DNA in Action: Rapid Application of DNA Variation to Sockeye Salmon Fisheries Management

Commitment to conservation-based management of exploited fish species imposes unprecedented requirements for adaptive, real-time management of biologically and socially complex mixed-stock fisheries such as those conducted for Pacific salmon. Stock identification is a key component of the management process, with population-specific timing and abundance information often incorporated into management decisions. By using both microsatellite and major histocompatibility complex genetic variation, we achieved highly accurate estimates of stock composition for Fraser River sockeye salmon. Over a 2-month period in 2002, we analyzed 9300 returning Fraser River sockeye salmon sampled in mixed-stock fisheries, and provided stock composition estimates to fishery managers within 9–30 h of sample delivery. Stock-specific exploitation targets governed by conservation concerns were achieved in this fishery.     

Comparison of SNPs and microsatellites for fine-scale application of genetic stock identification of Chinook salmon in the Columbia River Basin

Genetic stock identification (GSI) is an important tool in fisheries management. Microsatellites (μSATs) have been the dominant genetic marker for GSI; however, increasing availability and numerous advantages of single-nucleotide polymorphism (SNP) markers make them an appealing alternative. We tested performance of 13 μSAT vs. 92 SNP loci in a fine-scale application of GSI, using a new baseline for Chinook salmon consisting of 49 collections (n = 4014) distributed across the Columbia River Basin. In GSI, baseline genotypes for both marker sets were used independently to analyse a real fishery mixture (n = 2731) representing the total run of Chinook salmon passing Bonneville Dam in the Columbia River. Marker sets were evaluated using three criteria: (i) ability to differentiate reporting groups, (ii) proportion of correct assignment in mixture simulation tests and baseline leave-one-out analyses and (iii) individual assignment and confidence intervals around estimated stock proportions of a real fishery mixture. The μSATs outperformed the SNPs in resolving fine-scale relationships, but all 105 markers combined provided greatest power for GSI. SNPs were ranked by relative information content based on both an iterative procedure that optimized correct assignment to the baseline and ranking by minor allele frequency. For both methods, we identified a subset of the top 50 ranked loci, which were similar in assignment accuracy, and both reached maximum available power of the total 92 SNP loci (correct assignment = 73%). Our estimates indicate that between 100 and 200 highly informative SNP loci are required to meet management standards (correct assignment > 90%) for resolving stocks in finer-scale GSI applications.     

Minisatellite DNA variation and stock identification of coho salmon

Geographic variation in minisatellite DNA variation was examined in 18 stocks of coho salmon Oncorhynchus kisutch from British Columbia and three stocks from Kamchatka or Western Alaska. Genomic DNA was restricted with Mbo I or Hae III and hybridized with two minisatellite probes (p Ssa -A34, Ots PBS-1). Allele frequencies and DNA band counts derived from the two probes were combined with band counts from the probe Ssa to show a regional stock structure. In British Columbia, stocks from the Fraser River were distinct from those on Vancouver Island, and all were differentiated from those on the mainland of British Columbia. Average heterozygosity at the Ssa -A34 locus was 71%. Compared with a previous study of British Columbia coho salmon population structure in which variation at 26 allozyme loci was examined, greater population differentiation and higher heterozygosity were observed at minisatellite loci. Estimated stock compositions of simulated mixtures of fishery samples from British Columbia stocks were accurate and precise, with the potential of identifying stocks within the drainage basin of a major river, the Fraser River. Minisatellite DNA variation may provide accurate and precise estimates of stock composition in actual fishery applications, and has the potential of identifying individual fish to region or stock of origin.     

Close relatives in population samples: Evaluation of the consequences for genetic stock identification

Determining the origin of individuals in mixed population samples is key in many ecological, conservation and management contexts. Genetic data can be analyzed using genetic stock identification (GSI), where the origin of single individuals is determined using Individual Assignment (IA) and population proportions are estimated with Mixed Stock Analysis (MSA). In such analyses, allele frequencies in a reference baseline are required. Unknown individuals or mixture proportions are assigned to source populations based on the likelihood that their multilocus genotypes occur in a particular baseline sample. Representative sampling of populations included in a baseline is important when designing and performing GSI. Here, we investigate the effects of family sampling on GSI, using both simulated and empirical genotypes for Atlantic salmon (Salmo salar). We show that nonrepresentative sampling leading to inclusion of close relatives in a reference baseline may introduce bias in estimated proportions of contributing populations in a mixed sample, and increases the amount of incorrectly assigned individual fish. Simulated data further show that the induced bias increases with increasing family structure, but that it can be partly mitigated by increased baseline population sample sizes. Results from standard accuracy tests of GSI (using only a reference baseline and/or self‐assignment) gave a false and elevated indication of the baseline power and accuracy to identify stock proportions and individuals. These findings suggest that family structure in baseline population samples should be quantified and its consequences evaluated, before carrying out GSI.     

