18 research outputs found
Evaluating Atlantic bluefin tuna harvest strategies that use conventional genetic tagging data
An individual tagging model was implemented within the spatial, seasonal, multi-stock, multi-fleet operating models of the peer-reviewed Management Strategy Evaluation (MSE) framework for Atlantic bluefin tuna to evaluate the benefits of a harvest strategy that utilizes conventional gene tagging. A multi-year Brownie estimator was developed to test the accuracy and precision of exploitation rate estimates arising from gene tagging programs with various scenarios for spatial release distribution, release numbers and fishery exploitation rates. Harvest strategies that used the Brownie estimator were tested to evaluate yield and resource conservation performance relative to idealized management using perfect information. For the eastern stock, releasing 1,000 fish throughout the Atlantic and genotyping 27% of all landed fish at an estimated cost of US2.5M. Harvest strategies using the gene tagging data provided expected yield and resource conservation performance that was not substantially lower than a harvest strategy assuming using perfect information regarding vulnerable biomass. Reducing the number of releases most strongly affected the worst-case ‘lower-tail’ outcomes for West area yield and eastern stock biomass. Conventional gene tagging harvest strategies offer a promising basis for calculating management advice for Atlantic bluefin tuna that may be cheaper, simpler, and more robust than the current conventional stock assessment paradigm
KONSEP HAK PENGELOLAAN PERIKANAN SEBAGAI ALAT PENGELOLAAN PERIKANAN BERKELANJUTAN DI INDONESIA
Pengelolaan perikanan di Indonesia saat ini belum sepenuhnya mampu mengatasi motivasi perlombaan menangkap ikan. Kondisi yang dikenal sebagai open access ini, perlu segera diatasi untuk mencegah berlanjutnya tangkap lebih. Artikel ini bertujuan untuk menjelaskan konsep Hak Pengelolaan Perikanan (HPP), yang berpotensi diterapkan sebagai alat pengelolaan perikanan termasuk yang berada dekat pantai di Indonesia untuk mengatasi masalah perikanan open access. Metoda qualitative content analysis yang ditriangulasi melalui diskusi kelompok terfokus melibatkan para ahli, pengambil keputusan dan praktisi, digunakan untuk menjelaskan konsep HPP di Indonesia. Hasilnya menunjukkan bahwa pendekatan pengelolaan HPP melegitimasi entitas pemegang HPP mengamankan kesempatannya menangkap ikan secara ekslusif dengan mencegah pihak lain mengeksploitasi sumber daya ikan secara berlebihan. Pembelajaran dari negara lain menunjukkan bahwa HPP yang diintegrasikan kedalam kerangka rencana pengelolaan perikanan, bisa mengatasi permasalahan perikanan open access, karena mampu meredam motivasi dan tindakan nelayan dalam melakukan perlombaan menangkap ikan. Penggunaan ilmu pengetahuan kontemporer dan kearifan lokal dalam menentukan batasan tangkapan lestari dibarengi dengan upaya pemantauan dan penegakan aturan menentukan keberhasilan penerapannya. Terlihat juga bahwa praktek tradisional seperti Sasi di Maluku yang dimungkinkan oleh adanya pengakuan hak ulayat ‘petuanan laut’ merupakan konsep pemanfaatan sumber daya alam secara eksklusif yang selaras dengan esensi dari HPP. Direkomendasikan agar model pengelolaan berbasis HPP ini dilegitimasi kedalam peraturan perundang-undangan, termasuk Undang-Undang Perikanan Republik Indonesia. The existing management measures of Indonesian fisheries has not yet successfully resolved the overfishing. Fishers are still motivated to race for fish resources as typically occurs in an open access fisheries. This circumstance must be addressed immediately to prevent fisheries collapse. This research aims to describe a concept of Fisheries Management Rights (FMRs) as a management tool. This concept is potentially applicable in Indonesia, especially for near-shore fisheries. A qualitative content analysis method, triangulated through focus group discussions that involved experts, decision makers and practitioners was used to describe FMRs concept. The results indicated that this approach legitimizes the entities of the right holders to secure their exploitation right and to prevent others from over exploiting their fisheries resources. Lessons learnt from other countries showed that this approach that have been integrated within fisheries management plan, successfully addressed open access problem as it prevents fishers’ motivation to the race for fish. This approach need the contemporary and traditional sciences to inform allowable catch to ensure the success implementation. For instance, “Sasi”, traditional fishing right in Maluku is have similar framework with the contemporary FMRs. Therefore, FMRs should be acknowledged and adopted into Indonesian’ regulations to prevent the over-exploitatio
Method evaluation and risk assessment: A framework for evaluating management strategies for data-limited fisheries
Fisheries managers are in need of quantitative tools to inform decisions regarding selection of robust management practices, prioritising research gaps and stocks to focus on, particularly where there are limited resources or data. To support these decisions, the use of Management Strategy Evaluation (MSE), that is, closed loop simulation-testing of management procedures, is widely regarded as best practice. However, applying MSE is time- and computationally intensive, and requires highly skilled expertise and processes for stakeholder input and peer review. For data- and capacity-limited fisheries, MSE may be particularly challenging to implement. Yet, these are the contexts where it is most critical to test assumptions, evaluate the implications of all sources of uncertainty and identify the most informative data sources. To facilitate wider use of MSE, the Method Evaluation and Risk Assessment (MERA) framework was developed as an accessible online interface, with quick processing time, focused on generic data-limited management procedures, but allowing progression to tailored and more data-rich methods. The framework links a quantitative questionnaire and data input standard to a flexible operating model with optional customisation via command line access to the back-end open-source R libraries. Here, we illustrate a case study application of MERA for the bocinegro (Pagrus pagrus, Sparidae) fishery in the Gulf of Cadiz, where in conjunction with fishery stakeholders, a custom management procedure was developed and tested and key research gaps and data collection priorities were identified. We discuss implications for wider use of MSE in various contexts, including eco-certification and fishery improvement projects.MERA was initially commissioned by the Marine Stewardship Council, and benefits from the ongoing support of the David & Lucile Packard Foundation, the Marine Stewardship Council, the Natural Resources Defense Council, the Walton Family Foundation and the United Nations Food and Agricultural Organization.Peer reviewe
