38 datasets found
  1. N

    New Zealand Population: South Island (SI)

    • ceicdata.com
    Updated Oct 15, 2025
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    CEICdata.com (2025). New Zealand Population: South Island (SI) [Dataset]. https://www.ceicdata.com/en/new-zealand/population-by-region/population-south-island-si
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    Dataset updated
    Oct 15, 2025
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jun 1, 2013 - Jun 1, 2024
    Area covered
    New Zealand
    Variables measured
    Population
    Description

    New Zealand Population: South Island (SI) data was reported at 1,242,300.000 Person in 2024. This records an increase from the previous number of 1,226,100.000 Person for 2023. New Zealand Population: South Island (SI) data is updated yearly, averaging 1,033,700.000 Person from Jun 1996 (Median) to 2024, with 29 observations. The data reached an all-time high of 1,242,300.000 Person in 2024 and a record low of 921,100.000 Person in 1996. New Zealand Population: South Island (SI) data remains active status in CEIC and is reported by Stats NZ. The data is categorized under Global Database’s New Zealand – Table NZ.G005: Population: by Region.

  2. N

    New Zealand Population: North Island (NI)

    • ceicdata.com
    Updated Oct 15, 2025
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    CEICdata.com (2025). New Zealand Population: North Island (NI) [Dataset]. https://www.ceicdata.com/en/new-zealand/population-by-region/population-north-island-ni
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    Dataset updated
    Oct 15, 2025
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jun 1, 2013 - Jun 1, 2024
    Area covered
    New Zealand
    Variables measured
    Population
    Description

    New Zealand Population: North Island (NI) data was reported at 4,044,600.000 Person in 2024. This records an increase from the previous number of 3,973,400.000 Person for 2023. New Zealand Population: North Island (NI) data is updated yearly, averaging 3,311,700.000 Person from Jun 1996 (Median) to 2024, with 29 observations. The data reached an all-time high of 4,044,600.000 Person in 2024 and a record low of 2,810,100.000 Person in 1996. New Zealand Population: North Island (NI) data remains active status in CEIC and is reported by Stats NZ. The data is categorized under Global Database’s New Zealand – Table NZ.G005: Population: by Region.

  3. Suburb Locality - Major Name

    • geodata.nz
    • data.linz.govt.nz
    Updated Jun 19, 2023
    + more versions
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    Toitū Te Whenua Land Information New Zealand (2023). Suburb Locality - Major Name [Dataset]. https://geodata.nz/geonetwork/srv/api/records/a4ce8830-bbcd-58f7-faeb-ce03557d88c3
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    Dataset updated
    Jun 19, 2023
    Dataset provided by
    Land Information New Zealandhttps://www.linz.govt.nz/
    Authors
    Toitū Te Whenua Land Information New Zealand
    Area covered
    Description

    The Major Name data table is part of NZ Suburbs and Localities Dataset. Major names describe the wider area in which the boundary is located.

    NZ Suburbs and Localities is an easy to use layer generated from the normalised NZ Suburbs and Localities Dataset. It describes the spatial extent and name of communities in urban areas (suburbs) and rural areas (localities) for navigation and location purposes.

    The suburb and locality boundaries cover New Zealand including North Island, South Island, Stewart Island/Rakiura, Chatham Islands, and nearby offshore islands.

    Each suburb and locality is assigned a name, major name, Territorial Authority and, if appropriate, additional in use names. A population estimate is provided for each suburb and locality by Stats NZ.

    For more information please refer to the NZ Suburbs and Localities Guidance documents:

    Data Dictionary "https://www.linz.govt.nz/products-services/data/types-linz-data/suburbs-and-localities-data">Change Request Process "https://www.linz.govt.nz/products-services/data/types-linz-data/suburbs-and-localities-data">Change Request Principles, Requirements and Rules Changes to NZ Suburbs and Localities can be requested by emailing addresses@linz.govt.nz

  4. Statistical Area 2 2023 (generalised)

    • datafinder.stats.govt.nz
    csv, dwg, geodatabase +6
    Updated Dec 20, 2022
    + more versions
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    Stats NZ (2022). Statistical Area 2 2023 (generalised) [Dataset]. https://datafinder.stats.govt.nz/layer/111227-statistical-area-2-2023-generalised/
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    geodatabase, kml, mapinfo tab, shapefile, dwg, mapinfo mif, pdf, csv, geopackage / sqliteAvailable download formats
    Dataset updated
    Dec 20, 2022
    Dataset provided by
    Statistics New Zealandhttp://www.stats.govt.nz/
    Authors
    Stats NZ
    License

    https://datafinder.stats.govt.nz/license/attribution-4-0-international/https://datafinder.stats.govt.nz/license/attribution-4-0-international/

    Area covered
    Description

    Statistical Area 2 2023 update

    SA2 2023 is the first major update of the geography since it was first created in 2018. The update is to ensure SA2s are relevant and meet criteria before each five-yearly population and dwelling census. SA2 2023 contains 135 new SA2s. Updates were made to reflect real world change of population and dwelling growth mainly in urban areas, and to make some improvements to their delineation of communities of interest.

    Description

    This dataset is the definitive version of the annually released statistical area 2 (SA2) boundaries as at 1 January 2023 as defined by Stats NZ. This version contains 2,395 SA2s (2,379 digitised and 16 with empty or null geometries (non-digitised)).

    SA2 is an output geography that provides higher aggregations of population data than can be provided at the statistical area 1 (SA1) level. The SA2 geography aims to reflect communities that interact together socially and economically. In populated areas, SA2s generally contain similar sized populations.

    The SA2 should:

    form a contiguous cluster of one or more SA1s,

    excluding exceptions below, allow the release of multivariate statistics with minimal data suppression,

    capture a similar type of area, such as a high-density urban area, farmland, wilderness area, and water area,

    be socially homogeneous and capture a community of interest. It may have, for example:

    • a shared road network,
    • shared community facilities,
    • shared historical or social links, or
    • socio-economic similarity,

    form a nested hierarchy with statistical output geographies and administrative boundaries. It must:

    • be built from SA1s,
    • either define or aggregate to define SA3s, urban areas, territorial authorities, and regional councils.

    SA2s in city council areas generally have a population of 2,000–4,000 residents while SA2s in district council areas generally have a population of 1,000–3,000 residents.

