INTEGRATED INTERPRETATION OF SURVEY AND EXPERIMENTAL 

APPROACHES FOR DETERMINING NUTRIENT THRESHOLDS FOR 

MACROALGAE IN FLORIDA SPRINGS

LABORATORY EXPERIMENTS AND DISTURBANCE STUDY 

DELIVERABLES FOR TASKS 2.1-2.8 

DEP CONTRACT NUMBER S0291 

 

SUBMITTED TO THE FLORIDA DEPARTMENT OF ENVIRONMENTAL 

PROTECTION 

October 31, 2007 

AUTHORS: 

AGNIESZKA PINOWSKA 

R. JAN STEVENSON 

JAMES O. SICKMAN 

ANDREA ALBERTIN 

MARTIN ANDERSON 
2

Integrated interpretation of survey and experimental approaches for determining 

nutrient thresholds for macroalgae in Florida springs. 

Description of deliverables for Task 2.1-2.8 

Task 2.1-2.3 

The deliverable for this task consists of 2 papers: one on Lyngbya wollei and one on 

Vaucheria sp. The papers describe the results of laboratory experiments on the light, 

conductivity and microelement requirements of the two taxa. 

Effects of light, conductivity and microelements on the growth of Lyngbya wollei.

Effects of light, conductivity and microelements on the growth of Vaucheria sp. 

Task 2.4 

The deliverable consists of a short description of the results of field experiments on the 

recovery of mats of Lyngbya wollei and Vaucheria sp. after complete biomass removal. 

Recovery of filamentous algal mats of Lyngbya wollei and Vaucheria sp. after 

disturbance. 

Task 2.5-2.8 

The deliverable for this task consists of 2 papers: one on Lyngbya wollei and one on 

Vaucheria sp. The papers describe the results of laboratory experiments on the effects of 
3

nitrogen (in the form of nitrate and ammonia) and phosphorus on the growth of the two 

taxa. 

Differential effect of PO4, NO3 and NH4 on the growth of Lyngbya wollei

Differential effect of PO4, NO3 and NH4 on the growth of Vaucheria sp.

In the Vaucheria sp. paper, not all of the results from the laboratory experiments 

conducted in small microcosms were included. Vaucheria sp. did not respond well to the 

handling procedure we originally used. In some of the experiments we observed a large 

variability within our data, and we did not observe any effects of the experimental 

treatments. When cutting off tips of Vaucheria sp., it is necessary to observe whether the 

protoplast was damaged in the process. It often can be seen under the dissecting scope 

when the tip is cut off. Our final solution to this concern was to cut tips off 2 days before 

the experiment and only use tips that were still healthy 48 hours later. The quality of the 

algal mat used for the experiments was crucial. If the Vaucheria sp. collected was 

healthy and vigorously growing in the field and sent to us within 24 hours from collection 

following the protocol that we developed, we were very successful with the experiments. 

All mats that I personally collected resulted in healthy growing tips for the experiments 

and good experimental results. Lyngbya wollei filaments have thick cell walls and can 

take more abuse than filaments of Vaucheria sp. 
4

A protocol for collection of Vaucheria sp. for use in experiments 

A kit to collect live Vaucheria sp. consists of a cooler, two ice packs and two 1 gallon 

Ziploc® bags. A mat that is intensively growing, has a bright green color, and is free of 

debris, sediments and invertebrates should be selected for collection. A fragment of a 

mat should be gently detached and rinsed in the site water by shaking while submersed. 

A 1 gallon bag should be filled with the site water and a well rinsed mat should be placed 

inside. The mat should have plenty of water and should not fill more than half of the bag 

when it returns to its original volume, leaving half of the bag filled just with the site water. 

The first bag should be placed inside the second bag, sealed and placed on an ice pack in 

a cooler and covered with an ice pack. If there is any empty space left, it should be filled 

with bubble wrap to make sure nothing is loose inside the cooler. The lid should be taped 

and sealed to the cooler using duct tape. The cooler should be shipped overnight and 

received within 24 hours from collection to assure that the algae will be alive and 

growing. Upon receipt of the shipment, the bag with algae should be taken out of the 

cooler and left on the counter for 2-3 hours until its temperature adjusts to room 

temperature. Then the algae can be examined, any debris should be removed, and the 

algae can be transferred to the growth media. The growth medium used to maintain fresh 

collections is a Z8Fl Fe200 medium modified to reflect the median chemistry of fresh 

water in Florida springs with reduced N and P concentration (Appendix 1). 
5

Effects of light, conductivity and microelements on the growth of Lyngbya wollei. 

Introduction 

Most of the algae nutrition studies focus on the most important macronutrients: nitrogen 

and phosphorus. In the case of Lyngbya wollei, a cyanobacterium forming nuisance mats 

in lakes, ponds, rivers, streams and springs, studies have focused on the effects of 

nitrogen, phosphorus, salinity and light (Turner 1990, Speziale and Dyck 1992, Cowell 

and Botts 1994, Yin et al. 1997, Cowell and Dawes 2004). None of the studies looked at 

growth at very low light levels and at growth in different conductivity water (at the levels 

found in fresh water springs). There also are no studies on the effects of iron and 

micronutrients on the growth of L. wollei. The growth media used in other studies were 

BG11, Z8 and LM6E. Most of these media were developed to sustain algal growth in 

long-term batch cultures, however, not to optimize the short term growth. In this study 

we developed a new medium based on the Z8 medium that reflects the median chemistry 

of freshwater Florida springs. We also tested a new microcosm system for the growth of 

filamentous algae consisting of polyethylene microcentrifuge tubes. 

The objectives of this study were: (i) to compare L. wollei growth rates in natural spring 

water to the ones in the growth medium and to test whether single or multiple filaments 

should be used while growing algae in microcentrifuge tubes, (ii) to investigate the 

growth of L. wollei at different levels of water conductivity, (iii) to investigate the growth 

of L. wollei under different light levels, (iv) to study the growth of L. wollei in media with 

different iron concentrations and (v) to compare the growth of L. wollei in the media with 

and without the addition of micronutrients. 
6

Materials and methods 

Five experiments were conducted using small algal microcosms (Table 1). The goal of 

any experiment investigating the effects of nutrients on algal growth is to achieve high 

replication, to test as many nutrient levels as possible, and to grow algae in a continuous 

culture with constant nutrient levels. To achieve high replication and a large number of 

treatments, we used microcentrifuge tubes as microcosms in which to grow algae. To 

achieve semi-continuous culture conditions, we kept the ratio between the algal 

biovolume and the volume of the growth medium very low, and we frequently changed 

growth media. 

Experimental setup 

Filaments of Lyngbya wollei were grown in 1.5 ml sterile microcentrifuge tubes filled 

with 1 ml of growth media. Growth media were changed every 48 hours. Racks made of 

clear polyethylene were placed on an orbital shaker (60 RPM). Microcentrifuge tubes 

with L. wollei were incubated under grow lights providing 25 μmol/m2

/s of light with the 

exception of the light gradient experiment. The unobstructed grow lights provided 250 

μmol/m2

/s, thus, the desired light intensity was obtained by covering the racks with a 

neutral density film. The initial filament length was 1-2 mm. The filaments were 

photographed using a digital video camera system installed on a Leica MZ12.5 

Stereomicroscope under 8x magnification at the beginning and at the end of each 

experiment. Filament length was measured on the digital images using Image J software 

(Rasband 2003). Incubation time was 11 or 12 days. Each treatment was replicated 10 
7

times. Since some of the filaments were lost during media changes, the final number of 

replicates used for the data analyses was lower than set at the beginning of the 

experiment. 

All experiments had a complete factorial ANOVA design with 1 or 2 factors. Experiment 

1 had a 2 factor design with 3 media treatments (spring water from Alexander, spring 

water from Silver Glen and Z8Fl medium) and 2 algal biomass treatments (1 and 5 

filaments of L. wollei in each microcentrifuge tube). Due to an error in preparation of the 

Z8Fl medium for this experiment, no nitrate was added to the medium. Experiment 2 had 

a 1 factor design with 5 conductivity treatments (100, 300, 500, 1000 and 3000 μS/cm). 

The desired water conductivity was obtained by a combination of salts reflecting the 

chemistry of spring water with different conductivity levels (Table 2). Experiment 3 had 

a 2 factor design with 15 treatments: a combination of 3 conductivity levels (100, 300, 

1000 μS/cm) and 5 light intensities (1, 2.5, 5, 25, 250 μmol/m2

/s). Experiment 4 had 2 

treatments: a growth medium with and without the addition of microelements. 

Experiment 5 had a 1 factor design, with 4 iron concentrations (0, 20, 200, 600 μg Fe/L). 

If not stated differently, all treatments had the same concentration of microelements, Fe, 

N, P, Ca, Mg, CO3 as in the standard Z8Fl medium (Appendix 1). 

Growth media 

A new growth medium was developed based on the Z8 medium (Kotai 1972). The Z8 

medium was modified to simulate the median chemistry of macronutrients in Florida 

spring water (referred to as medium Z8Fl) (Appendix 1). All growth media were 

autoclaved or filter sterilized. 
8

Water analyses 

Ammonia nitrogen, Kjeldahl nitrogen, nitrite-nitrate nitrogen and total phosphorus 

concentrations were analyzed in the prepared growth media by FDEP (Table 3). A single 

sample of each growth medium was sent for the analyses. When the concentration of a 

compound was below the detection limit of the laboratory method, the method’s 

detection limit is reported (Table 4). None of the water analyses results were designated 

as Q or Y. Total nitrogen was calculated as a sum of nitrite-nitrate nitrogen (nitrates) and 

Kjeldahl nitrogen. Water conductivity was measured using YSI 556 MSP. 

Experimental conditions 

All experiments were conducted in the walk-in growth room. The temperature in the 

growth room was set for 22.5oC to reflect the average water temperature of the Florida 

springs. The minimum and maximum temperatures were recorded daily on a max-min 

thermometer. 

Relative growth rates 

Algal relative growth rate (RGR) in the small microcosm experiments was calculated 

using the following formula (Hunt 1990): 

Data analyses 

Data were analyzed using R statistical software (R Development Core Team 2006). 

Analysis of variance was conducted using a general linear model with car package. If 

# of days

ln(Final Length) ln(Initial Length) RGR = −
9

necessary, data were square root or 1/square root transformed to meet the assumptions of 

normality and variance homogeneity. 

Results 

Experiment 1 - growth of L. wollei in spring water and in growth media 

Both growth media and the number of filaments in the microcosm affected the growth 

rate of L. wollei (ANOVA for medium effect p<0.026 and for number of filaments effect 

p<0.022) (Fig. 1). When 5 filaments were present in the microcosm, their growth rates 

were lower than in the microcosms with 1 filament. Overall, the growth of L. wollei was 

affected by the nitrate concentration in the water (Table 5). Due to an error in the 

preparation of the Z8Fl medium for this experiment, we were not able to truly test the 

medium in comparison to spring water, but in later experiments using the Z8Fl medium, 

we observed growth rates higher than the ones in spring water in this experiment. 

Experiment 2 - growth of L. wollei in water with different conductivity 

Lyngbya wollei grew well in water with conductivity from 100 to 1000 μS/cm. Its 

growth was reduced at 3000 μS/cm (ANOVA for conductivity effect p<0.022) (Fig. 2). 

Actual conductivities measured in the treatments were: 105, 331, 516, 963 and 2942 

μS/cm. All treatments had the same nitrogen and phosphorus concentrations, indicating 

that the observed growth differences were the result of different conductivity levels in the 

growth media (Table 5). 
10

Experiment 3 -growth of L. wollei under different light levels and water conductivities 

Both light and conductivity affected the growth rates of L. wollei (ANOVA for light 

effect p<0.001; for conductivity effect p<0.040 and for interaction light*conductivity 

p<0.004). Lyngbya wollei grew even at very low light levels, but it had the highest 

growth rates at a light intensity of 25 μmol/m2

/s or higher (Fig. 3). Only at the lowest 

light level (1 μmol/m2

/s) water conductivity had an effect on the growth rates of L. wollei

and at that light level filaments in 100 μS/cm conductivity water grew better than 

filaments in 1000 μS/cm conductivity water (TukeyHSD p<0.010). 

Experiment 4 - growth of L. wollei in the media with and without micronutrients added 

Surprisingly, addition of microelements to the growth media resulted in reduced growth 

rates (ANOVA for micronutrient effect p<0.001) (Fig. 4). The Gaffron’s micronutrient 

mix used in the Z8 medium has relatively low micronutrient concentrations compared to 

other freshwater growth media. There was no difference in the nitrogen and phosphorus 

concentration between the different growth media (Table 5). 

Experiment 5 - growth of L. wollei in different iron concentrations 

Iron is an important micronutrient for the growth of L. wollei. (ANOVA for the iron 

effect p<0.001) (Fig. 5). When no iron was added to the growth media, very low growth 

rates of L. wollei were observed. Surprisingly, an iron concentration of 600 μg/L, found 

in the standard Z8 medium, had a negative effect on the growth of L. wollei. High 

growth rates were observed at 20 and 200 μg Fe/L. There were no differences in the 

nitrogen and phosphorus concentrations between the different growth media (Table 5). 
11

Discussion 

Lyngbya wollei is clearly a freshwater species, since it did not grow well in high 

conductivity water (Fig. 2). Speziale and Dyck (1992) and Cowell and Botts (1994) also 

observed reduced growth rates and loss of pigment when L. wollei was grown in growth 

media to which salt or sea water had been added . Lyngbya wollei grew well at low light 

levels (Fig.3), as also described by Turner (1990) and Yin et al. (1997). It did not 

respond well to the addition of microelements and to a high concentration of iron in the 

growth media (600 μg Fe/L) (Fig. 5). This is opposite to Lyngbya majuscula, which has 

a very high iron requirement, 1400-6000 μg/L (Gross and Martin 1996). Microcentrifuge 

tubes used as microcosms for the growth of algal filaments worked very well, and using 

one 1-2 mm long filament worked better then using multiple filaments. Even though all 

chemicals used to prepare media were ACS certified, they have microelements in them as 

contaminants, and these are probably sufficient for L. wollei growth. Further study on the 

effects of particular microelements is needed to determine which micronutrient in 

Gaffron’s mix is causing the reduction of growth rates. When conducting experimental 

work on L. wollei, growth media with reduced iron and micronutrient concentrations 

should be used as proposed in Appendix 1. 

