1. Intercalibration Angiosperms Mediterranean
Presented by COAST coordinator W.Bonne at ECOSTAT 28 June 2011
Intercalibration Angiosperms Mediterranean
Teresa Alcoverro (coordinator)

2. The methods

3. Metrics Employed
PREI (5): shoot density, shoot leaf area, epiphyte biomass/leaf biomass, depth of the lower limit, type of the lower limit
POMI (14): shoot density, cover, percent plagiotrophic rhizomes, shoot surface, necrosis, nitrogen content rhizomes, sucrose content in the rhizomes, P rhizome, N content in epiphytes, Cu, Pb, Zn in rhizomes, N15 rhizomes, S34 in rhizomes
VALENCIA CS (9): shoot density, cover, dead matter, percent of plagiotrophic rhizomes, rhizomes burial/baring, shoot surface, necrosis, herbivore pressure, leaf epiphyte biomass

4. Integration Method PREI: Average of the metrics
POMI: Principal Components Analysis
Valencian CS: Principal Components Analysis

5. COASTAL WATERS – Mediterranean Sea GIG – Seagrasses
Member State
Full BQE method
Abundance a
Disturbance sensitive taxa
Diversity
Method tested against pressure
Spain, Croatia
POMI
Yes
Shoot density, meadow cover, shoot leaf surface
1 selected sensitive species, Posidonia oceanica + percent foliar necrosis, sucrose content in rhizomes, δ15N and δ34S isotopic ratio in rhizomes, N content in epiphytes, Pb content in rhizomes
No, only
1 species
Yes, with antropiza-tion index
Spain
Valencian-CS
Shoot density, meadow cover, dead matter cover, shoot leaf surface area
1 selected sensitive species, Posidonia oceanica + percent of plagiotropic rhizomes, rhizome baring/burial, percent of foliar necrosis, herbivore pressure, leaf epiphyte biomass
France, Italy, Cyprus
PREI
Shoot density, shoot leaf surface area, maximum depth of the meadow (lower limit), type of lower limit
1 selected sensitive species, Posidonia oceanica,+ ratio of epiphytic biomass and leaf biomass (E/L ratio)
No, only 1 species
Greece
No ?
???
Leaf length distribution asymmetry of 1 selected sensitive species Cymodocea nodosa
Malta No
Greece submitted justification for Cymodocea method

6. Participating Member States (that have provided data/information)
o Spain (All regions: only data from Catalonia and Valencia for Option 2)
o France (all data for Option 2)
o Croatia
o Cyprus
o Italy
o Greece (no Posidonia data)
o Malta (preliminary data 1st phase, not included in analysis)
(common metric 1st phase not applicable)
Intercalibration between the methods PREI (FR), CS (ES – Valencia) and POMI (ES, Catalonia)
Benchmarking with the other countries using the same method

7. Intercalibration of the methods
The methods: PREI, POMI and CS
Relationship between methods and pressures
Option 2: using an intercalibration common metric
Type of pressure: subtraction: Option 2_substraction
Determination of the benchmarks

8. How reference conditions are established
PREI: Average of the best 3 values for each metric
POMI: Average of the best 3 values for each metric
Valencian CS: Average of the best 3 values for each metric

9. The pressures
Anthropogenic pressures that have been observed to effect Posidonia oceanica ecosystems: eutrophication, organic matter and direct effects. All different integrated pressures will consider this factors.

10. Relationships with the pressures: PREI
Figure 1: Comparison of the mean σ + SE among the 3 POMI indices for each of the factors used in the study. White bars represent POMI 14, grey bars = POMI 9 and black bars = POMI met-mean. Horizontal dashed lines represent the 5 classifications of σ, adapted from Clarke and Hering (2006). ‘Very low’ σ signifies a mean SD which is less than 10 % of the status class range. Low σ signifies an SD of 11 to 29 % of the status class range, 30 % ≤ medium < 50 %, 50 % ≤ high < 100 % and very high indicates that the SD is greater than the range of the status class. <