Assessing seasonal changes in stock composition of Atlantic salmon catches in the Baltic Sea with genetic stock identification

The feasibility of using genetic stock identification to analyse seasonal changes in stock compositions of Atlantic salmon catches in the Baltic Sea was examined. The analysis employed seven variable allozyme loci from most of the potentially contributing stocks (16) from Finland and Sweden. Catch samples were collected from Finnish salmon fisheries in the eastern Bothnian Sea during the 1992 fishing season. Simulation studies were used to evaluate the feasibility of identifying Baltic salmon stocks with allozyme data. Special attention was paid to analysing the wild production of salmon stocks. Clear seasonal differences in stock composition were found. The estimates were compared with smolt production and Carlin-tag data. The proportions of the Neva and Oulujoki river stocks could be estimated as individual stocks, whereas the contributions of the remaining stocks were estimated as four composite stock groups. One of the groups consisted of wild stocks from the rivers Kalixälven and Simojoki. Identification of this group, which could be used as an index of wild production in the catches, requires catch sample sizes >300 salmon if <15% error is required.     

Microsatellite DNA Population Structure and Stock Identification of Steelhead Trout (<Emphasis Type="BoldItalic">Oncorhynchus mykiss</Emphasis>) in the Nass and Skeena Rivers in Northern British Columbia

Population structure and the application to genetic stock identification for steelhead (Oncorhynchus mykiss) in the Nass and Skeena Rivers in northern British Columbia was examined using microsatellite markers. Variation at 8 microsatellite loci (Oki200, Omy77, Ots1, Ots3, Ssa85, Ots100, Ots103, and Ots108) was surveyed for approximately 930 steelhead from 7 populations in the Skeena River drainage and 850 steelhead from 10 populations in the Nass River drainage, as well as 1550 steelhead from test fisheries near the mouth of each river. Differentiation among populations within rivers accounted for about 1.9 times the variation observed among years within populations, with differences between drainages less than variation among populations within drainages. In the Nass River, winter-run populations formed a distinct group from the summer-run populations. Winter-run populations were not assessed in the Skeena River watershed. Simulated mixed-stock samples suggested that variation at the 8 microsatellite loci surveyed should provide relatively accurate and precise estimates of stock composition for fishery management applications within drainages. In the Skeena River drainage in 1998, Babine River (27%) and Bulkley drainage populations (31%) comprised the main components of the returns. For the Nass River in 1998 steelhead returning to Bell-Irving River were estimated to have comprised 39% of the fish sampled in the test fishery, with another 27% of the returns estimated to be derived from Cranberry River. The survey of microsatellite variation did not reveal enough differentiation between Nass River and Skeena River populations to be applied confidently in estimation of stock composition in marine fisheries at this time. Received January 14, 2000; accepted July 13, 2000.     

Population Structure and Stock Identification of Steelhead Trout (Oncorhynchus mykiss) in British Columbia and the Columbia River Based on Microsatellite Variation

Variation at 13 microsatellite loci was surveyed from ～3 800 steelhead trout, Oncorhynchus mykiss, from 51 populations in British Columbia, Washington, and the Columbia River drainage. Mean F_ST over all 13 loci and 51 populations was 0.066. Regional structuring of populations was apparent, with Thompson River, upper Fraser River, and Columbia River populations forming distinct groups. In the Nass River, winter-run populations were distinct from the summer-run populations. Significant differences in allele frequencies were observed among regional stock groups at all loci. Analysis of variance components indicated that 5.7% of the total observed variation was distributed among 11 regions, and 2.3% of the variation was among populations within regions. Analysis of simulated mixed-stock samples suggested that variation at the microsatellite loci provided relatively accurate and precise estimates of stock composition for fishery management applications, and this was confirmed by application to actual fishery samples of known origin. Within the Fraser River drainage, individual steelhead trout can be identified to one of the three regions of origin with an accuracy of 94–97%. Microsatellites provided an effective way to determine population structure, and provided reliable estimates of stock composition in mixed-stock fisheries.     

