Adrian Hordyk

Blue Matter Science

Length limit regulations are widely recommended to sustain fish biomass and fishery yields, particularly for dataand capacity-limited fisheries. However, previous findings were generally derived from equilibrium conditions, used hypothetical fisheries, and/or did not explicitly quantify the performance of length limits under a combination of implem...

Management strategy evaluation using the Method Evaluation and Risk Assessment (MERA) platform was used to evaluate management procedures (MPs) for improving the management of the leopard coral grouper (Plectropomus leopardus) fishery in Saleh Bay, Indonesia. This grouper is a valuable species currently under high fishing pressure. It is targeted b...

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...

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 o...

A retrospective pattern within a stock assessment occurs when historical estimates systematically increase or decrease as data are removed and has been cited as a cause of persistent overfishing. For two case studies, Gulf of Maine cod and New England pollock, we demonstrated how closed-loop simulation can be used to evaluate the impacts of retrosp...

The relationships between fecundity and size of Atlantic herring (Clupea harengus) were estimated within five different spawning areas off the coast of Nova Scotia in 2019 and 2020. Statistically significant differences in fecundity relative to body weight were observed among spawning areas and between years. Fecundity-at-length on the German Bank...

The precautionary approach to fisheries management advocates for risk‐averse management strategies that include biological reference points and account for scientific uncertainty (i.e. process, model and observation uncertainty). In this regard, two approaches have been recommended: (a) biomass reference points to safeguard against low stock biomas...

This is the proceedings from two workshops on 7 data-limited fisheries in Indonesia. It synthesises the available information and data on the biology, fisheries and management of the fisheries and the results from applying the Method Evaluation and Risk Assessment application (MERA). MERA was used to evaluate the effect of alternative management op...

Growth and recruitment overfishing can co-occur when a fishery is subjecting small and immature fish in conjunction with adult fish to excessive exploitation rates such that it reduces the spawning biomass to the point where recruitment is significantly impaired. Such conditions are generally evident in open-access fisheries and are especially detr...

The precautionary approach to fisheries management advocates for risk-averse management strategies that include biological reference points as well as decision rules and account for scientific uncertainty. In this regard, two approaches have been recommended: (i) harvest control rules (HCRs) with threshold reference points to safeguard against low...

The Group reviewed the most up-to-date swordfish (SWO) fishery statistics (T1NC: Task I nominal catches; T2CE: Task II catch & effort; T2SZ: Task II size frequencies; T2CS: Task II catch-at-size reported) and conventional tagging data, available in the ICCAT database system (ICCAT-DB). The three swordfish stocks (SWO-N: North Atlantic; SWO-S: South...

Small-scale fisheries (SSF) in southeast Asia contribute more food fish for human consumption than industrial fisheries and in Indonesia, employ almost 85% of the total fisheries employees. Grouper and snapper are commercially important species highly targeted, including by small-scale fishers. We estimate the spawning potential ratios (SPRs) of hi...

Fisheries management rights (FMRs), such as territorial use rights in fisheries (TURFs), are a promising approach for fisheries management that, if implemented on larger geographic scales, may be able to reduce the risk of fisheries decline, particularly for small-scale fisheries (SSF). SSF are significant throughout Asia, Africa and South America...

Quantitative assessment and management of small-scale fisheries is a persistent problem for fisheries. Crustaceans are particularly challenging for conventional techniques because their lack of permanent hard body parts makes ageing difficult. While a growing body of literature is aimed at developing alternative approaches to small-scale fisheries...

Stock assessments are often used to provide management advice, such as a total allowable catch (TAC), to fishery managers. Many stocks are not assessed annually, and the TAC from the previous assessment is often maintained in years between assessments. We developed two interim management procedures (MPs) that update the estimate of current vulnerab...

