ORCID Profile
0000-0002-9358-1013
Current Organisation
CSIRO
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Publisher: CSIRO Publishing
Date: 2011
DOI: 10.1071/MF10279
Abstract: Climate change presents significant challenges to modelling and managing aquatic resources. Equilibrium assumptions common in many modelling approaches need to be replaced by formulations that allow for changing baselines and integration of ongoing changes and adaptations by species, ecosystems and humans. As ecosystems change, so will the ways humans use, monitor and manage them. Consequently, adaptive management loops and supporting tools deserve more prominence in the management toolbox. Models are critical tools for providing an early understanding of the challenges to be faced by integrating observations and examining possible solutions. We review modelling tools currently available to incorporate the effect of climate change on marine and freshwater ecosystems, and the implications for management of natural resources. System non-linearity can confound interpretations and hence adaptive management responses are needed that are robust to unexpected outcomes. An improvement in the ability to model the effects of climate change from a social and economic perspective is necessary. The outputs from ‘end-to-end’ and socio-ecological models can potentially inform planning, in both Australia and the Pacific region, about how best to build resilience to climate change. In this context, the importance of well directed data-collection programs is also emphasised. Lessons from this region, which is advanced with regard to modelling approaches, can guide increased use of models to test options for managing aquatic resources worldwide.
Publisher: CSIRO Marine and Atmospheric Research
Date: 2013
Publisher: Elsevier BV
Date: 04-2011
Publisher: Wiley
Date: 07-08-2008
Publisher: CSIRO
Date: 2019
Publisher: SciELO Agencia Nacional de Investigacion y Desarrollo (ANID)
Date: 1997
Publisher: Oxford University Press (OUP)
Date: 28-01-2019
Abstract: To assess fishing effects on data-poor species, impact can be derived from spatial overlap between species distribution and fishing effort and gear catchability. Here, we enhance the existing sustainability assessment for fishing effect method by estimating gear efficiency and heterogeneous density from sporadic catch data. We apply the method to two chondrichthyan bycatch species, Bight Skate and Draughtboard Shark in Australia, to assess cumulative fishing mortality (Fcum) from multiple fisheries. Gear efficiency is estimated from a Bayesian mixture distribution model and fish density is predicted by a generalized additive model. These results, combined with actual fishing effort, allow estimation of fishing mortality in each sector and subsequently, the Fcum. Risk is quantified by comparing Fcum with reference points based on life history parameters. When only the point estimates were considered, our result indicates that for the period 2009 and 2010 Bight Skate caught in 14 fisheries was at high cumulative risk (Fcum ≥ Flim) while Draughtboard Shark caught by 19 fisheries was at low cumulative risk (Fcum ≤ Fmsy). Because of the high cost of conducting cumulative risk assessments, we recommend examining the distribution of fishing effort across fisheries before carrying out the assessments.
Publisher: American Association for the Advancement of Science (AAAS)
Date: 02-03-2012
Abstract: Balanced fishing across a range of species, stocks, and sizes could mitigate adverse effects and address food security better than increased selectivity.
Publisher: Wiley
Date: 05-2006
DOI: 10.1577/T04-204.1
Publisher: Wiley
Date: 08-2007
Publisher: Cambridge University Press (CUP)
Date: 10-05-2013
DOI: 10.1017/S037689291300012X
Abstract: Fisheries bycatch threatens populations of marine megafauna such as marine mammals, turtles, seabirds, sharks and rays, but fisheries impacts on non-target populations are often difficult to assess due to factors such as data limitation, poorly defined management objectives and lack of quantitative bycatch reduction targets. Limit reference points can be used to address these issues and thereby facilitate adoption and implementation of mitigation efforts. Reference points based on catch data and life history analysis can identify sustainability limits for bycatch with respect to defined population goals even when data are quite limited. This can expedite assessments for large numbers of species and enable prioritization of management actions based on mitigation urgency and efficacy. This paper reviews limit reference point estimators for marine megafauna bycatch, with the aim of highlighting their utility in fisheries management and promoting best practices for use. Different estimators share a common basic structure that can be flexibly applied to different contexts depending on species life history and available data types. Information on demographic vital rates and abundance is required of these, abundance is the most data-dependent and thus most limiting factor for application. There are different approaches for handling management risk stemming from uncertainty in reference point and bycatch estimates. Risk tolerance can be incorporated explicitly into the reference point estimator itself, or probability distributions may be used to describe uncertainties in bycatch and reference point estimates, and risk tolerance may guide how those are factored into the management process. Either approach requires simulation-based performance testing such as management strategy evaluation to ensure that management objectives can be achieved. Factoring potential sources of bias into such evaluations is critical. This paper reviews the technical, operational, and political challenges to widespread application of reference points for management of marine megafauna bycatch, while emphasizing the importance of developing assessment frameworks that can facilitate sustainable fishing practices.
