Wur2008c

Wur2008c
The impact of ocean acidification on microbial
dynamics and activities - a mesocosm study
in the Baltic Sea
Diplomarbeit
im Diplomstudiengang Marine Umweltwissenschaften
am Institut für Chemie und Biologie des Meeres
der Carl von Ossietzky Universität Oldenburg
vorgelegt von
Mascha Wurst
Erster und betreuender Gutachter:
Dr. Mirko Lunau
(AWI, Bremerhaven)
Zweiter Gutachter:
Prof. Dr. Wolfgang Ebenhöh
(ICBM, Oldenburg)
Oldenburg, 20. April 2008
CONTENTS
Contents
LIST OF FIGURES ........................................................................................... IV
LIST OF TABLES ............................................................................................. IX
ABBREVIATIONS ............................................................................................. X
1
INTRODUCTION ........................................................................................ 1
CARBONATE SYSTEM ......................................................................................... 3
THE MARINE CARBON CYCLE .............................................................................. 5
MARINE PRIMARY PRODUCTION .......................................................................... 7
MICROBIAL LOOP............................................................................................... 8
HOW TO STUDY THE EFFECTS OF RISING CO2 CONCENTRATION ON MARINE
ENVIRONMENTS?...............................................................................................
9
THIS STUDY .................................................................................................... 10
2
MATERIALS AND METHODS ............................................................. - 13 SETUP AND SAMPLING ..................................................................................- 13 MEASUREMENTS AND ANALYSES ...................................................................- 15 PHYSICOCHEMICAL PARAMETERS ..................................................................- 15 BIOGEOCHEMICAL PARAMETERS ....................................................................- 15 AMINO ACIDS ...............................................................................................- 16 TRANSPARENT EXOPOLYMER PARTICLES .......................................................- 18 PLANKTON ABUNDANCES ..............................................................................- 19 DIAZOTROPHIC CYANOBACTERIA DYNAMICS ....................................................- 19 PHYTOPLANKTON ACTIVITY ...........................................................................- 19 BACTERIAL DYNAMICS ..................................................................................- 20 HYDROLYTIC ENZYME ACTIVITIES ...................................................................- 21 BACTERIAL ACTIVITIES ..................................................................................- 23 CALCULATION OF GROWTH RATES .................................................................- 24 STATISTICAL ANALYSES ................................................................................- 24 -
3
RESULTS ............................................................................................. - 25 -
I
CONTENTS
EXPERIMENTAL BOUNDARY CONDITIONS ........................................................- 25 VERTICAL DISTRIBUTIONS (CTD MEASUREMENTS)..........................................- 26 TEMPERATURE.............................................................................................- 26 SALINITY .....................................................................................................- 28 PH AND PCO2 ..............................................................................................- 29 -
THE PH AND PCO2 HISTORY OF EVERY SINGLE MESOCOSM .............................- 32 BIOGEOCHEMICAL PROCESSES .....................................................................- 35 PARTICULATE ORGANIC MATTER (POM)........................................................- 35 C:N:P RATIO ...............................................................................................- 38 CHLOROPHYLL A AND NUTRIENTS ..................................................................- 41 AMINO ACIDS ...............................................................................................- 42 TRANSPARENT EXOPOLYMER PARTICLES ......................................................- 43 EUKARYOTIC PHYTOPLANKTON DYNAMICS .....................................................- 44 DIAZOTROPHIC CYANOBACTERIA DYNAMICS ...................................................- 45 PHYTOPLANKTON ACTIVITY ...........................................................................- 47 CO2 UPTAKE ................................................................................................- 47 N2 FIXATION .................................................................................................- 48 UNICELLULAR CYANOBACTERIA ....................................................................- 50 BACTERIAL DYNAMICS ..................................................................................- 51 HYDROLYTIC ENZYME ACTIVITIES...................................................................- 53 Α-GLUCOSIDASE ...........................................................................................- 53 -
LEUCINE-AMINOPEPTIDASE ...........................................................................- 54 ALKALINE PHOSPHATASE ..............................................................................- 55 BACTERIAL ACTIVITIES .................................................................................- 56 GROWTH RATES...........................................................................................- 57 4
DISCUSSION AND CONCLUSION...................................................... - 60 EXPERIMENTAL SETUP..................................................................................- 60 EFFECTS OF INCREASING PCO2 ON BIOGEOCHEMICAL PROCESSES ..................- 62 EFFECTS OF INCREASING PCO2 ON MICROBIAL DYNAMICS AND ACTIVITIES .......- 66 CONCLUSIONS .............................................................................................- 70 -
ACKNOWLEDGEMENTS............................................................................ - 71 -
II
CONTENTS
APPENDIX................................................................................................... - 72 REFERENCES............................................................................................. - 75 -
III
LIST OF FIGURES
List of Figures
FIGURE 1: SCHEMATIC VIEW OF THE COMPONENTS OF THE CLIMATE SYSTEM (BOLD),
THEIR PROCESSES AND INTERACTIONS (THIN ARROWS) AND SOME ASPECTS THAT
MAY CHANGE (BOLD ARROWS) (AFTER HOUGHTON ET AL. 2001)........................
1
FIGURE 2: SCHEMATIC ILLUSTRATION OF THE CARBONATE SYSTEM IN THE OCEAN. CO2
IS EXCHANGED BETWEEN ATMOSPHERE AND OCEAN VIA EQUILIBRATION OF CO2
(G) AND DISSOLVED CO2. DISSOLVED CO2 IS PART OF THE CARBONATE SYSTEM IN
-
SEAWATER THAT INCLUDES BICARBONATE, HCO3 , AND CARBONATE ION, CO3
2-
(AFTER ZEEBE AND WOLF-GLADROW 2001). ................................................... 4
FIGURE 3: CYCLING OF ORGANIC MATTER AND MICROBIAL LOOP. INTERPLAY BETWEEN
LIGHT, NUTRIENTS, TEMPERATURE, PRIMARY PRODUCTION OF PHYTOPLANKTON
(CARBON DIOXIDE (CO2) UPTAKE, NITROGEN (N2) FIXATION), RESPIRATION OF
OXYGEN (O2), EXPORT OF PARTICULATE ORGANIC MATTER (POM), RELEASE OF
DISSOLVED ORGANIC MATTER (DOM) AND BACTERIAL DEGRADATION PROCESSES
OF DOM & POM (HYDROLYTIC ENZYME ACTIVITY (HEA), AND UPTAKE OF
MONOMERIC DOM). THE DOM POOL CONSISTS OF DISSOLVED ORGANIC
NITROGEN (DON, MAINLY AMINO ACIDS (AA)), DISSOLVED ORGANIC CARBON
(DOC, MAINLY CARBOHYDRATES (CHO), AA, AND LIPIDS (L)) AND DISSOLVED
ORGANIC PHOSPHOROUS (DOP). TRANSPARENT EXOPOLYMER PARICLES (TEP)
FORM FROM DOM PRECURSORS AND SUBSEQUENTLY PROMOTE SEDIMENTATION
AND EXPORT OF POM. THE POM POOL CONSISTS OF PARTICULATE ORGANIC
CARBON (POC), PARTICULATE ORGANIC NITROGEN (PON) AND PARTICULATE
ORGANIC PHOSPHOROUS (POP) (M. LUNAU, AWI BREMERHAVEN). ................
12
FIGURE 4: MAP OF NORTHERN EUROPE (INSET) AND OF THE BALTIC SEA INCLUDING
THE SAMPLING AREA (MAP SOURCE: GOOGLE.MAPS); DRIFT OF THE MESOCOSMS
DURING THE EXPERIMENT (11 DAYS, MODIFIED AFTER DR. K. VON BRÖCKEL, IFM-
GEOMAR)..............................................................................................- 13 FIGURE 5: REACTION SCHEME OF THE ORTHO-PHTALDIALDEHYDE (OPA)
DERIVATIZATION.
......................................................................................- 17 -
FIGURE 6: BOUNDARY CONDITIONS IN THE BALTIC SEA IN JULY 2007: WATER
TEMPERATURE (°C) (BLUE LINE) OF THE BALTIC AND WIND SPEED (M/S)(RED LINE).
IV
LIST OF FIGURES
SAMPLING FREQUENCY OF MESOCOSMS IS MARKED WITH BLACK DOTS.
ACIDIFICATION EVENTS ARE HIGHLIGHTED BY BOXES....................................- 25 FIGURE 7: COMPARISONS OF THE VERTICAL DISTRIBUTION OF WATER TEMPERATURES
IN THE MESOCOSMS (MC) 1 - 6 AND IN THE BALTIC BEFORE (A) AND AFTER THE
ACIDIFICATIONS (B, C, D) (SOLID LINES: 0 - 10 M, DOTTED LINES: 10 - 17.5 M)
(DATA, K. SCHULZ). ..................................................................................- 26 FIGURE 8 : VERTICAL PROFILES OF WATER TEMPERATURE IN THE MESOCOSMS (MC) 1 6 AND IN THE BALTIC FOR 10TH JULY (BLUE), 14TH JULY (YELLOW), 16TH JULY (RED)
TH
AND 20
JULY (GREEN). (SOLID LINES: 0 - 10 M, DOTTED LINES: 10 - 17.5 M)
(DATA, K. SCHULZ) ...................................................................................- 27 FIGURE 9: VERTICAL PROFILES OF SALINITY IN THE MESOCOSMS (MC) 1 - 6 AND IN THE
BALTIC FOR 10TH JULY (BLUE), 14TH JULY (YELLOW), 16TH JULY (RED) AND 20TH
JULY (GREEN). (SOLID LINES: 0 - 10 M, DOTTED LINES: 10 - 17.5 M) (DATA, K.
SCHULZ)..................................................................................................- 29 FIGURE 10: VERTICAL PROFILES OF PCO2 (CALCULATED BY PH AND ALKALINITY)) IN
TH
THE MESOCOSMS (MC) 1 - 6 AND IN THE BALTIC FOR 10
JULY (BLUE), 14TH JULY
(YELLOW), 16TH JULY (RED) AND 20TH JULY (GREEN). (SOLID LINES: 0 - 10 M,
DOTTED LINES: 10 - 17.5 M)
......................................................................- 30 -
FIGURE 11: VERTICAL PROFILES OF PH IN THE MESOCOSMS (MC) 1 - 6 AND IN THE
BALTIC FOR 10TH JULY (BLUE), 14TH JULY (YELLOW), 16TH JULY (RED) AND 20TH
JULY (GREEN). (SOLID LINES: 0 - 10 M, DOTTED LINES: 10 - 17.5 M) (DATA, K.
SCHULZ)..................................................................................................- 31 FIGURE 12: RANGE OF PH (MEAN OF 0-10 M) IN THE MESOCOSMS (MC) 1-6 DURING
THE ENTIRE EXPERIMENT (SOLID LINE: MEDIAN, DOTTED LINE: MEAN) .............- 32 -
FIGURE 13: TEMPORAL DEVELOPMENT OF THE PCO2 CONCENTRATIONS IN THE
ST
MESOCOSMS (NOT, WEAKLY, MEDIUM AND STRONGLY ACIDIFIED) FOR THE 1
AND 3
RD
, 2ND
ACIDIFICATION EXPERIMENTS.........................................................- 33 -
FIGURE 14: RANGE OF PCO2 CONCENTRATIONS IN THE MESOCOSMS (NOT, WEAKLY,
MEDIUM AND STRONGLY ACIDIFIED) FOR THE 1
EXPERIMENT.
ST
(A) AND 2ND (B) ACIDIFICATION
...........................................................................................- 34 -
V
LIST OF FIGURES
FIGURE 15: MEANS OF PARTICULATE ORGANIC CARBON (POC) CONCENTRATIONS IN
ST
THE MESOCOSMS (NOT, WEAKLY, MEDIUM AND STRONGLY ACIDIFIED) FOR THE 1
(A) AND 2ND (B) ACIDIFICATION EXPERIMENT (DATA, M. VOSS). .....................- 35 FIGURE 16: MEANS OF PARTICULATE ORGANIC NITROGEN (PON) CONCENTRATIONS IN
ST
THE MESOCOSMS (NOT, WEAKLY, MEDIUM AND STRONGLY ACIDIFIED) FOR THE 1
(A) AND 2ND (B) ACIDIFICATION EXPERIMENT (DATA: M. VOSS). .....................- 36 FIGURE 17: MEANS OF PARTICULATE ORGANIC PHOSPHORUS (POP)
CONCENTRATIONS IN THE MESOCOSMS (NOT, WEAKLY, MEDIUM AND STRONGLY
ACIDIFIED) FOR THE 1
ST
(A) AND 2ND (B) ACIDIFICATION EXPERIMENT (DATA, K.
ISENSEE). ................................................................................................- 37 FIGURE 18: MEANS OF THE CARBON/NITROGEN (C/N) RATIO (MOL/MOL) IN THE
ST
MESOCOSMS (NOT, WEAKLY, MEDIUM AND STRONGLY ACIDIFIED) FOR THE 1
AND 2
ND
(A)
(B) ACIDIFICATION EXPERIMENT (RED SOLID LINES: REDFIELD RATIO OF
6.6).........................................................................................................- 38 FIGURE 19: MEANS OF THE CARBON/PHOSPHORUS (C/P) RATIO IN THE MESOCOSMS
(NOT, WEAKLY, MEDIUM AND STRONGLY ACIDIFIED) FOR THE 1ST (A) AND 2ND (B)
ACIDIFICATION EXPERIMENT (RED SOLID LINES: REDFIELD RATIO OF 106).
.....- 39 -
FIGURE 20: MEANS OF THE NITROGEN/PHOSPHORUS (N/P) RATIO IN THE MESOCOSMS
(NOT, WEAKLY, MEDIUM AND STRONGLY ACIDIFIED) FOR THE 1ST (A) AND 2ND (B)
ACIDIFICATION EXPERIMENT (RED SOLID LINES: REDFIELD RATIO OF 16).
.......- 40 -
FIGURE 21: MEANS OF CHLOROPHYLL A (CHL A) CONCENTRATIONS IN THE
ST
MESOCOSMS (NOT, WEAKLY, MEDIUM AND STRONGLY ACIDIFIED) FOR THE 1
AND 2
ND
(A)
(B) ACIDIFICATION EXPERIMENT (DATA, P. FRITSCHE)......................- 41 -
FIGURE 22: MEANS OF DISSOLVED FREE AMINO ACID (DFAA) CONCENTRATIONS IN THE
ST
MESOCOSMS (NOT, WEAKLY, MEDIUM AND STRONGLY ACIDIFIED) FOR THE 1
AND 2
ND
(A)
(B) ACIDIFICATION EXPERIMENT. ....................................................- 42 -
FIGURE 23: MEANS OF TRANSPARENT EXOPOLYMER PARTICLES (TEP) IN THE
ST
MESOCOSMS (NOT, WEAKLY, MEDIUM AND STRONGLY ACIDIFIED) FOR THE 1
AND 2
ND
(A)
(B) ACIDIFICATION EXPERIMENT. ....................................................- 43 -
FIGURE 24: MEANS OF EUKARYOTIC PHYTOPLANKTON ABUNDANCES IN THE
ST
MESOCOSMS (NOT, WEAKLY, MEDIUM AND STRONGLY ACIDIFIED) FOR THE 1
(A)
VI
LIST OF FIGURES
AND 2
ND
(B) ACIDIFICATION EXPERIMENT (DATA, H. JOHANSEN & A.
GRÜTTMÜLLER). .......................................................................................- 44 FIGURE 25: TEMPORAL DYNAMICS OF NODULARIA SPP. (A) AND APHANIZOMENON SPP.
(B) IN THE MESOCOSMS (NOT, WEAKLY, MEDIUM AND STRONGLY ACIDIFIED) FOR
ST
THE 1
ND
AND 2
ACIDIFICATION EXPERIMENT (1 UNIT = 100 µM) (DATA, K.