References 

Cowell, B. C., and P. S. Botts. 1994. Factors Influencing the Distribution, Abundance and 

Growth of Lyngbya-Wollei in Central Florida. Aquatic Botany 49:1-17. 

Cowell, B. C., and C. J. Dawes. 2004. Growth and nitrate-nitrogen uptake by the 

cyanobacterium Lyngbya wollei. Journal of Aquatic Plant Management 42:69-71. 

Gross, E. D., and D. F. Martin. 1996. Iron dependence of Lyngbya majuscula. Journal of 

Aquatic Plant Management 34:17-20. 

Hunt, R. 1990. Basic growth analysis. Unvwin Hyman Ltd., London. 
12

Kotai, J. 1972. Instructions for preparation of modified nutrient solution Z8 for algae. 

Norwegian Institute for Water Research, publication B-11/69. Blindern, Oslo. 

R Development Core Team. 2006. R: a language and environment for statistical 

computing. Vienna, Austria. 

Rasband, W. 2003. ImageJ v 1.61. National Institutes of Health, Bethesda, Maryland. 

Speziale, B. J., and L. A. Dyck. 1992. Lyngbya infestations: comparative taxonomy of 

Lyngbya wollei comb. nov. (Cyanobacteria). Journal of Phycology 28:693-706. 

Stevenson, R. J., A. Pinowska, and Y. K. Wang. 2004. Ecological conditions of algae and 

nutrients in Florida springs. Final report. Florida Department of Environmental 

Protection contract number WM858, Michigan State University, East Lansing, MI. 

Turner, G. 1990. Studies on the biology of Lyngbya wollei. Master's Thesis. Clemson 

University, South Carolina. 

Yin, Q. Q., W. W. Carmichael, and W. R. Evans. 1997. Factors influencing growth and 

toxin production by cultures of the freshwater cyanobacterium Lyngbya wollei 

Farlow ex Gomont. Journal of Applied Phycology 9:55-63. 
13

Fig. 1 

Box plot showing relative growth rates (RGR) or L. wollei in a factorial mesocosm 

experiment with 3 growth media (spring water from Alexander, spring water from Silver 

Glen and Z8Fl growth medium but with very low nitrogen and phosphorus content) and 2 

biomass levels: 1 or 5 filaments (n=57). 
14

Fig. 2 

Box plots showing relative growth rates (RGR) of L. wollei in different conductivity 

water (n=45). Boxes sharing the same letter do not differ (Tukey’s test p<0.05). 
15

Fig. 3 

Box plots showing relative growth rates (RGR) in a factorial mesocosm experiment with 

5 light levels and 3 conductivity levels (n=121). 
16

Fig. 4 

Box plots showing relative growth rates (RGR) L. wollei in growth media with and 

without micronutrients added (n=17). 
17

Fig. 5 

Box plot showing relative growth rates (RGR) of L. wollei in 4 iron concentrations 

(n=37). Boxes sharing the same letter do not differ (Tukey’s test p<0.05). 
18

Table 1 

Lyngbya wollei experiments. Experiment numbers in parenthesis refer to numbers used in 

the 2004 report (Stevenson et al. 2004). 

Experiment 

(project 

experiment 

number) 

Treatments Algae 

collection 

location 

Season Growth 

medium 

Mean min and 

max 

temperature 

(oC) 

1 (6) 

2 (13) 

3 (13) 

4 (14) 

5 (14) 

Spring water, media and number 

of filaments in the tube 

Conductivity 

Light and conductivity 

Microelements 

Iron 

Ichetucknee 

Ichetucknee 

Ichetucknee 

Ichetucknee 

Ichetucknee 

Summer 

Summer 

Summer 

Summer 

Summer 

Z8Fl 

Z8Fl 

Z8Fl 

Z8Fl 

Z8Fl 

20.6 & 24.9 

20.4 & 24.8 

20.4 & 24.8 

20.6 & 24.8 

20.6 & 24.8 

Table 2 

Chemical composition of a component of growth media in experiments 2 and 3 

responsible for desired conductivity in the medium. 

Conductivity 

(μS/cm) 

CaCl2·2H2O 

(mM) 

MgSO4·7H2O 

(mM) 

Na2CO3

(mM) 

KCl 

(mM) 

NaCl 

(mM) 

100 

300 

500 

1000 

3000 

0.116 

0.496 

0.747 

1.618 

2.739 

0.101 

0.203 

0.284 

0.284 

0.284 

0.198 

0.792 

1.293 

1.293 

1.293 

0 

0 

0 

0.123 

0.875 

0 

0 

0 

0.123 

0.875 

Table 3 

Methods used for analyses of water samples. 

Parameter Method Description 

Ammonia-N EPA 350.1 (1983) Ammonia in aquaeous matrices as mg N/L 

NO2NO3-N EPA 353.2 (1983) Nitrite/Nitrate in aqueous matrices as mg N/L 

N_KJEL_TOT EPA 351.2 (1983) Total Kjeldahl Nitrogen in aqueous matrices 

Total-P EPA 365.4 Total Phosphorus in aqueous matrices 
19

Table 4 

Detection limits of water chemical analyses. When the concentration of a compound was 

below the detection limit of the laboratory method, the method detection limit is reported. 

Compound Detection limit (mg/L)

Ammonia nitrogen 0.010 

Total Kjeldahl nitrogen 0.060 

Nitrates 0.004 

Total phosphorus 0.004 

 Table 5 

Measured concentration of nitrate, ammonia, total nitrogen and total phosphorus in the 

growth media used in the experiments. 

Treatments NH4-N (μg/L) NO3-N (μg/L) TN (μg/L) TP (μg/L) 

Experiment 1: 

 Alexander spring water 

 Silver Glen spring water 

 Z8Fl 

Experiment 2 – conductivity: 

 100 μS/cm 

 300 μS/cm 

 500 μS/cm 

 1000 μS/cm 

 3000 μS/cm 

Experiment 4 – microelements: 

 not added 

 added 

Experiment 5 – Fe: 

 0 μg/L 

 20 μg/L 

 200 μg/L 

 600 μg/L 

22 

13 

<10 

<10 

18 

<10 

<10 

11 

<10 

13 

18 

16 

17 

16 

53 

19 

6 

1000 

1000 

1000 

990 

990 

1100 

1000 

1000 

1000 

1000 

1000 

220 

180 

270 

1360 

1350 

1360 

1320 

1370 

1370 

1200 

1120 

1190 

1240 

1220 

41 

24 

42 

94 

74 

73 

77 

69 

110 

100 

95 

94 

80 

110 
20

Effects of light, conductivity and microelements on the growth of Vaucheria sp. 

Introduction 

Vaucheria sp. (Xanthophyce) is a common filamentous mat-forming species in 

streams, rivers and lakes (Entwisle 1990, McIntire et al. 1994, Necchi et al. 1994). There 

are many studies on the ecological and environmental requirements of Vaucheria sp. 

(Lakatos 1978, Gómez et al. 1994, Aboal et al. 1996). Many species of Vaucheria show 

high tolerance to different water salinities (Moreno et al. 2001), although they do prefer 

sites with high light availability (Ensminger et al. 2005) (Leukart and Hanelt 1995). 

Vaucheria sp. is also commonly used in studies on cell structure (Kataoka and Watanabe 

1993, Tornbom and Oliveira 1993, Raven and Brownlee 2001, Takahashi et al. 2001). 

However, there are very few laboratory studies on the nutrition requirements of

Vaucheria sp., and these studies focus on macronutrients such as nitrogen and 

phosphorus (Sudlow 1936, Ozimek et al. 1991). 

The objectives of this study were: (i) to compare Vaucheria sp. growth rates in 

natural spring water to the ones in the growth medium and to test whether single or 

multiple filaments should be used while growing algae in microcentrifuge tubes, (ii) to 

investigate the growth of Vaucheria sp. at different levels of water conductivity, (iii) to 

investigate the growth of Vaucheria sp. under different light levels, (iv) to study the 

growth of Vaucheria sp. in media with different iron concentrations and (v) to compare 

the growth of Vaucheria sp. in media with and without the addition of micronutrients. 
21

Materials and methods 

Five experiments were conducted using small algal microcosms (Table 1). The goal of 

any experiment investigating the effects of nutrients on algal growth is to achieve high 

replication, to test as many nutrient levels as possible, and to grow algae in a continuous 

culture with constant nutrient levels. To achieve high replication and a large number of 

treatments, we used microcentrifuge tubes as microcosms in which to grow algae. To 

achieve semi-continuous culture conditions, we kept the ratio between the algal 

biovolume and the volume of the growth medium very low, and we frequently changed 

growth media. 

Experimental setup 

Filaments of Vaucheria sp. were grown in 1.5 ml sterile microcentrifuge tubes filled with 

1 ml of growth media. Growth media were changed every 48 hours. Racks made of 

clear polyethylene were placed on an orbital shaker (60 RPM). Microcentrifuge tubes 

with Vaucheria sp. were incubated under grow lights providing 25 μmol/m2

/s of light, 

with the exception of the light gradient experiment. The unobstructed grow lights 

provided 250 μmol/m2

/s, thus, the desired light intensity was obtained by covering the 

racks with a neutral density film. The initial filament length was 1-2mm. The filaments 

were photographed using a digital video camera system installed on a Leica MZ12.5 

Stereomicroscope under 8x magnification at the beginning and at the end of each 

experiment. Filament length was measured on the digital images using Image J software 

(Rasband 2003). Incubation time was 11 or 12 days. Each treatment was replicated 10 

times. Since some of the filaments were lost during media changes, the final number of 
22

replicates used for the data analyses was lower then set at the beginning of the 

experiment. 

All experiments had a complete factorial ANOVA design with 1 or 2 factors. 

Experiment 1 had a 2 factor design with 3 media treatments (spring water from 

Alexander, spring water from Silver Glen and Z8Fl medium) and 2 algal biomass 

treatments (1 and 5 filaments of Vaucheria sp. in each microcentrifuge tube). Due to an 

error in preparation of the Z8Fl medium for this experiment, no nitrate was added to the 

medium. Experiment 2 had a 1 factor design with 5 conductivity treatments (100, 300, 

500, 1000 and 3000 μS/cm). The desired water conductivity was obtained by a 

combination of salts reflecting the chemistry of spring water with different conductivity 

levels (Table 2). Experiment 3 had a 2 factor design with 15 treatments: a combination 

of 3 conductivity levels (100, 300, 1000 μS/cm) and 5 light intensities (1, 2.5, 5, 25, 250 

μmol/m2

/s). Experiment 4 had 2 treatments: a growth medium with and without the 

addition of microelements. Experiment 5 had a 1 factor design, with 4 iron 

concentrations (0, 20, 200, 600 μg Fe/L). If not stated differently, all treatments had the 

same concentration of microelements, Fe, N, P, Ca, Mg, CO3 as in the standard Z8Fl 

medium (Appendix 1). 

Growth media 

A new growth medium was developed based on the Z8 medium (Kotai 1972). The Z8 

medium was modified to simulate the median chemistry of macronutrients in Florida 

spring water (referred to as medium Z8Fl) (Appendix 1). All growth media were 

autoclaved or filter sterilized. 
23

Water analyses 

Ammonia nitrogen, Kjeldahl nitrogen, nitrite-nitrate nitrogen and total phosphorus 

concentrations were analyzed in the prepared growth media by FDEP (Table 3). A single 

sample of each growth medium was sent for the analyses. When the concentration of a 

compound was below the detection limit of the laboratory method, the method’s 

detection limit is reported (Table 4). None of the water analyses results were designated 

as Q or Y. Total nitrogen was calculated as a sum of nitrite-nitrate nitrogen (nitrates) and 

Kjeldahl nitrogen. Water conductivity was measured using YSI 556 MSP. 

Experimental conditions 

All experiments were conducted in the walk-in grow room. The temperature in the grow 

room was set for 22.5oC to reflect the average water temperature of the Florida springs. 

The minimum and maximum temperatures were recorded daily on a max-min 

thermometer. 

Relative growth rates 

Algal relative growth rate (RGR) in the small microcosm experiments was calculated 

using the following formula (Hunt 1990): 

Identification of Vaucheria species 

Since the presence of reproductive structures is necessary to identify the species of 

Vaucheria, we incubated a small fragment of the mat (Ott and Oldham-Ott 2003). The 

# of days

ln(Final Length) ln(Initial Length) RGR = −
24

mat fragment was placed onto a Petri dish filled with Z8Fl growth medium with 100 μg/L 

P and 1000 μg/L N and placed by the window. We were successful in observing 

reproductive structures in the samples collected from Manatee spring. The species was 

Vaucheria geminata (Prescott 1982). 

Data analyses 

Data were analyzed using R statistical software (R Development Core Team 2006). 

Analysis of variance was conducted using a general linear model with car package. If 

necessary, data were square root or 1/square root transformed to meet the assumptions of 

normality and variance homogeneity. 

Results 

Experiment 1 - growth of Vaucheria sp. in spring water and in growth media 

Neither the growth media nor the number of filaments in the microcosm had an effect on 

the growth rate of Vaucheria sp. (ANOVA for medium effect p<0.091 and for number of 

filaments effect p<0.622) (Fig. 1). Due to an error in the preparation of the Z8Fl medium 

for this experiment, we were not able to truly test the medium in comparison to spring 

water. In later experiments using the Z8Fl medium, however, we observed growth rates 

higher than the ones in spring water in Experiment 1. 

