Management strategy evaluation of the Queensland east coast sea cucumber fishery, with data to June 2023

The Queensland Sea Cucumber Fishery is a recreational and commercial fishery comprised of twenty-one sea cucumber species. The fishery has a dynamic history of species catch composition whereby the main target species were black teatfish (Holothuria whitmaei), then white teatfish (Holothuria fuscogilva) and presently burrowing blackfish (Actinopyga spinea) with opportunistic harvest of herrmanni curryfish (Stichopus herrmanni) and prickly redfish (Thelonata ananas). This is the second management strategy evaluation conducted on the Queensland sea cucumber fishery but the first by Fisheries Queensland. A management strategy evaluation of the Queensland sea cucumber fishery conducted by CSIRO in 2014 evaluated the benefits of the rotational harvest strategy (Skewes et al. 2014). While some specific results differ between the previous and current management strategy evaluation are difficult to compare as fishery reference points have been updated between reports, consistent conclusions were reached. Management strategy evaluation is a simulation tool for comparing the effectiveness of different management procedures against fishery objectives. The simulations capture the growth, reproduction, movement and mortality of a fish population and potential management procedures which dictate the fishery operating on the population. Uncertainty in these processes is characterised by running many simulations with slightly different biological specifications. The management procedures prescribe a mode of operation rather than a specific catch-limit or effort control. The performance of each management procedure is quantified to answer important management questions. Management procedures that perform well over a range of simulations are more likely to achieve the desired management goals. Well-performing management procedures become recommendations for the fishery. This management strategy evaluation was undertaken using the openMSE package developed by Blue Matter Science. The evaluation considered commercial catch and effort data spanning 1995 to 2023, biological data provided by Fishwell Consulting and Macquarie University and results from co-produced stock assessments. The biology of many sea cucumber species is unknown or uncertain and often places this taxon in a data-limited space. This applies to many species in the Queensland sea cucumber fishery and the data-limited nature of the fishery has been captured in this management strategy evaluation through an increased level of uncertainty for species biology. This management strategy evaluation found that the settings contained in the harvest strategy and other legislated and enforceable management arrangements are likely sufficient to meet the fishery’ objective of attaining maximum economic yield (defined in the harvest strategy as target biomass level of 60% of unfished biomass for stocks harvested in the fishery). The current management containing the rotational harvest strategy, catch limits and size limits management arrangements suggests the risk of depletion for most species was low

Stock assessment of Queensland east coast burrowing blackfish (Actinopyga spinea), with data to June 2023

Burrowing blackfish are species of sea cucumber from the family Holothuriidae that is found in northeastern Australia, New Caledonia, and possibly other Melanesian countries. In Australia, burrowing blackfish distributions extend along the entire Great Barrier Reef (GBR). They often occur in shallow to deeper depths from 1–25 m. This is the first stock assessment conducted on Queensland east coast burrowing blackfish by Fisheries Queensland. This stock assessment considered burrowing blackfish as three distinct populations, one associated with Gould Reef (Gould), one associated with the Capricorn Bunker Group (Bunker), and one associated with Lizard Island (Lizard). No stock assessment result is provided for Lizard. All assessment inputs and outputs are referenced on a financial year basis (that is, ‘2023’ means July 2022–June 2023). This assessment used a one-sex age-structured population model and a delay-difference model which led to similar results. The outputs of the age-structured model are presented as the main results for all three species in this assessment. The assessment incorporated commercial catch and effort data spanning 1995 to 2023 as well as length composition data and estimates of absolute abundance from recent surveys undertaken in 2023. No recreational or Indigenous catch data were available and catches from these sectors are considered negligible. There are no discards due to the highly selective nature of the fishery. Several Stock Synthesis scenarios were run to examine the implications of different fixed model parameters such as steepness (h) and natural mortality (M) on model outcomes. All scenarios were optimised using Markov chain Monte Carlo (MCMC) to better explore the robustness of the models. From these exploratory scenarios a final base case was chosen for each species. The base case Stock Synthesis results indicated that the biomass ratio of Gould at the beginning of 2024 financial year was between 51% and 101% of unfished levels. The base case Stock Synthesis results indicated that the biomass ratio of Bunker at the beginning of 2024 financial year was between 78% and 109% of unfished levels. The Lizard stock assessment modelling process failed to reconcile fishing pressure with the biomass decline observed through survey estimates of absolute biomass