    In major urban areas, an SA2 or a group of SA2s often approximates a single suburb. In rural areas, rural settlements are included in their respective SA2 with the surrounding rural area.

    SA2s in urban areas where there is significant business and industrial activity, for example ports, airports, industrial, commercial, and retail areas, often have fewer than 1,000 residents. These SA2s are useful for analysing business demographics, labour markets, and commuting patterns.

    In rural areas, some SA2s have fewer than 1,000 residents because they are in conservation areas or contain sparse populations that cover a large area.

    To minimise suppression of population data, small islands with zero or low populations close to the mainland, and marinas are generally included in their adjacent land-based SA2.

    Zero or nominal population SA2s

    To ensure that the SA2 geography covers all of New Zealand and aligns with New Zealand’s topography and local government boundaries, some SA2s have zero or nominal populations. These include:

    • SA2s where territorial authority boundaries straddle regional council boundaries. These SA2s each have fewer than 200 residents and are: Arahiwi, Tiroa, Rangataiki, Kaimanawa, Taharua, Te More, Ngamatea, Whangamomona, and Mara.
    • SA2s created for single islands or groups of islands that are some distance from the mainland or to separate large unpopulated islands from urban areas
    • SA2s that represent inland water, inlets or oceanic areas including: inland lakes larger than 50 square kilometres, harbours larger than 40 square kilometres, major ports, other non-contiguous inlets and harbours defined by territorial authority, and contiguous oceanic areas defined by regional council.
    • SA2s for non-digitised oceanic areas, offshore oil rigs, islands, and the Ross Dependency. Each SA2 is represented by a single meshblock. The following 16 SA2s are held in non-digitised form (SA2 code; SA2 name):

    400001; New Zealand Economic Zone, 400002; Oceanic Kermadec Islands, 400003; Kermadec Islands, 400004; Oceanic Oil Rig Taranaki, 400005; Oceanic Campbell Island, 400006; Campbell Island, 400007; Oceanic Oil Rig Southland, 400008; Oceanic Auckland Islands, 400009; Auckland Islands, 400010 ; Oceanic Bounty Islands, 400011; Bounty Islands, 400012; Oceanic Snares Islands, 400013; Snares Islands, 400014; Oceanic Antipodes Islands, 400015; Antipodes Islands, 400016; Ross Dependency.

    SA2 numbering and naming

    Each SA2 is a single geographic entity with a name and a numeric code. The name refers to a geographic feature or a recognised place name or suburb. In some instances where place names are the same or very similar, the SA2s are differentiated by their territorial authority name, for example, Gladstone (Carterton District) and Gladstone (Invercargill City).

    SA2 codes have six digits. North Island SA2 codes start with a 1 or 2, South Island SA2 codes start with a 3 and non-digitised SA2 codes start with a 4. They are numbered approximately north to south within their respective territorial authorities. To ensure the north–south code pattern is maintained, the SA2 codes were given 00 for the last two digits when the geography was created in 2018. When SA2 names or boundaries change only the last two digits of the code will change.

    For more information please refer to the Statistical standard for geographic areas 2023.

    Generalised version

    This generalised version has been simplified for rapid drawing and is designed for thematic or web mapping purposes.

    Macrons

    Names are provided with and without tohutō/macrons. The column name for those without macrons is suffixed ‘ascii’.

    Digital data

    Digital boundary data became freely available on 1 July 2007.

    To download geographic classifications in table formats such as CSV please use Ariā

  5. o

    Data from: You can't go home again: Changes in trophic niche following...

    • ourarchive.otago.ac.nz
    Updated Mar 1, 2025
    + more versions
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    Stephen Wing; Lucy Wing; Amandine Sabadel (2025). Data from: You can't go home again: Changes in trophic niche following extinction and recolonization of the New Zealand sea lion [Dataset]. https://ourarchive.otago.ac.nz/esploro/outputs/dataset/Data-from-You-cant-go-home/9926716976301891
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    Dataset updated
    Mar 1, 2025
    Dataset provided by
    Dryad
    Authors
    Stephen Wing; Lucy Wing; Amandine Sabadel
    Time period covered
    Mar 1, 2025
    Area covered
    New Zealand
    Dataset funded by
    Royal Society Te Apārangi (New Zealand, Wellington)
    Description

    Recolonization or range expansion of large marine predators can be facilitated by reestablishing formally important trophic linkages within intact coastal marine food webs. We analyzed long-term changes in the structure of coastal marine food webs supporting remnant and recolonizing populations of New Zealand sea lions (Phocarctos hookeri), an apex marine predator, using trophic position and a mixture of alternate sources of organic matter as metrics for their resource niche. We measured both d¹³C, d¹⁵N, and d¹⁵NAA of amino acids in the collagen of archived prehistoric bone samples and modern bone, muscle, and fur samples. Using the resulting isotopic values we calculated individual-based estimates of trophic position and basal organic matter source use from pelagic and benthic habitats, phytoplankton versus macroalgae, in the underlying food webs supporting sea lions from the Auckland Islands, Stewart Island, Southland, and Otago among discrete time periods dating to the first human settlements in New Zealand. The data resolved significant changes in the trophic position of New Zealand sea lions since the first arrivals of Māori in New Zealand (ca 1250-1450 CE), the advent of European whaling and sealing (ca 1650 -1850 CE) when sea lions were extirpated from the South Island, and expansion of industrialized fishing (ca 1950 -present CE) indicating a vastly altered resource landscape for recolonizing populations on the South Island. New Zealand is the last major land mass to be settled by people therefore the patterns we observe comprise the complete time course of human influences on the marine ecosystem. These patterns provide a unique understanding of how long-term changes in coastal marine food webs influence the trophic position and population recovery of apex predators.

  6. Statistical Area 2 2025

    • datafinder.stats.govt.nz
    csv, dwg, geodatabase +6
    Updated Aug 8, 2025
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    Stats NZ (2025). Statistical Area 2 2025 [Dataset]. https://datafinder.stats.govt.nz/layer/120978-statistical-area-2-2025/
    Explore at:
    pdf, csv, kml, mapinfo tab, shapefile, geopackage / sqlite, geodatabase, dwg, mapinfo mifAvailable download formats
    Dataset updated
    Aug 8, 2025
    Dataset provided by
    Statistics New Zealandhttp://www.stats.govt.nz/
    Authors
    Stats NZ
    License

    https://datafinder.stats.govt.nz/license/attribution-4-0-international/https://datafinder.stats.govt.nz/license/attribution-4-0-international/

    Area covered
    Description

    Refer to the 'Current Geographic Boundaries Table' layer for a list of all current geographies and recent updates.

