Lakes Northern GIG Phytoplankton (comp) / Eutrophication FI: Ansa Pilke and Liisa Lepistö, Finnish Environment Institute NO: Dag Rosland, Norwegian National Pollution Control Authority Robert Ptacnik, NIVA, Anne Lyche Solheim, NIVA/JRC SE: Mikaela Gönzci, Swedish EPA and Eva Willèn, SLU UK: Geoff Phillips and Sian Davies, Environmental Agency for England and Wales IE: Deirdre Thierney, and Wayne Trodd, Irish EPA

Common metric: % Cyanobacteria, defined as % of total phytoplankton biovolume: All Cyanobacteria, excluding Chroococcales, but including Microcystis. The following genera are included: Achroonema, Anabaena, Aphanizomenon, Cylindrospermopsis, Gloeotrichia, Limnothrix, Lynbya, Oscillatoria, Phormidium, Planktolyngbya, Planktothrix, Pseudanabaena, Tychonema, Microcystis, Woronichinia. Only late summer samples used, max 4 obs./lake

No difference between clearwater types No difference between humic types proportion Cyanobacteria proportion Cyanobacteria But clearwater types different from humic types

Types aggregated to two major types: Type description Countries participating, LN1 Lowland, mod. alk., clear, shallow NO, UK, IE LN2a Lowland, low alk, clear, shallow NO, SE, FI, UK, IE LN2b Lowland, low alk, clear, deep NO, UK LN3a Lowland, low alk. mesohumic, shallow LN5a Boreal, low alk., clear, shallow (may also include high latitude lakes) NO, SE, LN6a Boreal, low alk., mesohumic, shallow LN8a Lowland, mod alk., mesohumic, shallow NO, SE (?), FI, UK, IE Clear Humic Latitude is maybe equally important in the Scandinavian countries LN8, not enough data

Setting reference conditions Using median of values from ref. lakes 170 ref.lakes from clearwater types 40 ref.lakes from humic lake types Ref. values: Clearwater lakes: 1% Cyanobacteria Humic lakes: 2% Cyanobacteria These values are also consistent with response curves for these two major types

Setting boundaries – starting point Could we use the response curves and agreed chla boundaries directly? Response curves not useful because: If using the agreed G/M chlorophyll boundaries, the corresponding % Cyanobacteria was so low (<5% for all types) that this would not represent any real change in the taxonomic composition of the phytoplankton community, and thus not be compliant with the normative definitions. Also the differences between the ref. value, H/G and G/M boundaries would be so small (1, 2 and 5% for Clearwater lakes, and virtually no difference for humic lakes due to a flat reponse curve, see Annex C), that it would be impossible to distinguish the different classes due to the uncertainty of analyses. Thus a different approach was developed

Setting boundaries – new probabilistic approach Divided all late summer samples (July – Sept.) into two groups: reference lakes with chla lower than the mean H/G boundary (< 4 µg/L in clear lakes and < 5 µg/L humic lakes) impacted lakes (from moderate to bad status) with chla higher than the mean G/M boundaries (> 7 µg/L in clear lakes and > 9 µg/L humic lakes) Box-plots used to show the statistical distribution of samples (proportion of observations) exceeding different values of % Cyanobacteria. Such box-plots were made for ref. lakes and for impact lakes for each major lake type. Different values of % Cyano were tested to find which ones that best would separate the reference samples and impact samples for the two major lake types.

clearwater Ref lakes = REF Impacted lakes = no-R humic Probability 0 0.2 0.4 0.6 Probability Ref lakes = REF Impacted lakes = no-R humic 0 0.1 0.2 0.3 Probability

Setting G/M boundaries Decided which value of % Cyanobactreria that could be used as the G/M boundary for each major lake type. Three criteria were used to make this decision: the mean probability of observations exceeding a certain value of % Cyanobacteria had to be close to zero for reference samples. This is based on the need for managers to be able to distinguish reference sites from clearly impacted sites (< good status) with a very high probability. the mean probability of observations exceeding a certain value of % Cyanobacteria had to be significantly different between reference samples and impact samples. the boundary value should be high enough to be compliant with the normative definitions, e.g. the % Cyanobacteria in the impacted sites should represent a real change in the taxonomic composition of the phytoplankton, and also represent a real risk for undesirable secondary impacts, such as Cyanotoxins. There was a general expert agreement within the NGIG group that this value should be at least 20% Cyanobacteria.

clearwater Ref lakes = REF Impacted lakes = no-R humic Probability 0 0.2 0.4 0.6 Probability Ref lakes = REF Impacted lakes = no-R humic 0 0.1 0.2 0.3 Probability

Setting boundaries – H/G boundaries and EQRs H/G boundary was judged from the need to distinguish ref. sites from impacted sites with an uncertainty in phytoplankton composition analyses that is at least 20%. The difference between the G/M and H/G boundary thus must be at least 20%. The final step was to calculate the EQRs. To avoid too low EQRs we normalized the ratio, using the following formula: EQR = (1- boundary value) / (1-ref.value).

Results (preliminary) Boundary Clearwater lakes Humic lakes Ref value 1% 2% H/G value 5% 10% H/G EQR 0.96 0.92 G/M value 25% 35% G/M EQR 0.76 0.66

Next steps untill July Testing common metric vs. national metrics for SE (ready now) and UK (expected ready in early May) New NGIG meeting in Oslo 25th May to discuss results of the tests and accept, adjust or reject the common metric and the preliminary boundaries Revise the milestone report before ECOSTAT in July