Perfect simulation from unbiased simulation

We show that any application of the technique of unbiased simulation becomes perfect simulation when coalescence of the two coupled Markov chains can be practically assured in advance. This happens when a fixed number of iterations is high enough that the probability of needing any more to achieve coalescence is negligible; we suggest a value of $10^{-20}$. This finding enormously increases the range of problems for which perfect simulation, which exactly follows the target distribution, can be implemented. We design a new algorithm to make practical use of the high number of iterations by producing extra perfect sample points with little extra computational effort, at a cost of a small, controllable amount of serial correlation within sample sets of about 20 points. Different sample sets remain completely independent. The algorithm includes maximal coupling for continuous processes, to bring together chains that are already close. We illustrate the methodology on a simple, two-state Markov chain and on standard normal distributions up to 20 dimensions. Our technical formulation involves a nonzero probability, which can be made arbitrarily small, that a single perfect sample point may have its place taken by a "string" of many points which are assigned weights, each equal to $\pm 1$, that sum to~$1$. A point with a weight of $-1$ is a "hole", which is an object that can be cancelled by an equivalent point that has the same value but opposite weight $+1$.Comment: 17 pages, 4 figures; for associated R scripts, see https://github.com/George-Leigh/PerfectSimulatio

Untangling multi-species fisheries data with species distribution models

Long-term trends in fisheries catch are useful to monitor effects of fishing on wild populations. However, fisheries catch data are often aggregated in multi-species complexes, complicating assessments of individual species. Non-target species are often grouped together in this way, but this becomes problematic when increasingly common shifts toward targeting incidental species demand closer management focus at the species level. Species distribution models (SDMs) offer an under-utilised tool to allocate aggregated catch data among species for individual assessments. Here, we present a case study of two shovel-nosed lobsters (Thenus spp.), previously caught incidentally and recorded together in logbook records, to illustrate the design and use of catch allocation SDMs to untangle multi-species data for stock assessments of individual species. We demonstrate how catch allocation SDMs reveal previously masked species-specific catch trends from aggregated data and can identify shifts in fishing behaviour, e.g., changes in target species. Finally, we review key assumptions and limitations of this approach that may arise when applied across a broad geographic or taxonomic scope. Our aim is to provide a template to assist researchers and managers seeking to assess stocks of individual species using aggregated multi-species data

Stock assessment of Queensland east coast prickly redfish, herrmanni curryfish and vastus curryfish with data to December 2023

Prickly redfish, herrmanni curryfish and vastus curryfish are species of sea cucumber from the family Stichopodidae. All three species have a broad Indo-Pacific distribution and are found in multiple countries with coral reef ecosystems. All three species occur across the GBR but at varying depth ranges: 10-30 m for prickly redfish, 0-25 m for herrmanni curryfish and 0-8 m for vastus curryfish. This is the first stock assessment conducted on Queensland east coast prickly redfish, herrmanni curryfish and vastus curryfish by Fisheries Queensland. All assessment inputs and outputs are referenced on a calendar year basis (that is, ‘2023’ means January 2023–December 2023). This assessment used a one-sex age-structured population model and a delay-difference model which led to similar results. The outputs of the age-structured model are presented as the main results for all three species in this assessment. The assessment incorporated commercial catch and effort data spanning 1995 to 2023 as well as length composition data and estimates of absolute abundance from recent surveys undertaken in 2023. No recreational or Indigenous catch data were available and catches from these sectors are considered negligible. There are no discards due to the highly selective nature of the fishery. Several Stock Synthesis scenarios were run to examine the implications of different fixed model parameters such as steepness (h) and natural mortality (M) on model outcomes. All scenarios were optimised using Markov chain Monte Carlo (MCMC) to better explore the robustness of the models. From these exploratory scenarios a final base case was chosen for each species. The base case Stock Synthesis results indicated that the biomass ratio of prickly redfish at the beginning of 2024 was between 73% and 116% of unfished levels. The base case Stock Synthesis results indicated that the biomass ratio of herrmanni curryfish at the beginning of 2024 was between 81% and 141% of unfished levels. The base case Stock Synthesis results indicated that the biomass ratio of vastus curryfish at the beginning of 2024 was between 65% and 124% of unfished levels

Stock assessment of Queensland east coast endeavour prawns (Metapenaeus endeavouri and Metapenaeus ensis), Australia, with data to December 2021

