21 datasets found
  1. l

    Revised extent of wetlands in New Zealand - Dataset - DataStore

    • datastore.landcareresearch.co.nz
    Updated Apr 4, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    (2023). Revised extent of wetlands in New Zealand - Dataset - DataStore [Dataset]. https://datastore.landcareresearch.co.nz/dataset/revised-extent-of-wetlands-in-new-zealand
    Explore at:
    Dataset updated
    Apr 4, 2023
    License

    Attribution-NonCommercial-ShareAlike 4.0 (CC BY-NC-SA 4.0)https://creativecommons.org/licenses/by-nc-sa/4.0/
    License information was derived automatically

    Area covered
    New Zealand
    Description

    Wetlands are highly valued and significant ecosystems with a large range of services and functions. To help manage and protect them, it is important to map and monitor their spatial extent and condition. However, wetlands have not yet been comprehensively and reliably mapped at the national level, although elements for mapping national coverage exist in two of our national databases: Waters of National Importance (WONI), and the New Zealand Land Cover Database (LCDB). The extent of freshwater wetlands in WONI was derived by identifying all types of freshwater wetlands, excluding inland saline. The extent of freshwater wetlands in the LCDB was derived by identifying areas with either a wet context, herbaceous freshwater vegetation, or flax. We then combined identified freshwater wetlands from the two databases recognising the superior boundary delineation of LCDB and the superior wetland detection of WONI. The current spatial extent of freshwater wetlands in New Zealand is now calculated at 249,214 ha, or 10.08% of the historical extent, rather than the 7.4% reported by LCDB5 alone. This is at least 5,954 ha less than that in 1996. The revised extent of freshwater wetlands is an improvement over either WONI or LCDB because it now includes a more comprehensive set of wetlands over 0.5 ha in area with well-defined boundaries. However, the revised extent does not include small wetlands less than 0.5 ha in area. While adding little to the total area of wetlands in New Zealand, small wetlands have significant ecological value. The National Policy Statement for Freshwater Management mandates the national mapping of the small wetlands down to 0.05 ha, but we suggest their ecological value be considered in land use change decisions only, thereby avoiding the excessive cost of mapping many millions of small wetlands.

  2. m

    Nutritional Dataset for New Zealand Foods

    • data.mendeley.com
    Updated Sep 14, 2020
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Chanjief Chandrakumar (2020). Nutritional Dataset for New Zealand Foods [Dataset]. http://doi.org/10.17632/vs5d9hv2dd.1
    Explore at:
    Dataset updated
    Sep 14, 2020
    Authors
    Chanjief Chandrakumar
    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

    This dataset was developed to understand the nutrient content of the commonly consumed foods in New Zealand.

    • The linkages between two prominent New Zealand studies (or databases) were evaluated, in order to determine the matching between the foods in those studies.
    • The first study was the 2008/09 New Zealand Adult Nutrition Survey (NZANS) for the total New Zealand population, which presents the commonly consumed foods (a total of 346) in New Zealand.
    • The second study was the New Zealand FOODfiles™ 2018 Version 01, which is a database that provides nutrition information (both essential nutrients and essential amino acids) for 2,767 foods.
    • Some of the foods in the 2008/09 NZANS are dishes (or menus); the nutrient content of each of those dishes was constructed based on the work by Drew et al. (2020).

    References

    1. Drew J, Cleghorn C, Macmillan A, Mizdrak A. 2020. Healthy and Climate-Friendly Eating Patterns in the New Zealand Context. Environ Health Perspect. 128(1): 017007.
    2. Plant and Food Research, Ministry of Health. 2019. New Zealand Food Composition Database. The New Zealand Institute for Plant and Food Research Limited. [accessed 12 Feb 2020]. https://www.foodcomposition.co.nz/
    3. University of Otago, Ministry of Health. 2011. A Focus on Nutrition: Key Findings of the 2008/09 New Zealand Adult Nutrition Survey. Wellington, New Zealand: Ministry of Health.

