Comprehensive Summaries of Uppsala Dissertationsfrom the Faculty of Science and Technology 1016

Pigment and Thiamine Dynamicsin Marine Phytoplankton and

Copepods

BY

INGRID WÄNSTRAND

ACTA UNIVERSITATIS UPSALIENSISUPPSALA 2004

Till Olle

List of Papers

This thesis is based on the following six papers, which will be referred to in the text by their Roman numerals (I–VI):

I Wänstrand I & Snoeijs P. Seasonal phytoplankton pigment dy-namics in the northern Baltic Sea: assessment by ships-of-opportunity. Submitted manuscript.

II Wänstrand I & Snoeijs P. Phytoplankton community dynamics in nutrient-enriched mesocosms in the Baltic Sea: a chemotax-onomical approach. Manuscript.

III Van Nieuwerburgh L, Wänstrand I & Snoeijs P (2004). Growth and C:N:P ratios in copepods grazing on N- or Si-limited phyto-plankton blooms. Hydrobiologia 514:57-72.

IV Van Nieuwerburgh L, Wänstrand I, Liu J & Snoeijs P. Astaxan-thin production in marine pelagic copepods grazing on two dif-ferent phytoplankton diets. Journal of Sea Research: accepted.

V Wänstrand I, Barros MP, Pinto E, Pedersén M & Snoeijs P. Inor-ganic nutrients regulate astaxanthin production in copepods via phytoplankton community dynamics. Submitted manuscript.

VI Snoeijs P, Wänstrand I, Pinto E, Van Nieuwerburgh L, Barros MP, Colepicolo P & Pedersén M. Thiamine (vitamin B1) dynam-ics in phytoplankton and copepods is regulated by inorganic nu-trient supply. Submitted manuscript.

Paper III is reproduced with kind permission from the publisher.

My contribution to the papers

For all papers I planned the research jointly with the co-authors, but I had the main responsibility for the planning of papers I, II and V.

In paper I, I carried out the field work, analyzed the pigments, processed the data and was responsible for compiling the manuscript.

In paper II, I participated in the experiment, analyzed the pigments, proc-essed the data and was responsible for compiling the manuscript.

In paper III, I carried out the experiments together with L. Van Nieuwer-burgh and J. Liu and actively participated in compiling the manuscript.

In paper IV, I carried out the experiment together with L. Van Nieuwerburgh and J. Liu and actively participated in compiling the manuscript.

In paper V, I carried out the experiments together with M.P. Barros and E. Pinto, analyzed all pigment and plankton samples, processed the data and was responsible for compiling the manuscript.

In paper VI, I carried out one experiment together with L. Van Nieuwer-burgh and J. Liu and two experiments together with M.P. Barros and E. Pinto and actively participated in compiling the manuscript.

Contents

Introduction.....................................................................................................9Coastal eutrophication and the pelagic food web.......................................9

Nutrient supply and phytoplankton communities ..................................9Consequences for the food web...........................................................10The M74 syndrome in Baltic Sea salmon stocks.................................10Astaxanthin – a potent antioxidant ......................................................11Thiamine – essential in metabolism.....................................................11

Pigments characterize phytoplankton communities .................................12Unattended phytoplankton sampling........................................................13

Aims of this thesis.........................................................................................14

Material and methods....................................................................................15Study areas ...............................................................................................15Ship-of-opportunity sampling ..................................................................16Pigments as chemotaxonomic biomarkers ...............................................17Mesocosm experiments with nutrient manipulations ...............................18Analyses of pigments and thiamine..........................................................20

Results and discussion ..................................................................................21Seasonal phytoplankton pigment variation ..............................................21Successful chemotaxonomy .....................................................................22Plankton community responses to fertilization ........................................24Inorganic nutrients regulate astaxanthin production… ............................26…and thiamine dynamics.........................................................................26Relationships between astaxanthin and thiamine .....................................27Ecosystem implications and future perspectives......................................28

Conclusions...................................................................................................30

Acknowledgements.......................................................................................31

References.....................................................................................................32

Pigment och tiamin i planktonalger och hoppkräftor – effekter av övergödning i Östersjöns näringsväv............................................................37

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Introduction

Coastal eutrophication and the pelagic food web

Nutrient supply and phytoplankton communities During the last century, eutrophication has become a major problem for coastal ecosystems worldwide (Cloern 2001). The general situation is that dissolved inorganic phosphorus (DIP) and nitrogen (DIN) stocks increase while dissolved silicate (DSi) decreases in surface waters (Conley et al. 1993). Nixon (1995) defined eutrophication as ‘the process of increased organic enrichment of an ecosystem, generally through increased nutrient inputs’. However, ecosystem responses include not only increased primary production, but also changes in species diversity and community structure (Cloern 2001).

In the brackish Baltic Sea, loading of nitrogen has increased four-fold and loading of phosphorus has increased eight-fold over a 100-year period with strong accelerations in the 1960’s (Larsson et al. 1985). This coincided with lowered DSi:DIN ratios (Rahm et al. 1996). Also during the same time pe-riod, pelagic primary production increased with 30–70% (Elmgren 1989), and water transparency (summer Secchi depth) decreased by about 3 m (Sandén & Håkansson 1996).

The supply and stoichiometric ratios of macronutrients regulate the spe-cies composition of phytoplankton communities (Turner 2002), and are thus central for bottom-up ecosystem control. Phytoplankton generally incorpo-rates carbon, nitrogen and phosphorus in the molar proportions 106:16:1, known as the Redfield ratio (Redfield et al. 1963). Diatoms also require sili-cate (Si(OH)4) in a Si:N ratio of ca 1:1 to construct their frustules (Brzezinski 1985), and a lower ratio may therefore prevent growth of diatoms in favour of non-siliceous phytoplankters as e.g. flagellates (Officer & Ryther 1980). Dominance shifts from diatoms towards (dino)flagellates have indeed been recorded during the latter half of the 20th century in several coastal areas, i.e. the North Sea (Radach et al. 1990), the Black Sea (Humborg et al. 2000) and the Baltic Sea (Wasmund et al. 1998).

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Consequences for the food webAs diatoms are considered central agents of primary production in aquatic systems, fuelling the food chain phytoplankton–copepods–planktivorous fish–predatory fish–top predators, decreased diatom abundance may affect transfer of energy and matter from phytoplankton to higher trophic levels (Officer & Ryther 1980, Turner et al. 1998). In a food web based on phyto-flagellate production, a larger part of the assimilated carbon is transferred through microzooplankton and the microbial loop, and transfer to higher trophic levels is considered less effective.

Substantial food web changes have been observed in the Baltic Sea during the last couple of decades. Dominance shifts from diatoms towards (dino)flagellates have been documented (Wasmund et al. 1998, Humborg et al. 2000, Wasmund & Uhlig 2003), as well as increased abundances of N-fixing cyanobacteria (Finni et al. 2001). The latter phenomenon has explic-itly been attributed to eutrophication and reduced N:P ratios, although N-limitation and the occurrence of cyanobacterial blooms are natural phenom-ena in the Baltic Sea (Bianchi et al. 2000).

