Chlorophyll in transitional, coastal and marine waters

Indicator Specification
Indicator codes: CSI 023 , MAR 006
Created 31 Oct 2014 Published 03 Mar 2015 Last modified 04 Sep 2015, 06:59 PM
Topics: , ,
This indicator illustrates the levels and trends in mean summer surface concentrations of chlorophyll-a (microgram/l) in the regional seas of Europe.

Assessment versions

Published (reviewed and quality assured)

Rationale

Justification for indicator selection

Anthropogenic activities, such as the application of agricultural fertilisers and manure, the discharge of wastewater and airborne emissions from shipping and combustion processes may lead to nutrient over-enrichment and eutrophication in transitional, coastal and marine waters. Nutrient enrichment/eutrophication may give rise to increased phytoplankton biomass, increased frequency and duration of phytoplankton blooms and increased primary production. Measurements of chlorophyll-a, used as an estimate of phytoplankton biomass, are included in most eutrophication monitoring programmes. Concentrations of chlorophyll-a represent the biological eutrophication indicator with the best geographical coverage at European level. Measurements of water-leaving radiance in the visible range (ocean colour), carried out using satellite radiometres, are also, nowadays, used to determine the chlorophyll-a concentration. Chlorophyll-a can be estimated from ocean colour data at daily frequency and 250m horizontal resolutions.

The primary effect of eutrophication is excessive growth of plankton algae, which increases the concentration of chlorophyll-a. The negative effects of excessive phytoplankton growth are 1) changes in species composition and functioning of the pelagic food web, 2) increased sedimentation of organic material, and 3) increase in oxygen consumption that may lead to oxygen depletion and the consequent changes in community structure or death of benthic fauna. The excessive settling of plankton algae may be enhanced by changes in species composition and functioning of the pelagic food web. Eutrophication can also promote harmful algal blooms that may cause discoloration of the water, foam formation, death of benthic fauna and fish or shellfish poisoning of humans. 

Chlorophyll-a concentrations can also be used to assess the effects of measures taken to reduce eutrophication (i.e. through discharges of nutrients, namely nitrogen). However, due to variations in freshwater run-off, light climate, hydro-geographic variability of the coastal zone and internal cycling processes, trends in chlorophyll-a concentrations, as such, cannot be directly related to measures, but must be evaluated in a broader context. Also, Europe´s regional seas have different sensitivities to eutrophication, determined by their physical characteristics. The Baltic and Black Seas have high sensitivity to eutrophication due to limited water exchange with connecting seas.

Scientific references

Indicator definition

This indicator illustrates the levels and trends in mean summer surface concentrations of chlorophyll-a (microgram/l) in the regional seas of Europe.

Units

The concentration of chlorophyll-a is expressed as microgramme per lire (mg/l) in the uppermost 10m of the water column during summer.

Policy context and targets

Context description

There are a number of EU Directives aimed at reducing the loads and impacts of nutrients. These include: the Nitrates Directive (91/676/EEC), aimed at reducing nitrate pollution from agricultural land; the Urban Waste Water Treatment Directive (91/271/EEC), aimed at reducing pollution from sewage treatment works and certain industries; the Integrated Pollution Prevention and Control Directive (96/61/EEC), aimed at controlling and preventing the pollution of water from industry; the Water Framework Directive (2000/60/EC), which requires the achievement of good ecological status or good ecological potential of transitional and coastal waters across the EU by 2015; and the Marine Strategy Framework Directive (2008/56/EC), which requires the achievement or maintenance of good environmental status in European sea basins by 2020 at the latest, through the adoption of plans of action based on 11 qualitative descriptors, one of which is Eutrophication.

Measures also arise from a number of other international initiatives and policies including: the UN Global Programme of Action for the Protection of the Marine environment against Land-based Activities; the Mediterranean Action Plan (MAP) 1975; the Helsinki Convention 1992 (HELCOM) on the Protection of the Marine Environment of the Baltic Sea Area; OSPAR Convention 1998 for the Protection of the Marine Environment of the North East Atlantic; and the Black Sea Environmental Programme (BSEP).

Targets

The most relevant EU policy target, with regard to chlorophyll concentrations, is from the Water Framework Directive (WFD), which aims to reach good ecological status of all EU surface waters by 2015. Target chlorophyll concentrations/ranges that support the WFD biological quality elements at a good status (i.e. high-good boundary and good-moderate boundary) have been defined in the Commission Decision (2008/915/EC). These are based on the results of the intercalibration exercise carried out by the geographical intercalibration groups in Baltic Sea, North East Atlantic and Mediterranean. These target chlorophyll concentrations/ranges are determined locally for different water types and water categories, including coastal and transitional water bodies.