Using management strategy evaluation to establish indicators of changing fisheries
A new indicator is described that uses multivariate posterior predictive data arising from management strategy evaluation (MSE) to detect operating model misspecification (â exceptional circumstancesâ ) due to changing system dynamics. The statistical power of the indicator was calculated for 5 case studies for which fishery stock assessments have estimated changes in recruitment, natural mortality rate, growth, fishing efficiency and size selectivity. The importance of the component data types that inform the indicator was also calculated. The indicator was tested for multiple types of management procedures (e.g. catch limits by stock assessment, size limits, spatial closures) given varying qualities of data. The statistical power of the indicator could be high even over short time periods and depended on the type of system change and quality of data. Statistical power depended strongly on the type of management approach, suggesting that indicators should be established that rigorously account for feedbacks between proposed management and observed data. Management strategy evaluation processes should use alternative operating models to evaluate protocols for exceptional circumstances to ensure they are of acceptable statistical power.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author
A quantitative evaluation of a qualitative risk assessment framework: Examining the assumptions and predictions of the Productivity Susceptibility Analysis (PSA)
<div><p>Qualitative risk assessment frameworks, such as the Productivity Susceptibility Analysis (PSA), have been developed to rapidly evaluate the risks of fishing to marine populations and prioritize management and research among species. Despite being applied to over 1,000 fish populations, and an ongoing debate about the most appropriate method to convert biological and fishery characteristics into an overall measure of risk, the assumptions and predictive capacity of these approaches have not been evaluated. Several interpretations of the PSA were mapped to a conventional age-structured fisheries dynamics model to evaluate the performance of the approach under a range of assumptions regarding exploitation rates and measures of biological risk. The results demonstrate that the underlying assumptions of these qualitative risk-based approaches are inappropriate, and the expected performance is poor for a wide range of conditions. The information required to score a fishery using a PSA-type approach is comparable to that required to populate an operating model and evaluating the population dynamics within a simulation framework. In addition to providing a more credible characterization of complex system dynamics, the operating model approach is transparent, reproducible and can evaluate alternative management strategies over a range of plausible hypotheses for the system.</p></div
Similarity scores of the observed relationship between the productivity and susceptibility scores and risk compare to that assumed by the PSA.
<p>The similarity scores of the observed relationship between the productivity and susceptibility scores and risk compare to that assumed by the PSA for the standard PSA (sPSA) with low, medium and high initial stock status (black circle, triangle and square respectively) and the extended PSA (ePSA) for three quantitative measures of risk (columns) and three future exploitation rates (rows). The results are shown for both the additive and multiplicative method for calculating the overall susceptibility score (x-axis).</p
The assumed and observed relationship between productivity and susceptibility scores and risk.
<p>The relationship between the productivity and susceptibility scores and risk assumed by the PSA (top left) and the observed patterns for the analysis with the highest similarity score (top right; additive ePSA with low exploitation rate and B < 0.2B<sub>0</sub> reference point), mean similarity score (bottom left; multiplicative sPSA with low initial stock size, high exploitation rate and B < 0.1B<sub>0</sub> reference point) and the lowest similarity score (bottom right; multiplicative sPSA with high initial stock size, high exploitation rate and B < 0.2B<sub>0</sub> reference point). Risk in each plot has been standardized to a minimum and maximum value of 0 and 1 and the similarity score is shown in white text in the top right corner of each plot.</p
The productivity and susceptibility attributes and the risk categories used for the standard PSA (sPSA) and the extended PSA (ePSA).
<p>The productivity and susceptibility attributes and the risk categories used for the standard PSA (sPSA) and the extended PSA (ePSA).</p
Scatterplots of PSA vulnerability scores and quantitative measure of risk for the extended PSA.
<p>Scatterplots showing PSA vulnerability scores (x-axis) and the probability of biomass being below 0.5<i>B</i><sub>MSY</sub> (y-axis) for the extended PSA (ePSA) using the additive method for calculating overall susceptibility score, for low, medium, and high exploitation rate (columns). The gray shaded regions represent the 5<sup>th</sup> and 95<sup>th</sup> (light gray) and 25<sup>th</sup> and 75<sup>th</sup> (dark gray) percentiles of applications of the ePSA [<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0198298#pone.0198298.ref020" target="_blank">20</a>] and show that the scores for most applications fall within the mid-range values of the vulnerability score.</p
The relative contribution of the productivity and susceptibility attributes to overall risk for the exended PSA.
<p>The relative contribution of the 7 productivity and 5 susceptibility (italics) attributes of the additive extended PSA in explaining the variation of spawning biomass (B) at the end of the projection period being below 0.5B<sub>MSY</sub> under conditions of low, medium, and high exploitation rates.</p