This statistic displays the forecast of the Indian population in New Zealand from 2013 to 2038, by age group. The Indian population in New Zealand between 40 and 64 years old is projected to be around *** thousand people by the year 2038.

Demographic projections provide an indication of future trends in the size and composition of the population, labour force, families and households. National Projections are produced at the national level (New Zealand) for the population (total, Māori, Pacific, Asian, and European ethnic groups), families, households and labour force. This dataset contains 2018-base projections of the European or Other (including New Zealander), Maori, Asian, Pacific, Middle Eastern/Latin American/African, Chinese, Indian, and Samoan ethnic populations usually living in New Zealand (released May 2021). These projections have the estimated resident population of each ethnic group at 30 June 2018 as a base.

The expansion of human settlements over the past few centuries is responsible for an unprecedented number of invasive species introductions globally. An important component of biological invasion management is understanding how introduction history and post-introduction processes have jointly shaped present-day distributions and patterns of population structure, diversity, and adaptation. One example of a successful invader is the European starling (Sturnus vulgaris), which was intentionally introduced to numerous countries in the 19th century, including Aotearoa New Zealand, where it has become firmly established. We used reduced-representation sequencing to characterise the genetic population structure of the European starling in New Zealand, and compared the population structure to that present in sampling locations in the native range and invasive Australian range. We found that population structure and genetic diversity patterns suggested restricted gene flow from the majority of New Zealand to the northmost sampling location (Auckland). We also profiled genetic bottlenecks and shared outlier genomic regions, which supported historical accounts of translocations between both Australian subpopulations and New Zealand, and provided evidence of which documented translocation events were more likely to have been successful. Using these results as well as historic demographic patterns, we demonstrate how genomic analysis complements even well-documented invasion histories to better understand invasion processes, with direct implication for understanding contemporary gene flow and informing invasion management. Methods Sample Collection A total of 106 starling specimen samples were obtained from various contributors within New Zealand from five geographically distinct locations between May 2022 and October 2023. Sampling covered three locations in the North Island, specifically in the Auckland region (AUK: n=18), the Manawatū-Whanganui region (WHA: n=12), the Wellington region (WEL: n=40) and two in the South Island in the Marlborough region (MRL: n=15) and Canterbury region (CAN: n=21). In addition to the newly obtained samples, we also incorporated sequence data from the native European range (Antwerp, Belgium; ANT: n=15, Newcastle, United Kingdom; NWC: n=15, Monks Wood, United Kingdom; MKW: n=15), as well as two locations from within the invasive Australian range (Orange; ORG: n=15, McLaren Vale; MLV: n=15) from a previously published Diversity Arrays Technology Pty Ltd sequencing (DArT-seq) dataset. DNA Extraction and Sequencing Extracted DNA from the newly collected New Zealand samples was sent to Diversity Arrays for sequencing. Sequencing was performed on an Illumina Hiseq2500/Novaseq6000. Raw Sequence Processing The previously published raw DArT-seq data, along with the MRL samples (January 2023 sequencing batch) were demultiplexed using stacks v2.2 process_radtags, while also discarding low quality reads (-q), reads with uncalled bases (-c), and rescuing barcodes and RAD-Tag cut sites (-r). It was not necessary to perform this step on the remainder of the new raw sequence data because DArT performed in-house demultiplexing using a proprietary bioinformatic pipeline. For all the data, we used fastp v0.23.2 to remove adapter sequences and in the same step filtered reads for a minimum Phred quality score of 22 (-q 22) and a minimum length of 40 (-l 40). Both batches of sequence data produced as part of this study were additionally length trimmed to reduce the read length of the newer sequence data to match the base length of the older sequence data (-b 69). Mapping, Variant Calling, and Filtering We used the program bwa v0.7.17 to index the reference genome S. vulgaris vAU1.0 and align the trimmed DArT reads using the bwa aln function (-B 5 to trim the first 5 base pairs of each read), which is optimised for single-end short reads. This was then followed by the bwa samse function for producing the SAM formatted output files containing the alignments and their respective base qualities. Alignments were then sorted and indexed using samtools v1.16.1, and single nucleotide polymorphisms (SNPs) were subsequently called and annotated using bcftools v1.16 with the mpileup (-a "DP,AD,SP", --ignore-RG) and call (-mv, -f GQ) functions. We removed known technical replicates and identified relatives from the data. vcftools v0.1.15 was used to remove indels (--remove-indels), and quality filter for a minimum site quality score of 30 (--minQ30), minimum genotype quality score of 20 (--minGQ 20), and minimum and maximum depth of coverage of 5 (--minDP 5) and 100 (--maxDP 100). Then, to account for batch effects that may impact the sequenced loci, we kept only SNPs present in at least 50% of the individuals in each sampling location. We ran one final filtering step to ensure appropriate levels of missingness and rare alleles using the following parameters: maximum missingness per site of 30% (--max-missing 0.7), minor allele count of 5 (--mac 5), and a minimum and maximum allele per locus of 2 (--min-alleles 2 --max-alleles 2), resulting in a dataset containing 19,174 SNPs and 141 individuals.