11. Relationships with the pressures: CS
Figure 1: Comparison of the mean σ + SE among the 3 POMI indices for each of the factors used in the study. White bars represent POMI 14, grey bars = POMI 9 and black bars = POMI met-mean. Horizontal dashed lines represent the 5 classifications of σ, adapted from Clarke and Hering (2006). ‘Very low’ σ signifies a mean SD which is less than 10 % of the status class range. Low σ signifies an SD of 11 to 29 % of the status class range, 30 % ≤ medium < 50 %, 50 % ≤ high < 100 % and very high indicates that the SD is greater than the range of the status class. <
Pressures

12. Relationships with the pressures: POMI
Figure 1: Comparison of the mean σ + SE among the 3 POMI indices for each of the factors used in the study. White bars represent POMI 14, grey bars = POMI 9 and black bars = POMI met-mean. Horizontal dashed lines represent the 5 classifications of σ, adapted from Clarke and Hering (2006). ‘Very low’ σ signifies a mean SD which is less than 10 % of the status class range. Low σ signifies an SD of 11 to 29 % of the status class range, 30 % ≤ medium < 50 %, 50 % ≤ high < 100 % and very high indicates that the SD is greater than the range of the status class. <

13. Common metric: ICM
The intercalibration Common Metric: ICCM based in 2 metrics:
the lower limit type of the meadows and
leaf surface area per shoot integrated following the BiPo index (Lopez y Royo et al. 2008)

14. Determining a benchmark
We have defined benchmark sites as sites presenting very low pressures following the next criteria:
-low population density: no settlement in the next 3 km (or less than 100 habitats/ha within that area)
-mooring density lower than 2 mooring ha-1
-no harbour or mooring facility in 3 km
-no beach regeneration within 10 km
-no trawling in the area
-no industries within the 3 km
-no fish farms
-no desalination plants
-no evidence of meadow degradation due to other unconsidered impacts

15. Values of the benchmark in the different regions
POMI BALEARIC
POMI CATALONIA
POMI CROATIA
Average
0,85
0,79
0,81 SD
0,07
0,08
0,12
PREI FRANCE
PREI ITALY
0,77
0,76
0,02
0,11

16. Relationship between methods and ICM: PREI
Figure 2: Comparison of the mean σ + SE between POMI and PREI for each of the factors used in the study. White bars represent POMI and black bars represent PREI. Horizontal dashed lines represent the 5 classifications of σ, adapted from Clarke and Hering (2006). ‘Very low’ σ signifies a mean SD which is less than 10 % of the status class range. Low σ signifies an SD of 11 to 29 % of the status class range, 30 % ≤ moderate < 50 %, 50 % ≤ high < 100 % and very high indicates that the SD is greater than the range of the status class.
EQR PREI
Results extracted from IC_Opt2_subSeagrass MED.xlsx

17. Relationship between methods and ICM: CS
Figure 2: Comparison of the mean σ + SE between POMI and PREI for each of the factors used in the study. White bars represent POMI and black bars represent PREI. Horizontal dashed lines represent the 5 classifications of σ, adapted from Clarke and Hering (2006). ‘Very low’ σ signifies a mean SD which is less than 10 % of the status class range. Low σ signifies an SD of 11 to 29 % of the status class range, 30 % ≤ moderate < 50 %, 50 % ≤ high < 100 % and very high indicates that the SD is greater than the range of the status class.
EQR CS
Results extracted from IC_Opt2_subSeagrass MED.xlsx

18. Relationship between methods and ICM: POMI
Figure 2: Comparison of the mean σ + SE between POMI and PREI for each of the factors used in the study. White bars represent POMI and black bars represent PREI. Horizontal dashed lines represent the 5 classifications of σ, adapted from Clarke and Hering (2006). ‘Very low’ σ signifies a mean SD which is less than 10 % of the status class range. Low σ signifies an SD of 11 to 29 % of the status class range, 30 % ≤ moderate < 50 %, 50 % ≤ high < 100 % and very high indicates that the SD is greater than the range of the status class.
EQR POMI
Results extracted from IC_Opt2_subSeagrass MED.xlsx

19. Intercalibration process-substraction
Class boundaries of each national classification system are translated onto the ICCM, using the file IC_Opt2_subSEAGRASS MED.XLSX

20. Results

21. Results: acceptable ranges

22. Intercalibration with the rest of the countries-same method
We have done and ANOVA between benchmarks of each regions within each method

23. Final points
We consider this intercalibration phase to be finished for Spain, France, Italy, Cyprus, Croatia
Some countries have to do the intercalibration or use an ongoing method (Malta).
Greece has presented a new method cymo-skew that needs to be accepted by the commission. Intercalibration need to be performed in the next phase.