    Last update: 12 September 2020

  3. Land Environments New Zealand (LENZ) - Level 1 Grid (2010)

    • catalogue.data.govt.nz
    • data.mfe.govt.nz
    aaigrid, gtiff, kea +1
    Updated Mar 2, 2015
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Ministry for the Environment (2015). Land Environments New Zealand (LENZ) - Level 1 Grid (2010) [Dataset]. https://catalogue.data.govt.nz/dataset/groups/land-environments-new-zealand-lenz-level-1-grid-2010
    Explore at:
    kea, pdf, aaigrid, gtiffAvailable download formats
    Dataset updated
    Mar 2, 2015
    Dataset provided by
    Ministry For The Environmenthttps://environment.govt.nz/
    License

    Attribution 3.0 (CC BY 3.0)https://creativecommons.org/licenses/by/3.0/
    License information was derived automatically

    Area covered
    New Zealand
    Description

    Land Environments of New Zealand (LENZ) is a classification of fifteen climate, landform, and soil variables chosen for their relevance to biological distributions. Classification groups were derived by automatic classification using a multivariate procedure. Four levels of classification detail have been produced from this analysis, containing 20, 100, 200, and 500 groups respectively. More information is available from the LENZ web site: http://www.landcareresearch.co.nz/databases/lenz/

  4. f

    Analytical tools and databases that use predictive microbiology to support...

    • plos.figshare.com
    • figshare.com
    xls
    Updated Aug 23, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Joan B. Rose; Nynke Hofstra; Erica Hollmann; Panagis Katsivelis; Gertjan J. Medema; Heather M. Murphy; Colleen C. Naughton; Matthew E. Verbyla (2023). Analytical tools and databases that use predictive microbiology to support safe water and/or safe sanitation systems. [Dataset]. http://doi.org/10.1371/journal.pwat.0000166.t003
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Aug 23, 2023
    Dataset provided by
    PLOS Water
    Authors
    Joan B. Rose; Nynke Hofstra; Erica Hollmann; Panagis Katsivelis; Gertjan J. Medema; Heather M. Murphy; Colleen C. Naughton; Matthew E. Verbyla
    License

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

    Description

    Analytical tools and databases that use predictive microbiology to support safe water and/or safe sanitation systems.

  5. Land Environments New Zealand (LENZ) - Level 4 Grid (2009)

    • data.mfe.govt.nz
    ascii grid, geotiff +2
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Ministry for the Environment, Land Environments New Zealand (LENZ) - Level 4 Grid (2009) [Dataset]. https://data.mfe.govt.nz/layer/51801-land-environments-new-zealand-lenz-level-4-grid-2009/
    Explore at:
    geotiff, kea, pdf, ascii gridAvailable download formats
    Dataset provided by
    Ministry For The Environmenthttps://environment.govt.nz/
    Authors
    Ministry for the Environment
    License

    https://data.mfe.govt.nz/license/attribution-3-0-new-zealand/https://data.mfe.govt.nz/license/attribution-3-0-new-zealand/

    Area covered
    Description

    Land Environments of New Zealand (LENZ) is a classification of fifteen climate, landform, and soil variables chosen for their relevance to biological distributions. Classification groups were derived by automatic classification using a multivariate procedure. Four levels of classification detail have been produced from this analysis, containing 20, 100, 200, and 500 groups respectively. More information is available from the LENZ web site: http://www.landcareresearch.co.nz/databases/lenz/

  6. Network of scientific collaborations between New Zealand institutions based...

    • figshare.com
    zip
    Updated May 31, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Samin Aref; David Friggens; Shaun Hendy (2023). Network of scientific collaborations between New Zealand institutions based on Scopus publications from 2010 to 2015 [Dataset]. http://doi.org/10.6084/m9.figshare.5705167.v1
    Explore at:
    zipAvailable download formats
    Dataset updated
    May 31, 2023
    Dataset provided by
    Figsharehttp://figshare.com/
    Authors
    Samin Aref; David Friggens; Shaun Hendy
    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

    This dataset contains major outputs of a study on collaboration links between all New Zealand universities based on Scopus publications within 2010-2015. For more details about the study, one may refer toSamin Aref, David Friggens, and Shaun Hendy. 2018. Analysing Scientific Collaborations of New Zealand Institutions using Scopus Bibliometric Data. In Proceedings of ACSW 2018: Australasian Computer Science Week 2018, January 29-February 2, 2018, Brisbane, QLD, Australia, 10 pages.

