Near real‐time spatial management based on habitat predictions for a longline bycatch species

By A. Hobday, Klaas Hartmann. 2006

229 citations recorded by the source corpus.

Southern bluefin tuna (SBT), Thunnus maccoyii (Castelnau), is a quota-managed species that makes annual winter migrations to the Tasman Sea off south-eastern Australia. During this period it interacts with a year-round tropical tuna longline fishery (Eastern Tuna and Billfish Fishery, ETBF). ETBF managers seek to minimise the bycatch of SBT by commercial ETBF longline fishers with limited or no SBT quota through spatial restrictions. Access to areas where SBT are believed to be present is restricted to fishers holding SBT quota. A temperature-based SBT habitat model was developed to provide managers with an estimate of tuna distribution upon which to base their decisions about placement of management boundaries. Adult SBT temperature preferences were determined using pop-up satellite archival tags. The near real-time predicted location of SBT was determined by matching temperature preferences to satellite sea surface temperature data and vertical temperature data from an oceanographic model. Regular reports detailing the location of temperature-based SBT habitat were produced during the period of the ETBF fishing season when interactions with SBT occur. The SBT habitat model included: (i) predictions based on the current vertical structure of the ocean; (ii) seasonally adjusted temperature preference data for the 60 calendar days centred on the prediction date; and (iii) development of a temperaturebased SBT habitat climatology that allowed visualisation of the expected change in the distribution of the SBT habitat zones throughout the season. At the conclusion of the fishing season an automated method for placing management boundaries was compared with the subjective approach used by managers. Applying this automated procedure to the habitat predictions enabled an investigation of the effects of setting management boundaries using old data and updating management boundaries infrequently. Direct comparison with the management boundaries allowed an evaluation of the efficiency and biases produced by this aspect of the fishery management process. Near real-time fishery management continues to be a realistic prospect that new scientific approaches using novel tools can support and advance.

Subfields: Ecology, Global and Planetary Change

View Paper: https://www.semanticscholar.org/paper/56d4b35a021e98d9f50c46aac5ac62f97308525a

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Citations in the corpus

Migratory marine species: their status, threats and conservation management needs (2014, background): “…around the world for MMS conservation, but has been used effectively to manage human activities affecting MMS, such as direct exploitation of tuna (Hobday and Hartmann, 2006; Hobday et al., 2011), turtle bycatch (Howell et al., 2008) and ship strikes (Van Parijs et al., 2009; Asaro, 2012).”
Multispecies fisheries management and conservation: tactical applications using models of intermediate complexity (2014, background): “Alternatively, dynamic movement involves time-dependent factors, such as reproduction or prey/competitor density and environmental conditions (Hobday and Hartmann 2006), impacting rates of movement.”
Global habitat preferences of commercially valuable tuna (2015, background): “…and movement patterns at relevant scales for management (e.g. Block et al., 2005; Block et al., 2011; Hartog et al., 2011; Hazen et al., 2013; Hobday and Hartmann, 2006), most tagging studies are local with short deployment periods (e.g. Cosgrove et al., 2014), and provide information about…”
Seasonal forecasting of tuna habitat in the Great Australian Bight (2015, methodology): “Environmental information can be useful to fishers on a range of time scales from real-time (Hobday and Hartmann, 2006; Howell et al., 2008) to several months into the future (Hobday et al., 2011).”
Linking Movement Ecology with Wildlife Management and Conservation (2016, background): “…- area closures may also achieve conservation targets whilst incorporating stakeholder interests , for example by maintaining alternative land - use or harvesting practices , and are being increasingly utilized in marine and freshwater ecosystems ( Hobday and Hartmann , 2006 ; O ' Neal et al .”
Evaluating effectiveness of time/area closures, quotas/caps, and fleet communications to reduce fisheries bycatch (2014, background): “Efforts to model the effects of closures have become more prevalent in recent literature (Adlerstein and Trumble, 1998; Hobday and Hartmann, 2006; Grantham et al., 2008; Powers and Abeare, 2009; Diamond et al., 2010) and can be informative for management decisions on size, location, and duration of ”
Tracking seabirds to identify potential Marine Protected Areas in the tropical western Indian Ocean (2012, background): “…and help to sustain these fisheries ((Worm et al., 2009; Koldewey et al., 2010), although the conservation of highly migratory fish like tuna is more challenging (Steffansson and Rosenberg, 2006) and may require the implementation of dynamic MPAs (see for instance Hobday and Hartmann, 2006).”
Dynamic ocean management: Defining and conceptualizing real-time management of the ocean (2015, unknown): “In the East Australian multispecies longline fishery, managers regulate fishing effort and allocate observer coverage for quota-managed southern bluefin tuna (Thunnus maccoyii) [39,40] using real-time habitat predictions based on tuna’s temperature-dependent habitat preferences (Fig.”