Estimates Of Effective Population Size Research Articles

Population genomics and demographic modeling enhance our understanding of trophic level interactions in biological control

In this paper, we focus on the application of population genomics, including next-generation sequencing and demographic modeling, to enhance the understanding of historical and contemporary trophic level interactions that are a fundamental basis of biological control. We outline how the integration of ecological approaches with population genomics and demographic modeling can provide additional insights into existing trophic interactions and how natural enemies, their parasitoids, and pest species evolve through these interactions, potentially affecting future levels of biological control. We briefly review and summarize our recent population genomic studies of predatory ladybird beetles and discuss how our results provide guidelines for the use of population genomics techniques and population demographic modeling to enhance our understanding of trophic level interactions. Our intent is to demonstrate as a proof of concept, how these methods can supplement currently used techniques and add a complementary genomic aspect to ecological understandings of trophic level interactions, including estimates of effective population sizes of natural enemies and pest species, examination of correlations between these effective population sizes, and evolutionary changes in natural enemies and pest species which may influence levels of biological control. This in combination with experiments and simulations provide a well-rounded framework for using population genomics to inform multi-tier trophic level interactions.

Genomic Characterization of Local Croatian Sheep Breeds-Effective Population Size, Inbreeding & Signatures of Selection.

The Istrian (IS) and the Pag sheep (PS) are local Croatian breeds which provide significant income for the regional economy and have a cultural and traditional importance for the inhabitants. The aim of this study was to estimate some important population specific genetic parameters in IS (N = 1293) and PS (N = 2637) based on genome wide SNPs. Estimates of linkage disequilibrium effective population size (Ne) evidenced more genetic variability in PS (Ne = 838) compared to IS (Ne = 197), regardless of historical time (both recent and ancient genetic variability). The discrepancy in the recent genetic variability between these breeds was additionally confirmed by the estimates of genomic inbreeding (FROH), which was estimated to be notably higher in IS (FROH>2 = 0.062) than in PS (FROH>2 = 0.029). The average FROH2-4, FROH4-8, FROH8-16, and FROH>16 were 0.26, 1.65, 2.14, and 3.72 for IS and 0.22, 0.61, 0.75, and 1.58 for PS, thus evidencing a high contribution of recent inbreeding in the overall inbreeding. One ROH island with > 30% of SNP incidence in ROHs was detected in IS (OAR6; 34,253,440-38,238,124 bp) while there was no ROH islands detected in PS. Seven genes (CCSER1, HERC3, LCORL, NAP1L5, PKD2, PYURF, and SPP1) involved in growth, feed intake, milk production, immune responses, and resistance were associated with the found autozygosity. The results of this study represent the first comprehensive insight into genomic variability of these two Croatian local sheep breeds and will serve as a baseline for setting up the most promising strategy of genomic Optimum Contribution Selection.

Low-coverage sequencing and Wahlund effect severely bias estimates of inbreeding, heterozygosity and effective population size in North American wolves.

vonHoldt etal. ((2024), Molecular Ecology, 33, e17231) (vH24) used low-coverage (average ~ 7X read depth) restriction site-associated DNA sequence data to estimate individual inbreeding and heterozygosity, and recent effective population size (Ne), in Great Lakes (GL) and Northern Rocky Mountain (RM) wolves. They concluded that RM heterozygosity rapidly declined between 1991 and 2020, and that Ne declined substantially in GL and RM over the last 50 generations. Here, we evaluate the effects of low sequence coverage and sampling strategy on vH24's findings and provide general recommendations for using sequence data to evaluate inbreeding, heterozygosity and Ne. Low-coverage sequencing resulted in downwardly biased estimates of individual inbreeding and heterozygosity, and an erroneous large temporal decline in RM heterozygosity due to declining read depth through time. Additionally, vH24's sampling strategy-which combined individuals from several genetically differentiated populations and across at least eight wolf generations-is expected to have resulted in severe downward bias in estimates of recent Ne for RM. We recommend using high-coverage sequence data ( 15-20X) to estimate inbreeding and heterozygosity. Carefully filtering individuals, loci and genotypes, and using genotype imputation or likelihoods can help to minimise bias when low-coverage sequence data must be used. For estimation of contemporary Ne, the marginal benefits of using more than 103-104 loci are small, so aggressive filtering of loci with low average read depth potentially can retain most individuals without sacrificing much precision. Individuals are relatively more valuable than loci because analyses of contemporary Ne should focus on roughly single-generation samples from local breeding populations.