Time-series studies of mesozooplankton have shown that large copepod species have decreased at the expense of smaller copepods, cladocerans and protozoans in the Baltic Sea (e.g. Schiewer 1998, Vuorinen et al. 1998). Herring Clupea harengus L. selectively prey on large copepods in the Baltic Sea (Hansson et al. 1990, Viitasalo et al. 2001) and Flinkman et al. (1998) reported that stomach fullness in herring decreased from 1980’s to the 1990’s, which was explained by simultaneously decreased abundance of large copepods.

Community changes in Baltic Sea mesozooplankton have in some cases been explained by decreased salinity (Vuorinen et al. 1998) or increased predation pressure from sprat Sprattus sprattus L. (Kornilovs et al. 2001). However, mesozooplankton is also bottom-up controlled by eutrophication (Schiewer 1998).

The M74 syndrome in Baltic Sea salmon stocks The M74 syndrome is a reproductive disturbance in Atlantic salmon Salmo salar L. in the Baltic Sea (Bengtsson et al. 1999). Affected yolk-sac fry suf-fer from thiamine deficiency (Amcoff et al. 1998), but M74 is also associ-ated with low levels of the carotenoid astaxanthin and increased oxidative stress in the fry (Lundström et al. 1999, Pettersson & Lignell 1999). The probable cause of M74 is chemical changes in the salmon diet (Hansson et al. 2001), possibly resulting from changes at lower trophic levels caused by eutrophication.

Similar reproductional disturbances in other salmonid fish stocks are also associated with thiamine deficiency: the early mortality syndrome (EMS) in

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the Great Lakes and the Cayuga syndrome in the New York Finger Lakes (Honeyfield et al. 1998). The M74, EMS and Cayuga syndromes are all en-tirely confined to eggs collected from feral broodstock; eggs from fish main-tained on commercial feeds are not affected.

Carotenoids and thiamine in the salmon diet originate from phytoplank-ton. If the observed shifts in phytoplankton production and community com-position result in decreased pelagic production of these compounds, the sup-ply to fish may eventually be reduced. The hypothetical causal relationship between eutrophication and the M74 syndrome could thus be outlined as follows: Altered Si:N and N:P supply and ratios changed phytoplankton community and biochemical composition less -carotene/thiamine in-gested by copepods lowered pelagic astaxanthin production less astax-anthin/thiamine in salmon prey fish less astaxanthin/thiamine in female salmon increased M74 mortality. This hypothetical chain of events was the background for our investigations in papers III–VI.

Astaxanthin – a potent antioxidant The ketocarotenoid astaxanthin is a potent antioxidant (Kobayashi & Saka-moto 1999) protecting cells from free radicals. It can also act as a sunscreen pigment (Wang et al. 2003). Astaxanthin in its free and esterified form is the major pigment in many marine animals such as crustaceans (Castillo et al. 1982), where it is involved in gonadal maturation, and in early development and growth (Liñán-Cabello et al. 2002). Lorenz & Cysewski (2000) have summarized the functions of carotenoids in aquaculture as antioxidants, hormone precursors and provitamins, as well as in immune enhancement, reproduction, growth, maturation and photoprotection.

Copepods are the main producers of astaxanthin in marine pelagic food webs. They cannot synthesize it de novo, but depend on carotenoid precur-sors from their algal diet. These precursors are mainly -carotene and zeax-anthin (Matsuno 2001, Liñán-Cabello et al. 2002) and the two main biosyn-thetic pathways from -carotene are via (1) -cryptoxanthin, zeaxanthin and adonixanthin and via (2) echinenone, canthaxanthin and adonirubin (Harker & Young 1995). -carotene occurs in almost all phytoplankton classes, while zeaxanthin is basically restricted to cyanobacteria and chlorophytes (Jeffrey & Vesk 1997).

Thiamine – essential in metabolism Thiamine (vitamin B1) is an essential vitamin for basically all organisms (Combs 1998) and deficiency in humans induces neurological or cardiovas-cular symptoms known as beriberi. Free thiamine (TF) is a precursor of the biologically active form thiamine diphosphate (TDP), which acts as a coen-zyme in carbohydrate metabolism.

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In pelagic ecosystems, thiamine is mainly produced by microorganisms. The ability to synthesize thiamine is species-specific in microalgae: Provasoli & Carlucci (1974) observed that thiamine addition to the medium was required for ca 20% of the over 300 species tested in culture. Several species of diatoms and green microalgae have the highest production in comparison with other species (De Roeck-Holtzhauer et al. 1991, Seguineau et al. 1996, Brown et al. 1999). Carlucci & Bowes (1970) discovered that non-producers can utilize thiamine excreted by other phytoplankton species when growing in mixed culture. Direct uptake of thiamine from water may thus be an important source for lower trophic level organisms, while the diet is probably more important among higher trophic level species such as fish (Niimi et al. 1997).

Pigments characterize phytoplankton communities The dynamics of phytoplankton composition constitute crucial data in envi-ronmental monitoring. Traditional assessment requires large investments in off-shore sampling and experienced personnel performing microscopic analyses.

An alternative method for characterizing phytoplankton communities is to determine their pigment composition by using high-performance liquid chromatography, HPLC (Millie et al. 1993). Since accessory pigments vary in chemotaxonomic specificity, their relative abundance can reveal phyto-plankton community structure at the level of algal group (mostly at class level, Millie et al. 1993). Examples of unambiguous pigment biomarkers of single algal divisions/classes are alloxanthin for Cryptophyta, peridinin for Dinophyta, 19'-hexanoyloxyfucoxanthin for Prymnesiophyceae and prasi-noxanthin for Prasinophyceae (Jeffrey & Vesk 1997). Less specific pigments common for two or three classes are e.g. fucoxanthin, lutein, zeaxanthin and chlorophyll b (chl b). In contrast, some carotenoids are distributed over a wide taxonomical range of algae, as for example -carotene which is present in most algal classes and chlorophyll c (chl c) and diadinoxanthin which occur in all groups within the division Chromophyta.

Pigment analysis is generally faster and more reproducible than the tradi-tional microscopic method. It is also more sensitive and objective, including organisms difficult to identify microscopically like small pico- and nanoal-gae or species that are easily deformed by preservatives.

Different approaches have been used for computing algal group abun-dances from measurements of phytoplankton pigment composition in natural communities: (1) simple or multiple linear regression (e.g. Gieskes & Kraay 1983), which is statistically sound but does not distinguish algal groups with shared marker pigments, (2) multiple simultaneous equations (e.g. Letelier et al. 1993), which allows shared marker pigments but are complicated to con-

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struct and (3) matrix factorization, which has been used in the CHEMTAX programme developed by Mackey et al. (1996). The latter method has the advantage that it distinguishes algal groups with qualitatively identical pig-ment compositions using differences in pigment ratios (Wright et al. 1996).

