Water column stratification, phytoplankton diversity and ... · relationship between phytoplankton diversity and carbon dynamics has not been investigated in marine environments.

Water column stratification, phytoplankton diversity and

consequences for resource use and productivity

NTNU Sletvik Fieldstation

NTNU Sletvik Field Station Phytoplankton Diversty and Water

Column Stratification

EC contract no. 261520

Status: draft

Date: Jul 2009

Infrastructure NTNU Sletvik Fieldstation

Project Water column stratification, phytoplankton diversity and consequences

for resource use and productivity

Campaign HyIII-NTNU-24

Title NTNU Sletvik Field Station Phytoplankton Diversty and Water Column

Stratification

Lead Author Maren Striebel Email [email protected]

Contributors

Email

Date

Campaign

Start

21/07/2009 Date

Campaign

End

21/08/2009

Date Final

Completion

Contents:

Heading:

Contents:

1 Scientific aim and background

2 User-Project Achievements and difficulties encountered (max 250 words)

3 Highlights important research results (max 250 words)

4 Publications, reports from the project

5 Description

5.1 General description, including sketch

5.2 Definition of the coordinate systems used

5.3 Instruments used

5.4 Definition of time origin and instrument synchronisation

6 Definition and notation of the experimental parameters

6.1 Fixed parameters

6.2 Variable independent parameters

6.3 Derived parameters and relevant non-dimensional numbers

7 Description of the experimental campaign, list of experiments

8 Data processing

9 Organisation of data files

10 Remarks about the experimental campaign, problems and things to improve

1. Scientific aim and background:

Stratification and diversity

The seasonal stratification of water columns determines the general availability of the resources

light and nutrients for phytoplankton growth (Diehl 2002; Diehl et al. 2002). Experiments

manipulating the depth of mixing layers and/or the mixing intensity showed that these physical

parameters strongly affect phytoplankton primary production by influencing phytoplankton light

exposure and affecting phytoplankton mortality by sedimentation (Diehl 2007; Jäger et al. 2008).

However, seasonal stratification can be affected and disturbed by aseasonal effects such as strong

rain and wind events. Hence, disturbances of water column stratification imply disturbances for

phytoplankton dynamics since it causes alterations in the relative supply of light and nutrients

(Flöder & Sommer 1999). According to ecological theory, the frequency of disturbance strongly

affects the diversity of biological communities (Huston 1994). Whether disturbances increase or

decrease the diversity of a community also depends on the productivity and the resource supply rate

(Huston 1994). In environments with low nutrient supply, the same disturbance may have opposing

effects on phytoplankton communities as compared to environments with high nutrient supply. This

important interaction between disturbances and nutrient supply rate is, however, seldom considered

in investigations of disturbance effects on plankton communities.

Diversity and resource use efficiency

Environmental effects on phytoplankton diversity will have extensive consequences extending

beyond changes in species composition. A recent metaanalysis including about 3000 freshwater and

brackish phytoplankton samples shows that diversity is the best predictor for the resource use

efficiency (and thereby carbon production) and the stability of the resource use efficiency in

phytoplankton communities (Ptacnik et al. 2008). Consequences of these findings are that in less

diverse communities resources may be more easily monopolized by bloom forming species and that

phytoplankton – zooplankton interactions are less stable, possibly hampering trophic transfer

(Ptacnik et al. 2008). Based on data from experiments with natural algal communities from 46 lakes

and 30 laboratory cultures we demonstrated experimentally that the efficiency of using the resource

light, the carbon production and the biomass composition (carbon to nutrient ratio) of freshwater

phytoplankton communities is indeed related to diversity (Striebel et al. 2009a, 2009b). The carbon

to nutrient ratio of phytoplankton in turn is an important parameter determining nutrient recycling,

transfer efficiency between phytoplankton and zooplankton, stability of phytoplankton -

zooplankton interactions and diversity of zooplankton communities (Urabe & Sterner 1996; Sterner

et al. 1997; Urabe et al. 2002). Therefore, disturbance mediated effects of diversity on resource use

and biomass stoichiometry of phytoplankton communities can have major impacts on the

functioning of the entire pelagic ecosystem.