Publisher: Wiley
Date: 11-2000
Publisher: Springer Science and Business Media LLC
Date: 11-06-2019
Publisher: Wiley
Date: 03-02-2015
DOI: 10.1111/FAF.12077
Publisher: Oxford University Press (OUP)
Date: 22-04-2016
Abstract: Since “balanced harvest” was proposed in 2010 as a possible tool in the operationalization of the ecosystem approach to fisheries (EAF), the concept gained extensive international attention. Because maintaining ecosystem structure and achieving maximum sustainable yields have become two of the key international legal obligations in fisheries management, balanced harvest is as topical as ever. An international workshop on balanced harvest, organized by the IUCN Fisheries Expert Group at FAO headquarters in 2014, reviewed the progress in the field and discussed its prospects and challenges. Several articles in this theme set, mostly based on presentations from the workshop, discuss ecological, economical, legal, social, and operational issues surrounding the key management goals. Progress is being made on understanding of the theoretical underpinnings of balanced harvest and its practical feasibility. Yet, a basic debate on the concept of balanced harvest continues. To move the EAF forward, we anticipate and encourage further research and discussion on balanced harvest and similar ideas.
Publisher: Wiley
Date: 14-11-2022
DOI: 10.1111/FAF.12627
Abstract: Sharks (class Chondrichthyes, subclass Elasmobranchii) typically have a long lifespan, slow growth rate and low fecundity, leading to low productivity and hence relatively high vulnerability to fishing. Information for managing fisheries catches of elasmobranchs is often lacking, because elasmobranchs are usually non‐target species, often with low abundance. It is more feasible to develop management reference points for elasmobranchs based on their life‐history information than through traditional stock assessments. The natural mortality rate ( M ) is the leading life‐history parameter (LHP) required by many methods for developing reference points and is itself often derived indirectly from other LHPs. In this paper, we evaluate nine M estimators, using 15 shark stocks in the Western and Central Pacific Ocean as ex les. We then compare four methods for developing fishing mortality reference points F msy , including empirical modelling, the Euler‐Lotka equation, an M ‐productivity‐based method and the spawning potential rate converted method. Our analyses show that popular M estimators developed mainly from teleost data resulted in large deviations from the average and were not suitable for elasmobranchs. All four methods for estimating F msy performed similarly. However, the empirical method is very simple and cost‐effective and tended to produce smaller deviations from the average than the other three methods. Nonetheless, it is recommended that multiple methods should be used to minimize possible bias and reflect uncertainty, if the required LHPs are available.
Publisher: CSIRO Publishing
Date: 2015
DOI: 10.1071/MF14146
Abstract: Tropical sea cucumbers are commonly exploited by small-scale, poorly managed fisheries. A fundamental problem in managing sea cucumber fisheries is the lack of basic knowledge of important life history characteristics for most species. As a result of plastic body dimensions, biological research on this group of animals becomes exceptionally challenging. To improve our understanding of essential biological parameters, we conducted a study to investigate correlations among various body measurements. We analysed a total of 18 sea cucumber species and more than 6600 in iduals collected at Scott Reef in the Timor Sea, north-west Australia. We used hierarchical Bayesian errors-in-variables models to specifically take into account measurement errors that are obviously unavoidable. The measures included three types of weights (wet weight, gutted weight and dry weight) and two body dimensions (length and width). The modelling reveals that using both body length and width as independent variables, wet weight increases approximately linearly with body length, but is a power function (~1.6) of body width, although variability exists among species. Dry weight tends to increase more slowly with body length, but has a similar power function of body width. Linear relationships are established between the three types of weights. On average, ~11% of a live specimen and ~16% of a gutted specimen is processed to the commercially traded dry body wall. Our results can be applied to sea cucumbers in other areas and can be useful for data standardisation and size-based fisheries management.