HAYNERT)................................................................................................- 45 FIGURE 26: MEANS OF CO2 UPTAKE RATES OF ORGANISMS >10µM (BLACK) AND <10µM
(GREY) IN THE MESOCOSMS (NOT, WEAKLY, MEDIUM AND STRONGLY ACIDIFIED)
ST
FOR THE 1
(A) AND 2ND (B) ACIDIFICATION EXPERIMENT (DATA, M. VOSS)....- 47 -
FIGURE 27: MEANS OF NITROGEN FIXATION (N2 FIX) RATES OF ORGANISMS >10µM
(BLACK) AND <10µM (GREY) IN THE MESOCOSMS (NOT, WEAKLY, MEDIUM AND
ST
STRONGLY ACIDIFIED) FOR THE 1
(A) AND 2ND (B) ACIDIFICATION EXPERIMENT
(DATA, M. VOSS). .....................................................................................- 49 FIGURE 28: MEANS OF UNICELLULAR CYANOBACTERIA (DETERMINED BY FLOW
CYTOMETRY) ABUNDANCES IN THE MESOCOSMS (NOT, WEAKLY, MEDIUM AND
ST
STRONGLY ACIDIFIED) FOR THE 1
(A) AND 2ND (B) ACIDIFICATION EXPERIMENT
(DATA, H. JOHANSEN & A. GRÜTTMÜLLER). ................................................- 50 FIGURE 29: MEANS OF HETEROTROPHIC BACTERIA ABUNDANCES IN THE MESOCOSMS
(NOT, WEAKLY, MEDIUM AND STRONGLY ACIDIFIED) FOR THE 1ST (A) AND 2ND (B)
ND
ACIDIFICATION EXPERIMENT (MEDIUM OF 2
ACIDIFICATION: N=1).................- 51 -
FIGURE 30: LINEAR CORRELATIONS BETWEEN TRANSPARENT EXOPOLYMER
PARTICLES (TEP) AND. CYANOBACTERIA (ORANGE) (A) AND TEP VS.
HETEROTROPHIC BACTERIA (BLUE) (B). DATA OF THE NOT ACIDIFIED MESOCOSMS
(1ST ACIDIFICATION (RED) AND 2ND ACIDIFICATION (BLACK)) WERE NEGLECTED. - 52
FIGURE 31: LINEAR MODEL FIT OF THE ENZYME EFFICIENCY (VMAX/KM) OF ΑGLUCOSIDASE IN ALL MESOCOSMS AND DURING THE ENTIRE EXPERIMENT
(MULTIPLE R(Z/XY) = 0.23, P = 0.2). ..........................................................- 53 FIGURE 32: LINEAR MODEL FIT OF THE ENZYME EFFICIENCY (VMAX/KM) OF LEUCINEAMINOPEPTIDASE IN ALL MESOCOSMS AND DURING THE ENTIRE EXPERIMENT
(MULTIPLE R(Z/XY) = 0.68, P < 0.001)........................................................- 54 -
VII
LIST OF FIGURES
FIGURE 33: LINEAR MODEL FIT OF THE ENZYME EFFICIENCY (VMAX/KM) OF ALKALINE
PHOSPHATASE IN ALL MESOCOSMS AND DURING THE ENTIRE EXPERIMENT
(MULTIPLE R(Z/XY) = 0.68, P < 0.001)........................................................- 55 FIGURE 34: MEANS OF LLEUCINE (LEU) (A, B) AND THYMIDINE (THY) (C; D) UPTAKE
RATES IN THE MESOCOSMS (NOT, WEAKLY, MEDIUM AND STRONGLY ACIDIFIED)
ST
FOR THE 1
AND 2
ND
ACIDIFICATION EXPERIMENT.
.......................................- 56 -
FIGURE 35: TEMPORAL DYNAMICS OF HETEROTROPHIC BACTERIA ABUNDANCES IN
THREE DIFFERENT (NOT (A), WEAKLY (B) AND STRONGLY (C) ACIDIFIED)
MESOCOSMS FOR THE 2
ND
ACIDIFICATION EXPERIMENT (ERROR BARS INDICATE
ANALYTICAL ERRORS OF CYTOMETRICAL ANALYSES (4%))............................- 57 -
FIGURE 36: TEMPORAL DYNAMICS OF UNICELLULAR CYANOBACTERIA ABUNDANCES IN
THREE DIFFERENT (NOT (A), WEAKLY (B) AND STRONGLY (C) ACIDIFIED)
MESOCOSMS FOR THE 2
ND
ACIDIFICATION EXPERIMENT (ERROR BARS INDICATE
ANALYTICAL ERRORS OF CYTOMETRICAL ANALYSES (8%))............................- 58 -
FIGURE 37: GROWTH RATES OF UNICELLULAR CYANOBACTERIA (WHITE) AND
HETEROTROPHIC BACTERIA (GREY) IN THREE DIFFERENT (NOT, WEAKLY AND
ND
STRONGLY ACIDIFIED) MESOCOSMS FOR THE 2
ACIDIFICATION EXPERIMENT.- 59 -
FIGURE 38: CHANGES IN NUTRIENT CHARACTERISTICS ACROSS A PRODUCTIVITY
GRADIENT. (A-H COUPLING: AUTOTROPHIC-HETEROTROPHIC COUPLING) (FROM
COTNER AND BIDDANDA 2002)..................................................................- 69 FIGURE 39: DISSOLVED FREE AMINO ACID (DFAA) COMPOSITION IN THE MESOCOSMS
(NOT, WEAKLY AND STRONGLY ACIDIFIED) OF THE 1ST AND 2ND ACIDIFICATION
EXPERIMENT. TEMPORAL DEVELOPMENT WITHIN THE TREATMENTS AND
ACIDIFICATION. .........................................................................................- 74 -
VIII
LIST OF TABLES
List of Tables
TABLE 1: SOLUBILITY OF 4-METHYLUMBELLIFERYL (MUF)- Α-D-GLUCOSIDE, MUFPHOSPHATE AND L-LEUCINE 7-AMINO-4-METHYLCOUMARIN (AMC).
.............- 21 -
TABLE 2: INITIAL VALUES OF MEASURED PARAMETERS BEFORE ACIDIFICATION AT ALL .. 72 TABLE 3: SOLUBILITY OF MUF- AND AMC- LABELLED SUBSTRATE ANALOGUES .....- 73 -
IX
ABBREVIATIONS
Abbreviations
α-ABA
α-amino butyric acid
AMC
7-amino-4-methylcoumarin
approx.
approximately
AR4
4th assessment report
ASN
asparagines
Bft
Beaufort
BPP
baterial protein production
Bq
Becquerel
C
carbon
CA
carbonate alkalinity
CaCO3
calcium carbonate
CCM
CO2 concentrating system
CFCs
chlorofluorocarbons
CH4
methane
Chl a
chlorophyll a
CHO
carbohydrates
CO2
carbon dioxide
CO32-
carbonate ion
CTD
conductivity, temperature, depth
DCAA
dissolved combined amino acids
DFAA
dissolved free amino acids
DIC
dissolved inorganic carbon
DMSO
dimethyl sulfoxide
DNA
desoxyribonucleic acid
DOC
dissolved organic carbon
DOM
dissolved organic matter
DON
dissolved organic nitrogen
DOP
dissolved organic phosphorous
e.g.
for example, abbreviation of Latin 'exempli gratia’
Em.
emission
X
ABBREVIATIONS
Ex.
Extinction
FL1
fluorescence 1
GCMs
global climate models
GDA
glutardialdehyde
GLN
glutamine
+
H
protons
HCl
hydrochloric acid
HCO3-
bicarbonate
HEA
hydrolytic enzyme activity
HMW
high-molecular-weight
HNA
high nucleic acid subgroup
H2O
water vapour
H2SO4
sulphuric acid
HPLC
high performance liquid chromatography
IPCC
Intergovernmental Panel on Climate Change
KOSMOS
Kiel Off-Shore Mesocosms for future Ocean Simulations
Km
Michaelis constant (affinity for substrate)
LNA
low nucleic acid subgroup
MC
mesocosm
min-1
per minute
MUF
4-methylumbelliferyl
NaOH
sodium hydroxide
nm
nautical miles
N2
nitrogen
N2O
nitrous oxide
NO3-
nitrate
O2
oxygen
O3
ozone
OPA
ortho-phtaldialdehyde
pCO2
carbon dioxide partial pressure
PE
polyethylene
PIC
particulate inorganic carbon
XI
ABBREVIATIONS
POC
particulate organic carbon
POM
particulate organic matter
PON
particulate organic nitrogen
POP
particulate organic phosphorous
pH
pH is a measure of the acidity or alkalinity of a solution
PO4
3-
phosphate
ppm
parts per million
RV
research vessel
RubisCO
Ribulose-1,5-bisphosphate carboxylase/oxygenase
sec-1
per second
SG1
SybrGreen I
SG2
SybrGreen II
Si
silicate
SOPRAN
Surface Ocean PRocesses in the Anthropocene
SSC
sidescatter
TA
total alkalinity
TCA
trichloroacetic acid
TEP
transparent exopolymer particles
THDAA
total hydrolysable dissolved amino acids
TLZ
Technik- und Logistikzentrum
UV-vis.
ultraviolet-visible
Vmax
maxiumin veloocity of enzyme
vs.
Versus
Xeq.
GumXanthan equivalents
°C
degree Celsius
3
H-Leu
3
[H]-leucine, tritiated leucine
3
H-TdR
3
[H]-thymidine, tritiated thymidine
XII
Section 1: Introduction
1
Introduction
The earth’s climate is a highly complex system usually separated in five major
components: the atmosphere, the hydrosphere, the cryosphere, the land
surface and the biosphere (Fig. 1). These components are influenced on the
one hand by various external forcing mechanisms, such as solar irradiance and
orbital patterns. But on the other hand, their chemical, physical and biological
interactions and internal feedbacks play an important role. The components of
the climate system are all linked by fluxes of mass, heat and momentum,
although their composition, chemical and physical properties, structure and
behaviour are very different (Houghton et al. 2001).
Figure 1: Schematic view of the components of the climate system (bold), their
processes and interactions (thin arrows) and some aspects that may change (bold
arrows) (after Houghton et al. 2001).
In recent years many attention was spent on investigating the changes of the
atmospheric composition. The so called ‘natural greenhouse effect’ keeps the
1
Section 1: Introduction
earth’s surface warm by trapping heat due to the greenhouse gases. The
primary greenhouse gases are water vapour (H2O), carbon dioxide (CO2),
methane (CH4), nitrous oxide (N2O) and ozone (O3). Without these gases the
earth’s average surface temperature would be about -18°C, instead of 15°C
(Houghton et al. 2001). The extent of change in climate, CO2 and other climaterelevant gases is controlled by a variety of mechanisms. Among these
mechanisms, biologically-driven reactions and feedbacks, involving both
terrestrial and marine ecosystems, are tend to play a critical role (Riebesell
2004).
During the past 420,000 years before the industrial period the earth’s climate
system settled into a persistent pattern of glacial-interglacial cycles, with
atmospheric CO2 oscillating between 180 µatm in glacial and 280 µatm in
interglacial times (Petit et al. 1999). Concentrations of atmospheric greenhouse
gases and their radiative forcing have continued to increase as a result of
human activities in the past 200 years. Since 1750 the increase of CO2
emissions has been 31%, primarily due to fossil fuel use and changes in land
use (Houghton et al. 2001). According to the 4th assessment report (AR4) of the
Intergovernmental Panel on Climate Change (IPCC, 2007), the global
atmospheric CO2 concentration increased from a pre-industrial value of
280 µatm to 379 µatm in 2005. Current CO2 concentration has not been
exceeded during the past 650,000 years and likely not during the past 20 million
years. The mean annual increase of CO2 concentration was in average
1.9 µatm per year during the period from 1995 to 2005 (IPCC, 2007). Estimates
of future atmospheric CO2 concentrations, based on the IPCC ‘business-asusual’ emission scenario (IS92a), predict that the CO2 concentrations will rise by
a factor of two relative to the present value (~380 µatm) in the year 2100, and
could increase by a factor of three by the middle of the next century (Houghton
et al. 2001).
About 98% of the CO2 in the combined atmosphere-ocean system is dissolved
in water. Atmospheric CO2 reacts with water to bicarbonate and carbonate ions
(see carbonate system) (Zeebe and Wolf-Gladrow 2001). If global emissions of
2
Section 1: Introduction
CO2 from human activities continue to rise, the oceans will become more acidic
by an average of 0.5 units (on the logarithmic scale of pH) (Caldeira and
Wickett 2003; Raven 2005). Possible consequences of ocean acidification can
range from physiological responses on organism level, changes in ecosystem
structures, to shifts in biogeochemical cycling. Although the carbon cycle is
most strongly affected by human activities, this anthropogenic influence has
consequences for the earth system as a whole, since the carbon cycle is
coupled with climate, water cycle, nutrient cycles and photosynthesis on land
and in oceans (Falkowski et al. 2000; Riebesell 2004; Gruber and Galloway
2008).
Carbonate system
In order to understand the effect of rising atmospheric CO2 concentrations on
seawater chemistry, a fundamental knowledge of the carbonate system is
needed.
Because of its solubility and chemical reactivity, CO2 is taken up by the ocean
much more effectively than other anthropogenic gases (e.g. chlorofluorocarbons
(CFCs) and CH4). Since pre-industrial times the world’s oceans have absorbed
nearly one third of the anthropogenic CO2 emitted to the atmosphere (Sabine et
al. 2004), making it the second largest sink for CO2 after the atmosphere itself
(Houghton et al. 2001).
At the surface ocean, where seawater is in contact with the atmosphere, gases
(e.g. CO2) can dissolve into the water and vice versa. In equilibrium the partial
pressure of CO2 (pCO2) in the atmosphere equals the partial pressure of CO2 in
the surface ocean, which is related to the concentration of CO2 by Henry’s law:
CO2( aq ) = α ⋅ pCO2
(1)
where α is the solubility coefficient of CO2 in seawater, which is temperature-,
pressure- and salinity-dependent. When CO2 reacts with seawater, it is
hydrated to carbonic acid (H2CO3), which subsequently dissociated to
3
Section 1: Introduction
bicarbonate (HCO3-), carbonate ion (CO32-) and protons (H+) as shown in
Figure 2 (Zeebe and Wolf-Gladrow 2001).
Figure 2: Schematic illustration of the carbonate system in the ocean. CO2 is
exchanged between atmosphere and ocean via equilibration of CO2 (g) and dissolved
CO2. Dissolved CO2 is part of the carbonate system in seawater that includes
bicarbonate, HCO3-, and carbonate ion, CO32- (after Zeebe and Wolf-Gladrow 2001).
The sum of all dissolved forms is called total dissolved inorganic carbon (DIC)
and is given by:
DIC = CO2 + HCO3− + CO32−
(2)
A further quantitative parameter for the description of the carbonate system is
the alkalinity, which is closely related to the charge balance in seawater. The
total alkalinity (TA) of seawater is a measure of the ability of a solution to
neutralize acids to the equivalence point of HCO3- or CO32-.The TA consists of
various components of seawater:
4
Section 1: Introduction
−
TA = ⎡⎣ HCO3− ⎤⎦ + 2 ⎡⎣CO32 − ⎤⎦ + ⎡ B ( OH )4 ⎤ + ⎡⎣OH − ⎤⎦ − ⎡⎣ H + ⎤⎦ + minor components
⎣
⎦
(3)
where [H+] is the free concentration of hydrogen ion (Dickson, 1981).