CHEMTAX has been applied successfully in several marine and estuarine areas over the world (e.g. Mackey et al. 1998, Schlüter et al. 2000, Lohrenz et al. 2003, Havskum et al. 2004), but so far never in the Baltic Sea. The programme requires an input pigment ratio matrix adjusted to the regional characteristics of phytoplankton pigment composition (Mackey et al. 1998). Certain knowledge of the phytoplankton composition of the samples and of ratios of accessory pigments to chlorophyll a (chl a) is therefore required.

In paper II, we firstly evaluated the precision of CHEMTAX for Baltic Sea conditions using phytoplankton pigment data from a Baltic Sea meso-cosm study. This was done by using different input pigment ratios from the literature as well as ratios modified to characteristics of our sample material. The CHEMTAX results were evaluated by comparing with data on phyto-plankton composition from microscopic cell counts of replicate samples.

Secondly, we compared the CHEMTAX results with data from the micro-scopic cell counts and with the original pigment data. Ordination analyses were used to evaluate the potential applicability of these three different data types in monitoring or ecological studies.

Unattended phytoplankton sampling The distribution of phytoplankton species and biomass is highly dynamic in both space and time (Harris 1986). Frequent sampling is therefore essential for our understanding of complicated phenomena such as eutrophication and harmful algal blooms as well as for food-web studies and ecosystem model-ling. Expensive off-shore sampling has formerly often restricted sampling frequency, and only during the last decade the “ships-of-opportunity tech-nique” has enabled unattended spatially semi-continuous biomass recordings along regular ship routes. This is made by chl a fluorescence measurements, which are now operational in the Baltic Sea (Rantajärvi 2003, http://www.fimr.fi) and other marine areas (e.g. http://www.soc.soton.ac.uk, http://www.nies.go.jp). For quantification of phytoplankton taxa, however, the standard method is still microscopy, even if ship-based automatic multi-fluorescence analysers are being tested for this purpose (Colijn et al. 2002, http://coast.gkss.de/projects/ferrybox).

In this thesis, pigment analyses combined with ship-of-opportunity sam-pling (paper I) or CHEMTAX data processing (paper II) were evaluated as methods for monitoring or ecological studies of phytoplankton the Baltic Sea.

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Aims of this thesis

The general objectives were (1) to evaluate the use of pigments as chemo-taxonomical biomarkers for phytoplankton community composition in the Baltic Sea and (2) to investigate the effects of eutrophication on production and transfer of carotenoids and thiamine at the phytoplankton–copepod level in marine pelagic food webs.

In one field study (Paper I) and five mesocosm experiments (Papers II–VI), the following specific hypotheses were addressed:

1. Seasonal environmental factors, and especially the supply of nitrogen, determine phytoplankton pigment composition (I).

2. Unattended phytoplankton sampling combined with the use of pigments as chemotaxonomical biomarkers analyzed in CHEMTAX can be used to calculate phytoplankton taxonomic composition from pigment com-position in the Baltic Sea (I, II).

3. Inorganic nutrients regulate the growth of grazing copepods bottom-up via their phytoplankton diet (III, V).

4. Inorganic nutrient supply regulates astaxanthin production in copepods via altered phytoplankton biomass and community composition (IV, V).

5. Inorganic nutrient supply affects thiamine levels in phytoplankton com-munities through changed community composition. Thiamine levels in grazing copepods depend on the levels in their phytoplankton diet (VI).

6. Thiamine shortage in plankton communities can be diagnosed from their thiamine content in combination with the relative abundance of the ac-tive co-enzyme TDP (VI).

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Material and methods

Study areas The study areas in the Baltic Sea were situated in the northern Baltic Sea proper (salinity 6 psu) and in the Norwegian Sea, one inside the Trond-heim Fjord (~26 psu) and one outside the fjord (~30 psu).

Figure. X. Map of the study locations indicated with (A) Ship-of-opportunity sam-pling stations (I), (B) Tvärminne (II), (C) Trondhjem (III), (D) Hopavågen (III, IV,VI) and (E) Askö (paper V, VI). Surface salinity (psu) is shown with thick lines.

C

A

B

E

D

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Ship-of-opportunity sampling In paper I, we followed changes in phytoplankton pigment composition and hydrographical variables during one year in the northern Baltic Sea proper. Sea-water samples were collected approximately biweekly at three open sea positions with an unattended sampling system (Fig. 2) installed and main-tained by the Finnish Institute of Marine Research (FIMR) onboard a pas-senger ferry connecting Helsinki and Stockholm (Fig. 1). This ship-of-opportunity system is used for regular monitoring within the Alg@line monitoring programme (Rantajärvi 2003, http://www.fimr.fi).

Sea-water was pumped through an inlet at 5 m depth in the hull of the ship close to the stern. Water temperature, salinity and in vivo chl a fluores-cence were logged semi-continuously in the flow-through system. Sea-water samplings were pre-programmed and the samples were stored in darkness at 4˚C for 10–20 hours before further handling.

Seasonal and spatial variation in phytoplankton pigment composition and effects of environmental parameters on this variation were examined by principal components analysis (PCA) and redundancy analysis (RDA). Data on inorganic nutrient concentrations and phytoplankton composition were generously provided by FIMR.

Figure 2. Scheme of the unattended flow-through sampling system used in this study. Sea-water flow directions are shown with arrows. Printed with permission from Rantajärvi (2003).

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Pigments as chemotaxonomic biomarkers In paper I, the chemotaxonomic specificity of accessory pigments was used to estimate the structure of the phytoplankton communities at group (often class) level. Pigment composition data from our ship-of-opportunity samples were compared with cell counts made by light microscopy within the Alg@line monitoring programme (Alg@line Database, unpublished data). The samples for cell counts were taken at the same positions as the pigment samples, but at different times; sampling dates differed with 1–9 days. As the two data sets were not from replicate samples, formal correlation tests were not possible. Comparisons between phytoplankton pigment and com-munity composition over time were therefore simply made visually for each sampling position.

In paper II, we tested the CHEMTAX programme (Mackey et al. 1996, http://www.cofc.edu/~ditullio/ChemTax.html) for Baltic Sea conditions us-ing phytoplankton pigment data from the mesocosm experiment in the NE Baltic Sea (Table 1). CHEMTAX works within the MATLAB® computing platform to determine the taxonomic composition of a phytoplankton sample based on the pigments found in the sample by HPLC separation. CHEM-TAX needs one input matrix with measured pigment abundance data and one constructed input matrix with pigment ratios to chl a in different algal groups. The programme provides a final matrix of phytoplankton composi-tion, expressed as group-specific relative contributions to chl a.

Firstly, the pigment data were combined with each of three input pigment ratio data sets: (1) ratios used in the original CHEMTAX publication by Mackey et al. (1996), (2) ratios based on cultivations of estuarine and coastal species by Schlüter et al. (2000) and Zapata et al. (2004) and (3) as (2), but with modifications to the present Baltic Sea data set. The predictive power of CHEMTAX for the different algal groups was evaluated by linear regression analyses.