We proposed to analyze the above described un-investigated links between disturbances of water

column stratification and diversity and its consequences for marine plankton dynamics in a gradient

of disturbances at different nutrient supply rates in a large scale mesocosm experiment. We

hypothesized that experimental disturbances of water column stratification will have consequences

for phytoplankton diversity and thereby affect the resource use efficiency and carbon production of

phytoplankton and phytoplankton – zooplankton interactions.

The objectives of our study were as follows:

1) To analyze the relationship between disturbance of water column stratification and

phytoplankton diversity

The relationship between water column stratification, rate of disturbance and phytoplankton

diversity has been studied to some detail in freshwater environments. However, there is a

considerable lack of evidence for marine environments. Closing this gap of knowledge will allow

generalizing possible relationships between stratification disturbances and phytoplankton diversity

in pelagic environments.

2) To analyze the relationship between phytoplankton diversity and diversity dependent resource

use efficiency, the stability of resource use efficiency and carbon production

Data from meta-analyses and experiments clearly demonstrate that species diversity is one of the

best predictors of the resource use efficiency and the carbon dynamics of phytoplankton

communities in freshwater and brackish environments. It is surprising that, despite the global

importance of marine phytoplankton (responsible for about 50% of global carbon production), the

relationship between phytoplankton diversity and carbon dynamics has not been investigated in

marine environments. Our experiments will result in a first data set showing how species diversity,

resource use efficiency and carbon production are linked within a marine phytoplankton

community.

3) To analyze the relationship between diversity dependent carbon dynamics of phytoplankton and

zooplankton growth

The carbon content and the carbon to nutrient ratio of phytoplankton biomass are most important

for zooplankton growth. In freshwater experiments it has been shown that phytoplankton diversity

influences carbon assimilation and nutrient uptake unequally. This results in phytoplankton

diversity dependent shifts in the carbon to nutrient ratio within phytoplankton biomass, influencing

phytoplankton food quality for zooplankton. We investigate the link between disturbances of the

water column, phytoplankton diversity and its consequences for zooplankton growth in a marine

pelagic community.

4) To analyze the relationship between disturbance and the growth and diversity of ciliates

Ciliates have population growth rates equaling or exceeding those of phytoplankton. As a result, the

response to disturbance of phytoplankton in ciliate-edible size classes may be masked by changes in

abundance and diversity of their ciliate grazers. Our experiments show how rapid changes in the

grazer community can influence the impact of disturbance on primary producers.

5) To analyze the relationship between disturbance of water column stratification and the

abundance and diversity of mixotrophic protists

The exact mechanisms controlling the abundance and diversity of mixotrophic protists and their

contribution as producers and consumers to the carbon flow are still poorly understood. Changes in

water column stratification and the resulting (hypothesized) abiotic and biotic changes are likely to

also affect the mixotrophs in the mesocosms. These direct and indirect effects were investigated in

our experiments.

References:

Connell, J. H. 1978. Diversity in tropical rain forests and coral reefs – high diversity of trees and

corals is maintained only in a non-equilibrium state. Science 199:1302-1310.

Diehl, S. 2002. Phytoplankton, light, and nutrients in a gradient of mixing depths: Theory. Ecology

83:386-398.

Diehl, S. 2007. Paradoxes of enrichment: Effects of increased light versus nutrient supply on

pelagic producer-grazer systems. The American Naturalist 169:E173-E191.

Diehl, S., S. Berger, R. Ptacnik, and A. Wild. 2002. Phytoplankton, light, and nutrients in a gradient

of mixing depths: Field experiments. Ecology 83:399-411.

Floder, S., and U. Sommer. 1999. Diversity in planktonic communities: An experimental test of the

intermediate disturbance hypothesis. Limnology and Oceanography 44:1114-1119.

Grime, J. P. 1973. Competitive exclusion in herbaceous vegetation. Nature 242:344-347.

Huston M. A. 1994. Biological Diversity: The Coexistence of Species on Changing Landscapes.

Cambridge University Press, Cambridge.

