this graph was created in R:

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driven primarily by high birth rates in developing countries and advancements in healthcare. According to the United Nations, the global population surpassed 8 billion in 2023, marking a critical milestone in human history. This growth, however, is unevenly distributed across continents and countries, leading to varied population densities and urban pressures.

Surface area and population density play vital roles in shaping the demographic and economic landscape of each country. For instance, countries with large land masses such as Russia, Canada, and Australia have low population densities despite their significant populations, as vast portions of their land are sparsely populated or uninhabitable. Conversely, nations like Bangladesh and South Korea exhibit extremely high population densities due to smaller land areas combined with large populations.

Population density, measured as the number of people per square kilometer, affects resource availability, environmental sustainability, and quality of life. High-density areas face greater challenges in housing, infrastructure, and environmental management, often experiencing increased pollution and resource strain. In contrast, low-density areas may struggle with underdeveloped infrastructure and limited access to services due to the dispersed population.

Urbanization trends are another important aspect of these dynamics. As people migrate to cities seeking better economic opportunities, urban areas grow more densely populated, amplifying the need for efficient land use and sustainable urban planning. The UN reports that over half of the world’s population currently resides in urban areas, with this figure expected to rise to nearly 70% by 2050. This shift requires nations to balance population growth and density with sustainable development strategies to ensure a higher quality of life and environmental stewardship for future generations.

Through an understanding of population size, surface area, and density, policymakers can better address challenges related to urban development, rural depopulation, and resource allocation, supporting a balanced approach to population management and economic development.

Context

This is a dataset of the most highly populated city (if applicable) in a form easy to join with the COVID19 Global Forecasting (Week 1) dataset. You can see how to use it in this kernel

Content

There are four columns. The first two correspond to the columns from the original COVID19 Global Forecasting (Week 1) dataset. The other two is the highest population density, at city level, for the given country/state. Note that some countries are very small and in those cases the population density reflects the entire country. Since the original dataset has a few cruise ships as well, I've added them there.

Acknowledgements

Thanks a lot to Kaggle for this competition that gave me the opportunity to look closely at some data and understand this problem better.

Inspiration

Summary: I believe that the square root of the population density should relate to the logistic growth factor of the SIR model. I think the SEIR model isn't applicable due to any intervention being too late for a fast-spreading virus like this, especially in places with dense populations.

After playing with the data provided in COVID19 Global Forecasting (Week 1) (and everything else online or media) a bit, one thing becomes clear. They have nothing to do with epidemiology. They reflect sociopolitical characteristics of a country/state and, more specifically, the reactivity and attitude towards testing.

The testing method used (PCR tests) means that what we measure could potentially be a proxy for the number of people infected during the last 3 weeks, i.e the growth (with lag). It's not how many people have been infected and recovered. Antibody or serology tests would measure that, and by using them, we could go back to normality faster... but those will arrive too late. Way earlier, China will have experimentally shown that it's safe to go back to normal as soon as your number of newly infected per day is close to zero.

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My view, as a person living in NYC, about this virus, is that by the time governments react to media pressure, to lockdown or even test, it's too late. In dense areas, everyone susceptible has already amble opportunities to be infected. Especially for a virus with 5-14 days lag between infections and symptoms, a period during which hosts spread it all over on subway, the conditions are hopeless. Active populations have already been exposed, mostly asymptomatic and recovered. Sensitive/older populations are more self-isolated/careful in affluent societies (maybe this isn't the case in North Italy). As the virus finishes exploring the active population, it starts penetrating the more isolated ones. At this point in time, the first fatalities happen. Then testing starts. Then the media and the lockdown. Lockdown seems overly effective because it coincides with the tail of the disease spread. It helps slow down the virus exploring the long-tail of sensitive population, and we should all contribute by doing it, but it doesn't cause the end of the disease. If it did, then as soon as people were back in the streets (see China), there would be repeated outbreaks.

Smart politicians will test a lot because it will make their condition look worse. It helps them demand more resources. At the same time, they will have a low rate of fatalities due to large denominator. They can take credit for managing well a disproportionally major crisis - in contrast to people who didn't test.

We were lucky this time. We, Westerners, have woken up to the potential of a pandemic. I'm sure we will give further resources for prevention. Additionally, we will be more open-minded, helping politicians to have more direct responses. We will also require them to be more responsible in their messages and reactions.