Secondly, the CHEMTAX results were compared with matching data from microscopic cell counts obtained from the Finnish plankton ecology research group PELAG and with the original HPLC pigment data. PCA was used on three parallel data sets: (1) biomass (µmol C l-1) for each algal group from microscopical cell counts, (2) algal pigment concentrations (nmol l-1)measured by HPLC and (3) group-specific contributions to chl a calculated by CHEMTAX from the HPLC pigment data. To evaluate differences in predictive power of environmental variation between these three types of phytoplankton community data, a set of environmental variables (e.g. treat-ment, time, nutrient concentrations and nutrient quotes) was by multiple regression analysis fitted on the results of the three PCA analyses.

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Mesocosm experiments with nutrient manipulations Mesocosms have frequently been used for studying effects of nutrient avail-ability on phytoplankton growth and taxonomic composition (e.g. Egge & Jacobsen 1997, Carlsson & Granéli 1999) and for studying food web interac-tions (e.g. Hansen et al. 2000, Stibor et al 2004). A mesocosm is an experi-mental enclosure of a water-body, in some cases including bottom sub-strates. In our studies, the mesocosms enclosed surface-water columns open to the air. We chose this semi-natural experimental scale to keep the com-plex structure of the pelagic food web as natural as possible. Details on the experimental set-ups and initial conditions are presented in Table 1.

The study presented in paper II was performed together with the Finnish plankton ecology research team PELAG. Each of eight 51 m3 mesocosms received a unique nutrient treatment combination of high or low dose and high (40), balanced (16) or low (6) molar N:P ratio. One mesocosm was used as a control and one received high and balanced NP addition plus silicate in the ratio Si:N = 1. These nutrient manipulations resulted in different phyto-plankton community developments, which suited our aim to investigate the use of pigments as biomarkers for phytoplankton composition. We combined pigment data and microscopic data on phytoplankton composition in CHEMTAX and ordination analyses.

In four other mesocosm experiments, we combined inorganic nutrient manipulation and copepod grazing in the same experimental set-up (papers III–VI). Different phytoplankton communities were created by nutrient ma-nipulations and subsequently natural copepod assemblages were added to graze. We assessed how fertilization affected phytoplankton and grazing copepods in terms of astaxanthin and thiamine dynamics, as well as elemen-tal composition and growth. Two experiments were carried out in the brack-ish Baltic Sea (papers V, VI) and two in the Norwegian Sea (papers III, IV,VI), which is truly marine and practically unaffected by eutrophication.

Three different nutrient regimes were applied in triplicates (Table 1). The NPSi treatments received daily additions of DSi, DIN and DIP, the NP treatments received only DIN and DIP, and the controls neither DSi, DIN nor DIP. The daily doses corresponded to natural winter concentrations (HELCOM 1996,) and to the molar ratio Si:N:P = 48:16:1. We used the Red-field ratio of N:P (Redfield et al. 1963) and a 3:1 ratio of Si:N to ensure ex-cess Si for diatom growth.

Copepodites were collected locally and added at different densities in the four experiments (Table 1). The initial copepod densities were rather high in the Baltic Sea experiments, but still well below maximum densities meas-ured in the Baltic Sea in summer (HELCOM 1990). As we focussed on re-sponses of the whole copepodite communities from a systems ecology per-spective, copepodite developmental stages were always treated collectively.

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Table 1. Summary of the experimental set-ups including daily DIN, DIP and DSi additions, initial phytoplankton biomass and added copepod densities and biomass (mean SD, n = number of mesocosms) in the five mesocosm experiments.

NE Baltic Sea Norwegian Sea Exp 1

Norwegian Sea Exp 2

NW Baltic Sea Exp 1

NW Baltic Sea Exp 2

Abbreviations NS1 NS2 BS1 BS2 Paper II III III, IV, VI V, VI V, VI Location Tvärminne Trondheim Hopavågen Askö Askö

Dates 23/6–11/71998

12/8–20/81999

29/8–9/91999

8/7–19/7 2000

16/8–27/8 2000

Duration (days) 19 9 12 12 12 Salinity (psu) ~5.7 26.5 0.4 30.1 0.3 5.7 ± 0.1 5.8 ± 0.0 Water temperature (ºC) ~14 13.3 ± 0.7 12.6 ± 0.4 15.7 ± 0.9 15.6 ± 1.7 Number of mesocosms 8 9 6 9 9 Volume (m3) 51 2.0 2.0 1.2 1.6 Diameter (m) 2.3 1.0 1.0 0.9 0.9 Depth (m) 14 2.5 2.5 2.0 2.5

Treatments

Control, L6, L16, L40, H6,

H16, H40, H16+Sia

Control,NP, NPSi NP, NPSi Control,

NP, NPSi Control,

NP, NPSi

DIN (µmol l-1 d-1) 0.12, 0.29, 0.73 4.00 4.00 5.33 4.00 DIP (µmol l-1 d-1) 0.01, 0.02, 0.05 0.25 0.25 0.33 0.25 DSi (µmol l-1 d-1) 0.28, 0.69 12.00 12.00 16.00 12.00 DIN:DIP (mol:mol) 6, 16, 40 16 16 16 16 Phytoplankton (nmol chl a l-1) 3.5 0.3 2.2 0.4 5.9 0.3 3.8 0.4 2.7 0.2

Phytoplankton (µmol C l-1) – 18 1 32 4 43 6 26 2

Copepod density(ind l-1) –b 12 2 18 3 57 6 40 8

Copepod density(µmol C l-1) –b 4.5 1.2 5.8 0.7 9.8 1.2 3.7 0.6

Pigment analyses Yesc Yes Yes Yes Yes Thiamine analyses No No Yes Yes Yes aAbbreviations refer to low (L) och high (H) nutrient dose and to the molar N:P ratios (6, 16, or 40). Silicate addition is indicated with +Si. bNo copepods were added. cAnalyses of phyto-plankton pigments only.

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Analyses of pigments and thiamine The pigment analyses of phytoplankton and copepods were based on the reversed-phase high-performance liquid chromatography (HPLC) method developed by Wright & Jeffrey (1997). Chlorophylls and carotenoids were identified and quantified by their retention times and absorbance at 436 nm with the help of commercial pigment standards. Extracts of Haematococcus pluvialis Flotow cysts were used for identification of esterified astaxanthin. The sum of free and esterified astaxanthin is hereafter referred to as ‘astax-anthin’. In paper IV, PCA was used to classify some unknown pigments as either copepod body pigments or phytoplankton pigments present in the co-pepod samples.

Pigment degradation during sample storage was investigated in paper V,and carotenoids and chlorophylls were found to degrade to a similar extent during storage at -86ºC for ca 17 months. In papers II and V, all pigment concentrations were therefore standardized to the chl a concentrations meas-ured by standard methods during the experiments.

Thiamine in free form (TF) as well as its two most common phosphate es-ters, thiamine monophosphate (TMP) and thiamine diphosphate (TDP) were analyzed by HPLC according to the method described by Pinto et al. (2002). This method allowed accurate quantification of small amounts of these three thiamine species. In this thesis, total thiamine is defined as the sum of TF, TMP and TDP.

