In 2024, Millennials were the largest generation group in the United States, making up about 21.81 percent of the population. However, Generation Z was not far behind, with Gen Z accounting for around 20.81 percent of the population in that year.

Millennials were the largest generation group in the United States in 2024, with an estimated population of ***** million. Born between 1981 and 1996, Millennials recently surpassed Baby Boomers as the biggest group, and they will continue to be a major part of the population for many years. The rise of Generation Alpha Generation Alpha is the most recent to have been named, and many group members will not be able to remember a time before smartphones and social media. As of 2024, the oldest Generation Alpha members were still only aging into adolescents. However, the group already makes up around ***** percent of the U.S. population, and they are said to be the most racially and ethnically diverse of all the generation groups. Boomers vs. Millennials The number of Baby Boomers, whose generation was defined by the boom in births following the Second World War, has fallen by around ***** million since 2010. However, they remain the second-largest generation group, and aging Boomers are contributing to steady increases in the median age of the population. Meanwhile, the Millennial generation continues to grow, and one reason for this is the increasing number of young immigrants arriving in the United States.

In 2023, there were about 72.7 million Millennials estimated to be living in the United States, making them the largest generation group in the country. In comparison, there were 69.31 million Gen Z and 65.35 million Gen X estimated to be in the United States in that year.

The statistic shows the number of people in the U.S. in 2011 and 2030, by generation. By 2030, the Millennial generation will have 78 million people whereas the Boomer generation will only have 56 million people in the United States.

In 2023, there were approximately 14.69 million millennials in the United Kingdom, making it the largest generational cohort at that time. Millennials surpassed the Baby Boomer generation as the largest generation for the first time in 2019. The two youngest generations, Gen Z and Gen Alpha, numbered approximately 13.2 million, and 8.3 million respectively. Gen X are, as of the most recent year, the second-largest generation in the UK at 14.04 million people, with their parent's generation, the Silent Generation, numbering around 4.3 million people in the same year. There were estimated to be 85,920 people who belonged to the Greatest Generation, the parents of the Baby Boomer generation, who lived through major events such as the Great Depression and World War Two. Post-War Baby Boom The baby boomer generation was the largest generation for much of this period due to the spike in births that happened after the Second World War. In 1947 for example, there were over one million live births in the United Kingdom, compared with just 657,038 live births just thirty years later in 1977. Members of this generation are typically the parents of millennials, and were the driving force behind the countercultural movement of the 1960s, due to their large numbers relative to older generations at the time. The next generational cohort after Boomers are Generation X, born between 1965 and 1980. This generation had fewer members than the Boomer generation for most of its existence, and only became larger than it in 2021. Millennials and Gen Z As of 2022, the most common single year of age in the United Kingdom in 2020 was 34, with approximately 944,491 people this age. Furthermore, people aged between 30 and 34 were the most numerous age group in this year, at approximately 4.67 million people. As of 2022, people in this age group were Millennials, the large generation who came of age in the late 1990s and early 2000s. Many members of this generation entered the workforce following the 2008 financial crash, and suffered through high levels of unemployment during the early 2010s. The generation that followed Millennials, Generation Z, have also experienced tough socio-economic conditions recently, with key formative years dominated by the COVID-19 pandemic, climate change, and an increasingly unstable geopolitical situation.

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If not actively managed, small and isolated populations lose their genetic variability and the inbreeding rate increases. Combined, these factors limit the ability of populations to adapt to environmental changes, increasing their risk of extinction. The effective population size (Ne) is proportional to the loss of genetic diversity and therefore of considerable conservation relevance. However, estimators of Ne that account for demographic parameters in species with overlapping generations require sampling of populations across generations, which is often not feasible in long-lived species. We created an individual-based model that allows calculation of Ne based on demographic parameters that can be obtained in a time period much shorter than a generation. It can be adapted to every life-history parameter combination. The model is freely available as an r-package NEff. The model was first used in a simulation experiment observing changes in Ne in response to different degrees of generational overlap. Results showed that increased generational overlap slowed annual rates of heterozygosity loss, resulting in higher annual effective sizes (Ny) but decreased Ne per generation. Adding the effect of different recruitment rates only affected Ne for populations with low generational overlap. The model was further tested using real population data of the Australian arboreal gecko Gehyra variegata. Simulation results were compared to genetic analyses and matched estimates of the real population very well. Unlike other estimation methods of Ne, NEff neither requires long time series of population monitoring nor genetic analyses of changes in gene frequencies. Thus, it seems to be the first method for calculating Ne within short time periods and comparably low costs facilitating the use of Ne in applied conservation and management.

As of 2021, Millennials and Baby Boomers made up an equal share of the Australian population at around 21.5 percent each, making them the largest generational groups at the time. Those aged 75 years and over made up the smallest portion of the population, followed by Gen Alpha, or those aged 0 to 9 years at the time.

