EFFICIENCY OF DIATOM AND
FLAGELLATE-BASED MARINE FOOD WEBS
Yasmina Hamladji
Master Thesis in Biology (30hp)
Supervisor: Agneta Andersson and Sonia Brugel
Abstract
Aquatic microbial food webs are in general size structured. Phytoplankton, which constitute the base of the food web, are grazed by protozoa and mesozooplankton, which in turn are consumed by planktivorous fish. Food web efficiency (FWE) is a measure of how efficiently energy is transported up the food web. FWE is low if the phytoplankton is inedible by the grazers, while FWE is higher if the phytoplankton community is dominated by edible phytoplankton. Recently, the presence of microfungi in aquatic food webs have been suggested to facilitate energy transfer up the food web, via the “mycoloop”. The aim of the study was to set-up a model system of phytoplankton – zooplankton food chains, relevant to the Baltic Sea, and to test FWE in diatom and flagellate-based food webs. Further, I wanted to introduce microfungi in the system and observe their impact on FWE. After many phytoplankton and zooplankton species tests, I decided to perform grazing experiments using one grazer, the ciliate Tetrahymena pyriformis, and two phytoplankton species: a diatom (Skeletonema marinoi) and a flagellate (Rhodomonas baltica). I hypothesized that T. pyriformis would more efficiently feed on flagellates than on diatoms. I performed a grazing experiment where the increase in ciliate abundance was measured, the consumption of the phytoplankton monitored and the FWE estimated. The diatom-based food web led to 14 times higher FWE than the flagellate-based food web. The variation in FWE may be explained by a difference in initial abundances introduced in the experimental treatment, which created unequal grazer:prey ratio between treatments. Further, the swimming behaviour of the flagellate might have reduced the capture efficiency by the ciliate. Microfungi were introduce in an experiment, from a natural seawater sample, but fungal infection was not observed for any of the tested phytoplankton species. Further development is needed to test the effects of microfungi on marine FWE.
Key words: phytoplankton, flagellate, diatoms, ciliates food web efficiency, fungi
Preface
Generally, I am grateful to integrate Agneta’s team and make me discover the research work conditions. Deeply, I want to thank Agneta Andersson, my supervisor to accept me working in her team along this project at the Department of Ecology and Environmental Science (EMG) at Umeå University. She also helped me to improve my skills in writing. Moreover, I thank Sonia Brugel by supervising and explaining to me with passion the practical work.
Over this few month, I collaborated with Siv Huseby at UMF (Umeå Marina Forskningscentrum) to kindly get us some water samples from the Baltic Sea. As another collaboration, I am thankful to Karolina Eriksson and Kesava Ramasamy for giving me an aliquot of the ciliate Tetrahymena pyriformis from their experiments.
Table of content
Master Thesis
Abstract ... 2
Preface ... 3
Table of content ... 4
Introduction ... 5
Materials and methods ... 7
Culture preparation ... 7
Experimental set-up ... 8
Grazing experiment ... 8
Fungal experiment ... 9
Sample processing ... 10
Statistical analyses ... 10
Results ... 11
Grazing experiment ... 11
Fungal experiment ... 13
Discussion ...14
T. pyriformis grazing on S. marinoi and R. baltica ...14
No infection for C. wighamii, S. marinoi and R. baltica ...14
Conclusion ... 15
References ...16
Appendices ... 18
Annex 1: f/2 medium recipe ... 18
Annex 2: Food web efficiency experiment protocol...19
Annex 3: Fungal experiment protocol ...19
Introduction
Aquatic food webs are highly diverse and structured by environmental conditions at both lower and higher trophic levels. At the bottom of the food web, picoplankton are composed of organisms in the size range of 0.2-2 µm, nanoplankton of 2-20 µm organisms, microplankton of 20-200 µm and mesoplankton of organisms in the size range 200-2000 µm. Although many studies have been performed to unravel the regulation of the food web dynamics, many questions remain, for example how microfungi interact with microorganisms (Li et al., 2014).
Trophic interactions are essential for material and energy flows in every ecosystem (Agha et al., 2016). An important function of the “microbial food web” is the assimilation of dissolved organic matter (DOM) by heterotrophic bacteria, and transfer of that energy to protozoa, eukaryotic microzooplankton and mesozooplankton. Mesozooplankton are food for planktivorous fish. The microbial food web thus constitutes a link for organic matter transfer through lower, e.g., bacteria, to higher trophic levels, e.g., fish (Berglund et al., 2007).