24. Final requests
Cyprus is invited to explain how they have taken into account potential differences from an island perspective (how is this reflected in the reference)
Italy is invited to explain their opinion why the PREI is similarly applicable in their territory
Amount of benchmark values is low – but it is the only group who has applied a common boundary setting procedure
Ecological characterization of G/M boundary

25. Coordination of group: Xavier Torras, Luisa Mangialajo
WG Macroalgae – CW
Presentation: S. Orfanidis
Coordination of group:
Xavier Torras, Luisa Mangialajo
(with the support of Paola Gennaro)

26. COASTAL WATERS – Mediterranean Sea GIG – Macroalgae and seagrasses
Member State
Full BQE method
Abundance a
Disturbance sensitive taxa
Diversity (non mandatory parameter)
Method tested against pressure
Croatia, France, Italy, Spain
(CARLIT)
Yes
Cover (length of coast in meters) of 9 preclassified sensitivity classes
Communities sorted into 9 sensitivity classes No
Against Land Use Simplified Index
Croatia, Cyprus, Greece, Slovenia (EEI)
Percentage cover (destructively collected sample cm2) of 5 preclassified sensitivity classes
Species sorted into 5 sensitivity classes
Malta -

27. Two Methods: CARLIT, EEI-c IC option 2: The common dataset
Validation workshop WFD: Intercalibration: Internet meeting (22 June 2011)
Two Methods: CARLIT, EEI-c
IC option 2: The common dataset
133 taxa (a reduced species list)
62 Sites [40 CARLIT, 22 (186 replicates) EEI-c] + 2 ideal Sites (Reference, Degrated)
SPAIN: 6 Benchmarks (median EQR 0.89), GREECE: 8 Benchmarks (median EQR 0.81) 27

28. Two Methods: CARLIT, EEI-c IC option 2: PCO analysis, ICM
Validation workshop WFD: Intercalibration: Internet meeting (22 June 2011)
Two Methods: CARLIT, EEI-c
IC option 2: PCO analysis, ICM
ICM
COMMA (Common macroalgae)
(the 1st axis of a multivariate analysis) 28

29. Two Methods: CARLIT, EEI-c IC option 2: ICM-Indices relationships
Validation workshop WFD: Intercalibration: Internet meeting (22 June 2011)
Two Methods: CARLIT, EEI-c
IC option 2: ICM-Indices relationships 29

30. Two Methods: CARLIT, EEI-c
Validation workshop WFD: Intercalibration: Internet meeting (22 June 2011)
Two Methods: CARLIT, EEI-c
IC option 2 H/G and G/M boundary EQR values 30

31. Two Methods: CARLIT, EEI-c IC option 2: INTERCALBRATION FINAL RESULTS
Validation workshop WFD: Intercalibration: Internet meeting (22 June 2011)
Two Methods: CARLIT, EEI-c
IC option 2: INTERCALBRATION FINAL RESULTS
(excel sheet IC_Opt2_sub v 1.24; MS_A=SPAIN, MS_B=GREECE) 31

32. Two Methods: CARLIT, EEI-c
Validation workshop WFD: Intercalibration: Internet meeting (22 June 2011)
Two Methods: CARLIT, EEI-c
IC option 2: NOT ANY ADJUSTMENT IS NEEDED! Why, any explanation??
Analysis of variance between the different benchmarks for each method (CARLIT, EEI-c) at a bilateral (Spain, Greece) scale
Average and standard deviation values for the different benchmarks at each country.
-The Benchmark EQR values were assessed by CARLIT (0.915) were higher than those of EEI-c (0.836) across Mediterranean Sea.
-This difference may due to different sampling strategies implemented: while the sampling of CARLIT method realized during the high growth period of Cystoseira species may estimate maximum EQR values of the benchmark sites, the sampling of EEI-c method realized during whole year may estimate average EQR values of the benchmark sites. 32

33. Pressure relationships: adjustment of pressure indexFR ES IT GR