School of Natural Sciences
Degree project work in biology
Kristofer Bergström Subject: Marine Biology Level: D
Rapid Changes in Salinity and
Cyanobacterial Exposure
Influence Condition of Young of the Year
(YOY) Perch (Perca fluviatilis);
a Field Study in the Curonian Lagoon
(Lithuania).
Rapid Changes in Salinity and Cyanobacterial Exposure Influence
condition of Young of the Year (YOY) Perch (Perca fluviatilis);
a Field Study in the Curonian Lagoon(Lithuania).
Kristofer Bergström
Degree project work in marine biology, 45 hp for Master of Science.
Supervisors: Professor Catherine Legrand, Linnæus University; PhD-student Karl-Johan Persson, Linnæus University.
Examiner: Professor Roland Engkvist, Linnæus University.
Abstract
Two decades ago the recruitment of YOY perch (Perca fluviatilis) started to decline along the Swedish east cost of the Baltic Sea. Factors that influence recruitment are e.g.
eutrophication that causes habitat losses and overfishing of cod (Gadus morhua) which causes cascading effects in the food web. Filamentous cyanobacterial blooms are often toxic and has increased in the Baltic Sea and its coastal waters. The aim of this field study was to evaluate the effects of salinity and cyanobacterial exposure on fitness related parameters of young of the year (YOY) perch (Perca Fluviatilis) in a natural environment. Our study was performed in the Curonian Lagoon (Lithuania) in August 2009. The lagoon offers a temporary salinity gradient (wind induced influxes from the Baltic Sea) ranging from 7 psu in the north to 0 psu in the south. Submerged enclosures containing YOY perch were set up at three different locations along the salinity gradient in the Lagoon (referred to as North, Middle, South). The duration of the experiment was 21 or 27 days, depending on treatment.
Measurements of perch condition were specific growth rate, somatic condition index (SCI) and whole fish lipid and protein content. Average chl a values for the three stations during the experimental time were: north 180 ± 70 µg/l chl a, middle 133 ± 36 µg/l chl a and south 180 ± 52 µg/l chl a. The North and the Middle stations experienced two different salinity influxes reaching a maximum salinity of 6.5 psu at the northern station. The duration of each saline influx was approximately 4-6 days. The saline water did not reach the Southern station at any time. Results show that perch from the southern station were in best condition in terms of specific growth rate and contents of total lipids. Compared to the South the perch condition declined to the Middle station and was lowest at the Northern station which experienced the highest degree of fluctuation in terms of salinity and cyanobacterial exposure. Examination of the abundance of the main food resource at the different stations revealed no statistical differences, which suggest that availability of food was not a factor in explaining the differences in growth. The results possibly indicates that a changing environment with the potential synergistic negative effects of salinity and cyanobacteria has a higher negative impact on YOY perch condition compared to constantly high concentrations of cyanobacteria.
2
Swedish summary
För två årtionden sedan började rekryteringen av Abborre (Perca fluviatilis) årsyngel att minska längs med den svenska östkusten. Faktorer som påverkar rekryteringen är exempelvis övergödning som orsakar habitat förluster samt överfisket av Torsk (Gadus morhua) som orsakar kaskad effekter i närningskedjan. Filamentösa cyanobakterie blomningar är oftast toxiska och dessa har ökat i Östersjöns kustvatten. Målet med denna fältstudie är att utvärdera effekterna av salthalt och cyanobakterier på fitness relaterade parametrar hos abborre (Perca Fluviatilis) årsyngel i en naturlig miljö. Studien utfördes i den Kuriska sjön (Litauen), som erbjuder en salthalts gradient (vind inducerade inflöden från östersjön) från 7 psu in nord till 0 psu i de södra delarna. Undervattens burar som innehöll årsyngel av abborre placerades vid tre olika stationer (kallade Nord, Mitt och Syd) längs med lagunen. Försöken varade i 21 eller 27 dagar, beroende på behandling. Parametrar för abborre kondition var specifik tillväxt, somatiskt konditions index (SCI) samt hel fisks lipid och protein innehåll. Medelvärden för klorofyll a koncentrationen för de tre stationerna var, Nord 180 ± 70 µg/l chl a, Mitt 133 ± 36 µg/l chl a och Syd 180 ± 52 µg/l chl a. Nord och Mitt stationerna upplevde två olika saltvattens inflöden med en maximal salthalt på 6,5 psu vid den norra stationen. Inflödena varade mellan 4-6 dagar. Saltvattnet nådde inte vid något tillfälle den södra stationen. Resultaten visar att abborre från den södra stationen hade bäst kondition i termer av specifik tillväxt samt lipid innehåll. Jämfört med den södra stationen minskade abborre konditionen till den mittersta stationen och var lägst vid den norra som utsattes för den högsta graden av fluktuationer i salthalt och cyanobakterie exponering.