The relationship between population size, inbreeding, loss of genetic variation and evolutionary potential of fitness traits is still unresolved, and large-scale empirical studies testing theoretical expectations are surprisingly scarce. Here we present a highly replicated experimental evolution setup with 120 lines of Drosophila melanogaster having experienced inbreeding caused by low population size for a variable number of generations. Genetic variation in inbred lines and in outbred control lines was assessed by genotyping-by-sequencing (GBS) of pooled samples consisting of 15 males per line. All lines were reared on a novel stressful medium for 10 generations during which body mass, productivity, and extinctions were scored in each generation. In addition, we investigated egg-to-adult viability in the benign and the stressful environments before and after rearing at the stressful conditions for 10 generations. We found strong positive correlations between levels of genetic variation and evolutionary response in all investigated traits, and showed that genomic variation was more informative in predicting evolutionary responses than population history reflected by expected inbreeding levels. We also found that lines with lower genetic diversity were at greater risk of extinction. For viability, the results suggested a trade-off in the costs of adapting to the stressful environments when tested in a benign environment. This work presents convincing support for long-standing evolutionary theory, and it provides novel insights into the association between genetic variation and evolutionary capacity in a gradient of diversity rather than dichotomous inbred/outbred groups.

1. Interactions between hosts and pathogens are dynamic at both ecological and evolutionary levels. In the resultant "eco-evolutionary dynamics" ecological and evolutionary processes affect each other. For example, the house finch (Haemorhous mexicanus) and its recently-emerged pathogen, the bacterium Mycoplasma gallisepticum, form a system in which evidence suggests that changes in bacterial virulence through time enhance levels of host immunity in ways that drive the evolution of virulence in an arms race.

2. We use data from two associated citizen science projects in order to determine whether this arms race has had any detectable effect at the population level in the northeastern United States.

3. We used data from two citizen science projects, based on observations of birds at bird feeders, which provide information on the long-term changes in sizes of aggregations of house finches (host population density), and the probabilities that these house finches have observable disease (disease prevalence).

4. The initial emergence of M. gallisepticum caused a rapid halving of house finch densities; this was then followed by house finch populations remaining stable or slowly declining. Disease prevalence also decreased sharply after the initial emergence and has remained low, although with fluctuations through time. Surprisingly, while initially higher local disease prevalence was found at sites with higher local densities of finches, this relationship has reversed over time.

5. The ability of a vertebrate host species, with a generation time of at least one year, to maintain stable populations in the face of evolved higher virulence of a bacterium, with generation times measurable in minutes, suggests that genetic changes in the host are insufficient to explain the observed population-level patterns. We suggest that acquired immunity plays an important role in the observed interaction between house finches and M. gallisepticum.

The asymptotic giant branch (AGB) phase is the final stage of nuclear burning for low-mass stars. Although Milky Way globular clusters are now known to harbour (at least) two generations of stars, they still provide relatively homogeneous samples of stars that are used to constrain stellar evolution theory. It is predicted by stellar models that the majority of cluster stars with masses around the current turn-off mass (that is, the mass of the stars that are currently leaving the main sequence phase) will evolve through the AGB phase. Here we report that all of the second-generation stars in the globular cluster NGC 6752 - 70 per cent of the cluster population - fail to reach the AGB phase. Through spectroscopic abundance measurements, we found that every AGB star in our sample has a low sodium abundance, indicating that they are exclusively first-generation stars. This implies that many clusters cannot reliably be used for star counts to test stellar evolution timescales if the AGB population is included. We have no clear explanation for this observation.

Genetic data are useful for detecting sudden population declines in species that are difficult to study in the field. Yet this indirect approach has its own drawbacks, including population structure, mutation patterns, and generation overlap. The ivory gull (Pagophila eburnea), a long-lived Arctic seabird, is currently suffering from rapid alteration of its primary habitat (i.e., sea ice), and dramatic climatic events affecting reproduction and recruitment. However, ivory gulls live in remote areas, and it is difficult to assess the population trend of the species across its distribution. Here we present complementary microsatellite- and SNP-based genetic analyses to test a recent bottleneck genetic signal in ivory gulls over a large portion of their distribution. With attention to the potential effects of population structure, mutation patterns, and sample size, we found no significant signatures of population decline worldwide. At a finer scale, we found a significant bottleneck signal at one location in Canada. These results were compared with predictions from simulations showing how generation time and generation overlap can delay and reduce the bottleneck microsatellite heterozygosity excess signal. The consistency of the results obtained with independent methods strongly indicates that the species shows no genetic evidence of an overall decline in population size. However, drawing conclusions related to the species' population trends will require a better understanding of the effect of age structure in long-lived species. In addition, estimates of the effective global population size of ivory gulls were surprisingly low (approximately 1000 ind.), suggesting that the evolutionary potential of the species is not assured.