Chlorophyll concentration in the water column is considered to be an indicator of the direct effect of nutrient enrichment in marine waters under the Marine Strategy Framework Directive’s Good Environmental Status (GES) Descriptor 5: Human-Induced Eutrophication. The aim of the MSFD is to reach or maintain GES of the marine environment by 2020. The assessment of eutrophication in marine waters needs to take into account the assessment for coastal and transitional waters under the Water Framework Directive and related guidance, in a way which ensures comparability. It must also take into consideration information and knowledge gathered and approaches developed in the framework of regional sea conventions. Chlorophyll targets or thresholds for achieving good environmental status in marine water have not yet been determined.

Related policy documents

Key policy question

Is eutrophication in European transitional, coastal and marine waters decreasing?

Methodology

Methodology for indicator calculation

The data used in this indicator is part of the WISE - State of the Environment (SoE) data, available in Waterbase - TCM (Transitional, Coastal and Marine) waters. Waterbase is the generic name given to the EEA´s database on status, quality and quantity of Europe´s water resources. Waterbase – TCM waters contains data collected both from EEA member countries (i.e. belonging to the EIONET) and from the Regional Seas Conventions through the WISE-SoE TCM data collection process. The resulting WISE SoE TCM dataset is therefore made of sub-samples of national data assembled for the purpose of providing comparable indicators of state, pressures and impacts of transitional, coastal and marine waters (TCM-data) on a Europe-wide scale.

Consistent time series are used as the basis for assessment of the development over time. The trend analyses are based on time series from 1985 onwards. Stations where data is available, at least in the last six years (2007 or later), and for five or more years in the period since 1985 are selected.

The summer period is defined as follows:

  • June to September for stations north of latitude 59 degrees in the Baltic Sea (Gulf of Bothnia and Gulf of Finland)
  • May to September for all other stations 

Primary aggregation

The primary aggregation consists of:

  • Identifying stations and assigning them to countries and sea regions
  •  Creating statistical estimates for each combination of station and year

Geographical classification: Sea region, coastal/offshore

All geographical positions defined in the data (i.e. in stations) are assigned to Europe´s regional seas by coordinates and used in the aggregation process for different determinants. The stations are then further classified as coastal or open water (>20 km from coast) by checking them against the coastal contour. Open water stations – off-shore - are distinguished per regional sea, whereas coastal stations are further attributed to countries. These classifications are done in ArcGIS.

Eionet stations

TCM data reported directly from countries is assigned to station identifiers that are listed with coordinates.

 

Marine convention data from ICES

For data reported through ICES, there are no consistent station identifiers available in the reported data but only geographical positions (latitude/longitude). The reported coordinates for what is intended to be the same station may vary between sampling visits because the exact sampling position is recorded, not the target position. Identifying stations by real sampling position may fragment time series too much. Therefore, for open waters (>20 km from land), coordinates are rounded to two decimal points. This is used to create stations (i.e. time series) with station names derived from rounded coordinates. The station coordinates used are the average coordinates from sampling visits to the station, rather then the rounded coordinates. This ensures that in cases were most observations are in a tight cluster within the rounding area, a position within the cluster is used. For the coastal ICES stations, there may be overlap with Eionet stations. In coastal stations, rounding coordinates to two decimals may be too much (about 500m to 1km). However, the rounding is also done for coastal stations but the grouping of observations to rounded coordinates is done only within observations from each country separately, and the originator country is listed. Note that these stations are not necessarily close to the coast of the originator country.

Many countries have made measurements over large areas, including some observations fairly close to the coasts of other countries, although probably not normally within territorial waters of other countries. This means that, at least for open waters, assigning data to originating country may not necessarily reflect geographical location. Duplicates between data reported through ICES, or from the Eionet directly, may occur. A visual inspection of coastal data (< 20 km from shoreline) is performed to identify those issues and correct them where possible (namely through feedback with the originator country(ies).

 

Statistical aggregation per station and year

The aggregation is done in two- or three-stage query sequences,which include:

  • Selecting season (month) and depth;
  • If needed, building a cross-table with determinants in columns, and water samples in rows, and deriving composite determinants from that;
  • Aggregating over depth for each combination of station and date; and
  • Aggregating over dates within each combination of station and year. 