Experiment 2 - growth of Vaucheria sp. in water with different conductivity 

Vaucheria sp. grew well in water with conductivity at 100, 300 and 1000 μS/cm, but its 

growth was reduced in water with conductivity at 500 and 3000 μS/cm (ANOVA for 
25

conductivity effect p<0.016) (Fig. 2). However, when the means were compared using 

the Tukey HSD test, none of the differences among the means was significant at p=0.05. 

At the levels of conductivity tested, the effect of conductivity on growth of Vaucheria sp. 

was indefinite. Actual conductivities measured in the treatments were: 105, 331, 516, 

963 and 2942 μS/cm. All treatments had the same nitrogen concentrations and the same 

phosphorus concentrations, indicating that the observed growth differences resulted from 

different conductivity levels in the growth media (Table 5). 

Experiment 3 -growth of Vaucheria sp. under different light levels and water 

conductivities 

Light affected the growth rates of Vaucheria sp. and conductivity did not (ANOVA for 

light effect p<0.001; for conductivity effect p<0.657 and for interaction 

light*conductivity p<0.046). Vaucheria sp. grew even at very low light levels, but the 

growth rates were very low (Fig. 3). The highest growth rates were observed at a light 

intensity of 25 μmol/m2

/s or higher. 

Experiment 4 - growth of Vaucheria sp. in the media with and without micronutrients 

added 

The addition of microelements to the growth media had no effect on the growth rates of 

Vaucheria sp. (ANOVA for micronutrient effect p<0.382) (Fig. 4). There was no 

difference in the nitrogen and phosphorus concentration in the growth media (Table 5). 

Experiment 5 - growth of Vaucheria sp. in different iron concentrations 

Iron is an important micronutrient for the growth of Vaucheria sp. (ANOVA for the iron 

effect p<0.001) (Fig. 5). When no iron was added to the growth media and when the iron 
26

concentration in the media was 20 μg/L, very low growth rates of Vaucheria sp. were 

observed. Surprisingly, the iron concentration of 600 μg/L found in the standard Z8 

medium had a negative effect on the growth of Vaucheria sp. High growth rates were 

observed at 200 μg Fe/L. There were no differences in the nitrogen and phosphorus 

concentrations measured in the growth media (Table 5). 

Discussion 

Vaucheria sp. had comparable growth rates in spring water and in the artificial 

growth medium, and there were no differences in the growth rate between 1 and 5 

filaments incubated in 1 microcentrifuge tube (Fig. 1). We also did not observe a trend in 

the response of Vaucheria sp. to different conductivities of water (Fig. 2). Many species 

of Vaucheria are adapted to changes in water conductivity and are found from fresh water 

to marine environments ( Moreno et al. 2001, Johanson 2005). Vaucheria sp. did not 

grow well at very low light levels, 1 and 2.5 μmol/m2

/s. The highest growth rates were 

found at a light intensity of 25 μmol/m2/s. In the streams, Vaucheria sp. prefers areas 

well exposed to light and does not adapt to low light levels (Ensminger et al. 2005). We 

did not observe a difference in the growth rate of Vaucheria sp. incubated in the growth 

media with or without the addition of micronutrients. Vaucheria sp. is tolerant to high 

levels of metals in the water, much higher than the concentrations used in our 

experiments (Pirszel et al. 1995, Skowronski et al. 1998, Alessa and Oliveira 2001). We 

were, however, surprised that it did not prefer the media with added micronutrients. The 

optimum iron concentration for the growth of Vaucheria sp. was 200 μg/L. It did not 

grow well in the iron concentration of 600 μg/L found in the Z8 growth medium. 
27

In our experiments, Vaucheria sp. showed a large variability of growth rates in all 

of the treatments. Also, in all of the experimental treatments, we found many filaments 

that did not grow at all (0 relative growth rate). This was due to the process of cutting 

short 1-2 mm tips of Vaucheria sp. for the experiments. Even though Vaucheria sp. is 

known for its ability to heal wounded areas, not all of the tips survived the process of 

being cut off. (Tornbom and Oliveira 1993) found that after excising a 3 mm long 

vegetative filament of Vaucheria longicaulis, the wound-healing process took several 

hours and new growth occurred 43 hours after wounding. Therefore, we changed our 

methodology in further experiments on Vaucheria sp. and incubated 1-2mm tips for 2 

days in the Z8Fl growth medium (Appendix 1) before using them in the experiments. 

References 

Aboal, M., M. Prefasi, and A. D. Asencio. 1996. The aquatic microphytes and 

macrophytes of the transvase Tajo-Segura irrigation system, southeastern Spain. 

Hydrobiologia 340:101-107. 

Alessa, L., and L. Oliveira. 2001. Aluminum toxicity studies in Vaucheria longicaulis var. 

macounii (Xanthophyta, Tribophyceae). I. Effects on cytoplasmic organization. 

Environmental and Experimental Botany 45:205-222. 

Ensminger, I., J. Foerster, C. Hagen, and W. Braune. 2005. Plasticity and acclimation to 

light reflected in temporal and spatial changes of small-scale macroalgal 

distribution in a stream. Journal of Experimental Botany 56:2047-2058. 

Entwisle, T. J. 1990. Macroalgae in the Upper Yarra and Watts River Catchments - 

Distribution and Phenology. Australian Journal of Marine and Freshwater 

Research 41:505-522. 

Gómez, R., M. R. Vidal-Abarca, and M. L. Suárez. 1994. Bioavailability of phosphorus 

in Ajauque Stream wetland (SE Spain). Verh. Internat. Verein. Limnol. 25:1357-

1360. 

Hunt, R. 1990. Basic growth analysis. Unvwin Hyman Ltd., London. 

Johanson, L. R. 2005. Phylum Xanthophyta (yellow-green algae). Pages 245-270 in D. M. 

John, B. A. Whitton, and A. J. Brook, editors. The freshwater algal flora of the 

British Isles. Cambridge University Press, Cambridge. 

Kataoka, H., and M. Watanabe. 1993. Negative Phototropism in Vaucheria-Terrestris 

Regulated by Calcium .3. The Role of Calcium Characterized by Use of a High-
28

Power Argon-Ion Laser as the Source of Unilateral Blue-Light. Plant and Cell 

Physiology 34:737-744. 

Kotai, J. 1972. Instructions for preparation of modified nutrient solution Z8 for algae. 

Norwegian Institute for Water Research, publication B-11/69, Blindern, Oslo. 

Lakatos, G. 1978. The phenomenon and significance of benthonic eutrophication in Lake 

Velencei, Hungary. Acta Biological Debrecina 15:147-168. 

Leukart, P., and D. Hanelt. 1995. Light requirements for photosynthesis and growth in 

several macroalgae from a small soft-water stream in the Spessart Mountains, 

Germany. Phycologia 34:528-532. 

McIntire, C. D., H. K. Phinney, G. L. Larson, and M. Buktenica. 1994. VerticalDistribution of a Deep-Water Moss and Associated Epiphytes in Crater Lake, 

Oregon. Northwest Science 68:11-21. 

Moreno, J. L., M. Aboal, M. R. Vidal-Abarca, and M. L. Suarez. 2001. Macroalgae and 

submerged macrophytes from fresh and saline waterbodies of ephemeral streams 

('ramblas') in semiarid south-eastern Spain. Marine and Freshwater Research 

52:891-905. 

Necchi, O., D. Pascoaloto, and L. H. Z. Branco. 1994. Distribution of Macroalgae in a 

Tropical River Basin from Southeastern Brazil. Archiv Fur Hydrobiologie 

129:459-471. 

Ott, D. W., and C. K. Oldham-Ott. 2003. Eustigmatophyte, raphidophyte, and tribophyte 

algae. Pages 423-469 in J. D. Wehr and R. G. Sheath, editors. Freshwater algae of 

North America. Academic Press, San Diego. 

Ozimek, T., E. Pieczynska, and A. Hankiewicz. 1991. Effect of filamentous algae on 

submerged macrophyte growth: a laboratory experiment. Aquatic Botany 41:309-

315. 

Pirszel, J., B. Pawlik, and T. Skowronski. 1995. Cation-Exchange Capacity of Algae and 

Cyanobacteria - a Parameter of Their Metal Sorption Abilities. Journal of 

Industrial Microbiology 14:319-322. 

Prescott, G. W. 1982. Algae of the Western Great Lakes Area. Otto Koeltz Science 

Publishers, Koenigstein. 

R Development Core Team. 2006. R: a language and environment for statistical 

computing. in, Vienna, Austria. 

Rasband, W. 2003. ImageJ v 1.61. in. National Institutes of Health, Bethesda, Maryland. 

Raven, J. A., and C. Brownlee. 2001. Understanding membrane function. Journal of 

Phycology 37:960-967. 

Skowronski, T., J. A. de Knecht, J. Simons, and J. A. C. Verkleij. 1998. Phytochelatin 

synthesis in response to cadmium uptake in Vaucheria (Xanthophyceae). 

European Journal of Phycology 33:87-91. 

Stevenson, R. J., A. Pinowska, and Y. K. Wang. 2004. Ecological conditions of algae and 

nutrients in Florida springs. Final report. Florida Department of Environmental 

Protection contract number WM858, Michigan State University, East Lansing, MI. 

Sudlow, P. L. 1936. Growth of Vaucheria in culture. Master's Thesis. Ohio State 

University. 

Takahashi, F., T. Hishinuma, and H. Kataoka. 2001. Blue light-induced branching in 

Vaucheria. Requirement of nuclear accumulation in the irradiated region. Plant 

and Cell Physiology 42:274-285. 
29

Tornbom, L., and L. Oliveira. 1993. Wound-Healing in Vaucheria-Longicaulis Hoppaugh 

Var Macounii Blum .2. Cytoplasmic Streaming and Organelle Movement. New 

Phytologist 124:135-148. 
30

Fig. 1 

Box plot showing relative growth rates (RGR) or Vaucheria sp. in a factorial mesocosm 

experiment with 3 growth media (spring water from Alexander, spring water from Silver 

Glen and Z8Fl growth medium but with very low nitrogen and phosphorus content) and 2 

biomass levels: 1 or 5 filaments (n=50). 
31

Fig. 2 

Box plots showing relative growth rates (RGR) of Vaucheria sp. in different conductivity 

water (n=48). 
32

Fig. 3 

Box plots showing relative growth rates (RGR) of Vaucheria sp. in a factorial mesocosm 

experiment with 5 light levels and 3 conductivity levels (n=121). 
33

Fig. 4 

Box plots showing relative growth rates (RGR) of Vaucheria sp. in growth media with 

and without micronutrients added (n=18). 
34

Fig. 5 

Box plot showing relative growth rates (RGR) of Vaucheria sp. in 4 iron concentrations 

(n=39). Boxes sharing the same letter do not differ (Tukey’s test p<0.05). 
35

Table 1 

Vaucheria sp. experiments. Experiment numbers in parenthesis refer to numbers used in 

the 2004 report (Stevenson et al. 2004). 

Experiment 

(project 

experiment 

number) 

Treatments Algae 

collection 

location 

Season Growth 

medium 

Mean min and 

max 

temperature 

(oC) 

1 (6) 

2 (13) 

3 (13) 

4 (14) 

5 (14) 

Spring water, media and number 

of filaments in the tube 

Conductivity 

Light and conductivity 

Microelements 

Iron 

Manatee 

Manatee 

Manatee 

Manatee 

Manatee 

Summer 

Summer 

Summer 

Summer 

Summer 

Z8Fl 

Z8Fl 

Z8Fl 

Z8Fl 

Z8Fl 

20.7 &25.0 

20.4 & 24.7 

20.4 & 24.7 

20.6 & 24.8 

20.6 & 24.8 

Table 2 

Chemical composition of a component of growth media in experiments 2 and 3 

responsible for desired conductivity in the medium. 

Conductivity 

(μS/cm) 

CaCl2·2H2O 

(mM) 

MgSO4·7H2O 

(mM) 

Na2CO3

(mM) 

KCl 

(mM) 

NaCl 

(mM) 

100 

300 

500 

1000 

3000 

0.116 

0.496 

0.747 

1.618 

2.739 

0.101 

0.203 

0.284 

0.284 

0.284 

0.198 

0.792 

1.293 

1.293 

1.293 

0 

0 

0 

0.123 

0.875 

0 

0 

0 

0.123 

0.875 

Table 3 

Methods used for analyses of water samples. 

Parameter Method Description 

Ammonia-N EPA 350.1 (1983) Ammonia in aquaeous matrices as mg N/L 

NO2NO3-N EPA 353.2 (1983) Nitrite/Nitrate in aqueous matrices as mg N/L 

N_KJEL_TOT EPA 351.2 (1983) Total Kjeldahl Nitrogen in aqueous matrices 

Total-P EPA 365.4 Total Phosphorus in aqueous matrices 
36

Table 4 

Detection limits of water chemical analyses. When the concentration of a compound was 

below the detection limit of the laboratory method, the method detection limit is reported. 

Compound Detection limit (mg/L)

Ammonia nitrogen 0.010 

Total Kjeldahl nitrogen 0.060 

Nitrates 0.004 

Total phosphorus 0.004 

Table 5 

Measured concentration of nitrates, ammonia, total nitrogen and total phosphorus in the 

growth media used in the experiments. 