Genetic stock identification of Atlantic salmon (Salmo salar) populations in the southern part of the European range

Background

Anadromous migratory fish species such as Atlantic salmon (Salmo salar) have significant economic, cultural and ecological importance, but present a complex case for management and conservation due to the range of their migration. Atlantic salmon exist in rivers across the North Atlantic, returning to their river of birth with a high degree of accuracy; however, despite continuing efforts and improvements in in-river conservation, they are in steep decline across their range. Salmon from rivers across Europe migrate along similar routes, where they have, historically, been subject to commercial netting. This mixed stock exploitation has the potential to devastate weak and declining populations where they are exploited indiscriminately. Despite various tagging and marking studies, the effect of marine exploitation and the marine element of the salmon lifecycle in general, remain the "black-box" of salmon management. In a number of Pacific salmonid species and in several regions within the range of the Atlantic salmon, genetic stock identification and mixed stock analysis have been used successfully to quantify exploitation rates and identify the natal origins of fish outside their home waters - to date this has not been attempted for Atlantic salmon in the south of their European range.

Results

To facilitate mixed stock analysis (MSA) of Atlantic salmon, we have produced a baseline of genetic data for salmon populations originating from the largest rivers from Spain to northern Scotland, a region in which declines have been particularly marked. Using 12 microsatellites, 3,730 individual fish from 57 river catchments have been genotyped. Detailed patterns of population genetic diversity of Atlantic salmon at a sub-continent-wide level have been evaluated, demonstrating the existence of regional genetic signatures. Critically, these appear to be independent of more commonly recognised terrestrial biogeographical and political boundaries, allowing reporting regions to be defined. The implications of these results on the accuracy of MSA are evaluated and indicate that the success of MSA is not uniform across the range studied; our findings indicate large differences in the relative accuracy of stock composition estimates and MSA apportioning across the geographical range of the study, with a much higher degree of accuracy achieved when assigning and apportioning to populations in the south of the area studied. This result probably reflects the more genetically distinct nature of populations in the database from Spain, northwest France and southern England. Genetic stock identification has been undertaken and validation of the baseline microsatellite dataset with rod-and-line and estuary net fisheries of known origin has produced realistic estimates of stock composition at a regional scale.

Conclusions

This southern European database and supporting phylogeographic and mixed-stock analyses of net samples provide a unique tool for Atlantic salmon research and management, in both their natal rivers and the marine environment. However, the success of MSA is not uniform across the area studied, with large differences in the relative accuracy of stock composition estimates and MSA apportioning, with a much higher degree of accuracy achieved when assigning and apportioning to populations in the south of the region. More broadly, this study provides a basis for long-term salmon management across the region and confirms the value of this genetic approach for fisheries management of anadromous species.     

Using 2 Genetic Markers to Discriminate Among Canada Goose Populations in Ohio

Abstract: Canada goose (Branta canadensis) harvest management depends on reliable estimates of harvest composition, and established genetic methods provide an alternative to traditional methods. We expanded upon previous genetic studies by comparing the utility of 6 nuclear microsatellite loci and mitochondrial (mtDNA) control region sequences for discriminating among giant (B. c. maxima) and interior (B. c. interior) populations in Ohio (USA) Canada goose harvests at both individual and population levels. Subspecies and populations exhibited greater differentiation in mtDNA (F_ST = 0.202) than microsatellites (F_ST = 0.021), as would be expected based on differences in effective population size. Neither microsatellites nor mtDNA alone were sufficient for estimating harvest composition at the subspecies or population level in simulations and empirical blind tests using individuals of known origin; however, a combined microsatellite + mtDNA dataset yielded accurate and precise harvest derivations at the subspecies level. Both population-level mixed stock analysis and individual-level assignment tests provided accurate results, but a large proportion of birds could not be assigned with confidence at the individual level. We applied mixed stock analysis and the combined microsatellite + mtDNA dataset to Ohio's 2003–2004 harvest and found that interior populations accounted for 4.9% (95% CI = 1.7–8.0%) of the statewide early season and 9.3% (95% CI = 6.9–11.6%) of the regular and late-season harvested sample. These results suggest that maximum likelihood harvest derivations are highly dependent on the choice of genetic markers. Studies should only employ markers that exhibit sufficient variation and have been shown through simulations and empirical testing to accurately discriminate among the subspecies or management populations of interest.     