Oral presentation to Theme N "Data Limited tool an Management" in ICES Annual Science Conference 2019, Gothenburg, Sweden at 9-12 september

The Chilean sea urchin is one of the most economic, social and ecological important benthic invertebrate fishery in the world. Different data types exist to evaluate this population such as catch, an index of abundance and length composition from the catch. However, these data are not informative and for this reason the stock remains unassessed. In...

The Chilean sea urchin is one of the most economic, social and ecological important benthic invertebrate fishery in the world. Different data types exist to evaluate this population such as catch, an index of abundance and length composition from the catch. However, these data are not informative and for this reason the stock remains unassessed. In...

Common uncertainties in stock assessment relate to parameters or assumptions that strongly determine both the estimates of quantities of management interest (e.g. stock depletion) and related reference points (e.g. biomass at maximum sustainable yield). The risks associated with these uncertainties are often presented to managers in the form of dec...

Potential users of the model proposed by Froese et al. (2018) should be aware of several issues. First, the method to calculate equilibrium numbers-at-length is incomplete and leads to negatively biased estimates of fishing mortality. Second, inadequate simulation testing fails to reveal that the method is highly sensitive to assumptions of equilib...

El presente documento tiene como objetivo aplicar la metodologia del metodo de evualación de stock basado en datos pobres llamado Length-Based Spawning Potential Ratio (LBSPR) (Hordyk, 2014). En este ejercicio se estudia el caso de la almeja (Venus antiqua) de la región XI en el sur de Chile. Este adelanto metodológico se ha realizado en las 2 ulti...

This article describes a study undertaken in Fiji in order to develop a system of legal minimum size limits for reef fish. The study, which was supported primarily by the David and Lucile Packard Foundation and NZAID, involved a unique collaboration of international scientists from Biospherics Pty Ltd, Australia, University of British Columbia (UBC...

Small-scale capture fisheries have a very important place globally, but unfortunately are still mostly unregulated. Typically, they are defined based on capture fisheries characteristics, technical attributes of fishing vessels, and socio-economic attributes of fishers. Indonesia uses the term 'small-scale fisher’ (nelayan kecil), currently defined...

The Workshop on the Development of Quantitative Assessment Methodologies based on Life-history traits, exploitation characteristics, and other relevant parameters for stocks in categories 3–6 (WKLIFE VIII), chaired by Carl O'Brien (UK) and Manuela Azevedo (Portugal) met in Lisbon, Portugal, 8–12 October 2018, to further develop methods for stock as...

The cost, complexity and the lack of technical capacity in many countries have made the scientific assessment and sustainable management of data‐poor fisheries a persistent problem. New and innovative approaches are needed to stop the ongoing decline of data‐poor fisheries and loss of coastal biodiversity they are driving. In recent decades, marine...

A simulation‐based approach known as management strategy evaluation ( MSE ) is increasingly used by resource managers to identify management procedures that are robust to uncertainties in system dynamics. The majority of global fish populations are data limited and there is large uncertainty over their population and exploitation dynamics. The Data...

A new indicator is described that uses multivariate posterior predictive data arising from management strategy evaluation (MSE) to detect operating model misspecification (exceptional circumstances) due to changing system dynamics. The statistical power of the indicator was calculated for five case studies for which fishery stock assessments have e...

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 conv...

The relationship between the productivity and susceptibility scores and the probability of B < 0.2B0 as predicted by the PSA and the observed pattern for the multiplicative standard PSA (sPSA). Risk in each plot has been standardized to a minimum and maximum value of 0 and 1. (PNG)

The relationship between the productivity and susceptibility scores and the probability of B < 0.1B0 as predicted by the PSA and the observed pattern for the multiplicative standard PSA (sPSA). Risk in each plot has been standardized to a minimum and maximum value of 0 and 1. (PNG)

The relationship between the productivity and susceptibility scores and the probability of B < 0.2B0 as predicted by the PSA and the observed pattern for the additive extended PSA (ePSA). Risk in each plot has been standardized to a minimum and maximum value of 0 and 1. (PNG)