Publisher: Inter-Research Science Center
Date: 27-12-2017
DOI: 10.3354/MEPS12402
Publisher: CSIRO Publishing
Date: 2008
DOI: 10.1071/MF07090
Abstract: Abundance and catchability are crucial quantities in fisheries management, yet they are very difficult to estimate, particularly for short-lived invertebrates. Using two distinct approaches – a standard non-hierarchical model (NH) and a hierarchical Bayesian model (HB) – abundance and catchability coefficients from a fishery depletion process for banana prawns (Penaeus merguiensis) in northern Australia were estimated. Non-hierarchical models treated each stock and year separately and in idually, whereas the hierarchical models assumed some form of common underlying population from which the parameters for the in idual cases generated by the combination of stock and year were drawn. Two HBs were considered. In HB1 it was assumed that annual abundance and catchability parameters came from separate populations, or distributions, for each stock. In HB2 it was assumed that these stock region distributions were not separate, but had their parameters drawn from a common distribution. Thus in HB2 all stocks shared information at the regional level. The results for both NH and HB methods were similar in most cases, indicating a fair degree of stability irrespective of the particular form of model chosen. However, the NH method suffered because the data were analysed in generally small sections and in many cases these sections were too small to allow precise estimation of both parameters and confidence intervals. The deviations of point estimates between the HB1, HB2 and NH models were more marked in catchability coefficient estimates than in abundance estimates, and large relative deviations typically occurred in stock regions and years with low fishing efforts, low catch or poor depletion trends over time. We conclude that the combined analysis using HB was superior because it could handle limited data, yielded credible interval estimates for all parameters and was computationally more efficient.
Publisher: Frontiers Media SA
Date: 10-06-2021
DOI: 10.3389/FMARS.2021.581952
Abstract: Due to persistent fishing expansion in the China Seas over the past six decades, fisheries resources have been over-exploited as a result, exploited fish have become smaller in size and younger in age. Marine piscivorous fish constituted a large portion of Chinese fisheries catch, long-term variability of which has rarely been investigated despite intense fishing pressure and climate change. In this study, we attempt to identify their responses to climate change and fishing activities and to provide scientific basis for sustainable exploitation of these resources. Seven taxa from pelagic to demersal species inhabiting either cold-water or warm-water were selected to represent the piscivorous fish assemblage in the China Seas. Total catch of these piscivorous fish in the China Seas increased during the early 1990s, stabilizing around 1.2 million tons after 1997. Principal component analysis (PCA) showed evident interannual-decadal variabilities in the catch of these fish with step changes around 1985/86 and 1997/98. In idual taxa, however, showed different trends in catches with sharks, rays, and lizardfishes manifesting downward trends while Pacific cod, eels, and hairtail increasing. Common dolphinfish and Japanese-Spanish mackerel increased largely in the 1990s but declined slightly during the 2000s. Although there were temporal overlaps between climate change and fishing variabilities, results of gradient forest analyses indicated that fishing effort imposed the most important influence on piscivorous fish. And among all climate variables explored in this study, sea surface temperature (SST) especially that of the East China Sea, had greatest impacts on variations in piscivorous fish catch, which may have been gradually exacerbated by the continued high fishing intensity. In addition, significant changes were identified in the life history traits in the species we evaluated, such as reduced average body sizes and truncated age compositions, strongly indicating the effect of fishing. We therefore advocate precautionary fishery practices under climate change.
