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Supporting information
Methodology
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"text": "The primary data source for this indicator is the OceanCSI_1980 - 2023 dataset (ICES 2023), which compiles information from ICES, EMODnet, and the WISE SoE \u2013 Water Quality (WISE-6). The data handling processes\u2014extraction, selection, aggregation, trend analysis and plotting\u2014are performed using the R programming language. "
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"text": "Data flagged as bad quality (bad value, probably bad value), uncertain quality (value in excess, uncertain value, missing value), or duplicates are excluded, and the 99.9% percentile of the highest values are sorted out. The analysis considers only data from depths of less than 10 meters and during the winter months, which include January to March for stations in the Baltic Sea east of 15E and January to February for all other stations. "
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"text": "Average values are calculated using a combination of estimated marginal means (EMM) and arithmetic means, where the EMM were used for time series containing data from both different years and months and the arithmetic means were used for time-series with yearly observations. Initial calculations of average annual concentrations are done by location and by month-year to standardise observations across different depths and time (days, hours or even minutes in some cases). "
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"text": "Stations are geographically defined by their longitude and latitude in decimal degrees. All geographical positions in the data are mapped to a marine (sub) region based on coordinates. The data often lack reliable and consistent station identifiers, which can lead to fragmented time series. To improve time series aggregation, data are grouped into 1.375km squares for coastal stations (within 20km of the coastline) and 5.5km squares for open water stations. While this procedure does not eliminate the risk of incorrect data aggregation or the breaking of time series due to minor positional shifts, it significantly reduces these issues. These aggregated clusters are designated as \u2018locations\u2019. "
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"text": "Temporal trends are analysed based on the yearly averages for each time-series within a grid cell. A linear regression model (lm) is then applied to identify trends over time, with the slope indicating whether the trend is positive or negative. To assess statistical significance (p.value < 0.05), a robustness test is conducted. Additionally, the Mann-Kendall test is used to validate the trends. Based on the Mann-Kendall results, trends are classified as \"increasing,\" \"decreasing,\" or \"no trend.\" If the initial test deems a model \"not robust,\" the trend is automatically set to \"no trend.\" Only stations with at least five years of data are included in the analysis. "
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Data sources and providers
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Definition
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"text": "This indicator shows the geographical distribution and trends in winter concentrations of DIN (sum of ammonium, nitrite and nitrate) and DIP (orthophosphate), (\u00b5mol/l) in the upper 10 meters of the water column during the assessment period 1980-2023, in Europe\u2019 seas. The purpose of this indicator is to illustrate the effectiveness of regulatory measures aimed at reducing nutrient discharges and their impact on phytoplankton levels. "
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Unit of measure
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"text": " are directly addressing human activities and are aiming to reduce the loads of nutrients emitted in aquatic systems. "
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"text": " \u2014 also outline measures that aim to reduce the loads and impacts of nutrients and include countries beyond the EU."
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"children": [
{
"text": "This indicator assesses trends in nutrient levels in European transitional, coastal and marine waters to provide an indication of whether measures taken to reduce the risk of eutrophication are on track to be effective. It does not provide information on whether or not policy objectives have been achieved, as threshold values (boundaries between good and bad condition) were not available for each location."
}
],
"type": "p"
}
]
Frequency of dissemination
1
Accuracy and uncertainties
[
{
"type": "p",
"children": [
{
"text": " No uncertainties have been quantified. The data availability is variable across the different regional seas, with higher data coverage over space and time in the North Sea and the Baltic Sea. Hence, the accuracy of the assessment is more precise for those regions. All observations have been gathered from large databases with differences between methods for sampling and analysing which cannot be identified or quantified but may influence the results in some areas. The databases are also known to include faulty data, which slips though the first data cleaning process, therefore a second cleaning was performed by removing the 99.9 % percentile of the highest values in each region. The risk of removing potential correct data by this extra cleaning was estimated to be very low and would to have negligible effect on the assessment, as the number of excluded data was very low compared to the total number of observations, and the extreme values and potential faulty observations were sorted out which could have had a potential effect on the assessment. "
}
]
},
{
"children": [
{
"text": ""
}
],
"type": "p"
},
{
"children": [
{
"text": " "
}
],
"type": "p"
},
{
"children": [
{
"text": ""
},
{
"children": [
{
"text": "Geographical comparability "
}
],
"type": "strong"
},
{
"text": ""
}
],
"type": "p"
},
{
"children": [
{
"text": "The natural ranges of nutrient values vary greatly depending on the geographical characteristics of monitored locations. Nutrient concentrations tend to be higher in coastal waters due to river discharges and direct nutrient inputs. Thus, geographical comparisons of results should be made only within regional seas and between similar water types (i.e. transitional, coastal, or offshore locations). "
}
],
"type": "p"
},
{
"children": [
{
"text": " "
}
],
"type": "p"
},
{
"children": [
{
"text": ""
},
{
"children": [
{
"text": "Comparability over time"
}
],
"type": "b"
},
{
"text": " "
}
],
"type": "p"
},
{
"type": "p",
"children": [
{
"text": " The natural ranges of nutrient values also vary greatly depending on the season. However, as assessments have been made on a yearly basis and only for winter months (January to March for Baltic Sea stations east of 15E and January to February for all other stations), temporal comparability is possible. It is also important to note that the temporal range of data at different locations varies depending on the availability of data, although all locations have at least five-yearly observations. "
}
]
}
]