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Results and discussion

Seasonal phytoplankton pigment variation The seasonal variation in phytoplankton community pigment composition in our field study (paper I) was explained by a combination of total phosphorus concentration, water temperature, DIN-concentration and salinity (together explaining 35% of the variation). DIN was not the principal explaining fac-tor although primary production is nitrogen-limited in the area (HELCOM 2002). This reflects the complexity of phytoplankton community structure control (Harris 1986). Also, we did not include potentially influential pa-rameters as light influx, hydrodynamic variability and grazing in the analy-sis. In addition, many environmental variables vary with season in temperate seas and are therefore frequently auto-correlated. The importance of a single factor as regulator of phytoplankton community composition may therefore be difficult to determine without experimental investigations.

The pigment dynamics adequately described the general seasonal pattern of pelagic primary production in the northern Baltic Sea area, which is char-acterized by four periods: a low biomass winter state, an extensive spring bloom in April–May dominated by dinoflagellates (sometimes together with diatoms), high prevalence of filamentous nitrogen-fixing cyanobacteria dur-ing summer and, commonly, a less pronounced dinoflagellate or diatom au-tumn bloom (HELCOM 2002).

Main features of the pigment data were the spring peridinin (dinoflagel-late) peak (30–40% of the total carotenoids), immediately followed by an alloxanthin (cryptophyte) peak. Zeaxanthin (cyanobacteria) was highly abundant from May to October, and a peak of 19'-hexanoyloxyfucoxanthin (prymnesiophytes) appeared in late summer–early autumn. The diatom indi-cator fucoxanthin was fairly abundant (7–25% of the total carotenoids) throughout summer and autumn at all stations. No autumn blooms were ob-served in the pigment data.

Maximum abundances of diadinoxanthin coincided with the spring bio-mass peaks. Although diadinoxanthin and chl c are major accessory pig-ments of both dinoflagellates and diatoms, dinoflagellates were seemingly the main contributors of both pigments, as they correlated strongly with peridinin and weakly or not at all with fucoxanthin. Zeaxanthin correlated

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significantly with the cyanobacterial carotenoids -carotene, canthaxanthin and echinenone but not with chl b, lutein or violaxanthin, which are major pigments in Chlorophyceae. We therefore considered zeaxanthin as mainly originating from cyanobacteria and not from chlorophyceans, in which it is a minor pigment. Such basic observations are important for the interpretation of pigment data from field samples, for example when adjusting input pig-ment ratios for CHEMTAX calculations, as discussed below.

The visual comparison between our pigment data and the microscopic phytoplankton data in paper I showed a high resemblance over time between abundances of peridinin and dinoflagellates, 19'-hexanoyloxyfucoxanthin and prymnesiophytes as well as between chlorophyte pigments (chl b, an-theraxanthin, lutein, prasinoxanthin and violaxanthin) and chloro/euglenophytes. Zeaxanthin generally followed the variations in cyanobacterial abundance, but a dense summer bloom of the filamentous cyanobacterium Aphanizomenon sp. was not fully reflected in the pigment data set. Dissimilarities were also found between fucoxanthin and diatoms: a few ephemeral diatom blooms in the autumn were registered microscopically without corresponding peaks in fucoxanthin concentrations.

The annual chl a concentration maxima differed with as much as 35–70% between our study and the Alg@line monitoring programme (Alg@line Da-tabase, unpublished data). This emphasizes that phytoplankton biomass variation cannot be described appropriately with biweekly sampling, and that higher monitoring frequency is necessary, especially during dynamical peri-ods such as the vernal bloom.

The time lag between samplings and differences between the microscopic and pigment techniques may be reasons for the discrepancies between the pigment and phytoplankton data sets. The abundance of small phytoplankton cells can for example be underestimated in microscopic analysis, especially as no epifluorescence microscopy was used (Schlüter et al. 2000).

Successful chemotaxonomy In paper II, the different input pigment ratios used in the three CHEMTAX calculations resulted in output ratios that differed from the input ratios with on average 6.5% for the originally published ratios (Mackey et al. 1996), 15.7% for the published culture ratios (Schlüter et al. 2000, Zapata et al. 2004) and 4.2% for our modified ratios. The original ratios and the originally published ratios were thus closer to the ‘best fit’ values, while the culture ratios deviated more. The reason may be that the original ratios were com-piled from a larger number of species, making the ratios more universal, while the culture ratios were averages of extreme values for one or a few species within each group. To further calibrate CHEMTAX for the Baltic Sea conditions, field-based pigment studies may therefore be more useful

23

than collecting more data from single culture species, although the latter has been recommended by several authors (e.g. Mackey et al. 1996, Schlüter et al. 2000).

Irrespective of which input ratio was used, CHEMTAX had good predic-tive power for the dominant phytoplankton groups cyanobacteria, dinoflagel-lates, prasinophytes and prymnesiophytes. CHEMTAX can thus apparently provide robust results for dominant groups even if input ratios are not espe-cially adapted to local characteristics of the phytoplankton. Among the rare groups, chrysophytes were more abundant in our data set than diatoms, but CHEMTAX with the originally published ratios and culture ratios predicted diatoms and practically no chrysophytes. Diatoms and chrysophytes were combined in the analysis with modified ratios, but the prediction was still weak. This was true also for the low-abundant chlorophytes and crypto-phytes.

The three PCA analyses on the basis of (1) biomass for each algal group from microscopical cell counts, (2) algal pigment concentrations measured by HPLC and (3) group-specific contributions to chl a calculated by CHEMTAX from the HPLC pigment data yielded similar patterns of varia-tion in the ordination diagrams. However, the eigenvalues of the first two ordination axes and the length of the gradients indicated that the cell count data and CHEMTAX data had higher explanatory power than the HPLC pigment data regarding the effects of environmental (mainly nutrient) varia-tion on phytoplankton communities.

My conclusions from the results presented in papers I and II are that unat-tended sampling on regular ship routes combined with HPLC pigment analy-ses and subsequent CHEMTAX data processing can be an accurate, time- and resource-saving alternative to cell counts in Baltic Sea phytoplankton studies. Microscopic and CHEMTAX analyses were equally good for deter-mining phytoplankton community composition at class level. Important to note here is that the cell count data in our study were of high quality, as they were acquired by both light and epifluorescence microscopy. Schlüter et al. (2000) found that data from analyses with only light microscope and CHEMTAX agreed badly for small flagellates and cyanobacteria. In con-trast, Havskum et al. (2004) reported that microscopic and pigment data correlated well with all groups except for pico-sized (<2 µm) cyanobacteria detected by epifluorescence microscopy and flow-cytometry.

Further calibrations of CHEMTAX to regional and seasonal characteris-tics of the phytoplankton in the Baltic Sea could promote use of this method and make comparisons between different laboratories operating in the area possible. Regular use of pigment data in phytoplankton monitoring would in addition improve our scarce knowledge of natural concentrations of carote-noids in marine ecosystems.