A README file is provided as well as a description of the dataset directly within the datafile.

1Country of origin is country of birth, except for second generation migrants where it is the country of birth of the parents.2Education: Low = no higher than ‘12th grade without diploma’, Middle = from ‘high school diploma or equivalent’ to ‘college but no degree’, High = from ‘associate degree’ to ‘doctorate degree’.32nd Generation: those born in the US whose parents are both foreign-born.*Other Africa: Ghana, Kenya and South Africa.

Data contains a Readme file and the datasets used to address the three aims in the paper. Included is:- Data used to quantify activity and boldness in founders and the F1 generation of house mice.-Testing for a behavioural syndrome between activity and boldness.-Testing for a personality bias among treatments within the Founder and F1 generation following a field-trial.- GUD trials for founder mice only. Also included are two video files showing the differences in behaviours used to quantify personality traits between a High Activity and a Low Activity mouse.

Simulated Ancient Genomic Kinship Dataset: VCF and BAM (1x and 5x) Files for Related (including inbred) Pairs

Description:

This dataset comprises simulated pedigrees (VCF files containing 8,677,101 autosomal biallelic and 298,625 X chromosomal SNP positions) generated using Ped-sim (v1.3) and comprising pairs of diverse familial relationship types up to third-degree. The first-degree relationships are parent-offspring and siblings; the second-degree relationships are half-siblings, grandparent-grandchild, and avuncular pairs; and third-degree relationships are first cousins, great-grandparent-great-grandchild, and grand avuncular pairs. For each of these 8 relationship types, our dataset includes 48 pairs of individuals. It also contains unrelated pairs. Additionally, the dataset includes first- and second-degree relatives, with inbreeding (parent-offspring pairs where the parents of the offspring are the first cousins and grandparent-grandchild pairs where the grandchild is the offspring of first cousins). Our simulations encompass all combinations of kinship types regarding sex. The dataset was further enriched by simulating ancient DNA-like sequencing data (5x and 1x BAM files) of Ped-sim simulated individuals using the gargammel tool, employing procedures akin to standard paleogenomic sequencing libraries. Note that the BAM files contain only randomly chosen 200K autosomal SNP positions. Positions can be found in the "200K_positions" file. Details can be found in Aktürk, Mapelli and Güler et al. 2023.

Data Sources and Generation:

Founder genotypes for pedigree simulation were created from the Tuscany (TSI) population SNPs within the 1000 Genomes Dataset v3. Notably, the founder genotypes lack background relatedness or runs of homozygosity (ROH).

Description of File Naming Conventions:

The naming conventions of the BAM files in this dataset are designed to convey key information regarding the specifics of each file.

cov1x or cov5x: This segment denotes the coverage level of the BAM files, indicating whether the sequencing coverage for the individuals in the files is 1x or 5x.

run_*: Signifies the particular batch from which the pedigree and individuals are derived. This name segment also applies to VCF files.

parent-offspring_* or similar identifiers: Reflects the origin of the individual from the corresponding VCF file. For instance, "parent-offspring_1" corresponds to the individuals present in the "run_*_parent-offspring_1.vcf" file.

parent-offspring* or similar identifiers:

Indicates the origin of the individual from the sets within the VCF files. For example, "parent-offspring1" signifies the first set of parent-offspring pedigrees within the VCF file. Note that parent-offspring, grandparent-grandchild, and great-grandparent-great-grandchild and the inbreeding VCFs contain only one set, so this identifier is always 1. This convention can be 1 or 2 for the rest of the pedigrees, as the VCF files contain two sets of related pairs.