Undersökning av förekomsten av den huvudsakliga födoresursen vid de olika stationerna uppvisade inga statistiska skillnader, vilket antyder att födotillgång inte var en faktor till tillväxtskillnaderna. Resultatet antyder möjligen att en föränderlig miljö med möjliga synergi effekter från salthalt och cyanobakterier har en högre negativ påverkan på abborre årsyngels kondition jämfört med konstant höga cyanobakterie koncentrationer.
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Table of contents
1 Introduction 4
2 Material and methods 6
2.1 Rearing of perch 6
2.2 Study site 6
2.3 Analysis 8
2.3.1 Lipid content 8
2.3.2 Protein content 9
2.3.2 Statistics 9
3 Results 10
3.1 Mortality and the food resource experiment 10
3.2 Chlorophyll a and salinity 10
3.3 Parameters of condition for YOY perch 12
3.3.1 Lipid and protein content 12
4 Discussion 15
5 Conclusions 18
6 Acknowledgments 18
7 References 19
8 Appendix 1 23
4
1 Introduction
In the Baltic Sea decreasing recruitment of pike (Esox lucius) and perch (Perca fluviatilis) has been observed in the Kalmar sound, the outer Stockholm archipelago, the coast of Gotland and the coast of Finland including Åland (Ljunggren et al. 2005). Possible explanations for the decreasing recruitment could be habitat changes (biological and physical), food availiability for juvenile fish, predation, parasites, disease, overfishing and environmental pollutants (Ljunggren et al. 2005). Eutrophication is often connected to both positive and negative habitat changes for fish as in availability of spawning grounds and structural refuge for juvenile fish. The magnitude of eutrophication has increased the last decades due to that the Baltic Sea has a large drainage area with about 85 million human inhabitants; this generates large outputs of nitrogen and phosphorus through riverine inputs to the Baltic Sea. Riverine inputs together with atmospheric deposition, nitrogen fixation and point sources create an excess of nutrients, which contributes to the increasing eutrophication that can manifest as increased cyanobacterial blooms during the summer (Kononen et al., 2001). Cyanobacteria may also affect fish recruitment by reducing fish survival and condition either directly (toxicity, turbidity, changes in pH and oxygen levels, Karjalainen et al. 2005; Engström-Öst et al. 2006; Ljunggren et al. 2007; Persson et al. 2010) or indirectly (toxin transfer via copepods, reduced nutritional value of copepods and changes in the zooplankton community, Demott et al.1991, Ahlgren et al. 1992, Koski et al. 1999, Lehtiniemi et al. 2002, Kozlowsky-Suzuki et al. 2003, Karjalainen et al. 2003, Ruokalainen et al. 2006). These negative impacts have been shown in laboratory studies but corresponding studies in the field are to my knowledge nonexisting. The objective with our study was to investigate how perch fitness related parameters (in this study specific growth rate, whole fish lipid and protein content) is affected by living along a salinity gradient with its respective cyanobacterial community and their toxins in a natural environment.
The species in our study was Eurasian perch (Perca fluviatilis), which is a piscivorous fish that is widespread in coastal areas along the Baltic Sea. Spawning takes place in April-June in shallow waters, often with reeds, in the coastal zone (Andersson, 2009). The male is sexually mature at 2-4 years of age while the female matures after 3-5 years (Andersson, 2009).
Perch consume different prey at different developmental stages; juveniles initially feed on zooplankton but switch diet to benthic prey and finally become a piscivore as an adult (Andersson, 2009). Energy reserves are predominantly stored as fat, protein and glycogen.
Glycogen is the first and fastest reserve to be utilized, followed by fat and lastly proteins (Jobling 1980; Collins and Anderson 1995; Evans and Claiborne 2006). For many fishes including perch it has been shown that the major energy reserve, lipids, vary with size and have a positive correlation with increasing fish size (Sogard and Olla, 2000; Biro et al., 2004;
Borcherding et al., 2007; Heermann et al., 2009). Low contents of lipids and proteins in fish or embryos may be used as an early indicator in fish to environmental stress (Mayer et al.
1992).
5 Perch (Perca fluviatilis) is a fresh and brackish water species with an upper salinity tolerance of 10-15 psu (Lutz, 1972). The optimal salinity for growth of YOY (young of the year) perch has been shown to range between 0-5 psu (Ložys, 2004; Overton et al., 2008; Tibblin, 2009).