    https://doi.org/10.1145/3167918.3167920The number of collaboration records of 15 New Zealand universities and crown research institutes (government-funded research centres) are categorised based on the type of collaborator (business enterprise, government, higher education, and private not-for-profit) and the subject of publication venue and provided as a CSV file.New Zealand scientific collaboration network is provided in 3 formats: .gephi, .graphml, and an edge list in .csv format7 Induced subgraphs of the network are also provided. Each induced subgraph (ego network) represents the collaborators network of a crown research institute. Two formats are provided: .gephi and .graphml.Please cite the research paper (doi: 10.1145/3167918.3167920) as well as this Figshare dataset (doi 10.6084/m9.figshare.5705167) when using the data.ACKNOWLEDGMENTSAndrew Marriott and Sam Holmes at Ministry of Business Innovation & Employment (MBIE) performed much of the work classifying New Zealand institutions. The first author would like to thank Peter Ellis and Franz Smith for their support.

  7. f

    A summary of water quality models in use around the globe (not exhaustive).

    • figshare.com
    xls
    Updated Aug 23, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Joan B. Rose; Nynke Hofstra; Erica Hollmann; Panagis Katsivelis; Gertjan J. Medema; Heather M. Murphy; Colleen C. Naughton; Matthew E. Verbyla (2023). A summary of water quality models in use around the globe (not exhaustive). [Dataset]. http://doi.org/10.1371/journal.pwat.0000166.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Aug 23, 2023
    Dataset provided by
    PLOS Water
    Authors
    Joan B. Rose; Nynke Hofstra; Erica Hollmann; Panagis Katsivelis; Gertjan J. Medema; Heather M. Murphy; Colleen C. Naughton; Matthew E. Verbyla
    License

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

    Description

    A summary of water quality models in use around the globe (not exhaustive).

  8. Data for "The influence of fault geometrical complexity on surface rupture...

    • zenodo.org
    bin, csv, zip
    Updated Aug 10, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Alba Mar Rodriguez Padilla; Alba Mar Rodriguez Padilla; Michael Oskin; Michael Oskin; Emily Brodsky; Emily Brodsky; Kelian Dascher-Cousineau; Kelian Dascher-Cousineau; Vanessa Herrera; Sophia White; Vanessa Herrera; Sophia White (2024). Data for "The influence of fault geometrical complexity on surface rupture length" [Dataset]. http://doi.org/10.5281/zenodo.12696715
    Explore at:
    zip, bin, csvAvailable download formats
    Dataset updated
    Aug 10, 2024
    Dataset provided by
    Zenodohttp://zenodo.org/
    Authors
    Alba Mar Rodriguez Padilla; Alba Mar Rodriguez Padilla; Michael Oskin; Michael Oskin; Emily Brodsky; Emily Brodsky; Kelian Dascher-Cousineau; Kelian Dascher-Cousineau; Vanessa Herrera; Sophia White; Vanessa Herrera; Sophia White
    License

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

    Description

    This repository contains the data generated in and some data from the FDHI database (Sarmiento et al., 2021) required to run the scripts used in our publication "The effect of fault geometrical complexity on surface rupture length".

    Table of contents:

    File/directoryFile typeNotesReferences (if applicable)
    geometrical_complexity_shapefiles_v1.zipShapefiles

    Shapefiles for the breached and unbreached geometrical features in Rodriguez Padilla et al. 202X. The name of each file is the geometrical feature, followed by whether the feature is breached or unbreached, followed by the name of the event the feature was mapped from.

    Example: stepover_breached_Borrego.shp

    Note some shapefiles are empty because that feature type was not observed for a given event.

    Rodriguez Padilla et al. (202X)

    Sarmiento et al. (2021) https://www.risksciences.ucla.edu/nhr3/fdhi/databases

    Regional_maps.zipShapefilesShapefiles for each regional fault map (Qfaults for US, NZAFD for New Zealand, AFEAD for Asia and the Middle East, and GEM for remaining regions)USGS and CGS, Langridge et al. (2016), Bachmanov et al. (2021), Styron and Pagani (2020)
    event_rupture_shp.zipShapefilesShapefiles with the primary ruptures for each of the events as mapped in the FDHI database

    Sarmiento et al. (2021) https://www.risksciences.ucla.edu/nhr3/fdhi/databases

    data_FDHI.xlsxSpreadhsheetEvent information, including magnitude, date, displacement distribution, etc. from the FDHI database. The data that is compiled in the spreadsheet can be accessed from the appendices of the FDHI database.

