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Abstract Estimation of the effective number of breeders per reproductive event (Nb) using single sample DNA-marker-based methods has rapidly grown in recent years. However, estimating Nb is difficult in age-structured populations because the performance of estimators is influenced by the Nb / Ne ratio, which varies among species with different life histories. We provide a computer program, AgeStrucNb, to simulate age-structured populations (including life history) and also estimate Nb. The AgeStrucNb program is composed of 4 major components to simulate, subsample, estimate, and then visualize Nb time series data. AgeStrucNb allows users to also quantify the precision and accuracy of any set of loci or sample size to estimate Nb for many species and populations. AgeStrucNb allows users to conduct power analysis to evaluate sensitivity to detect changes in Nb or the power to detect a correlation between trends in Nb and environmental variables (e.g., temperature, habitat quality, predator or pathogen abundance) that could be driving changes in Nb. The software provides Nb estimates for empirical data sets using the LDNe (linkage disequilibrium) method, includes publication-quality output graphs, and outputs genotype files in Genepop format for use in other programs. AgeStrucNb will help advance the application of genetic markers for monitoring Nb, which will help biologists to detect population declines and growth, which is crucial for research and conservation of natural and managed populations. 

Environmental change is intensifying the biodiversity crisis and threatening species across the tree of life. Conservation genomics can help inform conservation actions and slow biodiversity loss. However, more training, appropriate use of novel genomic methods and communication with managers are needed. Here, we review practical guidance to improve applied conservation genomics. We share insights aimed at ensuring effectiveness of conservation actions around three themes: (1) improving pedagogy and training in conservation genomics including for online global audiences, (2) conducting rigorous population genomic analyses properly considering theory, marker types and data interpretation and (3) facilitating communication and collaboration between managers and researchers. We aim to update students and professionals and expand their conservation toolkit with genomic principles and recent approaches for conserving and managing biodiversity. The biodiversity crisis is a global problem and, as such, requires international involvement, training, collaboration and frequent reviews of the literature and workshops as we do here.

 

Identification of genes underlying genomic signatures of natural selection is key to understanding adaptation to local conditions. We used targeted resequencing to identifySNPmarkers in 5321 candidate adaptive genes associated with known immunological, metabolic and growth functions in ovids and other ungulates. We selectively targeted 8161 exons in protein‐coding and nearby 5′ and 3′ untranslated regions of chosen candidate genes. Targeted sequences were taken from bighorn sheep (Ovis canadensis) exon capture data and directly from the domestic sheep genome (Ovis ariesv. 3; oviAri3). The bighorn sheep sequences used in the Dall's sheep (Ovis dalli dalli) exon capture aligned to 2350 genes on the oviAri3 genome with an average of 2 exons each. We developed a microfluidic qPCR‐basedSNPchip to genotype 476 Dall's sheep from locations across their range and test for patterns of selection. Using multiple corroborating approaches (lositanandbayescan), we detected 28SNPloci potentially under selection. We additionally identified candidate loci significantly associated with latitude, longitude, precipitation and temperature, suggesting local environmental adaptation. The three methods demonstrated consistent support for natural selection on nine genes with immune and disease‐regulating functions (e.g. Ovar‐DRA,APC,BATF2,MAGEB18), cell regulation signalling pathways (e.g.KRIT1,PI3K,ORRC3), and respiratory health (CYSLTR1). Characterizing adaptive allele distributions from novel genetic techniques will facilitate investigation of the influence of environmental variation on local adaptation of a northern alpine ungulate throughout its range. This research demonstrated the utility of exon capture for gene‐targetedSNPdiscovery and subsequentSNPchip genotyping using low‐quality samples in a nonmodel species.