The relationship between the productivity and susceptibility scores and the probability of B < 0.5BMSY as predicted by the PSA and the observed pattern for the multiplicative standard PSA (sPSA). Risk in each plot has been standardized to a minimum and maximum value of 0 and 1. (PNG)

The relationship between the productivity and susceptibility scores and the probability of B < 0.2B0 as predicted by the PSA and the observed pattern for the additive standard PSA (sPSA). Risk in each plot has been standardized to a minimum and maximum value of 0 and 1. (PNG)

The relationship between the productivity and susceptibility scores and the probability of B < 0.1B0 as predicted by the PSA and the observed pattern for the additive standard PSA (sPSA). Risk in each plot has been standardized to a minimum and maximum value of 0 and 1. (PNG)

The relationship between the productivity and susceptibility scores and the probability of B < 0.5BMSY as predicted by the PSA and the observed pattern for the additive extended PSA (ePSA). Risk in each plot has been standardized to a minimum and maximum value of 0 and 1. (PNG)

The relationship between the productivity and susceptibility scores and the probability of B < 0.2B0 as predicted by the PSA and the observed pattern for the multiplicative extended PSA (ePSA). Risk in each plot has been standardized to a minimum and maximum value of 0 and 1. (PNG)

The relationship between the productivity and susceptibility scores and the probability of B < 0.5BMSY as predicted by the PSA and the observed pattern for the additive standard PSA (sPSA). Risk in each plot has been standardized to a minimum and maximum value of 0 and 1. (PNG)

The relationship between the productivity and susceptibility scores and the probability of B < 0.5BMSY as predicted by the PSA and the observed pattern for the multiplicative extended PSA (ePSA). Risk in each plot has been standardized to a minimum and maximum value of 0 and 1. (PNG)

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 0.1B0 under conditions of low, medium, and high exploitation rates. (PNG)

The relative contribution of the 7 productivity and 5 susceptibility (italics) attributes of the multiplicative extended PSA in explaining the variation of spawning biomass (B) at the end of the projection period being below 0.5BMSY under conditions of low, medium, and high exploitation rates. (PNG)

The relationship between the productivity and susceptibility scores and the probability of B < 0.1B0 as predicted by the PSA and the observed pattern for the multiplicative extended PSA (ePSA). Risk in each plot has been standardized to a minimum and maximum value of 0 and 1. (PNG)

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 0.2B0 under conditions of low, medium, and high exploitation rates. (PNG)

The relative contribution of the 7 productivity and 5 susceptibility (italics) attributes of the multiplicative extended PSA in explaining the variation of spawning biomass (B) at the end of the projection period being below 0.1B0 under conditions of low, medium, and high exploitation rates. (PNG)

The relationship between the productivity and susceptibility scores and the probability of B < 0.1B0 as predicted by the PSA and the observed pattern for the additive extended PSA (ePSA). Risk in each plot has been standardized to a minimum and maximum value of 0 and 1. (PNG)

The relative contribution of the 7 productivity and 5 susceptibility (italics) attributes of the multiplicative extended PSA in explaining the variation of spawning biomass (B) at the end of the projection period being below 0.2B0 under conditions of low, medium, and high exploitation rates. (PNG)

The relative contribution of the 5 productivity and 4 susceptibility (italics) attributes of the additive standard PSA in explaining the variation of spawning biomass (B) at the end of the projection period being below 0.1B0 under conditions of low, medium and high initial stock size (rows) and low, medium, and high exploitation rates (columns). (P...

