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  • 1.
    Ejhed, Heléne
    et al.
    Perfomers of environmental monitoring, Institutes, Swedish Environmental Research Institute, IVL.
    Widén-Nilsson,, Elin
    Perfomers of environmental monitoring, Universities, Swedish University of Agricultural Sciences, SLU.
    Tengdelius Brunell, Johanna
    Perfomers of environmental monitoring, Government Agencies, SMHI.
    Hytteborn, Julia
    SCB.
    Näringsbelastningen på Östersjön och Västerhavet 2014: Sveriges underlag till Helcoms sjätte Pollution Load Compilation2016Report (Other academic)
    Abstract [en]

    This report represents the latest, most detailed and reliable assessment of nutrient loads from Swedish sources yet made. This report, together with its background reports, presents results, source data and calculations techniques with a level of detail intended to achieve full transparency and traceability as well as to permit further use of this work in Swedish water management. 

    The Swedish Agency for Marine and Water Management gave SMED the task of evaluating sources of nitrogen- and phosphorus loads for the year 2014 and assessing the magnitude of those loads on lakes, water courses and the sea across Sweden. The aim was to produce the basis for Sweden’s national reporting to the Helcom ’Pollution Load Compilation 6 – PLC 6’ and to support water management work in Sweden. Similar calculations have been made previously but never with such high resolution in the input data. The work required processing and analysis of large amounts data to give complete information for the whole of Sweden, divided up into approximately 23 000 water bodies. 

    This increased resolution, together with the improved quality of input data and newly developed calculation routines provide more reliable estimates of total loads even at the local scale. The development work that has been completed will form the basis of the next load assessment report, PLC 7, the indepth evaluation of the national environmental target ’Zero eutrophication’ and future work within marine and water management. 

    The new calculations make use of new, high resolution land-use and soiltype maps, new data concerning purification in off-mains sewerage and storm water as well as a new height database (with 2 metres horizontal resolution). The height database has been used to calculate slope steepness, which is of great importance for estimates of phosphorus leakage. New observations in forest areas in southwestern Sweden have provided a better understanding of nutrient leakage in woodland areas and a new nutrient retention model has been developed as a result. These improved input data and high resolution calculation tools improve certainty in the results even at a local scale for individual water bodies. The results are made publically available through a new web tool, ’Technical Calculation System: Water’ (TBV, tbv.smhi.se).

    The results are presented in terms of gross- and net loads. Gross loads are the amount of nutrients released at source to a water body or lake from for example a sewage treatment works or an agricultural field. Net loads are the proportion of the gross loads that reach the sea. Additionally, results are presented as anthropogenic and total loads. Anthropogenic loads come from human activities, such as crop production in agriculture or emissions from industry. Total loads are the sum of the anthropogenic loads and background loads, which are the natural loads which would occur even if people were not present. The boundary between what is background and what are anthropogenic loads is based on the Helcom definition where all soil use contributes with both a natural load and possibly also an anthropogenic load. For example loads from landuse covered with forest are considered background, while loads from a clearcut or agriculture are considered the sum of both anthropogenic and background loads. In results where only anthropogenic loads are presented, the background loads have been taken away.

    Agricultural and forest land are the two largest sources of total loads to the sea for both nitrogen and phosphorus, with 34 100 and 34 900 tonnes of nitrogen and 1 100 and 850 tonnes of phosphorus, respectively during 2014. Together, these sources account for roughly 60% of the total load. For anthropogenic loads, agriculture is the largest source (23 300 tonnes nitrogen and 460 tonnes phosphorus), followed by emissions from sewage treatment works (14 000 tonnes of nitrogen and 240 tonnes of phosphorus). Loads from forest soils contribute only to the background loads while clear cuts, which a classed as an anthropogenic load contribute with only about 1500 tonnes of nitrogen and 20 tonnes of phosphorus. 

    The Bothnian Sea, Baltic Proper and Kattegat are those sea areas which receive the most nitrogen from Sweden’s total loads (29 500 tonnes, 29 400 tonnes and 28 700 tonnes respectively, or approximately 25% each). In the Bothnian Sea however, the greater part of this load is ’natural’ background loads. The Baltic Proper and Kattegat receive the most anthropogenic nitrogen, 33% and 31% respectively.  For phosphorus, most goes to the Bothnian Sea (990 tonnes or 30% of the total load). Just under a quarter reaches the Baltic Proper (780 tonnes) and about a fifth reaches the Kattegat and the Bothnian Sea (680 and 630 tonnes respectively). 