At a typical surface ocean pH value of 8.2, less than 1% of dissolving CO2
remains as dissolved CO2, while the rest is converted into HCO3- (~90%) and
CO32- (~9%) (Riebesell 2004). Because the pH is the negative decadic
logarithm of the hydrogen-ion concentration, increasing atmospheric CO2
concentrations lead to an increase of H+-ion concentration and a decrease of
the pH. This acidification causes a shift of the pH-dependent equilibrium of the
carbonate system towards higher proportions of CO2 and lower proportions of
CO32-. This mechanism is called the buffer capacity of seawater as DIC forming
anions react with H+-ions and thus buffer the system. Therefore, an invasion of
anthropogenic CO2 leads to an increase of DIC, but does not change TA,
because the charge balance is not affected. A more detailed description is given
in Zeebe & Wolf-Gladrow (2001).
The marine carbon cycle
The global carbon cycle is a biogeochemical cycle by which carbon is
exchanged between atmosphere, land and oceans of the Earth. The marine
carbon cycle refers only to the fate of carbon in the oceans. The cycling of
carbon in the marine environment involves both physical and biological
processes and is a boundless system of inputs, fluxes, sinks and outputs. It
includes the transfer of carbon from the atmosphere to the ocean, the fixation of
carbon by phytoplankton, the flux of carbon through the marine food chain and
the long-term fate of carbon in the marine environment.
Two of the most common processes involving carbon on land and in water, are
utilization and release of CO2 by photosynthesis and respiration, respectively.
Marine biota contain comparatively low amounts of carbon (~3 Gt C) in contrast
to terrestrial ecosystems (~500 Gt C plant biomass). However, the annual
5
Section 1: Introduction
amount of photosynthetically fixed carbon of marine primary producers
(phytoplankton) is almost as high as of terrestrial biomass (103 Gt C a-1 and
120 Gt C a-1, respectively) (Körtzinger 2006).
The marine biosphere operates like a biological pump. In the sunlit uppermost
~100 m of the ocean (euphotic zone), photosynthesis of phytoplankton serves
as a source of oxygen and a sink for CO2 and nutrients like nitrogen and
phosphorous. Using the sunlight as their source of energy for growth,
phytoplankton fix CO2 into organic compounds like sugars. Whenever primary
producers have enough DIC and light for photosynthesis the uptake of CO2
continues, although nutrient concentrations are low. A consequence of this
excess assimilation of carbon is extracellular release of organic matter. This
release of organic matter is an important source for DOC in the upper ocean. A
major fraction of DOC consists of polysaccharides, containing acidic sugars.
This sticky organic matter coagulates into particles known as transparent
exopolymer particles (TEP). TEP play an important role in aggregation,
promoting the sedimentation of particles and thus export of organic and
inorganic matter (Engel and Passow 2001; Passow 2002; Engel 2004b; Engel
2004a). The fixation of dissolved inorganic carbon (DIC) via photosynthesis and
the vertical flux of particulate organic matter (POM), for example of TEP, dead
organisms and/or fecal pellets, into deeper parts of the oceans cause a
drawdown of CO2 in the surface ocean and subsequently a supply of CO2 from
the atmosphere. On its way to the deeper ocean organic matter is either
remineralized by bacteria (microbial loop) or it is deposited on and into the
sediment. This is called the organic carbon or soft-tissue pump. Hence, the
ocean is commonly regarded as a carbon sink.
Contrariwise, a second biological carbon pump, the carbonate carbon pump or
hard-tissue pump can be a source of CO2 for the atmosphere. The formation of
particulate inorganic carbon (PIC) involves a net release of CO2, which can be
used for photosynthesis or is released into the atmosphere. A major source of
PIC is calcium carbonate (CaCO3), which is produced by calcification of for
example calcifying algae species. Thus, the carbonate pump refers to the
sinking of particulate inorganic carbon (PIC) to the deep ocean. The rain-ratio
represents the relative ratio of the two biological carbon pumps (PIC/POC ratio),
6
Section 1: Introduction
thus, the relative importance of inorganic to organic carbon in exported biogenic
matter.
An acidification of ocean waters will potentially change the productivity of
autotrophic phytoplankton and subsequently affect the efficiency of the
biological carbon pump in the future, as recently hypothesized by Riebesell et
al. (2007). From this hypothesis follows that the stoichiometric composition of
C:N:P may alter in the future. This would subsequently change microbial
processes and biogeochemical cycling.
Marine primary production
Several studies have shown that some macroalgae (Gao et al. 1993), diatoms
(Riebesell et al. 1993) and cyanobacteria (Qiu and Gao 2002; Barcelos E
Ramos et al. 2007) exhibit higher photosynthesis rates under CO2 enrichment.
The overall oceanic primary production was shown to be higher under
increased CO2 concentrations (Hein and Sand-Jensen 1997), influenced by the
species composition of phytoplankton assemblages.
Photosynthetic carbon fixation of marine phytoplankton has been reported to be
affected by elevated pCO2 concentrations (Riebesell et al. 1993; Rothschild
1994; Hein and Sand-Jensen 1997; Raven 2003; Leonardos and Geider 2005).
The processes of photosynthetic carbon fixation and diazotrophic N2 fixation are
both energy demanding processes. Cyanobacteria have to invest significant
amounts of energy to concentrate CO2 at the site of carboxylation, due to the
relatively low affinity of their main carboxylating enzyme RubisCO (Ribulose1,5-bisphosphate carboxylase/oxygenase) (Tortell 2000). This causes a
competition and reduction of energy for other cellular processes, such as
protein synthesis and carbon acquisition (Kaplan and Reinhold 1999). In
response to increasing CO2 availability cyanobacteria are known to downregulate their CO2 concentrating mechanism (CCM) and allocate energy to
other cellular processes (Giordano et al. 2005). Thus, the energetic benefit at
7
Section 1: Introduction
elevated
CO2
may
be
higher
in
cyanobacteria
compared
to
other
phytoplanktonic groups with RubisCOs characterized by higher CO2 affinities.
Microbial loop
Within the marine carbon cycle, the microbial loop describe a trophic pathway,
where DOM is reintroduced to the food web through the incorporation into
bacteria (Azam et al. 1983) (Fig. 3). Bacteria are consumed mostly by protists
such as flagellates and ciliates. These protists, in turn, are consumed by larger
aquatic organisms (for example small crustaceans like copepods). Thus, the
recycling of this organic matter into the food web results in additional energy
available to higher trophic levels (e.g. fish). The DOM is introduced into aquatic
environments from several sources, such as the leakage of fixed carbon from
algal cells or the exudation by microbes. DOM is also produced by the
breakdown and dissolution of organic particles. In turn, ~30% of the DOC
incorporated into bacteria is respired and released as CO2 (Stoderegger and
Herndl 1998).
Heterotrophic bacteria play a major role in organic matter cycling (e.g. Cole et
al. 1988; Azam 1998; Azam and Malfatti 2007). Their dynamics and activities
depend on the availability of DOM either in form of monomeric substances or
dissolved free amino acids, which can directly transferred into the cell (Chrost
1991). This directly utilizable DOM limits the growth rate and metabolism of
heterotrophic bacteria. However, the majority (>95%) of organic matter in
aquatic ecosystems is composed of polymeric, high molecular weight (HMW)
compounds, like polysaccharides, proteins, lipids etc., which means that only a
small portion of total DOM is readily utilizable in natural waters (Muenster 1985;
Jorgensen 1987). Various aquatic microorganisms are able to efficiently utilize
polymeric DOM by enzymatic hydrolysis (Hoppe 1983; Chrost et al. 1989).
The efficiency of the microbial loop can be determined by bacterial incorporation
of radiolabeled substrates like
3
H-thymidine (Fuhrman and Azam 1982;
3
Kirchman et al. 1982), and H-leucine (Simon and Azam 1989).
8
Section 1: Introduction
How to study the effects of rising CO2 concentration on marine
environments?
There are several possibilities to study the effects of rising CO2 concentration
on marine environments.
Perturbation studies can be conducted on a laboratory scale for example in
batch cultures or in chemostat systems. Batch cultures are determined by the
starting conditions and follow their own dynamic thereafter (e.g. Barcelos E
Ramos et al. 2007). The chemostat is an open system, in which organisms can
be grown continuously in a well defined physiological state (e.g. Sciandra et al.
2003; e.g. Koch 2007). While laboratory investigations and bottle incubation
experiments on small scales have the advantage of being easier to handle, the
dynamics of a natural environment with interactions e.g. on trophic levels are
not well simulated. Field studies with respect to rising CO2 concentrations were
conducted in mesocosm experiments (Engel et al. 2005; Grossart et al. 2006;
Riebesell et al. 2007). The use of mesocosms allows to study ecosystems
under semi-natural conditions in large bodies of sea-water from a few hundred
litres to dozens of cubic meters including all its organisms. Until recently,
mesocosms were only deployed close to the coast within protected areas.
Newly developed free-floating offshore mesocosms can be used in open waters
with the advantage of e.g. covering natural light and temperature variability and
different kinds of environments.
Ecosystem models are a useful and important tool to predict the patterns of
carbon flux, primarily regarding to potential consequences of climate change
(Falkowski et al. 2000; Gruber and Galloway 2008). Numerous simulations of
coupled atmosphere-ocean global climate models (GCMs) or biogeochemical
models has been carried out, including projections into the 21st century. But
most models do not include microbial processes on organism level, mainly, due
to our limited knowledge of the factors and processes that determine the
abundance, distribution and activities of key groups of marine organisms. These
9
Section 1: Introduction
uncertainties affect our ability to predict specific responses (Falkowski et al.
2000), for example, to ocean acidification. The impact of microorganisms on
biogeochemical cycles must be addressed on nanometre (molecular) to
millimetre scale to make useful predictions of how marine ecosystems in the
ocean may respond to global change (Azam and Malfatti 2007).
This study
In the Baltic Sea, N2 fixation by diazotrophic cyanobacteria is an important
factor that determines overall growth and biomass of autotrophic plankton and,
thereby, primary production. As in most other marine environments,
phytoplankton blooms in the Baltic Sea are controlled by nitrogen (N2) (Graneli
et al. 1990; Tamminen 1995). The advantage of diazotrophic cyanobacteria is
the capability of using atmospheric N2 as their sole source of nitrogen (Niemi
1979). Blooms of diazotrophic cyanobacteria mainly consist of small-sized
picocyanobacteria
(Synechococcus
spp.)
and
larger,
colony-forming,
filamentous, heterocystous, N2 fixing cyanobacteria (Nodularia spumigena,
Aphanizomenon flos-aquae and Anabaena spp.) (Stal et al. 2003). During
summer in the Baltic Sea, in areas where the N:P ratio is below the Redfield
ratio of 16, blooms of diazotrophic cyanobacteria develop. But not only the N:P
ratio is an important factor, an adequate concentration of both elements is
essential for bloom formation (De Nobel 1997).
In this study offshore mesocosms were used to investigate the impact of rising
pCO2 concentration on a natural plankton community in the Baltic Sea.
Recent studies revealed that oceanic primary production increases with rising
CO2 (Fig. 3) (Hein and Sand-Jensen 1997). An acidification of ocean waters will
potentially
change
the
productivity
of
autotrophic
phytoplankton
and
subsequently the efficiency of the biological carbon pump in the future. From a
biogeochemical point of view the elemental composition of C:N:P will change,
and subsequently alter biogeochemical cycling and vertical export of organic
and inorganic matter (Riebesell et al. 2007). This will affect the recycling of
10
Section 1: Introduction
organic matter within the microbial loop. Linked to phytoplankton, an increase of
the availability of DOM will increase heterotrophic bacterial activity and
productivity, and therefore growth and/or abundance (Grossart et al. 2006).
Preliminary studies indicate that enzyme efficiencies decrease with decreasing
pH (Piontek et al. 2007a; Piontek et al. 2007b; Lunau et al. 2008).
In order to reliable predict consequences of ocean acidification on microbial
dynamics and activities, there is a great necessity for repeated studies under
controlled environmental conditions.
In this study rising pCO2 concentrations were simulated in offshore mesocosms
by the addition of hydrochloric acid. Low concentrations of Chlorophyll a and
low primary production revealed a non-bloom situation. Our study shows that
acidification of Baltic Sea water led to a loss of POC over time. The perturbation
by hydrochloric acid induced a community shift from eukaryotes to prokaryotes.
However, in contrast to hydrolytic enzyme efficiencies, microbial uptake rates of
DOM were not influenced by the acid treatment. Autotrophic unicellular
cyanobacteria
outcompeted
heterotrophic
bacteria
under
strong
acidic
conditions.
11
Section 1: Introduction
Figure 3: Cycling of organic matter and microbial loop. Interplay between light,
nutrients, temperature, primary production of phytoplankton (carbon dioxide (CO2)
uptake, nitrogen (N2) fixation), respiration of oxygen (O2), export of particulate organic
matter (POM), release of dissolved organic matter (DOM) and bacterial degradation
processes of DOM & POM (hydrolytic enzyme activity (HEA), and uptake of monomeric
DOM). The DOM pool consists of dissolved organic nitrogen (DON, mainly amino acids
(AA)), dissolved organic carbon (DOC, mainly carbohydrates (CHO), AA, and lipids (L))
and dissolved organic phosphorous (DOP). Transparent Exopolymer Paricles (TEP)
form from DOM precursors and subsequently promote sedimentation and export of
POM. The POM pool consists of particulate organic carbon (POC), particulate organic
nitrogen (PON) and particulate organic phosphorous (POP) (M. Lunau, AWI
Bremerhaven).
12
Section 2: Material and methods
2
Materials and methods
In this study we measured the effect of Baltic Sea acidification on microbial
dynamics and activities. Offshore mesocosms were used to simulate different
levels of carbon dioxide partial pressure (pCO2). This work was done in the
frame
of
the
project
SOPRAN
(Surface
Ocean
PRocesses
in
the
ANthropocene).
Setup and sampling
The offshore mesocosm experiment was carried out during a research cruise
with the RV Alkor (AL-302) and the RV Heincke (HE-273) in the Baltic Sea in
July 2007. The experimental system was designed by the IFM-GEOMAR.
Briefly,
the
KOSMOS
(Kiel
Off-Shore
Mesocosms
for
future
Ocean
Simulations), constructed by the TLZ (Technik- und Logistikzentrum) of the IFMGEOMAR, facilitate the use of free-drifting mesocosms offshore.
3rd
sampling area
Northern Europe
Baltic Sea
2nd
sampling area
Poland
start
1st
Figure 4: Map of northern Europe (inset) and of the Baltic Sea including the sampling
area (map source: google.maps); Drift of the mesocosms during the experiment (11
days, modified after Dr. K. von Bröckel, IFM-GEOMAR)
- 13 -
Section 2: Material and methods
The sampling area is shown in Figure 4. The six mesocosms were launched at
the 10th of July and than connected to each others by tampen. They were taken
back on board RV Alkor at the 21st of July just before a storm came up.
Throughout the 11 days of the experiment, the mesocosms drifted approx. 55
nautical miles (nm) along a transect between 55°15’N, 17°30’E and 55°17’N,
18°02’E and 55°29’N, 17°45’E as shown in Figure 4.
Six mesocosms (ca. 60 m3, diameter of 2 m, 20 m water depth) were used with
six different pCO2 levels to simulate a large CO2 gradient. Different amounts of
HCl (3.75 M) in a range of 0 – 110 µmol were added to acidify the water masses
in the mesocosms by using a mixing spindle.
Due to the weather conditions five mesocosms were acidified three times. At
the 10th of July reference measurements of all mesocosms were performed
before the first HCl-treatment of the mesocosms to determine how equal the
enclosed water masses were. Initial values of all parameter can be found in
Table 2 in the appendix. Mesocosm 4 was used as a reference during the
experiment, since it was not treated.