    This dataset is the definitive version of the annually released statistical area 2 (SA2) boundaries as at 1 January 2025 as defined by Stats NZ. This version contains 2,395 SA2s (2,379 digitised and 16 with empty or null geometries (non-digitised)).

    SA2 is an output geography that provides higher aggregations of population data than can be provided at the statistical area 1 (SA1) level. The SA2 geography aims to reflect communities that interact together socially and economically. In populated areas, SA2s generally contain similar sized populations.

    The SA2 should:

    form a contiguous cluster of one or more SA1s,

    excluding exceptions below, allow the release of multivariate statistics with minimal data suppression,

    capture a similar type of area, such as a high-density urban area, farmland, wilderness area, and water area,

    be socially homogeneous and capture a community of interest. It may have, for example:

    • a shared road network,
    • shared community facilities,
    • shared historical or social links, or
    • socio-economic similarity,

    form a nested hierarchy with statistical output geographies and administrative boundaries. It must:

    • be built from SA1s,
    • either define or aggregate to define SA3s, urban areas, territorial authorities, and regional councils.

    SA2s in city council areas generally have a population of 2,000–4,000 residents while SA2s in district council areas generally have a population of 1,000–3,000 residents.

    In major urban areas, an SA2 or a group of SA2s often approximates a single suburb. In rural areas, rural settlements are included in their respective SA2 with the surrounding rural area.

    SA2s in urban areas where there is significant business and industrial activity, for example ports, airports, industrial, commercial, and retail areas, often have fewer than 1,000 residents. These SA2s are useful for analysing business demographics, labour markets, and commuting patterns.

    In rural areas, some SA2s have fewer than 1,000 residents because they are in conservation areas or contain sparse populations that cover a large area.

    To minimise suppression of population data, small islands with zero or low populations close to the mainland, and marinas are generally included in their adjacent land-based SA2.

    Zero or nominal population SA2s

    To ensure that the SA2 geography covers all of New Zealand and aligns with New Zealand’s topography and local government boundaries, some SA2s have zero or nominal populations. These include:

    • SA2s where territorial authority boundaries straddle regional council boundaries. These SA2s each have fewer than 200 residents and are: Arahiwi, Tiroa, Rangataiki, Kaimanawa, Taharua, Te More, Ngamatea, Whangamomona, and Mara.
    • SA2s created for single islands or groups of islands that are some distance from the mainland or to separate large unpopulated islands from urban areas
    • SA2s that represent inland water, inlets or oceanic areas including: inland lakes larger than 50 square kilometres, harbours larger than 40 square kilometres, major ports, other non-contiguous inlets and harbours defined by territorial authority, and contiguous oceanic areas defined by regional council.
    • SA2s for non-digitised oceanic areas, offshore oil rigs, islands, and the Ross Dependency. Each SA2 is represented by a single meshblock. The following 16 SA2s are held in non-digitised form (SA2 code; SA2 name):

    400001; New Zealand Economic Zone, 400002; Oceanic Kermadec Islands, 400003; Kermadec Islands, 400004; Oceanic Oil Rig Taranaki, 400005; Oceanic Campbell Island, 400006; Campbell Island, 400007; Oceanic Oil Rig Southland, 400008; Oceanic Auckland Islands, 400009; Auckland Islands, 400010 ; Oceanic Bounty Islands, 400011; Bounty Islands, 400012; Oceanic Snares Islands, 400013; Snares Islands, 400014; Oceanic Antipodes Islands, 400015; Antipodes Islands, 400016; Ross Dependency.

    SA2 numbering and naming

    Each SA2 is a single geographic entity with a name and a numeric code. The name refers to a geographic feature or a recognised place name or suburb. In some instances where place names are the same or very similar, the SA2s are differentiated by their territorial authority name, for example, Gladstone (Carterton District) and Gladstone (Invercargill City).

    SA2 codes have six digits. North Island SA2 codes start with a 1 or 2, South Island SA2 codes start with a 3 and non-digitised SA2 codes start with a 4. They are numbered approximately north to south within their respective territorial authorities. To ensure the north–south code pattern is maintained, the SA2 codes were given 00 for the last two digits when the geography was created in 2018. When SA2 names or boundaries change only the last two digits of the code will change.

    High-definition version

    This high definition (HD) version is the most detailed geometry, suitable for use in GIS for geometric analysis operations and for the computation of areas, centroids and other metrics. The HD version is aligned to the LINZ cadastre.

    Macrons

    Names are provided with and without tohutō/macrons. The column name for those without macrons is suffixed ‘ascii’.

    Digital data

    Digital boundary data became freely available on 1 July 2007.

    Further information

    To download geographic classifications in table formats such as CSV please use Ariā

    For more information please refer to the Statistical standard for geographic areas 2023.

    Contact: geography@stats.govt.nz

  7. n

    Data from: Population structure within an alpine archipelago: strong...

    • data-staging.niaid.nih.gov
    • datasetcatalog.nlm.nih.gov
    • +2more
    zip
    Updated Aug 18, 2015
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    Kerry A. Weston; B. C. Robertson (2015). Population structure within an alpine archipelago: strong signature of past climate change in the New Zealand rock wren (Xenicus gilviventris) [Dataset]. http://doi.org/10.5061/dryad.g44c1
    Explore at:
    zipAvailable download formats
    Dataset updated
    Aug 18, 2015
    Dataset provided by
    University of Otago
    Authors
    Kerry A. Weston; B. C. Robertson
    License

    https://spdx.org/licenses/CC0-1.0.htmlhttps://spdx.org/licenses/CC0-1.0.html

    Area covered
    Te Waipounamu / South Island, New Zealand, New Zealand, Te Waipounamu / South Island, New Zealand, Te Waipounamu / South Island
    Description