Phytoplankton constitute the base of the aquatic food web (Lignell et al., 1993), and via predation they support higher trophic levels with organic carbon, nitrogen and phosphorus.
Phytoplankton are grazed by mesozooplankton and protozoa; and then the energy is channelled to planktivorous fish (Lignell et al., 1993). This pathway is named “the classical food web”. Transfer efficiency between trophic levels as well as the number of trophic levels are important for the overall food web efficiency (Berglund et al., 2007). Food web efficiency (FWE) can be defined as the production by highest trophic level in a system divided by the production by lowest trophic level. The transfer efficiency between trophic levels has been shown to be ~25-30% in aquatic systems (Straile 1997). Thus, the number of trophic levels is of crucial importance for how much energy reaches higher trophic levels. Mesozooplankton and other grazers of phytoplankton play a key role in the aquatic food web by linking the microbial and the classical food web.
Phytoplankton are the main primary producers in the Baltic Sea as in other larger aquatic ecosystems (Lignell et al., 1993). Diatoms and different types of flagellates are commonly occurring phytoplankton groups (Irigoien et al., 2004). During spring, phytoplankton grow rapidly and often an exponential increase in abundance can be observed (Lignell et al., 1993).
Both the phytoplankton and bacterial food web pathway play an important role by providing energy and nutrients to intermediate trophic levels, such as zooplankton and protozoa. Finally the energy ends up at higher trophic levels, for example in predatory fish (Li et al., 2014).
However, the size and edibility of the basal trophic level to a large degree influence the transfer efficiency to higher trophic levels. If the basal food source is relatively inedible, an extra internal trophic level could be induced causing increased of energy losses in the food web. How the food web efficiency vary depends on what phytoplankton is dominating at the base of the food web (Andersson et al., 2015). Berglund et al. (2007) showed that a food web based on phytoplankton held higher efficiency compared to a bacteria-based food web. This means that an additional internal trophic level lead to much lower FWE. Large phytoplankton, like chain- forming diatoms, would be too large to be directly consumed by mesozooplankton. In this case, the major carbon pathway will be via phytoplankton exudation to bacteria, protozoa and then to mesozooplankton.
Recently, aquatic research has turned into focusing on the role of parasites in the food web (Agha et al., 2016). Chrytrids are parasitic microfungi that use phytoplankton as host. They infect phytoplankton, use the organic content to reproduce and release zoospores to infect new phytoplankton host cells. Their zoospores are in the nanoplankton size range; thus, it may be expected that they can be consumed by mesozooplankton. Therefore, one theory is that microfungi, like chytrids, facilitate or even enables energy transfer up the food web, even though the food zooplankton sizes show mismatches in size. Fungal infections can have both negative and positive impacts, by influencing several higher trophic levels at the same time (Lignell et al., 1993). Zooplankton can feed directly on fungal zoospores (Agha et al., 2016).
Then, zooplankton may improve the productivity and transfer to higher level by being eaten by planktivorous fishes. The fungal pathway is called the mycoloop. This new pathway may
facilitates the energy transfer up the food webs (Kagami et al., 2014). Further, this flow of energy might even improve the quality of the food web via trophic upgrading (Gutiérrez et al., 2016).
The aim of the project was to set up a laboratory model system and measure transfer efficiency or FWE of selected phytoplankton-based food webs. In the second phase, microfungi should be introduced into the system and an eventual change in FWE measured. Rhodomonas baltica was chosen as a representative of flagellates, while Skeletonema marinoi and Chaetoceros wighamii were chosen as representative of chain-forming diatoms. Additionally, parasitic fungi were introduced into flagellate and diatom cultures to determine if hosts are specifically infected at the species or strain level.
I expected that (1) flagellates would be preferred food by zooplankton over diatoms. Thus, the FWE would be higher in the flagellate-based food web than in the diatom-based food webs, and (2) the introduction of parasitic fungi in phytoplankton culture would show an infection at the species level.
Materials and methods
Culture preparation
The phytoplankton cultures used in the project were ordered from different culture collections:
Algal Bank GUMACC at Gothenburg University NORCCA at NIVA/Oslo University, and FINMARI Algal Culture Collection at Tvärminne Zoological Station, University of Helsinki.
The first step of the process was to select different types of phytoplankton found in Baltic Sea.