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Plankton community responses to fertilization Fertilization of the mesocosms increased phytoplankton biomass manifold and altered community composition considerably in the Norwegian Sea and NW Baltic Sea experiments (papers III, V). From constituting a minor part, diatoms became completely dominant after a few days in the NPSi treat-ments of all four experiments. In the NP treatments, DSi was rapidly ex-hausted and a diverse community composed of dinoflagellates, other phyto-flagellates and ciliates developed. Dominance of non-silicified taxa in Si-depleted systems has been demonstrated before by e.g. Egge & Aksnes (1992) and Duarte et al. (2000).

During the NE Baltic Sea experiment (paper II), phytoplankton commu-nity responses were obvious but slower due to the 5–44 times lower doses of added nutrients. Prymnesiophytes were abundant until the last experimental week. Abundances of dinoflagellates, prymnesiophytes and filamentous cyanobacteria generally increased at the expense of chrysophytes, crypto-phytes and prasinophytes. Diatoms were scarce and their growth was negli-gible and, consequently, DSi never became limiting in any of the treatments.

The grazing copepods responded to the nutrient additions by numerical and somatic growth, while taxonomic composition remained relatively con-stant in all treatments throughout all four experiments (papers III, V). Popu-lation densities generally increased more at low sea-water Si:N ratios (NP treatments, triangles in Fig. 3) and less at high ratios (NPSi treatments, squares in Fig. 3).

As copepod density development was measured as the net result of cope-podite mortality and recruitment to copepodites from eggs and nauplius lar-vae, the observed patterns may have several explanations. One is that the dense diatom blooms inhibited development of eggs and/or nauplii to cope-podites by excretion of inhibitory substances. Release of toxic aldehydes from diatoms has in laboratory experiments been shown to induce egg mor-tality in copepods offered a diatom diet (Paffenhöfer 2002).

Another explanation for the restrained population development in our NPSi treatments may be low phytoplankton diversity and low ciliate densi-ties as compared to the NP treatments. A varied, omnivorous diet is consid-ered as important for optimal nutrition in copepods (Kleppel 1993, Bonnet & Carlotti 2001). Experimental and field studies by Nejstgaard et al. (2001) and Miralto et al. (2003) also demonstrated that a mixed diet was more bene-ficial for copepod growth and reproductive success than a diatom-dominated diet.

Diatoms with heavily silicified frustules can also be less palatable and therefore avoided by grazers. In the Norwegian Sea experiments, micro-scopic observations confirmed that diatoms had thicker frustules in the NPSi treatments (paper III). The pigment content of the copepods furthermore

25

indicated negative selective grazing on diatoms in these treatments, which has also been reported by Andersson et al. (2003).

Somatic growth measured as individual carbon content was, opposite to population growth, generally highest in the NPSi treatments and lowest in the controls (Fig. 3). This probably indicated sufficient food supply in the fertilized treatments. In the unfertilized controls, limited food abundance and too small food items (<10 µm) apparently hindered copepod somatic growth, while net population growth rate was still at least as high as in the NP-treatments.

The rather dense copepod populations probably also affected the (phyto)plankton communities by nutrient recirculation and selective grazing. Such top-down effects have been experimentally studied by e.g. Stibor et al. (2004), who found that copepods reduced large algae by grazing, but simul-taneously promoted small algae by feeding on their ciliate grazers.

0

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0 20 40 60 80 100 120 140Copepod density (ind l-1)

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Figure 3. Copepod density versus carbon individual carbon content during the final 9–12 days of the four mesocosm experiments Norwegian Sea Exp 1 and 2 (NS1 and NS2) and NW Baltic Sea Exp 1 and 2 (BS1 and BS2). Note that day 9 was the last day of NS1. For each experiment, initial means of all mesocosms on Day 6 are shown.

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Inorganic nutrients regulate astaxanthin production… Inorganic nutrients were found to regulate astaxanthin production in cope-pods in a complex way via phytoplankton biomass and community composi-tion (papers IV, V). Fertilization induced divergent responses in somatic and population growth of the copepods (Fig. 3) and simultaneously increased astaxanthin content per individual (larger individuals). Net astaxanthin pro-duction per volume sea-water therefore turned out similar irrespective of treatment in all three experiments.

For the individual copepods, astaxanthin body concentration became low-est in the NPSi treatments in the Baltic Sea experiment (paper V). Net pro-duction rate of astaxanthin was positive (increased body concentrations) only in the unfertilized controls. Fertilization in general and a diatom-dominated diet in particular apparently hampered astaxanthin production in the Baltic Sea experiments. In the Norwegian Sea experiment (lacking a control), body concentrations of astaxanthin were also reduced with fertilization, but with-out any difference between the NP and NPSi treatments (paper IV). The results indicate that astaxanthin production was restricted by decreased con-tent of necessary precursors in the diet, especially in the diatom blooms.

In addition to the effects of diet, high phytoplankton densities reduced under-water light levels which were related to lowered body concentration of astaxanthin in the copepods (paper V). These observations are consistent with the photo-protective role of astaxanthin in copepods, experimentally shown by Hairston (1979), Byron (1982) and Hansson (2000).

In the Baltic Sea experiments, the natural (initial) astaxanthin concentra-tions in copepods was almost twice as high in August (ca 10 µmol (mol C)-1)as in July (ca 6 µmol (mol C)-1, Fig. 4). In the Norwegian Sea in late August it was still higher (ca 15 µmol (mol C)-1). This may reflect a seasonal pattern of pigmentation, which has earlier been documented in a biannual field study in the Norwegian Sea by van der Meeren (2003). He found minimum con-centrations in June–July and maxima during late autumn. Further field stud-ies are needed to determine whether astaxanthin concentrations are generally lower in the Baltic Sea than in the Norwegian Sea, and if the observed sea-sonal variations are universal.

…and thiamine dynamics The N and P additions resulted in lowered thiamine production (per biomass unit) in phytoplankton in all three experiments, regardless whether DSi was supplied or not (Paper VI). This implies that the thiamine synthesis rate was lower than the rate of biomass increase. The fast growing phytoplankton was apparently able to produce new thiamine, but also utilized large reserves of TF to maintain levels of the active coenzyme TDP. The copepod body con-

27

centrations of thiamine were higher when their phytoplankton diet was dominated by flagellates (NP treatments) compared to diatoms (NPSi treat-ments, Fig. 4).

The balance of TDP and the thiamine reserves (mainly TF) could be used as indicators of thiamine shortage in phytoplankton and copepod communi-ties, similar to previous observations in fish (Brown et al. 1998a,b). Thia-mine shortage was defined as exhaustion of the thiamine reserves and de-crease of TDP. Although this never occurred during our experiments, we were able to quantify the limits of shortage by modelling the dynamics of the different forms of thiamine. The limits were calculated to 19.1 µmol thia-mine (mol C)-1 and 5% TDP for phytoplankton communities and 6.8 µmol (mol C)-1 and 11% TDP for copepod communities. We think that these limits are representative and general, given that our model is based on a large data set representing different environmental conditions (e.g. nutrient concentra-tions, salinity) and plankton community compositions. Data published from the Great Lakes also fitted well with our model (Niimi et al. 1997, Fitzsi-mons et al. 1998). With respect to the documented problems of thiamine deficiency in salmonids (Honeyfield et al. 1998), the obvious practical appli-cation of these limits is that they can be used for diagnosing the thiamine status of the ecosystem.

