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This web map is provides the data and maps used in the story map Population density and diversity in New Zealand, created by Stats NZ. It uses Statistical Area 1 (SA1) data collected and published as part of the 2018 Census. The web map uses a mapping technique called multi-variate dot density mapping. The data used in the map can be found at this web service - 2018 Census Individual part 1 data by SA1.For questions or comments on the data or maps, please contact info@stats.govt.nz Census Data Quality Notes:We combined data from the census forms with administrative data to create the 2018 Census dataset, which meets Stats NZ’s quality criteria for population structure information.We added real data about real people to the dataset where we were confident the people should be counted but hadn’t completed a census form. We also used data from the 2013 Census and administrative sources and statistical imputation methods to fill in some missing characteristics of people and dwellings.Data quality for 2018 Census provides more information on the quality of the 2018 Census data.An independent panel of experts has assessed the quality of the 2018 Census dataset. The panel has endorsed Stats NZ’s overall methods and concluded that the use of government administrative records has improved the coverage of key variables such as age, sex, ethnicity, and place. The panel’s Initial Report of the 2018 Census External Data Quality Panel (September 2019), assessed the methodologies used by Stats NZ to produce the final dataset, as well as the quality of some of the key variables. Its second report 2018 Census External Data Quality Panel: Assessment of variables (December 2019) assessed an additional 31 variables. In its third report, Final report of the 2018 Census External Data Quality Panel (February 2020), the panel made 24 recommendations, several relating to preparations for the 2023 Census. Along with this report, the panel, supported by Stats NZ, produced a series of graphs summarising the sources of data for key 2018 Census individual variables, 2018 Census External Data Quality Panel: Data sources for key 2018 Census individual variables.The Quick guide to the 2018 Census outlines the key changes we introduced as we prepared for the 2018 Census, and the changes we made once collection was complete.The geographic boundaries are as at 1 January 2018. See Statistical standard for geographic areas 2018.2018 Census – DataInfo+ provides information about methods, and related metadata.Data quality ratings for 2018 Census variables provides information on data quality ratings.
In a 2018 survey about the importance of diversity issues for public sector organizations in New Zealand, 79.2 percent of respondents said that wellbeing was an important diversity issue. On the other end of the scale, only 16.8 percent said that religion was an important diversity issue.
In a survey about the importance of diversity issues for small organizations in New Zealand conducted in March 2020, 62 percent of respondents said that wellbeing was an important diversity issue. Additionally, around ten percent said that religion was an important diversity issue.
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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.
In a survey about the importance of diversity issues for large organizations in New Zealand conducted in March 2020, 78 percent of respondents said that wellbeing was an important diversity issue. Notably, significantly more respondents said that gender and bias were important diversity issues than those from both small and medium organizations.
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Changes in the functional structures of communities are rarely examined along multiple large-scale environmental gradients. Here, we describe patterns in functional beta diversity for New Zealand marine fishes vs depth and latitude, including broad-scale delineation of functional bioregions. We derived eight functional traits related to food acquisition and locomotion and calculated complementary indices of functional beta diversity for 144 species of marine ray-finned fishes occurring along large-scale depth (50 - 1200 m) and latitudinal gradients (29° - 51° S) in the New Zealand Exclusive Economic Zone. We focused on a suite of morphological traits calculated directly from in situ Baited Remote Underwater Stereo-Video (stereo-BRUV) footage and museum specimens. We found that functional changes were primarily structured by depth followed by latitude, and that latitudinal functional turnover decreased with increasing depth. Functional turnover among cells increased with increasing depth distance, but this relationship plateaued for greater depth distances (> 750 m). In contrast, functional turnover did not change significantly with increasing latitudinal distance at 700 - 1200 m depths. Shallow functional bioregions (50 - 100 m) were distinct at different latitudes, whereas deeper bioregions extended across broad latitudinal ranges. Fishes in shallow depths had a body shape conducive to efficient propulsion, while fishes in deeper depths were more elongated, enabling slow, energy-efficient locomotion, and had large eyes to enhance vision. Environmental filtering may be a primary driver of broad-scale patterns of functional beta diversity in the deep sea. Greater environmental homogeneity may lead to greater functional homogeneity across latitudinal gradients at deeper depths (700 - 1200 m). We suggest that communities living at depth may follow a ‘functional village hypothesis’, whereby similar key functional niches in fish communities may be maintained over large spatial scales.
