Crinkles in connectivity: combining genetics and other types of biological data to estimate movement and interbreeding between populations

Marine species generally have large population sizes, continuous distributions and high dispersal capacity. Despite this, they are often subdivided into separate populations, which are the basic units of fisheries management. For example, populations of some fisheries species across the deep water of the Timor Trench are genetically different, inferring minimal movement and interbreeding. When connectivity is higher than the Timor Trench example, but not so high that the populations become one, connectivity between populations is crinkled. Crinkled connectivity occurs when migration is above the threshold required to link populations genetically, but below the threshold for demographic links. In future, genetic estimates of connectivity over crinkled links could be uniquely combined with other data, such as estimates of population size and tagging and tracking data, to quantify demographic connectedness between these types of populations. Elasmobranch species may be ideal targets for this research because connectivity between populations is more likely to be crinkled than for finfish species. Fisheries stock-assessment models could be strengthened with estimates of connectivity to improve the strategic and sustainable harvesting of biological resources.

A novel method for the age estimation of Saddletail snapper (Lutjanus malabaricus) using Fourier Transform-near infrared (FT-NIR) spectroscopy

Near infrared (NIR) spectroscopy was investigated as a potential rapid method of estimating fish age from whole otoliths of Saddletail snapper (Lutjanus malabaricus). Whole otoliths from 209 Saddletail snapper were extracted and the NIR spectral characteristics were acquired over a spectral range of 800–2780 nm. Partial least-squares models (PLS) were developed from the diffuse reflectance spectra and reference-validated age estimates (based on traditional sectioned otolith increments) to predict age for independent otolith samples. Predictive models developed for a specific season and geographical location performed poorly against a different season and geographical location. However, overall PLS regression statistics for predicting a combined population incorporating both geographic location and season variables were: coefficient of determination (R2) = 0.94, root mean square error of prediction (RMSEP) = 1.54 for age estimation, indicating that Saddletail age could be predicted within 1.5 increment counts. This level of accuracy suggests the method warrants further development for Saddletail snapper and may have potential for other fish species. A rapid method of fish age estimation could have the potential to reduce greatly both costs of time and materials in the assessment and management of commercial fisheries.

Social objectives of fisheries management: What are managers' priorities?

Increasingly, social considerations are having an influence on fisheries policy as well as day-to-day management decision making. Social objectives, unlike economic or conservation objectives, are often poorly defined in fisheries policy, providing substantial leeway for managers to develop management plans in response to the perceived importance of different social outcomes, and potential inconsistencies between different fisheries and jurisdictions. In this paper, through a literature review and workshop with managers across different Australian jurisdictions, we develop a set of social objectives that may be applicable in Australian fisheries. We assess the importance of these different objectives using the Analytic Hierarchy Process, and find considerable diversity in opinion as to which social objectives fisheries management should prioritise to achieve. This diversity of opinion is not directly related to jurisdiction, but does seem related to the context and social environment in which fisheries managers are operating.

Integrating different approaches in the definition of biological stocks: A northern Australian multi-jurisdictional fisheries example using grey mackerel, Scomberomorus semifasciatus

A holistic approach to stock structure studies utilises multiple different techniques on the same individuals sampled from selected populations and combines results across spatial and temporal scales to produce a weight of evidence conclusion. It is the most powerful and reliable source of information to use in formulating resource management and monitoring plans. Few examples of the use of a holistic approach in stock structure studies exist, although more recently this is changing. Using such an approach makes integration of results from each technique challenging. An integrated stock definition (ISD) approach for holistic stock structure studies was developed in this study to aid in the appropriate interpretation of stock structure results to guide the determination of fishery management units. The ISD approach is applied herein to a study of the northern Australian endemic grey mackerel, Scomberomorus semifasciatus (Scombridae). Analyses of genetic (mitochondrial DNA and microsatellites), parasite, otolith stable isotope, and growth data are synthesised to determine the stock structure of S. semifasciatus across northern Australia. Integration of the results from all techniques identified at least six S. semifasciatus stocks for management purposes. Further, the use of the ISD approach provided a simple basis for integrating multiple techniques and for their interpretation. The use of this holistic approach was a powerful tool in providing greater certainty about the appropriate management units for S. semifasciatus. Future stock structure studies investigating spatial management questions in the fisheries context should adopt a holistic approach and apply the ISD approach for a more accurate definition of biological stocks to improve fisheries management.

