3 research outputs found

    The Physics of the B Factories

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    Improving guidelines for implementing harvest strategies in capacity-limited fisheries – Lessons from Tonga's deepwater line fishery

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    © 2018 Elsevier Ltd The majority of the world's fisheries lack formal management and assessment due to limitations in data, management capacity, or both. Capacity-limited fisheries generally contain some combination of limited infrastructure, personnel or expertise which hampers the ability of fisheries administrations to develop, implement and maintain desired management structures. Fisheries that fall within this category are at greater risk of performing poorly in terms of sustainability and economic benefits. In the process of applying a number of recently developed data-poor specific tools to Tonga's deepwater line fishery, it was apparent that reconciling the lack of resources with options for management required greater attention. Some of the challenges encountered are highlighted herein and processes to consider in order to overcome these are discussed. This resulted in a reprioritisation of the stepwise processes often used to develop harvest strategies by giving earlier prominence to management capacity and stakeholder engagement within a more iterative framework. This provides capacity-limited managers with a mechanism to develop a coherent harvest strategy across all components that is more viable long-term, irrespective of available management resources. Our case study extends the discussion on harvest strategies from data-rich to data-poor fisheries to include those fisheries that are both data-poor and capacity-limited. Application of formalised harvest strategies has been promoted as a tool to relieve the excessive fishing pressure apparent in many regions. The proposed refinements to the harvest strategy development process proposed here should improve capacity for fisheries management in circumstances where it is lacking

    Evolution of genes and genomes on the Drosophila phylogeny

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    Comparative analysis of multiple genomes in a phylogenetic framework dramatically improves the precision and sensitivity of evolutionary inference, producing more robust results than single-genome analyses can provide. The genomes of 12 Drosophila species, ten of which are presented here for the first time (sechellia, simulans, yakuba, erecta, ananassae, persimilis, willistoni, mojavensis, virilis and grimshawi), illustrate how rates and patterns of sequence divergence across taxa can illuminate evolutionary processes on a genomic scale. These genome sequences augment the formidable genetic tools that have made Drosophila melanogaster a pre-eminent model for animal genetics, and will further catalyse fundamental research on mechanisms of development, cell biology, genetics, disease, neurobiology, behaviour, physiology and evolution. Despite remarkable similarities among these Drosophila species, we identified many putatively non-neutral changes in protein-coding genes, non-coding RNA genes, and cis-regulatory regions. These may prove to underlie differences in the ecology and behaviour of these diverse species
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