Rhodomonas (Rhodomonas salina (Wislouch) D.R.A.Hill & R.Wetherbee 1989, strain 126 from GUMACC, Rhodomonas marina (P.A.Dangeard) Lemmermann 1903, strain crypto 07- B3 from Tvärminne Zoological Station and Rhodomonas baltica Karsten 1898, strain NIVA- 5/91 from NORCCA) is an autotrophic flagellate, which size range from 18 to 30 µm (Throndsen, 1997). The diatoms selected were Skeletonema marinoi Sarno & Zingone 2005 (strain 143 from GUMACC, strain C1407 from Tvärminne Zoological Station and strain NIVA- BAC 60 from NORCCA), Chaetoceros wighamii Brightwell 1856 (strain NIVA-BAC50 from NORCCA and strain CWTV C1 from Tvärminne Zoological Station) and Melosira nummuloides C. Agardh 1824 (strain BB004-B from GUMACC). They are unicellular photosynthetic algae from 5 to 20 µm for Skeletonema and Chaetoceros in culture conditions, however, in natural conditions they can form chains. Melosira was the only diatom forming chains in culture conditions. Diatoms have a siliceous skeleton (Scholz et al., 2016) (Figure 1).
Rhodomonas baltica Chaetoceros wighamii
Skeletonema marinoi
Melosira nummuloides Figure 1 Pictures of phytoplankton cultures, stained with Lugol solution.
First, I worked with phytoplankton cultures to adapt the cultures to the salinity in the northern Baltic Sea, which is close to 5 psu (practical salinity units). After testing the optimal time of phytoplankton adaptation, the change of salinity in the culture medium was planned every 2 weeks. The medium was a mix of artificial sea water, composed of synthetic sea salt and distilled water, combined to f/2 medium components (Annex 1) (Guillard and Ryther, 1962).
The cultures were grown in vented tissue culture flask. The original salinity was 26 psu in the cultures from GUMACC, 25 psu in the cultures from NORCCA and 6 psu in the cultures from Tvärminne Zoological Station. Practically, I progressively decreased the salinity by steps of 5 psu down to a final salinity of 5 psu. The final experiments were run at 5 psu. The cultures were maintained at 15°C under 40 µmol photon.m-2.s-1 with a photoperiod of 12:12. Moreover, I
followed the growth by counting phytoplankton under microscope at each step of salinity decrease at the first day and after 2 weeks.
Samples to monitor the cultures were preserved with acidic Lugol solution (Helsinki Commission and Baltic Marine Environment Protection Commission, 2006). The samples were analysed in a Sedgewick-Rafter counting chamber or an Utermöhl counting chamber (Hydrobios) by using a Nikon Elipse Ti-s inverted microscope (LeGresley and McDermott, 2010; Paxinos and Mitchell, 2000). Also, I pictured species by using the microscope camera DS Camera Head digital sight D5-U3.
The phytoplankton taxa relevant to the northern Baltic Sea ecosystem do not have a high growth rate, even under culture conditions. Hence, finding a grazer that can successfully be fed with these cultures is challenging. I wanted to adapt different types of zooplankton to the culture conditions in order to investigate food web efficiency. At first, I planned to use the cladoceran Daphnia magna as grazer, since it is a well-known intermediate trophic level taxon in aquatic food webs (Wojtal-Frankiewicz, 2012). A Daphnia magna culture was purchased from Planktovie. I tried to adapt them at 5 psu but the Daphnia did not survive the transfer.
Looking for another alternative, I tried to hatch rotifer eggs from Brachionus calyciflorus at 5 psu. Unfortunately, their food demand was too high compared to the potential growth of the phytoplankton cultures available to use this grazer in the experiment. At last, I decided to use a ciliate, Tetrahymena pyriformis (Culture Collection of Algae and Protozoa, UK). This grazer turned out to be useful in my experiment.
Experimental set-up Grazing experiment
The phytoplankton kept for the final experiment were R. baltica (NIVA-5/91), and S. marinoi (C1407).
The grazer of phytoplankton was a ciliate, Tetrahymena pyriformis (TP) (Figure 2). It was available in axenic culture in the EcoChange laboratory (EMG department). This species did not endure adaptation to the medium owing to previous experience in the group working with the ciliate in experiments in natural local seawater.
Figure 2 T. pyriformis, stained by Lugol solution.
The grazing experiment was performed over 7 days with the following 3 treatments (Figure 3):
(1) Rhodomonas+TP, (2) Skeletonema+TP, (3) TP and their 3 replicates (Annex 2).