When comparing salinity effects between freshwater populations and saline water populations no conclusive local adaptations have been shown so far (Ložys, 2004; Overton et al., 2008; Tibblin, 2009). It is generally considered that by rearing fish near their iso-osmotic point there is energy saving effects (Gaumet et al., 1995; Boeuf and Payan, 2001), due to reduction in energy cost of ion regulation (Brett, 1979; Jobling, 1994). However, there are several examples of fishes reared in iso-osmotic conditions, or close iso-osmotic conditions, where a reduction in growth has been shown (Wang et al., 1997; Altinok & Grizzle, 2001;
Overton et al., 2008; Tibblin, 2009). The reduction in growth at isotonic salinity has been hypothesized to be due to reduced food consumption (loss of appetite) and/or reduced food conversion efficiency (Wang et al., 1997; Overton et al., 2008). The effects of rapid salinity changes on fishes and especially on perch are a subject that is scarcely studied. In a study on Spot (Leiostomus xanthurus) and Croaker (Micropogonias undulatus) it has been shown that smaller (<70mm) fish are more sensitive to rapid salinity changes and need longer time to adjust compared to larger ones (Moser and Lawrence, 1989). Another study on Sheepshead minnow (Cyprinodon variegatus variegatus) indicates that individuals that previously have experienced rapid salinity changes regulate plasma osmolality better than inexperienced individuals (Haney 1999).
Another factor of our interest influencing YOY perch condition is cyanobacterial exposure.
During the summer time the Curonian Lagoon is dominated by cyanobacteria (Pilkaitytè 2007) with blooms under favorable weather conditions (Paldaviciene et al. 2009). Because of the influx from the Baltic Sea the brackish water species Nodularia spumigena has been documented in the northern part of the Lagoon (Paldaviciene et al. 2009). The toxin nodularin from Nodularia spumigena and four microcystins (MC-LR, MC-RR, MC-LY, MC-YR) from Microcystis aeruginosa have been detected in the lagoon (Paldaviciene et al. 2009).
Cyanobacteria have both direct and indirect effects on fish. Direct effects include toxicity, increased turbidity, changes in pH and oxygen levels while indirect effects are a lowered nutritional value in zooplankton, changes in zooplankton composition and toxin transfers through the food chain. Cyanobacteria contain several bioactive compounds such as peptides, alkaloids and lipopolysaccharides (Carmichael, 1994, Codd et al. 2005). The dominating bloom-forming cyanobacteria in the Baltic Sea produce different types of toxins.
Nodularia spumigena produces a hepatotoxin called nodularin, whereas Anabaena produces a neurotoxin called anatoxin-a. Aphanizomenon has not been identified as a toxin producer in the Baltic Sea. The freshwater species Microcystis aeruginosa produces toxins called microcystins. Cyanotoxins are released to the surrounding water during cell lysis which might occur during rapid salinity changes (Codd et al. 2001; Cazenave et al. 2005). This means that fish might be exposed to cyanotoxins by ingestion of cyanobacteria cells, dissolved toxins or contaminated food. Previous studies of fish exposed to cyanobacteria
6 have shown reduced growth in perch and brown trout (Salmo trutta) (Bury et al. 1995;
Persson et al. 2010), decreased feeding rate in perch and pike (Karjalainen et al. 2005;
Engström-Öst et al. 2006; Persson et al. 2010), increased mortality and developmental abnormalities in loach (Misguruns mizolepis) (Liu et al. 2002a), in zebra fish (Oberemm et al.
1997) and in carp (Cyprinus carpio) (Palíkova et al. 2003).
Cyanobacterial blooms lead to increased water turbidity which can affect juvenile fishes more than adults because of their lower mobility (Engström-Öst et al. 2006). Increased water turbidity negatively affects perch foraging ability by impaired vision and/or clogging of the gills (Engström-Öst et al. 2006; Karjalainen et al. 2006; Ljunggren et al. 2007). Turbidity involve an energy cost on perch that may lead to a lowered growth rate compared to clear waters (Ljunggren et al. 2007; Persson et al. 2010).
2 Material and methods
2.1 Rearing of perch
The perch used in this field study originated from the Hossmo River that flows into the Kalmar sound (southeast Sweden). During May 2009 roe strings were collected from wildspawners (10 different mothers) and reared in individual aquaria’s (20 L). During the first 4-6 weeks the perch larvae were fed Artemia nauplii four times a day until saturation. 5 ml of Artemia cysts (Advanced hatchery technology, Inc, USA.) were put into 1 L bottles containing deionized water and 45 g of seasalt (Coralife ©). The bottles were heavily aerated and heated (25 Co) with a 250 Watt lamp. Artemia naupli were harvested every 24 hours.
After six weeks the diet was switched to Blood worms (Chironomidae larvae) four times a day until saturation, this was continued until departure for Lithuania. During the transport from Sweden to Lithuania (36 h) the perch were kept in aerated aquaria´s (20 L) and water exchanges were performed with 4-6 hours intervals. During the journey the perch were fed Blood worms four times a day until saturation.
2.2 Study site
Our study was performed in the Curonian Lagoon (Fig. 1), in Lithuania, during August 2009.
The Curonian Lagoon is situated in the south east part of the Baltic Sea and it is separated from the Baltic Sea by a long sand strip called the Curonian spit. Politically the lagoon is divided between Lithuania (north) and Russia, Kaliningrad (south). The Curonian lagoon is the largest lagoon in the Baltic Sea and covers an area of 1584 km2 and has an average depth of 3.7 m. Wind induced influxes from the Baltic Sea occasionally cause temporary saline intrusions in the northern parts but otherwise the lagoon is considered a freshwater basin.