Methods Fish community data
Baited Remote Underwear Stereo-Video systems (Stereo-BRUVs) were used to sample marine ray-finned fishes (Class Actinopterygii) in situ at off-shore locations across northern, eastern and southern New Zealand (see Zintzen et al. 2012; 2017 for detailed positions). The Stereo-BRUVs were deployed in a stratified random sampling design at each of seven depths (50 m, 100 m, 300 m, 500 m, 700 m, 900 m and 1200 m) within each of seven locations (from north to south): Rangitāhua, the Kermadec Islands (KER), Three Kings Islands (TKI), Great Barrier Island (GBI), Whakaari, White Island (WI), Kaikōura (KKA), Otago Peninsula (OTA) and the Auckland Islands (AUC) that spanned 21° of latitude in New Zealand waters (with n = 5 - 7 replicate deployments per depth-by-location, see Figure 1 from Zintzen et al. 2017 for a detailed map showing exact sampling locations). Video footage was obtained from a total of 329 deployments (2 hours each) across 47 depth-by-location cells (2 cells were not sampled – White Island at 1200 m and Auckland Islands at 1200 m, due to poor weather conditions). For further details regarding the sampling design, the Stereo-BRUV apparatus and deployment, calibration of measurements and associated methodologies, see Zintzen et al. (2012; 2017).
Functional traits
Fifteen raw morphological measurements were obtained from individuals of each species of fish, in situ, by reviewing footage obtained from each Stereo-BRUV deployment and using the software ‘EventMeasure’ (www.seagis.com.au; see Myers et al. (in press) and Table S1 in Supporting Information). Where possible, measurements from multiple individuals of a single species within a given depth-by-location cell were obtained. A complete set of morphological measurements were not always possible to obtain for every species observed in the video footage. For individuals that were missing no more than 3 (out of 15) measurements, the missing values were imputed using a random-forest machine-learning algorithm (Stekhoven & Bühlmann 2012), based on the other individuals of that species in the dataset having a complete set of measurements. This imputation relies on the assumption that relationships among the morphological variables remain constant within a given species. In addition, to ensure we would have a full set of measured traits for every fish species, we also took raw morphological measurements directly from two preserved museum specimens (held within the National Fish Collection at the Museum of New Zealand Te Papa Tongarewa, Wellington) for every species seen in the video footage (voucher registrations are provided in Table S2 in Supporting Information). In total, there were 144 species recorded across the 47 depth-by-location cells, and 509 species-by-cell occurrences. The original dataset comprised a complete set of 15 raw morphological measurements for 722 individuals observed in video footage (136 of these required some random-forest imputation, and missing traits were remeasured for 4 individuals), plus 291 museum specimens.
We calculated 8 trait variables, namely: eye size, oral gape position, jaw length relative to head length, elongation, eye position, caudal peduncle throttling, pectoral fin position and total body length – each as a function of the 15 raw morphological measurements (2 of the raw morphological measurements were used only for data imputation, Table S3, Supporting Information). These morphological traits focused on key aspects of locomotion, visual perception and feeding for fishes that correspond to important functional variations in the body plan and structure of fishes across large depth gradients (Myers et al. 2019).
We obtained representative trait values for every species within every cell in the study design, while taking into account the intraspecific trait variability. To do so we compiled a table of 8 unique traits (columns) for each species in each depth-by-location cell (509 rows), we randomly drew 1 individual from the list of all complete individuals for each species that were (in order of preference): (i) within that depth-by-location cell, (ii) at the same depth, (iii) from anywhere within the Stereo-BRUV study design or (iv) from a museum specimen. We replicated this random-draw procedure 100 times to generate 100 species-cell × trait (509 × 8) data tables. These data tables enabled us to build 100 multivariate functional spaces based on the 8 normalised continuous trait variables that were used to compute the Euclidean distances between species. By calculating beta diversity values for all 100 tables, then averaging these values, we were able to integrate the available individual-level (within-species) morphological variation into the study, given the logistic constraints on the number of individuals of each species we were able to measure, while also maintaining spatial variation in morphologies encountered within each species as well as possible.