Endeavour prawns (Metapenaeus endeavouri and Metapenaeus ensis) are endemic to the tropical and subtropical waters of Australia and are widely distributed along the coastline of northern Australia from Shark Bay in Western Australia to the eastern coast of northern New South Wales. The species live approximately two years and have a maximum observed size of 44 mm carapace length for female and 32 mm carapace length for male blue endeavour prawns and 41 mm carapace length for female and 33 mm carapace length for male red endeavour prawns. Sexual maturity is reached at approximately 6 months of age and around 24–26 mm carapace length. This is the first stock assessment conducted on Queensland east coast endeavour prawns by Fisheries Queensland. Assessment work carried out during a Master’s Thesis did not produce comparable outputs. This stock assessment includes input data through to December 2021. All assessment inputs and outputs were referenced on a calendar year basis (that is, ‘2021’ means January 2021–December 2021). The assessment used a one-sex monthly delay-difference population model, fitted to catch rates. An age-structured model was also trialled, however this did not lead to outcomes that were considered plausible by the project team. The model incorporated data spanning the period 1958 to 2021 including mandatory daily commercial logbook data collected by Fisheries Queensland (1988–2021), historic voluntary logbook data (1970–1988), Queensland Fish Board data (1958–1981), historic catch records (1958–2014), survey and logbook gear data collected by Fisheries Queensland (1988–2021), high resolution vessel tracking data collected by Fisheries Queensland (2000–2021) and lunar data (1958–2021). Length data collected by Fisheries Queensland (1998–2009) were also incorporated in a modelling scenario. The stock assessment was guided by a project team consisting of scientists, managers, and industry representatives. Fourteen scenarios were run using a delay-difference model, covering a range of modelling assumptions and sensitivity tests. All scenarios were optimised using Markov chain Monte Carlo (MCMC) to better explore the robustness of the models. Project team preferred scenario results indicated that the endeavour prawn stock experienced a decline from the period 1958 to 1997 to reach 34% of unfished biomass. The biomass has been steadily rising since this time, and in 2021 the stock level was estimated to be 69% of unfished biomass (54–87% range across the 95% credible interval)

Stock assessment of Queensland east coast red spot king prawns (Melicertus longistylus), Australia, with data to December 2021

Red spot king prawns (Melicertus longistylus, formerly known as Penaeus longistylus) are found in tropical waters of Australia from Shark Bay in Western Australia to near Yeppoon in Queensland. Red spot king prawns generally occur along the eastern coastline of Queensland above 22◦ S. The species live around two years and have a maximum observed size of 51 mm carapace length for females and 42 mm carapace length for males. Sexual maturity for females is reached at approximately 8 months of age and 33 mm carapace length. This is the first stock assessment conducted on Queensland east coast red spot king prawns by Fisheries Queensland. Assessment work carried out during a Master’s Thesis did not produce comparable outputs. This stock assessment includes input data through to December 2021. All assessment inputs and outputs were referenced on a calendar year basis (that is, ‘2021’ means January 2021–December 2021). The assessment used a one-sex monthly delay-difference population model, fitted to catch rates. An age-structured model was also trialled. The model incorporated data spanning the period 1958 to 2021 including mandatory daily commercial logbook data collected by Fisheries Queensland (1988–2021), historic voluntary logbook data (1980–1988), Queensland Fish Board data (1958–1981), historic catch records (1958–2014), survey and logbook gear data collected by Fisheries Queensland (1988–2021), high resolution vessel tracking data collected by Fisheries Queensland (2000–2021) and lunar data (1958–2021). Length data collected by Fisheries Queensland (1998–2009) were also incorporated in a modelling scenario. The stock assessment was guided by a project team consisting of scientists, managers, and industry representatives. Twenty-four scenarios were run using a delay-difference model, covering a range of modelling assumptions and sensitivity tests. All scenarios were optimised using Markov chain Monte Carlo (MCMC) to better explore the robustness of the models. The models had varying success across the 24 scenarios, with nine models achieving convergence. These nine scenarios resulted in a wide range of final biomass estimates, and some non-converged scenarios had better model fit. On this basis the stock level is reported as undefined. Full results for all 24 scenarios are presented in this report

Perfect simulation from unbiased simulation

We show that any application of the technique of unbiased simulation becomes perfect simulation when coalescence of the two coupled Markov chains can be practically assured in advance. This happens when a fixed number of iterations is high enough that the probability of needing any more to achieve coalescence is negligible; we suggest a value of 10−20. This finding enormously increases the range of problems for which perfect simulation, which exactly follows the target distribution, can be implemented. We design a new algorithm to make practical use of the high number of iterations by producing extra perfect sample points with little extra computational effort, at a cost of a small, controllable amount of serial correlation within sample sets of about 20 points. Different sample sets remain completely independent. The algorithm includes maximal coupling for continuous processes, to bring together chains that are already close. We illustrate the methodology on a simple, two-state Markov chain and on standard normal distributions up to 20 dimensions. Our technical formulation involves a nonzero probability, which can be made arbitrarily small, that a single perfect sample point may have its place taken by a "string" of many points which are assigned weights, each equal to ±1, that sum to~1. A point with a weight of −1 is a "hole", which is an object that can be cancelled by an equivalent point that has the same value but opposite weight +1

Stock assessment of Queensland east coast tiger prawns (Penaeus esculentus and Penaeus semisulcatus), Australia, with data to December 2021