Publisher: Oxford University Press (OUP)
Date: 18-07-2022
Abstract: Using length frequency distribution data (LFD) is cost-effective for estimating somatic growth in fish or invertebrates as length data are relatively easy to obtain. The recently developed R packages TropFishR and fishboot extend classic ELEFAN (Electronic LEngth Frequency ANalysis) programs and include more powerful optimization procedures and a bootstrap method for estimating uncertainties. Yet, the fundamental functions require users to provide search conditions (e.g. upper and lower limits for each parameter, length-class size, number of length-classes for the calculation of moving average), which can significantly affect the results. In this paper, we compare the ELEFAN approach with a Bayesian approach in analysing LFD, employing both standard and seasonal von Bertalanffy growth functions. We apply both approaches to a commercially valuable but poorly studied red endeavour prawn (Metapenaeus ensis) harvested in Australia's Northern Prawn Fishery. Sensitivity tests on ELEFAN confirm that any change in search settings would affect the results. Simulation studies on Bayesian growth models show that Linf and K can be accurately obtained even with modal progression of only one year-class and using non-informative priors. However, age information, including the theoretical age at length zero (t0), is difficult to estimate and requires LFD from multiple age classes and informative priors. The Bayesian models yield mean parameters of: Linf = 36.56 mm (carapace length), K = 2.74 yr–1, and t0 = -0.02 yr for the males, and Linf = 51.81 mm, K = 1.94 yr–1, and t0 = -0.02 yr for the females. Seasonal oscillation models fit the LFD better, but the improvement is small and the estimated season-related parameters have large variances.
Publisher: MDPI AG
Date: 08-2019
DOI: 10.3390/NU11081766
Abstract: Fish and seafood consumption in Australia has been growing, yet the implications of this trend across the food system, from both a health and sustainability perspective have not been fully explored. This paper aims to map out the fish and seafood food system in Australia, linking production and consumption, to articulate challenges and opportunities for enhancing the sector’s contribution to future healthy and sustainable diets. We conducted a secondary analysis of publicly available datasets on fish and seafood production and consumption, triangulated and supplemented with peer-reviewed and grey literature on environmental, economic and social sustainability issues throughout the food system. A key challenge for health is the high proportion of fish and seafood consumed as discretionary food, particularly among children. Key challenges for sustainability include the narrow focus on environmental sustainability (with little consideration of the other domains), and the focus on production with little consideration for sustainability throughout post-harvest handling, processing, retail, distribution and consumption. Key opportunities for health and sustainability include the innovative use of processing and packaging technology to maximise nutritional quality creation of markets and supply chains for a greater ersity of underutilised fish and seafood species and processing by-products and reductions in waste and loss throughout the entire supply chain.
Publisher: Elsevier BV
Date: 03-2011
Publisher: Elsevier BV
Date: 12-2008
Publisher: Elsevier BV
Date: 2019
Publisher: Elsevier BV
Date: 11-2016
Publisher: CSIRO
Date: 2013
Publisher: Canadian Science Publishing
Date: 09-2011
DOI: 10.1139/F2011-083
Abstract: Fisheries typically experience large changes over time in fishing effort. The size of the area fished may also change substantially over time, mimicking the trend in fishing effort, and may have major effects on the population dynamics and fishing process. We extend a biomass dynamics model to incorporate fished area and relative fish density in fished and unfished areas. The fishable population is defined as those in iduals in the fished area and those that are sufficiently close to the fished area that they could potentially move into fished area during the fishing season. We estimate fishable biomass using three models assuming different level of population mixing between fished and unfished areas (i.e., partial mixing, full mixing, and no mixing). The models are implemented within a hierarchical Bayesian framework. Model performance is explored using simulations, and the approach is illustrated using logbook data for two tiger prawn species in Australia’s Northern Prawn Fishery. The partial mixing model that involves estimating a mixing parameter performs better than the models that assume no or full mixing. The methods could be applied to other fisheries where the area fished has changed substantially over the history of the fishery.
