Dinophyta Characterise Nitrogen Scarcity More Strongly Than Cyanobacteria in Moderately Deep Lakes

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Acta Protozool. (2013) 52: 203–216 http://www.eko.uj.edu.pl/ap Acta doi:10.4467/16890027AP.13.0018.1115 protozoologica Special issue: Protists as Bioindicators of Past and Present Environmental Conditions

Dinophyta Characterise Nitrogen Scarcity More Strongly than Cyanobacteria in Moderately Deep Lakes

Jane FISHER1,2, Cassandra S. JAMES1,3, Victoria L. MOORE1 and Brian MOSS1

1School of Environmental Sciences, University of Liverpool, Liverpool, UK; 2School of Natural Sciences and Psychology, John Moores University, Liverpool, UK; 3Australian Rivers Institute, Nathan Campus, Griffith University, Nathan, QLD, Australia

Abstract. A survey of the summer phytoplankton communities of thirty-six moderately-deep north temperate lowland lakes showed that the proportions of Dinophyta and non-heterocyst-bearing cyanobacteria taxa, measured as biovolume, were inversely related to the total nitrogen:total phosphorus (TN:TP) ratio and that these groups were predominant in lakes where available nitrogen fell to undetectable concentrations. The proportion of heterocyst-bearing cyanobacteria was positively correlated to the TN:TP ratio and nitrate. Dinophyta and/or non-heterocystous cyanobacteria were prevalent in lakes with the highest epilimnion nutrient concentrations, whilst heterocystous cyanobacteria predominated in lakes with moderate nutrient concentrations. It is argued that the ability of Dinophyta to migrate vertically and to supplement their nutrient requirements though heterotrophy may enable them to be at least as successful as cyanobacteria in high nutrient lakes and in overcoming nitrogen-scarcity. Our findings provide evidence that Dinophyta can be used as indicators of water quality.

Key words: Lakes, Shropshire and Cheshire Meres, phytoplankton, seasonality, nutrients, vertical movement.