Treatments NH4-N (μg/L) NO3-N (μg/L) TN (μg/L) TP (μg/L) 

Experiment 1: 

 Alexander spring water 

 Silver Glen spring water 

 Z8Fl 

Experiment 2 – conductivity: 

 100 μS/cm 

 300 μS/cm 

 500 μS/cm 

 1000 μS/cm 

 3000 μS/cm 

Experiment 4 – microelements: 

 not added 

 added 

Experiment 5 – Fe: 

 0 μg/L 

 20 μg/L 

 200 μg/L 

 600 μg/L 

22 

13 

<10 

<10 

18 

<10 

<10 

11 

<10 

13 

18 

16 

17 

16 

53 

19 

6 

1000 

1000 

1000 

990 

990 

1100 

1000 

1000 

1000 

1000 

1000 

220 

180 

270 

1360 

1350 

1360 

1320 

1370 

1370 

1200 

1120 

1190 

1240 

1220 

41 

24 

42 

94 

74 

73 

77 

69 

110 

100 

95 

94 

80 

110 
37

Recovery of filamentous algal mats of Lyngbya wollei and Vaucheria sp. after 

disturbance. 

Introduction 

Algae in Florida springs are subject to physical disturbance, most commonly flooding 

and physical disturbance by large animals (large fish, manatees and alligators) or human 

activity (swimming, snorkeling, SCUBA diving). This results in sediment deposition 

which reduces light availability or direct biomass removal. The goal of this investigation 

was to simulate the effects of large animal herbivory and disturbance and the effects of 

sever flooding with turbid water that result in mass algal die off. In this study we 

monitored the regrowth of filamentous algal mats of Lyngbya wollei and Vaucheria sp. 

after direct biomass removal. 

Materials and methods 

This study was conducted at two locations: Manatee spring and Blue Hole in the 

Ichetucknee spring system. The dominant mat-forming filamentous alga at Manatee 

spring is Vaucheria sp (Stevenson et al. 2004). The Manatee spring waters are frequently 

turbid due to flooding from the Suwannee River, and as its name suggests, the spring is 

also frequently visited by manatees that graze on algae. The Blue Hole spring bottom is 

covered by macrophytes and mats of Lyngbya wollei. The Blue Hole spring stays clear 

even during severe flooding events. This study was conducted from January to May 

2006. Three sites were selected within each spring. Each site consisted of 2 
38

experimental plots (50cm x 50cm each) delineated by PVC poles driven into the 

sediments. All of the sites were within restricted areas that are not affected by direct 

human activity. At each site, the initial thickness of the mat was measured. There were 

no differences in the pretreatment mat thickness for the disturbed and control plots, 

indicating that there were no site-specific differences between the plots. After the initial 

measurement of mat thickness, one plot within each site was disturbed. Using a rake, all 

visible filamentous algae were removed down to the sediments. The recolonization of 

disturbed areas and algal growth on the control (undisturbed) plots were initially 

monitored every 2 weeks, and later less frequently depending on the recolonization rates. 

Mat thickness was measured with a 1⁄4” diameter dowel at 13 evenly distributed points on 

each plot. On each observation date, the water depth, dissolved oxygen (DO), pH, 

conductivity and temperature were measured. 

Data were analyzed using SAS statistical software (SAS 2000) (repeated measures 

ANOVA with LS means test) and R statistical software (R Development Core Team 

2006). Data were square root transformed to reduce deviations from normality and 

homoscedasticity. 

Results 

The two populations studied had very different recovery rates after disturbance. The 

control mats of Lyngbya wollei did not change in thickness during the course of this study. 

Disturbed plots of Lyngbya wollei slowly grew back but did not recover from 

thedisturbance even after 108 days (repeated measures ANOVA: time effect p<0.0013, 

disturbance effect p< 0.0021) (Fig. 1). 
39

Fig. 1 

Average thickness of the mats of Lyngbya wollei at Blue Hole in Ichetucknee springs. 

Disturbed sites were completely scraped on the 31 of January and control sites were 

undisturbed. 

Vaucheria sp. in the control plots had the thickest mats on February 17. Later, mat 

thickness decreased and in April control plots were senescing and decomposing. 

Disturbed Vaucheria sp. recovered very quickly, and after 24 days there was no 
40

difference in the thickness of the mat at the disturbed and control sites (LS means for 24 

Feb p=0.2067, for 3 Mar p=0.3108, for 10 Mar p=0.2600, 7 Apr p=0.8269). By the end 

of our study, the control mats had begun to senesce and disintegrate (Fig. 2). 

Fig. 2 

Average thickness of the mats of Vaucheria sp. at Manatee spring. Disturbed sites were 

completely scraped on January 31 and control sites were undisturbed. 
41

The two sites studied had comparable water parameters, however, Manatee springs is 

characterized by a higher amplitude of changes in conductivity and dissolved oxygen 

(Table 1). 

Table 1 

Water parameters at the two studied sites. 

Spring Conductivity 

(μS/cm) 

Dissolved 

oxygen (mg/L) 

pH Temperature 

(oC) 

Blue Hole 279-312 2.3-2.6 6.8-7.7 21.35-21.43 

Manatee 285-502 1.0-2.4 6.7-7.8 21.35-22.1 

Discussion 

Even though in our lab experiments the relative growth rates of Vaucheria sp. and 

Lyngbya wollei were similar, Vaucheria sp. recovered very quickly after disturbance and 

Lyngbya wollei did not recover even after 108 days. Both sites studied are characterized 

by high nutrient levels (Stevenson et al. 2004). The difference between the two taxa in 

the speed of recovery after disturbance can be explained by their different means of 

reproduction and the differences in their growth forms. Vaucheria sp. can reproduce 

asexually by fragmentation of the mat and through production of zoospores, akinets and 

aplanospores (Starmach 1972, Johanson 2005). It can also reproduce sexually by 

formation of antheridia and oogonia. The mat is formed from multinucleate filaments 
42

and attached by colorless rhizoids to the substrate. Lyngbya wollei reproduces only by 

fragmentation of trychomes (Komárek and Anagnostidis 2005). The fact that Vaucheria 

sp. can reproduce much faster than L. wollei probably explains why Vaucheria sp. is the 

dominant taxon in springs along the Suwannee River. Manatee, Fanning and Guaranto 

springs are dominated by mats of Vaucheria sp. These springs also frequently experience 

the intrusion of turbid waters from the Suwannee River during floods. 

References 

Johanson, L. R. 2005. Phylum Xanthophyta (yellow-green algae). Pages 245-270 in D. M. 

John, B. A. Whitton, and A. J. Brook, editors. The freshwater algal flora of the 

British Isles. Cambridge University Press, Cambridge. 

Komárek, J., and K. Anagnostidis. 2005. Cyanoprokaryota. 2. Teil: Oscillatoriales. 

Gustav Fischer, Jena. 

R Development Core Team. 2006. R: a language and environment for statistical 

computing. in Vienna, Austria. 

SAS. 2000. SAS/STAT. in SAS Institute, Cary, N.C. 

Starmach, K. 1972. Chlorophyta III. Zielenice nitkowate: Ulotrhichales, Ulvales, 

Prasiolales, Shaeropleales, Cladophorales, Chaetophorales, Trentepohliales, 

Siphonales, Dichotomosiphonales. Panstwowe Wydawnictwo Naukowe, Kraków. 

Stevenson, R. J., A. Pinowska, and Y. K. Wang. 2004. Ecological conditions of algae and 

nutrients in Florida springs. Final report. Florida Department of Environmental 

Protection. Contract number WM858, Michigan State University, East Lansing, 

MI. 
43

Differential effect of PO4, NO3 and NH4 on the growth of Lyngbya wollei

Introduction 

Lyngbya wollei (Farlow ex Gomont), family Oscillatoriace, a filamentous blue green alga 

with unusually thick, often over 60 μm wide, trichomes, forms nuisance growths in many 

Florida springs. In the algae surveys of 68 Florida spring sites conducted in 2003 and 

2006 (Stevenson et al. 2004), and unpublished data) it was found that large mats were 

most commonly formed by L. wollei. This filamentous alga is found in water bodies 

throughout the southeastern United States (Speziale and Dyck 1992, Cowell and Botts 

1994, Cowell and Dawes 2004), Texas (Owens et al. 2005), Canada (Macbeth 2004) and 

other locations. Lyngbya wollei can fix atmospheric nitrogen (Phlips et al. 1992) but 

large mats are often found at sites with high nitrate concentrations (Cowell and Botts 

1994, Stevenson et al. 2004). 

In the natural environment the growth of filamentous algal mats is highly affected by 

many biotic and abiotic factors. Even though L. wollei mats are not readily consumed by 

herbivores (Camacho and Thacker 2006) in Florida springs the mats are disturbed by 

large vertebrates and people visiting the springs. To successfully study nutrient effects 

on the growth of algae, the mats have to be moved to controlled laboratory conditions. 

Several studies investigated the effects of nitrogen and phosphorus on the growth of L. 

wollei (Turner 1990, Cowell and Botts 1994, Yin et al. 1997, Cowell and Dawes 2004). 

These studies used only a few concentrations of nutrients in their experiments and none 

of them investigated the threshold levels of nutrients for the growth of L. wollei. . 
44

This study focused only on L. wollei from Florida springs. The objectives of this 

study were: (i) to investigate the effects of a wide range of concentrations of nitrogen (in 

the form of nitrate and ammonia) and phosphorus on the growth of L. wollei, (ii) to 

determine whether nitrate or ammonia is a preferred source of nitrogen for L. wollei, (iii) 

to study the importance of the size of algal mats when L. wollei was grown under 

different nutrient levels, and (iv) to investigate whether L. wollei populations show 

seasonal differences in their growth rates and whether populations from different Florida 

springs differ in their growth rates as well. 

Materials and methods 

Two experimental systems were used to study the growth of filamentous algae: small 

microcosms and large microcosms. The small microcosm system allowed a large number 

of replicates but restricted the experimental unit to a short algal filament. The large 

microcosm system could accommodate small filamentous algal mats of varying sizes but 

restricted the number of replicates. We conducted 9 small microcosm experiments and 3 

large microcosm experiments (Table 1). The nutrient levels used in the experiments 

reflected phosphate and nitrate concentrations observed in Florida springs water. 

Ammonia concentrations used in the experiments were higher than those observed in 

Florida springs water but in the range of those observed inside the L. wollei mats (Task 3 

of the report – the study conducted by Albertin and Sickman). 
45

Small microcosm experiments 

Filaments of L. wollei were grown in 1.5 ml microcentrifuge tubes filled with 1 ml of 

growth media. Growth media were changed every 48 hours. Racks made of clear 

polyethylene were placed on an orbital shaker (60 RPM) and incubated under grow lights 

providing 25 μmol/m2

/s of light. To achieve this light intensity, the racks were covered 

with neutral density film. Light intensity of 25 μmol/m2

/s was found to be the optimal 

intensity for the growth of individual filaments in microcentrifuge tubes. The initial 

filament length was 1-2mm. The filament was photographed using a digital video camera 

system installed on a Leica MZ12.5 Stereomicroscope under 8x magnification at the 

beginning and at the end of each experiment. Filament length was measured on the 

digital images using Image J software (Rasband 2003). Incubation time was 11 or 12 

days. Each treatment was replicated 10 times, or 5 times if L. wollei from two locations 

(2 different springs) was used. Since some of the filaments were lost during the media 

changes, the final number of replicates used for the data analyses was lower than set at 

the beginning of the experiment. All experiments had a complete factorial ANOVA 

design with 1 or 2 factors. Experiments 1, 2 and 3 had a 2 factor design with 10 nutrient 

treatments each (PO4-P concentrations: 1, 5, 10, 20, 30, 40, 60, 80, 100 and 250 μg P/L) 

and 2 population location treatments. The NO3-N concentration in experiment 1, 2 and 3 

was 1000 μg/L. Experiment 5 had a one factor design with 11 nutrient treatments (NO3-

N concentrations: 10, 30, 60, 125, 250, 500, 750, 1000, 1500, 2500 and 5000 μg N/L) and 

experiments 6, 7 and 8 had a 2 factor design with 10 nutrient treatments (NO3-N 

concentrations: 10, 30, 60, 125, 250, 500, 750, 1000, 2000 and 5000 μg N/L) and 2 

population location treatments. Experiment 10 had a 1 factor design with 11 nutrient 
46

treatments (NH4-N concentrations: 10, 30, 60, 125, 250, 500, 750, 1000, 1500, 2500 and 

5000 μg N/L). Experiment 12 had a 2 factor design with 16 nutrient treatments: a 

combination of 4 ammonia concentrations (20, 100, 500 and 1000 μg N/L) and 4 nitrate 

concentrations (20, 100, 500 and 1000 μg N/L). The PO4-P concentration in experiments 

5, 6, 7, 8, 10 and 12 was 100 μg/L. 

Large microcosm experiments 

The large microcosm system consisted of a flat platform with Plexiglas cylindrical 

raceways (Manoylov 2005). The platform was placed on an orbital shaker table (60RMP) 

in a walk-in growth room. The platform was illuminated with fluorescent grow lights 

providing 150 μmol/m2

/s of light. Each microcosm was filled with 100 ml of growth 

medium. The media were changed daily. At the beginning and at the end of the 

experiment, small fragments of L. wollei mats were held between a Nitex screen and 

gently patted dry with a paper towel to remove excess water, then weighed (fresh mass). 

