phytoplankton groups Andres Jaanus & Elise Joonas, Estonian - - PowerPoint PPT Presentation

Seasonal succession of functional phytoplankton groups

Andres Jaanus & Elise Joonas, Estonian Marine Institute, University of Tartu

• Phytoplankton – the key primary producer in marine ecosystems
• Functionally diverse groups
• Seasonal cycle
• No Baltic wide phytoplankton species composition based indicator so far

Seasonal succession of functional phytoplankton groups

• HELCOM Assessment Unit

Level: 3, 4

• The indicator is applicable in: all

coastal areas around the Baltic Sea / open sea

• Test areas: Southern Gulf of

Finland, coastal Gulf of Gdansk

• Data provided: northern Gulf of

Finland, Gulf of Riga, (Curonian Lagoon)

Seasonal succession of functional phytoplankton groups

Analysis description

1) Wet weight biomasses of four major functional groups, including cyanobacteria, dinoflagellates, diatoms and the autotrophic ciliate Mesodinium rubrum are averaged for each month over a sampling year. 2) Skewed data is accounted for by the transformation of phytoplankton biomass

• n a natural log scale (ln bm).

3) Monthly mean and standard deviations are calculated for each functional group 4) Monthly Z scores are calculated by subtracting the overall mean from the

• verall monthly mean of the reference period and dividing with overall stdev.

5) Acceptable deviations for monthly values are calculated (Z-scores ±1/2 stdev) A positive Z score indicates that the observation is greater than the mean and a negative score indicates that the observation is less than the mean. 6) Type-specific reference curves are established (mean and ±acceptable deviations)

Seasonal succession of functional phytoplankton groups

Assessment procedure 1) Data points are calculated as in 4 of analysis description, the overall monthly means are replaced with the monthly means of the reference period. 2) The score is based on the number of data points from the test area which fall within the acceptable deviation range set for each monthly point of the reference growth curve 3) Percentage based thresholds are established for each functional group to determine GES boundary (EQR values) for the assessment of the ecological status The GES boundary in the southern Gulf of Finland has preliminarily set at EQR value 0.67

Seasonal succession of functional phytoplankton groups

• Tested in the Gulf of

Finland, Gulf of Gdansk

• GES is determined by the
• no. of observations falling

inside the reference envelope (EQR)

• EQRGES/sub-GES=0.67 (may

be different in different sub-basins)

• 3
• 1

1 3 4 5 6 7 8 9 10

ln biomass, µg l-1

Reference envelope (mean ± 0.5 SD), diatoms, Tallinn Bay

zmonth Zmonth+0.5 SD Zmonth-0.5 SD 2009 2010 2011 2012 2013 mean SD year 2.83 3.02 month mean SD n SE zmonth Zmonth+0. 5 SD Zmonth-0.5 SD 2009 2010 2011 2012 2013 4 6.91 1.38 38 0.22 1.35 1.85 0.85 1.39 1.52 1.80 1.85 1.53 5 5.17 2.44 71 0.29 0.78 1.28 0.28 0.51 0.50 1.03 1.46 0.05 6 2.10 2.34 69 0.28

• 0.24

0.26

• 0.74

0.14

• 0.33
• 1.38
• 0.04

0.31 7 0.88 2.77 74 0.32

• 0.65
• 0.15
• 1.15
• 1.84
• 0.17
• 0.44
• 0.31
• 0.47

8 1.36 2.75 73 0.32

• 0.49

0.01

• 0.99
• 0.21
• 0.14
• 0.12

0.02 0.24 9 2.91 1.92 40 0.30 0.03 0.53

• 0.47
• 0.04
• 0.14
• 0.48

1.02 0.15 10 3.39 1.97 41 0.31 0.19 0.69

• 0.31
• 0.06

0.60

• 0.15

0.32 0.80

Seasonal succession of functional phytoplankton groups

• Concept and analysis design in place
• Technical guidelines in place
• Assessment method available and described
• Definition of reference conditions based on expert judgment
• GES proposed, but needs more supporting data and discussion
• Requirements for datasets:

– at least monthly sampling to design reference growth curves (time-series of at least 10 years needed) – Should be focused on areas/sites with historical datasets – Data submission arrangements to be incorporated into the indicator should be discussed, preliminary strategy and schedule agreed among experts - TM, HELCOM

Seasonal succession of functional phytoplankton groups

List of issues that still need to be solved for the indicator Describe what is hindering solving the issue

Low confidence in the result Funding for data collection and analysis is still unsecure and the amount of data needed for the analysis has not yet been met. Low number of sites/basins meeting the criteria Insufficient monitoring frequency, too short time-series Weak coordination of monitoring activities in the open sea areas