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The benefits of physiological biomarkers, knowledge and concepts are well-established in fish and wildlife management as they confer the ability to understand mechanistic processes, identify cause-and-effect relationships, and develop predictive models. Although this approach is gaining momentum in the context of species conservation, the use of physiological biomarkers in exploited marine fish stock management and recovery plans remains relatively rare. Here, we present five essential issues to consider to implement physiological biomarkers in fisheries management: (i) choice of relevant biomarkers that have a well-known mechanistic basis, (ii) identification of species-specific biomarkers reflecting a meaningful timespan for management, (iii) selection of biomarkers compatible with data collection during routine scientific fisheries surveys, (iv) use of biomarkers as early-warning signals and complementary indicators of population-level changes in life history traits and (v) how physiological biomarkers may help to refine long-term population dynamic projections under climate change and management scenarios. Overall, if based on well-established mechanisms linked to individuals' fitness, a focus on physiological biomarkers should help to better understand the mechanisms behind stock declines, changes in stock characteristics, and thus more efficiently manage marine fisheries and conserve populations. As this approach is transferable among species, locations, and times, the integration of physiological biomarkers in fisheries science has the potential to more broadly enhance assessments and management of fish stocks. [ABSTRACT FROM AUTHOR]

In the summer of 2004, a video survey was carried out in the northern part of the central mud bank (Grande Vasière) of the Bay of Biscay to study the small scale relationship between the dominant crustacean megafauna Nephrops norvegicus, Munida rugosa and Goneplax rhomboides and juvenile hake ( Merluccius merluccius). Using a towed body, high-resolution videos were recorded in six sampling sites. Statistical modelling using generalised additive models (GAM) revealed variations in activity patterns for two species. More N. norvegicus were observed outside their burrows at dawn and somewhat at dusk (no observations during night) while G. rhomboides was less observed in the morning. In addition, reduced spatial overlap between G. rhomboides and N. norvegicus suggested reduced competition for food but also space as both are burrowing species. The observed temporal and spatial activity patterns may contribute to regulating assemblage structure as competing species may be actively foraging at different times and locations thus reducing direct competition. [ABSTRACT FROM AUTHOR]