At the end of the experiment, all samples were processed for dry mass (DM). At the 

beginning of each experiment, 10 algal samples from each initial mass treatment were 

patted dry in between a Nitex screen, weighed to measure the initial fresh mass (FM), 

dried in the oven, and weighed again (DM). This allowed the calculation of the initial 

dry mass of the experimental samples based on their initial fresh mass. All samples for 

DM were dried in the oven at 105oC for 24 hours (Eaton et al. 1995). All experiments 

had a complete factorial ANOVA design with 2 experimental factors: nutrient 

concentration and initial biomass. Experiment 4 had a total of 15 treatments that were a 

combination of 5 phosphate concentrations (PO4-P concentrations: 2, 10, 30, 60, 150 μg 
47

P/L) and 3 initial fresh mass levels (0.01g, 0.05g, 0.2g). The NO3-N concentration in 

experiment 4 was 1000 μg/L. Experiment 9 had a total of 15 treatments that were a 

combination of 5 nitrate concentrations (NO3-N concentrations: 20, 125, 500, 1000, 2500 

μg N/L) and 3 initial fresh mass levels (0.01g, 0.05g, 0.2g). Experiment 11 had a total of 

15 treatments that were a combination of 5 ammonia concentrations (NH4-N 

concentrations: 20, 125, 500, 1000, 2500 μg N/L) and 3 initial fresh mass levels (0.01g, 

0.05g, 0.2g). The PO4-P concentration in experiment 9 and 11 was 100 μg/L. 

Relative growth rates 

Algal relative growth rate (RGR) in the large microcosm experiments was calculated 

using the following formula (Hunt 1990): 

In the small microcosm experiments, algal initial and final filament length was used 

instead of algal mass. 

Growth media 

A new growth medium was developed based on the Z8 medium (Kotai 1972). The Z8 

medium was modified to simulate the median chemistry of macronutrients in Florida 

spring water (referred to as medium Z8Fl) (Appendix 1). We originally used a Z8Fl 

# of days

ln(Final Mass) ln(Initial Mass) RGR = −
48

Fe600 medium that had the original concentration of iron (600 μg/L) found in the Z8 

medium. Later we used Z8Fl Fe200 with the iron concentration reduced to 200μg/L, 

because we found an Fe concentration of 600μg/L to have a suppressing effect on the 

growth of L. wollei sp. We used the Gaffron micronutrients mix as used by Kotai (1972). 

To 1L of the final growth medium we also added 10ml of CaCl2·2H2O solution (stock 

solution 18.3g CaCl2·2H2O in 1L of deionized water), 10ml of MgSO4·7H2O solution 

(stock solution 7g MgSO4·7H2O in 1L of deionized water), and 10ml of Na2CO3 solution 

(stock solution 13.7g Na2CO3 in 1L deionized water). We used NaNO3 and NH4Cl as 

sources of nitrogen and K2HPO4 as a source of phosphorus. When NaNO3 gradient was 

investigated, NaCl was also added to keep the Na concentration constant in all the 

treatments. In the experiments with K2HPO4, gradient KCl was added to keep the K 

concentration constant in all of the treatments, following the experimental design of 

(Ahlgren 1977). 

Experimental conditions 

All experiments were conducted in the walk-in growth room. The temperature in the 

growth room was set for 22.5oC to reflect the average water temperature in Florida 

springs. The minimum and maximum temperature was recorded daily on a max-min 

thermometer. 
49

Water analyses 

Water samples of prepared growth media and from experimental macrocosms were sent 

to FDEP for analyses. On last day of experiment a sample of water in which algae were 

growing for 24 hours was collected for analyses. 

Data analyses 

Data were analyzed using SAS statistical software (SAS 2000) (repeated measures 

ANOVA) and R statistical software (R Development Core Team 2006). Logistic 

regression analysis was conducted using drc package for R (Ritz and Streibig 2007). All 

final and initial filament length and small mat biomass data were first tested using 

repeated measures ANOVA to test the significance of nutrient effect and time effect 

(indicating algal growth). Next, factorial analysis of variance was used to test the effect 

of nutrient concentration, season and L. wollei population location on relative growth 

rates (RGR). A lowess smooth line was fitted through the data for general assessment of 

the trends in the data. If a significant nutrient effect was found in the ANOVA analysis, a 

logistic curve was fitted through the RGR data. If the logistic curve did not provide a 

good fit and data were distributed along a straight line, a linear regression was calculated. 

Various logistic models were fitted through the data (Ritz and Streibig 2005, Ritz and 

Streibig 2006) and the best fitting models are presented in the results. The best fitting 

models for our data were: four parameter logistic model (l4()), four parameter logistic 

model with variance calculated as a power function of the mean to account for 

heterogeneity of the data (l4() varPower), Monod model (calculated using code for 
50

Michaelis-Menten model from the drc package) and five parameter Brain-Cousens 

hormesis model (Borchardt 1996, Schabenberger et al. 1999, Ritz and Streibig 2007). 

When seasonal effects were compared using factorial ANOVA, only data from 

experiments conducted using exactly the same growth media and for populations 

collected from the same locations during different seasons were used. When population 

effects were compared, only experiments conducted in the same media and season were 

used. All data sets were checked for normality and heterogeneity of variance, and, where 

necessary, data were transformed for the ANOVA analyses. All analyses using the drc 

package were conducted on untransformed RGR data. 

Results 

Lyngbya wollei grew in all experiments under all nutrient concentrations. Relative 

growth rates (RGR) varied from 0 to 0.40. Low nutrient levels resulted in low growth 

rates and high nutrient levels resulted in high growth rates, with the exception of 

ammonia treatments. In these, the highest NH4 concentrations in the small microcosm 

experiments resulted in reduced growth rates. 

Effects of PO4

In the small microcosm experiments, an increase in phosphate phosphorus had a 

significant effect on the growth of L. wollei (Fig 1). The relative growth rate data were 

well described by a logistic dose-response curve (Fig. 1, Table 2). The threshold 

concentration of phosphate phosphorus for the growth of L. wollei was 17.5 μg/L - the 

Effective Dose of 50% growth saturation (ED50). The mean growth rate in the 
51

experiments conducted on the L. wollei population from the Ichetucknee in the spring of 

the year (0.29±0.08 mm/mm/day) was higher than in the fall (0.20±0.10 mm/mm/day) 

(ANOVA for the season effect, P<0.001). The three populations of L. wollei studied did 

not differ in their RGRs (ANOVA for the location effect, P<0.543). 

In the large microcosm experiments, L. wollei mats with smaller initial biomass grew 

faster than larger mats, especially in high phosphate concentrations (ANOVA for biomass 

effect, P<0.001) (Fig.2). A dose response curve was successfully fitted only through the 

lowest initial biomass data. The threshold phosphate phosphorus concentration was 49 

μg/L (Fig.2, Table 3). 

Effect of NO3 

In the small microcosm experiments, an increase in nitrate nitrogen had a positive effect 

on the growth of L. wollei (Fig. 3). The RGR data were well described by a logistic doseresponse curve (Fig. 3, Table 2). The threshold nitrate nitrogen concentration for the 

growth of L. wollei was 88.1 μg/L (ED50). The mean growth rate in the experiments 

conducted on the L. wollei population from the Ichetucknee in the spring of the year 

(0.27±0.08 mm/mm/day) was higher then in the fall (0.19±0.08 mm/mm/day) (ANOVA 

for the season effect, P<0.001). Among the three studied populations of L. wollei, the

Ichetucknee population (0.22±0.10 mm/mm/day) had lower relative growth rates than the 

Silver Glen and Alexander populations (0.24±0.09 mm/mm/day and 0.24±0.08 

mm/mm/day) (ANOVA for the location effect, P<0.001). 

In the large microcosm experiments, L. wollei mats with smaller initial biomass grew 

faster than larger mats (ANOVA for biomass effect, P<0.001) (Fig.4). Dose response 

curves were fitted through the data. The threshold nitrate nitrogen concentration was 519 
52

μg/L for the 0.01g initial biomass and 546 μg/L for the 0.05g initial biomass (Fig.4, 

Table 3). 

Effect of NH4

In the small microcosm experiments, an increase in ammonia nitrogen resulted in 

increased growth rates up to a 796.3 μg/L NH4-N concentration, where it reached the 

highest growth rate of 0.27 mm/mm/day (Fig. 5). The RGR data were well described by 

the Brain-Cousens hormesis curve (Fig. 5, Table 2). 

In the large microcosm experiments, L. wollei mats with smaller initial biomass grew 

faster than larger mats in high ammonia concentrations (ANOVA for biomass effect, 

P<0.001) (Fig.6). Dose response curves were fitted through the 0.01g and 0.05g initial 

biomass data. The threshold ammonia nitrogen concentration was 248 μg/L for the 0.01g 

initial biomass and 227 μg/L for the 0.05g initial biomass (Fig.6, Table 3). 

Combined effect of NO3 and NH4

In the small microcosm experiments, nitrogen was added in the form of ammonia, nitrate 

or a combination of those two forms. Both nitrate and ammonia nitrogen had a positive 

effect on the growth of L. wollei (ANOVA for NO3 effect, P<0.001, for NH4 effect 

P<0.001) (Fig.7). We also found that the form of nitrogen used did not matter and only 

an absolute concentration of nitrogen had an effect on the growth rates of L. wollei. The 

RGR data were well described by the Monod model (Fig. 8, Table 2). The half saturation 

constant Kμ was reached at a 104μg/L combined nitrogen concentration.
53

Discussion 

In our experiments Lyngbya wollei grew in all experimental conditions (Table 4). A 

maximum doubling rate of 0.4 was lower or similar to the growth rates of other species of 

filamentous algae (Borchardt 1996, Hall and Payne 1997). On the other hand. the 

doubling rates of L. wollei in our study were higher or similar to the growth rates of L. 

wollei observed by others (Cowell and Botts 1994, Yin et al. 1997, Cowell and Dawes 

2004). Cowell and Dawes (2004) investigated the effect of nitrate on the growth of small 

mats of L. wollei in a continuous culture and found that the growth rate increased when 

the nitrate concentration was equal to or above 600 μg N/L. When we examined the 

growth of L. wollei mats in different nitrate concentrations, we found a threshold 

concentration of 518-546 μg N/L, which is in agreement with the results of Cowell and 

Dawes (2004). Turner (1990) and Yin et al. (1997) experimented with very high nutrient 

concentrations. These concentrations were above the highest concentration used in this 

study. Some of the low growth rates observed by Turner (1990) and Yin et al. (1997) 

were possibly the result of nutrient toxicity. In our study we did not find L. wollei to 

show a preference for ammonia or nitrate as a source of nitrogen, which agrees with the 

results of Turner (1990). In this study growth rates of single filaments were saturated at 

lower nutrient levels than growth rates of algal mats. Also, different size mats of L. 

wollei were used, and withlarger mat sizes, the saturating nutrient concentration was 

increased as well. Overall, for individual filaments, the nitrate concentration in almost all 

Florida springs (Stevenson et al. 2004) were above threshold concentrations for the 

growth of L. wollei, and in many of the springs the nitrate concentrations were above the 

threshold concentration for the growth and establishment of mats. Once mats develop, 
54

they can recycle nutrients within the mat, thus, their growth is less dependent on the 

nutrients available from the water column. The water phosphate concentration in many 

Florida springs is above the threshold concentration for the growth of individual 

filaments. However, it was below 50 μg/L, the threshold concentration for the growth of 

mats, in 76% of the springs surveyed (Stevenson et al. 2004). 

References 

Ahlgren, G. 1977. Growth of Oscillatoria-Agardhii in Chemostat Culture .1. Nitrogen and 

Phosphorus Requirements. Oikos 29:209-224. 

Borchardt, M. A. 1996. Nutrients. Pages 183-227 in R. J. Stevenson, M. L. Bothwell, and 

R. L. Lowe, editors. Algal ecology. Academic Press, Sand Diego. 

Camacho, F. A., and R. W. Thacker. 2006. Amphipod herbivory on the freshwater 

cyanobacterium Lyngbya wollei: Chemical stimulants and morphological 

defenses. Limnology and Oceanography 51:1870-1875. 

Cowell, B. C., and P. S. Botts. 1994. Factors Influencing the Distribution, Abundance and 

Growth of Lyngbya-Wollei in Central Florida. Aquatic Botany 49:1-17. 

Cowell, B. C., and C. J. Dawes. 2004. Growth and nitrate-nitrogen uptake by the 

cyanobacterium Lyngbya wollei. Journal of Aquatic Plant Management 42:69-71. 

Eaton, A. D., L. S. Clesceri, and A. E. Greenberg, Eds. 1995. Standard methods for the 

examination of water and wastewater, 19th edition. American Public Health 

Association, Washington, D.C. 

Hall, J., and G. Payne. 1997. Factors controlling the growth of field populations of 

Hydrodictyon reticulatum in New Zealand. Journal of Applied Phycology 9:229-

236. 

Hunt, R. 1990. Basic growth analysis. Unvwin Hyman Ltd., London. 

Kotai, J. 1972. Instructions for preparation of modified nutrient solution Z8 for algae. 

Norwegian Institute for Water Research, publication B-11/69., Blindern, Oslo. 

Macbeth, A. J. 2004. Investigation of an introduced subtropical alga (Lyngbya wollei) in 

Whiteshell Provincial Park, Manitoba. Masters Thesis. University of Manitoba, 

Winnipeg. 

Manoylov, K. M. 2005. Ecological strategies of benthic diatoms for 

nutrient competition. Ph.D. Dissertation. Michigan State University, East Lansing. 

Owens, C. S., M. J. Grodwitz, and F. Nibling. 2005. A survey of the invasive aquatic and 

riparian plants of the lower Rio Grande, 2004. U.S. Army Corps of Engineers, 

Washington, DC 20314-1000. 

Phlips, E. J., J. Ihnat, and M. Conroy. 1992. Nitrogen fixation by the benthic freshwater 

cyanobacterium Lyngbya wollei. Hydrobiologia 234:59-64. 
55

R Development Core Team. 2006. R: a language and environment for statistical 

computing. in, Vienna, Austria. 

Rasband, W. 2003. ImageJ v 1.61. in. National Institute of Health, Bethesda, Maryland. 

Ritz, c., and J. C. Streibig. 2005. Bioassay analysis using R. Journal of Statistical 

Software 12:1-22. 

Ritz, C., and J. C. Streibig. 2006. Bioassay for allelochemicals: examples with R. Pages 

24 in. 