Jäger, C. G., S. Diehl, Schmidt, and M. G. 2008. Influence of water depth and mixing intensity on

phytoplankton biomass and functional community composition. Limnology and Oceanography

53:2361-2373.

Lampert W., and U. Sommer. 2007. Limnoecology., Second edition. Oxford University Press Inc.,

New York.

Moorthi, S. and U.-G. Berninger. 2006. Mixotrophic nanoflagellates in coastal sediments of the

western Baltic Sea. Aquatic Microbial Ecology 45:79-87.

Ptacnik, R., S. Diehl, and S. Berger. 2003. Performance of sinking and nonsinking phytoplankton

taxa in a gradient of mixing depths. Limnology and Oceanography 48:1903-1912.

Ptacnik, R., U. Sommer, T. Hansen, and V. Martens. 2004. Effects of microzooplankton and

mixotrophy in an experimental planktonic food web. Limnology and Oceanography 49:1435-1445.

Ptacnik, R., A. G. Solimini, T. Andersen, T. Tamminen, P. Brettum, L. Lepistö, E. Willén, and S.

Rekolainen. 2008. Diversity predicts stability and resource use efficiency in natural phytoplankton

communities. Proceedings of the National Academy of Sciences of the United States of America

105:5134-5138.

Sanders, R.W., U.-G. Berninger, E.L. Lim, P.F. Kemp, and D.A. Caron. D.A. 2000. Heterotrophic

and mixotrophic nanoplankton predation on picoplankton in the Sargasso Sea and on Georges Bank.

Marine Ecology Progress Series 192: 103-118.

Sommer, U., T. Hansen, O. Blum, N. Holzner, O. Vadstein, and H. Stibor. 2005. Copepod and

microzooplankton grazing in mesocosms fertilised with different Si : N ratios: no overlap between

food spectra and Si : N influence on zooplankton trophic level. Oecologia 142:274-283.

Sterner, R. W., J. J. Elser, E. J. Fee, S. J. Guildford, and T. H. Chrzanowski. 1997. The

light:nutrient ratio in lakes: The balance of energy and materials affects ecosystem structure and

process. American Naturalist 150:663-684.

Stibor, H., O. Vadstein, S. Diehl, A. Gelzleichter, T. Hansen, F. Hantzsche, A. Katechakis, B.

Lippert, K. Loseth, C. Peters, W. Roederer, M. Sandow, L. Sundt-Hansen, and Y. Olsen. 2004a.

Copepods act as a switch between alternative trophic cascades in marine pelagic food webs.

Ecology Letters 7:321-328.

Stibor, H., O. Vadstein, B. Lippert, W. Roederer, and Y. Olsen. 2004b. Calanoid copepods and

nutrient enrichment determine population dynamics of the appendicularian Oikopleura dioica: a

mesocosm experiment. Marine Ecology-Progress Series 270:209-215.

Stibor, H., A. Gelzleichter, F. Hantzsche, U. Sommer, M. Striebel, O. Vadstein, and Y. Olsen.

2006a. Combining dialysis and dilution techniques to estimate gross growth rate of phytoplankton

and grazing by micro- and mesozooplankton in situ. Archiv Fur Hydrobiologie 167:403-419.

Stibor, H., A. Gelzleichter, F. Hantzsche, U. Sommer, M. Striebel, O. Vadstein, and Y. Olsen.

2006b. Combining dialysis and dilution techniques to estimate gross growth rate of phytoplankton

and grazing by micro- and mesozooplankton in situ. Archiv Fur Hydrobiologie 167:403-419.

Striebel, M., S. Behl, S. Diehl, and H. Stibor. 2009a. Spectral niche complementarity and carbon

dynamics in pelagic ecosystems. The American Naturalist 174:141-147.

Striebel, M., S. Behl, and H. Stibor. 2009b. The coupling of biodiversity and productivity in

phytoplankton communities: Consequences for biomass stoichiometry. Ecology 90:2025-2031.

Urabe, J., and R. W. Sterner. 1996. Regulation of herbivore growth by the balance of light and

nutrients. Proceedings of the National Academy of Sciences of the United States of America

93:8465-8469.