Equivalent mating system parameters in post‐mining and undisturbed native plant populations confirms restitution of bird‐pollinator function

Abstract The restoration of diverse self‐sustaining ecosystems requires re‐establishment of functional interactions among species. For plant communities, pollinators are usually essential for pollination, seed set and seed quality. A common assumption in ecological restoration for plants pollinated by animals is one of ‘build it and they will come’, which is rarely tested. Beyond seed set, there may be negative genetic consequences for seed quality if pollinators and their behaviour do not reflect those in reference populations. Here, we conduct an ecological genetic assessment of seed quality via mating system parameters in Lambertia multiflora (Proteaceae), a species dependent on nectar‐feeding birds for pollination. Four populations of L. multiflora in disturbed sites that were rehabilitated following mineral sands mining were compared with four native reference populations, near Eneabba, Western Australia. In each population, approximately 10 offspring from each of 10 maternal plants were genotyped with 11 highly polymorphic microsatellite markers. From these data, genetic diversity and mating system parameters were assessed, and found to be equivalent across all populations. Mean allelic diversity and heterozygosity across loci were very high. All populations were completely outcrossing with no bi‐parental inbreeding. Mean correlated paternity, sibship and effective population size estimates for restored and natural populations were not significantly different and reflected uniformly high paternal diversity and wide outcrossing. Equivalent genetic results for restored and natural reference populations indicate successful restitution of bird‐pollinator services for L. multiflora in these post‐mining rehabilitation sites. Synthesis and applications. Reviewing our results with other published studies to date suggests a resilience of bird‐pollinator services in restored plant communities. These findings provide some reassurance to restoration practitioners working in these global south systems where bird pollination is a feature, at least for similar landscape scenarios. Our study also highlights the global contribution of ecological genetics to the objective assessment of functional species interactions in ecological restoration, an increasingly important goal of land managers and regulators seeking to improve restoration standards.

Estimation of contemporary effective population size in plant populations: Limitations of genomic datasets.

Effective population size (N e) is a pivotal evolutionary parameter with crucial implications in conservation practice and policy. Genetic methods to estimate N e have been preferred over demographic methods because they rely on genetic data rather than time-consuming ecological monitoring. Methods based on linkage disequilibrium (LD), in particular, have become popular in conservation as they require a single sampling and provide estimates that refer to recent generations. A software program based on the LD method, GONE, looks particularly promising to estimate contemporary and recent-historical N e (up to 200 generations in the past). Genomic datasets from non-model species, especially plants, may present some constraints to the use of GONE, as linkage maps and reference genomes are seldom available, and SNP genotyping is usually based on reduced-representation methods. In this study, we use empirical datasets from four plant species to explore the limitations of plant genomic datasets when estimating N e using the algorithm implemented in GONE, in addition to exploring some typical biological limitations that may affect N e estimation using the LD method, such as the occurrence of population structure. We show how accuracy and precision of N e estimates potentially change with the following factors: occurrence of missing data, limited number of SNPs/individuals sampled, and lack of information about the location of SNPs on chromosomes, with the latter producing a significant bias, previously unexplored with empirical data. We finally compare the N e estimates obtained with GONE for the last generations with the contemporary N e estimates obtained with the programs currentNe and NeEstimator.

Genetic variation of English yew (Taxus baccata L.) in the Bavarian Forest National Park, Germany