Population genetics of Mioscirtus wagneri,a grasshopper showing a highly fragmented distribution

The genetic consequences of population fragmentation and isolation are major issues in conservation biology. In this study we analyse the genetic variability and structure of the Iberian populations of Mioscirtus wagneri, a specialized grasshopper exclusively inhabiting highly fragmented hypersaline low grounds. For this purpose we have used seven species‐specific microsatellite markers to type 478 individuals from 24 localities and obtain accurate estimates of their genetic variability. Genetic diversity was relatively low and we detected genetic signatures suggesting that certain populations of M. wagneri have probably passed through severe demographic bottlenecks. We have found that the populations of this grasshopper show a strong genetic structure even at small geographical scales, indicating that they mostly behave as isolated populations with low levels of gene flow among them. Thus, several populations can be regarded as independent and genetically differentiated units which require adequate conservation strategies to avoid eventual extinctions that in highly isolated localities are not likely to be compensated for with the arrival of immigrants from neighbouring populations. Overall, our results show that these populations probably represent the ‘fragments’ of a formerly more widespread population and highlight the importance of protecting Iberian hypersaline environments due to the high number of rare and endangered species they sustain.     

Estimating quantitative genetic parameters in wild populations: a comparison of pedigree and genomic approaches

The estimation of quantitative genetic parameters in wild populations is generally limited by the accuracy and completeness of the available pedigree information. Using relatedness at genomewide markers can potentially remove this limitation and lead to less biased and more precise estimates. We estimated heritability, maternal genetic effects and genetic correlations for body size traits in an unmanaged long‐term study population of Soay sheep on St Kilda using three increasingly complete and accurate estimates of relatedness: (i) Pedigree 1, using observation‐derived maternal links and microsatellite‐derived paternal links; (ii) Pedigree 2, using SNP‐derived assignment of both maternity and paternity; and (iii) whole‐genome relatedness at 37 037 autosomal SNPs. In initial analyses, heritability estimates were strikingly similar for all three methods, while standard errors were systematically lower in analyses based on Pedigree 2 and genomic relatedness. Genetic correlations were generally strong, differed little between the three estimates of relatedness and the standard errors declined only very slightly with improved relatedness information. When partitioning maternal effects into separate genetic and environmental components, maternal genetic effects found in juvenile traits increased substantially across the three relatedness estimates. Heritability declined compared to parallel models where only a maternal environment effect was fitted, suggesting that maternal genetic effects are confounded with direct genetic effects and that more accurate estimates of relatedness were better able to separate maternal genetic effects from direct genetic effects. We found that the heritability captured by SNP markers asymptoted at about half the SNPs available, suggesting that denser marker panels are not necessarily required for precise and unbiased heritability estimates. Finally, we present guidelines for the use of genomic relatedness in future quantitative genetics studies in natural populations.     

Genetic affinities of an introduced predator: Nile perch in Lake Victoria, East Africa

Although the introduction of Nile perch, Lates niloticus , to Lake Victoria has received intense global attention, especially in relation to its impact on endemic cichlid species and on fishery yields, fundamental information on its taxonomy and population genetics is lacking. Most importantly, the introduced fish originated from two lakes (Lakes Albert and Turkana) containing three Lates species, and it has never been entirely clear which of these became established in Lake Victoria, or indeed whether the Lake Victoria population is derived from hybridization between Lates species. In addition, genetic drift caused by the relatively small founder population (≈ 400), the initially slow population increase followed by a period of explosive population growth, and selection pressures in the new environment may have resulted in substantial genetic changes. Allozyme data indicated that the introduced Nile perch of Lake Victoria were mainly L. niloticus from Lake Albert, although maximum likelihood estimates of stock contributions (GSI) suggested the presence of L. macrophthalmus. In contrast, introduced Nile perch in adjacent smaller lakes (Lakes Kyoga and Nabugabo) appeared to be entirely L. niloticus . The effect of the introductions on allozyme diversity varied among lakes and appeared to be uncorrelated to the number of fish introduced.     

Population Structure and Stock Identification of Eulachon (Thaleichthys pacificus), an Anadromous Smelt, in the Pacific Northwest

The genetic structure of eulachon (Thaleichthys pacificus) populations was examined in an analysis of variation of 14 microsatellite loci representing approximately 1900 fish from 9 sites between the Columbia River and Cook Inlet, Alaska. Significant genetic differentiation occurred among the putative populations. The mean F_ST for all loci was 0.0046, and there was a significant correlation between population genetic differentiation (F_ST) and geographic distance. Simulated mixed-stock samples comprising populations from different regions suggested that variation at microsatellite loci provided reasonably accurate estimates of stock composition for potential fishery samples. Marine sampling indicated that immature eulachons from different rivers, during the 2 to 3 years of prespawning life in offshore marine waters, do not mix thoroughly. For eulachons captured incidentally in offshore trawl fisheries, there was a clear geographic cline in relative abundance of eulachons from different geographic areas. The sample from northern British Columbia was dominated by northern and central coastal populations of British Columbia, the sample from central British Columbia was composed of eulachons from all regions, and the sample from southern British Columbia was dominated by Columbia River and Fraser River populations. These results have implications for the management of trawl fisheries and conservation of spawning populations in some rivers where abundance is at historically low levels.     

