Enhancing the TurtleWatch product for leatherback sea turtles, a dynamic habitat model for ecosystem‐based management

Abstract

Fishery management measures to reduce interactions between fisheries and endangered or threatened species have typically relied on static time‐area closures. While these efforts have reduced interactions, they can be costly and inefficient for managing highly migratory species such as sea turtles. The NOAA TurtleWatch product was created in 2006 as a tool to reduce the rates of interactions of loggerhead sea turtles with shallow‐set longline gear deployed by the Hawaii‐based pelagic longline fishery targeting swordfish. TurtleWatch provides information on loggerhead habitat and can be used by managers and industry to make dynamic management decisions to potentially reduce incidentally capturing turtles during fishing operations. TurtleWatch is expanded here to include information on endangered leatherback turtles to help reduce incidental capture rates in the central North Pacific. Fishery‐dependent data were combined with fishing effort, bycatch and satellite tracking data of leatherbacks to characterize sea surface temperature (SST) relationships that identify habitat or interaction ‘hotspots’. Analysis of SST identified two zones, centered at 17.2° and 22.9°C, occupied by leatherbacks on fishing grounds of the Hawaii‐based swordfish fishery. This new information was used to expand the TurtleWatch product to provide managers and industry near real‐time habitat information for both loggerheads and leatherbacks. The updated TurtleWatch product provides a tool for dynamic management of the Hawaii‐based shallow‐set fishery to aid in the bycatch reduction of both species. Updating the management strategy to dynamically adapt to shifts in multi‐species habitat use through time is a step towards an ecosystem‐based approach to fisheries management in pelagic ecosystems.

Sea Turtle Bycatch Mitigation in U.S. Longline Fisheries

“…The range of SST with positive sea turtle captures was more protracted in the Pacific, with the frequency of sets with sea turtle bycatch highest when SST ranged between ∼17 and 19 • C for both loggerheads and leatherbacks. These ranges overlap entirely with the species' atcapture peak SST ranges previously reported in the North Pacific (Howell et al, 2008(Howell et al, , 2015Kobayashi et al, 2008;Abecassis et al, 2013). "Within hook type comparison" results represent the percent increase for squid or "other" category baits relative to fish bait within each hook type category (Circle, J, or Other).…”

“…For pelagic longline fisheries operating in the north Atlantic, Brazner and McMillan (2008) investigated the frequency of loggerhead turtle capture as a function of SST and suggested limiting fishing activity in SST >20 • C to minimize loggerhead bycatch. In the North Pacific, Howell et al (2008Howell et al ( , 2015 used extensive satellite tracking data to identify oceanographic features such as SST that could be used to predict the presence of loggerhead and leatherback turtles with the ultimate goal to develop a means to reduce sea turtle captures in longline fisheries. The result is an internet-based product, NOAA TurtleWatch (www.pifsc.noaa.gov/eod/turtlewatch.php), that serves to provide information on preferred sea turtle habitat, specifically SST, that can be used by managers and fishers to make dynamic decisions to reduce the incidental capture of loggerhead and leatherback turtles during longline fishing operations (Howell et al, 2008(Howell et al, , 2015.…”

“…In the North Pacific, Howell et al (2008Howell et al ( , 2015 used extensive satellite tracking data to identify oceanographic features such as SST that could be used to predict the presence of loggerhead and leatherback turtles with the ultimate goal to develop a means to reduce sea turtle captures in longline fisheries. The result is an internet-based product, NOAA TurtleWatch (www.pifsc.noaa.gov/eod/turtlewatch.php), that serves to provide information on preferred sea turtle habitat, specifically SST, that can be used by managers and fishers to make dynamic decisions to reduce the incidental capture of loggerhead and leatherback turtles during longline fishing operations (Howell et al, 2008(Howell et al, , 2015. This is particularly valuable in the shallow-set sector of the Hawaii fishery that operates under sea turtle bycatch limits, whereby the fishery is mandated to immediately cease fishing operations until the remainder of the calendar year once a certain number of turtle interactions by species occurs.…”

“…This is particularly valuable in the shallow-set sector of the Hawaii fishery that operates under sea turtle bycatch limits, whereby the fishery is mandated to immediately cease fishing operations until the remainder of the calendar year once a certain number of turtle interactions by species occurs. Howell et al (2015) proposed a dynamic management concept based upon a SST habitat boundary, whereby fishing effort should be avoided in the FIGURE 8 | Effect of gear characteristicsand location on the probability of catch of loggerheads (A-D) and leatherbacks (E,F) in the Pacific. The y-axis is in logit units and represents deviation from the logit mean.…”

Fisheries bycatch reduction within the least-cost biodiversity mitigation hierarchy: Conservatory offsets with an application to sea turtles

“…Application of the U.S. Endangered 673 674 675 676 677 678 679 680 681 682 683 684 685 686 687 688 689 690 691 692 693 694 695 696 697 698 699 700 701 702 703 704 705 706 707 708 709 710 711 712 713 714 715 716 717 718 719 720 721 722 723 724 725 726 727 728 14 management program TurtleWatch, that is on-stock, in-kind, essentially on-site, to avoid sea turtle "hot spots" [10]. the California drift gillnet fishery, even allowing for risk [8].…”