    Sarmiento et al. (2021)

    https://www.risksciences.ucla.edu/nhr3/fdhi/databases

    reflines_FDHI.zipShapefiles

    ECS reference lines for each event from the FDHI database (Sarmiento et al., 2021) in shapefile format

    Sarmiento et al. (2021)

    https://www.risksciences.ucla.edu/nhr3/fdhi/databases

    geometries.csvSpreadsheet

    Feature geometries, including lengths, widths, angles, and other measured attributes, generated using the Matlab code measure_EQgates.m in Github repository https://github.com/absrp/passing_probabilities_EQgates

    This csv file also serves as the input for the Jupyter Notebook for estimating passing probabilities and event likelihoods.

    Rodriguez Padilla et al. (202X)

  9. f

    Summary of key microbial water quality databasesa.

    • plos.figshare.com
    xls
    Updated Aug 23, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Joan B. Rose; Nynke Hofstra; Erica Hollmann; Panagis Katsivelis; Gertjan J. Medema; Heather M. Murphy; Colleen C. Naughton; Matthew E. Verbyla (2023). Summary of key microbial water quality databasesa. [Dataset]. http://doi.org/10.1371/journal.pwat.0000166.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Aug 23, 2023
    Dataset provided by
    PLOS Water
    Authors
    Joan B. Rose; Nynke Hofstra; Erica Hollmann; Panagis Katsivelis; Gertjan J. Medema; Heather M. Murphy; Colleen C. Naughton; Matthew E. Verbyla
    License

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

    Description

    Summary of key microbial water quality databasesa.

  10. f

    Data_Sheet_1_Harmonizing and Searching Macroinvertebrate Trait Information...

    • frontiersin.figshare.com
    xlsx
    Updated Jun 14, 2023
    + more versions
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Sicheng Ao; Xianfu Li; Zhen Tian; Jiancheng Hu; Qinghua Cai (2023). Data_Sheet_1_Harmonizing and Searching Macroinvertebrate Trait Information in Alpine Streams: Method and Application–A Case Study in the Three Parallel Rivers Region, China.xlsx [Dataset]. http://doi.org/10.3389/fevo.2022.945824.s002
    Explore at:
    xlsxAvailable download formats
    Dataset updated
    Jun 14, 2023
    Dataset provided by
    Frontiers
    Authors
    Sicheng Ao; Xianfu Li; Zhen Tian; Jiancheng Hu; Qinghua Cai
    License

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

    Area covered
    China
    Description

    The traits of organisms provide critical information for understanding changes in biodiversity and ecosystem function at large scales. In recent years, trait databases of macroinvertebrates have been developed across continents. Anyone using different databases to search for traits will encounter a series of problems that lead to uncertain results due to the inconsistency of the trait information. For example, traits for a particular macroinvertebrate taxon may be inconsistent across databases, coded in inconsistent ways, or cannot be found. However, most of the current studies do not clearly state their solutions, which seriously hinders the accuracy and comparability of global trait studies. To solve these problems, we collected representative databases from several continents, including the United States, Europe, South Africa, Bolivia, Australia, and New Zealand. By comparing the inconsistency of similar trait classifications in the nine databases, we harmonized 41 of these grouping features. We found that these databases differed widely in terms of the range and category of traits. And the method of coding traits also varies from database to database. Moreover, we showed a set of trait searching rules that integrate trait databases from different regions of the world, allowing traits to be identified more easily and uniformly using different trait databases worldwide. We also applied this method to determine the traits of 155 macroinvertebrate taxa in the Three Parallel Rivers Region (TPRR). The results showed that among a total of 155 macroinvertebrate taxa, the 41 grouping features of all genera were not fully identified, and 32 genera were not recorded (thus using family-level data). No trait information was found at all for two families, which contain two genera. This suggests that many macroinvertebrate taxa and their traits have not been fully studied, especially in those regions, including China, where macroinvertebrate trait studies are lagging. This inadequacy and unevenness have seriously hindered the study and development of macroinvertebrate trait and functional diversity worldwide. Our results complement the information on stream macroinvertebrate traits in the TPRR, a global biodiversity hotspot, and greatly promote the uniformity of global trait research and the accuracy and comparability of trait research in different regions.