The Lundehund is an old dog breed with remarkable anatomical features including polydactyly in all four limbs and extraordinary flexibility of the spine. We genotyped 28 Lundehund using the canine Illumina high density beadchip to estimate the effective population size (Ne) and inbreeding coefficients as well as to identify potential regions of positive selection. The decay of linkage disequilibrium was slow with r2 = 0.95 in 50 kb distance. The last 7-200 generations ago, Ne was at 10-13. An increase of Ne was noted in the very recent generations with a peak value of 19 for Ne at generation 4. The FROH estimated for 50-, 65- and 358-SNP windows were 0.87, 087 and 0.81, respectively. The most likely estimates for FROH after removing identical-by-state segments due to linkage disequilibria were at 0.80-0.81. The extreme loss of heterozygosity has been accumulated through continued inbreeding over 200 generations within a probably closed population with a small effective population size. The mean inbreeding coefficient based on pedigree data for the last 11 generations (FPed = 0.10) was strongly biased downwards due to the unknown coancestry of the founders in this pedigree data. The long-range haplotype test identified regions with genes involved in processes of immunity, olfaction, woundhealing and neuronal development as potential targets of selection. The genes QSOX2, BMPR1B and PRRX2 as well as MYOM1 are candidates for selection on the Lundehund characteristics small body size, increased number of digits per paw and extraordinary mobility, respectively.

Optimized setting of population size, differential weight & crossover at various maximum generation number.

Ne500_IdealRawPopulationFilesThese are the "true" population files for ideal (isolation) populations of size 500 simulated from Nemo. They contain all individuals and many extra loci, from which these were sampled to obtain the inputs used in analyses (see Program_InputFiles). Temporal samplers used two time points, from which the files here are identified as belonging to generation 0 or generation 1.Ideal500_Raw.zipNe5000_IdealRawPopulationFilesThese are the "true" population files for ideal (isolation) populations of size 5000 simulated from Nemo. They contain all individuals and many extra loci, from which these were sampled to obtain the inputs used in analyses (see Program_InputFiles). Temporal samplers used two time points, from which the files here are identified as belonging to generation 0 or generation 1.Ideal5000_Raw.zipNe50_Generation0_IdealRawPopulationFilesThese are the "true" population files for ideal (isolation) populations of size 50 simulated from Nemo. They contain a...

1.A population's effective size (Ne) is a key parameter that shapes rates of inbreeding and loss of genetic diversity, thereby influencing evolutionary processes and population viability. However estimating Ne, and identifying key demographic mechanisms that underlie the Ne to census population size (N) ratio, remains challenging, especially for small populations with overlapping generations and substantial environmental and demographic stochasticity and hence dynamic age-structure.

2.A sophisticated demographic method of estimating Ne/N, which uses Fisher's reproductive value to account for dynamic age-structure, has been formulated. However this method requires detailed individual- and population-level data on sex- and age-specific reproduction and survival, and has rarely been implemented.

3.Here we use the reproductive value method and detailed demographic data to estimate Ne/N for a small and apparently isolated red-billed chough (Pyrrhocorax pyrrhocorax) population of high conservation concern. We additionally calculated two single-sample molecular genetic estimates of Ne to corroborate the demographic estimate and examine evidence for unobserved immigration and gene flow.

4.The demographic estimate of Ne/N was 0.21, reflecting a high total demographic variance (σ2dg) of 0.71. Females and males made similar overall contributions to σ2dg. However, contributions varied among sex-age classes, with greater contributions from 3 year-old females than males, but greater contributions from ≥5 year-old males than females.

5.The demographic estimate of Ne was ~30, suggesting that rates of increase of inbreeding and loss of genetic variation per generation will be relatively high. Molecular genetic estimates of Ne computed from linkage disequilibrium and approximate Bayesian computation were approximately 50 and 30 respectively, providing no evidence of substantial unobserved immigration which could bias demographic estimates of Ne.

1. Our analyses identify key sex-age classes contributing to demographic variance and thus decreasing Ne/N in a small age-structured population inhabiting a variable environment. They thereby demonstrate how assessments of Ne can incorporate stochastic sex- and age-specific demography and elucidate key demographic processes affecting a population's evolutionary trajectory and viability. Furthermore, our analyses show that Ne for the focal chough population is critically small, implying that management to re-establish genetic connectivity may be required to ensure population viability.

The rate and fitness effects of new mutations have been investigated by mutation accumulation (MA) experiments in which organisms are maintained at a constant minimal population size to facilitate the accumulation of mutations with minimal efficacy of selection. We evolved 35 MA lines of Caenorhabditis elegans in parallel for 409 generations at three population sizes (N = 1, 10, and 100), representing the first spontaneous long-term MA experiment at varying population sizes with corresponding differences in the efficacy of selection. Productivity and survivorship in the N = 1 lines declined by 44% and 12%, respectively. The average effects of deleterious mutations in N = 1 lines are estimated to be 16.4% for productivity and 11.8% for survivorship. Larger populations (N = 10 and 100) did not suffer a significant decline in fitness traits despite a lengthy and sustained regime of consecutive bottlenecks exceeding 400 generations. Together, these results suggest that fitness decline in very small populations is dominated by mutations with large deleterious effects. It is possible that the MA lines at larger population sizes contain a load of cryptic deleterious mutations of small to moderate effects that would be revealed in more challenging environments.