Measures of functional beta diversity
We calculated the functional turnover, or functional beta diversity, by considering the functional distances between each of the species occurring within one cell, with every species occurring within another cell (Swenson 2014). We calculated the following metrics between every pair of cells: (i) mean pairwise functional distance (MPFD.beta) which corresponds in the beta context to the mean distance in functional space between all pairs of species across two cells (Swenson 2014), and (ii) mean nearest neighbor distance (MNND.beta) which corresponds in the beta context to the average of the minimum functional distance between each species in one cell, to every species in another cell (Swenson & Weiser 2014). Previously, MPFD has been defined in an alpha context as the functional analogue to average taxonomic distinctness (Clarke & Warwick 1998), and is also called mean phylogenetic pairwise distance (Swenson 2014) when used in a phylogenetic context. MNND, also called Gamma+ (Clarke et al. 2006), has been used previously in both phylogenetic (Webb et al. 2002) and functional contexts (Swenson & Weiser 2014; Pigot, Trisos & Tobias 2016) where it has been used to estimate functional originality (Mouillot et al. 2013; Leitao et al.2016), and can be considered as an indicator of differences in niche (Swenson et al. 2020). These two functional beta diversity metrics allow the full dimensionality of the functional space to be entirely maintained, which is not necessarily possible with earlier-described metrics, such as convex hulls (Villéger et al. 2013), or hypervolumes (Blonder et al. 2014; 2018). These typically require a rather drastic reduction in dimensionality, especially for species-poor communities such as those encountered in the deep sea.
We calculated the MPFD.beta and MNND.beta metrics between every pair of cells for each of the 100 species-cell by trait (509 × 8) data matrices, then computed the mean and standard deviation across the 100 tables for subsequent analyses. The result was a 47 × 47 matrix of functional dissimilarities (either MPFD.beta or MNND.beta) among all pairs of cells in our study design.
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This dataset presents the locality, and species diversity measures of Recent benthic foraminifera in shallow water (<50 m) around New Zealand. Census data on 89 species of benthic foraminiferal tests from 131 samples from brackish-water environments throughout New Zealand are analysed by cluster and correspondence analyses. Ten brackish-water faunal associations are recognised. When mapped in study areas they can be seen to inhabit distinct estuarine and tidal inlet environments.
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Biodiversity is unevenly distributed worldwide in terms of both species diversity and species endemism. Although centres of endemism are a conservation priority, both patterns and drivers of endemism are poorly understood in New Zealand. Here we explore whether invertebrate species distribution records in New Zealand represent the complete geographic range of species. We use distribution records of 2,322 invertebrate species to survey variation in range size and regional-endemism among 28 New Zealand regions, and explore the correlates of diversity and regional-endemism. Our data suggest patterns of regional-endemism in New Zealand invertebrates are not artefacts of sampling effort and the majority of species are not widespread. We found that endemism-score (which is a measure that corrects for species diversity) correlates positively with the relative size of the region three million years ago. Five variables (and their interactions) contributed to the relative level of invertebrate species endemism within a region (in a generalised linear model). Level of endemism tends to be lower in regions with greater geographic connectivity. This suggests that high levels of regional-endemism are not simply the product of the accumulation of species over time, but depends on the ability of a region to retain local species.
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This dataset contains the digitized treatments in Plazi based on the original journal article Dohlen, Von (2013): Native aphids of New Zealand — diversity and host associations. Zootaxa 3647 (4): 501-517, DOI: 10.11646/zootaxa.3647.4.1
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A brief informal outline of the diversity of Lachnaceae (Leotiomycetes, Helotiales) known for New Zealand, based on PDD and ICMP specimens with DNA sequences. The phylogenetic diversity of the New Zealand taxa is compared with that globally. Asperopilum entry updated 2024.