The initial thiamine levels in natural phytoplankton and copepod assem-blages were higher in the Baltic Sea (7–8 µmol (mol C)-1) than in the Nor-wegian Sea (ca 4 µmol (mol C)-1), Fig. 4). The Baltic Sea copepod concen-trations were also higher than in wild crustacean plankton in the Great Lakes (Fitzsimons et al. 1998) and in copepods in Norwegian coastal lagoons (Maeland et al. 2000, van der Meeren et al. 2003). Salmonid fish in the Great Lakes suffer from thiamine-deficiency while Norwegian salmon stocks do not. My results contradict the hypothesis that the thiamine deficiency ob-served in Baltic salmon stocks originates from lower trophic levels, but the scarcity of published data makes such conclusions impossible. As for astax-anthin, field investigations of thiamine concentrations are scarce.

Relationships between astaxanthin and thiamine The concentrations of thiamine and astaxanthin in the individual cope-

pods were positively correlated in all three experiments (linear regression analyses, NS2: R2 = 0.30, p < 0.01, n = 72, BS1: R2 = 0.29, p < 0.0001, n = 108, BS2: R2 = 0.15, p < 0.00001, n = 108, Fig. 4), although regression coef-ficients differed considerably (NS2: 1.2, BS1: 6.5, BS2: 3.9). The results show that the flow of both thiamine and astaxanthin to higher trophic levels may be reduced due to lowered food quality of the copepods caused by fer-tilization.

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As both thiamine and astaxanthin are deficient in M74-affected salmon, there is a need for physiological and molecular investigations of possible interactions between the two compounds in living cells.

0

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Figure 4. Total thiamine plotted against total astaxanthin per copepod carbon unit during the final 9–12 days of the three mesocosm experiments Norwegian Sea Exp 2 (NS2) and NW Baltic Sea Exp 1 and 2 (BS1 and BS2). For each experiment, initial means of all mesocosms on Day 6 are shown. Note the logarithmic scale for astaxan-thin.

Ecosystem implications and future perspectives As copepods constitute a major link between pelagic primary producers and higher trophic levels, the observed effects of fertilization have the potential to affect astaxanthin and thiamine levels in fish, seabirds and other marine top-predators.

The M74 syndrome strikingly appeared soon after the escalation of the large-scale eutrophication in the Baltic Sea during the 1960’s. Water trans-parency also decreased considerably in the Baltic Sea during the 20th century (Sandén & Håkansson 1996). My results show that reduced underwater light levels may lower the need of photo-protective antioxidants (such as astaxan-thin) in crustacean zooplankton. This could be most important in individuals

29

with restricted possibilities to escape from harmful light by vertical migra-tion (e.g. larvae).

An individual copepod of large size and with higher total content of C, N, astaxanthin and thiamine, as in our fertilised treatments, should be a more cost-effective catch to a predator. For example, selective predation on large copepods has been reported for herring in the Baltic Sea (Viitasalo et al. 2001). The trade-off between the risks of predation (visibility by larger size and pigmentation) and harmful ultraviolet radiation (UVR) as discussed by Hansson (2000) is probably of minor importance in a eutrophied system in which high turbidity both decreases UVR and limits the risk of detection by a predator. Seasonal variation of astaxanthin content in copepods (van der Meeren 2003, this thesis) may also affect transfer to higher trophic levels, depending on seasonal feeding behaviour of planktivorous fish.

The high natural thiamine levels in Baltic Sea plankton compared to other coastal areas contradict the hypothesis that thiamine deficiency in Baltic salmon stocks originates from lower trophic levels. Thiamine models for the links copepods–prey fish and prey fish–predators could be developed fur-ther, including the role of fish thiaminases (Wistbacka et al. 2002) and other physiological factors in fish.

Salmon affected by M74 suffer from oxidative stress (Lundström et al. 1999) which may be related to impaired oxidative and metabolic functions. Physiological studies of these functions in crustaceans and in salmon muscle and eggs could clarify possible relationships between thiamine and astaxan-thin (and other antioxidants).

To increase our knowledge of thiamine and astaxanthin availability in ma-rine pelagic ecosystems, offshore surveys of natural levels in different food web compartments over large spatial and temporal scales are necessary.

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Conclusions

Referring to my six hypotheses the following specific findings emerged from this thesis:

1. Part of the seasonal variation in phytoplankton pigment composition was explained by the availability of nitrogen, but other seasonally dependent environmental factors (phosphorus concentrations, water temperature and salinity) were also important (I).

2. Unattended sampling combined with pigment analysis and subsequent CHEMTAX data analysis is an accurate, time- and resource-saving al-ternative to cell counts in Baltic Sea phytoplankton monitoring and eco-logical studies (I, II). The method needs further adaptions to regional characteristics of phytoplankton species and pigment composition.

3. Somatic and numerical growth of copepods can be regulated by sea-water Si:N ratios via diatoms (III, V). At high Si:N ratios (diatom blooms) copepod somatic growth was enhanced while population growth was hampered.

4. Inorganic nutrients regulate astaxanthin production in copepods via phytoplankton biomass and community composition (IV, V). Fertiliza-tion increased the sea-water concentrations of astaxanthin by increasing copepod biomass, while the net production rate of astaxanthin (per unit copepod C) was positive only in the unfertilized controls. Astaxanthin concentration was positively associated with under-water light levels in one of the experiments suggesting a lower need for photoprotection in the shade from dense phytoplankton blooms (V). Eutrophication may in this way lower the food quality of copepods in terms of astaxanthin, thus reducing the transfer of astaxanthin to higher trophic levels.

5. Inorganic nutrient supply decreases the thiamine production (per bio-mass unit) in phytoplankton communities (VI). Copepod body concen-trations were higher when their phytoplankton diet was dominated by flagellates compared to diatoms.

6. Modelling predicted that thiamine shortage occurs below 19.1 and 6.8 µmol total thiamine (mol C)-1 and above 5 and 11% TDP in phytoplank-ton and copepod communities, respectively (VI). These limits can be used for diagnosing the thiamine status of an ecosystem.