_g*-b*-: Provides information about the individual's generational level within the VCF. This follows the Ped-sim syntax. For example, for parent-offspring type, "_g1-b1-" indicates the first parent (generation 1) within a specific pedigree, and "_g1-b2-" indicates the second parent (generation 1) while "_g2-b1-" represents the offspring (generation 2).

Example Naming Structure:

For instance, the file "cov1x_run1_parent-offspring_1_parent-offspring1_g1-b1-i1.all.hs37d5.cons.90perc.trimBAM.bam" signifies a BAM file with 1x coverage, originating from "run1," containing individuals from the "run_*_parent-offspring_1.vcf" file (first set of parent-offspring pairs) where "_g1-b1-" designates the first parent in the first generation. The latter half of the name "hs37d5.cons.90perc.trimBAM.bam" is the same across all files.

Note1: Segments such as parent-offspring*_g*-b*- can also be tracked in the naming of the genotype columns in the VCF.

Note2: Sexual information within the VCF files is discernible from the genetic data present at X chromosome positions. Individuals carrying two genotypes on the X chromosome are female, while those with a single genotype are male.

Note3: Some of the individuals from distinct pedigrees may, in fact, be related due to shared ancestry through common founders. To suit specific research objectives, researchers may need to identify and exclude such relatives if the full dataset is used for kinship estimation.

For more details about the dataset's generation process, unique characteristics, or any specific inquiries, our team is available for further information. We welcome and encourage inquiries, aiming to provide comprehensive support and additional details that might aid researchers in utilizing this dataset effectively. Please don't hesitate to contact us for any specific information you may need.

This repository contains only VCFs and cov1x BAM and 200K_positions files. The rest of the files can be found at 10.5281/zenodo.10079625 and 10.5281/zenodo.10079685.

Data on visible minority by individual low-income status, generation status, age and gender for the population in private households in Canada, provinces and territories, census metropolitan areas, census agglomerations and parts.

The presence of multiple populations in globular clusters has been well established thanks to high-resolution spectroscopy. It is widely accepted that distinct populations are a consequence of different stellar generations: intra-cluster pollution episodes are required to produce the peculiar chemistry observed in almost all clusters. Unfortunately, the progenitors responsible have left an ambiguous signature and their nature remains unresolved. To constrain the candidate polluters, we have measured lithium and aluminium abundances in more than 180 giants across three systems: NGC 1904, NGC 2808, and NGC 362. The present investigation along with our previous analysis of M12 and M5 affords us the largest database of simultaneous determinations of Li and Al abundances. Our results indicate that Li production has occurred in each of the three clusters. In NGC 362 we detected an M12-like behaviour, with first and second-generation stars sharing very similar Li abundances favouring a progenitor that is able to produce Li, such as AGB stars. Multiple progenitor types are possible in NGC 1904 and NGC 2808, as they possess both an intermediate population comparable in lithium to the first generation stars and also an extreme population, that is enriched in Al but depleted in Li. A simple dilution model fails in reproducing this complex pattern. Finally, the internal Li variation seems to suggest that the production efficiency of this element is a function of the cluster's mass and metallicity - low-mass or relatively metal-rich clusters are more adept at producing Li. Cone search capability for table J/MNRAS/449/4038/table1 (Photometry, stellar parameters, kinematics, and chemical information for our stars)

Heterozygosity GLMM dataUsing this data set we fitted a binomial, non-linear, mixed-effects model (GLMM) with a logistic link function to assess the effects of genic and intergenic regions, chromosome length and distance from the centromere on the probability that a window would contain one or more heterozygous SNP. Note: Raw sequence data has been uploaded to NCBI. The pipeline for all of the analyses in this paper can be found at: https://github.com/Social-Insect-Genomics/JEB.heterozygosity.fitness.pipeline).het.glmm.covariate.jeb.csv

The modern generation of Cherenkov telescopes has revealed a new population of gamma-ray sources in the Galaxy. Some of them have been identified with previously known X-ray binary systems while other remain without clear counterparts a lower energies. Our initial goal here was reporting on extensive radio observations of the first extended and yet unidentified source, namely TeV J2032+4130. This object was originally detected by the HEGRA telescope in the direction of the Cygnus OB2 region and its nature has been a matter of debate during the latest years. The situation has become more complex with the Whipple and MILAGRO telescopes new TeV detections in the same field which could be consistent with the historic HEGRA source, although a different origin cannot be ruled out. We aim to pursue our radio exploration of the TeV J2032+4130 position that we initiated in a previous paper but taking now into account the latest results from new Whipple and MILAGRO TeV telescopes. The data presented here are an extended follow up of our previous work. Cone search capability for table J/A+A/472/557/table3 (Catalogue of GMRT sources detected at 610MHz)