AbstractTaxus baccata L. is a highly valuable species with wide distribution but scattered and locally rare occurrence. Human intervention, including forest management practices and fragmentation, can significantly impact the species’ genetic diversity, structure, and dynamics. In this study, we investigated these factors within T. baccata populations in the Bavarian Forest National Park (NP) in Germany and their implications for conservation. We used 13 EST-SSRs to assess the genetic diversity and structure of the population. Our analysis revealed a scarcity of small-diameter trees, indicating limited natural regeneration over time. However, conservation efforts, like selectively removing competitor species and using protective fencing, have improved growth conditions and promoted seedling emergence. The NP’s natural zone has no active management, which is confined to the development and management zones. Genetic diversity assessments revealed high genetic diversity (He: 0.612 and 0.614 for seedlings and adults, respectively) compared to other studies in Taxus baccata, dispelling concerns of significant inbreeding and showcasing a stable genetic structure. However, significant spatial clustering of related individuals (family structures) in both cohorts and low effective population size in the progeny hints at restricted gene flow, necessitating conservation efforts prioritizing safeguarding and promoting natural regeneration in development and management zones. Limited natural regeneration and the recent decrease in effective population size in the NP populations indicate habitat fragmentation and human interventions. Effective population size estimates emphasize the need for diverse conservation strategies. Conservation efforts should prioritize protecting natural regeneration and enhancing gene flow by actively promoting European yew, e.g., by shelterwood cutting, to ensure the long-term viability of T. baccata in the region outside the NP.

The genetic status and rescue measure for a geographically isolated population of Amur tigers

The Amur tiger is currently confronted with challenges of anthropogenic development, leading to its population becoming fragmented into two geographically isolated groups: smaller and larger ones. Small and isolated populations frequently face a greater extinction risk, yet the small tiger population’s genetic status and survival potential have not been assessed. Here, a total of 210 samples of suspected Amur tiger feces were collected from this small population, and the genetic background and population survival potentials were assessed by using 14 microsatellite loci. Our results demonstrated that the mean number of alleles in all loci was 3.7 and expected heterozygosity was 0.6, indicating a comparatively lower level of population genetic diversity compared to previously reported studies on other subspecies. The genetic estimates of effective population size (Ne) and the Ne/N ratio were merely 7.6 and 0.152, respectively, representing lower values in comparison to the Amur tiger population in Sikhote-Alin (the larger group). However, multiple methods have indicated the possibility of genetic divergence within our isolated population under study. Meanwhile, the maximum kinship recorded was 0.441, and the mean inbreeding coefficient stood at 0.0868, both of which are higher than those observed in other endangered species, such as the African lion and the grey wolf. Additionally, we have identified a significant risk of future extinction if the lethal equivalents were to reach 6.26, which is higher than that of other large carnivores. Further, our simulation results indicated that an increase in the number of breeding females would enhance the prospects of this population. In summary, our findings provide a critical theoretical basis for further bailout strategies concerning Amur tigers.

Patterns of Change in Nucleotide Diversity Over Gene Length.

Nucleotide diversity at a site is influenced by the relative strengths of neutral and selective population genetic processes. Therefore, attempts to estimate Effective population size based on the diversity of synonymous sites demand a better understanding of their selective constraints. The nucleotide diversity of a gene was previously found to correlate with its length. In this work, I measure nucleotide diversity at synonymous sites and uncover a pattern of low diversity towards the translation initiation site of a gene. The degree of reduction in diversity at the translation initiation site and the length of this region of reduced diversity can be quantified as "Effect Size" and "Effect Length" respectively, using parameters of an asymptotic regression model. Estimates of Effect Length across bacteria covaried with recombination rates as well as with a multitude of translation-associated traits such as the avoidance of mRNA secondary structure around translation initiation site, the number of rRNAs, and relative codon usage of ribosomal genes. Evolutionary simulations under purifying selection reproduce the observed patterns and diversity-length correlation and highlight that selective constraints on the 5'-region of a gene may be more extensive than previously believed. These results have implications for the estimation of effective population size, and relative mutation rates, and for genome scans of genes under positive selection based on "silent-site" diversity.

Influence of molecular marker type on estimating effective population size and other genetic parameters in a critically endangered parrot