Publisher: CSIRO
Date: 2013
Publisher: Carcinological Society of Japan
Date: 1997
Publisher: Elsevier BV
Date: 06-2007
Publisher: Wiley
Date: 24-03-2020
DOI: 10.1111/FAF.12459
Publisher: Oxford University Press (OUP)
Date: 11-03-2019
Abstract: The majority of catch per unit effort (cpue) standardizations use generalized linear models (GLMs) or generalized additive models (GAMs). We develop geostatistical models that model catch locations as continuous Gaussian random fields (GRFs) and apply them to standardizing cpue in Australia’s Eastern Tuna and Billfish Fishery (ETBF). The results are compared with the traditional GLMs currently used in ETBF assessments as well as GAMs. Specifically, we compare seven models in three groups: two GLMs, two GAMs, and three GRF models. Within each group, one model treats spatial and temporal variables independently, while the other model(s) treats them together as an interaction term. The two spatio-temporal GRF models differ in treating the spatial–temporal interaction: either as a random process or as an autoregressive process. We simulate catch rate data for five pelagic species based on real fishery catch rates so that the simulated data reflect real fishery patterns while the “true” annual abundance levels are known. The results show that within each group, the model with a spatial–temporal interaction term significantly outperforms the other model treating spatial and temporal variables independently. For spatial–temporal models between the three groups, prediction accuracy tends to improve from GLM to GAM and to the GRF models. Overall, the spatio-temporal GRF autoregressive model reduces mean relative predictive error by 43.4% from the GLM, 33.9% from the GAM, and reduces mean absolute predictive error by 23.5% from the GLM and 3.3% from the GAM, respectively. The comparison suggests a promising direction for further developing the geostatistical models for the ETBF.
Publisher: Elsevier BV
Date: 09-2007
Publisher: Wiley
Date: 16-11-2012
Publisher: CSIRO
Date: 2020
DOI: 10.25919/HY31-4K92
Publisher: Canadian Science Publishing
Date: 08-2012
DOI: 10.1139/F2012-060
Abstract: The rule of thumb that fishing mortality to achieve maximum sustainable yield (F MSY ) equals natural mortality (M) has been both criticised and supported by theoretical arguments. However, the relationship has been rarely investigated using empirical data. We carried out a meta-analysis on 245 fish species worldwide and linked three types of reference points (F BRP : F MSY , F proxy , and F 0.5r ) to M and other life history parameters (LHP). We used Bayesian hierarchical errors-in-variables models to investigate the relationships and included the effect of taxonomic class and order. We compared various models and found that natural mortality is the most important LHP affecting F BRP . Other covariates, such as von Bertalanffy growth coefficient, asymptotic length, maximum age, and habitat types, add little to the relationship, partially because of correlation and large measurement and process errors. The best model results in F MSY = 0.87M (standard deviation (SD) = 0.05) for teleosts and F MSY = 0.41M (SD = 0.09) for chondrichthyans. F proxy based on per-recruit analysis is about 15% smaller than F MSY . Results could be used to estimate F BRP from LHP in data-poor situations.
Publisher: Wiley
Date: 07-2002
Publisher: Wiley
Date: 11-2002
Publisher: CSIRO Publishing
Date: 2009
DOI: 10.1071/MF09022
Abstract: Conventional biomass dynamics models express next year’s biomass as this year’s biomass plus surplus production less catch. These models are typically applied to species with several age-classes but it is unclear how well they perform for short-lived species with low survival and high recruitment variation. Two alternative versions of the standard biomass dynamics model (Standard) were constructed for short-lived species by ignoring the ‘old biomass’ term (Annual), and assuming that the biomass at the start of the next year depends on density-dependent processes that are a function of that biomass (Stock-recruit). These models were fitted to catch and effort data for the grooved tiger prawn Penaeus semisulcatus using a hierarchical Bayesian technique. The results from the biomass dynamics models were compared with those from more complicated weekly delay-difference models. The analyses show that: the Standard model is flexible for short-lived species the Stock-recruit model provides the most parsimonious fit simple biomass dynamics models can provide virtually identical results to data-demanding models and spatial variability in key population dynamics parameters exists for P. semisulacatus. The method outlined in this paper provides a means to conduct quantitative population assessments for data-limited short-lived species.
