A novel size-based method for assessing the spawning potential ratio of data-poor octopus fisheries

Jeremy D. Prince^1,2Indah Rufiati^3*Wahyu Dita Septiani³Duranta Diandria Kembaren⁴Charlotte Louise Anne Gough^3,5

• ¹Biospherics P/L, South Fremantle, Western Australia, Australia, South Fremantle, Australia
• ²School of Veterinary and Life Sciences, Murdoch University, Murdoch, Western Australia, Australia, Murdoch, Australia
• ³Blue Ventures, London, United Kingdom
• ⁴Badan Riset dan Inovasi Nasional Republik Indonesia, Central Jakarta, Indonesia
• ⁵Centre for Ecology and Conservation, College of Life and Environmental Sciences, University of Exeter, Cornwall, United Kingdom, Cornwall, United Kingdom

Cephalopod biology, which is characaterised by short lifespans, semelparous reproduction, rapid non-asymptotic growth, and seasonally fluctuating biomass, presents a particular challenge stock assessment. Small scale, data-poor artisanal octopus fisheries are an increasingly important source of food and income for coastal fishing communities but pose a particularly pernicious assessment challenge. We developed and tested a novel size-based data-poor assessment methodology, demonstrating its applicability with 17 Indonesian fisheries for Octopus cyanea. The Short-Lived Assessment Model (SLAM) is similar to Length-based Spawning Potential Ratio Assessment (LBSPR) and Length-based Integrated Mixed Effects (LIME) methodologies, in assuming that taxa share both growth curves and a relativity between maximum size and size of maturity. Incorporating a power curve form of growth typical of cephalopods and monthly time steps SLAM estimates selectivity at age schedules, monthly fishing mortality rates (F) and spawning potential ratio (SPR). A minimum of 12 monthly samples of catch at weight data (CAW) are required, but longer time series and additional indices of effort and/or catch will produce more reliable results. SLAM's structure is flexible; with <24 months of CAW it parallels LBSPR in assuming equilibrium dynamics and constant monthly recruitment. With >24 months of CAW, a dynamic structure becomes possible similar to LIME, and seasonal recruitment patterns can be estimated.