Isolation of small populations is expected to reduce fitness through inbreeding and loss of genetic variation, impeding population growth and compromising population persistence. Species with long generation time are the least likely to be rescued by evolution alone. Management interventions that maintain or restore genetic variation to assure population viability are consequently of significant importance. We investigated, over 27 years, the genetic and demographic consequences of a demographic bottleneck followed by artificial supplementation in an isolated population of bighorn sheep (Ovis canadensis). Based on a long-term pedigree and individual monitoring, we documented the genetic decline, restoration and rescue of the population. Microsatellite analyses revealed that the demographic bottleneck reduced expected heterozygosity and allelic diversity by 6.2 and 11.3%, respectively, over two generations. Following supplementation, first-generation admixed lambs were 6.4% heavier at weaning and had 28.3% higher survival to 1 year compared to lambs of endemic ancestry. Expected heterozygosity and allelic diversity increased by 4.6 and 14.3% after two generations through new alleles contributed by translocated individuals. We found no evidence for outbreeding depression and did not see immediate evidence of swamping of local genes. Rapid intervention following the demographic bottleneck allowed the genetic restoration and rescue of this bighorn sheep population, likely preventing further losses at both the genetic and demographic levels. Our results provide further empirical evidence that translocation can be used to reduce inbreeding depression in nature and has the potential to mitigate the effect of human-driven environmental changes on wild population.

This table is part of a series of tables that present a portrait of Canada based on the various census topics. The tables range in complexity and levels of geography. Content varies from a simple overview of the country to complex cross-tabulations; the tables may also cover several censuses.

The census is Canada's largest and most comprehensive data source conducted by Statistics Canada every five years. The Census of Population collects demographics and linguistic information on every man, woman and child living in Canada. The data shown here is provided by Statistics Canada from the 2001 Census as a custom profile data order for the City of Vancouver, using the City's 22 local planning areas. The data may be reproduced provided they are credited to Statistics Canada, Census 2001, custom order for City of Vancouver Local Areas.Data AccessThis dataset has not yet been converted to a format compatible with our new platform. Please use the links below to access the files from our legacy site. Census local area profiles 2001 (CSV) Census local area profiles 2001 (XLS) Dataset schema (Attributes) Please see the Census local area profiles 2001 attributes page. NoteThe 22 Local Areas is defined by the Census blocks and is equal to the City'​s 22 local planning areas and includes the Musqueam 2 reserve.Vancouver CSD (Census Subdivision) is defined by the City of Vancouver municipal boundary which excludes the Musqueam 2 reserve but includes Stanley Park.Vancouver CMA (Census Metropolitan Area) is defined by the Metro Vancouver boundary which includes the following Census Subdivisions: Vancouver, Surrey, Burnaby, Richmond, Coquitlam, District of Langley, Delta, District of North Vancouver, Maple Ridge, New Westminster, Port Coquitlam, City of North Vancouver, West Vancouver, Port Moody, City of Langley, White Rock, Pitt Meadows, Greater Vancouver A, Bowen Island, Capilano 5, Anmore, Musqueam 2, Burrard Inlet 3, Lions Bay, Tsawwassen, Belcarra, Mission 1, Matsqui 4, Katzie 1, Semiahmoo, Seymour Creek 2, McMillian Island 6, Coquitlam 1, Musqueam 4, Coquitlam 2, Katzie 2, Whonnock 1, Barnston Island 3, and Langley 5. Data products that are identified as 20% sample data refer to information that was collected using the long census questionnaire. For the most part, these data were collected from 20% of the households; however they also include some areas, such as First Nations communities and remote areas, where long census form data were collected from 100% of the households. The following changes were made to the census family concept for 2001 and account for some of the increase in the total number of families, single parent families and children living at home: Two persons living in a same-sex common law relationship are now considered a family. Children living at home now include previously married children, provided they are not currently living with a spouse or common-law partner. A grandchild living in a three generation household where the parent (middle generation) was never married is now considered a child of the census family. A grandchild of a three-generation household where the middle generation is not present is now considered a child of the census family.Mode of transportation to work data is not reliable for the 2001 Census due to the TransLink Transit Strike that occurred during the data collection period. Data currencyThe data for Census 2001 was collected in May 2001. Data accuracyStatistics Canada is committed to protect the privacy of all Canadians and the confidentiality of the data they provide to us. As part of this commitment, some population counts of geographic areas are adjusted in order to ensure confidentiality. Counts of the total population are rounded to a base of 5 for any dissemination block having a population less than 15. Population counts for all standard geographic areas above the dissemination block level are derived by summing the adjusted dissemination block counts. The adjustment of dissemination block counts is controlled to ensure that the population counts for dissemination areas will always be within 5 of the actual values. The adjustment has no impact on the population counts of census divisions and large census subdivisions. Websites for further information Statistics Canada 2001 Census Dictionary Local area boundary dataset