Ritz, C., and J. C. Streibig. 2007. The drc package. Analysis of dose-response curves. in. 

SAS. 2000. SAS/STAT. in. SAS Institute, Cary, N.C. 

Schabenberger, O., B. E. Tharp, J. J. Kells, and D. Penner. 1999. Statistical tests for 

hormesis and effective dosages in herbicide dose response. Agronomy Journal 

91:713-721. 

Speziale, B. J., and L. A. Dyck. 1992. Lyngbya infestations: comparative taxonomy of 

Lyngbya wollei comb. nov. (Cyanobacteria). Journal of Phycology 28:693-706. 

Stevenson, R. J., A. Pinowska, and Y. K. Wang. 2004. Ecological conditions of algae and 

nutrients in Florida springs. Final report. Florida Department of Environmental 

Protection contract number WM858, Michigan State University, East Lansing, MI. 

Turner, G. 1990. Studies on the biology of Lyngbya wollei. Master Thesis. Clemson 

University, South Carolina. 

Yin, Q. Q., W. W. Carmichael, and W. R. Evans. 1997. Factors influencing growth and 

toxin production by cultures of the freshwater cyanobacterium Lyngbya wollei 

Farlow ex Gomont. Journal of Applied Phycology 9:55-63. 
56

Fig 1 

Relative growth rates (RGR) of Lyngbya wollei in different phosphate phosphorus 

concentrations (n=271). A four parameter logistic curve, with variance as a power 

function of the mean, was fitted through the combined data from small microcosm 

experiments (experiments 1, 2 and 3). Curve parameters are in Table 2. 
57

Fig. 2 

Relative growth rates (RGR) of Lyngbya wollei in a factorial experiment with 3 initial 

biomass levels (0.01g, 0.05g, 0.2g) and 5 phosphate phosphorus concentrations (n=45). 

A four parameter logistic curve and 2 regression lines (initial biomass 0.05g R2

=0.05, 

P<0.41; initial biomass 0.2g R2

=0.21, P<0.086) were fitted through the data from a large 

microcosm experiment (experiment 4). Curve parameters are in Table 3. 
58
59

Fig. 3 

Relative growth rates (RGR) of Lyngbya wollei in different nitrate nitrogen 

concentrations (n=380). A four parameter logistic curve, with variance as a power 

function of the mean, was fitted through the combined data from small microcosm 

experiments (experiments 5, 6, 7 and 8). Curve parameters are in Table 2. 
60

Fig. 4 

Relative growth rates (RGR) of Lyngbya wollei in a factorial experiment with 3 initial 

biomass levels (0.01g, 0.05g, 0.2g) and 5 nitrate nitrogen concentrations (n=45). Four 

parameter logistic curves were fitted through the data from a large microcosm experiment 

(experiment 9). Curve parameters are in Table 3. 
61

Fig. 5 

Relative growth rates (RGR) of Lyngbya wollei in different ammonia nitrogen 

concentrations (n=101). A five parameter Brain-Cousens hormesis logistic model was 

fitted through the data from a small microcosm experiment (experiment 10). Curve 

parameters are in Table 2. 
62

Fig. 6 

Relative growth rates (RGR) of Lyngbya wollei in a factorial experiment with 3 initial 

biomass levels (0.01g, 0.05g, 0.2g) and 5 ammonia nitrogen concentrations (n=45). Two 

four parameter logistic curves and a regression line (initial biomass 0.2g R2

=0.45, 

P<0.006) were fitted through the data from a large microcosm experiment (experiment 

11). Curve parameters are in Table 3. 
63

Fig. 7 

Boxplot of relative growth rates (RGR) of Lyngbya wollei in a combination of different 

ammonia and nitrate nitrogen concentrations (experiment 12). 
64

Fig. 8 

Relative growth rates (RGR) of Lyngbya wollei in different nitrogen (sum of NO3-N and 

NH4-N) concentrations (n=153). A Monod logistic curve starting at y0=0 was fitted 

through data from small microcosm experiment (experiment 12). The assumption that 

y0=0 was used since there were no data in the low range of concentrations. Curve 

parameters are in Table 2. 
65

Table 1 

Lyngbya wollei experiments. Experiment numbers in parenthesis refer to the numbers 

used in the 2006 report. 

Experiment 

(project 

experiment 

number) 

Micro

cosm 

Nutrient 

gradient 

Algae collection location Season Growth 

medium 

Mean min 

and max 

temperature 

(oC) 

1 (18) 

2 (19) 

3 (21) 

4 (8) 

5 (3) 

6 (16) 

7 (17) 

8 (20) 

9 (9) 

10 (4) 

11 (12) 

12 (2) 

Small 

Small 

Small 

Large 

Small 

Small 

Small 

Small 

Large 

Small 

Large 

Small 

PO4-P 

PO4-P 

PO4-P 

PO4-P 

NO3-N 

NO3-N 

NO3-N 

NO3-N 

NO3-N 

NH4-N 

NH4-N 

N (NH4

and 

NO3) 

Ichetucknee and Silver Glen 

Ichetucknee and Silver Glen 

Ichetucknee and Alexander 

Silver Glen 

Silver Glen 

Ichetucknee and Silver Glen 

Ichetucknee and Silver Glen 

Ichetucknee and Alexander 

Ichetucknee 

Silver Glen 

Silver Glen 

Silver Glen 

Fall 

Fall 

Spring 

Spring 

Spring 

Fall 

Fall 

Spring 

Spring 

Spring 

Fall 

Spring 

Z8Fl Fe200 

Z8Fl Fe200 

Z8Fl Fe200 

Z8Fl Fe600 

Z8Fl Fe600 

Z8Fl Fe200 

Z8Fl Fe200 

Z8Fl Fe200 

Z8Fl Fe600 

Z8Fl Fe600 

Z8Fl Fe600 

Z8Fl Fe600 

20.8 &24.3 

21.1 &25.3 

21.5 &24.9 

21.1 & 25.4 

21.9 & 24.2 

20.9 & 24.5 

20.8 & 24.3 

21.5 &24.9 

20.6 & 22.3 

21.5 & 24.5 

22.0 & 26.7 

21.0 & 24.3 
66

Table 2 

Parameters of the logistic dose-response model applied to the Lyngbya wollei RGR data 

from small microcosm experiments, where d and c denote the upper and lower limit of 

algae growth rates at infinitely low and high concentrations of nutrient. ED50 (also called 

e) denotes the concentration required to increase algal growth rate by half between the 

upper and lower limits and b is proportional to the slope (the rate of change) of the curve 

around ED50. Significant parameters are in boldface. ED10 and ED90 denote the 

concentration required for 10% and 90% growth saturation. For the Brain-Cousens 

hormesis model, c and d are the upper and lower asymptote of the response. The b and e

columns are related to the rate of change and point of inflection of the curve, respectively; 

and f indicates the initial rate of increase at low concentrations. For the Monod model, 

μmax is the maximum specific growth rate and Kμ is the half saturation constant. 

Significant parameters are in boldface. 

Nutrient Model d or μmax

(mm/mm/

day) 

c

(mm/mm/

day) 

b ED50 (μg/L) 

e or Kμ

ED90 (μg/L) 

or f

ED10 (μg/L) 

PO4

NO3

NH4

N (NO3

and NH4) 

l4() varPower 

l4() varPower 

Brain-Cousens 

Monod 

0.28±0.01 

0.26±0.00 

0.09±0.01 

0.19±0.01 

0.14±0.01 

0.10±0.01 

0.11±0.01 

- 

-4.65±1.39 

-2.29±0.31 

5.18±0.71 

- 

17.50±1.39 

88.10±6.14 

796.3±43.5 

104.2±21.5 

28.10±3.80 

230.05±32.06 

0.00037±0.00004 

- 

10.90±2.00 

33.74±5.28 

- 

- 
67

Table 3 

Parameters of the logistic dose-response model applied to the Lyngbya wollei growth 

response data from large microcosm experiments, where d and c denote the upper and 

lower limit of algae growth rates at infinitely low and high concentrations of nutrient. 

ED50 denotes the concentration required to increase the algal growth rate by half between 

the upper and lower limits and b is proportional to the slope of the curve around ED50. 

Significant parameters are in boldface. ED10 and ED90 denote the concentration required 

for 10% and 90% growth saturation. 

Nutrient and 

biomass 

Model d

(g/g/day) 

c

(g/g/day) 

b ED50 (μg/L) ED90 (μg/L) ED10 (μg/L) 

PO4 x 0.01g 

NO3 x0.01g 

NO3 x0.05g 

NO3 x0.2g 

NH4 x 0.01g 

NH4 x 0.05g 

l4() 

l4() 

l4() 

l4() 

l4() 

l4() 

0.23±0.01 

0.27±0.01

0.24±0.03 

0.15±0.03

0.23±0.01 

0.18±0.01

0.15±0.01 

0.15±0.01 

0.11±0.02 

0.11±0.02

0.11±0.01 

0.11±0.01

-3.05±1.41

-4.78±4.00

-1.19±0.87

-0.83±1.19

-1.90±0.47

-3.11±1.63

49.15±9.74 

518.6±47.9

546.0±250.0

808.2±2015 

247.51±39.26 

226.95±41.86

100.9±42.8 

820.6±353.7 

3440.0±5490.0 

11283±61207 

788.5±246.4 

460.2±205.8

23.9±8.3 

327.7±116.1 

86.66±106.1 

57.88±396.8 

77.70±26.74 

111.9±42.78
68

Table 4 

Summary of L. wollei growth parameters. 

Single filaments Mats Parameter 

PO4-P NO3-N NH4-N PO4-P NO3-N NH4-N 

Lowest nutrient concentration tested 

Average growth rate at lowest nutrient 

concentration 

Highest nutrient concentration tested 

Average growth rate at highest nutrient 

concentration 

Average maximum growth rate 

Lowest concentration at maximum growth rate 

Minimum concentration at which growth was 

observed 

Difference between maximum and minimum 

growth rate 

Average threshold concentration 

1 μg/L 

0.15 

250 μg/L 

0.27 

0.30 

60 μg/L 

1 μg/L 

0.15 

17.5 μg/L 

10 μg/L 

0.10 

5 mg/L 

0.28 

0.28 

5 mg/L 

10 μg/L 

0.18 

88μg/L 

10 μg/L 

0.08 

5 mg/L 

0.12 

0.26 

0.5 mg/L 

10 μg/L 

0.18 

796 μg/L 

2 μg/L 

0.15 

150 μg/L 

0.19 

0.19 

150 μg/L 

2 μg/L 

0.04 

49 μg/L 

20 μg/L 

0.11 

2.5 mg/L

0.22 

0.22 

2.5 mg/L

20 μg/L 

0.11 

532μg/L 

20 μg/L 

0.11 

2.5 mg/L 

0.16 

0.19 

1.5 mg/L 

20 μg/L 

0.09 

238 μg/L 

 
69

Differential effect of PO4, NO3 and NH4 on the growth of Vaucheria sp. 

Introduction 

Vaucheria sp. (Xanthophyce) is a common filamentous mat-forming species in streams, 

rivers and lakes (Entwisle 1990, McIntire et al. 1994, Necchi et al. 1994, Aboal et al. 

1996). It is often found at high nutrient sites, and its presence can be a symptom of 

system eutrophication (Lakatos 1978, Simons et al. 1994, Biggs 1996). Vaucheria sp. 

can also be found in the springs and areas of ground water input into streams (Davis and 

Gworek 1973, Moreno et al. 2001). In a survey of 60 sites within 28 spring systems in 

Northern and Central Florida, we found Vaucheria sp. mats at 33 sites (Stevenson et al. 

2004). At Manatee, Fanning and Guaranto springs, more than 70% of the spring bottoms 

were covered by Vaucheria sp. Even though Vaucheria sp. is commonly found in the 

fresh, brackish and marine water systems around the world, there are few laboratory 

studies on its nutrient requirements (Sudlow 1936, Ozimek 1990). 

This study was conducted on Vaucheria sp. in Florida springs. The objectives of the 

study were: (i) to investigate the effects of a wide range of concentrations of nitrogen (in 

the form of nitrate and ammonia) and phosphorus on the growth of Vaucheria sp., (ii) to 

determine whether nitrate or ammonia is a preferred source of nitrogen for Vaucheria sp., 

(iii) to study the importance of the size of algal mats when Vaucheria sp. was grown 

under different nutrient levels, and (iv) to investigate whether Vaucheria sp. populations 

from different Florida springs differ in their growth rates. 
70

Materials and methods 

Two experimental systems were used to study the growth of filamentous algae: small 

microcosms and large microcosms. The small microcosm system allowed a large number 

of replicates but restricted the experimental unit to short algal filaments. The large 

microcosm system could accommodate small filamentous algal mats of varying sizes but 

restricted the number of replicates. We conducted 4 small microcosm experiments and 3 

large microcosm experiments (Table 1). 

Small microcosm experiments 

Filaments of Vaucheria sp. were grown in 1.5 ml microcentrifuge tubes filled with 1ml of 

growth media. Growth media were changed every 48 hours. Racks made of clear 

polyethylene were placed on an orbital shaker (60 RPM) and incubated under grow lights 

providing 25 μmol/m2

/s of light. To achieve this light intensity, racks were covered with 

neutral density film. A light intensity of 25 μmol/m2

/s was found to be the optimal 

intensity for the growth of individual filaments in microcentrifuge tubes. Healthy, 

growing tips of Vaucheria sp. 1-2mm in length were cut from the filaments. Originally 

these tips were used directly for the experiments. However, we found that many of the 

cut off tips of Vaucheria sp. were damaged in the process and did not grow. Therefore, 

we changed our methodology and incubated 1-2mm tips for 2 days in Z8Fl growth 

medium (Appendix 1) with 100μg/L P and 1000μg/L N before we used them in the 

experiments. For experiment 1 and 3, tips were pre-incubated for 48 hours, and for 

experiments 4 and 6, tips were used right after cutting. A tip of Vaucheira sp. was 

photographed using a digital video camera system installed on a Leica MZ12.5 

Stereomicroscope under 8x magnification at the beginning and at the end of experiment. 
71

Filament length was measured on the digital images using ImageJ software (Rasband 

1997-2006). Incubation time was 11 or 12 days. Each treatment was replicated 5 times if 

Vaucheria from two locations (2 different springs) was used. If Vaucheria from one 

location was used, each treatment was replicated10 times. . Since some of the filaments 

were lost during the media changes, the final number of replicates used for the data 

analyses was lower then the number set at the beginning of the experiments. All 

experiments had a complete factorial ANOVA design with one or two factors. 