Urabe, J., J. J. Elser, M. Kyle, T. Yoshida, T. Sekino, and Z. Kawabata. 2002. Herbivorous animals

can mitigate unfavourable ratios of energy and material supplies by enhancing nutrient recycling.

Ecology Letters 5:177-185.

Vadstein, O., H. Stibor, B. Lippert, K. Loseth, W. Roederer, L. Sundt-Hansen, and Y. Olsen. 2004.

Moderate increase in the biomass of omnivorous copepods may ease grazing control of planktonic

algae. Marine Ecology-Progress Series 270:199-207.

Wickham, S. A., S. Nagel, and H. Hillebrand. 2004. Control of epibenthic ciliate communities by

grazers and nutrients. Aquatic Microbial Ecology 35:153-162.

Wickham, S. A., and U. G. Berninger. 2007. Krill larvae, copepods and the microbial food web:

interactions during the Antarctic fall. Aquatic Microbial Ecology 46:1-13.

2. User-Project Achievements and difficulties encountered:

We studied the responses of a natural coastal phytoplankton community to manipulations of the

stratified water column. We installed 24 enclosures (10m depth) and disturbed the stratification of

the water column by artificially mixing the water column with a Secci-plate with different time

intervals (1-16 days). Undisturbed mesocosms (mixed every 32 days) acted as the least disturbed

mesocosms in the gradient. We performed the experiments at two nutrient levels, a un-fertilized

and a moderate supply level (0.5 µg P l-1

d-1

; Si:N:P 16:16:1) compared to the natural loading of the

system (Vadstein et al. 2004). We followed the response of phytoplankton, protist (ciliate and

flagellate) and zooplankton communities to stratification disturbances for about 4 weeks. We were

especially interested in the consequences of stratification disturbances for phytoplankton diversity

and thereby phytoplankton resource use efficiency and carbon dynamics.

3. Highlights important research results:

At the moment we are still analyzing samples, phytoplankton, ciliates, and zooplankton samples

that are very time-consuming. Thus, we hope that we will finish these analyses until the beginning

of 2010. Then we will be able to investigate the relationship between disturbance of water column

stratification and phytoplankton and ciliate diversity.

Additionally, we just finished the nutrient analysis (C, N, P) and after gaining the phytoplankton

and ciliate data we will be able to analyse the relationship between marine phytoplankton diversity

and diversity dependent resource use efficiency, the stability of resource use efficiency and carbon

production. Moreover, we will analyse the relationship between diversity dependent carbon

dynamics of phytoplankton and zooplankton growth and analyse the relationship between

disturbance and the growth and diversity of ciliates.

4. Publications, reports from the project:

Counting of plankton samples and final analyses of the results will need until beginning of 2010. A

first paper will be submitted at the end of 2009 year for the proceedings of the HYDRALAB II Joint

user meeting. Additionally, we plan to publish a first paper originating from the experiment within

one year after its completion (2010) in an international peer reviewed journal such as Limnology

and Oceanography or Marine Ecology Progress Series

Striebel M, Ptacnik R, Stibor H, Behl S, Berninger U, Haupt F, Hingsamer P, Mangold C,

Ptacnikova R, Steinböck M, Stockenreiter M, Wickham S, Wollrab S (2010) Water column

stratification, phytoplankton diversity and consequences for resource use and productivity.

Proceedings of the HYDRALAB III Joint User Meeting, Hannover, February 2010

5. Description:

5.1. Description:

Mesocosm experiments with natural algal communities

We studied the responses of a natural coastal phytoplankton community to manipulations of the

stratified water column. We installed 24 enclosures (10m depth) and disturbed the stratification

of the water column by artificially mixing the water column (with a Secci-plate) using different

time intervals (1-16 days). Undisturbed mesocosms (mixing after 32 days) acted as the least

disturbed mesocosms in the gradient. We performed the experiment at two nutrient levels,

unfertilized treatments and treatments with a moderate supply level (0.5 μg P l-1 d-1; Si:N:P

16:16:1) compared to the natural loading of the system (Vadstein et al. 2004). We followed the

response of phytoplankton, protist (ciliate and flagellate) and zooplankton communities to

stratification disturbances for about 4 weeks. We were especially interested in the consequences

of stratification disturbances for phytoplankton diversity and thereby phytoplankton resource use

efficiency and carbon dynamics. Measurements included phytoplankton, ciliate, and zooplankton

biomass, composition, and dynamics, nutrient dynamics, phytoplankton stoichiometry and

resource use efficiency.