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Bottlenose dolphins (Tursiops truncatus) occupy a wide range of coastal and pelagic habitats throughout tropical and temperate waters worldwide. In some regions, "inshore" and "offshore" forms or ecotypes differ genetically and morphologically, despite no obvious boundaries to interchange. Around New Zealand, bottlenose dolphins inhabit 3 coastal regions: Northland, Marlborough Sounds, and Fiordland. Previous demographic studies showed no interchange of individuals among these populations. Here, we describe the genetic structure and diversity of these populations using skin samples collected with a remote biopsy dart. Analysis of the molecular variance from mitochondrial DNA (mtDNA) control region sequences (n = 193) showed considerable differentiation among populations (Fst = 0.17, Φst = 0.21, P < 0.001) suggesting little or no female gene flow or interchange. All 3 populations showed higher mtDNA diversity than expected given their small population sizes and isolation. To explain the source of this variation, 22 control region haplotypes from New Zealand were compared with 108 haplotypes worldwide representing 586 individuals from 19 populations and including both inshore and offshore ecotypes as described in the Western North Atlantic. All haplotypes found in the Pacific, regardless of population habitat use (i.e., coastal or pelagic), are more divergent from populations described as inshore ecotype in the Western North Atlantic than from populations described as offshore ecotype. Analysis of gene flow indicated long-distance dispersal among coastal and pelagic populations worldwide (except for those haplotypes described as inshore ecotype in the Western North Atlantic), suggesting that these populations are interconnected on an evolutionary timescale. This finding suggests that habitat specialization has occurred independently in different ocean basins, perhaps with Tursiops aduncus filling the ecological niche of the inshore ecotype in some coastal regions of the Indian and Western Pacific Oceans.
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ITS gene tree showing diversity of unnamed Leotiomycetes species within Hyphodiscaeae in New Zealand
Aim: Functional diversity metrics inform how species’ traits relate to ecosystem functions, useful for quantifying how exploitation and disturbance impact ecosystems. We compare the functional diversity of entire fish communities in a shallow-water region with a deep-sea region for further insight into the differences between these ecosystem types.
Location: The regions compared in this study were selected to represent a shallow-water coastal region, Tasman and Golden Bays (TBGB), and a deep-sea region, Chatham Rise (CR), in New Zealand.
Methods: Functional diversity was assessed using four metrics: functional richness, evenness, divergence, and dispersion. We compared these metrics across four key functions: habitat use, feeding, locomotion and life history.
Results: Our results showed that overall, the shallow-water and deep-sea ecosystems had equal diversity. When focusing on the four ecological functions, the two ecosystems exhibited equal diversity metrics across most anal...
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Aim: Functional diversity metrics inform how species' traits relate to ecosystem functions, useful for quantifying how exploitation and disturbance impact ecosystems. We compare the functional diversity of entire fish communities in a shallow-water region with a deep-sea region for further insight into the differences between these ecosystem types.
Location: The regions compared in this study were selected to represent a shallow-water coastal region, Tasman and Golden Bays (TBGB), and a deep-sea region, Chatham Rise (CR), in New Zealand.
Methods: Functional diversity was assessed using four metrics: functional richness, evenness, divergence, and dispersion. We compared these metrics across four key functions: habitat use, feeding, locomotion and life history.
Results: Our results showed that overall, the shallow-water and deep-sea ecosystems had equal diversity. When focusing on the four ecological functions, the two ecosystems exhibited equal diversity metrics across most analyses. Of the significantly different results, the deep-sea had higher functional richness for habitat use and locomotion traits, lower functional dispersion for feeding, and lower functional evenness for life history.
Main Conclusions: Differences across the functions highlight higher diversity of habitat utilisation by deep-sea fish, while lower diversity in feeding suggests deep-sea fish tend towards generalist diets, likely driven by low food availability. Deep-sea fish displayed an increased range of locomotive traits in our analyses, but this conflicts with existing evidence and warrants further study. Life history results suggests deep-sea fish exhibit higher clustering of traits, indicating potential under-utilisation of life history strategies in the deep-sea. Our results demonstrate that although deep-sea fish communities have similar levels of diversity to shallow-water communities, the traits that structure this diversity differ, and therefore, the systems may respond to exploitation differently.
