NeEstimator v2 is a completely revised and updated implementation of software that produces estimates of contemporary effective population size, using several different methods and a single input file. NeEstimator v2 includes three single-sample estimators (updated versions of the linkage disequilibrium and heterozygote-excess methods, and a new method based on molecular coancestry), as well as the two-sample (moment-based temporal) method. New features include the following: (i) an improved method for accounting for missing data; (ii) options for screening out rare alleles; (iii) confidence intervals for all methods; (iv) the ability to analyse data sets with large numbers of genetic markers (10 000 or more); (v) options for batch processing large numbers of different data sets, which will facilitate cross-method comparisons using simulated data; and (vi) correction for temporal estimates when individuals sampled are not removed from the population (Plan I sampling). The user is given considerable control over input data and composition, and format of output files. The freely available software has a new JAVA interface and runs under MacOS, Linux and Windows.

Since the first investigation 25 years ago, the application of genetic tools to address ecological and evolutionary questions in elasmobranch studies has greatly expanded. Major developments in genetic theory as well as in the availability, cost effectiveness and resolution of genetic markers were instrumental for particularly rapid progress over the last 10 years. Genetic studies of elasmobranchs are of direct importance and have application to fisheries management and conservation issues such as the definition of management units and identification of species from fins. In the future, increased application of the most recent and emerging technologies will enable accelerated genetic data production and the development of new markers at reduced costs, paving the way for a paradigm shift from gene to genome-scale research, and more focus on adaptive rather than just neutral variation. Current literature is reviewed in six fields of elasmobranch molecular genetics relevant to fisheries and conservation management (species identification, phylogeography, philopatry, genetic effective population size, molecular evolutionary rate and emerging methods). Where possible, examples from the Indo-Pacific region, which has been underrepresented in previous reviews, are emphasized within a global perspective.

Best use of scientific knowledge is required to maintain the fundamental role of seafood in human nutrition. While it is acknowledged that genomic-based methods allow the collection of powerful data, their value to inform fisheries management, aquaculture, and biosecurity applications remains underestimated. We review genomic applications of relevance to the sustainable management of seafood resources, illustrate the benefits of, and identify barriers to their integration. We conclude that the value of genomic information towards securing the future of seafood does not need to be further demonstrated. Instead, we need immediate efforts to remove structural roadblocks and focus on ways that support integration of genomic-informed methods into management and production practices. We propose solutions to pave the way forward.

Significant changes have occurred in the well‐established partnership between fisheries managers and geneticists over the last 50 years. It is therefore timely to review and recalibrate the ways in which genetic technologies can assist the fishing industry to maintain productive and sustainable harvests. Our objective is to contribute to the mutual understanding of all stakeholders in the genetics–management partnership. Genetic technologies that are relevant to fisheries management are grouped into eleven themes, which are described in plain language for a non‐specialist audience. The role that the genetic information plays in fisheries management is explained, along with an assessment of the challenges and barriers that may be preventing the uptake of the information into the fisheries management process. The compelling conclusion is that genetics offers a diverse collection of versatile and useful tools for informing fisheries managers about issues that have a biological basis. Presently, mainstream use of genetic tools focuses on a narrow set of fisheries management issues, but the diversity of genetic tools and the novel issues they can address indicates that uptake will grow, particularly as communication between geneticists and end‐users improves.

Background: The territorial fishing zones of Australia and Indonesia are contiguous to the north of Australia in the Timor and Arafura Seas and in the Indian Ocean to the north of Christmas Island. The area surrounding the shared boundary consists of a variety of bio-diverse marine habitats including shallow continental shelf waters, oceanic trenches and numerous offshore islands. Both countries exploit a variety of fisheries species, including whaler (Carcharhinus spp.) and hammerhead sharks (Sphyrna spp.). Despite their differences in social and financial arrangements, the two countries are motivated to develop complementary co-management practices to achieve resource sustainability. An essential starting point is knowledge of the degree of population subdivision, and hence fisheries stock status, in exploited species.

Despite international protection of white sharks Carcharodon carcharias, important conservation parameters such as abundance, population structure and genetic diversity are largely unknown. The tissue of 97 predominately juvenile white sharks sampled from spatially distant eastern and southwestern Australian coastlines was sequenced for the mitochondrial DNA (mtDNA) control region and genotyped with 6 nuclear-encoded microsatellite loci. MtDNA population structure was found between the eastern and southwestern coasts (F ST = 0.142, p < 0.0001), implying female reproductive philopatry. This concurs with recent satellite and acoustic tracking findings which suggest the sustained presence of discrete east coast nursery areas. Furthermore, population subdivision was found between the same regions with biparentally inherited microsatellite markers (F ST = 0.009, p < 0.05), suggesting that males may also exhibit some degree of reproductive philopatry; 5 sharks captured along the east coast had mtDNA haplotypes that resembled western Indian Ocean sharks more closely than Australian/New Zealand sharks, suggesting that transoceanic dispersal, or migration resulting in breeding, may occur sporadically. Our most robust estimate of contemporary genetic effective population size was low and close to thresholds at which adaptive potential may be lost. For a variety of reasons, these contemporary estimates were at least 1, possibly 2, orders of magnitude below our historical effective size estimates. Population decline could expose these genetically isolated populations to detrimental genetic effects. Regional Australian white shark conservation management units should be implemented until genetic population structure, size and diversity can be investigated in more detail.

Reproductive philopatry in bull sharks Carcharhinus leucas was investigated by comparing mitochondrial (NADH dehydrogenase subunit 4, 797 base pairs and control region genes 837 base pairs) and nuclear (three microsatellite loci) DNA of juveniles sampled from 13 river systems across northern Australia. High mitochondrial and low microsatellite genetic diversity among juveniles sampled from different rivers (mitochondrial φ(ST) = 0·0767, P < 0·05; microsatellite F(ST) = -0·0022, P > 0·05) supported female reproductive philopatry. Genetic structure was not further influenced by geographic distance (P > 0·05) or long-shore barriers to movement (P > 0·05). Additionally, results suggest that C. leucas in northern Australia has a long-term effective population size of 11 000-13 000 females and has undergone population bottlenecks and expansions that coincide with the timing of the last ice-ages.

The linkage disequilibrium method is currently the most widely used single sample estimator of genetic effective population size. The commonly used software packages come with two options, referred to as the parametric and jackknife methods, for computing the associated confidence intervals. However, little is known on the coverage performance of these methods, and the published data suggest there may be some room for improvement. Here, we propose two new methods for generating confidence intervals and compare them with the two in current use through a simulation study. The new confidence interval methods tend to be conservative but outperform the existing methods for generating confidence intervals under certain circumstances, such as those that may be encountered when making estimates using large numbers of single-nucleotide polymorphisms.