Experiment 1 had a two-factor design with 10 nutrient treatments (PO4-P concentrations: 

1, 5, 10, 20, 30, 40, 60, 80, 100 and 250 μg P/L) and 2 population location treatments. 

The NO3-N concentration in experiment 1 was 1000 μg/L. Experiment 3 had a twofactor design with 10 nutrient treatments (NO3-N concentrations: 10, 30, 60, 125, 250, 

500, 750, 1000, 2000 and 5000 μg N/L) and 2 population location treatments. The PO4-P 

concentration in experiment 3 was 100 μg/L. Experiment 5 had a one-factor design with 

11 nutrient treatments (NH4-N concentrations: 10, 30, 60, 125, 250, 500, 750, 1000, 1500, 

2500 and 5000 μg N/L). The PO4-P concentration in experiment 5 was 100 μg/L. 

Experiment 7 had a two-factor design with 16 nutrient treatments: a combination of 4 

ammonia concentrations (20, 100, 500 and 1000 μg N/L) and 4 nitrate concentrations (20, 

100, 500 and 1000 μg N/L). 

Large microcosm experiments 

The large microcosm system consisted of a flat platform with Plexiglas cylindrical 

raceways (Manoylov 2005). The platform was placed on an orbital shaker table (60RMP) 

in a walk-in growth room. The platform was illuminated with fluorescent growth lights 

providing 150 μmol/m2

/s of light. Each microcosm was filled with 100 ml of growth 
72

medium. The media were changed daily. At the beginning and at the end of the 

experiment small fragments of Vaucheria sp. mats were gently patted dry with a paper 

towel, while held in between a Nitex screen, to remove excess water, and weighed (fresh 

mass). At the end of the experiment all samples were processed for dry mass (DM). At 

the beginning of each experiment 10 algal samples from each initial mass treatment were 

patted dry in between a Nitex screen, weighed to measure initial fresh mass (FM), dried 

in the oven, and weighed again (DM). This allowed for the calculation of the initial dry 

mass of the experimental samples based on their initial fresh mass. All samples for DM 

were dried in the oven at 105oC for 24 hours (Eaton et al. 1995). All experiments had a 

complete factorial ANOVA design with 2 experimental factors: nutrient concentration 

and initial biomass. Experiment 2 had a total of 15 treatments that were a combination of 

5 phosphate concentrations (PO4-P concentrations: 2, 10, 30, 60, 150 μg P/L) and 3 initial 

fresh mass levels (0.01g, 0.05g, 0.2g). The NO3-N concentration in experiment 2 was 

1000 μg/L. Experiment 4 had a total of 15 treatments that were a combination of 5 nitrate 

concentrations (NO3-N concentrations: 20, 125, 500, 1000, 2500 μg N/L) and 3 initial 

fresh mass levels (0.01g, 0.05g, 0.2g). The PO4-P concentration in experiment 4 was 100 

μg/L. Experiment 6 had a total of 15 treatments that were a combination of 5 ammonia 

concentrations (NH4-N concentrations: 20, 125, 500, 1000, 2500 μg N/L) and 3 initial 

fresh mass levels (0.01g, 0.05g, 0.2g). The PO4-P concentration in experiment 6 was 100 

μg/L. 

Relative growth rates 

Algal relative growth rate (RGR) in the large microcosm experiments was calculated 

using the following formula (Hunt 1990): 
73

In the small microcosm experiments, the algal initial and final filament length was used 

instead of algal mass. 

Growth media 

A new growth medium was developed based on the Z8 medium (Kotai 1972). The Z8 

medium was modified to simulate the median chemistry of macronutrients in Florida 

spring water (referred to as medium Z8Fl) (Appendix 1). We originally used Z8Fl Fe600 

medium that had the original concentration of iron (600 μg/L) found in the Z8 medium. 

Later we used Z8Fl Fe200 with the iron concentration reduced to 200μg/L, because we 

found an Fe concentration of 600μg/L to have a suppressing effect on the growth of 

Vaucheria sp. We used the Gaffron micronutrients mix as used by Kotai (1972). To 1L 

of the final growth medium we also added 10ml of CaCl2·2H2O solution (stock solution 

18.3g CaCl2·2H2O in 1L of deionized water), 10ml of MgSO4·7H2O solution (stock 

solution 7g MgSO4·7H2O in 1L of deionized water), and 10ml of Na2CO3 solution (stock 

solution 13.7g Na2CO3 in 1L of deionized water). We used NaNO3 and NH4Cl as 

sources of nitrogen and K2HPO4 as a source of phosphorus. When the NaNO3 gradient 

was investigated, NaCl was also added to keep the Na concentration constant in all of the 

treatments. In the experiments with K2HPO4, gradient KCl was added to keep the K 

concentration constant in all of the treatments, following the experimental design of 

(Ahlgren 1977). 

# of days

ln(Final Mass) ln(Initial Mass) RGR = −
74

Water analyses 

Water samples of prepared growth media and from experimental macrocosms were sent 

to FDEP for analyses. On last day of experiment a sample of water in which algae were 

growing for 24 hours was collected for analyses. 

Experimental conditions 

All experiments were conducted in the walk-in growth room. The temperature in the 

growth room was set for 22.5oC to reflect the average water temperature of the Florida 

springs. The minimum and maximum temperatures were recorded daily on a max-min 

thermometer. 

Identification of Vaucheria species 

Since the presence of reproductive structures is necessary to identify the species of 

Vaucheria from each batch of algae used in the experiments, we incubated a small 

fragment of the mat (Ott and Oldham-Ott 2003). The mat fragment was placed onto a 

Petri dish filled with Z8Fl growth medium with 100μg/L P and 1000μg/L N and placed 

by the window. We were successful in observing reproductive structures only in the 

samples collected from Manatee spring. The species was Vaucheria geminata (Prescott 

1982) 

Data analyses 

Data were analyzed using SAS statistical software (SAS 2000) (repeated measures 

ANOVA) and R statistical software (R Development Core Team 2006). Logistic 

regression analysis was conducted using drc package for R (Ritz and Streibig 2007). All 

final and initial filament length and small mat biomass data were first tested using 
75

repeated measures ANOVA to test the significance of nutrient effect and time effect 

(indicating algal growth). Next, factorial analysis of variance was used to test the effect 

of nutrient concentration and Vaucheria sp. population location on relative growth rates 

(RGR). A lowess smooth line was fitted through the data for general assessment of the 

trends in the data. If a significant nutrient effect was found in the ANOVA analysis, a 

logistic curve was fitted through the RGR data. If the logistic curve did not provide a 

good fit and data were distributed along a straight line, a linear regression was calculated. 

Various logistic models were fitted through the data (Ritz and Streibig 2005, Ritz and 

Streibig 2006) and the best fitting models are presented in the results. For our data, the 

best fitting models were: the four parameter logistic model (l4()), the four parameter 

logistic model with variance calculated as a power function of the mean to account for 

heterogeneity of the data (l4() varPower), the Monod model (calculated using code for 

the Michaelis-Menten model from the drc package) and the five parameter BrainCousens hormesis model (Borchardt 1996, Schabenberger et al. 1999, Ritz and Streibig 

2007). 

In allof the treatments in the small microcosm experiments we had filaments of 

Vaucheria sp. that did not grow at all. This is probably because Vaucheria sp. did not 

like to be handled. Precutting tips 2 days before the experiment partially resolved that 

problem, but we still had tips that did not grow. All initial data analysis was conducted 

on a complete dataset. With the 0 growth samples in our data set, we were not able to fit 

any of the logistic models. The results from the small microcosm experiments presented 

here are based on the dataset with the 0 growth samples removed (less then 10% of the 
76

whole dataset). The 0 growth samples were randomly found in our datasets. There was 

no relationship between the experimental treatments and number of 0 growth samples. 

All data sets were checked for normality and heterogeneity of variance, and where 

necessary, data were transformed for the ANOVA analyses. All analyses using drs 

package were conducted on the untransformed RGR data. 

Results 

Vaucheria sp. grew in all experiments under all nutrient concentrations. Relative growth 

rates (RGR) varied from 0 to 0.35. In the small microcosm experiments, probably 

partially due to the cutting of filaments, we observed large variability in the growth rates 

for each treatment. In the large microcosm experiments, high nutrient levels resulted in 

high RGRs of Vaucheria sp. 

Effects of PO4

In the small microcosm experiments, an increase in phosphate phosphorus had a 

significant effect on the growth of Vaucheria sp. (Fig 1). The relative growth rate data 

were well described by a logistic dose-response curve (Fig. 1, Table 2). The threshold 

concentration of phosphate phosphorus for the growth of Vaucheria sp. was 11.6 μg/L - 

the Effective Dose of 50% growth saturation (ED50). The two populations of Vaucheria

sp. that were studied did not differ in their RGRs (ANOVA for the location effect, 

P<0.418). 

In the large microcosm experiments, Vaucheria sp. mats with smaller initial biomass 

grew faster than larger mats in high phosphate concentrations (ANOVA for biomass 
77

effect, P<0.001) (Fig.2). Dose response curves were fitted through the 0.01g and 0.05g 

initial biomass data. The threshold nitrogen concentration was 36.7 μg/L for the 0.01g 

initial biomass and 33.7 μg/L for the 0.05g initial biomass (Fig.2, Table 3). 

Effect of NO3 

Inthe small microcosm experiments, an increase in nitrate nitrogen did not have an effect 

on the growth of Vaucheria sp. (Fig. 3). The two populations of Vaucheria sp. that were

studied did not differ in their RGRs (ANOVA for the location effect, P<0.742). 

In the large microcosm experiments, Vaucheria sp. mats with smaller initial biomass 

grew faster than larger mats (ANOVA for biomass effect, P<0.001) (Fig.4). Dose 

response curves were fitted through the data. The threshold nitrogen concentrations were 

210 μg/L for the 0.01g initial biomass, 208 μg/L for the 0.05g initial biomass, and 499 

μg/L for the 0.2g initial biomass (Fig.4, Table 3). 

Effect of NH4

In the small microcosm experiments, an increase in ammonia nitrogen resulted in 

increased growth rates up to approximately 500 μg/L NH4-N concentration, where it 

reached the highest growth rate of 0.25 mm/mm/day (Fig. 5). The RGR data were well 

described by the Brain-Cousens hormesis curve (Fig. 5, Table 2). 

In the large microcosm experiments, Vaucheria sp. mats with smaller initial biomass 

grew faster than larger mats in 200, 500 and 1500 μg/L ammonia concentrations 

(ANOVA for biomass effect, P<0.001) (Fig.6). Brain-Cousens hormesis curves were 

fitted through the data, and a good fit was achieved for the initial biomass of 0.01g and 

0.05g (Fig.6, Table 3). A high ammonia concentration of 5000 μg/L resulted in reduced 
78

growth rates and, in 4 cases, death of the mats and/or due to take over by coccoid 

cyanobacteria. 

Combined effect of NO3 and NH4

In the small microcosm experiment, nitrogen was added as a combination of the two 

forms: ammonia and nitrate. Neither ammonia nor nitrate nitrogen had an effect on the 

growth of Vaucheria sp. (ANOVA for NO3 effect, P<0.797, for NH4 effect P<0.584) 

(Fig.7). Further, no effect was observed when both forms of nitrogen were summed and 

the growth of Vaucheria sp. was analyzed as a function of an absolute concentration of 

nitrogen (Fig. 8). 

Discussion 

Vaucheria sp. is usually found at locations with high nutrient concentrations. Leukart 

and Hanelt (1995) found Vaucheria bursata in a stream in Germany at phosphate 

concentrations above 200 μg/L and nitrate concentrations above 1700 μg/L Sabater et al. 

(2003), in his study of algal mats in the Llobregat River in Spain, found Vaucheria 

bursata at even higher levels of phosphate (400μg/L) and nitrate (3900 μg/L). In this 

laboratory study, we found a threshold concentration of phosphorus to be in the range 

from 11.6 to 36.7 μg P/L, and we also found that larger mats required higher phosphorus 

levels. The nitrate threshold concentrations were from 208 to 499 μg N/L. When 

ammonia was used as a source of nitrogen, we observed an increase in growth rates 

above 50 μgN/L. Above 1000 μgN/L, however, ammonia became toxic and growth rates 

were reduced (Fig. 5). Vaucheria sp. used ammonia and nitrate as a source of nitrogen 
79

and we did not observe any preference for either. Ozimek (1990), in laboratory 

experiments, grew mat fragments of Vaucheria dichotoma and found higher growth rates 

in higher nutrient concentrations. The relative growth rates calculated based on 

Ozimek’s (1990) data were in the lower range of those observed in this study ((0.01-0.05 

mg/mg/day dry weight). 
80

References 

Aboal, M., M. Prefasi, and A. D. Asencio. 1996. The aquatic microphytes and 

macrophytes of the transvase Tajo-Segura irrigation system, southeastern Spain. 

Hydrobiologia 340:101-107. 

Ahlgren, G. 1977. Growth of Oscillatoria-Agardhii in Chemostat Culture .1. Nitrogen and 

Phosphorus Requirements. Oikos 29:209-224. 