    The Baltic Sea Action Plan (BSAP) provides emissions targets, with the aim of achieving good environmental status in the Baltic Sea (including the Kattegat). According to this analysis, the target for phosphorus is achieved in all basins except the Baltic Proper, where the target is extremely challenging and it will be difficult to reduce the phosphorus loads under the load ceiling (308 tonnes).This requires substantial measures on the anthropogenic load, but further challenging, is that the background loads are a significant proportion of the total load. Total net phosphorus load to the Baltic Proper is 780 tonnes per year according to these calculations, of which 370 tonnes are background loads. This requires therefore that measures must even reduce the background load, for example through creation of wetlands. For even the Baltic  Proper to achieve good environmental status with regard to eutrophication, measures will be required in all sub-basins of the Baltic Sea.  Because of the major changes in methods and input data, it is not possible to directly compare how loads have changed since PLC 5 (based on 2006 data) or the in-depth analysis of the national environmental target ’Zero eutrophication’ (based on 2011 data). For example, the total area of agricultural land has fallen by 1900 km2 since 2006, which leads to a reduction in the estimated nutrient losses. The magnitude of this reduction cannot presently be read from the calculations as they have been made with higher resolution in data compared with earlier years. At the same time, the new calculations show that the anthropogenic part is lower than earlier calculated. Recalculation of the older PLC data with the new methods is necessary to clarify how much of the observed changes result from measures within farming and how much is due to the improved input data and calculations. Nutrient loads from point sources are calculated in the same way as before and for these it is clear that discharges have reduced. In PLC 6 (2014) sewage treatment works were responsible for 240 tonnes of phosphorus and 14 000 tonnes of nitrogen, while in PLC 5 (2006) loads were 350 tonnes of phosphorus and 17 000 tonnes of nitrogen (net). Industry have also reduced their impact and are responsible for 250 tonnes of phosphorus and 3 800 tonnes of nitrogen, compared with 320 tonnes phosphorus and 4 800 tonnes nitrogen in 2006.

  • 2.
    Karlson, Bengt
    Perfomers of environmental monitoring, Government Agencies, SMHI.
    Monitoring Methods of Phytoplankton in the Baltic Sea and Kattegat-Skagerrak2014Report (Other academic)
    Abstract [en]

    The aim of the report is to give input to the revision of the Swedish National Marine Monitoring Program with regard to phytoplankton. The Swedish environmental objectives, the EU Marine Strategy Framework Directive, the Water Directive as well as the Helsinki and Oslo-Paris conventions all include requirements for phytoplankton monitoring. In areas where aquaculture is carried out special demands for monitoring harmful algae, i.e. biotoxin producing species, are in effect (EU hygiene directive). Climate change also result in needs for improved phytoplankton monitoring.

    A summary of suggestions:

    1. Use caution when making changes in long term monitoring programs. Do not change methodology if there are long time series based on a certain method; instead add new methods and new parameters.

    Changes that can be implemented in year 2015

    2. Continue using existing analysis method for phytoplankton (the Utermöhl method) but add analysis of large volume samples to get better data on rare species and micro-zooplankton.

    3. Use carbon as the unit for phytoplankton biomass instead of bio-volume.

    4. Make sure that the same methods are used in all sea areas surrounding Sweden. a. Add analysis of autotrophic picoplankton where this is missing (the Baltic Proper, the Kattegat and the Skagerrak) b. Chlorophyll analyses should be made both on samples collected using tube sampling and samples collected at discrete depths (the Gulf of Bothnia is the sea area that differ from the others)

    5. High frequent sampling should be carried out at sentinel sites every two weeks, weekly during algal blooms.

    6. All major sea basins surrounding Sweden should have one high frequent off shore sentinel site and one high frequent coastal sentinel site for high quality phytoplankton monitoring for biodiversity, cell numbers and biomass based on cell volume measurements. In addition high frequent sampling for chlorophyll should be carried out at three off shore and three coastal sites in each major basin.

    7. Use FerryBox-systems to increase the water sampling frequency and to measure chlorophyll fluorescence, a proxy for phytoplankton biomass.