Data on visible minority by individual low-income status, generation status, age and gender for the population in private households in Canada, provinces and territories, census metropolitan areas, census agglomerations and parts.

These are data on variation in host specificity and genetics among 16 populations of an aphid parasitoid, Aphelinus certus, 15 from Asia and one from North America. Host range was the same for all the parasitoid populations, but levels of parasitism varied among aphid species, suggesting adaptation to locally abundant aphids. Differences in host specificity did not correlate with geographical distances among parasitoid populations, suggesting that local adaption is mosaic rather than clinal, with a spatial scale of less than 50 kilometers. Analysis of reduced representation libraries for each population showed genetic differentiation among them. Differences in host specificity correlated with genetic distances among the parasitoid populations.

• Resource Title: data dictionary for Aphelinus certus population variation.

  File Name: data_dictionary_Aphelinus_certus.csv

  Resource Description: This is the data dictionary for the other files (Aphelinus_certus_host_use.csv, Aphelinus_certus_culture_data.csv) in this project.




• Resource Title: Host specificity of Aphelinus certus populations.

  File Name: Aphelinus_certus_host_use.csv

  Resource Description: Results of no-choice experiments in the laboratory on parasitism, adult emergence rate, and progeny sex ratio for 15 populations of Aphelinus certus from China, Japan, and South Korea and one population from the US.




• Resource Title: Culture data for Aphelinus certus populations.

  File Name: Aphelinus_certus_culture_data.csv

  Resource Description: This file gives data on the locations, dates, founding numbers, and collectors for the populations of Aphelinus certus studied in this project.




• Resource Title: Fst and host use distances among populations of Aphelinus certus.

  File Name: A_certus_Fst_host_dist.csv

  Resource Description: We used next-generation sequencing of reduced-representation genomic libraries to genotype single nucleotide polymorphisms (SNPs) among the 16 A. certus populations. Libraries were prepared as described in Manching et al. (2017). Briefly, genomic DNA was extracted from pools of wasps from each population using Qiagen DNeasy Blood and Tissue Kits (Qiagen, Valencia, CA), following the standard protocol. The resulting DNA was digested with restriction endonucleases using one rare cutter (NgoMIV with a 6 bp recognition site) and one frequent cutter (CviQI with a 4 bp recognition site) (New England Biolabs, Inc., Ipswich, MA), which together determined the number of unique locations of fragments across the genome and the lengths of these fragments. Custom adaptors, with barcodes for each population that also served to register clusters on the Illumina HiSeq during sequencing, were ligated onto the fragments using T4 ligase (New England Biolabs, Inc., Ipswich, MA). The ligates were pooled and purified using Agencourt AMPure XP beads (Beckman Coulter, Indianapolis, IN). The purified ligate was separated into 10 aliquots that were amplified in separate PCR reactions to both increase copy number at each locus and add more adaptor sequence for sequencing. The adaptors were designed so that the only fragments that amplify would have the rare-common combination of cut sites. After PCR, the products were pooled and then size-selected (300-350 bp) using the BluePippin system (Sage Science, Beverly, MA). After quantification with qPCR, the resulting fragments were sequenced for ~100 nucleotides in single-end reads an Illumina HiSeq 2500 (Illumina, San Diego, CA) at the Delaware Biotechnology Institute.