Stock enhancement as a fisheries management tool

Stock enhancement has been viewed as a positive fisheries management tool for over 100 years. However, decisions to undertake such activities in the past have often been technology-based, i.e., driven by the ability to produce fishes, with most stock enhancement projects having limited or no demonstrated success. The reasons for this have been due to an inability to identify and/or control the underlying reasons why a fishery is under-performing or not meeting management objectives. Further, stock enhancement has often been applied in isolation from other fisheries management tools (e.g., effort control). To address these issues and consider stock enhancement in a broader ecosystem perspective, a new approach for stock enhancement is proposed. The proposed model comprises four major steps; a review of all information about an ecosystem/fishery/stock and the setting of clear management targets; a comparison of all relevant fisheries management tools with the potential to meet the management targets; the instigation of a scientifically based, pilot-scale, stock enhancement program with clear objectives, targets, and evaluations; and a full-scale stock enhancement program if the pilot project meets the objectives. The model uses a flow-chart that highlights a broad range of scientific and other information, and the decisions that need to be made in relation to stock enhancement and fisheries management in general. In this way all steps are transparent and all stakeholders (managers, scientists, extractive and non-extractive users, and the general public) can contribute to the information collection and decision making processes. If stock enhancement is subsequently identified as the most-appropriate tool, then the stepwise progression will provide the best possible chance of a positive outcome for a stock enhancement project, while minimizing risks and costs. In this way, stock enhancement may advance as a science and develop as a useful fisheries management tool in appropriate situations.     

An overview of recent global experience with recovery plans for depleted marine resources and suggested guidelines for recovery planning

Progress with stock recovery plans to date for depleted marine resources is reviewed, based on published and publicly available sources. Most plans began within the last two decades, so quantifying progress is difficult, but some 60 cases were found where a recovery effort had been explicitly tackled by either a closure or restrictive measures, and seven documented case studies were used to draw general conclusions on recovery procedures and to provide a list of considerations for best practice in recovery planning. More successes were documented for pelagic .sheries than demersals, especially with closures, while spontaneous recoveries of some depleted invertebrate resources seem related to reductions in predator pressure. Few shared, straddling or highly migratory stocks have been restored to date. Most successful recoveries occurred in the centre of the species geographical range and/or in favourable regimes. Success seems to depend on non-discretionary fishery control laws being applied. Depletions aggravated by unfavourable climatic regimes will be difficult to reverse, as illustrated by a simulation. Durations of recovery plans in particular depend on regime, and using stock information from favourable regimes to predict plan duration should be treated with caution. Although successful recoveries to date have tended to be decadal, a considerable proportion are still underway, and are likely to exceed this duration. An erratum to this article is available at .     

Genetic analysis provides insights into species distribution and population structure in East Atlantic horse mackerel (Trachurus trachurus and T. capensis)

Two sister species of horse mackerel (Trachurus trachurus and T. capensis) are described that are intensively harvested in East Atlantic waters. To address long-standing uncertainties as to their respective geographical ranges, overlap and intraspecific population structure this study combined genetic (mitochondrial DNA and microsatellite) analysis and targeted sampling of the hitherto understudied West African coast. mtDNA revealed two reciprocally monophyletic clades corresponding to each species with interspecies nuclear differentiation supported by F_ST values. The T. trachurus clade was found across the north-east Atlantic down to Ghana but was absent from Angolan and South African samples. The T. capensis clade was found only in South Africa, Angola and a single Ghanaian individual. This pattern suggests that both species may overlap in the waters around Ghana. The potential for cryptic hybridization and/or indiscriminate harvesting of both species in the region is discussed. For T. capensis mtDNA supports high gene flow across the Benguela upwelling system, which fits with the species' ecology. The data add to evidence of a lack of significant genetic structure throughout the range of T. trachurus though the assumption of demographic panmixia is cautioned against. For both species, resolution of stock recruitment heterogeneity relevant to fishery management, as well as potential hybridization, will require more powerful genomic analyses.     

