During the last 2 centuries, southern right whales Eubalaena australis were hunted to near extinction, and an estimated 150 000 were killed by pre-industrial whaling in the 19th century and illegal Soviet whaling in the 20th century. Here we focus on the coastal calving grounds of Australia and New Zealand (NZ), where previous work suggests 2 genetically distinct stocks of southern right whales are recovering. Historical migration patterns and spatially variable patterns of recovery suggest each of these stocks are subdivided into 2 stocks: (1) NZ, comprising NZ subantarctic (NZSA) and mainland NZ (MNZ) stocks; and (2) Australia, comprising southwest and southeast stocks. We expand upon previous work to investigate population subdivision by analysing over 1000 samples collected at 6 locations across NZ and Australia, although sample sizes were small from some locations. Mitochondrial DNA (mtDNA) control region haplotypes (500 bp) and microsatellite genotypes (13 loci) were used to identify 707 individual whales and to test for genetic differentiation. For the first time, we documented the movement of 7 individual whales between the NZSA and MNZ based on the matching of multilocus genotypes. Given the current and historical evidence, we hypothesise that individuals from the NZ subantarctic are slowly recolonising MNZ, where a former calving ground was extirpated. We also suggest that southeast Australian right whales represent a remnant stock, distinct from the southwest Australian stock, based on significant differentiation in mtDNA haplotype frequencies (F ST = 0.15, p < 0.01; Φ ST = 0.12, p = 0.02) and contrasting patterns of recovery. In comparison with significant differences in mtDNA haplotype frequencies found between the 3 proposed stocks (overall F ST = 0.07, Φ ST = 0.12, p < 0.001), we found no significant differentiation in microsatellite loci (overall

Animal culture, defined as "information or behavior-shared within a community-which is acquired from conspecifics through some form of social learning" (1), can have important consequences for the survival and reproduction of individuals, social groups, and potentially, entire populations (1, 2). Yet, until recently, conservation strategies and policies have focused primarily on broad demographic responses and the preservation of genetically defined, evolutionarily significant units. A burgeoning body of evidence on cultural transmission and other aspects of sociality (3) is now affording critical insights into what should be conserved (going beyond the protection of genetic diversity, to consider adaptive aspects of phenotypic variation), and why specific conservation programs succeed (e.g., through facilitating the resilience of cultural diversity) while others fail (e.g., by neglecting key repositories of socially transmitted knowledge). Here, we highlight how international legal instruments, such as the Convention on the Conservation of Migratory Species of Wild Animals (CMS), can facilitate smart, targeted conservation of a wide range of taxa, by explicitly considering aspects of their sociality and cultures. CONSEQUENCES OF SOCIAL KNOWLEDGE An important aspect of social learning is the speed with which new behaviors can potentially spread through populations, with effects that may be positive (e.g., adaptive exploitation of a new food source) or negative (e.g., increasing conflict with humans, such as when sperm whales learn to remove fish from longlines) (2). Transmission can be mediated by an inherent propensity to adopt innovations (e.g., "lobtail" feeding in humpback whales (1)), or curbed by cultural conservatism (e.g., southern resident killer whales' persistent foraging specialization on Chinook salmon (2)). Social learning can result in the emergence of subpopulations with distinctive behavioral profiles, erecting social barriers, as observed in distinct vocal clans of sperm whales (see the Figure). Culturally mediated population structure has important implications for conservation efforts (4), as it can influence species-wide phenotypic diversity and adaptability to changing conditions (5). In some cases, such as humpback or blue whale song, cultural variation can reflect demography and facilitate more efficient, or less invasive, assays of contemporary genetic population structure (1, 4). Most profoundly, culture can play a causal role in establishing and maintaining distinct evolutionary trajectories (6). Another consequence of social learning can be the increased importance of key individuals as repositories of accumulated knowledge, making their targeted protection particularly important for the persistence of social units. For example, the experience of African elephant matriarchs (see

Genetic erosion is a major threat to biodiversity because it can reduce fitness and ultimately contribute to the extinction of populations. Here, we explore the use of quantitative metrics to detect and monitor genetic erosion. Monitoring systems should not only characterize the mechanisms and drivers of genetic erosion (inbreeding, genetic drift, demographic instability, population fragmentation, introgressive hybridization, selection) but also its consequences (inbreeding and outbreeding depression, emergence of large‐effect detrimental alleles, maladaptation and loss of adaptability). Technological advances in genomics now allow the production of data the can be measured by new metrics with improved precision, increased efficiency and the potential to discriminate between neutral diversity (shaped mainly by population size and gene flow) and functional/adaptive diversity (shaped mainly by selection), allowing the assessment of management‐relevant genetic markers. The requirements of such studies in terms of sample size and marker density largely depend on the kind of population monitored, the questions to be answered and the metrics employed. We discuss prospects for the integration of this new information and metrics into conservation monitoring programmes.