Biggs, B. J. F. 1996. Patterns in benthic algae of streams. Pages 31-56 in R. J. Stevenson, 

M. L. Bothwell, and R. L. Lowe, editors. Algal ecology. Academic Press, San 

Diego. 

Borchardt, M. A. 1996. Nutrients. Pages 183-227 in R. J. Stevenson, M. L. Bothwell, and 

R. L. Lowe, editors. Algal ecology. Academic Press, Sand Diego. 

Davis, J. S., and W. F. Gworek. 1973. Rotifer Parasitizing Vaucheria in a Florida Spring. 

Transactions of the American Microscopical Society 92:135-140. 

Eaton, A. D., L. S. Clesceri, and A. E. Greenberg, Eds. 1995. Standard methods for the 

examination of water and wastewater, 19th edition. American Public Health 

Association, Washington, D.C. 

Entwisle, T. J. 1990. Macroalgae in the Upper Yarra and Watts River Catchments - 

Distribution and Phenology. Australian Journal of Marine and Freshwater 

Research 41:505-522. 

Hunt, R. 1990. Basic growth analysis. Unvwin Hyman Ltd., London. 

Kotai, J. 1972. Instructions for preparation of modified nutrient solution Z8 for algae. 

Norwegian Institute for Water Research, publication B-11/69., Blindern, Oslo. 

Lakatos, G. 1978. The phenomenon and significance of benthonic eutrophication in Lake 

Velencei, Hungary. Acta Biological Debrecina 15:147-168. 

Leukart, P., and D. Hanelt. 1995. Light requirements for photosynthesis and growth in 

several macroalgae from a small soft-water stream in the Spessart Mountains, 

Germany. Phycologia 34:528-532. 

Manoylov, K. M. 2005. Ecological strategies of benthic diatoms for nutrient competition. 

Ph.D. Dissertation. Michigan State University, East Lansing. 

McIntire, C. D., H. K. Phinney, G. L. Larson, and M. Buktenica. 1994. VerticalDistribution of a Deep-Water Moss and Associated Epiphytes in Crater Lake, 

Oregon. Northwest Science 68:11-21. 

Moreno, J. L., M. Aboal, M. R. Vidal-Abarca, and M. L. Suarez. 2001. Macroalgae and 

submerged macrophytes from fresh and saline waterbodies of ephemeral streams 

('ramblas') in semiarid south-eastern Spain. Marine and Freshwater Research 

52:891-905. 

Necchi, O., D. Pascoaloto, and L. H. Z. Branco. 1994. Distribution of Macroalgae in a 

Tropical River Basin from Southeastern Brazil. Archiv Fur Hydrobiologie 

129:459-471. 

Ott, D. W., and C. K. Oldham-Ott. 2003. Eustigmatophyte, raphidophyte, and tribophyte 

algae. Pages 423-469 in J. D. Wehr and R. G. Sheath, editors. Freshwater algae of 

North America. Academic Press, San Diego. 

Ozimek, T. 1990. Aspects of the ecology o filamentous alga in a eutrophicated lake. 

Hydrobiologia 191:23-27. 
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Prescott, G. W. 1982. Algae of the Western Great lakes Area. Otto Koeltz Science 

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24 in. 

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Ecological implications of mass growth of benthic cyanobacteria in rivers. 

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82

Fig 1 

Relative growth rate (RGR) of Vaucheria sp. in different phosphate phosphorus 

concentrations (n=65). A four parameter logistic curve was fitted through the data from 

the small microcosm experiments (experiment 1). Curve parameters are in Table 2. 
83

Fig. 2 

Relative growth rate (RGR) of Vaucheria sp. in a factorial experiment with 3 initial 

biomass levels (0.01g, 0.05g, 0.2g) and 5 phosphorus concentrations (n=45). A four 

parameter logistic curve and a regression line (initial biomass 0.2g R2

=0.048, P<0.433) 

were fitted through the data from a large microcosm experiment (experiment 2). Curve 

parameters are in Table 3. 
84
85

Fig. 3 

Relative growth rate (RGR) of Vaucheria sp. in different nitrate nitrogen concentrations 

(n=68). Linear regression was fitted through the data from a small microcosm 

experiment (experiment 3) (R2

=0.01, P<0.414). 
86

Fig. 4 

Relative growth rate (RGR) of Vaucheria sp. in a factorial experiment with 3 initial 

biomass levels (0.01g, 0.05g, 0.2g) and 5 nitrogen concentrations (n=45). Four parameter 

logistic curves were fitted through the data from a large microcosm experiment 

(experiment 4). Curve parameters are in Table 3. 
87

Fig. 5 

Relative growth rate (RGR) of Vaucheria sp. in different ammonia nitrogen 

concentrations (n=58). Five parameter Brain-Cousens hormesis logistic model was fitted 

through the data from small microcosm experiment (experiment 5). Since missing data 

did not allow the calculation of the full model, point of inflection e was set at 500 μg/L 

after analysis of lowess smooth line. Curve parameters in Table 2. 
88
89

Fig. 6 

Relative growth rate (RGR) of Vaucheria sp. in a factorial experiment with 3 initial 

biomass levels (0.01g, 0.05g, 0.2g) and 5 ammonia concentrations (n=41). Five 

parameter Brain-Cousens hormesis logistic model was fitted through the data from a 

large microcosm experiment (experiment 6). Since missing data from the 5000 μg/L 

treatment did not allow the calculation of the full model, point of inflection e was set at 

800 μg/L after analysis of lowess smooth lines. Curve parameters are in Table 3. 
90
91

Fig. 7 

Boxplot of relative growth rates (RGR) of Vaucheria sp. in a combination of different 

ammonia and nitrate nitrogen concentrations (experiment 7). 
92

Fig. 8 

Relative growth rate (RGR) of Vaucheria sp. in different nitrogen (sum of NO3-N and 

NH4-N) concentrations (n=99). Linear regression was fitted through the data from a 

small microcosm experiment (experiment 7) (R2

=0.03, P<0.097). 
93

Table 1 

Vaucheria sp. experiments. Experiment numbers in parenthesis refer to numbers used in 

the 2006 report. 

Experiment 

(project 

experiment 

number) 

Micro

cosm 

Nutrient 

gradient 

Algae collection location Season Growth 

medium 

Mean min 

and max 

temperature 

(oC) 

1 (21) 

2 (7) 

3 (20) 

4 (9) 

5 (4) 

6 (11) 

7 (2) 

Small 

Large 

Small 

Large 

Small 

Large 

Small 

PO4-P 

PO4-P 

NO3-N 

NO3-N 

NH4-N 

NH4-N 

N (NH4

and 

NO3) 

Ichetucknee and Alexander 

Ponce de Leon 

Ichetucknee and Alexander 

Alexander 

Manatee 

Ponce de Leon 

Manatee 

Spring 

Winter 

Spring 

Spring 

Summer 

Winter 

Fall 

Z8Fl Fe200 

Z8Fl Fe200 

Z8Fl Fe200 

Z8Fl Fe200 

Z8Fl Fe600 

Z8Fl Fe200 

Z8Fl Fe600 

21.4 &24.9 

20.2 & 24.0 

21.3 &24.9 

20.8 & 22.3 

20.7 & 24.8 

20.2 & 23.8 

20.8 & 24.4 
94

Table 2 

Parameters of the logistic dose-response model applied to the Vaucheria sp. RGR data 

from small microcosm experiments, where d and c denote the upper and lower limit of 

algae growth rates at zero and infinite concentrations of nutrient. ED50 (also called e) 

denotes the concentration required to increase the algal growth rate by half between the 

upper and lower limits and b is proportional to the slope (the rate of change) of the curve 

around ED50. Significant parameters are in boldface. ED10 and ED90 denote the 

concentration required for 10% and 90% growth saturation. For the Brain-Cousens 

hormesis model, c and d are the upper and lower asymptote of the response. The 

columns designated b and e are related to the rate of change and the point of inflection of 

the curve respectively; and f indicates the initial rate of increase at low concentrations. 

Nutrien

t 

Model d 

(mm/mm/

day) 

c

(mm/mm/

day) 

b ED50 (μg/L) 

e 

ED90 (μg/L) 

or f

ED10 (μg/L) 

PO4 

NH4

l4() 

Brain-Cousens 

0.27±0.01 

0.03±0.01 

0.16±0.01 

0.08±0.01 

-3.54±1.68 

5.40±1.54 

11.59±2.59 

set at 500

21.53±8.19 

0.0004±0.0001 

6.24±2.22 

- 
95

Table 3 

Parameters of the logistic dose-response model applied to the Vaucheria sp. growth 

response data from large microcosm experiments, where d and c denote the upper and 

lower limit of algae growth rates at zero and infinite concentrations of nutrient. ED50

denotes the concentration required to increase the algal growth rate by half between the 

upper and lower limits and b is proportional to the slope of the curve around ED50. 

Significant parameters are in boldface. ED10 and ED90 denote the concentration required 

for 10% and 90% growth saturation. For the Brain-Cousens hormesis model, c and d are 

the upper and lower asymptote of the response. The columns designated b and e are 

related to the rate of change and point of inflection of the curve respectively; and f 

indicates the initial rate of increase at low concentrations. 

Appendix 1 

Z8Fl medium was derived from Z8 medium (Kotai 1972) for the culture of filamentous 

algae from Florida springs. It was adopted to reflect the Florida springs’ water chemistry. 

The concentrations of nitrogen and phosphorus were reduced and the concentrations of 

calcium, magnesium and bicarbonate were increased. The original Z8 medium had an Fe 

concentration of 600μg/L. We found that this concentration reduced the growth rates of 

the algae, and we later used a concentration of 200μg/L. We used the original 

Nutrient and 

biomass 

Model d

(g/g/day) 

c

(g/g/day) 

b ED50 (μg/L) 

e 

ED90 (μg/L) 

of f

ED10 (μg/L) 

PO4 x 0.01g 

PO4 x 0.05g 

NO3 x0.01g 

NO3 x0.05g 

NO3 x0.2g 

NH4 x 0.01g 

NH4 x 0.05g 

l4() 

l4() 

l4() 

l4() 

l4() 

Brain-Cousens 

Brain-Cousens 

0.15±0.02 

0.11±0.02

0.25±0.01 

0.19±0.01

0.11±0.01 

0.11±0.01 

0.07±0.01

0.02±0.01 

0.06±0.01 

0.10±0.01 

0.07±0.01

0.05±0.01 

0.06±0.00 

-0.02±0.0 

-2.89±1.34

-2.71±3.60

-1.96±0.42

-1.25±0.43

-4.13±2.87

1.78±0.31 

1.67±0.59 

36.68±8.95 

33.67±20.61 

210.3±30.4 

207.8±56.6

499.2±68.9 

set at 800 

set at 800 

78.37±40.24 

75.78±107.9 

644.0±202.2 

1200±797.0 

849.9.5±315.1 

0.00028±0.00007 

0.00024±0.00001 

17.17±5.55 

14.96±15.31 

68.67±16.62 

35.97±23.92 

293.2±122.4 

- 

- 
96

concentration of microelements, but for future work this concentration probably should 

be reduced to one-half of the original concentration, because we found that the original 

concentration of microelements was limiting the growth of Lyngbya wollei. Solutions 1 

and 2 were filter sterilized. Solution 5 was autoclaved. 

To prepare 1 L of Z8Fl medium, fill a flask with 957ml of deionized water (DIH2O), then 

add solutions 3, 4, 6 and 7 and autoclave. After autoclaving add solutions 1, 2, and 5. 

The prepared medium should be left for 24 hours for the gases to equalize. The target pH 

concentration should be around 8.5. The pH might have to be adjusted to that value. 

1. Fe-EDTA 10ml (can be used at reduced level, then use 3ml) 

10ml ●FeCl3 solution (2.8 g FeCl3·6H2O dissolved in 100ml 0.1N HCl) and 

9.5ml from an ●EDTA-solution (3.9g EDTA-Na2 dissolved in 100 ml 0.1N NaOH) 

mixed and filled up to 1000ml with distilled water. 

2. Gaffron’s trace element solution 1ml (can be used at reduced level, then use 0.5ml) 

Stock solutions (kept separate) 

Each in g in 100ml DIH2O 

●ZnSO4·7H2O 0.287 g

●(NH4)6Mo7O24·4H2O 0.088 g

●Co(NO3)2·6H2O 0.146 g

●VOSO4·6H2O 0.035 g

●Al2(SO4)3K2SO4·2H2O 0.474 g

●NiSO4(NH4)2SO4·6H2O 0.198 g

●Cd(NO3)2·4H2O 0.155 g

●Cr(NO3)3·7H2O 0.037 g

●Na2WO4·2H2O 0.033 g

●KBr 0.119 g

●KI 0.083 g

●Cu(SO4)·5H2O 0.125 g

Take 10ml of each solution. 

●H3BO3 3.10 g and MnSO4·H2O 1.69 g in 1L DIH2O. Take 100ml. 
97

Final trace element stock solution: 12x10ml + 100ml + DIH2O (780 ml) to 1L. 

3. NaNO3 solution 1ml 

● 6.1g NaNO3 in 1L DIH2O 

4. K2HPO4 solution 1ml

● 0.56g K2HPO4 in 1L DIH2O 

5. CaCl2·2H2O solution 10ml

● 18.3g CaCl2·2H2O in 1L DIH2O 

6. MgSO4·7H2O solution 10ml

● 7g MgSO4·7H2O in 1L DIH2O 

7. Na2CO3 solution 10ml

● 13.7 g Na2CO3 in 1L DIH2O 

References 

Kotai, J. 1972. Instructions for preparation of modified nutrient solution Z8 for algae. 

Norwegian Institute for Water Research, publication B-11/69., Blindern, Oslo.