    Naturally subdivided populations such as those occupying high-altitude habitat patches of the ‘alpine archipelago’ can provide significant insight into past biogeographical change and serve as useful models for predicting future responses to anthropogenic climate change. Among New Zealand's alpine taxa, phylogenetic studies support two major radiations: the first correlating with geological forces (Pliocene uplift) and the second with climatic processes (Pleistocene glaciations). The rock wren (Xenicus gilviventris) is a threatened alpine passerine belonging to the endemic New Zealand wren family (Acanthisittidae). Rock wren constitute a widespread, naturally fragmented population, occurring in patches of suitable habitat over c. 900 m in altitude throughout the length of the South Island, New Zealand. We investigated the relative role of historical geological versus climatic processes in shaping the genetic structure of rock wren (N = 134) throughout their range. Using microsatellites combined with nuclear and mtDNA sequence data, we identify a deep north–south divergence in rock wren (3.7 ± 0.5% at cytochrome b) consistent with the glacial refugia hypothesis whereby populations were restricted in isolated refugia during the Pleistocene c. 2 Ma. This is the first study of an alpine vertebrate to test and provide strong evidence for the glacial refugia hypothesis as an explanation for the low endemicity central zone known as the biotic ‘gap’ in the South Island of New Zealand.

  8. 新西兰 人口:South Island (SI)

    • ceicdata.com
    Updated Oct 15, 2025
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    CEICdata.com (2025). 新西兰 人口:South Island (SI) [Dataset]. https://www.ceicdata.com/zh-hans/new-zealand/population-by-region/population-south-island-si
    Explore at:
    Dataset updated
    Oct 15, 2025
    Dataset provided by
    CEICdata.com
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Time period covered
    Jun 1, 2013 - Jun 1, 2024
    Area covered
    新西兰, 新西兰, 南岛
    Variables measured
    Population
    Description

    人口:South Island (SI)在06-01-2024达1,242,300.000人,相较于06-01-2023的1,226,100.000人有所增长。人口:South Island (SI)数据按年更新,06-01-1996至06-01-2024期间平均值为1,033,700.000人,共29份观测结果。该数据的历史最高值出现于06-01-2024,达1,242,300.000人,而历史最低值则出现于06-01-1996,为921,100.000人。CEIC提供的人口:South Island (SI)数据处于定期更新的状态,数据来源于Stats NZ,数据归类于全球数据库的新西兰 – Table NZ.G005: Population: by Region。

  9. Statistical Area 3 2025

    • datafinder.stats.govt.nz
    csv, dwg, geodatabase +6
    Updated Aug 8, 2025
    + more versions
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    Stats NZ (2025). Statistical Area 3 2025 [Dataset]. https://datafinder.stats.govt.nz/layer/120967-statistical-area-3-2025/
    Explore at:
    pdf, geodatabase, mapinfo mif, mapinfo tab, csv, shapefile, geopackage / sqlite, dwg, kmlAvailable download formats
    Dataset updated
    Aug 8, 2025
    Dataset provided by
    Statistics New Zealandhttp://www.stats.govt.nz/
    Authors
    Stats NZ
    License

    https://datafinder.stats.govt.nz/license/attribution-4-0-international/https://datafinder.stats.govt.nz/license/attribution-4-0-international/

    Area covered
    Description

    Refer to the 'Current Geographic Boundaries Table' layer for a list of all current geographies and recent updates.

    This dataset is the definitive version of the annually released statistical area 3 (SA3) boundaries as at 1 January 2025 as defined by Stats NZ. This version contains 929 SA3s, including 4 non-digitised SA3s.

    The SA3 geography aims to meet three purposes:

    1. approximate suburbs in major, large, and medium urban areas,
    2. in predominantly rural areas, provide geographical areas that are larger in area and population size than SA2s but smaller than territorial authorities,
    3. minimise data suppression.

    SA3s in major, large, and medium urban areas were created by combining SA2s to approximate suburbs as delineated in the Fire and Emergency NZ (FENZ) Localities dataset. Some of the resulting SA3s have very large populations.

    Outside of major, large, and medium urban areas, SA3s generally have populations of 5,000–10,000. These SA3s may represent either a single small urban area, a combination of small urban areas and their surrounding rural SA2s, or a combination of rural SA2s.

    Zero or nominal population SA3s

    To minimise the amount of unsuppressed data that can be provided in multivariate statistical tables, SA2s with fewer than 1,000 residents are combined with other SA2s wherever possible to reach the 1,000 SA3 population target. However, there are still a number of SA3s with zero or nominal populations.

    Small population SA2s designed to maintain alignment between territorial authority and regional council geographies are merged with other SA2s to reach the 5,000–10,000 SA3 population target. These merges mean that some SA3s do not align with regional council boundaries but are aligned to territorial authority.

    Small population island SA2s are included in their adjacent land-based SA3.

    Island SA2s outside territorial authority or region are the same in the SA3 geography.

    Inland water SA2s are aggregated and named by territorial authority, as in the urban rural classification.

    Inlet SA2s are aggregated and named by territorial authority or regional council where the water area is outside the territorial authority.

    Oceanic SA2s translate directly to SA3s as they are already aggregated to regional council.

    The 16 non-digitised SA2s are aggregated to the following 4 non-digitised SA3s (SA3 code; SA3 name):

    70001; Oceanic outside region, 70002; Oceanic oil rigs, 70003; Islands outside region, 70004; Ross Dependency outside region.

    SA3 numbering and naming

    Each SA3 is a single geographic entity with a name and a numeric code. The name refers to a suburb, recognised place name, or portion of a territorial authority. In some instances where place names are the same or very similar, the SA3s are differentiated by their territorial authority, for example, Hillcrest (Hamilton City) and Hillcrest (Rotorua District).

    SA3 codes have five digits. North Island SA3 codes start with a 5, South Island SA3 codes start with a 6 and non-digitised SA3 codes start with a 7. They are numbered approximately north to south within their respective territorial authorities. When first created in 2025, the last digit of each code was 0. When SA3 boundaries change in future, only the last digit of the code will change to ensure the north-south pattern is maintained.

    High-definition version

    This high definition (HD) version is the most detailed geometry, suitable for use in GIS for geometric analysis operations and for the computation of areas, centroids and other metrics. The HD version is aligned to the LINZ cadastre.

    Macrons

    Names are provided with and without tohutō/macrons. The column name for those without macrons is suffixed ‘ascii’.

    Digital data

    Digital boundary data became freely available on 1 July 2007

    Further information

    To download geographic classifications in table formats such as CSV please use Ariā

    For more information please refer to the Statistical standard for geographic areas 2023.