This temporary salinity gradient (0-7 psu) makes the Curonian Lagoon an ideal model system of the Baltic Sea and its properties. Enclosures containing YOY perch were placed at three stations along the Curonian spit, North (N 55º37.835’ S 021º07.951’), Middle (N 55º31.341’ S 021 º06.969), and South (N 55º19.255’ S 021º01.422’). The enclosures were placed in the littoral zone at a depth of 0.8-1 m.
7 Figure 1: To the left showing the Baltic Sea and its neighbouring countries. The middle map shows the whole Lagoon (earthobservatory.nasa.gov/IOTD/view.php?id=8179). To the right the Lithuanian part of the Curonian spit with the experimental sites, north, middle and south, indicated by red dots
(http://www.bicycle.lt/images/seaside/maps/EN2.jpg). The salinity scale to the right indicates the possible salinity range during a saline influx from the Baltic Sea.
The enclosures for the perch were made of plastic aquaria´s (20 L, 35*28*20 cm, Appendix Fig. 7). All sides except the lid were cut out (short sides 16*12 cm, long sides 25*12 cm and bottom 24*18 cm) and replaced with nylon nets. One treatment had nets of 200 µm (referred to as “fine”) and the other of 2000 µm (“rough”) mesh size. The Fine mesh size let algae pass trough but were not permeable to larger prey while the rough net were permeable to both prey and algae. Perch in the Rough experiment were living on food resources that entered the enclosures through the net while the perch in the Fine experiment were handfed equal amounts of blood worms. The Fine experiment was used in order to exclude differences in food density as a potential factor determining perch growth.
Before starting the experiment fish length and weight (ten individuals from each mother) were measured and used as initial value for growth calculations (Length 24.3±1.3 mm, weight 0.138±0.034 g). Enclosures with Fine net were placed in the North and South stations. Ten cages containing fifteen perch from the same mother each were placed at each station (Tab. 1). YOY perch were distributed at the stations and experiments according to Tab. 1.
Table 1: Schematic table of the experimental setup of YOY perch in both the Rough and the Fine experiment.
Station Rough (27 days) Fine (21 days) North 15 YOY * 10 mothers 15 YOY * 10 mothers Middle 15 YOY * 10 mothers None
South 15 YOY * 10 mothers 15 YOY * 10 mothers
8 The ten enclosures at each station were tied with ropes to a line fixed along the bottom.
(Appendix 1, Fig 6). Each individual enclosure was floating 30 cm below the surface and there was 0.8 m between each enclosure (Fig. 6). The fine enclosures were in the water during 21 days while the rough meshed enclosures were submerged for 27 days. The perch in each enclosure was counted every second day and when deviation (due to mortality) in density was detected, random individuals were removed from the other stations mother specific enclosures. The perch from all experiments were measured in length and weight after ending the field study. Whole fish were frozen (-20oC) until further analysis of protein and lipids.
Water samples for chlorophyll a (chl a) were collected every second day inside and outside the enclosures. Salinity was also measured every second day using a refractometer (Atago ATC-S/Mill-E). Water temperature, O2 and pH were measured with five days interval.
The densities of the main food source for the perch (Gammarus spp.) was investigated between the different stations. Empty perch enclosures were added to each experimental site (north, middle and south) and after two days all Gammarus that had entered them were collected and frozen (-20 o C). This was repeated three times and the collected Gammarus were later oven dried (60 o C, 24 h) and their weights determined.
2.3 Analysis
Specific growth for both length and weight was calculated by comparing with the initial measurements taken prior to the experiment. Somatic weight (weight of body and liver, SW) was also measured. SW was then used to calculate a Somatic Condition Index (SCI) by the formula (100*SW/(Length/10)3 (Bagenal et al., 1978, cited by Lozys, 2004).
Chl a was measured by filtration (glass fiber filters, Pall 25 mm), extraction (96 % ethanol for 24 h) and measured in a flurometer (Turner designs trilogy, model 040). The measured absorbance from the water samples was adjusted to Chl a µg/L by the formula:
Chl a (µg/L) = ((measured absorbance * ethanol ml) / filtered volume ml) * the dilution.
2. 3.1 Lipid content
YOY perch were analysed for lipid content using the Bligh-Dyer method (Bligh and Dyer, 1959). The Bligh-Dyer method is based on homogenization of a fish in a mixture of water, methanol and chlorophorm (1:1:2). The lipids are dissolved in the chloroform phase. A fraction of the lipid phase is transferred to a test tube with known weight and left for evaporation to only have lipids remaining. YOY perch were analysed according to the schematic table following (Tab. 2). Differences in fish size lead to differences in extracted volume after filtration which was later on weighted. A correction coefficient was created using the linear relationship between percentage lipids and aliquot volume. The correction coefficient was applied to the lipid analysis from the Fine experiment.
