Integrating different approaches in the definition of biological stocks: A northern Australian multi-jurisdictional fisheries example using grey mackerel, Scomberomorus semifasciatus

Welch, David J.; Newman, Stephen J.; Buckworth, Rik C.; Ovenden, Jennifer R.; Broderick, Damien; Lester, R. J. G.; Gribble, Neil; Ballagh, Aaron C.; Charters, R.; Stapley, Jason; Street, Raewyn; Garrett, Rod N.; Begg, Gavin A.

doi:10.1016/j.marpol.2015.01.010

Cited by 32 publications

(75 citation statements)

References 24 publications

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“…In this study, the combined application of genetic markers, otolith chemistry and parasites across the same specimens provided three independent lines of evidence and considerable power to detect the highly complex population structure of P. diacanthus across northern Australia. Relatively few studies to date have used this integrated approach to investigate population structure and connectivity or for stock identification (Abuanza et al., 2008; Welch et al., ; Izzo et al., ). These studies also concluded that the integrated use of multiple techniques considerably improved confidence in stock identification using index of stock differences (ISD) thresholds definition (Izzo et al., ; Welch et al., ) and were particularly effective for species with broadly dispersing larvae or adults that exhibit little or no genetic structure across their range (Waldman, ).…”

Section: Discussionmentioning

confidence: 99%

Strong population structure deduced from genetics, otolith chemistry and parasite abundances explains vulnerability to localized fishery collapse in a large Sciaenid fish, Protonibea diacanthus

Taillebois

Barton

Crook

et al. 2017

Evolutionary Applications

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As pressure on coastal marine resources is increasing globally, the need to quantitatively assess vulnerable fish stocks is crucial in order to avoid the ecological consequences of stock depletions. Species of Sciaenidae (croakers, drums) are important components of tropical and temperate fisheries and are especially vulnerable to exploitation. The black‐spotted croaker, Protonibea diacanthus, is the only large sciaenid in coastal waters of northern Australia where it is targeted by commercial, recreational and indigenous fishers due to its food value and predictable aggregating behaviour. Localized declines in the abundance of this species have been observed, highlighting the urgent requirement by managers for information on fine‐ and broad‐scale population connectivity. This study examined the population structure of P. diacanthus across north‐western Australia using three complementary methods: genetic variation in microsatellite markers, otolith elemental composition and parasite assemblage composition. The genetic analyses demonstrated that there were at least five genetically distinct populations across the study region, with gene flow most likely restricted by inshore biogeographic barriers such as the Dampier Peninsula. The otolith chemistry and parasite analyses also revealed strong spatial variation among locations within broad‐scale regions, suggesting fine‐scale location fidelity within the lifetimes of individual fish. The complementarity of the three techniques elucidated patterns of connectivity over a range of spatial and temporal scales. We conclude that fisheries stock assessments and management are required at fine scales (100 s of km) to account for the restricted exchange among populations (stocks) and to prevent localized extirpations of this species. Realistic management arrangements may involve the successive closure and opening of fishing areas to reduce fishing pressure.

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Section: Discussionmentioning

confidence: 99%

Strong population structure deduced from genetics, otolith chemistry and parasite abundances explains vulnerability to localized fishery collapse in a large Sciaenid fish, Protonibea diacanthus

Taillebois

Barton

Crook

et al. 2017

Evolutionary Applications

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“…processes affecting the spatial structure of exploited species (Welch et al 2015;Hawkins et al 2016). There are several studies inferring spatial structures of species using different methods (Reiss et al 2009;Ovenden 2013;Welch et al 2015;Hawkins et al 2016). However, different sources of information have only been used for specific species, and not in a standardized way (as proposed for genetic data by Laikre et al 2005a) across species.…”