INTRODUCTION anobacteria (Tilman et al. 1982, Harper 1992, Levine and Schindler 1999, Dokulil and Treubner 2000). Red- field (1958) noted that algae required N:P in aratio Recent studies into the frequency of occurrence of around 7:1 (by weight). At ratios lower than this, algae nitrogen and phosphorous scarcity in lakes suggest that that are capable of fixing their own nitrogen, (many cy- nitrogen limitation might be as common as phosphorus anobacteria and others having cyanobacterial symbi- limitation (Elser 2007, Lewis and Wurtsbaugh 2008). onts) are advantaged. Large populations of cyanobac- Eutrophication is often attributed to increased phos- teria are sometimes a nuisance and can result in toxic phorus loading, leading to a reduction in the ratio of blooms that pose a health risk to recreational users and nitrogen:phosphorus (N:P), further promoting nitrogen animals drinking the water (Howard et al. 1996). (N) limitation, a decrease in phytoplankton diversity, The proposed links among eutrophication, low N:P and a phytoplankton assemblage predominantly of cy- ratios and cyanobacterial dominance were emphasised Address for correspondence: Jane Fisher, School of Natural Sci- by Schindler (1974) who showed that addition of phos- ences and Psychology, John Moores University, Liverpool, L3 3AF, phorus (P) to one lobe of a lake, separated by a nylon UK; E-mail: [email protected] curtain from the rest of the lake, resulted in increased 204 J. Fisher et al. chlorophyll concentrations and a phytoplankton popula- logical tests of nutrient limitation. The “Redfield ratio” tion dominated by N-fixing cyanobacteria. Whilst many (Redfield 1958) suggests that N deficiency is likely to field and laboratory studies have shown cyanobacterial occur at N:P ratios < 7:1 (by weight). Absolute concen- domination to be greater in waters with low N:P ratios, trations are also important, as if the concentrations of there is growing evidence that such dominance is more both bio-available nutrients are high, the ratio becomes highly correlated with other indicators of trophic sta- irrelevant (Reynolds 1999) and ratios are incalculable tus (Prepas and Trimbee 1988, Reynolds and Petersen if concentrations are below laboratory detection levels. 2000). A survey of 99 lakes (Downing et al. 2001) Furthermore, the Redfield ratio reflects the average nu- showed cyanobacterial population to be correlated with trient requirement of algae while different species may total phosphorus (TP), total nitrogen (TN) and phyto- have different nutritional requirements (Rhee 1978, plankton production, rather than to ratios of N:P. Indeed, Klausmeier et al. 2004). In addition nutrient limitation the proportion of nuisance cyanobacteria, in conjunction is likely to be stoichiometric (Kilham 1990, Kim et al. with total chlorophyll, has been proposed as a means of 2007), and while it has been questioned if two or more monitoring nutrient enrichment in lakes under the Water nutrients can be simultaneously limiting to the same Framework Directive (WFD UKTAG 2008). species (Droop 1973) it is certain that different species The lack of a clear relationship between cyanobac- of algal will be limited by different nutrients, such as teria and measures of N-limitation in some studies may N, P, silica or carbon, at the same time. It is insufficient be a product of the diverse requirements of this group. to rely on annual mean nutrient concentrations to de- Blomquist et al. (1994) argue that it is more appropriate termine limitation, but sustained periods in which the to analyse the links among cyanobacteria, trophic sta- bioavailable form of a nutrient is undetectable indicates tus and low N:P ratio by considering N-fixing and non which nutrient is potentially limiting (Maberly et al. N-fixing species separately. Non N-fixing cyanobacteria 2004), though phytoplankton may be able to take-up will be favoured by the presence of ammonium, while nutrients at concentrations far lower than laboratory de- low concentrations of nitrogen in general will promote tection limits and be able to use luxury uptake to over- those cyanobacteria capable of fixing N (Blomquist et come periods when one or more nutrient may be limit- al. 1994). The ability of some cyanobacteria, such as the ing. This raises the issue of whether algal groups can Nostocales, to fix nitrogen can be recognised by their be used to indicate nutrient limitation, and whether cy- ability to produce heterocysts, (recently called hetero- anobacteria are effective indicators of nitrogen scarcity, cytes, which is etymologically correct, but the original despite strong conventional beliefs in their efficacy. term remains most widely used and understood). N-fixing Cyanobacteria are associated with moderate but not capabilities are not confined to these taxa however, and the highest nutrient concentrations, where green al- some species within the genera of Oscillatoria, Lyngbya gae, particularly Chlorococcales predominate, at least and Phormidium, all of which are non-heterocystous cy- in shallow unstratified lakes (Jensen et al. 1994). The anobacteria, are also capable of N-fixation (Paerl 1988), position in deeper lakes is less clear, but the predomi- though generally under microaerophilic conditions that nance of cyanobacteria in moderately deep, nutrient- are more associated with sediments and metalimnia than rich lakes seems to depend on their ability either to fix surface waters. In open waters, the frequency of het- N or to migrate between deeper, more nutrient-rich wa- erocysts is generally taken to be a reasonable guide to ters and the illuminated surface waters using regulation the potentiality for nitrogen-fixation. Investigations into of their content of gas vesicles (Reynolds and Walsby how to recognise which nutrient limits phytoplankton 1975, Ganf and Oliver 1982). Such migrations are pos- biomass are becoming more important now that there is sible also for flagellate algae. A clear indicator of nitro- increasing evidence that phosphorus limitation may not gen scarcity would be useful for monitoring purposes be so universal as once thought and that nitrogen limita- owing to the high cost of direct investigations and the tion or co-limitation by both N and P may be at least as number of lakes now requiring monitoring under the common (Maberly et al. 2002, James et al. 2003, Elser et European Water Framework Directive. In this study we al. 2007, Lewis and Wurtsbaugh 2008). investigated if other algae capable of vertical migration, Recognising N-limitation from in-lake nutrient con- such as the Dinophyta, are as effective as heterocystous centrations is challenging, though Hameed et al. (1999) cyanobacteria, at indicating nitrogen scarcity in moder- showed that interpretation of in-lake concentrations ately deep lakes. We used extensive correlation among were just as reliable as the results of a series of physio- lakes in the UK that are generally severely eutrophi- Dinophyta Characterise Nitrogen Scarcity 205 cated and lakes in Poland where agriculture has been integrated water samples were taken from the top one metre at the less intensive to investigate this hypothesis. centre of each lake, with the exception of Bomere where samples were taken from a jetty. The Polish lakes were visited once, between July and August 2001, and three replicate water samples were taken from wading depth from the shore, or from a jetty where possible, MATERIALS AND METHODS using a 2 m long extended sampler. Laboratory analysis Study sites One litre samples were filtered through Whatman GF/C glass-