9 Table 2: Schematic table of the lipid and protein analyses.
The rough experiment contained larger fish that did not cause any differences in aliquot volume. The correction factor created for different aliquot volumes was -0,016 % per increased µl of aliquot volume.
2. 3.2 Protein content
YOY perch were analyzed for protein content according to Table 2. The protein analyses were performed according to Bradford’s method (Bradford, 1976). Whole fishes where homogenized in a KH2PO4 buffer (pH 7.3), proteins were dyed (Protein reagent from Bio-Rad Laboratories Inc. (Catalog No. 500-0006)) and the solutions absorbance measured in a spectrophotometer. Absorbance was plotted on a standard curve created from known protein concentrations (Bovine serum albumin, BSA).
2.3.3 Statistics
Statistical analyses were performed in SPSS Statistics 17.0. Students T-tests were used to analyse the Fine experiment while ANOVA´s that were used for the Rough and these were blocked for mothers (mothers were used as a random factor), meaning that siblings from the different stations were compared to each other. The randomized design was used due to high variation in the response variables because of maternal effects. By using blocks we are able to explain some of the total variation in the response variable by differences between blocks (mothers) and thus reduce the residual unexplained variance. This will permit more precise estimates of parameters and more powerful tests of treatments. All ANOVA´s was further analysed with Tukey post-hoc tests. This blocking for mothers was also applied in the T-tests for the Fine samples. A Pearson correlation was utilized for analyzing possible relationships between lipids and body weight.
Lipid analysis
Station Rough (whole fishes) Fine (Somatic fishes) North 3 YOY * 5 mothers 3 YOY * 4 mothers Middle 3 YOY * 5 mothers None
South 3 YOY * 5 mothers 3 YOY * 4 mothers
Protein analysis
Station Rough (whole fishes) Fine (Somatic fishes) North 3 YOY * 5 mothers 3 YOY * 5 mothers Middle 3 YOY * 5 mothers None
South 3 YOY * 5 mothers 3 YOY * 5 mothers
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3 Results
The water temperature, pH and O2 were stable at all stations during the experimental time (Tab. 3). The study month, August, was sunny with an average air temperature of 18.5ºC (www.weatheronline.co.uk).
3.1 Mortality and the food resource experiment
Mortality in the Rough experiment was similar between the stations and ranged from 6-13%
while the mortality in the Fine experiment was significantly lower in the North compared to the South (Tab. 3). Mother 10 in the Fine experiment was lost due to high mortality, only one perch remaining when ending the experiment.
The presence of the main prey item, Gammarus spp, did not show any significant difference between the three stations in dry weight of Gammarus (p>0.05, ANOVA), 0.31 ± 0.16 g in the north, 0.32 ± 0.09 g in the middle and 0.34 ± 0.13 g in the south.
3.2 Chlorophyll a and salinity
The chlorophyll a (chl a) concentrations for all three stations were increasing (range of 60- 300 µg/L) during the first ten days (Fig. 2). In the Northern and Middle stations, chl a concentrations declined drastically as two saline intrusions spread southward in the Lagoon from day 11-14 and 16-20 (Fig. 2a and b). Between day 14 and 16 a small recovery of the algae community was observed. In the South station, not affected by saline water, a fluctuating pattern with modest decreases corresponding to the saline intrusions was exhibited from day 11-24 (Fig. 2c). In the Fine experiment the South had a significantly higher chl a level than the North during the salinity regime (after day 11, Tab. 3). In the Rough experiment there was a significant higher concentration of chl a in the North compared to the Middle station before the saline intrusions (Tab. 3) and the South station had a higher concentration than the other two during the salinity regime (Tab. 3).
11
Figure 2: Chl a concentration (the left y-axis) mean ± SD, n= 10 in Rough and Fine while n=3 in out, and salinity (the right y-axis) values for all stations.
0 1 2 3 4 5 6 7
0 50 100 150 200 250 300 350 400
Salinity
Chl a (µg/L)
North
RoughFine Out Salinity0 1 2 3 4 5 6 7
0 100 200 300 400
Salinity
Chl a (µg/L)
Middle
RoughOut Salinity
0 1 2 3 4 5 6 7
0 50 100 150 200 250 300 350 400
2 4 6 8 10 12 14 16 18 20 22 24
Salinity
Chl a (µg/L)
Day
South
RoughFineOut Salinity
12
3.3 Parameters of condition for YOY perch
When ending the Rough experiment (after 27 days) the perch showed significant differences between all sites in specific growth based on both length (Tab. 3) and weight (Fig. 3). The perch in the southern station had highest growth while the northern grew the least. The experiment with fine mesh size also showed significant differences between the Northern and Southern station in specific growth both based on length and weight. Perch from the southern station had highest growth while perch from the northern grew less (Fig. 3, Tab. 3).
SCI (Somatic Condition Index) in the Rough experiment increased significantly between all stations along a gradient, north to south (Tab. 3). In the Fine experiment SCI was statistically lower in the North compared to the South (Tab. 3).
