1 1 G. M. Pilling (graham.pilling@cefas.co.uk), P. Apostolaki and P. A. Large: Centre for Environment, Fisheries and Aquaculture Science, Pakefield Road, Lowestoft, Suffolk NR33 0HT, UK 2 P. Failler and C. Floros: Centre for the Economics and Management of Aquatic Resources (CEMARE), University of Portsmouth, UK 3 B. Morales-Nin: Institut Mediterrani d’Estudis Avançats, (IMEDEA, CSIC - UIB), Illes Balears, Spain 4 P. Reglero: Instituto Español de Oceanografía, Palma de Mallorca, Spain 5 K. I. Stergiou and A. C. Tsikliras: Aristotle University of Thessaloniki, School of Biology, Greece Assessment and management of data-poor fisheries Graham M. Pilling 1 , Panayiota Apostolaki 1 , Pierre Failler 2 , Christos Floros 2 , Philip A. Large 1 , Beatriz Morales-Nin 3 , Patricia Reglero 4 , Konstantinos I. Stergiou 5 and Athanassios C. Tsikliras 5 ABSTRACT: The problem of data-poor situations – where information is insufficient to estimate appropriate reference points and relative stock status – spans a wide range of fisheries all over the world, including some of the fisheries upon which Beverton and Holt published their work 50 years ago. Here, we look at a range of case studies to illustrate some of the approaches that have been, or have the potential to be, applied to meet the requirements of fisheries management where information is either lacking or highly uncertain. These approaches are diverse, ranging from more classic single-species approaches based upon catch, effort and biological information (tropical and deep-water examples), through the novel use of this information (calculation of catch trophic level in the Cyclades Islands of Greece) and information from markets (small-scale Spanish Mediterranean fisheries, UK inshore fisheries), to the incorporation of information from similar species or fisheries (blue shark in the Atlantic). Assessment should be driven by the aims of management, be they resource conservation, sustainable utilization, employment, economic viability, or a combination of these and other aims. Although many of the data- poor assessment methods applied concentrate on the assessment of biological resource status, methods to understand the economic drivers of fishers are also detailed. However, such approaches will only be successful where the will of management is strong enough to apply the precautionary approach in the face of uncertainty. In such cases, all available data should be considered and used to inform simple management guidelines and controls that are robust to the uncertainties within data-poor fisheries. Keywords: assessment, biology, data-poor, economics, management Pilling GM, Apostolaki P, Failler P, Floros C, Large PA, Morales-Nin B, Reglero P, Stergiou KI & Tsikliras AC (2008) Assessment and management of data-poor fisheries. In: A Payne, J Cotter, T Potter (eds) Advances in Fisheries science: 50 years on from Beverton and Holt, pp. 280-305. Blackwell Publishing, CEFAS.