  11. Rafter Radiocarbon Databases and Archive

    • geodata.nz
    Updated Apr 11, 2019
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    GNS Science (2019). Rafter Radiocarbon Databases and Archive [Dataset]. https://geodata.nz/geonetwork/srv/api/records/33fcb89a-9ba7-4904-9274-a558734578c3
    Explore at:
    www:link-1.0-http--linkAvailable download formats
    Dataset updated
    Apr 11, 2019
    Dataset authored and provided by
    GNS Sciencehttp://www.gns.cri.nz/
    Area covered
    Description

    The Rafter Radiocarbon Databases and Archive contain radiocarbon submission, treatment and measurement data spanning 70 years.

    The Rafter Radiocarbon Lab manages the digital databases, paper records and physical remains of submitted materials. All ~60,000 results reported by our laboratory since 1951 are digitised and available on request.

    Most gas counting results were reported prior to the implementation of the current radiocarbon reporting conventions and therefore we strongly recommend that users of our gas counting results contact us to obtain recalculated results that follow the current reporting conventions.

    For early samples, details of sample provenance and preparation are archived as paper records and access to these may incur a charge.

    AMS results can usually only be provided with permission of the original submitter. Full details are available digitally with permission.

    Contact radiocarbon@gns.cri.nz for data access.

  12. f

    Data_Sheet_1_Harmonizing and Searching Macroinvertebrate Trait Information...

    • frontiersin.figshare.com
    docx
    Updated Jun 17, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Sicheng Ao; Xianfu Li; Zhen Tian; Jiancheng Hu; Qinghua Cai (2023). Data_Sheet_1_Harmonizing and Searching Macroinvertebrate Trait Information in Alpine Streams: Method and Application–A Case Study in the Three Parallel Rivers Region, China.docx [Dataset]. http://doi.org/10.3389/fevo.2022.945824.s001
    Explore at:
    docxAvailable download formats
    Dataset updated
    Jun 17, 2023
    Dataset provided by
    Frontiers
    Authors
    Sicheng Ao; Xianfu Li; Zhen Tian; Jiancheng Hu; Qinghua Cai
    License

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

    Area covered
    China
    Description

    The traits of organisms provide critical information for understanding changes in biodiversity and ecosystem function at large scales. In recent years, trait databases of macroinvertebrates have been developed across continents. Anyone using different databases to search for traits will encounter a series of problems that lead to uncertain results due to the inconsistency of the trait information. For example, traits for a particular macroinvertebrate taxon may be inconsistent across databases, coded in inconsistent ways, or cannot be found. However, most of the current studies do not clearly state their solutions, which seriously hinders the accuracy and comparability of global trait studies. To solve these problems, we collected representative databases from several continents, including the United States, Europe, South Africa, Bolivia, Australia, and New Zealand. By comparing the inconsistency of similar trait classifications in the nine databases, we harmonized 41 of these grouping features. We found that these databases differed widely in terms of the range and category of traits. And the method of coding traits also varies from database to database. Moreover, we showed a set of trait searching rules that integrate trait databases from different regions of the world, allowing traits to be identified more easily and uniformly using different trait databases worldwide. We also applied this method to determine the traits of 155 macroinvertebrate taxa in the Three Parallel Rivers Region (TPRR). The results showed that among a total of 155 macroinvertebrate taxa, the 41 grouping features of all genera were not fully identified, and 32 genera were not recorded (thus using family-level data). No trait information was found at all for two families, which contain two genera. This suggests that many macroinvertebrate taxa and their traits have not been fully studied, especially in those regions, including China, where macroinvertebrate trait studies are lagging. This inadequacy and unevenness have seriously hindered the study and development of macroinvertebrate trait and functional diversity worldwide. Our results complement the information on stream macroinvertebrate traits in the TPRR, a global biodiversity hotspot, and greatly promote the uniformity of global trait research and the accuracy and comparability of trait research in different regions.

  13. f

    Overall percentage of products permitted and not permitted under each...

    • plos.figshare.com
    xls
    Updated Oct 25, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Rachel Jordan; Kelly Garton; Sally Mackay (2024). Overall percentage of products permitted and not permitted under each category of brands. [Dataset]. http://doi.org/10.1371/journal.pone.0311579.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Oct 25, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Rachel Jordan; Kelly Garton; Sally Mackay
    License

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

    Description

    Overall percentage of products permitted and not permitted under each category of brands.

  14. f

    Characteristics of included studies.