3.3.1 Lipid and protein content
In both the Rough and the Fine experiments the lipid content of YOY perch was significantly higher in the South compared to the North station (p<0.05, ANOVA for the Rough and T-test for the Fine, Fig. 4). In the Rough experiment the Middle and the North station showed similar values in lipid content (p>0.05, ANOVA, Fig.4a). There was a positive liner relationship between body weight and lipid content (R2=0.141, P=0.011, Pearson correlation).
Figure 3: Specific growth based on weight (showed in % growth per day, mean ± SD, n= 10) for both the fine and rough mesh sized experiment. Each group of bars contains all stations average growth for their fishes that are from the same mother. The rough and the fine experiment have been compared separately. Mother 10 in Fine was removed due to high mortality.
-3 -2 -1 0 1 2 3 4 5 6
1 2 3 4 5 6 7 8 9 10
Specific growth (% weight day-1)
Mother
Rough North Rough Middle Rough South Fine North Fine South
Mother
13 Figure 4: Lipid content from the Rough and Fine experiment, shown as average lipid content per mother from each station ± SD, n=3.
Protein content in all perch was similar (around 30 µg protein g-1 tissue) in both the Rough and the Fine experiments regardless of station (Tab 2).
0 1 2 3 4 5 6
M 3 M 5 M 6 M 8 M 9
Lipid content (% per g fish)
North Middle South
Rough
0 0,5 1 1,5 2 2,5 3 3,5 4 4,5
M 2 M 7 M 8 M 9
Lipid content (% per g fish)
Mother
North South
Fine
14 Table 3: Contains mean values ± SD, p-values between different stations and type of statistical test for other measured parameters, as Water Temp., O2, pH Specific growth based on length, SCI, mortality, protein content and Chl a.
Parameters
Mean±SD p-values
North Middle South
North- Middle
North- South
Middle- South
Statistical test Water Temperatur (oC) 21.3±1,18 22.2±1,50 21.3±1,15 P>0.05 P>0.05 P>0.05 ANOVA O2 (mg L-1) 8.02±1.27 8.98±1.07 8.58±0.89 P>0.05 P>0.05 P>0.05 ANOVA
pH 8.98±0.28 9.17±0,17 9.21±0.16 P>0.05 P>0.05 P>0.05 ANOVA
Chl a Rough before saline
intrusion (µg/l) 203.38±37.8 124.36±36.2 150.15±72.4 P<0.05 P>0.05 P>0.05
ANOVA, Tukey Chl a Rough during saline
intrusion (µg/l) 163.9±45.9 139.59±36.8 200.94±13.4 P>0.05 P<0.05 P<0.05
ANOVA, Tukey Chl a Fine before saline
intrusion (µg/l) 130.55±13.4 no data (nd) 148.16±72.07 nd P>0.05 nd
Student´s T-test Chl a Fine during saline
intrusion (µg/l) 124.4±15.3 nd 141.9±9.78 nd P<0.05 nd
Student´s T-test Final perch size Rough exp.,
length and weight (mm/g).
29.7±1.0 0.22±0.02
31.4±0.94 0.30±0.03
35±1.5
0.43±0.05 P< 0.05 P< 0.05 P< 0.05
ANOVA, Tukey Final perch size Fine exp.,
length and weight (mm/g).
24.6±2.3
0.12±0.04 nd
27.6±2.6
0.18±0.06 nd P< 0.05 nd
Student´s T-test Specific growth, length,
Rough experiment (% day -1) 0.71±0.16 0.90±0.20 1.29±0.14 P< 0.05 P< 0.05 P< 0.05
ANOVA, Tukey Specific growth, length,
Fine experiment (% day -1) 0.25±0.22 nd 0.81±0.45 nd P< 0.05 nd
Student´s T-test SCI, Rough experiment 0.70±0.04 0.79±0.05 0.89±0.04 P< 0.05 P< 0.05 P< 0.05
ANOVA, Tukey
SCI, Fine experiment 0.67±0.05 nd 0.72±0.04 nd P< 0.05 nd
Student´s T-test Protein content Rough (mg
protein / g fish tissue) 29.65±2.25 33.97±10.95 31.09±3.59 P>0.05 P>0.05 P>0.05 ANOVA Protein content Fine (mg
protein / g fish tissue) 28.77±3.52 nd 28.13±2.12 nd P>0.05 nd
Student´s T-test Mortality, Rough experiment
(%) 6 13 7 P>0.05 P>0.05 P>0.05 ANOVA
Mortality, Fine experiment (%) 41 nd 61 nd P<0.05 nd
Student´s T-test
15
4 Discussion
The fact that this study is a field study where no control treatments (cyanobacterial or salinity free) were able to be conducted causes complications. This makes it impossible to fully separate the effects from the salinity and the cyanobacterial community. It is though possible that when looking at all analyses to see trends and suggestions about the different effects. The advantage with a field study is that these effects on perch condition are actually occurring in a natural environment and not only in a hypothetical environment in the lab.