The first acidification was performed at the 13th of July at 12 am. The six
mesocosms were sampled at two times: 6 hours and 24 hours after the
acidification. The second acidification was performed at the 16th of July at
11 am. Three days after the first acidification the five mesocosms were already
conditioned with HCl. The mesocosms were sampled at two times, 6 h and 25 h
after acidification. The sampling frequency for three mesocosms was increased
as a result of the fast changes observed after the first acidification. Thus,
mesocosm 2, 4 and 5 were additionally sampled at 18.5 h, 21.5 h, 29.5 h, 33 h
and 42.5 h after acidification. The third acidification was performed at the 20th of
July at 10 am. Due to the breakage of three mesocosms (1, 3 and 4) during a
storm beforehand just three mesocosms (2, 5 and 6) were acidified. The Baltic
was used as an alternate reference, as the untreated control mesocosm 4 was
out of order. Sampling was performed at 2.5 h, 4.75 h, 6.5 h, 10 h, 18 h, 22 h
and 25.5 h after the third acidification.
- 14 -
Section 2: Material and methods
Integrated water samples of the upper 10 m of the water column were taken out
of each mesocosm during calm weather from a zodiac by using a pressure
controlled sampling device (Hydrobios, Kiel). The samples were directly
transferred into 250 ml Polyethylene (PE)- bottles and brought on board ship for
further treatment as soon as possible.
Measurements and analyses
Physicochemical parameters
Nautical, meteorological and ship-specific data were monitored by the ship’s
data distribution system ‘DATADIS’ (Böning Automationstechnologie GmbH &
Co. KG, Ganderkesee, Germany). Conductivity, temperature and depth (CTD)
as well as salinity and pH measurements were conducted daily (unless the
weather conditions did not allow measurements for safety reasons) by K.
Schulz (IFM-GEOMAR, Kiel, unpublished data). Furthermore, pCO2 values
were calculated from pH and alkalinity. On the basis of no more than one pH
measurement per day, pH values for sampling times were calculated. A linear
development between two or three measured pH values were presumed and
the slope of the linear regression was used for calculation. In addition pCO2
concentrations were calculated using the function of pH (CTD) and calculated
pCO2 for all sampling times.
Distinct pCO2 measurements were maintained less frequently using a CO2/H2O
analyzer LI-6262 (LI-COR Biosciences) by R. Schmidt (Baltic Sea Research
Institute, Warnemünde, unpublished data).
Biogeochemical parameters
POC and PON were analyzed with a C/N analyzer (CHN-O-rapid) by M.Voss
(Baltic Sea Research Institute, Warnemünde). Concentrations of particulate
- 15 -
Section 2: Material and methods
organic phosphorous (POP) were analyzed by K.Isensee (Baltic Sea Research
Institute, Warnemünde). POP concentrations were determined by alkaline
sulphate oxidation according to Koroleff & Grasshoff (1983). Concentrations of
Chlorophyll a (Chl a) and nutrients were analyzed by P. Fritsche (IFM-Geomar,
Kiel) following standard procedures.
Amino acids
Subsamples for dissolved free amino acids (DFAA) and total hydrolysable
dissolved amino acids (THDAA) were filtered on board through 0.45 µm
TUFFRYN ® membrane filters (Acrodisc, Whatman) und kept frozen for three
weeks at -20°C until analysis in the lab. Concentrations of DFAA and THDAA
were analysed by high performance liquid chromatography (HPLC) after precolumn derivatization with ortho-phtaldialdehyde (OPA) (Lindroth and Mopper
1979). Chromatographic separation method was carried out with an Agilent
HPLC-device (1100 Series) using an Alltima reserve-phase column (C-18,
5 µm, 250 mm, Alltech) in combination with an Analytical Guard (Agilent)
precolumn. The detection of dye-labelled amino acids (OPA derivatization) was
performed by a fluorescence detector (extinction: 342 nm, emission: 440 nm).
- 16 -
Section 2: Material and methods
COOH
CHO
+
C
R
OH
+
HS
H
CHO
OPA
NH2
amino acid
2-Mercaptoethanol
CH2CH2OH
S
C
room temperature
N
H
C
R
< 60 sec.
COOH
Isoindolderivate
Figure 5: Reaction scheme of the ortho-phtaldialdehyde (OPA) derivatization.
The DFAA were measured directly after addition of the internal standard αamino butyric acid (α-ABA, final concentration of 30 nM). Prior to injection, the
sample was derivatized with OPA (Fig. 5) and the reaction was stopped by
adding glacial acetic acid (pH <5 after addition).
The THDAA were analysed as DFAA after hydrolysis with 6N HCl at 155°C for
one hour in glass ampoules, sealed under nitrogen. Before hydrolysis 500 µl of
unfiltered subsamples were spiked with the internal standard (α-ABA, final
concentration of 100 nM) and ascorbic acid (10 µg ml-1 final concentration) was
added to prevent oxidation of amino acids by nitrate. Prior to analysis 500 µl of
the hydrolysed samples were neutralised with 6N NaOH and diluted by doubledistilled water to a final dilution of 1:4.
An external standard (Agilent amino acid standard spiked with α-ABA,
glutamine (GLN) and asparagine (ASN)) was used to identify and quantify the
amino acids. Response factors of the amino acids related to α-ABA were
calculated.
The concentration of dissolved combined amino acids (DCAA) was calculated
by subtracting the DFAA from the THDAA.
- 17 -
Section 2: Material and methods
Transparent Exopolymer Particles
Transparent Exopolymer Particles (TEP) were determined colorimetrically
according to the method described by Passow & Alldredge (1995). Briefly,
subsamples of 30 ml were filtered gently at low, constant vacuum (<200 Hg)
onto polycarbonate filters (0.45 µm Nuclepore, Whatman). TEP were stained for
three seconds with 1 ml of a 0.02% aqueous solution of the polysaccharidespecific dye alcian blue in 0.06% acetic acid (pH 2.5). Before use, the staining
solution was filtered (0.2 µm) to avoid particles in the dye solution. After
staining, the filters were rinsed with deionised water to remove excess dye. All
filters were prepared in triplicates and stored at -20°C until analysis within 2
months.
Due to reaggregation processes and prefiltration, the dye content of staining
solutions decreases with age. Therefore, a calibration of the staining solution
was necessary to compare samples measured with different batches of staining
solution. The calibration factor was determined by relating dry weight
measurements of Gum Xanthan particles retained on filters to their staining
capacity as described by Passow and Alldredge (1995) according to equation 4.
dry weightstandard ⎡⎣ µg l −1 ⎤⎦
calibration factor =
( absorptionaverage − absorptionblank ) * filtered volume [l ]−1
(
)
(4)
Dry weights of a calibration standard solution, prepared by mixing ~ 15 mg of
Gum Xanthan with 200 ml deionised water and grinding step by step into TEPsized particles, were examined by filtering 0.5 – 2 ml aliquots onto preweighed
filters. The filters were dried at 60°C overnight and stored in a desiccator. Alcian
blue stainable particles were measured by filtering 0.5 – 2 ml of the calibration
standard and staining as described above. The calculated calibration factor for
this study was 33.33.
The stain bonded to particles present in the samples was extracted by soaking
the filters in 6 ml of 80% sulphuric acid (H2SO4) for 2 h. The absorption of dye- 18 -
Section 2: Material and methods
labelled TEP was measured at 787 nm against deionised water with an UV-vis.
spectrophotometer (Shimadzu UV-1700 PharmaSpec).
Concentration of TEP was expressed in Gum Xanthan equivalents [µg l-1] and
was determined from equation 5.
TEPconc. = ( absorptionsample − absorptionblank ) ∗ filtered volume [l ] ∗ calibration factor [ µg ]
(5)
Plankton abundances
Abundances of unicellular cyanobacteria, nano- and picoplankton (diatoms and
green algae) were analyzed by H. Johansen and A. Grüttmüller (Baltic Sea
Research Institute, Warnemünde) using Flow Cytometry following standard
procedures. Eukaryotic phytoplankton abundances were calculated by the sum
of nano- and picoplankton.
Diazotrophic cyanobacteria dynamics
Abundances of diazotrophic bacteria were analyzed by K. Haynert (Baltic Sea
Research Institute, Warnemünde) using fluorescence microscopy. Abundances
of Nodularia spp. and Aphanizomenon spp. are given in units l-1, whereas one
unit is equivalent to 100 µm.
Phytoplankton activity
Autotrophic production rates of organisms larger and smaller than 10 µm were
analyzed by M. Voss (Baltic Sea Research Institute, Warnemünde). Nitrogen
(N2) fixation and CO2 uptake were measured using
solution and
15
13
C labelled bicarbonate
N2 enriched gas according to the method described by Montoya
et al. (1996). A more detailed description is given in Voss et al. (2006). The
- 19 -
Section 2: Material and methods
incubations of the samples were conducted with about 75% light intensity and
incubations times ranged from 3.5 to 8 h depending on the time of the day
(light).
Bacterial dynamics
Subsamples for bacterial cell counts were preserved with two different
fixations: glutardialdehyde (GDA, AppliChem; final concentration of 1.1%) and
Dekafald (contained DMDM Hydantonin and less than 1% formaldehyde, Jan
Dekker Nederland B.V., Netherlands; final concentration of 4.4%). For each
preservative, duplicates were prepared and stored at -20°C until further
analysis. Samples were analyzed by flow cytometry (FACSCalibur, Beckton
Dickinson, USA) within 2 months. All the cytometrical analyses were done
following exactly the same protocol, keeping all settings constant.
Prior to analyses nucleic acid was stained by SybrGreen I (SG1) and
SybrGreen II (SG2) (Invitrogen, Karlsruhe, Germany). Each dye working
solution was prepared freshly every day by diluting the stock solution (10000x)
1:40 with dimethyl sulfoxide (DMSO, Sigma), followed by a 1:40 dilution with the
sample (final dilution 10-3, final concentration 6.25x). As an internal standard
yellow-green fluorescent latex beads (0.94 µm diameter, Polyscience, USA)
were used for the volume normalization of counted events. TruCount beads
(Beckton Dickinson) were used for daily intercalibration according to del Giorgio
et al. (1996) and Gasol & del Giorgio (2000).
The instrument was equipped with an air cooled argon laser (15 mW, Ex.
488 nm). Green fluorescence intensity (GFL) was detected with the standard
filter setup (Em. 530 +/- 15 nm) as fluorescence 1 (FL1). Photomultiplier
voltages were adjusted so that the bacterial populations were centered in the
channels corresponding to the second and third logarithmic decade for
fluorescence and the second decade for sidescatter (SSC). Analyses were
performed at the lowest flow rate (approx. 14 µl min-1). Event range was
between 300 and 900 sec-1. A threshold for FL1 was set in order to remove
- 20 -
Section 2: Material and methods
background noise and to enhance processing speed. Manual gating was used
after visual inspection of the dot plot of SSC vs. FL1 to define a region of
interest.
Data were stored as list-mode files and subsequently displayed and calculated
either with CellQuest software version 3.3 or WinMDI (version 2.8; J. Trotter,
The Scripps Institute, Flow Cytometry Core Facility, La Jolla, USA).
Hydrolytic enzyme activities
Rates of hydrolytic enzyme activities were determined by kinetic measurements
using 4-methylumbelliferyl (MUF) and 7-amino-4-methylcoumarin (AMC)
labelled substrate analogues. Model substrate initial stock solutions (5 mM) of
MUF-α-D-glucoside, MUF-phosphate and L-Leucine-AMC were prepared
according to Table 1. Please note, that all solutions have always to be kept in
the dark (Hoppe, 1983).
Table 1: Solubility of 4-methylumbelliferyl (MUF)- α-D-glucoside, MUF- phosphate and
L-Leucine 7-amino-4-methylcoumarin (AMC).
substrate analogue
solubility
Hoppe et al. (1983)
Chrost et al. (1989)
Chrost et al. (2006)
this study
MUF α-D-glucoside
Methylcellosolve
MUF phosphate
Methylcellosolve
H2O
H2O
H2O (deionised)
L-Leucine AMC
Methylcellosolve
H2O
Ethanol 96%
Ethanol 96%
α-glucosidase,
phosphatase
For
this
study
kinetics
of
Methylcellosolve
and
leucine-
aminopeptidase were analyzed. A complete list of substrate analogues tested in
this experiment can be found in the appendix.
A set of five different concentrations for each substrate analogue (156.25,
312.50, 625, 1250, 2500 µM) were prepared by dilution of the initial stock
solutions with sterile deionised H2O. These stock solutions were kept at –30°C
less than two weeks. Prior to our experiment 96-well plates were prepared,
allowing numerous replicates and high sample throughput. Aliquots of each
- 21 -
Section 2: Material and methods
substrate analogue (20 µl) and of each concentration in triplicates were pipetted
into 96-well plates. These prepared 96-well plates were kept frozen, until kinetic
measurements were conducted.
Subsamples of 230 µl of the six mesocosms were transferred into the prepared
wells of the plate immediately after sampling. A multichannel pipette was used
to fasten this procedure. Thus, final concentrations of substrate solutions were
12.5, 25, 50, 100 and 200 µM. Initial fluorescence (t0) was measured shortly
after the addition of samples to the substrate analogue aliquots by using a
microplate reader (BMG Labtech FLUOstar OPTIMA, Germany), which is
equipped with a xenon flash lamp. Excitation and emission filters were adjusted
to the fluorochrome characteristics (355 and 460 nm, respectively). Incubations
were performed for 1h at in situ temperature in the dark. The amount of
measured fluorescence intensity is proportional to the amount of hydrolyzed
substrate analogue. The difference between the start-stop measurement is
needed to calculate the maximal velocity (Vmax) and the half saturation
constant (Km).
Because the intensity of fluorescence is influenced by pH, calibration curves of
MUF and AMC solutions with different pH were determined. In order to correct
the fluorescence intensity change due to different pH levels in the samples, a
calibration factor is necessary. MUF- and AMC- solutions (solved in sterile,
deionised H2O) were prepared in four different concentrations (final 0.156,
0.325, 1.25 and 2.5 µM). The initial stock solutions of MUF and AMC were
diluted in 50mM MOPS buffer solutions with six different pH values (6.5, 7, 7.5,
8, 8.5 and 9). The fluorescence intensities were measured in 96-well plates as
described above. The calibration factor was determined by relating the different
MUF respectively AMC concentrations to the obtained fluorescence intensities.
In respect to different pH, this relationship was characterized by different
slopes. For calculation of the pH-corrected fluorescence intensities a polynomial
fit was used to relate the slopes to pH. The equations of the polynomial fit were
used for correction.
- 22 -
Section 2: Material and methods
Enzyme efficiency (Vmax/Km) was calculated from hyperbolic fitting of kinetic
measurements using the corrected fluorescence intensities. Kinetics of the five
different concentrations were calculated (simple ligand binding, one site
saturation) for the three replicates and for t0 and t1 separately, using the
software SigmaPlot (Version 10.0, Systat Software, Inc., Germany). The mean
of the fits of the three replicates were calculated for t0 and t1. Vmax and Km of
the averaged difference of t1 and t0 was calculated again as described above.
Turnover rates of the substrate analogues at non saturating concentrations
(1.56 µM) were taken from this fit.
Bacterial activities
Rates of leucine uptake were determined by incorporation of
3
[H]-leucine
(3H-Leu) and thymidine uptake by incorporation of 3[H]-thymidine (3H-TdR),
roughly followed the protocols described by Simon & Azam (1989) and
Fuhrman & Azam (1982), respectively. Triplicate 1.5 ml samples and a pre-fixed
blank were incubated at in situ temperature in the dark for 1 h: one set was
amended with
3
H-Leu (5.29*1012 Bq mmol-1; (Moravek Biochemicals, Inc.,
California, USA)) at a final concentration of 80 nM and a second set received
3
H-TdR (2.52*1012 Bq mmol-1; (Moravek Biochemicals, Inc., California, USA)) at
a final concentration of 80 nM. Incubations were stopped by adding
formaldehyde buffered with 4% (v/v) boric acid. After 15 min of fixation, samples
were centrifuged with RCF = 6240xg at 4°C for 10 min and the supernatants
were gently removed by suction. Pellets were resuspended in ice-cold 5%
trichloroacetic acid (TCA). Thereafter, samples were centrifuged at 4°C for 10
min and aspirated again. Only the samples of the first set (3H-Leu incorporation)
were additionally washed with 1.5 ml of 80% ethanol, centrifuged at 4°C for 10
min and aspirated again. Finally samples were dissolved in 1.5 ml scintillation
cocktail (Ultima Gold, PerkinElmer) and kept refrigerated until radio-assay
analysis using a TriCarb (1600 TR) liquid scintillation counter within four weeks.
