Warsaw 16-17. March 201 6

1. Final results of the Lake Phytoplankton Intercalibration in the Eastern Continental GIG Gábor Borics, Gabriel Chiriac, Detelina Belkinova, Karl Donabaum, Gábor Várbíró, Andrea Zagyva and Georg Wolfram Warsaw16-17. March 2016

2. Countries and experts involved Bulgaria: Georg Wolfram, Detelina Belkinova, Karl Donabaum, Hungary: Gábor Borics, Gábor Várbíró, Andrea Zagyva Romania: Gabriel Chiriac, Levente Nagy, Stephan Miron JRC: Sandra Poikane, Laurence Carvalho

3. EasternContinental GIG HU RO BG

4. Common IC types

5. Difficulties Weak relationship between the nutrients and the biomass and composition metrics Significant differences between the philosophy of the national assessment methods Lack of reference lakes

6. Combinedstressordevelopment • Lake group 1: no fishing/angling activity and no artificial stocking of fish, fish abundance < 50 kg ha-1; Stressor value: 0.33 • Lake group 2: moderate fishing/angling activity with occasional artificial fish stocking, fish abundance is between 50 and 200 kg ha-1;Stressor value: 0.66 • Lake group 3: intensive fishing/angling, regular fish stocking, fish abundance > 200 kg ha-1.Stressor value: 1.00

7. Combinedstressordevelopment Using polynomial and/or piecewise linear transformation, each concentration are converted to normalized scale. Lake-use categories were also described by numerical values (LG1:0.33; LG2: 0.66; LG3:1.0). Combined stressor = NormTP +NormTN+NormCOD +NormLakeuse (range 0.5 -- 4).

8. Combinedstressor -- Chl-arelationship Distribution of growing season average chlorophyll-a concentrations along different values of the combined stressor.

9. Database Number of lake years: 80

10. Option 1 wasapplied The Hungarian metric HLPI was proposed to apply Composition metric: Biomass metric (Chl-a): Multimetric index: Bloom metric as absolute abundance of cyanobacteria

11. Leastdisturbedsitesas benchmark siteswereselected Criteria used for benchmark lake selection • no major point sources in catchment,complete zonation of the macrophytes in the littoral zone, • no (or insignificant) artificial modifications of the shore line, • no mass recreation (camping, swimming, rowing) • low/moderate fishing (fish standing stock <50 kg ha–1) • Based on TP, TN, COD values and intensity of fishing a combined stressor was developed. The stressor ranges from 0–4. Lakes considered as alternative benchmark sites have a combined stressor value <1.5. This means that: • Fishing is low (fish stock <50 kg ha–1) • Vegetation period mean TP <115 µg l-1 • Vegetation period mean TN <1550 µg l-1

12. Statistics on benchmark sites and highly disturbed sites for chlorophyll-a and the Q index.

13. Validation of theChl-a H/G boundary Multiple regression modell proposed to this lake group (Borics et al., 2013). The used formula is: LogChl-a = -0,087×log depth+ 0.0424×log TP+ 0.149×logTN+0.62×lake use + 0.051 Modell inputs: 25th percentile of the TP (76 µgl-1) 25th percentile of the TN (400 µgl-1) Lake use 1 Depth 3,0 m Chl-a value estimated by the model : 12.43 µgl-1. Proposed H/G boundary value derived from the benchmark lakes population (11.8 µgl-1).

14. Validation of theChl-aG/M boundary Ecological importance: Chl-a > ~ 25 µgl-1 increases the risk of development of anaerobic conditions in the Z > ~ 3m regions of lakes (Zeu=2.5×ZSD).

15. Chlorophyll-a and EQR boundaries EQRChl-a = IF(X>200; 0; IF(X<105.1;-0.000002444 X3 + 0.0004479 X2 – 0.0294 X + 1.089; -0.002 X + 0.3949)) X: Chl-a (µgl-1)

16. Setting of M/P and P/B boundariesforthecompositionmetric Relationship between the relative abundance of cyanobacteria and Q metric 50% of Cyanobacteria defined the MP boundary (Q = 0.40), 80% of Cyanobacteria was used a threshold to define the PB boundary (Q = 0.2).

17. Q metrics and EQR class boundaries EQRQ =IF(Q>0.4; 5.511 × Q3 -11.971 × Q2 + 9.1614 × Q – 1.7019;Q)

18. Stressor-metricrelationships (benchmark lakes and others)

19. Stressor-metricrelationships(countries’ data)

20. Long-awaitedremarks of thereviewer I’ve had a look at the new report.  I think it is a big improvement.  The HG and GM boundaries for Chl-a are much better aligned to similar lake types in Central Europe and fit well with the evidence from the EC GIG benchmark lakes. I also think your text justification of reference criteria and description of ox-bow lake functioning is clearer and justifies the criteria you have used better. I’m not sure about the “IC correctness” of using macrophyte dominance as a selection criterion, but I agree that low fish stocking is very important. I think the use of the 25th/75th percentiles for Chl & the Q Index HG boundaries are a much better choice and that an equivalent TP boundary of about 76 µg/L is much more aligned to values elsewhere in Europe.  The compositional changes used to define the MP & PB boundary for the Q Index also seem sensible. There are a couple of minor discrepancies between the main report and Annex (e.g. 25th % of TP 65 in A-4 but 76 on p.5 of the main report?)  , but this is nothing substantial to be concerned over.

21. Thanks for the attention!

22. Thanks for the attention!

23. Reference condition criteria for selection of lake reference sites in Hungary and Romania

24. Nutrient Chl-a relationship for EC lakes

27. Crucialquestion: dothelakesconsideredas benchmark lakesbelongtothereferencelakesoraretheyonlyleast-disturbedsiteswithunknown status?

28. Relationshipbetweenthelanduse and Log chl-a (EC GIG Lakes)

29. Paleolimnologicalevidences

30. Reviewer’sconcernsontheprevious (July, 2015) version of the EC GIG lakephytoplanktonreport • Setting of thereferenceconditions • No landusecriteriawereapplied • High TP values (asselectioncriteria) wereused • Setting of the H/G and G/M boundaries • The boundariesareinfluencedbythevalues of thereferencelakepopulations (whicharequestionable) • In summary, the general approach is good, but the process of boundary-setting is based on a questionable set of reference lakes. The Chl-a reference conditions, H/G and G/M boundary all appear too high in comparison to other similar lake types in central Europe. Without some strong evidence to suggest the biology is still in reference conditions (e.g. palaeolimnology), then the “reference” sites used appear to be more in line with the concept of “Least Disturbed Conditions” (LDC) (CIS, 2010) that refer to the best available sites. This is acceptable for intercalibration, but it is important to identify the position of the benchmark on the gradient of impact to document the deviation of the selected benchmark from reference conditions (CIS, 2010). This is important for boundary-setting and cross-GIG harmonisation efforts for benchmarking.

31. Reviewer’srecommendations 1) Provide more information on land-use and population criteria for individual reference lakes 2) Provide independent palaeolimnological data which demonstrate no significant change over the last 100 years in one or more reference lakes 3) Consider developing a lake-type specific reference model that incorporates flushing effects and compare with reference Chl-a values estimated using other site-specific models (e.g. Carvalho et al., 2009). 4) If above options suggest they are impacted, re-designate them as “alternative benchmark” lakes for use in IC comparison and consider implications for H/G and G/M boundaries