  Sequence data were processed with a reduced-representation computational pipeline called RedRep (described in Manching et al. (2017)); the scripts and documentation for the pipeline are available under an open source MIT license at https://github.com/UD-CBCB/RedRep. Briefly, sequences were deconvoluted by barcode using custom scripts and the FASTX-Toolkit (version 0.0.14; http://hannonlab.cshl.edu/fastx_toolkit). Custom scripts and CutAdapt (version 1.14; Martin 2011) were then used to remove adapters, trim low quality read ends, and filter out sequences that did not meet minimum length/quality standards or did not meet expectations for the restriction-site sequences. High-quality reads were mapped to the draft genome of A. certus using BWA-MEM program (version 0.7.16a; Li 2013). SNP loci were identified using the GATK HaplotypeCaller (version 3.5-0; McKenna et al. 2010). We filtered the SNP loci for read depth ≥ 50 and then for presence in all populations using BEDtools (version 2.26) and custom scripts written in R (version 3.3.3; R.Core.Team 2017). We tested the relationship between host use distance and genetic distance, as measured by FST. Because A. certus individuals were pooled within populations to make the libraries for sequencing, we used read depths to estimate allele frequencies for SNP loci. We filtered the data for SNP loci that were present in all populations and had read depth ≥ 50, and we used the numbers of individuals in each pool in calculating FST between populations with the calcPopDiff function in the polysat R package (version 1.7-2; Clark 2017). Using Mantel's permutation test, we compared the genetic and parasitism distance matrices (10,000 permutations with the mantel.randtest function in the ade4 R package).

  Clark, L. V. (2017) polysat version 1.7-2. Tools for polyploid microsatellite analysis. in. Li, H. (2013) Aligning sequence reads, clone sequences and assembly contigs with BWA-MEM. arXiv: 1303.3997v1 [q-bio.GN]. Manching, H., Sengupta, S., Hopper, K. R., Polson, S. W., Ji, Y. and Wisser, R. J. (2017) Phased genotyping-by-sequencing enhances analysis of genetic diversity and reveals divergent copy number variants in maize. Genes Genomes Genetics, 7(7), pp. 2161-2170. Martin, M. (2011) Cutadapt removes adapter sequences from high-throughput sequencing reads. . EMBnet.journal, 17, pp. 10-12. McKenna, A., Hanna, M., Banks, E., Sivachenko, A., Cibulskis, K., Kernytsky, A., Garimella, K., Altshuler, D., Gabriel, S., Daly, M. and DePristo, M. A. (2010) The Genome Analysis Toolkit: A MapReduce framework for analyzing next-generation DNA sequencing data. Genome Research, 20(9), pp. 1297-1303. R.Core.Team (2017) R: A language and environment for statistical computing. in: R Foundation for Statistical Computing, Vienna, Austria. https://www.R-project.org/.

The diamondback moth Plutella xylostella (Linnaeus) (Lepidoptera: Plutellidae) is one of the most destructive insect pests of cruciferous plants worldwide. Biological, ecological and genetic studies have indicated that this moth is migratory in many regions around the world. Although outbreaks of this pest occur annually in China and cause heavy damage, little is known concerning its migration. To better understand its migration pattern, we investigated the population genetic structure and demographic history of the diamondback moth by analyzing 27 geographical populations across China using four mitochondrial genes and nine microsatellite loci. The results showed that high haplotype diversity and low nucleotide diversity occurred in the diamondback moth populations, a finding that is typical for migratory species. No genetic differentiation among all populations and no correlation between genetic and geographical distance were found. However, pairwise analysis of the mitochondrial genes has indicated that populations from the southern region were more differentiated than those from the northern region. Gene flow analysis revealed that the effective number of migrants per generation into populations of the northern region is very high, whereas that into populations of the southern region is quite low. Neutrality testing, mismatch distribution and Bayesian Skyline Plot analyses based on mitochondrial genes all revealed that deviation from Hardy-Weinberg equilibrium and sudden expansion of the effective population size were present in populations from the northern region but not in those from the southern region. In conclusion, all our analyses strongly demonstrated that the diamondback moth migrates within China from the southern to northern regions with rare effective migration in the reverse direction. Our research provides a successful example of using population genetic approaches to resolve the seasonal migration of insects.