    8. Measure the fluorescence for phycocyanin when doing CTD-casts during monitoring cruises with research vessels to get information on the vertical distribution of cyanobacteria.

    9. Carry out measurements of irradiance in air and in water when making CTD-casts during monitoring cruises to calculate the attenuation coefficient at selected wavelengths.

    Changes that should be evaluated during one to three years to be fully implemented e.g. in 2018

    10. Document phytoplankton using digital photography during microscopy. Save images at the national data host archive

    11. Save phytoplankton in a sample bank for future analysis using methids unknown today.

    12. Use automated imaging flow cytometry for phytoplankton analysis as a complement to microscopy.

    13. Use molecular biological methodology, e.g. 16S and 18S rDNA barcoding, as a complement to biodiversity analysis methods based on analysing morphology of organisms.

    14. Use the new network of coastal instrumented buoys around the coast of Sweden to measure chlorophyll fluorescence, light attenuation at selected wavelength (~Secchi depth) and for automated water sampling for phytoplankton analysis.

    15. Integrate satellite remote sensing of ocean colour for estimating chlorophyll a, the distribution of cyanobacteria blooms and blooms of coccolithophorids in the National Marine Monitoring Programme. The new ESA satellites Sentinel 3a and 3b are planned to be launched at the earliest in April 2015. The quality of data must be compared to data from in situ sampling.  

  • 3.
    Karlson, Bengt
    et al.
    Perfomers of environmental monitoring, Government Agencies, SMHI.
    Mohlin, Malin
    Hu, Yue O. O.
    Andersson, Anders F.
    Miljöövervakning av växtplankton i Kattegatt och Östersjön med rDNA-barcoding och mikroskopi: En jämförelse av molekylärbiologisk metodik och mikroskopi2018Report (Other academic)
    Abstract [en]

    Phytoplankton is a fundamental part of the marine food web. Therefore, a national monitoring programme that is focused on the spatial and temporal distribution of phytoplankton in the sea around Sweden is ongoing. The design of surveillance is based on EU directives and intergovernmental conventions. Since some algal blooms can be harmful, there is a special focus on the algae that produces toxins and are potentially harmful in other ways. To carry out the monitoring in a cost effective way, several methods are conducted. This report presents a comparison of the results yielded by microscope-based analysis and rDNA metabarcoding-based analysis. Sampling was done with the help of a Ferrybox system in July 2013 in eighteen locations along a salinity gradient (3 - 24‰) from the Bothnian Bay through the Bothnian Sea and the Baltic Proper to the Kattegat. Results of rDNA metabarcoding showed a much greater biodiversity compared to the result from microscopic counting (Utermöhl method). In total, only 89 organisms were identified by Utermöhl method and the rest were marked as "unidentified flagellates" and "unidentified unicellular organisms". rDNA metabarcoding recorded a total number of almost 2,000 different organisms (excluding heterotrophic bacteria), which means that more than 95% of biodiversity was overlooked by Utermöhl method. Altogether 36 Operational Taxonomic Units (OTUs) were identified as cyanobacteria from the prokaryotes data (16S rDNA) and 1860 different OTUs were found in eukaryotes data (18S rDNA). There were still several organisms missing from the list that microscopic counting yielded. This result suggests that the reference databases for the 16S and 18S rDNA sequences lack some species common in the seas surrounding Sweden. Another reason may be that the 18S rDNA is identical to other species or a genus leading to that the classification is at a higher taxonomic level. Metabarcoding provides different types of data than microscopic counting. The rDNA-based data can offer a high resolution on biodiversity but cannot offer data on cell counts and biomass as microscopic counting does. An alternative molecular biological method is known as quantitative PCR (qPCR) which can determine the amount of DNA from individual organisms so that the cell count of the organisms can be inferred. At present it is only possible to perform qPCR on a small number of organisms in a sample. The authors suggest introducing the rDNA metabarcoding approach of plankton analysis in Swedish marine monitoring programs as a complement to other methods. Besides its advantage regarding the high resolution on biodiversity, rDNA barcoding has a low price per sample when many samples are analysed in one go, and it is not dependent on the taxonomists’ skill on identifying organisms. The plan includes the following elements: 1. Pilot study - rDNA data from a full year should be compared with microscopy and flow cytometry data; 2: Sequencing of the common species in the Baltic that are missing in the reference databases; 3: Standardization of sampling protocols; 4: Standardization of sequencing method; 5: Developing qPCR method targeting selected harmful species; 6: Standardization of sequencing data and comparing it with the available reference databases; 7: Structuring the data management system for the monitoring data and 8: Development of the assessment of the environmental status regarding biodiversity and invasive species based on rDNA data.

