A genomic approach to inferring kinship reveals limited intergenerational dispersal in the yellow fever mosquito

Understanding past dispersal and breeding events can provide insight into ecology and evolution and can help inform strategies for conservation and the control of pest species. However, parent-offspring dispersal can be difficult to investigate in rare species and in small pest species such as mosquitoes. Here, we develop a methodology for estimating parent-offspring dispersal from the spatial distribution of close kin, using pairwise kinship estimates derived from genome-wide single nucleotide polymorphisms (SNPs). SNPs were scored in 162 Aedes aegypti (yellow fever mosquito) collected from eight close-set, high-rise apartment buildings in an area of Malaysia with high dengue incidence. We used the SNPs to reconstruct kinship groups across three orders of kinship. We transformed the geographical distances between all kin pairs within each kinship category into axial standard deviations of these distances, then decomposed these into components representing past dispersal events. From these components, we isolated the axial standard deviation of parent-offspring dispersal and estimated neighbourhood area (129 m), median parent-offspring dispersal distance (75 m) and oviposition dispersal radius within a gonotrophic cycle (36 m). We also analysed genetic structure using distance-based redundancy analysis and linear regression, finding isolation by distance both within and between buildings and estimating neighbourhood size at 268 individuals. These findings indicate the scale required to suppress local outbreaks of arboviral disease and to target releases of modified mosquitoes for mosquito and disease control. Our methodology is readily implementable for studies of other species, including pests and species of conservation significance.

Genetic and genomic monitoring with minimally invasive sampling methods

The decreasing cost and increasing scope and power of emerging genomic technologies are reshaping the field of molecular ecology. However, many modern genomic approaches (e.g., RAD-seq) require large amounts of high-quality template DNA. This poses a problem for an active branch of conservation biology: genetic monitoring using minimally invasive sampling (MIS) methods. Without handling or even observing an animal, MIS methods (e.g., collection of hair, skin, faeces) can provide genetic information on individuals or populations. Such samples typically yield low-quality and/or quantities of DNA, restricting the type of molecular methods that can be used. Despite this limitation, genetic monitoring using MIS is an effective tool for estimating population demographic parameters and monitoring genetic diversity in natural populations. Genetic monitoring is likely to become more important in the future as many natural populations are undergoing anthropogenically driven declines, which are unlikely to abate without intensive adaptive management efforts that often include MIS approaches. Here, we profile the expanding suite of genomic methods and platforms compatible with producing genotypes from MIS, considering factors such as development costs and error rates. We evaluate how powerful new approaches will enhance our ability to investigate questions typically answered using genetic monitoring, such as estimating abundance, genetic structure and relatedness. As the field is in a period of unusually rapid transition, we also highlight the importance of legacy data sets and recommend how to address the challenges of moving between traditional and next-generation genetic monitoring platforms. Finally, we consider how genetic monitoring could move beyond genotypes in the future. For example, assessing microbiomes or epigenetic markers could provide a greater understanding of the relationship between individuals and their environment.

Inference from single occasion capture experiments using genetic markers

Accurate estimation of the size of animal populations is an important task in ecological science. Recent advances in the field of molecular genetics researches allow the use of genetic data to estimate the size of a population from a single capture occasion rather than repeated occasions as in the usual capture-recapture experiments. Estimating the population size using genetic data also has sometimes led to estimates that differ markedly from each other and also from classical capture-recapture estimates. Here, we develop a closed form estimator that uses genetic information to estimate the size of a population consisting of mothers and daughters, focusing on estimating the number of mothers, using data from a single sample. We demonstrate the estimator is consistent and propose a parametric bootstrap to estimate the standard errors. The estimator is evaluated in a simulation study and applied to real data. We also consider maximum likelihood in this setting and discover problems that preclude its general use.

Non-invasive genetic censusing and monitoring of primate populations

Knowing the density or abundance of primate populations is essential for their conservation management and contextualizing socio-demographic and behavioral observations. When direct counts of animals are not possible, genetic analysis of non-invasive samples collected from wildlife populations allows estimates of population size with higher accuracy and precision than is possible using indirect signs. Furthermore, in contrast to traditional indirect survey methods, prolonged or periodic genetic sampling across months or years enables inference of group membership, movement, dynamics, and some kin relationships. Data may also be used to estimate sex ratios, sex differences in dispersal distances, and detect gene flow among locations. Recent advances in capture-recapture models have further improved the precision of population estimates derived from non-invasive samples. Simulations using these methods have shown that the confidence interval of point estimates includes the true population size when assumptions of the models are met, and therefore this range of population size minima and maxima should be emphasized in population monitoring studies. Innovations such as the use of sniffer dogs or anti-poaching patrols for sample collection are important to ensure adequate sampling, and the expected development of efficient and cost-effective genotyping by sequencing methods for DNAs derived from non-invasive samples will automate and speed analyses.

Genetic relatedness reveals total population size of white sharks in eastern Australia and New Zealand

Conservation concerns exist for many sharks but robust estimates of abundance are often lacking. Improving population status is a performance measure for species under conservation or recovery plans, yet the lack of data permitting estimation of population size means the efficacy of management actions can be difficult to assess, and achieving the goal of removing species from conservation listing challenging. For potentially dangerous species, like the white shark, balancing conservation and public safety demands is politically and socially complex, often leading to vigorous debate about their population status. This increases the need for robust information to inform policy decisions. We developed a novel method for estimating the total abundance of white sharks in eastern Australia and New Zealand using the genetic-relatedness of juveniles and applying a close-kin mark-recapture framework and demographic model. Estimated numbers of adults are small (ca. 280-650), as is total population size (ca. 2,500-6,750). However, estimates of survival probability are high for adults (over 90%), and fairly high for juveniles (around 73%). This represents the first direct estimate of total white shark abundance and survival calculated from data across both the spatial and temporal life-history of the animal and provides a pathway to estimate population trend.