Figure 3 Experimental set-up. Each bottle with algae represents a treatment and a simple culture of T. pyriformis is the control. Each treatment had three replicates.
Fungal experiment
The phytoplankton kept for the final experiment were R. baltica (NIVA-5/91), S. marinoi (C1407), and C. wighamii (CWTV C1). S. marinoi and C. wighamii were included in this experiment due to the high potential of fungal infection.
Plankton was collected at a coastal station next to the Umea Marine Sciences Center to obtain fungi associated to their diatoms. The water was first adapted to culture condition (15°C, 40 µmol photons.m-2.s-1 and f/2 nutrients addition). After adaptation, the plankton was analyzed under microscope to check the presence of phytoplankton parasitic fungi (Figure 4). This water was later filtered through a 10 µm mesh filter, to remove as many large organisms as possible and to collect the fungal zoospores in the filtrate (Alster and Zohary, 2007; Gutiérrez et al., 2016).
Figure 4 Potential fungal infection in natural phytoplankton. Picture of infected Thalassiosira sp., taken at magnification 400.
The fungi experiment was performed over 15 days with the following 6 treatments (Figure 5):
(1) Rhodomonas, (2) Rhodomonas + Fungi, (3) Skeletonema, (4) Skeletonema+ Fungi, (5) Chaetoceros, (6) Chaetoceros+Fungi. All treatments were performed with 3 replicates (Annex 3).
Figure 5 Experimental set-up. Each bottle containing only algae represents a control and each bottle containing algae and fungal solution represents treatment. Each treatment had three replicates.
Sample processing
When I was collecting samples for both experiments, I took samples of 3 ml stained by Lugol solution and analysed under microscope for day 0 and day 7 or day 15. I used a Utermöhl counting chamber to count phytoplankton abundance in both experiments as well as T.
pyriformis abundance in the food web efficiency experiment (Paxinos and Mitchell, 2000).
Statistical analyses
During the culture preparation, I calculated biovolumes (BV) following HELCOM guidelines (Helsinki Commission and Baltic Marine Environment Protection Commission, 2006), and carbon biomass (BM), (Menden-Deuer and Lessard, 2000) of the phytoplankton and ciliate cells. The following formula were used for diatoms (1), S. marinoi, C. wighamii and M.
nummuloides, for R. baltica (2) and for T. pyriformis BV (3) and BM (2):
(1) BV = (PI/4) x d x d x h (d=diameter and h=height).
(2) BV = (PI/12) x d x d x (h+d/2) (3) BV = (PI/6) x d x d x h
(1) BM = 0,288 x BV0.811 (2) BM= 0,216 x BV0.939
Then, the percentage of change (figure 6 and table 1) was calculated by the following equation:
parametric data, I decided to perform t-test to compare algal and ciliates abundance at day 7 between Rhodomonas+TP and Skeletonema+TP treatments. And I used Mann-Whitney test for the data of percentage of change and FWE.
Results
Grazing experiment
After performing all pilot growth tests, I finally decided to use R. baltica, S. marinoi and T.
pyriformis in the grazing experiment.
Figure 6 Mean abundance of T. pyriformis abundance and alga (S. marinoi and R. baltica) from day 0 to day 7.
Error bars represent standard deviations.
The aim was to have the same start carbon biomass concentrations of the phytoplankton and the grazer in both treatments. However, by accident, the start abundances of T. pyriformis and algae differed in Rhodomonas+TP and Skeletonema+TP. During the time course of the experiment, T. pyriformis abundance increased in both treatments and in the control. The largest increase of abundance was found in the Skeletonema+TP treatment. Simultaneously, the algal abundance strongly decreased in the Skeletonema+TP treatment, while it increased in the Rhodomonas + TP treatment (Figure 6).
The algal abundances were significantly different in the Skeletonema+TP treatment and the Rhodomonas+TP treatment at day 7 (t-test, p = 1.90E-6). T. pyriformis abundance was also significantly different between both treatments at day 7 (t-test, p = 0.0004).
Figure 7 Mean percentage of change of T. pyriformis and algae biomass in treatments and control. Error bars represent standard deviations.
Whatever the treatment, the biomass of T. pyriformis increased. For instance, the average percentage increase was 2328±1598% in the Rhodomonas+TP treatment, 956±218% in the Skeletonema+TP treatment but only 290±214% in the control (TP). Moreover, the R. baltica biomass showed an increase of 58±50% while S. marinoi biomass decreased by 95±3% (Figure 7).