Additional information on the strains and sequences used in this study of the genetic and taxonomic diversity of the genus Trichoderma in New Zealand. Australasian Plant Pathology 46: 11-30, 2017
Abstract: This is the first comprehensive survey of the species diversity of Trichoderma for a region within the temperate Southern Hemisphere. New Zealand makes an ideal target for such a survey because of the extensive historical collections of this genus from both native and human-modified ecosystems. From the 320 Trichoderma strains sequenced for the translation elongation factor-1α (tef1α) gene, in addition to the names associated with voucher specimens at the New Zealand Fungarium (PDD, Landcare Research), we recognise 72 Trichoderma species as present in New Zealand. Thirty-three species are reported for the first time from New Zealand and 13 of these appear to represent undescribed taxa. The New Zealand species are positioned across most Trichoderma clades, with terminal lineages related to T. viride, T. koningii and T. harzianum well represented. Of the 14 undescribed species, Trichoderma sp. “atroviride B”, a sister species to T. atroviride s.s., was the most commonly recovered species. Records of several species known only from fungarium specimens could not be confirmed by DNA analysis. Populations of Trichoderma in New Zealand are likely to represent a mixture of ancient indigenous lineages, more recent natural introductions, and species introduced as a result of human-mediated dispersal. Twenty-eight Trichoderma species have been reported only from New Zealand or other Southern Hemisphere locations. The diversity of Trichoderma species in New Zealand, their phylogenetic relationships, distribution, ecology, and possible origins are discussed in this paper.
In a 2018 survey about the importance of diversity issues for medium organizations in New Zealand, 87.2 percent of respondents said that wellbeing was an important diversity issue. Additionally, 13.8 percent said that religion was an important diversity issue.
Phylogenies and summary of diversity of Erioscyphella (Leotiomycetes, Helotiales, Lachnaceae) in New Zealand
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Energy and environmental stability are positively correlated with species richness along broad-scale spatial gradients in terrestrial ecosystems, so their relative importance in generating and preserving diversity cannot be readily disentangled. This study seeks to exploit the negative correlation between energy and stability along the oceanic depth gradient to better understand their relative contribution in shaping broadscale biodiversity patterns. We develop a conceptual framework by simulating speciation and extinction along energy and stability gradients to generate expected patterns of biodiversity for a suite of complementary phylogenetic diversity metrics. Using a time-calibrated molecular phylogeny for New Zealand marine ray-finned fishes and a replicated community ecological sampling design, we then modelled these metrics along large-scale depth and latitude gradients. Our results indicate that energy-rich shallow waters may be an engine of diversity for percomorphs, but also suggest that recent speciation occurs in ancient fish lineages in the deep sea, hence questioning the role of energy as a key driver of speciation. Despite potentially facing high extinction early in their evolution, ancient phylogenetic lineages specialized for the deep-sea were likely preserved by environmental stability during the Cenozoic. Furthermore, intermediate depths might be a "museum" (or zone of overlap) for distinct lineages that occur predominantly in either shallow or deep-sea waters. These intermediate depths (500-900m) may form a "phylogenetic diversity bank", perhaps providing a refuge during ancient (Mesozoic) extreme anoxic events affecting the deep sea and more recent (Pliocene-Pleistocene) climatic events occurring in shallow ecosystems. Finally, the phylogenetic structures observed in fish communities at intermediate depths suggest other processes might restrict the co-occurrence of closely related species. Overall, by combining a conceptual framework with models of empirical phylogenetic diversity patterns, our study paves the way for understanding the determinants of biodiversity across the largest habitat on earth.
Island endemic species are often vulnerable to decline and extinction following human settlement, and the genetic study of historical museum specimens can be useful in understanding these processes. The kākāpō (Strigops habroptilus) is a critically endangered New Zealand parrot that was formerly widespread and abundant. It is well established that both Polynesian and European colonization of New Zealand impacted the native avifauna, but the timeframe and severity of impacts have differed depending on species. Here, we investigated the relative importance of the 2 waves of human settlement on kākāpō decline, using microsatellites and mitochondrial DNA (mtDNA) to characterize recent kākāpō genetic and demographic history. We analyzed samples from 49 contemporary individuals and 54 museum specimens dating from 1884 to 1985. Genetic diversity decreased significantly between historical and contemporary kākāpō, with a decline in mean number of microsatellite alleles from 6.15 to 3.08 and in n...