- 23 -
Section 2: Material and methods
Calculation of growth rates
Growth rates of unicellular cyanobacteria and heterotrophic bacteria were
calculated by using the following equation:
1
N
⎛ A(t ) ⎞
growth rate (t0 , t ) = ⎜
⎟ −1
A
(
t
)
⎝ 0 ⎠
(6)
where N = t-t0 is the number of time units between to and t, and A is the
parameter at the certain time t.
Statistical Analyses
Statistical analyses were performed with the software SigmaStat version 3.5
(Systat Software, Inc., Germany).
- 24 -
Section 3: Results
3
Results
Experimental boundary conditions
The experiment was conducted from 10th until 21st of July 2007. The
discontinuance of sampling as shown in Figure 6 was due to the weather
conditions. Sampling of the mesocosms was impossible as result of mean wind
speed of 7.7 m/s (4 Bft), with maximums up to 12-15 m/s, and wave heights up
to 2.5-3 m. Above wave heights of 1.5 m (at 4 Bft, wind speed 5-8 m/s) the
water of the mesocosms exchanged occasionally with surrounding Baltic Sea
water. At wave heights above 2.5 m the mesocosms became instable and
bounced for- and backwards, thus water exchanged frequently. In this work
equal water exchanged is assumed for all mesocosms. Throughout the entire
experiment the water temperature of the Baltic increased from ~12°C to ~17°C.
The mesocosms were acidified three times due to the boundary conditions.
Figure 6: Boundary conditions in the Baltic Sea in July 2007: Water temperature (°C)
(blue line) of the Baltic and wind speed (m/s)(red line). Sampling frequency of
mesocosms is marked with black dots. Acidification events are highlighted by boxes.
- 25 -
Section 3: Results
Vertical distributions (CTD measurements)
We focused on the upper 10 m of the mesocosms, which were sampled by an
integrating sampler. The vertical distributions of water temperature, salinity,
pCO2 and pH are given in the following.
Temperature
At the start of the experiments at the 10th of July, before acidification at all, the
water temperatures in the mesocosms differed in the upper 4 m considerably
(Fig. 7, A). Compared to the Baltic, in the mesocosms the water temperatures of
the surface layer (~1 m) were about 1 to 1.5°C warmer, whereas from 4 m down
to 17.5 m only slight differences were observed. After the 1st acidification mean
water temperatures down to 10 m were approx. 1°C warmer than mean
temperatures at the 10th of July (Fig. 7, B). In the upper 3 m water temperatures
were about 1°C warmer. The Baltic differed from the mesocosms in the surface
layer (~1 m) by 0.5°C. A thermocline established at about 10 m depth in the
Baltic, whereas water temperatures in the mesocosms decreased slowly from
13.5 to 12.5°C.from 10 to 17.5 m. After the 2nd acidification the decrease of the
water temperatures with depth was almost linear from 15°C in the surface layer
to 14°C at 10 m depth in the mesocosms (Fig. 7, C). The Baltic water was about
0.2°C warmer and followed the same trend down to 10 m. A thermocline was
observed in the Baltic but not in the mesocosms. However, mean water
temperatures were slightly higher after the 2nd acidification.
A
B
C
D
Figure 7: Comparisons of the vertical distribution of water temperatures in the
mesocosms (MC) 1 - 6 and in the Baltic before (A) and after the acidifications (B, C, D)
(solid lines: 0 - 10 m, dotted lines: 10 - 17.5 m) (data, K. Schulz).
- 26 -
Section 3: Results
During the experiment a maximum water temperature of more than 17°C was
observed in the surface layer of the Baltic after the third acidification (Fig. 7, D).
The changes of water temperatures with depth were more variable for
mesocosms (MCs) 1, 3 and 4, especially in the upper 6 m, since these
mesocosms were broken prior to the 3rd acidification and were not acidified
again. Water temperatures of the Baltic and of the remaining MCs 2, 5 and 6
were almost 2°C warmer in the upper 2 m than water temperatures from 2 to
10 m and did not differ from each other.
The increase of water temperatures in the upper 10 m during the experiment
was observed in all mesocosms as well as in the Baltic (Fig. 8). The differences
in the mesocosms between the 10th of July and the 1st acidification were almost
equal. After the 2nd acidification water temperatures in the surface layer did not
increase as much as before, whereas after the 3rd acidification the water
temperatures in the upper 2 m showed huge variability.
Figure 8 : Vertical profiles of water temperature in the mesocosms (MC) 1 - 6 and in
the Baltic for 10th July (blue), 14th July (yellow), 16th July (red) and 20th July (green).
(solid lines: 0 - 10 m, dotted lines: 10 - 17.5 m) (data, K. Schulz)
- 27 -
Section 3: Results
Salinity
Salinity showed mean values of ~7.5 psu in the upper 10 m in all mesocosms
and in the Baltic at the 10th of July (blue lines, Fig. 9). The salinity varied about
0.1 psu at the surface layers. A decrease of salinity was observed after 4 - 6
days, during the 1st and 2nd acidification (yellow and red lines). In the Baltic the
decrease was about 0.1 psu, while it varied between the mesocosms. However,
it was not more than +/- 0.05 psu. After the 3rd acidification (green lines) the
vertical distribution of the salinity differed immensely. Compared to the Baltic
(~7.4 psu, surface layer varied), the salinity of the remaining three mesocosms
(MC 2, 5 and 6) decreased with depth and varied from each other. In
mesocosms 2 and 6 the salinity was higher after the 3rd acidification compared
to the 1st and 2nd acidification and followed an increasing trend from surface to
10 m. The salinity in MC 5 further decreased to surface value of ~7.4 psu and
followed an increasing trend down to 10 m depth. Since Mcs 1, 3, and 4 were
broken prior to the 3rd acidification and not acidified a third time, the mean
salinity equalled Baltic Sea values.
Salinity measurements reveal that below 10 m an inflow of surrounding
seawater occurred in almost all mesocosms due to broken bottoms.
- 28 -
Section 3: Results
Figure 9: Vertical profiles of salinity in the mesocosms (MC) 1 - 6 and in the Baltic for
10th July (blue), 14th July (yellow), 16th July (red) and 20th July (green). (solid lines: 0 10 m, dotted lines: 10 - 17.5 m) (data, K. Schulz)
pH and pCO2
The variability of the vertical distribution of the experimental elevated pCO2
concentrations in the mesocosms was related with the overall amount of added
HCl (Fig. 10). The higher the amount of HCl (respectively the concentration of
pCO2), the higher were vertical heterogeneities. After the 1st acidification (yellow
line) the vertical distribution of the pCO2 in the upper 10 m did not vary much in
MCs 2 and 6, but were differently enhanced compared to the reference
measurements at the 10th of July. The higher the pCO2 concentration the higher
was the vertical variability in MCs 1, 3, and 5 after the 1st acidification. After the
2nd acidification (red line, Fig. 10) the vertical variability was even stronger in
- 29 -
Section 3: Results
MC 1, 3, and 5 than after the 1st acidification. The importance of the vertical
variability was underlined in MC 1 in the upper 10 m of the 2nd acidification,
where pCO2 values range from 1100 µatm up to a maximum of more than 3000
µatm.
After the 3rd acidification (green line, Fig. 10) the vertical distribution of pCO2 in
the remaining MCs 2, 5 and 6 was consistent. The pCO2 concentrations were
differently enhanced compared to the reference measurements at the 10th of
July.
Figure 10: Vertical profiles of pCO2 (calculated by pH and alkalinity)) in the
mesocosms (MC) 1 - 6 and in the Baltic for 10th July (blue), 14th July (yellow), 16th July
(red) and 20th July (green). (solid lines: 0 - 10 m, dotted lines: 10 - 17.5 m)
Similar patterns were found for the vertical distribution of pH (Fig. 11). Slight
differences in pH were observed in the Baltic and in the reference mesocosm 4
during the experiment, where the pH increased from 8 to 8.2 over time. Initial
pH values of 8.1 (blue lines) were equal in all mesocosms. After the 1st
- 30 -
Section 3: Results
acidification (yellow lines) the pH artificially decreased in MC 2 to 7.9 and in MC
6 to 7.8 compared to the reference measurement. In MC 3, 5 and 1 the pH
varied vertically, but mean values were about 7.6, 7.5 and 7.4, respectively.
After the 2nd acidification (red lines) in MC 2 and MC 6 the pH was 7.8 and 7.7,
respectively. In MC 3 and 5 the pH varied vertically again, but mean values
were about 7.6 and 7.4, respectively. The vertical variability of MC 1 ranged
from 7.6 to 7.2, with the mean value of 7.4.
Figure 11: Vertical profiles of pH in the mesocosms (MC) 1 - 6 and in the Baltic for 10th
July (blue), 14th July (yellow), 16th July (red) and 20th July (green). (solid lines: 0 - 10 m,
dotted lines: 10 - 17.5 m) (data, K. Schulz)
Despite the fact that there was an exchange of water due to the boundary
conditions and therefore mesocosm damages, the CTD values indicate that the
upper 10 m of the water column (of the mesocosms whose data were used for
this thesis) were only slightly affected.
- 31 -
Section 3: Results
The pH and pCO2 history of every single mesocosm
The addition of HCl to five of six mesocosms led to different levels of
acidification (respectively pCO2). During the whole experiment each mesocosm
was treated differently and the range of pH varied considerably. While the pH
(mean of 0-10 m) of the untreated mesocosm MC 4 varied between 8.1 and 8.2,
the range in MC 5 for example differed between 7.4 and 8.1 (Fig. 12). The
scope of the acidifications was to establish a gradient of diverse steady pH, but
the pH and pCO2 concentrations were not constant over time and changed
more or less fast back to values near present day.
8.4
n= 10
n= 19
n= 5
n= 13
n= 5
n= 19
MC 4
MC 2
MC 3
MC 6
MC 1
MC 5
8.2
pH (CTD)
8.0
7.8
7.6
7.4
7.2
Figure 12: Range of pH (mean of 0-10 m) in the mesocosms (MC) 1-6 during the
entire experiment (solid line: median, dotted line: mean)
The more acidic mesocosms changed faster with time than the less acidified
mesocosms due to the more pronounced gradient between sea surface/air.
Thus, the rebalance to present day values was not linear. Based on the fact that
- 32 -
Section 3: Results
the pH range of the untreated mesocosm 4 was stable over time, it was used as
a reference in this study.
Since mesocosms 1 and 3 were sampled less frequently (n=5) compared to the
other mesocosms and their pH values varied over a large range, data of
mesocosms 1 and 3 are not included in the analyses.
The temporal development of the pCO2 concentrations in the differently HCltreated mesocosms (MC 4 ≙ not, MC 2 ≙ weak, MC 6 ≙ medium and MC 5 ≙
strong) showed this decreasing trend within each acidification experiment
(Fig. 13). Data of the 3rd acidification experiment are not included in this diploma
thesis, because the not acidified reference mesocosm was not available
anymore. Additionally, it can not be ensured that the first 10 m of the three
remaining mesocosms were not affected by mesocosm damages and water
exchange with surrounding Baltic Sea water during this last acidification
experiment.
2000
st
nd
1
start
rd
2
3
1800
1600
pCO2 [µatm]
1400
strong
1200
medium
1000
weak
not
800
600
400
200
10/07
12/07
14/07
16/07
18/07
20/07
22/07
date
HCl
HCl
HCl
Figure 13: Temporal development of the pCO2 concentrations in the mesocosms (not,
weakly, medium and strongly acidified) for the 1st, 2nd and 3rd acidification experiments.
- 33 -
Section 3: Results
For further data analyses, means were calculated for the different mesocosms
representing different ranges of pCO2 concentrations for the 1st and 2nd
acidification experiment. Please note, that the categorized range of pCO2
concentrations in the mesocosms differed between the 1st to the 2nd acidification
experiment (Fig. 14).
st
pCO2 [µatm]
2000
nd
1 acidification
A
2
acidification
B
1500
1000
500
0
not weak med strong
not weak med strong
Figure 14: Range of pCO2 concentrations in the mesocosms (not, weakly, medium and
strongly acidified) for the 1st (A) and 2nd (B) acidification experiment.
This two acidifications were analysed as two different acidification experiments,
which certainly had a temporal relation to each other, but also differences in
their abiotic environments and pCO2 ranges from one to the other acidification
experiment.
- 34 -
Section 3: Results
Biogeochemical processes
Particulate Organic Matter (POM)
To address possible consequences of ocean acidification, the effects of
elevated pCO2 concentrations on biogeochemical level were studied in this field
experiment.
Mean concentrations of particulate organic carbon (POC) did not show any
significant response to the HCl treatment during the 1st acidification experiment
(Fig. 15, A). However, after the 2nd acidification POC concentrations were
significantly enhanced in the not acidified mesocosm compared to the
mesocosms that experienced acid treatment (ANOVA, Holm-Sidak, p = 0.01;
Fig. 15, B). Mean POC concentrations of the acidified mesocosms were
significantly reduced after the 2nd acidification when compared to the 1st
(ANOVA on ranks, Dunn’s, p = 0.005).
POC [µM]
60
1st acidification
A
2nd acidification
B
50
40
10
0
not
weak
med strong
not
weak
med strong
acidification by HCl (range ~350-1500 µatm pCO2)
Data: M. Voss
Figure 15: Means of Particulate Organic Carbon (POC) concentrations in the
mesocosms (not, weakly, medium and strongly acidified) for the 1st (A) and 2nd (B)
acidification experiment (data, M. Voss).
- 35 -
Section 3: Results
Mean concentrations of particulate organic nitrogen (PON) did not vary
significantly with increasing pCO2 concentrations between the 1st and 2nd
acidification experiment (Fig. 16).
PON [µM]
7
1st acidification
A
2nd acidification
B
6
5
4
0
not
weak
med strong
not
weak
med strong
acidification by HCl (range ~350-1500 µatm pCO2)
Data: M. Voss
Figure 16: Means of Particulate Organic Nitrogen (PON) concentrations in the
mesocosms (not, weakly, medium and strongly acidified) for the 1st (A) and 2nd (B)
acidification experiment (data: M. Voss).
- 36 -
Section 3: Results
Particulate organic phosphorus (POP) concentrations (means) did not change
significantly under elevated pCO2 concentrations during the 1st and 2nd
acidification experiment (Fig. 17). However, in contrast to the 1st acidification
experiment mean POP concentrations were significantly reduced in the
mesocosms that experienced acid treatment after the 2nd acidification (ANOVA,
Holm-Sidak, p = 0.01).
0.30
1st acidification
A
2nd acidification
B
POP [µM]
0.25
0.20
0.15
0.10
0.05
0.00
not
weak
med strong
not
weak
med strong
acidification by HCl (range ~350-1500 µatm pCO2)
Data: K. Isensee
Figure 17: Means of Particulate Organic Phosphorus (POP) concentrations in the
mesocosms (not, weakly, medium and strongly acidified) for the 1st (A) and 2nd (B)
acidification experiment (data, K. Isensee).
- 37 -
Section 3: Results
C:N:P ratio
During the 1st and 2nd acidification experiment means of the particulate
carbon/nitrogen (C/N) ratio (mol/mol) did not change significantly neither under
elevated pCO2 concentrations nor over time (Fig. 18). Mean C/N ratios were
higher in all mesocosms during both experiments. as expected by the canonical
Redfield ratio of 6.6 .