The percentage of change of T. pyriformis biomass did not show any significant difference between treatments (Skeletonema+TP vs. Rhodomonas+TP, Mann-Whitney U test, p = 0.19).
No significant difference was found for the algae percentage of change (Skeletonema+TP vs.
Rhodomonas+TP, Mann-Whitney U test, p =0.08).
The FWE in Rhodomonas+TP was 14.6±3% and in Skeletonema+TP 209±70% (Figure 8). The FWE was significantly lower in the Rhodomonas+TP treatment than in the Skeletonema+TP treatment (Mann-Whitney U test, p = 0.0495).
Fungal experiment
After two weeks, which is a usual experimental time for studying fungal infections in microalgae, no fungal infection was observed on R. baltica, S. marinoi and C. wighamii. After two weeks, S. marinoi abundance had strongly decreased, and C. wighamii was almost completely absent. The filtrate used to collect the fungal zoospores also contained other phytoplankton taxa that grew during the experiment (e.g. Monoraphidium contortum, Diatoma sp., Cylindrotheca closterium, Aphanothece sp.).
Discussion
T. pyriformis grazing on S. marinoi and R. baltica
The consumption of S. marinoi by T. pyriformis resulted in a marked increase of T. pyriformis abundance and a decrease of S. marinoi abundance (Figure 6). The carbon biomass of S.
marinoi showed as similar strong decrease during the experiment as did the abundance (Figure 7). The decrease of S. marinoi may either be explained by natural mortality or by ciliate grazing. Natural mortality would be caused by nutrient or light limitation but in this experiment, light and nutrient were in excess. Consequently, the diatom showed a large decrease, probably because of efficient feeding by the ciliate. Additionally, the ratio grazer-prey were relatively high, which means S. marinoi did not have time to grow and build up biomass (Balzano et al., 2011). During the pre-growth tests, I noticed that the growth rate of S. marinoi was relatively slow.
T. pyriformis grazing on R. baltica resulted in an increase of both the grazer and the prey abundances (Figure 6). Both R. baltica and T. pyriformis biomass percentage of change increased (Figure 7). This indicated that R. baltica was not submitted to a high grazing pressure. Likely, R. baltica was growing faster than T. pyriformis was grazing them (Calbet and Alcaraz, 1997). During the pre-growth tests, I noticed that the growth rate of R. baltica was relatively fast.
I was expecting that T. pyriformis would prefer to graze more on R. baltica than S. marinoi, due to the silica frustule built around diatoms (Berglund et al., 2007). Yet, the result indicated that S. marinoi was better incorporated in the food web than R. baltica (Uitto et al., 1997).
However, since R. baltica is a motile flagellate, swimming may be used as a mechanism to avoid grazing by T. pyriformis. Diatoms are not motile, hence ciliates may not spend as much energy to graze on S. marinoi. Moreover, S. marinoi has a slower growth rate than R. baltica that might explain the large difference between algae biomass percentage of change (Figure 7) (Balzano et al., 2011; Calbet and Alcaraz, 1997).
Another factor that needs to be considered when evaluating the FWE results is the different grazing pressure in different treatments. In the grazing experiment the start abundances of the grazer and the prey differed in different treatments. The abundance difference of T. pyriformis, R. baltica and S. marinoi at the end of the experiment might be related to the difference of initial abundance (Figure 6). This might explain the large difference in FWE between the diatom-based and the flagellate-based created food webs, 209±70% in Skeletonema+TP compared to 14.6±3% in Rhodomonas+TP (Figure 8). The outcomes may be connected to the ratio grazer:prey, which was higher in the Skeletonema+TP treatment and lower in the Rhodomonas+TP treatment. Indeed R. baltica was not submitted to a high grazing pressure, compared to S. marinoi, which did not have time to grow and build-up biomass. If the initial abundance and biomass of S. marinoi, R. baltica and T.pyriformis would have been similar, the outcomes may have changed the final FWE result (Figure 8). Further, I would consider that the Rhodomonas+TP treatment could be a more sustainable food web over time due to the higher growth rate of R. baltica (Calbet and Alcaraz, 1997).
