24 resultados para Vibrational contribution


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The process of invasion and the desire to predict the invasiveness (and associated impacts) of new arrivals has been a focus of attention for ecologists over centuries. The volunteer recording community has made unique and inspiring contributions to our understanding of invasion biology within Britain. Indeed information on non-native species (NNS) compiled within the GB Non-Native Species Information Portal (GB-NNSIP) would not have been possible without the involvement of volunteer experts from across Britain. Here we review examples of ways in which biological records have informed invasion biology. We specifically examine NNS information available within the GB-NNSIP to describe patterns in the arrival and establishment of NNS providing an overview of habitat associations of NNS in terrestrial, marine and freshwater environments. Monitoring and surveillance of the subset of NNS that are considered to be adversely affecting biodiversity, society or the economy, termed invasive non-native species (INNS), is critical for early warning and rapid response. Volunteers are major contributors to monitoring and surveillance of INNS and not only provide records from across Britain but also underpin the system of verification necessary to confirm the identification of sightings. Here we describe the so-called ‘alert system’ which links volunteer experts with the wider recording community to provide early warning of INNS occurrence. We highlight the need to increase understanding of community and ecosystem-level effects of invasions and particularly understanding of ecological resilience. Detailed field observations, through biological recording, will provide the spatial, temporal and taxonomic breadth required for such research. The role of the volunteer recording community in contributing to the understanding of invasion biology has been invaluable and it is clear that their expertise and commitment will continue to be so. © 2015 The Linnean Society of London, Biological Journal of the Linnean Society, 2015,

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Marine legislation is becoming more complex and marine ecosystem-based management is specified in national and regional legislative frameworks. Shelf-seas community and ecosystem models (hereafter termed ecosystem models) are central to the delivery of ecosystem-based management, but there is limited uptake and use of model products by decision makers in Europe and the UK in comparison with other countries. In this study, the challenges to the uptake and use of ecosystem models in support of marine environmental management are assessed using the UK capability as an example. The UK has a broad capability in marine ecosystem modelling, with at least 14 different models that support management, but few examples exist of ecosystem modelling that underpin policy or management decisions. To improve understanding of policy and management issues that can be addressed using ecosystem models, a workshop was convened that brought together advisors, assessors, biologists, social scientists, economists, modellers, statisticians, policy makers, and funders. Some policy requirements were identified that can be addressed without further model development including: attribution of environmental change to underlying drivers, integration of models and observations to develop more efficient monitoring programmes, assessment of indicator performance for different management goals, and the costs and benefit of legislation. Multi-model ensembles are being developed in cases where many models exist, but model structures are very diverse making a standardised approach of combining outputs a significant challenge, and there is a need for new methodologies for describing, analysing, and visualising uncertainties. A stronger link to social and economic systems is needed to increase the range of policy-related questions that can be addressed. It is also important to improve communication between policy and modelling communities so that there is a shared understanding of the strengths and limitations of ecosystem models.