Research Article: Fisheries management in the face of uncertainty: Designing time-area closures that are effective under multiple spatial patterns of fishing effort displacement in an estuarine gill net fishery

Date Published: January 18, 2019

Publisher: Public Library of Science

Author(s): Liza A. Hoos, Jeffrey A. Buckel, Jacob B. Boyd, Michael S. Loeffler, Laura M. Lee, Fraser Andrew Januchowski-Hartley.


A commonly cited reason for the failure of time-area closures to achieve fisheries management goals is the displacement of fishing effort from inside the closure into the surrounding area still open to fishing. Designing time-area closures that are predicted to achieve management goals under multiple spatial patterns of effort redistribution will increase chances of success. Using data from an estuarine gill net fishery, we tested if there are time-area closures predicted to reduce bycatch of two protected species groups while maintaining target catch under four simulated effort redistribution patterns. We found that the pattern of effort redistribution had a substantial impact on the amount of predicted bycatch in each closure scenario. Multiple closures were predicted to reduce bycatch of these species under all four simulations of effort redistribution. However, some combinations of closure and effort redistribution pattern resulted in estimated bycatch being higher than without a closure. We did not find any time-area closures that resulted in a predicted reduction in bycatch while maintaining target catch at original levels. We demonstrate a simple way for fisheries managers to account for the uncertainty in fishers’ behavior by designing time-area closures that are predicted to reduce bycatch under multiple potential patterns of spatial redistribution of fishing effort.

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Bycatch, or the unintentional catch of non-target species (e.g. finfish, sea turtles, marine mammals), is a global problem that occurs with almost every type of fishing gear [1]. Bycatch can contribute to population decline of the bycatch species and impact the larger ecosystem by removing or weakening key nodes of the food-web [2, 3]. Bycatch may also negatively impact fishers when bycatch mitigation regulations limit opportunities to fish for their target species or require costly gear modifications or replacement [3–5]. Ideally, approaches can be identified that reduce bycatch without negatively impacting the fishery’s profitability [6]. Providing incentives to reduce bycatch (e.g. quotas on bycatch that trigger fishery shutdown) have been shown to reduce bycatch rate but can require 100% observer coverage [7] which is cost-prohibitive for many fisheries. If finding such win-win solutions is not possible, an alternative objective is to find a solution that provides an optimal balance between a) the impact of bycatch on the health of the bycatch species’ population and ecosystem and b) the impact of bycatch mitigation strategies on the fishery [8].

Large mesh gill nets are used by commercial fishermen throughout NC’s estuarine waters, which together compose the third largest estuarine system in the world [20]. Depending on the season and location, these fishermen may be targeting a wide variety of species, including southern flounder (Paralichthys lethostigma) and American shad (Alosa sapidissima). Large mesh gill nets can have high rates of bycatch [21] and capture protected species such as Atlantic sturgeon [20, 22] and several species of sea turtles [8, 23, 24] that migrate in and out of the estuary system throughout their life history. Bycatch in gill nets has been listed as one of the major sources of human-induced mortality for Atlantic sturgeon in the southeastern United States [22], and Atlantic sturgeon are listed as endangered in the Carolina Distinct Population Segment under the Endangered Species Act (ESA). Bycatch in fishing gear has also been cited as contributing to decline of sea turtle populations worldwide [25], and all five species of sea turtles that are found in NC waters are listed as endangered or threatened under the ESA. Of these five species, three are commonly caught in gill nets in NC [24]: the green sea turtle (listed as threatened in the North Atlantic Ocean Distinct Population Segment), loggerhead sea turtle (listed as threatened in the Northwest Atlantic Ocean Distinct Population Segment), and Kemp’s ridley sea turtle (listed as endangered throughout its range).

In both study areas, effort redistribution pattern had a large effect on bycatch and target catch levels both within and among closures. When effort redistributed into the area still open to fishing (redistribution patterns 2–4), bycatch reduction was always less than if all displaced effort was removed from the system (redistribution pattern 1). Aside from this trend, none of the other possible redistribution patterns (2–4) consistently resulted in either the highest or lowest %CIC across closures and study areas. Closures did not always lead to a catch reduction; in both study areas, some closures led to increased catch levels under certain redistribution patterns.

We found one or more time-area closures that are predicted to reduce bycatch under all four patterns of fishing effort redistribution in both Pamlico and Albemarle Sound fisheries. If managers were to select one of these closures, it is more likely that the bycatch thresholds would be reached later in the season, or not at all. We did not find any time-area closures that both reduced bycatch and maintained target catch at original levels. All closures were predicted to either increase or decrease target catch. Our results clearly illustrate how fisher behavior after a closure can influence levels of bycatch and target catch. Thus, managers should incorporate the potential impacts of effort displacement into closure design. Given uncertainty about fishers’ spatial response, one of the simplest and most precautionary ways to do so is to select a closure that reduces bycatch under multiple possible effort redistribution patterns.

The methodology outlined in this paper will aid managers in evaluating potential time-area closures without the burden of complex and data-intensive modeling tasks. The approach also provides a concrete way for managers to weigh the gains of expected bycatch reduction against the perceived costs of lost target species catch due to banning fishing from historical fishing grounds. The results have already been useful in helping managers incorporate fishing effort displacement into their decision-making process when selecting closures to reduce bycatch in NC. For example, the closures X, Y, and Z were considered for the 2016 fishing season. Although this approach does not guarantee bycatch reduction with no significant impact on the fishery, it does bring to light many of the issues that managers need to consider in closure design such as effort redistribution, closure timing, placement of closures, and effects on target catch.




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