass in a few lakes in North Carolina to tuna in the Pacific Ocean) is the key to managing a fishery. After all, you have to have an idea of how many fish are out there in order to estimate how many fish we can harvest and still maintain a healthy population. Because we can’t just jump in and count all the fish in the water, there are a number of ways that scientists have come up with to estimate how many fish are in, let’s say, the ocean, and how much fishing pressure a population can handle and stay healthy.

One of the most common types of data used to estimate population size is called fishery dependent data. These data are collected by commercial and recreational fishers, and are also called catch data. Catch data are useful because there are often records of what fishers have caught since people first started catching those fish. However, there are a few problems with catch data. First and foremost, is that catch data are only collected in places where people fish- limiting the scope from all fish in the sea to only the part of the sea that people fish. Additionally, how the fish are caught influences catch data. For example, hook and line only includes hungry fish (they have to bite a line to be caught). These factors can lead to bias in the data and incorrect estimates of relative abundance.

Catch data also have to be standardized by effort. For instance, the more fishermen fish the more they will catch. If effort is not taken into account it may look like the number of fish in a population is increasing because the number of fish being caught is increasing, when really the fishermen are just fishing more. Effort is often measured as a unit of time (hours or days fishing). The measure for catch data used to estimate relative abundance is therefore catch-per-unit-effort. To complicate things a little more a unit of effort is not always equal over time. For example, an hour of fishing 50 years ago cannot be compared to an hour of fishing today, as fishers now have fish finders, GPS, faster boats, trawls, nets and electric reels that were not in existence 50 years ago.

Fishery independent data are data that are collected by fisheries scientists independent of commercial and recreational fishing. These surveys are specifically designed to sample objectively across the geographic range of the species and not just where the fish are most abundant. However, like catch data there are a number of limitations and bias that come with each type of fishery independent data. Therefore, fishery independent data are often used with catch data to provide the best estimations of population size. As seen in our recent article, ‘Listening to the wind for better fishery science“, these data can be used in numerous models to gain the best estimation of relative abundance.

Some have even begun to use fishery independent surveys that are non-extractive, meaning they do not remove fish from the water. For instance, in Hawaii they have begun to compare a number of non-extractive methods such as baited camera systems, remotely operated vehicles with cameras, acoustic surveys where sounds waves locate groups of fish underwater and catch data to determine the best fishery independent non-extractive method to estimate population size.

However, much of these considerations are moot if managers do not take scientific estimates of population size and recommendations for catch limits into account. A recent study by O’Leary and others in 2011 found that 68% of stock regulations in Europe were set higher than recommended by scientists and that these politically-driven adjustments to catch limits dramatically increased the likelihood of the stock collapsing within 40 years. Thus, while it is important to take politics into account and there is uncertainty in scientific estimates of population size and catch limits, regulations based on science are the best chance we have at estimating the number of fish in the sea and maintaining sustainable fisheries.

References and related material:

O’Leary BC, Smart JCR, Neale FC, Hawkins JP, Newman S, Milman AC, Robert CM. 2011. Fisheries mismanagement. Marine Pollution Bulletin 62:2642-2648.

Pauly D, Alder J, Bennett E, Christensen V, Tyedmers P, Watson R. 2003. The future for fisheries. Science 302:1359-1361.

Peel D, Bravington MV, Kelly N, Wood SN, Knuckey I. 2012. A model-based approach to designing a fishery-independent survey. Journal of Agricultural, Biological, and Environmental Statistics 18: 1-21.

Richards BL, Williams ID, Nadon MO, Zgliczynski BJ. 2011. A towed-diver survey method for mesoscale fishery-independent assessment of large-bodied reef fishes. Bulletin of Marine Science 87: 55-74.

Stallings CD. 2009. Fishery-independent data reveal negative effect of human population density on Caribbean predatory fish communities. PLoS ONE 4:e5333.

Yu H, Jiao Y, Su Z, Reid K. 2012. Performance comparison of tradition sampling designs and adaptive sampling designs for fishery-independent surveys: a simulation study. Fisheries Research 113:173-181.