The Rough experiment has similar mortality at all stations while in the Fine experiment the South station (61%) has significantly higher mortality then the North (41%). This despite the fact that the South stations perch grew most and that the densities of fish was balanced in enclosures containing siblings between the stations after mortality. The balancing was done because growth is a density dependant factor. This mortality difference could be caused by lower water circulation in the South cages, higher concentrations of cyanobacteria clogs the fine meshed nets faster and reduces the water flow. With lower water flow follows higher concentrations of waste products from the perch and perhaps more bacteria. High concentrations of waste products (e.g. ammonium) and bacteria could have induced sickness and caused the mortality difference (Laurent et al. 2000).
The simplest and most likely explanation for growth differences is that there would have been differences in the amount or quality of the food available. In our experimental setup the perch in the Rough experiment were living on food resources that entered the enclosures through the 2000 µm net while the perch in the Fine experiment were handfed blood worms since everything larger than 200 µm were sealed off from the cages. Despite this both the Fine and the Rough experiment are showing perch in better condition in the Southern station compared to the Northern (Fig. 3, 4 and Tab. 3). The fact that perch with equal amount of food in both the North and the South station are showing the same differences as perch from the Rough experiment indicates that food resources are not the sole factor responsible for these growth differences. Based on observations, Gammarus sp.
was believed to be the main food resource utilized by the perch, and therefore an additional experiment were conducted to evaluate this. The results showed that there was no difference in the amount of Gammarus entering the enclosures between the stations in the Rough experiment. This experiment further supports the conclusion that differences in food are not responsible for causing the growth differences. With food eliminated as the sole responsible factor behind the growth differences other factors like salinity and cyanobacteria have to be involved.
The chl a levels were increasing similarly for all stations until the saline intrusion occurred, although the North station had a higher concentration than the Middle in the Rough experiment (Tab. 3). During the salinity regime (after day 11) the South station had
16 significantly higher chl a concentrations compared to the other stations in both the Fine and the Rough experiment (Tab. 3). Since the Curonian Lagoon during the summer is dominated by cyanobacteria (Pilkaitytè 2007) a large fraction of the measured chl a probably consists of cyanobacteria. The high levels of cyanobacteria in the Curonian lagoon that all three stations most likely were subjected to might have affected the juvenile perch in many different ways, direct or indirect. By the presence of cyanobacterial cells the turbidity of the water
increases. Higher turbidity decreases perch growth by influencing their vision and thereby their attack and feeding rate (Ljunggren et al. 2007, Persson et al. 2010). The higher turbidity might also act as a stress factor causing the perch to spend more energy on unnecessary movement. The cyanobacterial toxins might also be responsible for decreased growth by forcing the perch to spend energy on detoxification of toxins instead of growth.
Cyanobacterial toxins might also have affected the perch by inducing sickness, damages or behavioural changes that has made the perches passive and non responsive to the prey’s presence (Karjalainen et al. 2005). It is also possible that the cyanobacterial presence has decreased the nutritional value of the Gammarus by their possible effects on the
zooplankton community (Demott et al.1991, Ahlgren et al. 1992, Koski et al. 1999, Ruokalainen et al. 2006). Zooplankton samples for counting and identification was also collected but will be processed as a part of a larger project. Thus, there can only be speculations about the possible effects of cyanobacteria on the nutritional value of Gammarus and the zooplankton community. But if the cyanobacteria have pushed the zooplankton community towards dominance by small rotifers (Ruokalainen et al. 2006) instead of cladocerans and copepods (Demott et al.1991, Koski et al. 1999) this might affect the perch as well as the Gammarus, since some Gammarus species are omnivores (Hunte and Myers 1984; Grigorovich et al. 2005). Perch and Gammarus might be affected by this trough decreased nutritional value in the zooplankton community (Ahlgren et al. 1992). If the rotifers are ingesting toxins and/or accumulating dissolved toxins they might also act as a vector for toxin transfer up the food web (Lehtiniemi et al. 2002, Kozlowsky-Suzuki et al.
2003, Karjalainen et al. 2003).
