Environmental Reporting Data

16 April 2020: Subsequent to publication in April 2019 we discovered two small errors with this dataset. These included:

• Errors in the coordinates of some sites and their associated metadata (such as landcover and elevation).
• Errors in our calculation of dominant landcover.

In addition, flow data from TopNet has also been updated.

These changes have a minor impact on overall results. These changes have have been corrected, and are republished here, as part of the Our freshwater 2020 release.

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This dataset measures how water quality in New Zealand’s rivers is changing over time. It contains nine parameters of water quality based on measurements made at monitored river sites in years 1990-2017:

• Nitrate-nitrogen
• Ammoniacal nitrogen
• Total nitrogen
• Total phosphorus
• Dissolved reactive phosphorus
• Water clarity
• Turbidity
• Escherichia coli
• Macroinvertebrate community index

More information on this dataset and how it relates to our environmental reporting indicators and topics can be found in the attached data quality pdf.

Summary report available at www.mfe.govt.nz/publications/fresh-water/water-qua....

DATA SOURCE: National Institute for Water and Atmospheric Research (NIWA)
[Technical report available at www.mfe.govt.nz/publications/environmental-reporti...]

Adapted by Ministry for the Environment and Statistics New Zealand to provide for environmental reporting transparency

This lowest aggregation dataset, was used to develop three ‘Our Atmosphere and Climate’ indicators. See Statistics New Zealand indicator links for specific methodologies and state/trend datasets (see ‘Shiny App’ downloads).
1) Temperature (www.stats.govt.nz/ndicators/temperature)
2) First and last frost days (www.stats.govt.nz/ndicators/frost-and-warm-days)
3) Growing degree days (www.stats.govt.nz/ndicators/growing-degree-days)

IMPORTANT INFORMATION
Due to the size of this dataset (111 MB), a 32-bit version of Microsoft Excel will only display/download ~ 1 million rows. A DBMS, statistical or GIS application is needed to view the entire dataset.

This dataset shows two measures of temperature change in New Zealand: New Zealand’s national temperature from NIWA’s ‘seven-station’ temperature series from 1909 to 2019, and temperature at 30 sites around the country from at least 1972 to 2019. For national temperature, we report daily average, minimum and maximum temperatures. We also present New Zealand national and global temperature anomalies.

More information on this dataset and how it relates to our environmental reporting indicators and topics can be found in the attached data quality pdf.

Land use that results in a change from indigenous to exotic cover can cause biodiversity loss and reduce functioning of ecosystems. Using more land for agriculture, forestry, and urbanisation is the main driver reducing indigenous land cover across New Zealand.

Column headings:
area_ha = area of land cover measured in hectares

This dataset relates to the "Land use" measure on the Environmental Indicators, Te taiao Aotearoa website.

Livestock farming is a widespread land use in New Zealand and contributes to our economy. High livestock numbers and the distribution of livestock across land environments can affect indigenous biodiversity and soil health (eg compaction). High livestock numbers and density in some land environments can also affect water quality, as nitrogen and bacteria from urine and faeces can leach into groundwater or run off the land into rivers and lakes.

We measure changes in the numbers of farmed livestock (eg beef and dairy cattle, deer, and sheep) across regions in New Zealand.

Dominant land uses in New Zealand include conservation (eg national and forestry parks), forestry (eg for timber resources/wood supply), urban (eg built up areas and open parkland), and agriculture and horticulture. Each land use places different pressures on the land and on receiving environments such as waterways. These pressures can be both positive (eg increased productivity) and negative (eg biodiversity loss and reduced functioning of ecosystems).

This measure reports on agricultural and horticultural land uses by region.

DATA SOURCE: Statistics New Zealand Agricultural Production Survey (APS)

Adapted by Ministry for the Environment and Statistics New Zealand to provide for environmental reporting transparency

Dataset used to develop the "Agricultural and horticultural land use" indicator (available at www.stats.govt.nz/indicators/agricultural-and-hort...)

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This indicator reports on the use of land for primary production purposes, specifically agricultural land uses, such as beef and sheep farming and dairying, horticultural land uses, such as fruit and berry, and vegetable growing, and other land uses, such as forestry. We do this for the period 2002 to 2019.

More information on this dataset and how it relates to our environmental reporting indicators and topics can be found in the attached data quality pdf.

This dataset relates to NIWA's 'seven-station' temperature series uses temperature measurements from seven 'climate stations'.
More information on this dataset and how it relates to our environmental reporting indicators and topics can be found in the attached data quality pdf.

River water quality water is valued for many reasons including ecological function and habitat, recreational value, its role in supporting people and industry, and its cultural significance. Nutrients such as nitrogen and phosphorus are essential for plant growth, however too much in rivers can lead to ‘nuisance’ growths of river algae and aquatic plants, degrading habitat. High concentrations in the form of ammoniacal nitrogen and nitrate-nitrogen can be toxic to fish and other aquatic animals. Water clarity is a measure of underwater visibility, and affects habitat of aquatic life such as fish and birds, and can also impact on aesthetic values and recreational use of rivers and streams. Escherichia coli (E.coli) can indicate the presence of pathogens (disease-causing organisms) from animal or human faeces, which can cause illness.

File contains raw data collected at regional council and NIWA monitored sites over the period 1975-2013. Fields are described as follows. Refer to Larned et al. 2015 for further details:
* nemarid ---- Unique NIWA ID
* lawaid ---- Unique LAWA ID
* rcid ---- Collection agency
* srcid ---- Region site is located in
* sflag ---- River (r) or Estuary (e)
* river ---- River name
* location ---- Name of site, assigned by collection agency
* nzmge ---- easting
* nzmgn ---- northing
* nzreach ---- REC1 segment identifier
* sdate ---- Sample date (yyyy-mm-dd)
* Q ---- Flow recorded when sample was taken (if available), cumecs
* npid ---- NIWA parameter ID (as used in Larned et al. 2015)
* lpid ---- LAWA parameter ID
* fdval ---- Parameter value (units are mg/m3, except CLAR (m) and ECOLI (n/100 mL))

For more information please see:
Larned, S, Snelder, T, Unwin, M, McBride, G, Verburg, P, McMillan, H (2015).Analysis of Water Quality in New Zealand lakes and Rivers: data sources, data sets, assumptions, limitations, methods and results. NIWA Client Report no. CHC2015-033. Available at data.mfe.govt.nz/x/Mo8VUY from the Ministry for the Environment dataservice.

This dataset relates to the "River water quality" measures on the Environmental Indicators, Te taiao Aotearoa website.

Extreme weather events are weather events that are rare or even statistically unlikely. In New Zealand, such events can be dangerous and costly, both socially and monetarily. They can cause damage that affects productivity and leads to millions of dollars in insurance claims.
This dataset relates to the "Insurance losses for extreme weather events" measure on the Environmental Indicators, Te taiao Aotearoa website.

Measured oceanic chlorophyll-a (chl-a) concentrations as an indicator of marine primary productivity. Phytoplankton are primary producers of biomass (mass of living organisms) and form the main basis of marine food chains. They use the chl-a pigment to capture the sun’s energy through the process of photosynthesis. Phytoplankton growth is affected by the availability of nutrients and light, which in turn are affected by the structure of the surface water column. The surface water column structure is affected by oceanographic and climate processes; large-scale changes to climate and oceanographic conditions can lead to changes in phytoplankton growth and chl-a concentrations.