土壤有机碳库的关键影响因素及其不确定性

土壤是陆地生态系统最大的有机碳库,比植被碳库或大气碳库的两倍还多。准确评估土壤有机碳库是预测全球变化与土壤有机碳之间反馈关系的关键。但目前对土壤有机碳库的估算还存在很大不确定性。该文综述了土壤有机碳库估算及其影响因素和土壤有机碳库估算不确定性的来源和常用的采样方法,以及计算土壤碳汇的最新研究进展。未来技术进步以及模型的不断完善可能会降低土壤有机碳库估算的不确定性,提高其估算的精度     

南海北部近海渔业资源密度概率分布特征

根据2014-2017年南海北部近海8个调查航次渔获量数据,结合统计方法分析该海域渔业资源密度分布特征并探索其适宜概率分布类型,进而估算区域平均资源密度.结果表明:各时期资源密度变异系数(CV)在0.67~1.03,说明该海域渔业资源密度呈较高程度的不均匀空间分布,且渔获资源密度频率分布呈现明显的右偏特征,总体以0~1000 kg·km-2资源密度为主导;单样本Kolmogorov-Smirnov检验结果表明,对数正态、伽玛和韦伯分布是该区域资源密度的适宜分布类型;在海域平均资源密度估算方面,对数正态所得结果与另两个分布类型在统计学上无显著差异,而伽玛和韦伯分布的估计值有显著差异.与1960-1970年代相比,该海域渔业资源密度适宜概率分布型已从单一类型转变为多类型,这主要归于渔业资源结构、捕捞强度以及气候变化等引起的低渔获量比例变化.     

Heritability and evolvability of fitness and nonfitness traits: Lessons from livestock

Data from natural populations have suggested a disconnection between trait heritability (variance standardized additive genetic variance, V_A) and evolvability (mean standardized V_A) and emphasized the importance of environmental variation as a determinant of trait heritability but not evolvability. However, these inferences are based on heterogeneous and often small datasets across species from different environments. We surveyed the relationship between evolvability and heritability in >100 traits in farmed cattle, taking advantage of large sample sizes and consistent genetic approaches. Heritability and evolvability estimates were positively correlated (r = 0.37/0.54 on untransformed/log scales) reflecting a substantial impact of V_A on both measures. Furthermore, heritabilities and residual variances were uncorrelated. The differences between this and previously described patterns may reflect lower environmental variation experienced in farmed systems, but also low and heterogeneous quality of data from natural populations. Similar to studies on wild populations, heritabilities for life‐history and behavioral traits were lower than for other traits. Traits having extremely low heritabilities and evolvabilities (17% of the studied traits) were almost exclusively life‐history or behavioral traits, suggesting that evolutionary constraints stemming from lack of genetic variability are likely to be most common for classical “fitness” (cf. life‐history) rather than for “nonfitness” (cf. morphological) traits.     

neogen: A tool to predict genetic effective population size (Ne) for species with generational overlap and to assist empirical Ne study design

Molecular genetic estimates of population effective size (N_e) lose accuracy and precision when insufficient numbers of samples or loci are used. Ideally, researchers would like to forecast the necessary power when planning their project. neogen (genetic N_e for Overlapping Generations) enables estimates of precision and accuracy in advance of empirical investigation and allows exploration of the power available in different user‐specified age‐structured sampling schemes. neogen provides a population simulation and genetic power analysis framework that simulates the demographics, genetic composition, and N_e, from species‐specific life history, mortality, population size, and genetic priors. neogen guides the user to establish a tractable sampling regime and to determine the numbers of samples and microsatellite or SNP loci required for accurate and precise genetic N_e estimates when sampling a natural population. neogen is useful at multiple stages of a study's life cycle: when budgeting, as sampling and locus development progresses, and for corroboration when empirical N_e estimates are available. The underlying model is applicable to a wide variety of iteroparous species with overlapping generations (e.g., mammals, birds, reptiles, long‐lived fishes). In this paper, we describe the neogen model, detail the workflow for the point‐and‐click software, and explain the graphical results. We demonstrate the use of neogen with empirical Australian east coast zebra shark (Stegostoma fasciatum) data. For researchers wishing to make accurate and precise genetic N_e estimates for overlapping generations species, neogen facilitates planning for sample and locus acquisition, and with existing empirical genetic N_e estimates neogen can corroborate population demographic and life history properties.