By: Dana Sackett

Mark and recapture is a common method used by ecologists and resource managers to estimate a species growth, movement, levels of harvest, population size, and/or natural mortality (the rate at which animals die from natural causes such as predators, disease, or old age).  For fisheries scientists, this method often involves capturing a fish, recording information on its size and where it was caught, then marking the fish with a tag prior to releasing it back into its environment.  These tagged fish are then available to be recaptured by local fishers that turn in tags for a reward after providing specific information back to the scientist.  This information provides the data needed to make targeted estimates.

Some additional benefits of using reward-based mark-recapture studies is that they offer a simple and direct approach to estimate information about a fishery independent from other common modeling techniques (for example, catch-at-age models).  Agreement among these independent approaches may then increase confidence in model-based estimates. On the other hand, disagreement highlights those assumptions and areas that need more investigation. In addition, mark-recapture studies often provide additional insights into a fishery, as the fishers are providing information directly to the researcher about their catch.

However, effective mark and recapture is more than simply a game of catch, measure, and repeat.  There are a number of factors to account for when designing a mark-recapture study for a fishery (see the video above for some of these).  For instance, knowing the number of tags that will be lost after the tagged fish are released (for example tags that fall off or are bitten off by another fish) is needed to know how many tagged fish are available to be recaptured by fishers.  One way of accounting for this is to double-tag some of the fish.  The number of double-tagged fish that are returned with only a single tag can then be used to estimate a tag-loss rate and ultimately the total number of fish that likely lost their tags.

Another consideration comes down to economics: reward type and amount.  The goal of the reward is to motivate the fisher to report the requested data.  To do that, the right award is key.  For example, rewarding fishers with merchandise, such as hats or t-shirts will not appeal to everyone and many may decide the effort of reporting the tag is not worth the prize; especially those that have already received a hat or t-shirt for turning in a previous tag (How many “I caught a Big Bass and all I got was this T-Shirt” t-shirts does any one person really need?).  For this reason, money is commonly used as a reward, though the amount can vary drastically.  Different reward amounts will illicit different levels of tag reporting by fishers. For instance, one study demonstrated that a reward amount of $5 resulted in a 20% reporting rate.  That means only 20% of those fishers that recaptured a tagged fish reported the tag.

High-reward mark-recapture studies aim to offer a reward amount high enough that 100% of fishers that recapture a tagged fish report it. However, this amount changes depending on the fishery.  Expensive fisheries, those that require hundreds of dollars in gas and large boats to fish, often require much higher reward amounts to illicit 100% reporting than a species that can be caught from the shore of a lake.

Another important consideration is that tagged fish will only be caught where the fishers are fishing (targeted sampling or where they expect to catch fish) rather than randomly sampling over the study area (fishery surveys).  So if tagged fish move to an area where fishers don’t typically fish or if a portion of the fish population isn’t vulnerable to the technique that fishers use to fish they will be unaccounted for in the data.  This is where combining mark-recapture with fish surveys can be very useful to fill in these data gaps.

Dr. Matt Catalano and I recently modeled several simulations of a red snapper population in the Gulf of Mexico to better understand how some of these study design considerations could impact the accuracy, precision, and costs of a mark-recapture study.  We were specifically interested in (1) knowing where and how many fish would need to be tagged, (2) how the distribution of the population, tags, fishing effort, and death rate from tagging would affect the reliability of fishery estimates and project costs, (3) what proportion of tagged fish should be double-tagged to estimate tag loss rates, (4) how incorrectly assuming a 100% reporting rate for high-reward tags would affect study results, and (5) the relative performance and costs of high-reward versus variable-reward (both low and high dollar reward amounts) tagging approaches.

Our results demonstrated that using all high-reward tags was more cost-effective than using both high- and low-rewards when the primary goal was to estimate harvest rates.  This result was largely because lower value tags are often not reported and therefore a much higher number of fish need to be tagged to produce the same level of accuracy and precision in study results.  However, a serious effort should be made to ensure the high-reward amount selected represents 100% reporting or results could be bias. We also discovered that distributing tags uniformly over a study area when the true distribution of the population and fishing effort varies over that area can drastically bias results.

Mark-recapture techniques provide a cost-effective way to essentially crowd-source or incentivize people with the know-how, resources, and time (they were going to be out there fishing anyway) to become data collectors.  These citizen scientists then provide the data needed to manage or improve the management of our natural resources.  Economically this is great because there are often more fishers out sampling the tagged population than scientists can afford to pull together and pay, and fishers are rewarded for doing what they love, fishing.

References and other reading material:

A great student activity for simulating fish tagging and monitoring by National Geographic: https://www.nationalgeographic.org/activity/fish-tagging-and-monitoring/

Cowen, L., S. J. Walsh, C. J. Schwarz, N. Cadigan, and J. Morgan. 2009. Estimating exploitation rates of migrating yellowtail flounder (Limanda ferruginea) using multistate mark-recapture methods incorporating tag loss and variable reporting rates. Canadian Journal of Fisheries and Aquatic Sciences 66:1245-1255.

Denson, M. R., W. E. Jenkins, A. G. Woodward, and T. I. J. Smith. 2002. Tag-reporting levels for red drum (Sciaenops ocellatus) caught by anglers in South Carolina and Georgia estuaries. Fishery Bulletin 100:35-41.

Minta S., and M. Mangel. 1989. A simple population estimate based on simulation for capture-recapture and capture-resight data. Ecology 70:1738-1751.

Nichols, J. D., R. J. Blohm, R. E. Reynolds, R. E. Trost, J. E. Hines, and J. P. Bladen. 1991. Reporting rates for mallards with reward bands of different dollar values. The Journal of Wildlife Management 55:119-126.

Pine, W. E., K. H. Pollock, J. E. Hightower, T. J. Kwak, and J. A. Rice. 2003. A review of tagging methods for estimating fish population size and components of mortality. Fisheries 28:10-23.

Pollock, K. H., J. M. Hoenig, W. S. Hearn, and B. Calingaert. 2001. Tag reporting rate estimation: 1. An evaluation of the high-reward tagging method. North American Journal of Fisheries Management 21:521-532.

Sackett, D. K., and M. Catalano. 2017. Spatial Heterogeneity, Variable Rewards, Tag Loss, and Tagging Mortality Affect the Performance of Mark–Recapture Designs to Estimate Exploitation: an Example using Red Snapper in the Northern Gulf of Mexico. North American Journal of Fisheries Management 37:558-573.  Link to this article: http://dx.doi.org/10.1080/02755947.2017.1303007

Taylor, R. G., J. A. Whittington, W. E. Pine III, and K. H. Pollock. 2006. Effect of different reward levels on tag reporting rates and behavior of common snook anglers in southeast Florida. North American Journal of Fisheries Management 26:645-651.