Figur 5.1.1 Scheme of the experimental setup. Arrangement of mesocosms observed from the

raft. Red numbers display fertilized treatments.

Table 5.1.1 Summary of the treatments: mixing frequency, unfertilized, and fertilized treatments.

Analyses

Phytoplankton species composition, phytoplankton stoichiometry (particulate organic carbon

(POC) particulate organic nitrogen (PN) and particulate organic phosphorus (PP); filtration with

GF-F filters) and nutrients were analyzed at the start of the experiment and afterwards every

third day. Phytoplankton will be enumerated from samples fixed with Lugol’s iodine with an

inverted microscope using Utermöhl chambers until beginning of 2010. Phytoplankton

biovolume was determined during the experiment using a cell counter (Casy® Counter). Primary

productivity of the different phytoplankton communities was determined with the dialysis

method (see below). Detailed pigment analyses will be performed with HPLC (November-

December 2009) to see whether taxonomic diversity is coupled with pigment diversity

(functional diversity). Zooplankton and ciliate abundance and species composition and

zooplankton biomass composition (POC, PP, PN) was analysed every third day and samples will

be counted until January 2010.

Figure 5.1.3 Experimental setup: (1) daily mixing, (2) experimental setup, (3) daily mixing and

fertilization, and (4) raft with enclosures.

Figure 5.1.4 Enclosure with bottle for ciliate growth experiments (5) and setup for dialysis

experiments to determine phytoplankton primary production and loss rates (6).

Phytoplankton growth and loss rates

To estimate phytoplankton growth and loss rates (mainly grazing by micro- and

mesozooplankton), in situ, different techniques were developed within the last centuries.

Disadvantages of these techniques were their often complicated enforcement and the

neccessarity to use potential harmful substances such as radioactive tracers. Due to safety

regulations, it is not always possible to use such methods in the field. Additionally, radioactive

tracer methods do not allow quantifying grazing rates on individual phytoplankton groups or

species.

Thus, we used a modification of the dilution method and used dialysis bags to estimate growth

and loss rates of phytoplankton instead of non permeable glass bottles (Stibor et al. 2006b).

Dialysis membranes possess the advantage to be permeable for nutrients and thereby allow an in

situ estimation of phytoplankton gross growth rates. Dialysis bags also allow simultaneously the

estimation of microzooplankton grazing by dilution of plankton communities.

Bags with a volume of 250 ml were constructed using dialysis membrane tubes with a molecular

weight cut-off of 6000. This allowed diffusion of molecules smaller than proteins which

equilibrilate rapidly with ambient water. Dialysis tubes were hydrated by soaking them in

deionised water for 12 h prior to use. Dialysis cultures consisted of depth integrated samples

from fertilized enclosures. Samples were taken with a tube sampler and filtered through a 200

μm mesh to exclude macrozooplankton.

The original sample was diluted with GF/F filtered water from the same water body in 5 steps.

The share unfiltered water was 12.5 %, 25 %, 50 %, 75% and 87.5 %.

Figure 5.1.5 Scheme of the dilution steps for the experimental setup of dialysis experiments.

Samples were incubated for 48 hours and this incubation period resulted in a clear and

measurable growth response of phytoplankton in all experiments. After incubation, dialysis tubes

were opened and from sub samples chlorophyll-a concentration (using a fluorometer), cell

numbers, and total cell volume (using a Casy® Counter) were determined. Additionally 100 ml

sub-samples were fixed with Lugol’s iodine. These samples will be counted until beginning of

2010 according to Utermöhl’s inverted microscope technique (Utermöhl 1958). Net growth rates,

grazing rates by microzooplankton, and grazing rates by mesozooplankton will be calculated.