The parent-offspring probability when sampling age-structured populations

We consider two individuals sampled from an age-structured population, and derive the probability that these have a parent-offspring relationship. Such probabilities play an important role in the recently proposed close-kin mark-recapture methods. The probability is decomposed into three terms. The first is the probability of the parent being alive, the second term involves the mechanism by which individuals are sampled, and the third term is a contribution from the observed age of the parent. A stable age distribution in the population is assumed, and we provide an expression for how this distribution is perturbed by the information that an individual has given birth at a particular time point in the past or in the future. Calculations are performed from the perspective of the offspring, but we also make comparison to the situation where the perspective is put on the parent. Although the resulting probabilities are the same, the actual calculations differ, due to the asymmetry of a parent-offspring relationship.

Inferring contemporary and historical genetic connectivity from juveniles

Measuring population connectivity is a critical task in conservation biology. While genetic markers can provide reliable long-term historical estimates of population connectivity, scientists are still limited in their ability to determine contemporary patterns of gene flow, the most practical time frame for management. Here, we tackled this issue by developing a new approach that only requires juvenile sampling at a single time period. To demonstrate the usefulness of our method, we used the Speartooth shark (Glyphis glyphis), a critically endangered species of river shark found only in tropical northern Australia and southern Papua New Guinea. Contemporary adult and juvenile shark movements, estimated with the spatial distribution of kin pairs across and within three river systems, was contrasted with historical long-term connectivity patterns, estimated from mitogenomes and genome-wide SNP data. We found strong support for river fidelity in juveniles with the within-cohort relationship analysis. Male breeding movements were highlighted with the cross-cohort relationship analysis, and female reproductive philopatry to the river systems was revealed by the mitogenomic analysis. We show that accounting for juvenile river fidelity and female philopatry is important in population structure analysis and that targeted sampling in nurseries and juvenile aggregations should be included in the genomic toolbox of threatened species management.

The role of genetics in fisheries management under the E.U. common fisheries policy

Exploitation of fish and shellfish stocks by the European Union fishing fleet is managed under the Common Fisheries Policy (CFP), which aims to ensure that fishing and aquaculture are environmentally, economically and socially sustainable and that they provide a source of healthy food for E.U. citizens. A notable feature of the CFP is its legally enshrined requirement for sound scientific advice to underpin its objectives. The CFP was first conceived in 1970 when it formed part of the Common Agricultural Policy. Its formal inception as a stand-alone regulation occurred in 1983 and since that time, the CFP has undergone reforms in 1992, 2002 and 2013, each time bringing additional challenges to the scientific advisory process as the scope of the advice increased in response to changing objectives arising from E.U. regulations and commitments to international agreements. This paper reviews the influence that genetics has had on fish stock assessments and the provision of management advice for European fisheries under successive reforms of the CFP. The developments in genetics since the inception of the CFP have given rise to a diverse and versatile set of genetic techniques that have the potential to provide significant added value to fisheries assessments and the scientific advisory process. While in some cases, notably Pacific salmon Oncorhynchus spp., genetics appear to be very well integrated into existing management schemes, it seems that for marine fishes, discussions on the use of genetics and genomics for fisheries management are often driven by the remarkable technological progress in this field, rather than imminent needs emerging from policy frameworks. An example is the recent suggestion to use environmental (e)DNA for monitoring purposes. While there is no denying that state-of-the-art genetic and genomic approaches can and will be of value to address a number of issues relevant for the management and conservation of marine renewable natural resources, a focus on technology rather than policy and management needs is prone to widen the gap between science and policy, governance and management, thereby further impeding the effective integration of genetic and genomic information into the fisheries management decision making process. Hence, rather than focusing on what is technically achievable, this review outlines suggestions as to which modern genetic and genomic approaches are likely to help address some of the most pressing fisheries management challenges under the CFP.

Can estimates of genetic effective population size contribute to fisheries stock assessments?

Sustainable exploitation of fisheries populations is challenging to achieve when the size of the population prior to exploitation and the actual numbers removed over time and across fishing zones are not clearly known. Quantitative fisheries' modeling is able to address this problem, but accurate and reliable model outcomes depend on high quality input data. Much of this information is obtained through the operation of the fishery under consideration, but while this seems appropriate, biases may occur. For example, poorly quantified changes in fishing methods that increase catch rates can erroneously suggest that the overall population size is increasing. Hence, the incorporation of estimates of abundance derived from independent data sources is preferable. We review and evaluate a fisheries-independent method of indexing population size; inferring adult abundance from estimates of the genetic effective size of a population (N_e ). Recent studies of elasmobranch species have shown correspondence between N_e and ecologically determined estimates of the population size (N). Simulation studies have flagged the possibility that the range of N_e /N ratios across species may be more restricted than previously thought, and also show that declines in N_e track declines in the abundance of model fisheries species. These key developments bring this new technology closer to implementation in fisheries science, particularly for data-poor fisheries or species of conservation interest.