12
1st acidification
A
2nd acidification
B
10
C/N
8
6
4
2
0
not
weak
med strong
not
weak
med strong
acidification by HCl (range ~350-1500 µatm pCO2)
Figure 18: Means of the carbon/nitrogen (C/N) ratio (mol/mol) in the mesocosms (not,
weakly, medium and strongly acidified) for the 1st (A) and 2nd (B) acidification
experiment (red solid lines: Redfield ratio of 6.6).
- 38 -
Section 3: Results
For both experiments no significant difference between the different HCl
treatments were observed for means of the particulate carbon/phosphorus (C/P)
ratios (Fig. 19). However, mean C/P ratios of the HCl treated mesocosms were
significantly higher during the 1st compared to the 2nd acidification experiment
(ANOVA on ranks, Dunn’s, p = 0.001).
Mean C/P ratios were three to two times higher during the 1st respectively 2nd
experiment compared to the Redfield ratio of 106.
400
1st acidification
A
2nd acidification
B
C/P
300
200
100
0
not
weak
med strong
not
weak
med strong
acidification by HCl (range ~350-1500 µatm pCO2)
Figure 19: Means of the carbon/phosphorus (C/P) ratio in the mesocosms (not,
weakly, medium and strongly acidified) for the 1st (A) and 2nd (B) acidification
experiment (red solid lines: Redfield ratio of 106).
- 39 -
Section 3: Results
Means of the particulate nitrogen/phosphorus (N/P) ratio did not change
significantly with increasing pCO2 concentrations during the 1st and 2nd
acidification experiment and varied between ~25 and ~30 (Fig. 20). However, in
contrast to the 1st acidification experiment mean N/P ratios were significantly
reduced in the mesocosms that experienced acid treatment after the 2nd
acidification (ANOVA, Holm-Sidak, p = 0.009).
Moreover, means of the N/P ratio were enhanced twofold compared to the
Redfield ratio of 16.
50
1st acidification
A
2nd acidification
B
N/P
40
30
20
10
0
not
weak
med strong
not
weak
med strong
acidification by HCl (range ~350-1500 µatm pCO2)
Figure 20: Means of the nitrogen/phosphorus (N/P) ratio in the mesocosms (not,
weakly, medium and strongly acidified) for the 1st (A) and 2nd (B) acidification
experiment (red solid lines: Redfield ratio of 16).
- 40 -
Section 3: Results
Chlorophyll a and nutrients
Chlorophyll a (Chl a) and nutrient concentrations were low in the Baltic, when
this campaign took place. Concentrations of nitrate (NO3-) were at the detection
limit. Phosphate (PO43-) concentrations were 0.22 (±0.04) µmol l-1 and
decreased by 0.1 µmol l-1 in all mesocosms over time (date not shown). Chl a
concentration was 2.13 (±0.26) µg l-1 and did not change significantly. Overall
the experiment was conducted in a non-bloom situation (Fig. 21).
-1
Chl a [µg l ]
4
1st acidification
A
2nd acidification
B
3
2
1
0
not weak med strong
not weak med strong
acidification by HCl (range ~350-1500 µatm pCO2)
Data: P. Fritsche
Figure 21: Means of Chlorophyll a (Chl a) concentrations in the mesocosms (not,
weakly, medium and strongly acidified) for the 1st (A) and 2nd (B) acidification
experiment (data, P. Fritsche).
- 41 -
Section 3: Results
Amino acids
Mean concentrations of dissolved free amino acids (DFAA) did not change
significantly with increasing pCO2 concentrations during the 1st and 2nd
acidification experiment (Fig. 22), although diurnal variabilities were observed
(data not shown). During the 1st acidification experiment DFAA concentrations
were significantly higher compared to the 2nd experiment (ANOVA on ranks,
Dunn’s, p = 0.032).
In general concentrations of DFAA were ~50% lower during both experiments in
all mesocosms compared to the mean start concentration of 131.6 nM .
The composition of the DFAA showed differences by comparing the three
acidification experiments (data not shown, appendix (Fig. 39)). However, the
DFAA composition did not show a direct response to the strength of acid
treatment.
120
1st acidification
A
2nd acidification
B
DFAA [nM]
100
80
60
40
20
0
not
weak
med strong
not
weak
med strong
acidification by HCl (range ~350-1500 µatm pCO2)
Figure 22: Means of dissolved free amino acid (DFAA) concentrations in the
mesocosms (not, weakly, medium and strongly acidified) for the 1st (A) and 2nd (B)
acidification experiment.
- 42 -
Section 3: Results
Transparent Exopolymer Particles
Dynamics of Transparent Exopolymer Particles (TEP) are a good indication for
biologically-driven
changes
of
the
carbon-pool.
In
this
study
mean
concentrations of TEP were considerable low between ~60 and ~100 µg
GumXanthan equivalents (Xeq.) l-1 (Fig. 23). After the 1st acidification TEP
concentrations of the not acidified mesocosm did not change compared to the
weakly acidified mesocosm (Fig. 23, A). However mean concentrations of TEP
significantly decreased with increasing pCO2 concentrations from the weakly to
the strongly acidified mesocosm (ANOVA on ranks, Turkey, p = 0.013). During
the 2nd acidification experiment a significant difference was observed between
the not acidified and the mesocosms that experienced acid treatment (Fig. 23,
B, (ANOVA, Holm-Sidak, p = 0.001)). TEP concentrations increased over time
in the not acidified mesocosm (t-test, p < 0.001).
st
-1
TEP [µg Xeq. l ]
120
nd
1 acidification
A
2
acidification
B
100
80
60
0
not
weak
med strong
not
weak
med strong
acidification by HCl (range ~350-1500 µatm pCO2)
Figure 23: Means of Transparent Exopolymer Particles (TEP) in the mesocosms (not,
weakly, medium and strongly acidified) for the 1st (A) and 2nd (B) acidification
experiment.
- 43 -
Section 3: Results
Eukaryotic phytoplankton dynamics
Phytoplankton plays a major role in biogeochemical cycling of inorganic and
organic matter, and is known as main TEP producer. Mean abundance of
eukaryotic phytoplankton, determined by flow-cytometry, decreased significantly
(linear regression analysis, r2 = 0.97; p = 0.016) from 4.28 (±0.01) x104 cells
ml-1 to 2.33 (±0.86) x104 cells ml-1 with increasing pCO2 concentrations after the
1st acidification (Fig. 24, A). During the 2nd acidification experiment the highest
mean abundance was observed in the not acidified mesocosm, which was
significantly higher compared to the abundance in the acidified mesocosms
(Fig. 24, B, (ANOVA, Holm-Sidak, p < 0.001)). The lowest abundance of
eukaryotic phytoplankton after the 2nd acidification was found in the medium
Eukaryotic phytoplankton
4
-1
[x10 cells ml ]
acidified mesocosm (ANOVA, Holm-Sidak, p< 0.001).
5
1st acidification
A
2nd acidification
B
4
3
2
1
0
R2 = 0.97
p = 0.016
not weak med strong
not weak med strong
acidification by HCl (range ~350-1500 µatm pCO2)
Data: H. Johansen & A. Grüttmüller
Figure 24: Means of eukaryotic phytoplankton abundances in the mesocosms (not,
weakly, medium and strongly acidified) for the 1st (A) and 2nd (B) acidification
experiment (data, H. Johansen & A. Grüttmüller).
- 44 -
Section 3: Results
Diazotrophic cyanobacteria dynamics
Abundances of diazotrophic cyanobacteria Nodularia spp. and Aphanizomenon
spp. were determined by fluorescence microscopy.
Abundances of Nodularia spp. did not change significantly between the different
treatments during the 1st and 2nd acidification experiment (Fig. 25. A). But
abundances decreased from ~3000 to ~900 units l-1 (one unit = 100 µm) over
time from the 1st to the 2nd acidification experiment.
HCl
A
not
weak
medium
strong
-1
Aphanizomenon spp. [units l ]
-1
Nodularia spp. [units l ]
5000
HCl
4000
3000
2000
1000
0
50000
B
40000
30000
20000
10000
0
13/07/07
15/07/07
17/07/07
19/07/07
21/07/07
date
Figure 25: Temporal dynamics of Nodularia spp. (A) and Aphanizomenon spp. (B) in
the mesocosms (not, weakly, medium and strongly acidified) for the 1st and 2nd
acidification experiment (1 unit = 100 µm) (data, K. Haynert).
- 45 -
Section 3: Results
Abundances of Aphanizomenon spp. were not significantly different during the
1st experiment, whereas during the 2nd acidification experiment abundances of
the not and weakly acidified mesocosms increased compared to the medium
and strongly acidified mesocosm (Fig. 25, B). In contrast to Nodularia spp.,
abundances of Aphanizomenon spp. increased in the not and weakly acidified
mesocosms over time.
- 46 -
Section 3: Results
Phytoplankton activity
Autotrophic rates, CO2 uptake and nitrogen (N2) fixation, were measured in
order to follow the impact of increasing CO2 concentrations on the physiology of
the autotrophs.
CO2 uptake
In general CO2 uptake rates were low, ranging from 0.02 to 0.25 µmol l-1 h-1
(Fig. 26). The CO2 uptake was dominated by organisms smaller than 10 µm
(grey bars) during the entire experiment. Mean CO2 uptake rates of organisms
larger than 10 µm (black bars) were not significantly affected by the HCl
treatment during the 1st and the 2nd acidification experiment. Furthermore only
CO2 uptake rates of organisms larger than 10µm decreased significantly from
the 1st to the 2nd acidification experiment (ANOVA on ranks, Dunn’s, p<0.001).
nd
-1
CO2 uptake [µmol l-1 h ]
st
0.35
0.30
2
1 acidification
A
acidification
B
>10µm
<10µm
0.25
0.20
0.15
0.10
0.05
0.00
not
weak
med
strong
not
weak
med
strong
acidification by HCl (range ~350-1500 µatm pCO2)
Data: M. Voss
Figure 26: Means of CO2 uptake rates of organisms >10µm (black) and <10µm (grey)
in the mesocosms (not, weakly, medium and strongly acidified) for the 1st (A) and 2nd
(B) acidification experiment (data, M. Voss).
- 47 -
Section 3: Results
Thus, the proportion of the CO2 uptake of organisms smaller to larger than 10
µm increased significantly from the 1st to the 2nd acidification experiment
(ANOVA on ranks, Dunn’s, p<0.001). The large error bars are due to the diurnal
variability (data not shown).
N2 fixation
Overall N2 fixation rates were low between 0.25 and 3 nmol l-1 h-1 (Fig. 27).
Mean N2 fixation rates of organisms larger 10 µm (black bars) did not change
with increasing pCO2 concentrations during the 1st acidification experiment (Fig.
27, A). After the 2nd acidification mean N2 fixation rates in the larger than 10 µm
size class were significantly higher in the not acidified mesocosm than in the
HCl-treated mesocosms (Fig. 27, B, (ANOVA, Holm-Sidak, p=0.004)).
Mean N2 fixation rates of organisms smaller than 10 µm (grey bars) did not
change significantly neither with increasing pCO2 concentrations during the 1st
and the 2nd acidification experiment nor over time from the 1st to the 2nd
acidification experiment (Fig. 27).
Finally N2 fixation was dominated by organisms smaller than 10 µm, due to the
decrease of mean N2 fixation rates of organisms larger than 10 µm over time.
Thus the proportion of N2 fixation rates of organisms smaller to larger than
10 µm increased significantly from the 1st to the 2nd acidification experiment
(ANOVA on ranks, Dunn’s, p<0.001).
- 48 -
Section 3: Results
-1
N2 fix [nmol l-1 h ]
3.5
3.0
1st acidification
A
2nd acidification
B
>10µm
<10µm
2.5
2.0
1.5
1.0
0.5
0.0
not
weak
med
strong
not
weak
med
strong
acidification by HCl (range ~350-1500 µatm pCO2)
Data: M. Voss
Figure 27: Means of nitrogen fixation (N2 fix) rates of organisms >10µm (black) and
<10µm (grey) in the mesocosms (not, weakly, medium and strongly acidified) for the 1st
(A) and 2nd (B) acidification experiment (data, M. Voss).
- 49 -
Section 3: Results
Unicellular cyanobacteria
Mean numbers of unicellular cyanobacteria, determined by Flow Cytometry, did
not response significantly to increasing pCO2 concentrations after the 1st and
2nd acidification (Fig. 28). No significant differences were observed from the 1st
to the 2nd acidification experiment, although mean numbers of small
Unicellular cyanobacteria
5
-1
[x10 cells ml ]
cyanobacteria increased slightly in the not acidified mesocosms.
st
6
5
1 acidification
A
2
nd
acidification
B
4
3
2
1
0
not weak med strong
not weak med strong
acidification by HCl (range ~350-1500 µatm
Data: H. Johansen & A. Grüttmüller
Figure 28: Means of unicellular cyanobacteria (determined by Flow Cytometry)
abundances in the mesocosms (not, weakly, medium and strongly acidified) for the 1st
(A) and 2nd (B) acidification experiment (data, H. Johansen & A. Grüttmüller).
- 50 -
Section 3: Results
Bacterial dynamics
Mean abundances of heterotrophic bacteria (determined by Flow Cytometry) did
not show any significant response to the HCl treatment after the 1st acidification
(Fig. 29, A). During the 2nd acidification experiment significantly increased
numbers of heterotrophic bacteria were observed in the not acidified mesocosm
compared to the mesocosms that experienced acid treatment (Fig. 29, B,
(ANOVA, Holm-Sidak, p < 0.001)). By comparing the abundance in the different
mesocosms between the 1st and 2nd acidification experiment separately,
statistically significant enhanced numbers of heterotrophic bacteria were
observed in the not, weakly and strongly acidified mesocosms after the 2nd
acidification (t-test, pnot = 0.008, pweak = 0.013, pstrong = 0.032).
6
-1
Bacteria [x10 cells ml ]
st
5
nd
1 acidification
A
2
acidification
B
4
3
2
1
0
not weak med strong
not weak med strong
acidification by HCl (range ~350-1500 µatm pCO2)
Figure 29: Means of heterotrophic bacteria abundances in the mesocosms (not,
weakly, medium and strongly acidified) for the 1st (A) and 2nd (B) acidification
experiment (medium of 2nd acidification: n=1).
- 51 -
Section 3: Results
Since TEP abiotically form from dissolved organic precursors, mainly released
by marine organisms, it is likely, that changes in TEP dynamics were correlated
with the dynamics of eukaryotic phytoplankton, cyanobacteria and heterotrophic
bacteria.
Indeed, TEP dynamics were significantly correlated with the dynamics of
cyanobacteria in all HCl-treated mesocosms during both experiments (Fig. 30,
A, (linear regression analysis, r2 = 0.95, p = 0.003)). A strong correlation was
also found between the dynamics of heterotrophic bacteria and TEP (Fig. 30, B,
(linear regression analysis, r2 = 0.98, p = 0.005)). Please note, that TEP vs.
pCO2 and TEP vs. eukaryotic phytoplankton did not show any correlation at all.
A
B
100
-1
TEP [µg Xeq. l ]
120
80
60
40
20
0
2.0
r² = 0.95
P = 0.003
2.4
2.8
3.2
5
3.6
-1
Cyanobacteria [x10 cells ml ]
r² = 0.98
P = 0.005
2.2
2.4
2.6
2.8
3.0
6
3.2
3.4
3.6
-1
Bacteria [x10 cells ml ]
Figure 30: Linear Correlations between Transparent Exopolymer Particles (TEP) and.
cyanobacteria (orange) (A) and TEP vs. heterotrophic bacteria (blue) (B). Data of the
not acidified mesocosms (1st acidification (red) and 2nd acidification (black)) were
neglected.