    Contact: geography@stats.govt.nz

  10. d

    Data from: Capturing the dynamics of small populations: A retrospective...

    • search.dataone.org
    • data.niaid.nih.gov
    • +1more
    Updated May 6, 2025
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    Doug Armstrong; Elizabeth Parlato; Barbara Egli; Wendy Dimond; Ã…sa Berggren; Mhairi McCready; Kevin Parker; John Ewen (2025). Capturing the dynamics of small populations: A retrospective assessment using long-term data for an island reintroduction [Dataset]. http://doi.org/10.5061/dryad.kkwh70s5f
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    Dataset updated
    May 6, 2025
    Dataset provided by
    Dryad Digital Repository
    Authors
    Doug Armstrong; Elizabeth Parlato; Barbara Egli; Wendy Dimond; Ã…sa Berggren; Mhairi McCready; Kevin Parker; John Ewen
    Time period covered
    Sep 16, 2021
    Description
    1. The art of population modelling is to incorporate factors essential for capturing a population’s dynamics while otherwise keeping the model as simple as possible. However, it is unclear how optimal model complexity should be assessed, and whether this optimal complexity has been affected by recent advances in modelling methodology. This issue is particularly relevant to small populations because they are subject to complex dynamics but inferences about those dynamics are often constrained by small sample sizes.

    2. We fitted Bayesian hierarchical models to long-term data on vital rates (survival and reproduction) for the toutouwai (Petroica longipes) population reintroduced to Tiritiri Matangi, a 220-ha New Zealand island, and quantified the performance of those models in terms of their likelihood of replicating the observed population dynamics. These dynamics consisted of overall growth from 33 (± 0.3) to 160 (± 6) birds from 1992–2018, including recoveries following five harvest ...

  11. Sheep livestock numbers in New Zealand 2014-2024

    • statista.com
    Updated Jun 23, 2025
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    Statista (2025). Sheep livestock numbers in New Zealand 2014-2024 [Dataset]. https://www.statista.com/statistics/974492/new-zealand-sheep-livestock-numbers/
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    Dataset updated
    Jun 23, 2025
    Dataset authored and provided by
    Statistahttp://statista.com/
    Area covered
    New Zealand
    Description

    As of June 2024, there were approximately ***** million sheep in New Zealand, a slight decrease from the previous year in which there were around ***** million sheep in the country. The number of sheep in the country has declined over the past decade.  Sheep farming New Zealand was once known for its disproportionate number of sheep per population. However, since the 1970s, the country’s sheep population has fallen drastically. A major factor that has contributed to this decline is sheep farming land lost to other purposes such as urban sprawl, dairy farming, and horticulture farming. The number of lamb livestock has similarly seen a decline. Consumption and exports Sheep in New Zealand are bred for wool and meat, including mutton and lamb. New Zealand is a significant player in the global wool market. The country exports strong wool to leading textile manufacturers around the world. However, along with sheep numbers, wool production has decreased significantly across New Zealand. In terms of domestic meat consumption, the per capita consumption of sheep meat in New Zealand was forecast to decline into the next decade. When looking at trade, the leading country for sheep meat exports from New Zealand was China, with the United Kingdom and the United States trailing behind.

  12. Urban Rural 2023 (generalised)

    • datafinder.stats.govt.nz
    csv, dwg, geodatabase +6
    Updated Nov 30, 2022
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    Stats NZ (2022). Urban Rural 2023 (generalised) [Dataset]. https://datafinder.stats.govt.nz/layer/111198-urban-rural-2023-generalised/
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    mapinfo mif, geopackage / sqlite, dwg, mapinfo tab, shapefile, kml, geodatabase, csv, pdfAvailable download formats
    Dataset updated
    Nov 30, 2022
    Dataset provided by
    Statistics New Zealandhttp://www.stats.govt.nz/
    Authors
    Stats NZ
    License

    https://datafinder.stats.govt.nz/license/attribution-4-0-international/https://datafinder.stats.govt.nz/license/attribution-4-0-international/

    Area covered
    Description

    Urban rural 2023 update

    UR 2023 is the first major update of the geography since it was first created in 2018. The update is to ensure UR geographies are relevant and meet criteria before each five-yearly population and dwelling census. UR 2023 contains 13 new rural settlements and 7 new small urban areas. Updates were made to reflect real world change including new subdivisions and motorways, and to improve delineation of urban areas and rural settlements. The Wānaka urban area, whose population has grown to be more than 10,000 based on population estimates, has been reclassified to a medium urban area in the 2023 urban rural indicator.

    In the 2023 classification there are:

    • 7 major urban areas
    • 13 large urban areas
    • 23 medium urban areas
    • 152 small urban areas
    • 402 rural settlements.

    This dataset is the definitive version of the annually released urban rural (UR) boundaries as at 1 January 2023 as defined by Stats NZ. This version contains 745 UR areas, including 195 urban areas and 402 rural settlements.

    Urban rural (UR) is an output geography that classifies New Zealand into areas that share common urban or rural characteristics and is used to disseminate a broad range of Stats NZ’s social, demographic and economic statistics.

    The UR separately identifies urban areas, rural settlements, other rural areas, and water areas. Urban areas and rural settlements are form-based geographies delineated by the inspection of aerial imagery, local government land designations on district plan maps, address registers, property title data, and any other available information. However, because the underlying meshblock pattern is used to define the geographies, boundaries may not align exactly with local government land designations or what can be seen in aerial images. Other rural areas, and bodies of water represent areas not included within an urban area.

    Urban areas are built from the statistical area 2 (SA2) geography, while rural and water areas are built from the statistical area 1 (SA1) geography.

    Non-digitised

    The following 4 non-digitised UR areas have been aggregated from the 16 non-digitised meshblocks/SA2s.

    6901; Oceanic outside region, 6902; Oceanic oil rigs, 6903; Islands outside region, 6904; Ross Dependency outside region.

    UR numbering and naming

    Each urban area and rural settlement is a single geographic entity with a name and a numeric code.

    Other rural areas, inland water areas, and inlets are defined by territorial authority; oceanic areas are defined by regional council; and each have a name and a numeric code.

    Urban rural codes have four digits. North Island locations start with a 1, South Island codes start with a 2, oceanic codes start with a 6 and non-digitised codes start with 69.