‘Tiger prawn’ is a collective term for two species: brown tiger prawn (Penaeus esculentus) and grooved tiger prawn (P. semisulcatus). Brown tiger prawns are endemic to tropical and subtropical waters of Australia, while grooved tiger prawns have a wider Indo–West Pacific distribution. This assessment focuses on tiger prawns found on the eastern coast of Queensland. The species live at least two years and have a maximum observed size of 44 mm carapace length for brown females, 35 mm carapace length for brown males, 52 mm carapace length for grooved females and 38 mm carapace length for grooved males. Sexual maturity is reached at approximately 6 months of age and around 32–39 mm carapace length. A previous assessment estimated the Northern management region was 49% of unfished in 2019, and separately estimated the Central management region was at 50% of unfished in 2019. This assessment assumes a single tiger prawn population north of 22 degrees latitude and contains significant updates to data and methodology. This stock assessment includes input data through to December 2021. All assessment inputs and outputs were referenced on a calendar year basis (that is, ‘2021’ means January 2021–December 2021). The assessment used a one-sex monthly delay-difference population model, fitted to catch rates. An age-structured model was also trialled, however this did not lead to outcomes that were considered plausible by the project team. The model incorporated data spanning the period 1958 to 2021 including mandatory daily commercial logbook data collected by Fisheries Queensland (1988–2021), historic voluntary logbook data (1970–1988), Queensland Fish Board data (1958–1981), historic catch records (1958–2014), survey and logbook gear data collected by Fisheries Queensland (1988–2021), high resolution vessel tracking data collected by Fisheries Queensland (2000–2021) and lunar data (1958–2021). Length data collected by Fisheries Queensland (1998–2009) were also incorporated in a modelling scenario. The stock assessment was guided by a project team consisting of scientists, managers, and industry representatives. Ten scenarios were run using a delay-difference model, covering a range of modelling assumptions and sensitivity tests. All scenarios were optimised using Markov chain Monte Carlo (MCMC) to better explore the robustness of the models. Project team preferred scenario results indicated that the tiger prawn stock experienced a decline from the period 1958 to 1996 to reach 31% of unfished biomass. The biomass has been steadily rising since this time, and in 2021 the stock level was estimated to be 79% of unfished biomass (70–89% range across the 95% credible interval)

Stock assessment of Moreton Bay bugs (Thenus australiensis and Thenus parindicus) in Queensland, Australia with data to December 2021

Moreton Bay bugs are distributed throughout tropical and subtropical coastal waters of Australia from northern New South Wales to Shark Bay in Western Australia. The Moreton Bay bug population on the east coast of Queensland is comprised of two species—Thenus australiensis, also known as the sand or reef bug, and Thenus parindicus, also known as the mud bug. Sand bug females reach 50% maturity at 82 mm carapace width (CW) or 59 mm carapace length (CL). Mud bug females reach 50% maturity at 75 mm carapace width or 53 mm carapace length. Both species spawn year-round with spawning peaks during the period between spring and mid-summer. This is the first stock assessment conducted on Queensland Moreton Bay bugs. This stock assessment includes input data through to December 2021. All assessment inputs and outputs were referenced on a calendar year basis (that is, ‘2021’ means January 2021–December 2021). For all stocks analysed, the assessment used a one-sex monthly delay-difference population model, fitted to catch rates. Age-structured models were also trialed, however these did not lead to outcomes that were considered plausible by the project team. For sand bugs, the data from 1968 to 2021 comprised of commercial catch and effort (1988—2021), historical commercial catch (1968–1981, 1974–1987), fishery independent survey data (2017-2021) and licence numbers (1968–2003). For mud bugs, the data from 1948 to 2021 comprised of commercial catch and effort (1988-–2021), historical commercial catch (1948–1981, 1974–1987) and licence numbers (1968–2003). The model split the fishery into two fleets to account for the rezoning of the Great Barrier Reef (GBR) in 2004—one for the commercial sector pre-July 2004, and one for commercial sector post-July 2004. The stock assessment was guided by a project team consisting of scientists, managers, and industry representatives. Thirteen model scenarios were run for the sand bug stock, covering a range of modelling assumptions and sensitivity tests. All scenarios were optimised using Markov chain Monte Carlo (MCMC) to better explore the robustness of the models. Project team preferred scenario results suggested that the sand bug stock experienced a decline in the period 1968 to 2000 to reach 67% of unfished biomass. The biomass has been generally increasing since, and in 2021 the stock level was estimated to be 78% (63—94% range across the 95% credible interval) of the unfished biomass. Thirteen model scenarios were run for the mud bug stock, covering a range of modelling assumptions and sensitivity tests. Seven scenarios had convergence problems, or diagnostics that indicated issues. The non-target nature of the fishery combined with fishery-dependent catch rates being the primary data set for model tuning makes assessment difficult. The status of the mud bug stock is undefined. The general trajectory across the thirteen scenarios shows the biomass experienced a decline from the period of 1968 until the mid 1980s, then slowly recovered since that time