Selecting and assessing social objectives for Australian fisheries management

This paper details Australian research that developed tools to assist fisheries managers and government agencies in engaging with the social dimension of industry and community welfare in fisheries management. These tools are in the form of objectives and indicators. These highlight the social dimensions and the effects of management plans and policy implementation on fishing industries and associated communities, while also taking into account the primacy of ecological imperatives. The deployment of these objectives and indicators initially provides a benchmark and, over the life of a management plan, can subsequently be used to identify trends in effects on a variety of social and economic elements that may be objectives in the management of a fishery. It is acknowledged that the degree to which factors can be monitored will be dependent upon resources of management agencies, however these frameworks provide a method for effectively monitoring and measuring change in the social dimension of fisheries management.Essentially, the work discussed in this paper provides fisheries management with the means to both track and begin to understand the effects of government policy and management plans on the social dimension of the fishing industry and its associated communities. Such tools allow the consideration of these elements, within an evidence base, into policy arrangements, and consequently provide an invaluable contribution to the ability to address resilience and sustainability of fishing industries and associated communities.

Bayesian fisheries stock assessment: integrating and updating knowledge

In this thesis the use of the Bayesian approach to statistical inference in fisheries stock assessment is studied. The work was conducted in collaboration of the Finnish Game and Fisheries Research Institute by using the problem of monitoring and prediction of the juvenile salmon population in the River Tornionjoki as an example application. The River Tornionjoki is the largest salmon river flowing into the Baltic Sea. This thesis tackles the issues of model formulation and model checking as well as computational problems related to Bayesian modelling in the context of fisheries stock assessment. Each article of the thesis provides a novel method either for extracting information from data obtained via a particular type of sampling system or for integrating the information about the fish stock from multiple sources in terms of a population dynamics model. Mark-recapture and removal sampling schemes and a random catch sampling method are covered for the estimation of the population size. In addition, a method for estimating the stock composition of a salmon catch based on DNA samples is also presented. For most of the articles, Markov chain Monte Carlo (MCMC) simulation has been used as a tool to approximate the posterior distribution. Problems arising from the sampling method are also briefly discussed and potential solutions for these problems are proposed. Special emphasis in the discussion is given to the philosophical foundation of the Bayesian approach in the context of fisheries stock assessment. It is argued that the role of subjective prior knowledge needed in practically all parts of a Bayesian model should be recognized and consequently fully utilised in the process of model formulation.

Improving the effectiveness of age-abundance indicators in the management of fisheries in Queensland, Australia

The development of fishery indicators is a crucial undertaking as it ultimately provides evidence to stakeholders about the status of fished species such as population size and survival rates. In Queensland, as in many other parts of the world, age-abundance indicators (e.g. fish catch rate and/or age composition data) are traditionally used as the evidence basis because they provide information on species life history traits as well as on changes in fishing pressures and population sizes. Often, however, the accuracy of the information from age-abundance indicators can be limited due to missing or biased data. Consequently, improved statistical methods are required to enhance the accuracy, precision and decision-support value of age-abundance indicators.

Otolith morphology of four mackerel species (Scomberomorus spp.) in Australia: Species differentiation and prediction for fisheries monitoring and assessment

Four species of large mackerels (Scomberomorus spp.) co-occur in the waters off northern Australia and are important to fisheries in the region. State fisheries agencies monitor these species for fisheries assessment; however, data inaccuracies may exist due to difficulties with identification of these closely related species, particularly when specimens are incomplete from fish processing. This study examined the efficacy of using otolith morphometrics to differentiate and predict among the four mackerel species off northeastern Australia. Seven otolith measurements and five shape indices were recorded from 555 mackerel specimens. Multivariate modelling including linear discriminant analysis (LDA) and support vector machines, successfully differentiated among the four species based on otolith morphometrics. Cross validation determined a predictive accuracy of at least 96% for both models. An optimum predictive model for the four mackerel species was an LDA model that included fork length, feret length, feret width, perimeter, area, roundness, form factor and rectangularity as explanatory variables. This analysis may improve the accuracy of fisheries monitoring, the estimates based on this monitoring (i.e. mortality rate) and the overall management of mackerel species in Australia.

Precise determination of aquatic plant wet mass using a salad spinner

The reliable assessment of macrophyte biomass is fundamental for ecological research and management of freshwater ecosystems. While dry mass is routinely used to determine aquatic plant biomass, wet (fresh) mass can be more practical. We tested the accuracy and precision of wet mass measurements by using a salad spinner to remove surface water from four macrophyte species differing in growth form and architectural complexity. The salad spinner aided in making precise and accurate wet mass with less than 3% error. There was also little difference between operators, with a user bias estimated to be below 5%. To achieve this level of precision, only 10–20 turns of the salad spinner are needed. Therefore, wet mass of a sample can be determined in less than 1 min. We demonstrated that a salad spinner is a rapid and economical technique to enable precise and accurate macrophyte wet mass measurements and is particularly suitable for experimental work. The method will also be useful for fieldwork in situations when sample sizes are not overly large.