  • 4.
    Karlson, Bengt
    et al.
    Perfomers of environmental monitoring, Government Agencies, SMHI.
    Strömberg, Patrik
    Perfomers of environmental monitoring, Government Agencies, SMHI.
    Skjevik, Ann-Turi
    Perfomers of environmental monitoring, Government Agencies, SMHI.
    Variability and Trends of Phytoplankton in the Baltic Sea and Kattegat-Skagerrak2015Report (Other academic)
    Abstract [en]

    The aim of the report is to describe results from analyses of time series of phytoplankton data from the Swedish marine monitoring programs. One issue is if it is possible to describe environmental change with the current sampling frequency. The three main aims are: (I) to investigate the statistical strength of time series of phytoplankton biomass, (II) to investigate the variability of species composition between stations and (III) to investigate the temporal variability regarding species composition. Results indicate how long time series are needed to detect change at a certain level. Also the variability in biodiversity is shown with some examples.  

    To quantify the biomass of phytoplankton different parameters may be investigated, e.g. chlorophyll content and the biovolume of phytoplankton. Chlorophyll a is designated in directives for describing the environmental status of the seas as an indicator for eutrophication. Sampling for chlorophyll is usually made using two different methods in the seas surrounding Sweden. Samples are collected using a hose, normally from 0-10 m depth, or by sampling at discrete depths, e.g. 1, 5 and 10 m. No difference was observed when comparing data from the hose sampling with depth-averaged data from the discrete depths. Thus the data from hose-sampling can be used together with the data based on sampling at discrete depths. To investigate if chlorophyll a works as a proxy for phytoplankton biomass data on total biovolume of phytoplankton, based on cell counts and cell volume estimates, was compared to chlorophyll a data. The data set include data from 1983 to 2014. A large part of the data emanates from 2010 and later. In the investigated data set there is a significant, but weak, correlation between chlorophyll a and total biovolume (n= 3119, p <0.01, R2 = 0.439).  

    Results about the statistical strength (power) of the time series of total biovolume of phytoplankton indicate that it on average takes 23 years to detect a change of 1% (p<0.01, power = 80%). A change of 10% is detected after 7 years and a change of 40% is detected in 5 years. Results regarding the statistical strength of time series of chlorophyll a show that it on average takes 33 years to detect a change of 1%. A change of 10% is detected after 14 years and a change of 40% in 7 years. Please note that these figures are based on data from monitoring programs that include the variability observed. When the data set was divided into geographical areas called the type areas it was evident that the amount of available data in the different type areas varies a lot. In some areas there is not enough data to carry out an analysis of the statistical strength. Another conclusion is that there is substantially less data on phytoplankton biodiversity and biomass based on cell counts and cell volume estimates compared to the amount of data on chlorophyll a.  

    Data was also split according to sea basins to show the statistical strength in the data if sampling frequency continues as up to now. To detect a change of Swedish Agency for Marine and Water Management report 2015:33  8 5% of chlorophyll a with the power of 80% the number of years needed if the present sampling frequency continues is on average:

    - The Kattegat-Skagerrak: 16 years

    - The Sound and the Southern Baltic Proper: 11 years

    - The Baltic Proper: 7->50 years

    - The Bothnian Sea: 19-41 years

    - The Bothnian Bay: 13-35 years  

    To investigate differences in biodiversity, data from intense sampling campaigns made in the period 2010-2012 was used. The sampling was made at a much larger number of locations compared to the normal monitoring program. Results of cluster analysis (Euclidian distance) on the species composition show that weekly sampling describes the natural variability in phytoplankton biodiversity well while sampling once a month does not resolve the natural variability in biodiversity. When investigating the spatial variability, i.e. the differences in species composition between stations, results indicate that samples from the same water mass, e.g. the southern Kattegat, are similar. The differences in closely located bays and fjords are large in regard to plankton biodiversity.

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