    Urban rural indicator (IUR)

    The accompanying urban rural indicator (IUR) classifies the urban, rural, and water areas by type. Urban areas are further classified by the size of their estimated resident population:

    • major urban area – 100,000 or more residents,
    • large urban area – 30,000–99,999 residents,
    • medium urban area – 10,000–29,999 residents,
    • small urban area – 1,000–9,999 residents.

    This was based on 2018 Census data and 2021 population estimates. Their IUR status (urban area size/rural settlement) may change if the 2023 Census population count moves them up or down a category.

    The indicators, by name, with their codes in brackets, are:

    urban area – major urban (11), large urban (12), medium urban (13), small urban (14),

    rural area – rural settlement (21), rural other (22),

    water – inland water (31), inlet (32), oceanic (33).

    The urban rural indicator complements the urban rural geography and is an attribute in this dataset. Further information on the urban rural indicator is available on the Stats NZ classification and coding tool ARIA.

    For more information please refer to the Statistical standard for geographic areas 2023.

    Generalised version

    This generalised version has been simplified for rapid drawing and is designed for thematic or web mapping purposes.

    Macrons

    Names are provided with and without tohutō/macrons. The column name for those without macrons is suffixed ‘ascii’.

    Digital data

    Digital boundary data became freely available on 1 July 2007.

    To download geographic classifications in table formats such as CSV please use Ariā

  13. n

    Data from: Broad-scale genetic patterns of New Zealand abalone, Haliotis...

    • data.niaid.nih.gov
    • datadryad.org
    zip
    Updated Jun 3, 2016
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    Margaret Will; Tom McCowan; Neil J. Gemmell (2016). Broad-scale genetic patterns of New Zealand abalone, Haliotis iris, across a distribution spanning 13° latitude and major oceanic water masses [Dataset]. http://doi.org/10.5061/dryad.575p1
    Explore at:
    zipAvailable download formats
    Dataset updated
    Jun 3, 2016
    Dataset provided by
    University of Otago
    Authors
    Margaret Will; Tom McCowan; Neil J. Gemmell
    License

    https://spdx.org/licenses/CC0-1.0.htmlhttps://spdx.org/licenses/CC0-1.0.html

    Area covered
    New Zealand
    Description

    The New Zealand black-foot abalone, Haliotis iris, or pāua, is endemic to the rocky reefs surrounding New Zealand, whose main land mass spans 13° of latitude and separates the Tasman Sea from the Pacific Ocean. In this study, we examined the population genetic structure of this important commercial, cultural and recreational species by genotyping nine microsatellite loci in 485 pāua from 27 locations distributed across mainland New Zealand and the Chatham Islands. We found low, but significant, levels of genetic differentiation. Key genetic breaks were identified among the Chatham Islands and mainland samples; patterns that are strongly corroborated by prior work employing mtDNA sequences. AMOVAs indicated that samples from the south of the North Island were more similar to the South Island samples than to other North Island samples, however multivariate analysis and Bayesian clustering could not identify a significant pattern. Differentiation between the Chatham Islands and the mainland is most likely due to isolation by distance, while differentiation of North Island samples corresponds with major components of New Zealand’s oceanography, Cook Strait and the East Cape. Despite intense fishing pressure, we detected no signature of genetic bottlenecks in any region suggesting that population sizes have remained relatively stable over recent time or that the census size of this species is much larger than its effective population size.

  14. NZ Suburbs and Localities

    • data.linz.govt.nz
    • geodata.nz
    csv, dwg, geodatabase +6
    Updated Jun 16, 2023
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    Land Information New Zealand (2023). NZ Suburbs and Localities [Dataset]. https://data.linz.govt.nz/layer/113764-nz-suburbs-and-localities/
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    geopackage / sqlite, dwg, kml, mapinfo tab, csv, pdf, shapefile, mapinfo mif, geodatabaseAvailable download formats
    Dataset updated
    Jun 16, 2023
    Dataset authored and provided by
    Land Information New Zealandhttps://www.linz.govt.nz/
    License

    https://data.linz.govt.nz/license/attribution-4-0-international/https://data.linz.govt.nz/license/attribution-4-0-international/

    Area covered
    New Zealand,
    Description

    NZ Suburbs and Localities describes the spatial extent and name of communities in urban areas (suburbs) and rural areas (localities) for navigation and location purposes.

    The suburb and locality boundaries cover New Zealand including North Island, South Island, Stewart Island/Rakiura, Chatham Islands, and nearby offshore islands.

    Each suburb and locality is assigned a name, major name, Territorial Authority and, if appropriate, additional in use names. A population estimate is provided for each suburb and locality by Stats NZ.

    For more information please refer to the NZ Suburbs and Localities Data Dictionary and the LINZ Website

    Changes to NZ Suburbs and Localities can be requested by emailing addresses@linz.govt.nz

    Change Request Guidance Documents: - Change Request Process - Change Request Principles, Requirements and Rules

    APIs and web services

    This dataset is available via ArcGIS Online and ArcGIS REST services, as well as our standard APIs. LDS APIs and OGC web services ArcGIS Online map services

  15. f

    Data from: Phylogeographic structure and historical demography of tarakihi...

    • tandf.figshare.com
    • datasetcatalog.nlm.nih.gov
    xlsx
    Updated Jun 1, 2023
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    Yvan Papa; Alexander G. Halliwell; Mark A. Morrison; Maren Wellenreuther; Peter A. Ritchie (2023). Phylogeographic structure and historical demography of tarakihi (Nemadactylus macropterus) and king tarakihi (Nemadactylus n.sp.) in New Zealand [Dataset]. http://doi.org/10.6084/m9.figshare.14386509.v1
    Explore at:
    xlsxAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    Taylor & Francis
    Authors
    Yvan Papa; Alexander G. Halliwell; Mark A. Morrison; Maren Wellenreuther; Peter A. Ritchie
    License

    Attribution-NonCommercial-NoDerivs 4.0 (CC BY-NC-ND 4.0)https://creativecommons.org/licenses/by-nc-nd/4.0/
    License information was derived automatically

    Area covered
    New Zealand
    Description

    Tarakihi (Nemadactylus macropterus) is a demersal fish that supports valuable commercial, recreational, and customary fisheries in New Zealand. However, little is known about its stock structure. The population genetic structure, genetic diversity, and demographic history of N. macropterus were investigated using the hypervariable region one of the mitochondrial control region. 370 samples from 14 locations around New Zealand were collected. While weak genetic breaks were detected between Hawke’s Bay and East Northland and between the west and east coasts of South Island, no clear genetic structure was detected for the overall New Zealand area (ФST = 0.002, P = 0.18), indicative of a panmictic genetic structure. N. macropterus display a high level of genetic diversity and appear to have a historically large and stable population with a long evolutionary history. Bayesian skyline analysis indicates that the historic population has gone through two expansions, likely caused by repeated glacial cycles during the second half of the Pleistocene. The addition of 15 king tarakihi samples (Nemadactylus n.sp.) collected from the Three Kings Islands showed a clear genetic differentiation between the two morphotypes. These findings can inform the future management of N. macropterus and N. n.sp. to ensure a sustainable harvest.