Thirty-six moderately deep (Zmax > 3 m) lowland freshwater fibre filters on the day of collection and the filter frozen for chlo- lakes were studied. Sixteen were among the North-West Midlands rophyll analyses. Chlorophyll-a concentration was determined by meres area of England, nine in the Lublin Uplands of Eastern Po- placing the filters in 90% acetone for extraction overnight at 4°C, land and eleven in the Mazurian Lake District of North-East Poland and the abstracted chlorophyll-a measured at 665 nm on a Jenway (Table 1). Most of the lakes are glacial in origin. The UK Meres are spectrophotometer (Model 6405). Filtered water samples were a cluster of over sixty lakes situated in the hummocky topography analysed on the day of sampling for soluble reactive phosphorus of fluvio-glacial sands, gravels and moraine which overlay Trias- (SRP), nitrate (NO3-N) and ammonium (NH4-N) concentrations us- sic sandstone (Reynolds 1979). They are among the most impor- ing standard methods outlined in Mackereth et al. (1978). In Poland, tant natural freshwater habitats in Britain for both ecological and nitrate-nitrogen and ammonium were analysed using colorimetric scientific reasons (Luther and Rzoska 1971, Twigger and Haslam CHEMets kits within 10 hours of sample collection (CHEMetrics 1991). Hanmer Mere, Cole Mere, Crose Mere and Rostherne Mere from GALGO(UK) Ltd). SRP was measurable to 5 μg l–1, and ni- are Sites of Special Scientific Interest (SSSI), and the latter is also trate and ammonium to a minimum detection limit of 10 μg l–1 N–l a Ramsar site and a National Nature Reserve (NNR). The Meres for both the laboratory and kit analyses. At high ammonia concen- –1 have few surface drainage channels, and lie at the approximate trations (> 50 μg l NH4-N) the resolution of the test kits was re- height of the water table. As a result the meres generally have long duced to 50 μg l–1 as the kits colour comparison, provided for these residence times (mean of 1.3 years–1, n = 18) and react slowly to higher ammonia concentrations, were only available at these lower changes in precipitation and drainage. The lakes lie in a region of resolutions. The accuracy of the CHEMets kits in comparison with mild, sub-oceanic conditions, and the local land use is dominated laboratory analyses were tested on natural water samples before by dairy farming and arable agriculture. Agricultural intensification the Polish fieldwork. Unfiltered water samples were preserved with and land drainage has led to soil erosion and the leaching of nu- 0.147 mM (final concentration) mercuric chloride (Klingaman and trients to the meres, causing eutrophication (Reynolds and Sinker Nelson 1976, German Chemists Association 1981), and refrigerated 1976, Reynolds 1979, Moss et al. 1994, Moss et al. 2004). in the dark for the analysis of total nitrogen (TN) and total phos- The lakes sampled in the Łęczyńsko-Włodawskie region lie to phorus (TP) concentrations, following microwave digestion (Johnes the north and east of Lublin. Drift sediments are fluvio-glacial and and Heathwaite 1992). Point measurements of pH, alkalinity and lacustrine in origin (Balaga 1982) and land use is a mosaic of decid- conductivity were also taken on the day of sampling though, due to uous and pine forests, arable land, pasture, and numerous villages equipment constraints, pH values of the Polish water samples were and hamlets. The wetland area has been reduced as a result of land not measured. drainage, and agriculture, which is less intensive than in the United Sites with mean TN:TP ratios lower than 7 or, where available Kingdom. This area of Eastern Poland is landlocked and dominated nitrogen (nitrate and ammonium) was undetectable on at least one by a continental climate with cold, dry winters, and warm summers sampling occasion, during the growth-season, were considered po- when the majority of the precipitation falls. tentially N-limited. Those samples in which mean TN:TP ratios The Mazurian Lakeland is more undulating than that of the were more than 15 or where SRP concentrations were below de- Łęczyńsko-Włodawskie region, and drift deposits also derive from tection limits on at least one sampling occasion were considered fluvio-glacial activity (Bajkiewicz-Grabowska 1983). Approxi- potentially P-limited (Table 1). mately 10% of the area is made up of lakes (Mikulski 1966) and is dominated by two large lake complexes centred around Jezioro Phytoplankton (‘lake’) Dargin and Jezioro Śniardwy. Natural and man-made navi- A 10 ml subsample of unfiltered water was preserved with gable sailing routes interconnect many of the lakes, and they re- 5 drops of Lugol’s iodine solution. Phytoplankton cells were settled ceive both groundwater and surface inflows (Bajkiewicz-Grabows- in sedimentation chambers before being identified (species shown ka 1983). Municipal sewage is discharged into some of the larger in Table 4) and counted using an inverted microscope at × 400 mag- lakes, while the intensification of agriculture is having a marked nification. A minimum of 400 organisms was counted per sample impact on the water quality of many of the sites (Zdanowski et al. and the length, width and diameter of randomly selected cells of 1984). The Mazurian Lakeland has a more maritime climate than each species were measured in order to calculate biovolumes. Bio- that of the Lublin region but again more than half of the precipita- volumes were calculated using standard formulae for the volumes tion falls in the summer (Bajkiewicz-Grabowska 1983). of known geometric shapes (Jones 1979). The biovolumes of those Field sampling species occurring rarely in the samples were obtained from the lit- erature (Prescott 1962). Cyanobacteria were divided into those that The north-west midland meres were visited regularly seven have heterocysts and potentially fix nitrogen in the open waters, and times, throughout the growing season (May until October 2000) and those without heterocysts that are unlikely to do so. 206 J. Fisher et al. ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? ? N N N N N N N N N N N N N N N+P N+P N+P BDC N or P ) –1 2.45 6.97 2.46 5.96 3.99 9.25 6.50 6.17 6.04 6.10 8.37 3.03 9.88 5.26 1.73 2.17 0.32 1.82 1.52 1.87 2.17 2.88 6.24 2.23 3.17 0.70 1.60 2.88 3.32 2.68 3.02 2.60 2.75 3.27 3.33 0.08 Alkalinity (mequiv l n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a n/a pH n/a 7.9 7.5 8.0 7.2 8.2 8.6 8.3 8.4 8.3 8.7 8.1 8.3 8.7 7.5 8.6 8.2 ) –1 -N 4 6 5 77 66 27 24 91 37 32 36 46 30 96 50 50 50 65 42 67 33 25 100 129 176 106 100 800 467 100 100 100 100 100 NH < 10 < 10 < 10 (µg l ) –1 -N 3 60 20 20 30 20 20 50 20 70 30 260 370 180 360 150 270 470 030 NO < 10 < 10 < 10 < 10 < 10 < 10 < 10 < 10 < 10 < 10 < 10 < 10 < 10 < 10 < 10 < 10 < 10 (µg l 1140 ) –1 2 4 7 9 1 2 1 6 5 3 3 9 15 33 19 97 63 70 65 35 36 35 40 43 62 54 19 18 38 26 SRP 278 152 761 105 587 (µg l 1240 ) –1 TN 0.4 2.3 1.5 1.4 1.0 1.7 1.4 1.3 1.2 1.3 2.6 1.3 1.0 3.0 1.4 1.8 1.5 0.5 0.9 0.9 0.7 1.4 1.1 1.6 1.4 1.3 0.9 1.5 0.8 1.0 0.8 1.5 0.7 1.0 0.9 0.6 (mg l ) –1 TP 14 97 62 49 55 96 87 14 22 17 31 30 42 43 45 47 21 35 33 92 22 76 24 28 390 361 262 894 251 196 146 694 127 102 184 (µg l 1590 6 6 6 1 1 7 2 8 31 17 22 23 29 13 12 27 25 12 39 40 63 24 15 36 38 31 29 19 40 28 25 17 32 14 36 24 TN:TP (weight) 70 70 91 55 16 91 87 91 76 76 90 16 80 