 

The basic data consists of two tables:

Measurements values table
WaterbaseID (Country and Station)
Date (Year, Month and Day)
SampleDepth
SampleID
Determinant with the Determinant code "Chlorophyll"

 

Stations table
Unique identifier: data provider, Country and StationID
Position
Sea region (Atlantic, North Sea, Baltic, Mediterranean and the Black Sea

The two tables are combined in a query which joins data to stations, linked by WaterbaseID, and including Country Code and Sea Region (used in Selection Criteria below). This query (or a table made from it) is used in the Aggregate queries.

Description of specific aggregation query sequencesChlorophyll

Step 1

Select query selecting data for determinand "Chlorophyll-a", and including Sea Region, WaterbaseID, date and SamplingDepth.

Include data for:

  • Depth less than or equal to 10 metres and
  • Month = 6,7,8,9 (Jun.-Sep.) for stations north of latitude 59 degrees in the Baltic Sea (Gulf of Bothnia and Gulf of Finland)
  • Month = 5,6,7,8,9 ( May-Sep.) for all other stations

For each combination of WaterbaseID*Station*Date, calculate arithmetic mean of chlorophyll-a over depths.

Step 2

For each combination of WaterbaseID*Year, calculate the arithmetic mean over the depth averages from Step 1.

Export result to Aggregate database as table 't_Base_Metadata_Chl_a'


Classification

Concentrations from the most recent year available (2012) are presented on a map, where concentrations are classified as low, moderate or high. Low concentrations are defined as concentrations smaller than the 20-percentile value of concentrations within the specific regional sea in the last six years (i.e. 2007-2012). High concentrations are those higher than the 80-percentile value of concentrations within the regional sea in the last six years (i.e. 2007-2012). All other concentrations are classified as moderate. This classification helps to identify areas of low and high concentrations and is based on six year percentiles, unlike previous assessments, which only considered the percentile values within a regional sea based on data from that specific year.

 

Trend analysis

Trend analysis was carried out for each station in a region where data was available at least in the last six years (2007 or later), and for five or more years in the period since 1985. Trend detection for each time series was done with Mann-Kendall Statistics using a two-sided test with a significance level of 5% (Sokal & Rohlf 1995).

In the presentation of the results, a distinction is made between trends based on relatively short time series (≤ 10 years) and longer time series (> 10 years).

The Mann-Kendall method is a non-parametric test and has been extensively used for environmental time series (Helsel and Hirsch, 2002; Hipel and McLeod, 2005). Mann-Kendall is a test for monotonic trends in a time series y(x), which, in this analysis, is chlorophyll concentration (y) as a function of year (x). The test is based on Kendall's rank correlation, which measures the strength of the monotonic association between the vectors x and y. In the case of no ties in the x and y variables, Kendall's rank correlation coefficient, tau, may be expressed as tau=S/D where S = sum {i<j} (sign(x[j]-x[i])*sign(y[j]-y[i])) and D = n(n-1)/2. S is called the score and D, the denominator, is the maximum possible value of S. The p-value of tau is computed by an algorithm given by Best and Gipps (1974). The tests reported here are two-sided (testing for both increasing and decreasing trends). Data series with p-value < 0.05 are reported as significantly increasing or decreasing. The test analyses only the direction and significance of the change, not the size of the change.

The Mann-Kendall test is a robust and accepted approach. Due to multiple trend analyses, approximately 5% of the conducted tests will turn out significant (identify a trend) if in fact there is no trend. The accuracy on regional level is of course largely influenced by the number of stations for which data is available.


Methodology for gap filling

n/a

Methodology references

Data specifications

EEA data references

  • No datasets have been specified here.

Data sources in latest figures

Uncertainties

Methodology uncertainty

In the current application, two growing seasons are distinguished, one for the northern part of the Baltic Sea (June to September) and one for the southern part of the Baltic Sea, the North Sea, northeastern Atlantic waters, Mediterranean and Black Sea (May to September). It is questionable whether using one growing season for all waters that range geographically from the Mediterranean and the Black Sea to the North Sea and Baltic Sea, is appropriate. Moreover, currently only surface concentrations are considered. However, in the Black Sea, not only do the chlorophyll concentrations show peaks in late winter, late spring and autumn, but these peaks do not only occur at the surface but also in subsurface layer (BS SoE, 2008).