Many life-history traits are important determinants of the generation time. For instance, semelparous species whose adults reproduce only once have shorter generation times than iteroparous species that reproduce on several occasions – assuming equal development duration. A shorter generation time ensures a higher growth rate in stable environments where resources are in excess, and is therefore a positively selected feature in this situation. In a stable and limiting environment, all combinations of traits that produce the same number of viable offspring are selectively equivalent. Here we study the neutral evolution of life-history strategies with different generation times, and show that the slowest strategy represents the most likely evolutionary out- come when mutation is considered. Indeed, strategies with longer generation times generate fewer mutants per time unit, which makes them less likely to be replaced within a given time period. This ‘turnover bias’ favors the evolution of strategies with long generation times. Its real impact, however, depends on both the population size and the nature of selection on life-history strategies. The latter is primarily impacted by the relationships between life- history traits whose estimation will be crucial to understand the evolution of life-history strategies.

In 2023, Millennials were the largest generational cohort in the United Kingdom, comprising approximately 21.5 percent of the population. Gen X was the next largest generation at 20.6 percent of the population, followed by Baby Boomers at 19.9 percent, and Gen Z on 19.4 percent.

Estimated power of the test under the second scenario (under , replace half of a -complete ancestor’s chromosomes for -chromosomes) for the four variants of the hypothesis test.

🇩🇪 독일 English Households total and by household size Household structure of the resident population by total number of households and by household size (by number of persons in the household). The data are presented for the city of Konstanz and for the 15 districts from 2010. The household structure of the resident population is not recorded directly in the population register. Therefore, the household generation programme HHGen is used to determine households in a multi-stage generation process. To this end, the programme identifies relationships between residents registered in Constance on the basis of family and birth names, the same residential address, the date of registration and other demographic characteristics such as age, gender, marital status and nationality. It is not always possible to capture all budgetary relations correctly. For this reason, the number of 1-person households tends to be overestimated and the number of 2-person households underestimated. The reason for this distortion is that, in particular, non-marital cohabitation or residential cohabitation cannot always be recognised as such. Source: City of Constance

Body size, and, by extension, growth has impacts on physiology, survival, attainment of sexual maturity, fecundity, generation time, and population dynamics, especially in ectotherm animals that often exhibit extensive growth following attainment of sexual maturity. Frequently, growth is analyzed at the population level, providing useful population mean growth parameters but ignoring individual variation that is also of ecological and evolutionary significance. Our long-term study of Lake Erie Watersnakes, Nerodia sipedon insularum, provides data sufficient for a detailed analysis of population and individual growth. We describe population mean growth separately for males and females based on size of known age individuals (847 captures of 769 males, 748 captures of 684 females) and annual growth increments of individuals of unknown age (1,152 males, 730 females). We characterize individual variation in asymptotic size based on repeated measurements of 69 males and 71 females that were each captured in five to nine different years. The most striking result of our analyses is that asymptotic size varies dramatically among individuals, ranging from 631–820 mm snout-vent length in males and from 835–1125 mm in females. Because female fecundity increases with increasing body size, we explore the impact of individual variation in asymptotic size on lifetime reproductive success using a range of realistic estimates of annual survival. When all females commence reproduction at the same age, lifetime reproductive success is greatest for females with greater asymptotic size regardless of annual survival. But when reproduction is delayed in females with greater asymptotic size, lifetime reproductive success is greatest for females with lower asymptotic size when annual survival is low. Possible causes of individual variation in asymptotic size, including individual- and cohort-specific variation in size at birth and early growth, warrant further investigation.

simulated data on density dependent populations and genetic drift and accompanying codesIncludes "raw" datafiles based on simulations used to estimate effective population size of monoecious populations in average environment and in fluctuating environments. Also includes datafiles based on simulations used to estimate LRS and generation time with respect to the population size at birth N0 (used in Table 2 in article). The codes used to generate the simulated data are also attached.Data.zip

Please find the pseudo dataset (in "data.tgz") of the evolution of Identity-by-descent in a Wright-Fisher population model, with drift as the only evolutionary pressure, with a constant population size, and panmictic without selfing. The individuals are diploids and the initial population are unrelated and non inbred, meaning that chromosome in the initial population are pairwisely different. In "data.tgz", one could find stored all the IBD blocks at specific generations (1,000,000 replicates, over 500 generations, population size of 20 diploid individuals). For each file, the first column is the number of the replicate, the second the number of the individual in the replicate and the third the length of the IBD block. Each line is an IBD block. This dataset was generated with the joint program "ibd-static", with the command line "./ibd -i 20 -r 1000000 -g $g -sa", where $g is the number of generations ranging from 1 to 500. The output file could be summarised in several mean values, what is done by "mfile.R", and the resulting file is "xmean".