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Authors: Thomas SH Paul1, Loretta G Garrett1, Simeon J Smaill2Affiliations: 1 Scion, Private Bag 3020, Rotorua 3046, New Zealand; 2 Scion, PO Box 29237, Riccarton, Christchurch 8440, New Zealand.The dataA data set from the New Forest trial series (FR531) spanning 4 sites in New Zealand. The data set includes initial, time zero, data on plant diversity, soil and trial sub-plot details. The dataset links to the Data in Brief publication Paul et al., (2024) which describes the sample collection and testing methods.The data includes one file with 9 data sheets and two data folders:· 1_New Forest PSP details – by each permeant plot sample (PSP) ID including block and plot ID, planting stock ID, slope, elevation, and aspect.· 2_Time zero plant diversity – data by PSP ID includes plant species diversity and abundance.· 3_Time zero soil chemistry – data by PSP ID and sample depth includes sampling method and soil total carbon and total nitrogen chemical analysis.· 4_Time zero soil bulk density – data by PSP ID and sample depth includes sampling method and soil bulk density.· 5_Time zero soil microbial – data by PSP ID and sample depth includes sampling method and soil microbial testing method.· 6_Time zero soil profile – data from one representative soil profile, includes soil horizon description and New Zealand soil classification.· 7_Time zero soil variability – data by PSP ID includes soil horizon depth and notation.· 8_Time zero topsoil depth – data by PSP ID includes topsoil depth.· 9_Time zero soil porosity – data by PSP ID for 0-10 cm total porosity, particle density, field air capacity and macro-porosity.· Folder FR531_MIR spectra: FR556 trial soil Mid-Infrared spectra opus files by sample ID.· Folder FR531_MIR spectra_csv: FR556 trial soil Mid-Infrared spectra csv files by sample ID.Contact: Loretta Garrett (loretta.garrett@scionresearch.com)AcknowledgmentsFunding to publish the data came from the New Zealand Ministry of Business, Innovation & Employment (MBIE) Strategic Science Investment Fund held by Scion (C04X1703). Funding for the trial installation and initial sample collection was provided from the Protecting and Enhancing the Environment through Forestry, which was funded by the New Zealand Foundation for Research, Science and Technology (C04X0304). We thank the landowners who provided land for the trial and their commitment to host the long-term trials.ReferencesPaul, T. S. H., Garrett, L. G., & Smaill, S. J. (2024). Afforestation using a range of tree species, in New Zealand: New Forest trial series establishment, site description, and initial data. Data in Brief, 110321. https://doi.org/https://doi.org/10.1016/j.dib.2024.110321 DisclaimerWe make no warranties regarding the accuracy or integrity of the Data. We accept no liability for any direct, indirect, special, consequential or other losses or damages of whatsoever kind arising out of access to, or the use of the Data. We are in no way to be held responsible for the use that you put the Data to. You rely on the Data entirely at your own risk.
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This web map is provides the data and maps used in the story map Population density and diversity in New Zealand, created by Stats NZ. It uses Statistical Area 1 (SA1) data collected and published as part of the 2018 Census. The web map uses a mapping technique called multi-variate dot density mapping. The data used in the map can be found at this web service - 2018 Census Individual part 1 data by SA1.For questions or comments on the data or maps, please contact info@stats.govt.nz Census Data Quality Notes:We combined data from the census forms with administrative data to create the 2018 Census dataset, which meets Stats NZ’s quality criteria for population structure information.We added real data about real people to the dataset where we were confident the people should be counted but hadn’t completed a census form. We also used data from the 2013 Census and administrative sources and statistical imputation methods to fill in some missing characteristics of people and dwellings.Data quality for 2018 Census provides more information on the quality of the 2018 Census data.An independent panel of experts has assessed the quality of the 2018 Census dataset. The panel has endorsed Stats NZ’s overall methods and concluded that the use of government administrative records has improved the coverage of key variables such as age, sex, ethnicity, and place. The panel’s Initial Report of the 2018 Census External Data Quality Panel (September 2019), assessed the methodologies used by Stats NZ to produce the final dataset, as well as the quality of some of the key variables. Its second report 2018 Census External Data Quality Panel: Assessment of variables (December 2019) assessed an additional 31 variables. In its third report, Final report of the 2018 Census External Data Quality Panel (February 2020), the panel made 24 recommendations, several relating to preparations for the 2023 Census. Along with this report, the panel, supported by Stats NZ, produced a series of graphs summarising the sources of data for key 2018 Census individual variables, 2018 Census External Data Quality Panel: Data sources for key 2018 Census individual variables.The Quick guide to the 2018 Census outlines the key changes we introduced as we prepared for the 2018 Census, and the changes we made once collection was complete.The geographic boundaries are as at 1 January 2018. See Statistical standard for geographic areas 2018.2018 Census – DataInfo+ provides information about methods, and related metadata.Data quality ratings for 2018 Census variables provides information on data quality ratings.