  16. k

    Population Ranking

    • datasource.kapsarc.org
    Updated Nov 7, 2025
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    (2025). Population Ranking [Dataset]. https://datasource.kapsarc.org/explore/dataset/worldbank-population/
    Explore at:
    Dataset updated
    Nov 7, 2025
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    Explore the World Bank Population dataset to access rankings and insights on global population statistics. Click here for extensive data on various countries.

    Rankings

    Afghanistan, Albania, Algeria, Andorra, Angola, Antigua and Barbuda, Argentina, Armenia, Australia, Austria, Azerbaijan, Bahamas, Bahrain, Bangladesh, Barbados, Belarus, Belgium, Belize, Benin, Bhutan, Bolivia, Bosnia and Herzegovina, Botswana, Brazil, Brunei, Bulgaria, Burkina Faso, Burundi, Cabo Verde, Cambodia, Cameroon, Canada, Central African Republic, Chad, Chile, China, Colombia, Comoros, Congo, Costa Rica, Croatia, Cuba, Cyprus, Denmark, Djibouti, Dominica, Dominican Republic, Ecuador, Egypt, El Salvador, Equatorial Guinea, Eritrea, Estonia, Eswatini, Ethiopia, Fiji, Finland, France, Gabon, Gambia, Georgia, Germany, Ghana, Greece, Grenada, Guatemala, Guinea, Guinea-Bissau, Guyana, Haiti, Honduras, Hungary, Iceland, India, Indonesia, Iran, Iraq, Ireland, Israel, Italy, Jamaica, Japan, Jordan, Kazakhstan, Kenya, Kiribati, Kuwait, Latvia, Lebanon, Lesotho, Liberia, Libya, Liechtenstein, Lithuania, Luxembourg, Madagascar, Malawi, Malaysia, Maldives, Mali, Malta, Marshall Islands, Mauritania, Mauritius, Mexico, Micronesia, Moldova, Monaco, Mongolia, Montenegro, Morocco, Mozambique, Myanmar, Namibia, Nauru, Nepal, Netherlands, New Zealand, Nicaragua, Niger, Nigeria, North Macedonia, Norway, Oman, Pakistan, Palau, Panama, Papua New Guinea, Paraguay, Peru, Philippines, Poland, Portugal, Qatar, Romania, Russia, Rwanda, Samoa, San Marino, Saudi Arabia, Senegal, Serbia, Seychelles, Sierra Leone, Singapore, Slovenia, Solomon Islands, Somalia, South Africa, South Sudan, Spain, Sri Lanka, Sudan, Suriname, Sweden, Switzerland, Syria, Tajikistan, Tanzania, Thailand, Timor-Leste, Togo, Tonga, Trinidad and Tobago, Tunisia, Turkmenistan, Tuvalu, Uganda, Ukraine, United Arab Emirates, United Kingdom, Uruguay, Uzbekistan, Vanuatu, Venezuela, Vietnam, Yemen, Zambia, ZimbabweFollow data.kapsarc.org for timely data to advance energy economics research..

  17. d

    Data for: Density dependence and spatial heterogeneity limit the population...

    • datadryad.org
    • search.dataone.org
    zip
    Updated Jun 22, 2021
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    Rowan Sprague; Philip Hulme; Elena Moltchanova; William Godsoe (2021). Data for: Density dependence and spatial heterogeneity limit the population growth rate of invasive pines at the landscape scale [Dataset]. http://doi.org/10.5061/dryad.wstqjq2mm
    Explore at:
    zipAvailable download formats
    Dataset updated
    Jun 22, 2021
    Dataset provided by
    Dryad
    Authors
    Rowan Sprague; Philip Hulme; Elena Moltchanova; William Godsoe
    Time period covered
    Jun 17, 2021
    Description

    We gathered imagery from eight invasion sites across the South Island of New Zealand for multiple time steps (2-4 points in time) using a combination of high resolution aerial imagery gathered from the Land Information New Zealand (LINZ) archives and high resolution satellite imagery downloaded from Google Earth. To detect the pine trees, we used an unsupervised, pixel-based classification method. First, we thresholded the imagery to separate out the dark-coloured trees against the light-coloured background vegetation (Ke and Quackenbush 2011). Then we segmented the pixels identified as trees using a process called watershedding in order to delineate the tree canopies (Komura et al. 2004, Wang et al. 2004, Deng et al. 2016). We extracted the centre point of each polygon identified as a tree, and for each site and time step, we generated a file of the point locations of every tree detected. To prepare the data derived from the image classification and detection m...

  18. f

    Data from: Phylogeography of the endemic New Zealand tree Entelea...

    • tandf.figshare.com
    • datasetcatalog.nlm.nih.gov
    docx
    Updated May 30, 2023
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    Lara D. Shepherd; Jonathan Frericks; Patrick J. Biggs; Peter J. de Lange (2023). Phylogeography of the endemic New Zealand tree Entelea arborescens (whau; Malvaceae) [Dataset]. http://doi.org/10.6084/m9.figshare.7770656.v1
    Explore at:
    docxAvailable download formats
    Dataset updated
    May 30, 2023
    Dataset provided by
    Taylor & Francis
    Authors
    Lara D. Shepherd; Jonathan Frericks; Patrick J. Biggs; Peter J. de Lange
    License

    Attribution-NonCommercial-NoDerivs 4.0 (CC BY-NC-ND 4.0)https://creativecommons.org/licenses/by-nc-nd/4.0/
    License information was derived automatically

    Area covered
    New Zealand
    Description

    We investigated the phylogeography of the New Zealand endemic monotypic coastal tree Entelea arborescens (whau; Malvaceae). The distribution of whau in the southern North Island and South Island has been suggested to result from pre-European Māori cultivation. Whau wood is extremely buoyant and was used to make fishing floats and rafts. We sequenced two chloroplast loci and the nuclear ITS region and genotyped nine microsatellite loci from samples collected across the species’ range. The different genetic markers produced concordant results and revealed two principal genetic clusters, which were estimated to have diverged during the Pleistocene. The distribution of these clusters shows an east–west split across the northern North Island, which does not correspond to the phylogeographic patterns observed to date for other New Zealand coastal plant species and is difficult to reconcile with any known geological or environmental events. Both clusters were represented in the putative translocated populations indicating that these southern populations had multiple origins. However, the wide distribution of these genetic clusters prevents determination of the source of these southern populations and a natural origin cannot be excluded.