    • plos.figshare.com
    xls
    Updated Apr 26, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Charlotte Williamson; Bethany Croak; Amos Simms; Nicola T. Fear; Marie-Louise Sharp; Sharon A. M. Stevelink (2024). Characteristics of included studies. [Dataset]. http://doi.org/10.1371/journal.pone.0299239.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Apr 26, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Charlotte Williamson; Bethany Croak; Amos Simms; Nicola T. Fear; Marie-Louise Sharp; Sharon A. M. Stevelink
    License

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

    Description

    BackgroundSelf-harm and suicide behaviours are a major public health concern. Several factors are associated with these behaviours among military communities. Identifying these factors may have important implications for policy and clinical services. The aim of this review was to identify the risk and protective factors associated with self-harm and suicide behaviours among serving and ex-serving personnel of the United Kingdom Armed Forces, Canadian Armed Forces, Australian Defence Force and New Zealand Defence Force.MethodsA systematic search of seven online databases (PubMed, Web of Science, Embase, Global Health, PsycINFO, PTSDpubs and CINAHL) was conducted alongside cross-referencing, in October 2022. Following an a priori PROSPERO approved protocol (CRD42022348867), papers were independently screened and assessed for quality. Data were synthesised using a narrative approach.ResultsOverall, 28 papers were included: 13 from Canada, 10 from the United Kingdom, five from Australia and none from New Zealand. Identified risk factors included being single/ex-relationship, early service leavers, shorter length of service (but not necessarily early service leavers), junior ranks, exposure to deployment-related traumatic events, physical and mental health diagnoses, and experience of childhood adversity. Protective factors included being married/in a relationship, higher educational attainment, employment, senior ranks, and higher levels of perceived social support.ConclusionAdequate care and support are a necessity for the military community. Prevention and intervention strategies for self-harm and suicide behaviours may be introduced early and may promote social networks as a key source of support. This review found a paucity of peer-reviewed research within some populations. More peer-reviewed research is needed, particularly among these populations where current work is limited, and regarding modifiable risk and protective factors.

  15. f

    Applying a threshold of brands permitted to be marketed.

    • plos.figshare.com
    xls
    Updated Oct 25, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Rachel Jordan; Kelly Garton; Sally Mackay (2024). Applying a threshold of brands permitted to be marketed. [Dataset]. http://doi.org/10.1371/journal.pone.0311579.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Oct 25, 2024
    Dataset provided by
    PLOS ONE
    Authors
    Rachel Jordan; Kelly Garton; Sally Mackay
    License

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

    Description

    Applying a threshold of brands permitted to be marketed.

  16. Risk and Protective Factors Identified in Included Studies (N = 28).

    • plos.figshare.com
    xls
    Updated Apr 26, 2024
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Charlotte Williamson; Bethany Croak; Amos Simms; Nicola T. Fear; Marie-Louise Sharp; Sharon A. M. Stevelink (2024). Risk and Protective Factors Identified in Included Studies (N = 28). [Dataset]. http://doi.org/10.1371/journal.pone.0299239.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Apr 26, 2024
    Dataset provided by
    PLOShttp://plos.org/
    Authors
    Charlotte Williamson; Bethany Croak; Amos Simms; Nicola T. Fear; Marie-Louise Sharp; Sharon A. M. Stevelink
    License

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

    Description

    Risk and Protective Factors Identified in Included Studies (N = 28).

  17. f

    Midwifery continuity of care: Where, how, by whom and for whom by income...

    • figshare.com
    • datasetcatalog.nlm.nih.gov
    xls
    Updated Jun 13, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Billie F. Bradford; Alyce N. Wilson; Anayda Portela; Fran McConville; Cristina Fernandez Turienzo; Caroline S. E. Homer (2023). Midwifery continuity of care: Where, how, by whom and for whom by income level. [Dataset]. http://doi.org/10.1371/journal.pgph.0000935.t002
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 13, 2023
    Dataset provided by
    PLOS Global Public Health
    Authors
    Billie F. Bradford; Alyce N. Wilson; Anayda Portela; Fran McConville; Cristina Fernandez Turienzo; Caroline S. E. Homer
    License

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

    Description

    Midwifery continuity of care: Where, how, by whom and for whom by income level.

  18. f

    Initiatives for women, newborns and families with risk of adverse outcomes...