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Acknowledgements

I am sincerely grateful to all who helped me during the past years: my supervisor Pauli Snoeijs for all support. I learned a lot! Marianne Pedersén for initializing the project together with Pauli and for being my co-supervisor my colleague and friend Lies Van Nieuwerburgh for everything the aquatic ecology group at Växtbio, especially my neighbours Gustav Johansson and Klemens Eriksson all other people at the department of Plant Ecology for a good working environment, friendship, parties and excursions Marcelo Paes de Barros, Jonas Casslén, Jonken Eriksson, Thomas Han-sen, Liu Jianguo, Helena Persson, Ernani Pinto and Herwig Stibor for pleasant company during field experiments Olle Paulsson, Marianne Pedersén, Pauli Snoeijs, Brita Svensson, Karo-lina Vessby and Jon Ågren for constructive comments on earlier versions of this thesis the alg@line programme at the Finnish Marine Research Institute, espe-cially Mikaela Ahlman, for good co-operation the plankton ecology research team PELAG in Helsinki, especially Risto Lignell and Timo Tamminen for hospitality and providing data from the MESOBAL98 study M.D. Mackey for a providing a copy of the CHEMTAX programme and to Eija Rantajärvi for letting me use Figure 2 Bo Tallmark, Kerstin Wallström, Ingrid Ahnesjö and other teachers I have worked with for teaching mentorship and inspiration all my inspiring supervisors, teachers and fellow students in Norway the staffs at the Askö laboratory, Trondheim Biological Station and Tvär-minne Zoological Station Anette Pettersson and Elisabeth Elwing at Thalassa AB for advice and for the gift of Haematococcus cysts my dear family for all love, help and support, especially mamma, pappa, Olle and Ylva my financial supporters: the Knut & Alice Wallenberg Foundation, the Norsk Hydro Research Foundation, the Stockholm Marine Research Cen-tre, Trondheim Marine Systems Research Infrastructure, the Swedish Foundation for International Cooperation in Research and Higher Educa-tion (STINT) and Helge Ax:son Johnsons stiftelse

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Pigment och tiamin i planktonalger och hoppkräftor – effekter av övergödning i Östersjöns näringsväv

I ett friskt hav är flödet av viktiga näringsämnen från alger till fisk i balans, men hur är det i Östersjön som är starkt påverkad av övergöd-ning? Kan förändringar i algfloran minska tillgången av tiamin och astaxanthin i näringsväven? Finns det ett samband mellan övergödning av havet och M74?

Övergödning påverkar planktonalgerna… Under 1900-talet har balansen mellan kväve, fosfor och kisel i Östersjön rubbats. Tillförseln av kväve och fosfor har ökat med fyra respektive åtta gånger medan tillförseln av kisel har minskat. Planktonalgerna har reagerat genom ökad tillväxt och ändrad sammansättning. Olika alggrupper behöver olika mängd näring för att kunna växa. Kiselalger behöver kisel till sina skal medan andra alger klarar sig utan. Långtidsstudier har visat att dinoflagella-ter och kvävefixerande cyanobakterier (blågrönalger) har blivit vanligare medan kiselalgerna har minskat i Östersjön. Cyanobakterierna har gynnats av att fosfortillförseln ökat mest, eftersom de kan utvinna kväve från luften.

…och troligtvis hela näringskedjan Laxen i Östersjön har varit drabbad av M74 sedan mitten av 70-talet. Sjuka fiskar lider brist på tiamin (vitamin B1) och det röda pigmentet astaxanthin. Tiaminet produceras främst av planktonalger, men alla arter har inte den förmågan. Hoppkräftor är de viktigaste producenterna av astaxanthin i havet, men de behöver speciella algpigment (betakaroten eller zeaxanthin) som byggstenar. Hoppkräftorna blir fiskföda och på så sätt förs astaxanthin vidare i näringskedjan, som kan beskrivas så här: planktonalger äts av hoppkräftor, som äts av sill och skarpsill, som äts av lax. Orsaken till M74 kan finnas i kedjans första länk. Tiamin- och astaxantinbristen hos lax kan bero på att de algarter som innehåller mycket tiamin, betakaroten och zeaxanthin har blivit ovanligare.

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Gödsling ändrar tiamin- och astaxanthinhalterna i plankton Jag undersökte i några experiment hur näringstillgången påverkar innehållet av tiamin och astaxanthin i planktonalger och hoppkräftor. När jag gödslade havsvatten med kväve, fosfor och kisel uppstod kiselalgblomningar. Göds-ling utan kisel ledde istället till blomningar av olika flagellater som saknar kiselskal. I ogödslade kontrollbehandlingar växte algerna knappast alls.

Tiaminhalterna i planktonalgerna var högst i kontrollerna och oftast högre i flagellatblomningarna än i kiselalgblomningarna. Samma mönster återkom hos hoppkräftorna, som ju fick tiaminet från algerna de åt. Gödsling tycks alltså minska hoppkräftornas kvalitet som fiskföda med avseende på tiamin. På grund av ökade mängder av alger blev däremot den totala halten av tia-min i vattnet högre vid gödsling.

På samma sätt visade sig hoppkräftornas tillväxt vara avgörande för den totala mängden astaxanthin i vattnet. Individerna växte mest i storlek medan antalet individer påverkades negativt i kiselalgblomningarna. I de ogödslade kontrollerna var det omvänt och i flagellatblomningarna ett mellanting. Mängden astaxanthin i vattnet skilde sig därför inte åt mellan de tre behand-lingarna och gödslingen hade alltså ingen effekt på den totala tillgången.

I de enskilda hoppkräftorna var effekten av näringstillförseln däremot tyd-lig. Deras kroppshalter av astaxanthin ökade i kontrollerna och minskade i kiselalgblomningarna. I ett experiment minskade de även i flagellatblom-ningen. Gödsling tycks alltså minska hoppkräftornas kvalitet som fiskföda även med avseende på astaxanthin.

Det fanns även ett samband mellan astaxanthinkoncentration och ljusin-strålning. Hoppkräftorna innehöll mindre astaxanthin när de skuggades av algblomningar. Eftersom astaxanthin skyddar mot skadligt ljus tydde detta på att deras behov av solskydd minskade.

”Pigmentsignaturer” kan användas för algövervakning Olika alggrupper har olika typer och mängder av pigment. Jag undersökte om dessa ”pigmentsignaturer” kan användas för att avgöra sammansättning-en av planktonalger i Östersjön. En beräkningsmetod som använts i andra havsområden visade sig fungera bra även i här. Genom att använda denna metod skulle övervakningen av alger i Östersjön kunna bli effektivare.

Sammanfattningsvis Effekterna av övergödning på näringsväven tycks vara sammansatta. Den totala mängden tiamin och astaxanthin påverkades inte av gödsling i mina experiment. Däremot minskade de enskilda hoppkräftornas innehåll av tia-min och astaxanthin och därför kan flödet till fisk ändå påverkas. Mina resul-tat tyder på att hoppkräftornas behov av astaxanthin som solskydd kan ha minskat i Östersjön, eftersom siktdjupet, och därmed ljusinstrålningen i vatt-net, har minskat under 1900-talet på grund av ökad algtillväxt.

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A doctoral dissertation from the Faculty of Science and Technology, UppsalaUniversity, is usually a summary of a number of papers. A few copies of thecomplete dissertation are kept at major Swedish research libraries, while thesummary alone is distributed internationally through the series ComprehensiveSummaries of Uppsala Dissertations from the Faculty of Science and Technology.(Prior to October, 1993, the series was published under the title “ComprehensiveSummaries of Uppsala Dissertations from the Faculty of Science”.)