  19. Phylogeographic Structure in Penguin Ticks across an Ocean Basin Indicates...

    • plos.figshare.com
    tiff
    Updated Jun 1, 2023
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    Katherine L. Moon; Sam C. Banks; Ceridwen I. Fraser (2023). Phylogeographic Structure in Penguin Ticks across an Ocean Basin Indicates Allopatric Divergence and Rare Trans-Oceanic Dispersal [Dataset]. http://doi.org/10.1371/journal.pone.0128514
    Explore at:
    tiffAvailable download formats
    Dataset updated
    Jun 1, 2023
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Katherine L. Moon; Sam C. Banks; Ceridwen I. Fraser
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Description

    The association of ticks (Acarina) and seabirds provides an intriguing system for assessing the influence of long-distance dispersal on the evolution of parasitic species. Recent research has focused on host-parasite evolutionary relationships and dispersal capacity of ticks parasitising flighted seabirds. Evolutionary research on the ticks of non-flighted seabirds is, in contrast, scarce. We conducted the first phylogeographic investigation of a hard tick species (Ixodes eudyptidis) that parasitises the Little Blue Penguin (Eudyptula minor). Using one nuclear (28S) and two mitochondrial (COI and 16S) markers, we assessed genetic diversity among several populations in Australia and a single population on the South Island of New Zealand. Our results reveal two deeply divergent lineages, possibly representing different species: one comprising all New Zealand samples and some from Australia, and the other representing all other samples from Australian sites. No significant population differentiation was observed among any Australian sites from within each major clade, even those separated by hundreds of kilometres of coastline. In contrast, the New Zealand population was significantly different to all samples from Australia. Our phylogenetic results suggest that the New Zealand and Australian populations are effectively isolated from each other; although rare long-distance dispersal events must occur, these are insufficient to maintain trans-Tasman gene flow. Despite the evidence for limited dispersal of penguin ticks between Australia and New Zealand, we found no evidence to suggest that ticks are unable to disperse shorter distances at sea with their hosts, with no pattern of population differentiation found among Australian sites. Our results suggest that terrestrial seabird parasites may be quite capable of short-distance movements, but only sporadic longer-distance (trans-oceanic) dispersal.

  20. Aotearoa|New Zealand coastal Diptera surveys

    • figshare.com
    xlsx
    Updated Mar 28, 2023
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    Rebecca Le Grice; Gregory Holwell; Darren Ward (2023). Aotearoa|New Zealand coastal Diptera surveys [Dataset]. http://doi.org/10.6084/m9.figshare.14897466.v1
    Explore at:
    xlsxAvailable download formats
    Dataset updated
    Mar 28, 2023
    Dataset provided by
    figshare
    Figsharehttp://figshare.com/
    Authors
    Rebecca Le Grice; Gregory Holwell; Darren Ward
    License

    Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
    License information was derived automatically

    Area covered
    New Zealand
    Description

    These datasets provide a record of Diptera found around the coast of Aotearoa|New Zealand.A total of 257 species or morphospecies were identified in total from surveys of both the overall coastal communities and wrack communities.The data also includes information on the ecology, geography, and general conditions present at each collection site. See methods below and ReadMe file (including ReadMe tabs provided within each spreadsheet) for more detailed information.Methods:

    We surveyed 109 coastal sites distributed around Aotearoa|New Zealand’s three main islands, with 59 sites in the North Island, 47 sites in the South Island, and three sites on Rakiura|Stewart Island. Each site was visited once and sampling trips were made over a three-year period from 2017 – 2019 during the months October – April.

    Wrack community surveys

    At sites where wrack was present (n = 79 sites) we carried out standardised collections of the Diptera present on and/or within wrack. For each wrack sample we placed a clear plastic bucket (22cm (L) x 22cm (W) x 23cm (D)) over patches of wrack and held the bucket in place for two minutes to allow time for any flies within the wrack to emerge and move up into the bucket. At each site with wrack we collected ten samples a minimum of 1m apart, with the exception of five sites. At two of these sites we collected 12 samples to ensure we had fully captured the variation in the wrack population present, and at three sites we collected fewer than the ten samples due to lack of wrack for repeat sampling.

    Overall coastal community surveys

    We also carried out standardised hand collection surveys at all sites. At each site we spent one hour searching the entire local coastal environment. This area was bounded by the supralittoral zone and current waterline. The searching technique included spending focussed time in all of these different microhabitats to collect as many different species as possible.

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CEICdata.com (2025). New Zealand Population: South Island (SI) [Dataset]. https://www.ceicdata.com/en/new-zealand/population-by-region/population-south-island-si

New Zealand Population: South Island (SI)

Explore at:
Dataset updated
Oct 15, 2025
Dataset provided by
CEICdata.com
License

Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically

Time period covered
Jun 1, 2013 - Jun 1, 2024
Area covered
New Zealand
Variables measured
Population
Description

New Zealand Population: South Island (SI) data was reported at 1,242,300.000 Person in 2024. This records an increase from the previous number of 1,226,100.000 Person for 2023. New Zealand Population: South Island (SI) data is updated yearly, averaging 1,033,700.000 Person from Jun 1996 (Median) to 2024, with 29 observations. The data reached an all-time high of 1,242,300.000 Person in 2024 and a record low of 921,100.000 Person in 1996. New Zealand Population: South Island (SI) data remains active status in CEIC and is reported by Stats NZ. The data is categorized under Global Database’s New Zealand – Table NZ.G005: Population: by Region.

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