AbstractGenetics is a fast‐moving field, and for conservation practitioners or ecologists, it can be bewildering. The choice of marker used in studies is fundamental; in the literature, preference has recently shifted from microsatellites to single nucleotide polymorphism (SNP) loci. Understanding how marker type affects estimates of population genetic parameters is important in the context of conservation, especially because the accuracy of estimates has a bearing on the actions taken to protect threatened species. We compare parameter estimates between seven microsatellites, 3761 SNP loci, and a random subset of 100 SNPs for the exact same 324 individual swift parrots, Lathamus discolor, and also use 457 additional samples from subsequent years to compare SNP estimates. Both marker types estimated a lower HO than HE. We show that microsatellites and SNPs mainly indicate a lack of spatial genetic structure, except when a priori collection locations were used on the SNP data in a discriminant analysis of principal components (DAPC). The 100‐SNP subset gave comparable results to when the full dataset was used. Estimates of effective population size (Ne) were comparable between markers when the same individuals were considered, but SNPs had narrower confidence intervals. This is reassuring because conservation assessments that rely on population genetic estimates based on a few microsatellites are unlikely to be nullified by the general shift toward SNPs in the literature. However, estimates between markers and datasets varied considerably when only adult samples were considered; hence, including samples of all age groups is recommended to be used when available. The estimated Ne was higher for the full SNP dataset (2010–2019) than the smaller comparison data (2010–2015), which might be a better reflection of the species status. The lower precision of microsatellites may not necessarily be a barrier for most conservation applications; however, SNPs will improve confidence limits, which may be useful for practitioners.

Effective population size of adult and offspring cohorts as a genetic monitoring tool in two stand-forming and wind-pollinated tree species: Fagus sylvatica L. and Picea abies (L.) Karst.

AbstractGenetic diversity is considered to be a prerequisite for adaptation and adaptability as it is a key element of biological diversity. However, the monitoring of genetic diversity has tended to be ignored in biodiversity monitoring. We report a comprehensive genetic monitoring effort in two dominant forest tree species, which was started with a baseline survey in 12 European beech populations and 10 Norway spruce populations in Germany. The standardized experimental design is based on collecting samples of at least 250 adult trees, and 400 natural regeneration and 400 seed samples and their genotyping with 15–16 high-resolution SSR markers. In addition to commonly used mean values across the markers to quantify genetic diversity, we placed special emphasis on various marker-based, pedigree-based and demographic models for estimating the contemporary effective population size Ne of the different generations. In both beech and spruce, no variation in genetic diversity with mean values across markers was detectable between the studied stands and between age cohorts. We detected that stable allelic diversity in progeny generations is ensured by sufficient gene flow from surrounding forests. However, estimates of effective population size show marked differentiation among populations and among age cohorts. Natural regeneration samples appear to converge on the parent generation, while seed samples show a clear bottleneck effect. The Ne parameter can be used to derive conclusions for sustainable natural regeneration management in forest stands and for seed stand approvals including adequate seed collections for appropriate artificial regenerations.The sibship frequency-based method for Ne estimates is presented as much more robust than the widely used LD estimates, which often fail for samples with too weak relatedness. Despite the distinct kinship structure in our monitoring plots, the contemporary effective population size proves to be an essential parameter for assessing the integrity of the reproductive system.

The weak genetic structure of Melolontha melolontha (L.) and Melolontha hippocastani (Fabr.), two important forest pests, indicates their large population sizes and effective gene flow

Abstract Cockchafers Melolontha spp. are polyphagous root pests and outbreak species of considerable economic importance to forestry in Europe. Knowledge of genetic diversity within and between cockchafer populations is largely unexplored but could lead to more effective monitoring and management strategies of these pests. In this study, we fill several gaps in the knowledge of the genetic population structure of Melolontha melolontha and Melolontha hippocastani. Using microsatellite loci and over 200 individuals per species, we examined the genetic structure of Melolontha spp. populations collected from three primary outbreak areas in central and southeastern Poland. We demonstrated that our focal species share some common genetic patterns, such as considerable genetic diversity within subpopulations (within sampling sites) with minor effects of past bottlenecks possibly masked by current population sizes. The estimates of effective population sizes, although subject to wide credibility intervals, indicated a large number of individuals contributing to further generations of the population. The migration rates exceed the threshold of one per generation required for gene flow and maintenance of population equilibrium, indicating limited impact from forest management practices on either cockchafer species. While genetic differentiation was observed in M. melolontha populations, supported by various indices (fixation index, principal coordinate analysis, assignment tests), the M. hippocastani populations were genetically similar. This disparity may hint at the potential historical divergence between these species. In this aspect, more detailed phylogeographic and population genetic studies covering a large area of the Palaearctic distributions of both species are required. Our findings constitute one of the initial efforts aimed at delineating the genetic diversity, differentiation, population structure, gene flow, and migration patterns within Melolontha spp. This exploration is especially significant for M. hippocastani, given its completely unexplored genetic population structure.