Publisher: CSIRO
Date: 2017
Publisher: Wiley
Date: 05-1997
Publisher: Canadian Science Publishing
Date: 07-2011
DOI: 10.1139/F2011-052
Abstract: Catchability and natural mortality are key quantities in fisheries stock assessment. However, it is difficult to estimate these two parameters simultaneously using only fishery catch and effort data. A Bayesian state–space modified delay–difference model is outlined that can estimate time series of catchability by fleet as well as natural mortality. This model, and three variants thereof, is fitted to data for grooved tiger prawns ( Penaeus semisulcatus ) in Australia’s Northern Prawn Fishery during the period of the year when there is little recruitment. A model that allows for both observation and process error and estimates natural mortality is best, in terms of model selection criteria as well as fit diagnostics. The posterior median estimate for catchability for the primary target fleet ranges from 6.15 × 10 −4 to 1.09 × 10 −4 during 1980–2007, while the posterior median estimate for catchability for a fleet with P. semisulcatus as its byproduct is about 20% of that for the primary fleet. Fishing efficiency increased at approximately 2% annually during 1980–2007, while the weekly natural mortality is estimated to be 0.053 week –1 .
Publisher: Elsevier BV
Date: 05-2008
Publisher: Wiley
Date: 05-2002
Publisher: Wiley
Date: 07-2010
Publisher: CSIRO
Date: 2015
Publisher: Wiley
Date: 08-2004
DOI: 10.1577/M03-056.1
Publisher: CSIRO
Date: 2020
Publisher: Oxford University Press (OUP)
Date: 13-12-2019
Abstract: Estimating fish growth from length frequency data is challenging. There is often a lack of clearly separated modes and modal progression in the length s les due to a combination of factors, including gear selectivity, slowing growth with increasing age, and spatial segregation of different year classes. In this study, we present an innovative Bayesian hierarchical model (BHM) that enables growth to be estimated where there are few distinguishable length modes in the s les. We analyse and identify the modes in multiple length frequency strata using a multinormal mixture model and then integrate the modes and associated variances into the BHM to estimate von Bertalanffy growth parameters. The hierarchical approach allows the parameters to be estimated at regional levels, where they are assumed to represent subpopulations, as well as at species level for the whole stock. We carry out simulations to validate the method and then demonstrate its application to Indian Ocean longtail tuna (Thunnus tonggol). The results show that the estimates are generally consistent with the range of estimates reported in the literature, but with less uncertainty. The BHM can be useful for deriving growth parameters for other species even if the length data contain few age classes and do not exhibit modal progression.
Publisher: Oxford University Press (OUP)
Date: 05-06-2020
Abstract: Empirical studies are popular in estimating fish natural mortality rate (M). However, these empirical methods derive M from other life-history parameters and are often perceived as being less reliable than direct methods. To improve the predictive performance and reliability of empirical methods, we develop ensemble learning models, including bagging trees, random forests, and boosting trees, to predict M based on a dataset of 256 records of both Chondrichthyes and Osteichthyes. Three common life-history parameters are used as predictors: the maximum age and two growth parameters (growth coefficient and asymptotic length). In addition, taxonomic variable class is included to distinguish Chondrichthyes and Osteichthyes. Results indicate that tree-based ensemble learning models significantly improve the accuracy of M estimate, compared to the traditional statistical regression models and the basic regression tree model. Among ensemble learning models, boosting trees and random forests perform best on the training dataset, but the former performs a slightly better on the test dataset. We develop four boosting trees models for estimating M based on varying life-history parameters, and an R package is provided for interested readers to estimate M of their new species.
