Site fidelity,survival and conservation options for the threatened flapper skate (Dipturus cf. intermedia)

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Stock assessment modeling provides a means to estimate the population dynamics of invasive fishes and may do so despite data limitations. Blue catfish (Ictalurus furcatus) were introduced to the Chesapeake Bay watershed to support recreational fisheries but also consume species of conservation need and economic importance. To assess management tradeoffs, managers need to understand the current status of the population and anticipate future population abundance and trends. A Bayesian size-based stock assessment model was used to estimate blue catfish abundance, fishing mortality, and size structure over time (2001–2016) in the tidal James River. The model estimated population size increases until around 2006, with declines in total abundance after 2011 and large blue catfish (≥80 cm total length) after 2001. These first estimates of blue catfish population dynamics in the Chesapeake Bay region provide inputs for projection models to evaluate prospective management actions and identify monitoring needs.     

Nineteenth century narratives reveal historic catch rates for Australian snapper (Pagrus auratus)

Snapper (Pagrus auratus) is widely distributed throughout subtropical and temperate southern oceans and forms a significant recreational and commercial fishery in Queensland, Australia. Using data from government reports, media sources, popular publications and a government fisheries survey carried out in 1910, we compiled information on individual snapper fishing trips that took place prior to the commencement of fisherywide organized data collection, from 1871 to 1939. In addition to extracting all available quantitative data, we translated qualitative information into bounded estimates and used multiple imputation to handle missing values, forming 287 records for which catch rate (snapper fisher^?1 h^?1) could be derived. Uncertainty was handled through a parametric maximum likelihood framework (a transformed trivariate Gaussian), which facilitated statistical comparisons between data sources. No statistically significant differences in catch rates were found among media sources and the government fisheries survey. Catch rates remained stable throughout the time series, averaging 3.75 snapper fisher^?1 h^?1 (95% confidence interval, 3.42–4.09) as the fishery expanded into new grounds. In comparison, a contemporary (1993–2002) south‐east Queensland charter fishery produced an average catch rate of 0.4 snapper fisher^?1 h^?1 (95% confidence interval, 0.31–0.58). These data illustrate the productivity of a fishery during its earliest years of development and represent the earliest catch rate data globally for this species. By adopting a formalized approach to address issues common to many historical records – missing data, a lack of quantitative information and reporting bias – our analysis demonstrates the potential for historical narratives to contribute to contemporary fisheries management.     

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There can be substantial differences in data quality and quantity among fished species. Consequently, the quality and type of assessments can also vary substantially. However, all species, especially those that are targeted, need to be managed. Several jurisdictions have developed hierarchical tier systems that categorize stocks based on, for example, the data available for assessment purposes and/or the extent to which quantities on which management advice is based can be estimated. Four case‐studies (Australia's Southern and Eastern Scalefish and Shark Fishery, the USA west coast groundfishery, the USA Alaskan crab fishery and EU fisheries) are used to contrast the types of hierarchical tier systems available, and to assess the extent to which each system constrains risk to be equivalent among the tiers (termed risk equivalency). Only the Australian system explicitly aims to achieve risk equivalency. However, this intent has not been fully operationalized. Our review reveals that best practice is not to define tiers simply on data availability, but also on what the assessments based on those data are capable of estimating. In addition, clearly differentiating the quantification of uncertainty from how decision‐makers wish to address that uncertainty would simplify justification of buffers (the gap between the assessment‐produced target catch or effort and the final management decision that accounts for uncertainty and risk). Risk equivalency can be achieved using management strategy evaluation to select the values for control variables, which determine the buffer given the uncertainty associated with the assessment.