Interaction plot of the 7 productivity and 5 susceptibility (italics) attributes of the additive extended PSA and the probablity of spawning biomass (B) ending below 0.5 BMSY at the end of the projection period with an exploitation rate of 0.2. (PNG)

Interaction plot of the 7 productivity and 5 susceptibility (italics) attributes of the additive extended PSA and the probablity of spawning biomass (B) ending below 0.2 B0 at the end of the projection period with an exploitation rate of 0.2. (PNG)

Interaction plot of the 7 productivity and 5 susceptibility (italics) attributes of the additive extended PSA and the probablity of spawning biomass (B) ending below 0.2 B0 at the end of the projection period with an exploitation rate of 0.4. (PNG)

Interaction plot of the 7 productivity and 5 susceptibility (italics) attributes of the additive extended PSA and the probablity of spawning biomass (B) ending below 0.1 B0 at the end of the projection period with an exploitation rate of 0.4. (PNG)

Interaction plot of the 7 productivity and 5 susceptibility (italics) attributes of the additive extended PSA and the probablity of spawning biomass (B) ending below 0.5 BMSY at the end of the projection period with an exploitation rate of 0.6. (PNG)

Scatterplots showing PSA Vulnerability scores (x-axis) and the probability of biomass being below 0.1B0 (y-axis) for the standard PSA (sPSA) using the additive method for calculating overall susceptibility score, for low, medium, and high initial stock size (rows) and low, medium, and high exploitation rate (columns). The gray shaded regions repres...

Scatterplots showing PSA Vulnerability scores (x-axis) and the probability of biomass being below 0.2B0 (y-axis) for the extended PSA (ePSA) using the multiplicative method for calculating overall susceptibility score, for low, medium, and high exploitation rate (columns). The gray shaded regions represent the 5th and 95th (light gray) and 25th and...

The relative contribution of the 5 productivity and 4 susceptibility (italics) attributes of the additive standard PSA in explaining the variation of spawning biomass (B) at the end of the projection period being below 0.2B0 under conditions of low, medium and high initial stock size (rows) and low, medium, and high exploitation rates (columns). (P...

The relative contribution of the 5 productivity and 4 susceptibility (italics) attributes of the multiplicative standard PSA in explaining the variation of spawning biomass (B) at the end of the projection period being below 0.5BMSY under conditions of low, medium and high initial stock size (rows) and low, medium, and high exploitation rates (colu...

The relative contribution of the 5 productivity and 4 susceptibility (italics) attributes of the multiplicative standard PSA in explaining the variation of spawning biomass (B) at the end of the projection period being below 0.1B0 under conditions of low, medium and high initial stock size (rows) and low, medium, and high exploitation rates (column...

Interaction plot of the 7 productivity and 5 susceptibility (italics) attributes of the additive extended PSA and the probablity of spawning biomass (B) ending below 0.2 B0 at the end of the projection period with an exploitation rate of 0.6. (PNG)

Interaction plot of the 7 productivity and 5 susceptibility (italics) attributes of the additive extended PSA and the probablity of spawning biomass (B) ending below 0.1 B0 at the end of the projection period with an exploitation rate of 0.2. (PNG)

Scatterplots showing PSA Vulnerability scores (x-axis) and the probability of biomass being below 0.2B0 (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 5th and 95th (light gray) and 25th and 75th...

The relative contribution of the 5 productivity and 4 susceptibility (italics) attributes of the multiplicative standard PSA in explaining the variation of spawning biomass (B) at the end of the projection period being below 0.2B0 under conditions of low, medium and high initial stock size (rows) and low, medium, and high exploitation rates (column...

Interaction plot of the 7 productivity and 5 susceptibility (italics) attributes of the additive extended PSA and the probablity of spawning biomass (B) ending below 0.1 B0 at the end of the projection period with an exploitation rate of 0.6. (PNG)

Scatterplots showing PSA Vulnerability scores (x-axis) and the probability of biomass being below 0.2B0 (y-axis) for the standard PSA (sPSA) using the additive method for calculating overall susceptibility score, for low, medium, and high initial stock size (rows) and low, medium, and high exploitation rate (columns). The gray shaded regions repres...