    • plos.figshare.com
    • datasetcatalog.nlm.nih.gov
    xls
    Updated Jun 13, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Billie F. Bradford; Alyce N. Wilson; Anayda Portela; Fran McConville; Cristina Fernandez Turienzo; Caroline S. E. Homer (2023). Initiatives for women, newborns and families with risk of adverse outcomes by country. [Dataset]. http://doi.org/10.1371/journal.pgph.0000935.t003
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 13, 2023
    Dataset provided by
    PLOS Global Public Health
    Authors
    Billie F. Bradford; Alyce N. Wilson; Anayda Portela; Fran McConville; Cristina Fernandez Turienzo; Caroline S. E. Homer
    License

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

    Description

    Initiatives for women, newborns and families with risk of adverse outcomes by country.

  19. f

    Methodological characterization of selected studies.

    • plos.figshare.com
    • datasetcatalog.nlm.nih.gov
    xls
    Updated Jun 4, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Viviane Belini Rodrigues; Everton Nunes da Silva; Maria Leonor Pacheco Santos (2023). Methodological characterization of selected studies. [Dataset]. http://doi.org/10.1371/journal.pone.0258488.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 4, 2023
    Dataset provided by
    PLOS ONE
    Authors
    Viviane Belini Rodrigues; Everton Nunes da Silva; Maria Leonor Pacheco Santos
    License

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

    Description

    Methodological characterization of selected studies.

  20. f

    Midwifery continuity of care publications by country.

    • plos.figshare.com
    • datasetcatalog.nlm.nih.gov
    xls
    Updated Jun 13, 2023
    Share
    FacebookFacebook
    TwitterTwitter
    Email
    Click to copy link
    Link copied
    Close
    Cite
    Billie F. Bradford; Alyce N. Wilson; Anayda Portela; Fran McConville; Cristina Fernandez Turienzo; Caroline S. E. Homer (2023). Midwifery continuity of care publications by country. [Dataset]. http://doi.org/10.1371/journal.pgph.0000935.t001
    Explore at:
    xlsAvailable download formats
    Dataset updated
    Jun 13, 2023
    Dataset provided by
    PLOS Global Public Health
    Authors
    Billie F. Bradford; Alyce N. Wilson; Anayda Portela; Fran McConville; Cristina Fernandez Turienzo; Caroline S. E. Homer
    License

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

    Description

    Midwifery continuity of care publications by country.

Share
FacebookFacebook
TwitterTwitter
Email
Click to copy link
Link copied
Close
Cite
(2023). Revised extent of wetlands in New Zealand - Dataset - DataStore [Dataset]. https://datastore.landcareresearch.co.nz/dataset/revised-extent-of-wetlands-in-new-zealand

Revised extent of wetlands in New Zealand - Dataset - DataStore

Explore at:
Dataset updated
Apr 4, 2023
License

Attribution-NonCommercial-ShareAlike 4.0 (CC BY-NC-SA 4.0)https://creativecommons.org/licenses/by-nc-sa/4.0/
License information was derived automatically

Area covered
New Zealand
Description

Wetlands are highly valued and significant ecosystems with a large range of services and functions. To help manage and protect them, it is important to map and monitor their spatial extent and condition. However, wetlands have not yet been comprehensively and reliably mapped at the national level, although elements for mapping national coverage exist in two of our national databases: Waters of National Importance (WONI), and the New Zealand Land Cover Database (LCDB). The extent of freshwater wetlands in WONI was derived by identifying all types of freshwater wetlands, excluding inland saline. The extent of freshwater wetlands in the LCDB was derived by identifying areas with either a wet context, herbaceous freshwater vegetation, or flax. We then combined identified freshwater wetlands from the two databases recognising the superior boundary delineation of LCDB and the superior wetland detection of WONI. The current spatial extent of freshwater wetlands in New Zealand is now calculated at 249,214 ha, or 10.08% of the historical extent, rather than the 7.4% reported by LCDB5 alone. This is at least 5,954 ha less than that in 1996. The revised extent of freshwater wetlands is an improvement over either WONI or LCDB because it now includes a more comprehensive set of wetlands over 0.5 ha in area with well-defined boundaries. However, the revised extent does not include small wetlands less than 0.5 ha in area. While adding little to the total area of wetlands in New Zealand, small wetlands have significant ecological value. The National Policy Statement for Freshwater Management mandates the national mapping of the small wetlands down to 0.05 ha, but we suggest their ecological value be considered in land use change decisions only, thereby avoiding the excessive cost of mapping many millions of small wetlands.

Search
Clear search
Close search
Google apps
Main menu