Using recent genetic history to inform conservation options of two Lesser Caymans iguana (Cyclura nubila caymanensis) populations

The Sister Islands rock iguana (Cyclura nubila caymanensis) is critically endangered and endemic to the Caribbean islands Little Cayman and Cayman Brac. The Cayman Brac population and indeed the entire species is under threat from habitat destruction, invasive species, and anthropogenic impacts on the island. We assessed the genetic diversity, estimated effective population sizes, and tested for differentiation of populations between these two islands to inform potential future translocation should this be needed for the Cayman Brac population. Two mitochondrial DNA markers (cytochrome b and NADH subunit 4) and seven DNA microsatellite markers were used to assess the genetic diversity, genetic structure, demographic history, and effective population size of the two iguana populations. Mitochondrial DNA showed no genetic differentiation between populations; however, we found little to moderate divergence with microsatellites. We compared multiple demographic scenarios and revealed that ongoing gene flow is likely. The demographic history implied a significant genetic bottleneck around 10,000 years ago, coinciding with the sea level rise at the close of the last glacial period, and the start of the Holocene. Estimates of current effective population sizes indicate a small-scale number of breeders on each island of similar magnitude to the census mature population size (between 100 and 800 individuals). The relatively low differentiation between populations supports the possible development of active genetic management plans to manage the declining populations of the Sister Islands rock iguana.

Genomic Architecture Predicts Tree Topology, Population Structuring, and Demographic History in Amazonian Birds.

Geographic barriers are frequently invoked to explain genetic structuring across the landscape. However, inferences on the spatial and temporal origins of population variation have been largely limited to evolutionary neutral models, ignoring the potential role of natural selection and intrinsic genomic processes known as genomic architecture in producing heterogeneity in differentiation across the genome. To test how variation in genomic characteristics (e.g. recombination rate) impacts our ability to reconstruct general patterns of differentiation between species that cooccur across geographic barriers, we sequenced the whole genomes of multiple bird populations that are distributed across rivers in southeastern Amazonia. We found that phylogenetic relationships within species and demographic parameters varied across the genome in predictable ways. Genetic diversity was positively associated with recombination rate and negatively associated with species tree support. Gene flow was less pervasive in genomic regions of low recombination, making these windows more likely to retain patterns of population structuring that matched the species tree. We further found that approximately a third of the genome showed evidence of selective sweeps and linked selection, skewing genome-wide estimates of effective population sizes and gene flow between populations toward lower values. In sum, we showed that the effects of intrinsic genomic characteristics and selection can be disentangled from neutral processes to elucidate spatial patterns of population differentiation.

Pseudogenes act as a neutral reference for detecting selection in prokaryotic pangenomes.

A long-standing question is to what degree genetic drift and selection drive the divergence in rare accessory gene content between closely related bacteria. Rare genes, including singletons, make up a large proportion of pangenomes (all genes in a set of genomes), but it remains unclear how many such genes are adaptive, deleterious or neutral to their host genome. Estimates of species' effective population sizes (Ne) are positively associated with pangenome size and fluidity, which has independently been interpreted as evidence for both neutral and adaptive pangenome models. We hypothesized that pseudogenes, used as a neutral reference, could be used to distinguish these models. We find that most functional categories are depleted for rare pseudogenes when a genome encodes only a single intact copy of a gene family. In contrast, transposons are enriched in pseudogenes, suggesting they are mostly neutral or deleterious to the host genome. Thus, even if individual rare accessory genes vary in their effects on host fitness, we can confidently reject a model of entirely neutral or deleterious rare genes. We also define the ratio of singleton intact genes to singleton pseudogenes (si/sp) within a pangenome, compare this measure across 668 prokaryotic species and detect a signal consistent with the adaptive value of many rare accessory genes. Taken together, our work demonstrates that comparing with pseudogenes can improve inferences of the evolutionary forces driving pangenome variation.

Limited impact of vector control on the population genetic structure of Glossina fuscipes fuscipes from the sleeping sickness focus of Maro, Chad.