Another possible fitness reducing factor is the influxes of saline water. From day 11 to 22 both the Middle and the Northern station were subjected to a salinity regime, manifested by influxes from the Baltic Sea (Fig 2). The saline water did not reach the South station at any time during the experiment (Fig. 2c). Salinity in the Northern station during the peaks of the influxes was 6 psu (day 14) and 6.5 psu (day 19) and both are above the level for optimal growth for Perch (Ložys, 2004; Overton et al., 2008; Tibblin, 2009). The salinity at the middle station did not exceed that level but was at the upper end of it, 5 psu on day 14 and 19. This elevated salinity might have caused the perch to spend energy on ion regulation instead of growth (Brett, 1979; Jobling, 1994). It is also possible that the perch has been suffering of reduced appetite and/or reduced food conversion efficiency due to the salinity (Wang et al., 1997; Overton et al., 2008). Since the duration of salinity levels above optimal for growth is very short (2 days out of 27) it seems unlikely that the salinity levels would be fully
17 responsible for the growth differences. That these influxes of saline water are such sudden and fast processes raises the question if the fast change in environmental living conditions has a greater impact than the salinity itself? There are hardly any studies performed on this subject. A study on Spot (Leiostomus xanthurus) and Croaker (Micropogonias undulatus) by Moser and Lawrence (1989) showed that these rapid changes have a higher impact and prolonged adjustment time in smaller individuals (<70 mm) than in larger ones. Another study on Sheepshead minnow (Cyprinodon variegates variegates) showed that fish that have never experienced rapid salinity changes need a longer adjustment time and that rising salinity has a greater impact than declining salinities (Haney, 1999). The perch used for the experiment would belong to the smaller size fraction (Fine<35mm and Rough< 45mm by the end of the experiment) and have spent their whole life in freshwater. They experienced salinity raises from 0 up to the peaks at 6.5 psu (North) and 5 psu (Middle) during 36 h. All these factors indicate that the perch would belong to the group were rapid salinity changes might take an extra toll of energy.
When trying to combine both salinity and cyanobacteria effects another more likely pattern emerges. In the Fine experiment chl a levels were the same at both stations before the saline intrusion, and after that significantly higher in the South while the North had two saline influxes during the same time (Tab. 3, Fig. 2). During the first time period (before the saline intrusions) both the North and South stations possibly suffers from the same growth diminishing effects from the cyanobacteria (Tab. 3). For the second time frame (during the saline intrusions) the South maintains a high concentration of cyanobacteria while the Northern station has significant lower concentrations (Tab. 3 and Fig. 2). This can imply that the combined negative effect of a changing environment in terms of salinity and cyanobacteria has a higher impact on the perch growth than constantly elevated cyanobacterial concentrations. The South and North station from the Rough experiment follows this pattern (Tab. 3). When comparing the Middle station to the Southern the pattern is the same, chl a values are equal before the saline intrusion and then higher in the south (Tab. 3) while the Middle station are experiencing salinity influxes (Fig. 2) and ending up with a lower growth then the South. Between the Northern station and the Middle there is significantly better condition of the perch from the Middle (Fig. 3, 4, Tab. 3) even though they are experiencing the same components of changes in their environment. This is possibly due to higher concentration of chl a before the saline intrusion in the North (Tab. 3) and that the saline influxes peaks at a higher value in the North (Fig. 2) compared to the Middle (Fig.
2). These differences create a higher grade of fluctuations in the environment in the North than the Middle which might be responsible for the growth differences between them.
Another scenario is that the growth deviations might depend on differences in composition of the phytoplankton community, different species have different impacts. Samples of the phytoplankton community were collected but will be processed as a part of a larger project and thus not incorporated in this study. If speculating it might be possible that the North and Middle stations were subjected to other phytoplankton then the South, perhaps
18 saline/brackish species like Nodularia spumigena brought on by the influxes from the Baltic Sea and that they had a higher impact on perch condition.
When studying these patterns it seems that rapid changes in salinity and/or cyanobacterial exposure have a more negative effect on perch condition than cyanobacteria alone. At the South station the perch have constantly high concentrations of cyanobacteria which give them time to adjust to face those challenges. The North and the Middle stations have to face challenges from both cyanobacteria, salinity and the rapid changes in concentrations between those two. These challenges force the perch to readjust after changing conditions, the ratio between toxin purification and ion regulation have to be constantly altered. These readjustments could possibly take a higher toll of energy then the salinity or cyanobacteria itself does.
5 Conclusions
What can be concluded with certainty by this field study is that the perch condition was declining northward in the curonian lagoon. The reason behind this could be the salinity, differences in the cyanobacterial community, a changing environment with possible synergistic effects from salinity and cyanobacteria or other unknown factors. Due to that this is a field study with no control treatment the responsible factor/factors cannot be determined. However, I believe that all of these factors have played a part but that the rapidly changing environment was the determinant.
6 Acknowledgments
I would like to thank my supervisors Karl-Johan Persson and Catherine Legrand for guidance, patience, support and a good time during this project.
Arturas Razinkovas and his coworkers at University of Klaipeda, Lithuania deserves a thanks for the practical help provided during the experiment.
This study was funded by Forskningsrådet för miljö, areella näringar och samhällsbyggande (FORMAS).
19
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8 Appendix
Figure 6: Showing the structure and setup of each experimental station. Two main anchors connected by a main line, with extra weights made of plastic bottles filled with sand. From the main line goes individual lines up to each of the ten cages, these are adjusted so the cages float 2-3 dm below the surface. Within each cage are fifteen perches from the same mother, ten cages gives 150 perches from ten mothers. This structure was replicated five times, rough north, middle, south and fine north, south.
Figure 7: One of the rough enclosures with the lid removed.
SE-391 82 Kalmar +46 480 446200 info.nv@lnu.se Lnu.se