- 52 -
Section 3: Results
Hydrolytic enzyme activities
In order to follow the impact of decreasing pH on the microbial degradation of
organic matter enzyme efficiency (Vmax/Km) of α-glucosidase, leucineaminopeptidase and alkaline phosphatase were measured by substrate kinetics
using MUF- and AMC-labelled substrate analogues.
α-glucosidase
In general turnover rates of α-glucosidase were low (0.021 ± 0.007 µmol l-1 h-1).
The enzyme efficiency (Vmax/Km) of α-glucosidase was only little affected by
Vmax/Km (MUF-α-glucose) [h-1]
pH during the entire experiment and varied only slightly over time (Fig. 31).
0.024
0.023
0.022
0.021
0.020
pH
date
Figure 31: Linear model fit of the enzyme efficiency (Vmax/Km) of α-glucosidase in all
mesocosms and during the entire experiment (multiple R(z/xy) = 0.23, p = 0.2).
- 53 -
Section 3: Results
Leucine-aminopeptidase
In contrast to α-glucosidase the enzyme efficiency of leucine-aminopeptidase
was more sensitive to changes in pH and dropped almost by 60 to 70% under
strong acidification (Fig. 32). The high ratio of Vmax vs. Km indicate a high
efficiency
in
substrate
turnover
(mean
leucine
turnover
was
1.2 ± 0.4 µmol l-1 h-1). Over time a slight increase of the ratio of Vmax vs. Km
was observed. Enzyme efficiency of leucine-aminopeptidase decreased in
Vmax/Km (AMC-leucine) [h-1]
average by ~40% with decreasing pH from 8.1 to 7.6.
1.00
0.75
0.50
0.25
0.00
pH
date
Figure 32: Linear model fit of the enzyme efficiency (Vmax/Km) of leucineaminopeptidase in all mesocosms and during the entire experiment (multiple R(z/xy) =
0.68, p < 0.001).
- 54 -
Section 3: Results
Alkaline phosphatase
Activity of alkaline phosphatase did not change over time during the entire
experiment, but responded noticeably to the HCl treatments (Fig. 33). The
calculated linear model shows a pronounced decrease in the Vmax/Km ratio of
Vmax/Km (MUF-phosphate) [h-1]
~20% with decreasing pH. Mean phosphate turnover was 0.85 ± 0.1 µmol l-1 h-1.
0.600
0.575
0.550
0.525
0.500
pH
date
Figure 33: Linear model fit of the enzyme efficiency (Vmax/Km) of alkaline
phosphatase in all mesocosms and during the entire experiment (multiple R(z/xy) =
0.68, p < 0.001).
- 55 -
Section 3: Results
Bacterial activities
Microbial activity was measured by uptake of radiolabeled 3H-Leucine (Leu) and
3
H-Thymidine (Thy). Uptake rates were high and ranged from 3.2 and 17.2 nmol
l-1 h-1, and 2.4 and 8.9 nmol l-1 h-1, respectively.
However, mean leucine uptake rates (proxy for biomass production) did not
change significantly under elevated pCO2 concentrations neither during the 1st
nor during the 2nd acidification experiment (Fig. 34, A, B). By comparing the 1st
and 2nd acidification experiment, statistically significant differences were
observed, since leucine uptake rates were on average four times higher after
the 1st than after the 2nd acidification (ANOVA on ranks, Dunn’s, p < 0.001). The
large error bars are due to the diurnal variability.
40
Leucine uptake
-1 -1
[nmol l h ]
35
1st acidification
A
2nd acidification
B
30
25
20
15
10
5
0
Thymidine uptake
-1 -1
[nmol l h ]
12
not
weak
med strong
C
not
weak
med strong
not
weak
med strong
D
10
8
6
4
2
0
not
weak
med strong
acidification by HCl (range ~350-1500 µatm pCO2)
Figure 34: Means of lleucine (Leu) (A, B) and thymidine (Thy) (C; D) uptake rates in
the mesocosms (not, weakly, medium and strongly acidified) for the 1st and 2nd
acidification experiment.
- 56 -
Section 3: Results
A complementary pattern was found for thymidine uptake rates (proxy for cell
deviation). No significant response to the acid treatment was observed during
the 1st and the 2nd acidification experiment (Fig. 34, C, D). Means of thymidine
uptake rates significantly increased from ~2 to ~8 nmol l-1 h-1 from the 1st to the
2nd acidification experiment (ANOVA on ranks, Dunn’s, p < 0.001).
However, the proportion of leucine vs. thymidine uptake decreased significantly
from the 1st to the 2nd acidification experiment indicating a shift to smaller
bacteria (ANOVA on ranks, Dunn’s, p < 0.001).
Growth rates
Unfortunately we have only a small data set (2nd acidification) which allows to
calculate growth rates. From this data it is obvious, that a significant increase of
heterotrophic bacteria abundances over time was observed in the not and
weakly acidified, but not in the strongly acidified mesocosm (Fig. 35).
Furthermore, the slope of the not acidified mesocosm was ~60% higher than of
4.5
4.0
not
weak
R2 = 0.83
P = 0.004
f = 0.03x+2.55
A
B
strong
C
R2 = 0.85
P = 0.003
f = 0.018x+2.26
3.5
6
-1
Bacteria [x10 cells ml ]
the weakly acidified mesocosm.
3.0
2.5
2.0
0.0
-10
0
10
20
30
40
50 -10
0
10
20
30
40
50 -10
0
10
20
30
40
50
time after 2nd acidification [h]
acidification by HCl (range ~350-1500 µatm pCO2)
Figure 35: Temporal dynamics of heterotrophic bacteria abundances in three different
(not (A), weakly (B) and strongly (C) acidified) mesocosms for the 2nd acidification
experiment (error bars indicate analytical errors of cytometrical analyses (4%)).
- 57 -
Section 3: Results
The complementary pattern was seen for the unicellular cyanobacteria.
Abundance of these prokaryotes did not significantly increase over time in the
not and weakly acidified mesocosms (Fig. 36). In fact a significant temporal
increase of cyanobacteria abundance was observed only with strong
acidification.
Unicellular cyanobacteria
5
-1
[x10 cells ml ]
2nd acidification
4.5
4.0
not
weak
A
strong
B
C
2
R = 0.81
P = 0.006
f = 0.03x+2.41
3.5
3.0
2.5
2.0
0.0
-10
0
10
20
30
40
50 -10
0
10
time after 2
20
nd
30
40
50 -10
0
10
20
30
40
50
acidification [h]
acidification by HCl (range ~350-1500 µatm pCO2)
Figure 36: Temporal dynamics of unicellular cyanobacteria abundances in three
different (not (A), weakly (B) and strongly (C) acidified) mesocosms for the 2nd
acidification experiment (error bars indicate analytical errors of cytometrical analyses
(8%)).
Calculated growth rates of unicellular cyanobacteria and heterotrophic bacteria
changed with increasing pCO2 concentrations (Fig. 37). Compared to the
unicellular cyanobacteria the growth rate of heterotrophic bacteria was ~80 %
higher in the not acidified mesocosm, whereas in the weakly acidified
mesocosm growth rates equalled. In the strong acidified mesocosm the growth
rate of the unicellular cyanobacteria was ~40% higher than the growth rate of
the heterotrophic bacteria.
- 58 -
Section 3: Results
2nd acidification
0.012
unicelluar cyanobacteria
heterotrophic bacteria
-1
growth rate [h ]
0.010
0.008
0.006
0.004
0.002
0.000
not
weak
strong
acidification by HCl (range ~350-1500 µatm pCO2)
Figure 37: Growth rates of unicellular cyanobacteria (white) and heterotrophic bacteria
(grey) in three different (not, weakly and strongly acidified) mesocosms for the 2nd
acidification experiment.
These findings may indicate a competition between heterotrophic bacteria and
unicellular
cyanobacteria
during
the
2nd
acidification
experiment.
- 59 -
Section 4: Discussion
4
Discussion and conclusion
Our knowledge of factors and processes that determine the abundance,
distribution and activities of marine microorganisms regarding to global change
is limited. These uncertainties affect our ability to predict specific responses to
the acidification of marine environments (Falkowski et al. 2000; Gruber and
Galloway
2008).
The
mechanisms
that
underlie
the
contribution
of
microorganisms in marine food webs and biogeochemical cycles need to be
assessed on nanometer to micrometer scale in order to make reliable
predictions with respect to the response of the ocean to global change.
Experimental setup
In general, testing the impact of enhanced pCO2 concentrations on natural
aquatic ecosystems is a difficult task. While laboratory studies and bottle
incubation experiments have the advantage of being highly reproducible when
CO2 concentrations were adjusted by aeration or addition of either acidic or
alkaline solutions, the dynamics of a natural environment are not well simulated.
Free-floating offshore mesocosms provide a reasonable alternative to in-situ
perturbation experiments by allowing the study of whole ecosystems under
semi-natural conditions in open waters. The mesocosms, which were used for
the very first time in this study, are still in the beginning of their technical
development and have to be further improved to sustain naturally occurring
boundary conditions (e.g. high wind speeds, waves, up- and down-movements
etc.). Due to unusual weather conditions for summer times (strong wind events
and therefore wave heights between 1.5 and 2.5 m), some mesocosms had
been damaged (mainly, broken bottom plates) over the time of the entire
experiment. Even though the mesocosms would have resisted the extreme
boundary conditions during the entire experiment, sampling of the mesocosms
- 60 -
Section 4: Discussion
is and will remain a problem during strong wind events, when waves are too
high to allow the use of zodiacs for sampling.
However, usually in summer times the Baltic Sea provides calm open waters,
which was certainly not the case in July 2007, when this mesocosm
manipulation experiment took place. The upper 10 m of the water column inside
the mesocosms was only slightly affected by exchange during the duration of
the single experiments (1st and 2nd acidification), even if it was observed
regularly in between. Please note, that in this work only data from those
mesocosms and depth are discussed, which were not affected by mixing and
water exchange as inferred from vertical CTD measurements from inside the
mesocosms.
In contrast to a land-base mesocosm study at the European Union Large Scale
Facility (LSF) in the Raunefjorden (in Bergen, Norway) in 2001 (Engel et al.
2005), the offshore mesocosms used here were not air-tight covered by domes.
Hence, the pCO2 concentrations in the weakly buffered Baltic Sea water rapidly
equilibrated with the atmosphere. Since phytoplankton activity was very low in
this study, the huge variability in pCO2 and thus in pH cannot be explained by
photosynthetic activity, which can account for up to 30% of diurnal variability of
CO2 in the upper water column during summer time (Yamashita et al. 1993). In
order to study long-term CO2 effects on natural aquatic ecosystems, an
experimental setup is required, which provides low variability in seawater
chemistry within different treatments. An alternative experimental setup was
used in the study of Engel and colleagues (2005), where the enclosed water
masses in the land-based mesocosms were acidified by aeration and a
fumigation of the tents was maintained to keep the CO2 partial pressure of the
overlying air at a constant level. Furthermore, they reported low variability in
seawater chemistry (pCO2, pH, alkalinity and inorganic nutrients) within their
treatments. Unfortunately, this experimental setup can not be used for offshore
mesocosms due to logistical reasons. Therefore, more developmental work on
acidification techniques and monitoring of seawater chemistry offshore have to
be done.
- 61 -
Section 4: Discussion
Moreover, the huge pCO2 gradient applied in this study (mean pCO2 of
1600 µatm in the strongest acidified mesocosm) reflects a future CO2 scenario,
which exceeds model predictions of 540 - 970 µatm for the year 2100 (IPCC
emission scenario, IS92 (Houghton et al. 2001)). For environmental, public and
political concerns a gradient of pCO2 concentrations up to ~1000 µatm might be
more relevant. Furthermore, an experimental setup of three different pCO2
concentrations up to ~1000 µatm and replicates may help to facilitate data
interpretation.
Since the acidification of the mesocosms was repeated three times and due to
the narrow intervals of continuous observations, our conclusions can only
account for short term effects of CO2 enrichment by HCl addition in a weakly
buffered aquatic environment.
Effects of increasing pCO2 on biogeochemical processes
In this field study, the effects of different pCO2 concentrations on a natural
phytoplankton community were investigated to address possible consequences
of future ocean acidification. An acidification of ocean waters will potentially
change the productivity of autotrophic phytoplankton and subsequently the
efficiency of the biological carbon pump in the future, as recently hypothesized
by Riebesell et al. (2007). This hypothesis implies potential changes in
stoichiometry of organic matter in the future. This would subsequently alter
microbial processes and biogeochemical cycling.
In contrast to what we expected, the situation in the Baltic in 2007 was
characterized by low concentrations of Chl a, low primary production, low
autotrophic activity and low concentrations of nutrients. Limitation in nitrate
(below the detection limit, low DFAA) but not in phosphorus (conc) indicated a
non-bloom situation. The elemental composition of organic matter in this
mesocosm study was much higher than the canonical Redfield ratio of 106:16:1
(Redfield et al. 1963). Although several studies showed a high species-specific
- 62 -
Section 4: Discussion
variability in the elemental stoichiometry (Sterner and Elser 2002), our results
support the assumption of a low productive system with low amounts of freshly
produced POM.
The increase of POC concentration (~8%) in the control mesocosm was mainly
due the increased TEP concentration and increased biomass of heterotrophic
bacteria. For calculation of the carbon content of TEP, a conversion factor of
0.75 was applied (Engel and Passow 2001). The carbon content of
heterotrophic bacteria of 20 fg C cell-1 was assumed according to Lee &
Fuhrman (1987). TEP is known to have a high carbon content, because it
mainly consists of polysaccharides. Therefore, the increased TEP concentration
and higher cell abundance of heterotrophic bacteria can explain the increased
POC concentration in the control mesocosm.
The substantial loss of POC concentrations (~10%) after 5 days due to
perturbation by HCl-treatment can either be explained by enhanced vertical
export of particulate material to deeper layers or by a degradation of biomass.
Although the main POC proportion (80%) was owing to the smaller than 10 µm
fraction, this loss of POC can only partly be accounted to the smaller than 10
µm size fraction (50%) (data not shown). Decreasing abundances of eukaryotic
phytoplankton may indicate also a loss of POC (<10 µm), but did not explain
this loss alone. Since abundances of heterotrophic bacteria, unicellular bacteria
and concentrations of TEP did not decrease after the 2nd acidification, it is
assumed that the unidentified part of the POC loss in the fraction smaller than
10 µm was exported into deeper layer of the mesocosm (below 10 m). Reduced
TEP concentrations related to high CO2 may be due to increased sedimentation
rates. Eukaryotic phytoplankton and diazotrophic cyanobacteria decayed after
acidification and over time, respectively. On the way down into deeper layer of
the mesocosms, cell lysis and degradation processes will change the POM
pool, recycle some of the organic matter back into the food web. During this
process, refractory particulate and dissolved matter may be produced, and
sedimentation processes of POM may increase due to the existence of TEP.
- 63 -
Section 4: Discussion
Our data showed that POC loss in the fraction larger than 10 µm was mainly
due to the decay of the abundances of Nodularia spp. before the 2nd
acidification. Although abundances of Aphanizomenon spp. increased after the
2nd acidification, a proliferation of Aphanizomenon spp. over Nodularia spp.
(Stal et al. 2003) only occurred in the control and weakly acidified mesocosm.
Therefore, strong HCl-treatment inhibited the growth of Aphanizomenon spp.,
and influenced their dynamic compared to the control mesocosm. In
accordance with results of this study, Caraco and Miller (1998) also suggested
that the abundance of Aphanizomenon flos aquae is negatively affected by the
impact of decreasing pH.