Tsetse flies (genus Glossina) transmit deadly trypanosomes to human populations and domestic animals in sub-Saharan Africa. Some foci of Human African Trypanosomiasis due to Trypanosoma brucei gambiense (g-HAT) persist in southern Chad, where a program of tsetse control was implemented against the local vector Glossina fuscipes fuscipes in 2018 in Maro. We analyzed the population genetics of G. f. fuscipes from the Maro focus before control (T0), one year (T1), and 18 months (T2) after the beginning of control efforts. Most flies captured displayed a local genetic profile (local survivors), but a few flies displayed outlier genotypes. Moreover, disturbance of isolation by distance signature (increase of genetic distance with geographic distance) and effective population size estimates, absence of any genetic signature of a bottleneck, and an increase of genetic diversity between T0 and T2 strongly suggest gene flows from various origins, and a limited impact of the vector control efforts on this tsetse population. Continuous control and surveillance of g-HAT transmission is thus recommended in Maro. Particular attention will need to be paid to the border with the Central African Republic, a country where the entomological and epidemiological status of g-HAT is unknown.

Genomic evidence for climate-linked diversity loss and increased vulnerability of wild barley spanning 28 years of climate warming

The information on how plant populations respond genetically to climate warming is scarce. Here, landscape genomic and machine learning approaches were integrated to assess genetic response of 10 wild barley (Hordeum vulgare ssp. spontaneum; WB) populations in the past and future, using whole genomic sequencing (WGS) data. The WB populations were sampled in 1980 and again in 2008. Phylogeny of accessions was roughly in conformity with sampling sites, which accompanied by admixture/introgressions. The 28-y climate warming resulted in decreased genetic diversity, increased selection pressure, and an increase in deleterious single nucleotide polymorphism (dSNP) numbers, heterozygous deleterious and total deleterious burdens for WB. Genome-environment associations identified some candidate genes belonging to peroxidase family (HORVU2Hr1G057450, HORVU4Hr1G052060 and HORVU4Hr1G057210) and heat shock protein 70 family (HORVU2Hr1G112630). The gene HORVU2Hr1G120170 identified by selective sweep analysis was under strong selection during the climate warming of the 28-y, and its derived haplotypes were fixed by WB when faced with the 28-y increasingly severe environment. Temperature variables were found to be more important than precipitation variables in influencing genomic variation, with an eco-physiological index gdd5 (growing degree-days at the baseline threshold temperature of 5 °C) being the most important determinant. Gradient forest modelling revealed higher predicted genomic vulnerability in Sede Boqer under future climate scenarios at 2041–2070 and 2071–2100. Additionally, estimates of effective population size (Ne) tracing back to 250 years indicated a forward decline in all populations over time. Our assessment about past genetic response and future vulnerability of WB under climate warming is crucial for informing conservation efforts for wild cereals and rational use strategies.

Unveiling the evolutionary history of lingonberry (Vaccinium vitis-idaea L.) through genome sequencing and assembly of European and North American subspecies.

Lingonberry (Vaccinium vitis-idaea L.) produces tiny red berries that are tart and nutty in flavor. It grows widely in the circumpolar region, including Scandinavia, northern parts of Eurasia, Alaska, and Canada. Although cultivation is currently limited, the plant has a long history of cultural use among indigenous communities. Given its potential as a food source, genomic resources for lingonberry are significantly lacking. To advance genomic knowledge, the genomes for 2 subspecies of lingonberry (V. vitis-idaea ssp. minus and ssp. vitis-idaea var. 'Red Candy') were sequenced and de novo assembled into contig-level assemblies. The assemblies were scaffolded using the bilberry genome (Vaccinium myrtillus) to generate a chromosome-anchored reference genome consisting of 12 chromosomes each with a total length of 548.07 Mb [contig N50 = 1.17 Mb, BUSCO (C%) = 96.5%] for ssp. vitis-idaea and 518.70 Mb [contig N50 = 1.40 Mb, BUSCO (C%) = 96.9%] for ssp. minus. RNA-seq-based gene annotation identified 27,243 and 25,718 genes on the respective assembly, and transposable element detection methods found that 45.82 and 44.58% of the genome were repeats. Phylogenetic analysis confirmed that lingonberry was most closely related to bilberry and was more closely related to blueberries than cranberries. Estimates of past effective population size suggested a continuous decline over the past 1-3 MYA, possibly due to the impacts of repeated glacial cycles during the Pleistocene leading to frequent population fragmentation. The genomic resource created in this study can be used to identify industry-relevant genes (e.g. anthocyanin production), infer phylogeny, and call sequence-level variants (e.g. SNPs) in future research.