Scatterplots showing PSA Vulnerability scores (x-axis) and the probability of biomass being below 0.2B0 (y-axis) for the standard PSA (sPSA) using the multiplicative method for calculating overall susceptibility score, for low, medium, and high initial stock size (rows) and low, medium, and high exploitation rate (columns). The gray shaded regions...

Scatterplots showing PSA Vulnerability scores (x-axis) and the probability of biomass being below 0.1B0 (y-axis) for the standard PSA (sPSA) using the multiplicative method for calculating overall susceptibility score, for low, medium, and high initial stock size (rows) and low, medium, and high exploitation rate (columns). The gray shaded regions...

Scatterplots showing PSA Vulnerability scores (x-axis) and the probability of biomass being below 0.1B0 (y-axis) for the extended PSA (ePSA) using the multiplicative method for calculating overall susceptibility score, for low, medium, and high exploitation rate (columns). The gray shaded regions represent the 5th and 95th (light gray) and 25th and...

Scatterplots showing PSA Vulnerability scores (x-axis) and the probability of biomass being below 0.5BMSY (y-axis) for the standard PSA (sPSA) using the multiplicative method for calculating overall susceptibility score, for low, medium, and high initial stock size (rows) and low, medium, and high exploitation rate (columns). The gray shaded region...

Scatterplots showing PSA Vulnerability scores (x-axis) and the probability of biomass being below 0.1B0 (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 5th and 95th (light gray) and 25th and 75th...

Scatterplots showing PSA Vulnerability scores (x-axis) and the probability of biomass being below 0.5BMSY (y-axis) for the extended PSA (ePSA) using the multiplicative method for calculating overall susceptibility score, for low, medium, and high exploitation rate (columns). The gray shaded regions represent the 5th and 95th (light gray) and 25th a...

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 pengelo...

For over two decades, Indonesia has reported higher average shark landings than any other nation, but very little local information exists on the fishery and life histories of targeted species. This poses severe challenges to shark sustainability and conservation in this vast archipelago. We draw on diverse sources of data to evaluate the sustainab...

Selectivity in fish is often size-dependent, which results in differential fishing mortality rates across fish of the same age, an effect known as “Lee’s Phenomenon”. We extend previous work on using length composition to estimate the spawning potential ratio (SPR) for data-limited stocks by developing a computationally efficient length-structured...

Indonesia has the world’s largest shark fishery, but very little locally relevant information is available on catch statistics or life history characteristics of targeted species. This poses major challenges for fisheries management and shark conservation in the region, particularly in the more remote coastal communities of Eastern Indonesia. Shark...

New Zealand sea lions (Phocarctos hookeri) have suffered significant female-biased population loss from bycatch in sub-Antarctic squid fisheries (Chilvers 2009). Analyses on habitat use in juvenile sea lions have illustrated that females have increased spatial overlap with fisheries. Furthermore, the majority of dives by juvenile females coincide w...

The complexity and cost of assessment techniques prohibits their application to 90% of fisheries. Simple generic approaches are needed for the world's small-scale and data-poor fisheries. This meta-analysis of the relationship between spawning potential and the normalized size and age of 123 marine species suggests that the so-called Beverton–Holt...

The spawning potential ratio (SPR) is a well-established biological reference point, and estimates of SPR could be used to inform management decisions for data-poor fisheries. Simulations were used to investigate the utility of the length-based model (LB-SPR) developed in Hordyk et al. (this issue. Some explorations of the life history ratios to de...

Evaluating the status of data-poor fish stocks is often limited by incomplete knowledge of the basic life history parameters: the natural mortality rate (M), the von Bertalanffy growth parameters (L1 and k), and the length at maturity (Lm). A common approach to estimate these individual parameters has been to use the Beverton–Holt life history inva...

Acoustic methodologies are important tools for monitoring deep-water fish and have the potential to provide high-precision estimates of aggregation size. However, they can be costly to design and implement for monitoring fish. Data from 2 years of scientific surveys of the spawning aggregations of orange roughy (Hoplostethus atlanticus, Collett, 18...