Figure 5.1.6 First results from biovolume data from the dialysis experiment (measured with the

Casy® Counter). A: Relationship between mixing intensity and phytoplankton growth in the

different treatments. B: Relationship between mixing intensity and micrograzing calculated after

Stibor et al. (2006).

Ciliate growth experiments

In order measure ciliate growth rates, water samples were taken from every mesocosm at the

surface (about 30 cm depth). Samples were filtered through 100 μm mesh to exclude

zooplankton. A starting sample (95 mL sample + 5 mL Bouins) was taken from every

mesocosm. The rest of the water was filled in a polycarbonate bottle (Nalgene, transparent with a

volume of 640 mL) and incubated in the mesocosm at a depth of 30 cm. After 24 hours the

bottles were taken out of the mesocosms and end samples were taken (95 mL sample + 5 mL

Bouins). The samples will be counted and determined under microscope and growth rates will be

calculated under the assumption of exponential growth.

The experiments will provide estimates of ciliate growth in the absence of predation. When

compared with ciliate growth rates in the mesocosms themselves, the effects of the experimental

manipulations on gross and net growth rates can be compared.

Lipid analysis

The FlowCAM® (Fluid Imaging, Portland) is a continuous imaging flow cytometer being used

for monitoring of microorganisms and particles in water. It combines microscopy, flow

cytometry, imaging and fluorescence technologies. A laser interacts with a high resolution digital

camera to capture images and data of passing cells or particles. It offers cell counts, size data,

pattern recognition, organism classification and image management. Hence, there are two

measurement modes can be used with the FlowCAM®: auto-trigger mode and fluorescence

mode.

To estimate the cell specific lipid content of marine phytoplankton we use the fluorescence

mode. For staining the algal cells we use the fluorescent lipophilic dye Nile Red with a shift of

emission from red to yellow. After staining 5ml algal sample with 20μl Nile Red solution

followed an incubation of 30min in the dark.

Fluorometric analysis ensued immediately with the FlowCAM® with an excitation wavelength

of 532nm and an emission wavelength of 645±20nm (green laser). In terms of the imaging

technology it is feasible getting images and the information of fluorescence of each detected cell.

Thus, it is possible to estimate the lipid content of each algal cell even in diverse communities.

5.2. Definition of the coordinate systems used:

5.3. Instruments used:

5.4. Definition of time origin and instrument synchronisation:

6. Definition and notation of the experimental parameters:

6.1. Fixed parameters:

For definition of parameters see part 5.1

6.2. Variable independent parameters:

Notation Name Unit Definition Remarks

Table 6.2.1

6.3. Derived parameters and relevant non-dimensional numbers:

Notation Name Unit Definition Remarks

Table 6.3.1

7. Description of the experimental campaign, list of experiments:

Experiment Name Experiment Date Remarks

Table 7.1

8. Data processing:

All analysis will be done until the beginning of 2010 and all data will be collected by the group

leader.

We will obtain data from nutrient analysis, HPLC, lipid measurements, phytoplankton composition

and biomass, ciliate composition and biomass, zooplankton composition and biomass and data

gained from the dialysis experiment with phytoplankton and growth data from the experiments with

ciliates.

9. Organisation of data files:

Data will be stored as:

Exel files: nutrient data, HPLC data, lipid (FlowCAM®) measurements, and for Casy® Counter

measurements.

Exel files: Phytoplankton, ciliate, and zooplankton counting’s.

Photos of the experimental setup.

Exel files for additional experiments (3 dialysis experiments and cilate growth experiments).

Word files: documentation and reports.

10. Remarks about the experimental campaign, problems and things to improve:

Everything was very good and there are no remarks concerning the experimental facility and the

assistance was perfect. The experimental setup was proven and everything necessary was on site or

organized quickly.

The disadvantage of such a large-scale experiment is that a lot of samples have to be analyzed after

the experiment and that these analyses are very time-consuming. That’s the reason why at the

present moment we are not able to present clear result and we just can show preliminary results.

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