Section: Movement-effectsmentioning

confidence: 99%

“…) that broadly can be divided into three categories: (i) Molecular methods – relying on DNA/RNA or proteins; (ii) Demographic characters – population growth rates, harvest rates and age‐size distributions; and (iii) Individual phenotypic traits – morphometrics, size at age, size/age at maturation, geochemical markers, dispersal from tagging, parasite fauna (Begg and Waldman ; Bohonak ; Welch et al . ). If individuals are sampled as adults during mating or as offspring before dispersal, the spatial genetic structure enables identification of management units of reproducing individuals (Allendorf et al .…”

Section: Introductionmentioning

confidence: 99%

“…In recent years, integrated stock definition (ISD) has been advocated to infer and integrate different processes affecting the spatial structure of exploited species (Welch et al . ; Hawkins et al . ).…”

Section: Introductionmentioning

confidence: 99%

“…Assessing the spatial structure of species is many time complicated, and there are numerous methods for inferring spatial structures reflecting different aspects of populations (Lowe and Allendorf 2010;Cadrin et al 2014;Hawkins et al 2016) that broadly can be divided into three categories: (i) Molecular methodsrelying on DNA/ RNA or proteins; (ii) Demographic characterspopulation growth rates, harvest rates and age-size distributions; and (iii) Individual phenotypic traits morphometrics, size at age, size/age at maturation, geochemical markers, dispersal from tagging, parasite fauna (Begg and Waldman 1999;Bohonak 1999;Welch et al 2015). If individuals are sampled as adults during mating or as offspring before dispersal, the spatial genetic structure enables identification of management units of reproducing individuals (Allendorf et al 2008;Blower et al 2012;Funk et al 2012), reflecting where individuals reproduce, assortative mating among individuals, gene flow among locations (in absolute terms), effective population sizes (genetic drift), but also evolutionary history and evolutionary significant units (Waples and Gaggiotti 2006;Lowe and Allendorf 2010).…”

Section: Introductionmentioning

confidence: 99%

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Inferring spatial structure from population genetics and spatial synchrony in demography of Baltic Sea fishes: implications for management

et al. 2016

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The spatial structure of species is important for their dynamics and evolution, but also for management and conservation. There are numerous ways of inferring spatial structures, and information from multiple methods is becoming more common to examine how different processes shape the spatial structures of species to improve fish management. Here, we investigate the spatial structure of a suite of Baltic Sea fish species based on the following: (i) spatial (presumably neutral) genetic differentiation, reviewed from the literature, and (ii) spatial synchrony in abundance changes from time series of fishery‐independent surveys, which we currently find to be underused given the amount of data available. For each of these two methods, species were classified as having a distinct, continuous or no/weak spatial structure. In addition, based on each source of information, we estimated the spatial scale of management units for species. The results show that only among species confined to the coastal zone the two sources of information yielded a congruence of the spatial structure (displaying a continuous spatial structure). In contrast, offshore species show weak spatial genetic structure but stronger spatial structure of synchrony in abundance. Based on this, we suggest that population genetic structure and synchrony in abundance should be used as complementary information as they reflect different spatial processes and suggest that management actions should differ with respect to scale depending on the management targets applied. We propose similar analysis should be applied to areas outside the Baltic Sea, and other stock identification methods, to improve management of fish resources.

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Key aspects of the biology, fisheries and management of Coral grouper

Frisch

Cameron

Pratchett

et al. 2016

Rev Fish Biol Fisheries

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Integrating different approaches in the definition of biological stocks: A northern Australian multi-jurisdictional fisheries example using grey mackerel, Scomberomorus semifasciatus

Cited by 32 publications

References 24 publications

Strong population structure deduced from genetics, otolith chemistry and parasite abundances explains vulnerability to localized fishery collapse in a large Sciaenid fish, Protonibea diacanthus

Strong population structure deduced from genetics, otolith chemistry and parasite abundances explains vulnerability to localized fishery collapse in a large Sciaenid fish, Protonibea diacanthus

Inferring spatial structure from population genetics and spatial synchrony in demography of Baltic Sea fishes: implications for management

Key aspects of the biology, fisheries and management of Coral grouper

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