Publisher: Elsevier BV
Date: 02-2016
Publisher: Elsevier BV
Date: 03-2009
Publisher: Oxford University Press (OUP)
Date: 22-12-2017
Publisher: Elsevier BV
Date: 12-2011
Publisher: Oxford University Press (OUP)
Date: 06-02-2012
Abstract: Zhou, S., Milton, D. A., and Fry, G. C. 2012. Integrated risk analysis for rare marine species impacted by fishing: sustainability assessment and population trend modelling. – ICES Journal of Marine Science, 69: 271–280. Risk assessment and conservation management of rare species are challenging due to a lack of data. We developed an integrated risk assessment approach to assess human impact on population sustainability of rare species. The approach involved two components: a quantitative sustainability assessment coupled with modelling trends in relative abundance. Both components took nil catches into account through zero-inflated statistical distributions that simultaneously modelled the zero and non-zero catches separately in submodels. The sustainability assessment used detection–non-detection data for population estimation and linked sustainability to easily collected life-history traits. This component provides an assessment of population sustainability at one point in time. The trend modelling applied zero-inflated negative binomial models to temporal trends in density and dispersion of species. It provided a complement to the static sustainability assessment. We applied this integrated approach to assess the risk to 14 species of rare, protected sea snakes incidentally caught in the Australian Northern Prawn Fishery. This approach can be applicable for risk assessment of many species with limited abundance data, a large number of absences and some presence–absence information only.
Publisher: Oxford University Press (OUP)
Date: 03-05-2010
Abstract: Punt, A. E., Deng, R. A., Dichmont, C. M., Kompas, T., Venables, W. N., Zhou, S., Pascoe, S., Hutton, T., Kenyon, R., van der Velde, T., and Kienzle, M. 2010. Integrating size-structured assessment and bioeconomic management advice in Australia's northern prawn fishery. – ICES Journal of Marine Science, 67: 1785–1801. Three species in Australia's northern prawn fishery (Penaeus semisulcatus, P. esculentus, and Metapenaeus endeavouri) are assessed using a size-structured population model that operates on a weekly time-step. The parameters of this multispecies population model are estimated using data on catches, catch rates, length frequency data from surveys and the fishery, and tag release–recapture data. The model allows for the technical interaction among the three species. The results from the multispecies stock assessment are used to calculate the time-series of catches and levels of fishing effort that maximize net present value. The bioeconomic model takes into account costs which are proportional to catches and those which are proportional to fishing effort, as well as fixed costs. The sensitivity of the results is examined by changing the assumptions regarding the values for the economic parameters of the bioeconomic model as well as those on which the assessment are based. The results suggest that fishing effort needs to be reduced in the short term to achieve economic goals, although most stocks are estimated currently to be above the stock size corresponding to maximum sustainable yield. Short-term catches and effort levels are sensitive to model assumptions, and in particular, to trends in prices and costs.
Publisher: Elsevier BV
Date: 06-1997
Publisher: Oxford University Press (OUP)
Date: 04-1998
DOI: 10.2307/1549328
Publisher: CSIRO
Date: 2016
Publisher: CSIRO Publishing
Date: 2009
DOI: 10.1071/MF08207
Abstract: A new sustainability assessment for fishing effects (SAFE) method was used to assess the biological sustainability of 456 teleost bycatch species in Australia’s Northern Prawn Fishery. This method can quantify the effects of fishing on sustainability for large numbers of species with limited data. The fishing mortality rate of each species based on its spatial distribution (estimated from detection/non-detection data) and the catch rate based on fishery-dependent or fishery-independent data were estimated. The sustainability of each species was assessed by two biological reference points approximated from life-history parameters. The point estimates indicated that only two species (but 21 when uncertainty was included) had estimated fishing mortality rates greater than a fishing mortality rate corresponding to the maximum sustainable yield. These two species also had their upper 95% confidence intervals (but not their point estimates) greater than their minimum unsustainable fishing mortality rates. The fact that large numbers of species are sustainable can be attributed mainly to their wide distributions in unfished areas, low catch rates within fished areas and short life spans (high biological productivity). The present study demonstrates how SAFE may be a cost-effective quantitative assessment method to support ecosystem-based fishery management.
Publisher: Wiley
Date: 04-03-2017
DOI: 10.1111/FAF.12201
Publisher: Wiley
Date: 02-2003
Location: Australia
No related grants have been discovered for Shijie Zhou.