The common myna (Acridotheres tristis) is one of the most invasive bird species in the world, yet its colonisation history is only partly understood. We identified the introduction history and population structure, and quantified the genetic diversity of myna populations from the native range in India and the introduced populations in New Zealand, Australia, Fiji, Hawaii, and South Africa, based on thousands of single nucleotide polymorphism markers in 814 individuals. We were able to identify the source population of mynas in several invasive locations: mynas from Fiji and Melbourne, Australia, were likely founded by individuals from a subpopulation in Maharashtra, India, while mynas in Hawaii and South Africa were likely independently founded by individuals from other localities in India. Our findings suggest that New Zealand mynas were founded by individuals from Melbourne, which, in turn, were founded by individuals from Maharashtra. We identified two genetic clusters among New Zealand mynas, divided by New Zealand’s North Island’s axial mountain ranges, confirming previous observations that mountains and thick forests may form barriers to myna dispersal. Our study provides a foundation for other population and invasion genomic studies and provides useful information for the management of this invasive species. Methods A total of 183 myna tissue samples in ethanol from India, New Zealand, Australia, South Africa, Hawaii and Fiji between 1975–1989 were received from the Royal Ontario Museum (ROM). A further 193 euthanized mynas were obtained from myna control programs from contributors in New Zealand between 2017–2020, and muscle tissue was subsampled from each individual. DNA was extracted from the ROM tissue samples using the DNeasy Blood & Tissue Kit (Qiagen) following the manufacturer's protocols. DNA was extracted from the New Zealand tissue samples using the Monarch Genomic DNA Purification Kit (NEB) following the manufacturer's protocols. DNA concentration was measured using a Qubit 2.0 Fluorometer (Thermo Fisher Scientific). DNA was diluted to standardized concentrations of 50–100 ng/μL, and sent to Diversity Arrays Technology Pty Ltd company (DArT P/L) for further processing. Samples from 363 individuals were successfully sequenced, including 13 duplicate samples, using the proprietary Diversity Arrays Technology platform and protocol (DArTseq). We included 13 duplicate samples. DArTseq also includes internal replicates of samples as part of its protocol. This dataset consists of raw reads generated from this study (363 individuals, 13 replicates, and 64 DArT internal replicates, totaling 440 files). The raw reads generated from this study were processed and co-analysed with the DArTseq data from 451 mynas from Australia from the Ewart et al. (2019) study (mynas sampled in 2014–2015). Files containing variants called using the BCFtools, STACKS, and DArTsoft14 pipelines can also be found here (See README.md and article supplementary information Appendix S2 for more details).

Migrants from the United Kingdom have long been Australia’s primary immigrant group and in 2023 there were roughly 960 thousand English-born people living in Australia. India and China held second and third place respectively with regard to Australia’s foreign-born population. The relative dominance of Asian countries in the list of top ten foreign-born residents of Australia represents a significant shift in Australia’s immigration patterns over the past few decades. Where European-born migrants had previously overshadowed other migrant groups, Australian migration figures are now showing greater migration numbers from neighboring countries in Asia and the Pacific. A history of migration Australia is often referred to as an ‘immigrant nation’, alongside the United States, Canada, and New Zealand. Before the Second World War, migrants to Australia were almost exclusively from the UK, however after 1945, Australia’s immigration policy was broadened to attract economic migrants and temporary skilled migrants. These policy changes saw and increase in immigrants particularly from Greece and Italy. Today, Australia maintains its status as an ‘’Immigrant nation’’, with almost 30 percent of the population born overseas and around 50 percent of the population having both that were born overseas. Australian visas The Australian immigration program has two main categories of visa, permanent and temporary. The permanent visa category offers three primary pathways: skilled, family and humanitarian. The skilled visa category is by far the most common, with more than a million permanent migrants living in Australia on this visa category at the last Australian census in 2021. Of the temporary visa categories, the higher education visa is the most popular, exceeding 180 thousand arrivals in 2023.

Invasive, non-native species are one of the major causes of global biodiversity loss. Although they are, by definition, successful in their non-native range, their populations generally show major reductions in their genetic diversity during the demographic bottleneck they experience during colonization. By investigating the mitochondrial genetic diversity of an invasive non-native species, the stoat Mustela erminea, in New Zealand and comparing it to diversity in the species’ native range in Great Britain, we reveal the opposite effect. We demonstrate that the New Zealand stoat population contains four mitochondrial haplotypes that have not been found in the native range. Stoats in Britain rely heavily on introduced rabbits Oryctolagus cuniculus as their primary prey and were introduced to New Zealand in a misguided attempt at biological control of rabbits, which had also been introduced there. While invasive stoats have since decimated the New Zealand avifauna, native stoat populations were themselves decimated by the introduction to Britain of Myxoma virus as a control measure for rabbits. We highlight the irony that while introduced species (rabbits) and subsequent biocontrol (myxomatosis) have caused population crashes of native stoats, invasive stoats in New Zealand, which were also introduced for biological control, now contain more genetic haplotypes than their most likely native source.