Fidelity to migratory destinations is an important driver of connectivity in marine and avian species. Here we assess the role of maternally directed learning of migratory habitats, or migratory culture, on the population structure of the endangered Australian and New Zealand southern right whale. Using DNA profiles, comprising mitochondrial DNA (mtDNA) haplotypes (500 bp), microsatellite genotypes (17 loci) and sex from 128 individually-identified whales, we find significant differentiation among winter calving grounds based on both mtDNA haplotype (FST = 0.048, ΦST = 0.109, p < 0.01) and microsatellite allele frequencies (FST = 0.008, p < 0.01), consistent with long-term fidelity to calving areas. However, most genetic comparisons of calving grounds and migratory corridors were not significant, supporting the idea that whales from different calving grounds mix in migratory corridors. Furthermore, we find a significant relationship between δ13C stable isotope profiles of 66 Australian southern right whales, a proxy for feeding ground location, and both mtDNA haplotypes and kinship inferred from microsatellite-based estimators of relatedness. This indicates migratory culture may influence genetic structure on feeding grounds. This fidelity to migratory destinations is likely to influence population recovery, as long-term estimates of historical abundance derived from estimates of genetic diversity indicate the South Pacific calving grounds remain at <10% of pre-whaling abundance.

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.

Abstract. Superpopulation capture-recapture models are useful for estimating the abundance of long-lived, migratory species because they are able to account for the fluid nature of annual residency at migratory destinations. Here we extend the superpopulation POPAN model to explicitly account for heterogeneity in capture probability linked to reproductive cycles (POPAN-s). This extension has potential application to a range of species that have temporally variable life stages (e.g., non-annual breeders such as albatrosses and baleen whales) and results in a significant reduction in bias over the standard POPAN model. We demonstrate the utility of this model in simultaneously estimating abundance and annual population growth rate (k) in the New Zealand (NZ) southern right whale (Eubalaena australis) from 1995 to 2009. DNA profiles were constructed for the individual identification of more than 700 whales, sampled during two sets of winter expeditions in 1995-1998 and 2006-2009. Due to differences in recapture rates between sexes, only sex-specific models were considered. The POPAN-s models, which explicitly account for a decrease in capture probability in non-calving years, fit the female data set significantly better than do standard superpopulation models (DAIC . 25). The best POPAN-s model (AIC) gave a superpopulation estimate of 1162 females for 1995-2009 (95% CL 921, 1467 and an estimated annual increase of 5% (95% CL À2%, 13%). The best model (AIC) gave a superpopulation estimate of 1007 males (95% CL 794, 1276) and an estimated annual increase of 7% (95% CL 5%, 9%) for 1995-2009. Combined, the total superpopulation estimate for 1995-2009 was 2169 whales (95% CL 1836, 2563). Simulations suggest that failure to account for the effect of reproductive status on the capture probability would result in a substantial positive bias (þ19%) in female abundance estimates.

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 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 datasets 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.PeerJ Preprints | https://doi.org/10.7287/peerj.preprints.3209v1 | CC BY 4.0 Open Access |

Reconstructing the history of exploited populations of whales requires fitting a trajectory through at least three points in time: (i) prior to exploitation, when abundance is assumed to be at the maximum allowed by environmental carrying capacity; (ii) the point of minimum abundance or 'bottleneck', usually near the time of protection or the abandonment of the hunt; and (iii) near the present, when protected populations are assumed to have undergone some recovery. As historical abundance is usually unknown, this trajectory must be extrapolated according to a population dynamic model using catch records, an assumed rate of increase and an estimate of current abundance, all of which have received considerable attention by the International Whaling Commission (IWC). Relatively little attention has been given to estimating minimum abundance (N(min)), although it is clear that genetic and demographic forces at this point are critical to the potential for recovery or extinction of a local population. We present a general analytical framework to improve estimates of N(min) using the number of mtDNA haplotypes (maternal lineages) surviving in a contemporary population of whales or other exploited species. We demonstrate the informative potential of this parameter as an a posteriori constraint on Bayesian logistic population dynamic models based on the IWC Comprehensive Assessment of the intensively exploited southern right whales (Eubalaena australis) and published surveys of mtDNA diversity for this species. Estimated historical trajectories from all demographic scenarios suggested a substantial loss of mtDNA haplotype richness as a result of 19th century commercial whaling and 20th century illegal whaling by the Soviet Union. However, the relatively high rates of population increase used by the IWC assessment predicted a bottleneck that was implausibly narrow (median, 67 mature females), given our corrected estimates of N(min). Further, high levels of remnant sequence diversity (theta) suggested that pre-exploitation abundance was larger than predicted by the logistic model given the catch record, which is known to be incomplete. Our results point to a need to better integrate evolutionary processes into population dynamic models to account for uncertainty in catch records, the influence of maternal fidelity on metapopulation dynamics, and the potential for inverse density dependence (an 'Allee effect') in severely depleted populations.