Genomic variation in montane bumblebees in Scandinavia: High levels of intraspecific diversity despite population vulnerability.

Populations of many bumblebee species are declining, with distributions shifting northwards to track suitable climates. Climate change is considered a major contributing factor. Arctic species are particularly vulnerable as they cannot shift further north, making assessment of their population viability important. Analysis of levels of whole-genome variation is a powerful way to analyse population declines and fragmentation. Here, we use genome sequencing to analyse genetic variation in seven species of bumblebee from the Scandinavian mountains, including two classified as vulnerable. We sequenced 333 samples from across the ranges of these species in Sweden. Estimates of effective population size (NE ) vary from ~55,000 for species with restricted high alpine distributions to 220,000 for more widespread species. Population fragmentation is generally very low or undetectable over large distances in the mountains, suggesting an absence of barriers to gene flow. The relatively high NE and low population structure indicate that none of the species are at immediate risk of negative genetic effects caused by high levels of genetic drift. However, reconstruction of historical fluctuations in NE indicates that the arctic specialist species Bombus hyperboreus has experienced population declines since the last ice age and we detected one highly inbred diploid male of this species close to the southern limit of its range, potentially indicating elevated genetic load. Although the levels of genetic variation in montane bumblebee populations are currently relatively high, their ranges are predicted to shrink drastically due to the effects of climate change and monitoring is essential to detect future population declines.

Demographic history shapes North American gray wolf genomic diversity and informs species' conservation.

Effective population size estimates are critical information needed for evolutionary predictions and conservation decisions. This is particularly true for species with social factors that restrict access to breeding or experience repeated fluctuations in population size across generations. We investigated the genomic estimates of effective population size along with diversity, subdivision, and inbreeding from 162,109 minimally filtered and 81,595 statistically neutral and unlinked SNPs genotyped in 437 grey wolf samples from North America collected between 1986 and 2021. We found genetic structure across North America, represented by three distinct demographic histories of western, central, and eastern regions of the continent. Further, grey wolves in the northern Rocky Mountains have lower genomic diversity than wolves of the western Great Lakes and have declined over time. Effective population size estimates revealed the historical signatures of continental efforts of predator extermination, despite a quarter century of recovery efforts. We are the first to provide molecular estimates of effective population size across distinct grey wolf populations in North America, which ranged between Ne ~ 275 and 3050 since early 1980s. We provide data that inform managers regarding the status and importance of effective population size estimates for grey wolf conservation, which are on average 5.2-9.3% of census estimates for this species. We show that while grey wolves fall above minimum effective population sizes needed to avoid extinction due to inbreeding depression in the short term, they are below sizes predicted to be necessary to avoid long-term risk of extinction.

Impact of population structure in the estimation of recent historical effective population size by the software GONE

BackgroundEffective population size (Ne) is a crucial parameter in conservation genetics and animal breeding. A recent method, implemented by the software GONE, has been shown to be rather accurate in estimating recent historical changes in Ne from a single sample of individuals. However, GONE estimations assume that the population being studied has remained isolated for a period of time, that is, without migration or confluence of other populations. If this occurs, the estimates of Ne can be heavily biased. In this paper, we evaluate the impact of migration and admixture on the estimates of historical Ne provided by GONE through a series of computer simulations considering several scenarios: (a) the mixture of two or more ancestral populations; (b) subpopulations that continuously exchange individuals through migration; (c) populations receiving migrants from a large source; and (d) populations with balanced systems of chromosomal inversions, which also generate genetic structure.ResultsOur results indicate that the estimates of historical Ne provided by GONE may be substantially biased when there has been a recent mixture of populations that were previously separated for a long period of time. Similarly, biases may occur when the rate of continued migration between populations is low, or when chromosomal inversions are present at high frequencies. However, some biases due to population structuring can be eliminated by conducting population structure analyses and restricting the estimation to the differentiated groups. In addition, disregarding the genomic regions that are involved in inversions can also remove biases in the estimates of Ne.ConclusionsDifferent kinds of deviations from isolation and panmixia of the populations can generate biases in the recent historical estimates of Ne. Therefore, estimation of past demography could benefit from performing population structure analyses beforehand, by mitigating the impact of these biases on historical Ne estimates.