Gridded Population of the World, Version 2 (GPWv2) consists of estimates of human population for the years 1995 and 1990 by 2.5 arc-minute grid cells. The data products are population counts (raw counts), population densities (per square km), and land area (actual area net of ice and water), all of which are available in two GIS-compatible data formats at the global, continent (Antarctica not included), and country levels. A proportional allocation gridding algorithm, utilizing 127,105 national and sub-national administrative units, is used to assign population values to grid cells. Advantages to GPWv2 include higher quality data from the U.S., Africa, Australia, Canada, Europe, Russia, New Zealand, and India; 8 times the number of administrative units; national population estimates that have been adjusted to match the United Nations national estimated population for each country; a proportional allocation algorithm that reduces error with multiple input polygons; and higher spatial resolution. GPWv2 is produced by the Columbia University Center for International Earth Science Information Network (CIESIN) in collaboration with the International Food Policy Research Institute (IFPRI) and the World Resources Institute (WRI). (Suggested Usage: To serve a wide user community by providing the latest data on human population distribution that can be used in interdisciplinary studies of the environment.)

Based on a comparison of coronavirus deaths in 210 countries relative to their population, Peru had the most losses to COVID-19 up until July 13, 2022. As of the same date, the virus had infected over 557.8 million people worldwide, and the number of deaths had totaled more than 6.3 million. Note, however, that COVID-19 test rates can vary per country. Additionally, big differences show up between countries when combining the number of deaths against confirmed COVID-19 cases. The source seemingly does not differentiate between "the Wuhan strain" (2019-nCOV) of COVID-19, "the Kent mutation" (B.1.1.7) that appeared in the UK in late 2020, the 2021 Delta variant (B.1.617.2) from India or the Omicron variant (B.1.1.529) from South Africa.

The difficulties of death figures

This table aims to provide a complete picture on the topic, but it very much relies on data that has become more difficult to compare. As the coronavirus pandemic developed across the world, countries already used different methods to count fatalities, and they sometimes changed them during the course of the pandemic. On April 16, for example, the Chinese city of Wuhan added a 50 percent increase in their death figures to account for community deaths. These deaths occurred outside of hospitals and went unaccounted for so far. The state of New York did something similar two days before, revising their figures with 3,700 new deaths as they started to include “assumed” coronavirus victims. The United Kingdom started counting deaths in care homes and private households on April 29, adjusting their number with about 5,000 new deaths (which were corrected lowered again by the same amount on August 18). This makes an already difficult comparison even more difficult. Belgium, for example, counts suspected coronavirus deaths in their figures, whereas other countries have not done that (yet). This means two things. First, it could have a big impact on both current as well as future figures. On April 16 already, UK health experts stated that if their numbers were corrected for community deaths like in Wuhan, the UK number would change from 205 to “above 300”. This is exactly what happened two weeks later. Second, it is difficult to pinpoint exactly which countries already have “revised” numbers (like Belgium, Wuhan or New York) and which ones do not. One work-around could be to look at (freely accessible) timelines that track the reported daily increase of deaths in certain countries. Several of these are available on our platform, such as for Belgium, Italy and Sweden. A sudden large increase might be an indicator that the domestic sources changed their methodology.

Where are these numbers coming from?

The numbers shown here were collected by Johns Hopkins University, a source that manually checks the data with domestic health authorities. For the majority of countries, this is from national authorities. In some cases, like China, the United States, Canada or Australia, city reports or other various state authorities were consulted. In this statistic, these separately reported numbers were put together. For more information or other freely accessible content, please visit our dedicated Facts and Figures page.

Human associated introduction of pathogens and consequent invasions are very evident in areas where no related organisms existed before. In areas where related but distinct populations or closely related cryptic species already exist, the invasion process is much harder to unravel. In this study, the population structure of the Eucalyptus leaf pathogen Teratosphaeria nubilosa was studied within its native range in Australia, including both commercial plantations and native forests. A collection of 521 isolates from across its distribution was characterized using eight microsatellite loci, resulting in 112 multilocus haplotypes (MLH). Multivariate and Bayesian analyses of the population conducted in STRUCTURE revealed three genetically isolated groups (A, B and C), with no evidence for recombination or hybridization among groups, even when they co-occur in the same plantation. DNA sequence data of the ITS (n=32), β-tubulin (n=32) and 27 anonymous loci (n=16) were consistent with microsatellite data in suggesting that T. nubilosa should be considered as a species complex. Patterns of genetic diversity provided evidence of biological invasions by the pathogen within Australia in the states of Western Australia and New South Wales, and helped unravel the pattern of invasion beyond Australia into New Zealand, Brazil and Uruguay. No significant genetic differences in pathogen populations collected in native forests and commercial plantations were observed. This emphasizes the importance of sanitation in the acquisition of nursery stock for the establishment of commercial plantations.