The Mann-Kendall test for the detection of trends used for statistical analysis of the data is a robust and accepted approach. Due to the multiple trend analyses, approximately 5% of the conducted tests will turn out significant (decrease or increase) if in fact there is no trend (type I error).

Data sets uncertainty

Data for this assessment is still scarce considering the large spatial and temporal variations inherent in European transitional, coastal and marine waters. Long stretches of European coastal waters are not covered by the analysis due to lack of data. 

For the assessment of chlorophyll-a concentrations, different analytical methods are generally used. Although these different analytical methods generally give comparable results with reasonable to good correlations between methods, simple fluorometric and photometric methods are less accurate and therefore may be a source of uncertainty.

Low sampling frequencies increase the risk of not detecting phytoplankton blooms and differences in sampling frequency between stations are an additional source of uncertainty.

Rationale uncertainty

Due to variations in freshwater runoff, hydro-geographic variability of the coastal zone and internal cycling processes, trends in chlorophyll-a concentrations, as such, cannot be directly related to measures taken, but must be evaluated in a broader context.

Further work

Short term work

Work specified here requires to be completed within 1 year from now.

Work description

It is necessary to get access to more data, in terms of better spatial coverage and longer time series, in order to improve the assessment. In order to obtain longer time series it is also important that data is associated with unique station identifiers such that observations within a specific area can be merged.  Other methodological aspects that require improvement are: a) analytical methods to determine chlorophyll b) definition of the growing season, c) classification and geographical aggregation.

Resource needs

No resource needs have been specified

Status

In progress

Deadline

2016/06/01 00:00:00 GMT+2

Work description

No further work description has been specified

Resource needs

a) Analytical methods

For the assessment of chlorophyll-a concentrations, different analytical methods are generally used. Although these different analytical methods generally give comparable results with reasonable to good correlations between methods, simple fluorometric and photometric methods are less accurate and therefore may be a source of uncertainty. It is recommended to include a description of analytical methods to determine chlorophyll and to account for different analytical methods in the trend analysis.

b) Definition of the growing season

In the current application, two growing seasons are distinguished, one for the northern part of the Baltic Sea (June-September) and one for the southern part of the Baltic Sea, the North Sea, NE Atlantic waters, Mediterranean and Black Sea (May-September). It is questionable whether using one growing season for all waters that range geographically from the Mediterranean, the Black Sea to the North Sea andBaltic Sea, is appropriate. For instance, in the Mediterranean Sea, growing seasons are not relevant whereas annual means may be more appropriate. Moreover, currently only surface concentrations are considered. However, in the Black Sea, not only do the chlorophyll concentrations show peaks in late winter, late spring and autumn, these peaks do not only occur at the surface but also in subsurface layer (BS SoE, 2008). It is therefore recommended to revise the definition of the summer period to a definition of the phytoplankton growing season that takes into account the differences between regional seas, for instance by applying the seasonal periods that were defined for the WFD or by RSCs. Adjustments of the definition of the growing season per subregion are currently being evaluated and will be taken into consideration in the future revision of the indicator methodology.

c) Classification and geographical aggregation

In the current trend analysis stations are aggregated per country and attributed to a regional sea, and there is no distinction between sampling stations that are strongly influenced by anthropogenic eutrophication (e.g. transitional and coastal waters) and sampling stations that are not or only to a minor extent influenced by eutrophication. It is therefore recommended to replace the classification system per regional sea by a classification system that accounts for the geographical differences within the seas. The threshold/targets established by the RSCs are already being evaluated and will be taken in consideration in future improvements of the indicator methodology. As the implementation of the MSFD is still in progress, a future option might be to apply the environmental targets that are being developed under the MSFD. 

Status

In progress

Deadline

2016/06/01 00:00:00 GMT+2

Long term work

Work specified here will require more than 1 year (from now) to be completed.

General metadata

Responsibility and ownership

EEA Contact Info

Constança De Carvalho Belchior

Ownership

European Environment Agency (EEA)

Identification

Indicator code
CSI 023
MAR 006
Specification
Version id: 2
Primary theme: Marine Marine

Permalinks

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Frequency of updates

Updates are scheduled every 2 years

Classification

DPSIR: Pressure
Typology: Descriptive indicator (Type A - What is happening to the environment and to humans?)

Related content

Data used

Latest figures and vizualizations

Relevant policy documents

European Environment Agency (EEA)
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1050 Copenhagen K
Denmark
Phone: +45 3336 7100