The final abundance of T. pyriformis was higher in both algal treatments compared to the control, suggesting that phytoplankton are a valuable food source for T. pyriformis. The higher increase of T. pyriformis in the Rhodomonas+TP treatment than in Skeletonema+TP may be
Chaetoceros+Fungi and Skeletonema+Fungi treatments, explaining the absence of observable infections. The natural parasitic fungi community could not be isolated by filtration without including other natural algal species. Therefore, the observed mortality of C. wighamii and S.
marinoi could have been caused by the species competition with other algae or by fungal infection. It is not possible to exclude or confirm the hypothesis about the fungal host- specificity at species or strain level.
Conclusion
To conclude, the FWE was higher in the Skeletonema+TP treatment than in Rhodomonas+TP.
The difference in FWE cannot be explained by different sizes of the prey, since the cell sizes of both R. baltica and S. marinoi were relatively similar. Instead, the results may be explained by the 6-fold higher initial T. pyriformis biomass and thereby a higher predation pressure and absolute increase in biomass (but not in growth rate) in the Skeletonema+TP treatment, but also by a potential grazing avoidance mechanism in the Rhodomonas+TP treatment. While S.
marinoi is immotile and easy to capture, R. baltica can use its swimming behaviour to avoid being captured and consumed by the grazer. However, over time, Rhodomonas+TP treatment might be more sustainable food web and give a higher FWE. Regarding the fungi infection experiment, I could not prove that infection did occur in the experiment.
Further studies would, however, be needed in order to be able to generalize the results to the landscape scale. Mimicking the Baltic Sea food webs in the laboratory was difficult and took long time due to the condition’s adaptation. The success of building up an experimental food web might be improved by adapting other species of zooplankton (e.g. rotifers, cladocerans, etc) to artificial seawater combined to f/2 medium before phytoplankton incorporation. In parallel, I would keep working with the ciliate T. pyriformis. Further, I would carefully add the same amount of carbon biomass of both the grazer and the prey in each treatment. The experimental time should be longer with samplings every week to evaluate the evolution of FWE over time, with different phytoplankton-based food webs. Furthermore, the fungal set- up should be improved by isolating fungi in culture from the seawater and testing more phytoplankton species. Finally, with the perspective of natural food webs in mind, I would combine both set-ups together to address the role of fungal infections through the mycoloop between the trophic levels. In this case, I would trace carbon or nitrogen isotopes from fungi to T. pyriformis or other zooplankton. Elucidating these research questions would lead to a better understanding of the food web channelling in aquatic systems.
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Appendices
Annex 1: f/2 medium recipe
The original protocol was made by Guillard and Ryther in 1962 (Guillard and Ryther, 1962;
Guillard, 1975). This medium is an enriched seawater medium specific to grow marine algae (flagellates, diatoms, etc.). (Andersen, 2005).
Annex 2: Food web efficiency experiment protocol
Table 1 Protocol followed during the food web efficiency experiment. For each treatment, 3 replicates were handled. (TP for T. piryformis, Rh means R. baltica, Sk means S. marinoi and ASW+ f/2medium + (ASW
represents the artificial sea water at 5 psu).
Day TP Rhodomonas+TP Skeletonema+TP+
28 ml ASW+ f/2
medium 20 ml ASW+ f/2
medium 20 ml ASW+ f/2
medium 100 µl TP pure
culture 100 µl TP pure
culture 100 µl TP pure culture -- 8 ml Rh pure culture 8 ml Sk pure culture
Sample D0 3 ml of sample + Lugol solution
Sample D7 3 ml of sample + Lugol solution
Annex 3: Fungal experiment protocol
Table 2 Protocol followed during the fungal experiment. For each treatment, 3 replicates were handled. (Cw for C.
wighamii, Rh means R. baltica, Sk means S. marinoi, ASW f/2 medium (ASW represents the artificial sea water at 5 psu). In FSW+ f/2 medium, a f/2 medium concentrate was added to natural sea water filtered through 10µm
(size of zoospore)).
Treatment
Day Sk Cw Rh Sk+F Cw+F Rh+F
3 ml Sk pure culture
3 ml Cw pure culture
3 ml Rh pure
culture 3 ml Sk pure culture
3 ml Cw pure culture
3 ml Rh pure culture 28 ml
ASW+
f/2 medium
28 ml ASW+
f/2 medium
28 ml ASW+
f/2 medium 28 ml
FSW f/2 28 ml
FSW+ f/2 28 ml FSW
f/2
Sample D0 3 ml of sample + Lugol solution
Sample D15 3 ml of sample + Lugol solution