Temporally increasing POP concentrations in the HCl-treated mesocosms
indicate an indirect response of the community change to phosphorous
acquisition. Due to the higher availability of DOM (loss of filamentous
cyanobacteria), heterotrophic bacteria and primarily unicellular cyanobacteria
were favored. Since phosphate was not limited, it is likely that a P accumulation
in the form of polyphosphate (poly-P) occurred.
While the C:N ratios remained nearly constant during the whole experiment,
C:P ratios decreased significantly after the 2nd HCl-treatment due to the
observed loss in POC and increase of POP concentrations. Recent studies
indicate that phytoplankton species differ in their CO2 requirement, suggesting
large differences in CO2-sensitivity between major phytoplankton taxonomic
groups (Riebesell 2004). The effects of elevated inorganic carbon and CO2
availability
revealed
considerable
changes
in
phytoplankton
elemental
composition of C:N:P even though these differences were highly speciesspecific (Burkhardt and Riebesell 1997; Burkhardt et al. 1999; Gervais and
Riebesell 2001; Riebesell et al. 2007). Barcelos e Ramos et al. (2007)
investigated the effects of CO2-induced changes in seawater chemistry on
Trichodesmium, a colony-forming cyanobacterium. Carbon, nitrogen and
phosphorus cellular contents, and cell dimensions decreased with rising CO2 as
a result of doubled cell division rate during their study. While C:P and N:P ratios
more than doubled, C:N ratios remained without change. Their findings would
imply a higher productivity of N-limited oligotrophic oceans, P limitation and
- 64 -
Section 4: Discussion
increase biological carbon sequestration in the ocean. In contrast to our study,
the effects of rising CO2 were investigated during exponential growth of
Trichodesmium. Prevailing environmental conditions play an important role
when investigating (1) changes in the ecosystem community structure and (2)
changes due to HCl treatment. The response to rising CO2 of a low primary
productive system may therefore differ from a nutrient-repleted high primary
productive system. In our case the C:N:P ratio was much higher than the
Redfield ratio and primary production was very low. A lowering of C:P may
therefore be the consequence of POC loss 5 days after acidification.
- 65 -
Section 4: Discussion
Effects of increasing pCO2 on microbial dynamics and activities
Dynamics of eukaryotic phytoplankton, diatoms and green algae, were sensitive
to the acidification. Abundances of Nodularia spp. decreased over time
regardless to the acid treatment, whereas abundances of Apanizomenon spp.
increased in the control and weakly acidified mesocosms. The composition of
diazotrophic cyanobacteria shifted between the two species in the control
mesocosm, as it was also observed by Stal et al. (2003). But in contrast to our
findings, their results showed a proliferation of Nodularia spumigena over A. flos
aquae during a plankton bloom, mainly due to different photosynthetic and N2
fixation potentials. As it was also suggest by Stal et al. (2003), dynamical
developments of species composition depend on the prevailing environmental
conditions. Our study took place during a non-bloom situation, where phosphate
was not limited. Kononen et al. (1996) suggested that Nodularia spp. is
favoured in situations when nutrients are limited, due to their ability to grow on
intracellular P-storage for several days (more than one cell devision) (Huber
and Hamel 1985). Furthermore, their study revealed, that Nodularia spp. and
Aphanizomenon spp. have different nutrient uptake kinetics. A higher affinity of
Nodularia spp. than Aphanizomenon spp. for phosphate has been observed by
Kononen et al. (1996). Thus, the observed temporal decrease of Nodularia spp.
and the increase of Aphanizomenon spp. were due to sufficient nutrient supply.
Moreover, the perturbation by the acid treatment caused an inhibition of the
growth of Aphanizomenon spp. under low pH, as it was also suggested by
Caraco and Miller (1998). Hence, among these interactions of natural
succession and direct or indirect effect of HCl treatment, it is assumed that
nutrient uptake kinetics may change in the future, possibly due to
disadvantageous pH optima for nutrient uptake enzymes in cyanobacteria.
Additionally the decrease of N2 fixation rates of organisms larger than 10 µm as
well as CO2 uptake (over time as well as HCl-induced) was due to the shift of
the
two
species.
Nodularia
spp.
has
80%
more
heterocysts
than
Aphanizomenon spp. (Stal et al. 2003). This physiological difference explains
- 66 -
Section 4: Discussion
the significant decrease N2 fixation from the 1st to the 2nd acidification, and the
HCl-induced differences during the 2nd acidification experiment.
These findings are in accordance with growth of unicellular cyanobacteria,
which can be mixotroph. Obviously, after the storm between the 1st and 2nd
acidification the water masses were mixed and the prokaryotes had enough
DOM for growth. This assumption is supported by autotrophic and heterotrophic
activities. CO2 uptake and N2 fixation rates of unicellular cyanobacteria
remained unchanged, but became a significant dominance in overall N2 fixation.
Our data suggest, therefore, that a perturbation by hydrochloric acid induced a
community shift from eukaryotes to prokaryotes.
While CO2 uptake and N2 fixation of unicellular cyanobacteria were not
influenced by the acid treatment, the decline of diazotrophic cyanobacteria
caused lower autotrophic rates. Since unicellular cyanobacteria abundances
were also not negatively affected by HCl treatment, their CO2 uptake and N2
fixation remained stable. This obvious advantage of being not directly affected
by HCl treatment, was also observed for heterotrophic bacteria.
Heterotrophic activities of bacteria shifted relatively from biomass production to
cell deviation, but were not directly influenced by the acid treatment. Leucine
(proxy for biomass production) was considered to be taken up exclusively by
heterotrophic bacteria (Kirchman et al. 1985; Riemann and Azam 1992), until
Kamjunke & Jähnichen (2000) reported significant leucine incorporation of
unicellular cyanobacteria. Recently, Hietanen et al. (2002) showed, that even
filamentous cyanobacteria (like Nodularia spp.) are capable to incorporate
leucine depending on the trophic state of the system. We can not be sure, that
diazotrophic cyanobacteria incorporate radiolabelled leucine in the beginning of
our study and therefore may falsify our results. But after the 2nd acidification,
when abundances of diazotrophic cyanobacteria decreased, and the activity
shifted relatively to cell deviation, these uptake rates of leucine and thymidine
can only account for heterotrophic bacteria and unicellular cyanobacteria. In
- 67 -
Section 4: Discussion
contrast to leucine, based on present knowledge, thymidine is taken up
exclusively by heterotrophic bacteria (Fuhrman and Azam 1982).
Although heterotrophic bacteria play a major role in organic matter cycling (e.g.
Cole et al. 1988; Azam 1998; Azam and Malfatti 2007), observed effects of
increased pCO2 on their dynamics and activities are rare. In this study bacterial
activity (thymidine incorporation) increased temporally, and was not directly
affected by the acid treatment. Recent studies (Coffin et al. 2004; Grossart et al.
2006) showed pCO2 related effects on bacterial production. While the results of
the study by Coffin et al. (2004) suggest that the bacterial production in the
deep ocean is moderately sensitive to seawater acidification (mild acidification
did not inhibit production, may even enhance it), Grossart et al. (2006) pointed
out, that the effects of changes in pCO2 on bacterial activities are mainly
indirectly linked to phytoplankton and presumably to particle dynamics.
Our results suggest that the high bacterial biomass production rates (leucine
incorporation) could be interfered by cyanobacteria and that the temporal
increasing cell deviation rates (thymidine incorporation) were mainly linked to
the high organic matter availability and utilization. Hence, it is suggested that
microbial uptake rates were not directly influenced by an increase in pCO2.
Unicellular cyanobacteria and heterotrophic bacteria profited of the organic
matter, which resulted e.g. from cell lysis and exudation. I assume, that these
osmotrophic prokaryotes competed for utilization of organic matter. Low
nanomolar concentrations of DFAA and very high leucine-aminopeptidase
efficiency refer to rapid turnover of leucine. Cottner and Biddanda (2002)
suggest a tight coupling of heterotrophs and autotrophs in low productivity
systems, when nutrients are primarily organic and dissolved, prokaryotic
heterotrophic respiration is equal or greater than primary production (Fig. 38).
- 68 -
Section 4: Discussion
Figure 38: Changes in nutrient characteristics across a productivity gradient.
(A-H coupling: autotrophic-heterotrophic coupling) (from Cotner and Biddanda 2002).
The effect of the HCl treatment on autotrophic-heterotrophic competition for
nutrient utilization was partly conditioned by the fact, that some very few known
unicellular cyanobacteria species are capable of fixing N2, when it is clearly
ecologically advantageous (Zehr et al. 2001). In cases of N limitation and low
amounts of utilizable DOM, these unicellular cyanobacteria acquire their
nutrients for growth and metabolism more easily. In addition to this privilege of
some unicellular cyanobacteria, our results indicate that the heterotrophic
bacteria seem to be inhibited in acquiring nutrients with increasing pCO2
regarding to their growth dynamics after the 2nd acidification. Enzyme
efficiencies of alkaline phosphatase and leucine-aminopeptidase
decreased
(<60-70% and 20%, respectively) in response to the acid treatment.
Furthermore, the slight increase of the enzyme efficiency of leucineaminopeptidase over time under low pH conditions lead to possible changes in
the substrate affinity. Overall, dynamics and calculated growth rates of
unicellular cyanobacteria and heterotrophic bacteria, as well as lower enzyme
efficiencies of heterotrophic bacteria lead to the assumption that unicellular
cyanobacteria outcompeted heterotrophic bacteria under strong acidified
- 69 -
Section 4: Discussion
conditions. Our results suggest that CO2-induced decrease of hydrolytical
enzyme efficiencies lead to a competition between heterotrophs and autotrophs.
Conclusions
In order to investigate the impact of ocean acidification on microbial dynamics
and activities, community structure and prevailing environmental conditions
have to be considered. In the present study, the situation was characterized as
a low productive system. Efficiencies of microbial exoenzymes decreased with
decreasing pH, while microbial uptake rates were not affected by acidification.
Autotrophic unicellular cyanobacteria outcompeted heterotrophic bacteria in
strongly acidified mesocosms (pH 7.5). This shift in the community structure
may have the potential to affect degradation and stoichiometry of organic matter
in the Baltic Sea. Observed short-term effects suggest ocean acidification to
potentially change trophic structures and interactions on the ecosystem level.
The mechanisms that underlie the contribution of microorganisms in marine
food webs and biogeochemical cycles need to be assessed on nanometer to
micrometer scale in order to make reliable predictions with respect to the
response of the ocean to global change. However, these complex, cascading
trophic interactions need further investigations to serve as a reliable basis for
accurate ecosystem models.
- 70 -
ACKNOWLEDGEMENTS
Acknowledgements
My special thanks go to my supervisor Dr. Mirko Lunau! Thank you for giving
me the opportunity to broaden my mind and my knowledge. I really appreciated
to work and discuss with you. Thanks for your support, for new perspectives, for
good advice and fruitful comments!
Thanks to Prof. Dr. Wolfgang Ebenhöh for the good modelling seminars during
my studies and for kindly being the secondary referee of this diploma thesis!
I would also like to thank Dr. Anja Engel for scientific discussions and helpful
comments. I greatly appreciate the scientific discussions and the practical help
of all participants of the SOPRAN 2007 cruise in the Baltic Sea. Thanks to
Maren Voss, Kai Schulz, Robert Schmidt, Kirsten Isensee, Henning Johansen,
Annett Grüttmüller, Peter Fritsche and Kristin Haynert for kindly providing their
data! I also thank the crew of RV Heincke and RV Alkor for their professional
support. I am grateful to Dr. Hans-Peter Grossart for all the conversations and
good advice. Thank you for analytical and technical support in your lab. Many
thanks to Nicole Händel, Judith Piontek and Corinna Borchard for practical
support, proofreading, helpful comments and the nice atmosphere in our
working group!
I would also like to thank the institutions, that funded this work: the BMBF
(SOPRAN, Theme 2), the Leibniz- and the Helmholtz Association (HZ-NG 102)
and the Leibniz-Institute of Freshwater Ecology and Inland-Fisheries (IGB).
Dir, Helge, danke ich für die Kraft, die Motivation, das Verständnis und die
Unterstützung während der letzten Jahre. Du hast mich stets ermutigt, meine
Interessen zu verfolgen und hast immer ein offenes Ohr für mich gehabt.
Danke!
Meiner Familie danke ich aus tiefstem Herzen für die Unterstützung, das
Vertrauen und die Liebe!
- 71 -
APPENDIX
Appendix
Table 2: Initial values of measured parameters before acidification at all
parameter
MC 1
MC 2
MC 3
MC 4
MC 5
MC 6
8.113
8.118
8.116
8.086
8.105
8.069
calculated pH (0-10m)
calculated pCO2 (0-10m) [µatm] 351.444 348.010 349.568 372.981 357.677 387.113
POC [µM]
PON [µM]
POP [µM]
C/N [mol/mol]
C/P [mol/mol]
N/P [mol/mol]
CHl a [µg l-1]
DFAA [nM]
TEP [µg Xeq. l-1]
eukaryotic phytoplankton
[x104 cells ml-1]
Nodularia spp [units l-1]
Aphanizomenon spp [units l-1]
CO2 UT total [µmol l-1 h-1]
CO2 UT >10 [µmol l-1 h-1]
CO2 UT <10 [µmol l-1 h-1]
N2 fix total [nmol l-1 h-1]
N2 fix >10 [nmol l-1 h-1]
N2 fix <10 [nmol l-1 h-1]
unicellular cyanobacteria
[x105 cells ml-1]
bacteria [x106 cells ml-1]
EE glucosidase [h-1]
EE peptidase [h-1]
EE phosphatase [h-1]
TO glucosidase [mol l-1 h-1]
TO peptidase [mol l-1 h-1]
TO phosphatase [mol l-1 h-1]
Thy UT [nmol l-1 h-1]
Leu UT [nmol l-1 h-1]
45.765
53.074
49.986 55.989 60.945
61.717
4.073
3.908
3.864
4.342
4.401
7.438
nn
0.088
nn
nn
0.053
nn
11.237
13.582
12.936 12.895 13.847
8.298
nn
604.411
nn
nn
1139.448
nn
nn
44.501
nn
nn
82.287
nn
2.092
2.094
2.194
1.890
2.043
1.956
145.879 198.908 131.678 106.726 106.629 99.572
72.742
70.929
68.672 71.558 71.743
71.928
2.232
nn
nn
nn
nn
nn
nn
nn
nn
nn
0.069
0.265
0.196
0.069
nn
nn
nn
0.011
nn
0.044
0.043
0.001
nn
nn
0.066
0.006
0.060
0.162
0.142
0.020
nn
nn
0.151
0.007
0.144
0.381
0.190
0.192
4158
6798
nn
nn
0.197
0.608
0.112
0.496
2970
5148
0.191
0.006
0.185
0.764
0.138
0.625
3.699
nn
nn
nn
nn
nn
2.288
0.033
0.953
0.577
0.050
1.416
0.858
nn
nn
2.572
0.015
0.847
0.613
0.023
1.268
0.919
nn
nn
2.273
0.022
0.954
0.580
0.033
1.407
0.866
nn
nn
2.303
0.023
1.102
0.575
0.035
1.607
0.858
nn
nn
2.284
0.031
0.996
0.630
0.046
1.469
0.946
nn
nn
2.375
0.025
0.837
0.621
0.038
1.249
0.934
nn
nn
- 72 -
APPENDIX
Table 3: Solubility of MUF- and AMC- labelled substrate analogues
- 73 -
APPENDIX
Figure 39: Dissolved free amino acid (DFAA) composition in the mesocosms (not,
weakly and strongly acidified) of the 1st and 2nd acidification experiment. Temporal
development within the treatments and acidification.
- 74 -
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EIDESSTATTLICHE ERKLÄRUNG
Hiermit versichere ich, dass ich diese Arbeit selbstständig verfasst und keine
anderen als die angegebenen Hilfsmittel benutzt habe.
Oldenburg, 20. April 2008
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