91 50 31 83 98 (m) n/a 117 116 116 116 116 125 170 168 167 159 160 160 161 160 164 120 122 Altitude 01′ 8″ E 58′ 4″ E 01′ 3″ E 32′ 0″ E 30′ 9″ E 01′ 1″ E 01′ 8″ E 56′ 8″ E 57′ 7″ E 56′ 9″ E 50′ 4″ E 41′ 8″ E 34′ 9″ E 32′ 0″ E 45′ 0″ E 50′ 0″ E 01′ 7″ E 28′ 7″ E 33′ 0″ E 27′ 4″ E o o o o o o o o o o o o o o o o o o o o Longitude 53′ 9″ W 53′ 9″ W 46′ 8″ W 52′ 1″ W 45′ 7″ W 31′ 0″ W 50′ 7″ W 51′ 0″ W 53′ 2″ W 48′ 9″ W 39′ 2″ W 51′ 4″ W 28′ 5″ W 13′ 6″ W 52′ 2″ W 24′ 1″ W 26′ 8″ o o o o o o o o o o o o o o o o 22 23 23 23 23 23 22 22 21 21 21 21 21 21 21 22 21 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 23 21 21 N 22′ 7″ 25′ 9″ 29′ 9″ 29′ 9″ 32′ 3″ 31′ 1″ 28′ 1″ 25′ 7″ 46′ 9″ 07′ 1″ 8″ 11′ 14′ 1″ 10′ 7″ 44′ 5″ 44′ 1″ 49′ 3″ 48′ 3″ Latitude 44′ 5″ 40′ 0″ 54′ 1″ 40′ 2″ 17′ 3″ 53′ 7″ 52′ 3″ 54′ 7″ 56′ 8″ 0′ 3″ 54′ 2″ 17′ 5″ 14′ 5″ 53′ 6″ 19′ 8″ 21′ 3″ 23′ 1″ 43′ 7″ 10′ 9″ o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o o 51 53 52 53 52 52 53 53 51 51 51 51 51 51 51 53 54 54 54 54 54 53 53 53 52 52 52 51 53 52 52 52 53 52 53 53 11 39 18 18 17 85 57 59 24 32 39 27 10 46 28 15 26 16 49 n/a n/a 8.4 8.3 4.4 6.4 (ha) 110 160 860 400 490 120 210 180 Area 2,500 1,100 11,000 a a a a a a b b b b b b b b b b b b b b b b b b b n/a 3.9 2.2 2.1 4.1 3.2 1.5 7.4 7.3 3 4 5.1 4.6 6 5.6 6.2 5.9 5.8 9.8 7 4.6 5.1 8.0 2.0 3.3 3.6 4.8 3.0 4.4 2.8 (m) 11.8 11.9 12.6 14.1 10.8 13.6 Z mean b (1999). a a a a a a b b b b b b b b b b b b b b b b n/a b b 5.1 5.2 5.9 9.3 6.5 8.0 9.2 8.1 9.4 11.5 11.4 (m) 15.2 18.8 16.4 25.4 26.9 38.8 25 33.6 10.9 14.1 14.5 27.5 18.2 36.1 33 43.8 16.7 14 23.84 36 10.1 15.6 12.5 16.4 et al. Z max c Depths taken from Jańczak Lake depths calculated from measurements made between 4 and 7 transects across each lake. small lake 500m south of Gąsior. A Bomere Ellesmere Newton Mere Rogόźno a b c Summary of morphological, geographical and mean growth season nutrient and physico-chemical variables of the thirty-six study lakes. Growth-season physico-chemical study lakes. of the thirty-six variables and physico-chemical growth season nutrient and mean geographical 1. Summary of morphological, Table – available Last column occasion. on one sampling taken samples from three and for Poland are a mean occasions, from 7 sampling UK are a mean variables for the and nutrient occasions and sampling on all detectable N and P ? – available occasion. one sampling (BDC) on at least concentrations (SRP) below detectable and P and ammonia) N (nitrate therefore unknown if either fell below detectable concentrations during the growth season, n/a = no data. Lake name

Alkmund Park Pool Gołdopiwo Cole Mere Redes Mere Piaseczno Włodawskie Zagłębocze Włodawskie Białe Betton Pool Blake Mere Budworth Mere Crose Mere Hanmer Mere Marbury Big Mere Pick Mere White Mere Mere Rostherne Mere Włodawskie Czarne Bialskie Sosnowickie Białoławki Maśluchowskie Krasne “Gąsior” Mamry (Północne) Rydzówka Silec Śniardwy Orzysz Inulec Czarne Sosnowickie Stręgiel Majcz Wielki Majcz Dinophyta Characterise Nitrogen Scarcity 207

Statistical analysis phytoplankton biovolume and the greatest proportions Ordinations were carried out using CANOCO for Windows ver- (medians 24%, 13% and 15% respectively) in the thir- sion 4 (ter Braak and Šmilauer 1998). Linear ordination techniques ty-six lakes studied (Table 2). were chosen after examination of the gradient lengths of the species The proportion of Dinophyta biovolume was also response curves showed species responses to environmental gradi- significantly positively correlated with TP (p < 0.01) ents to be linear. The gradient lengths were viewed after running and TN (p < 0.1) concentrations (Table 3). Non-hete- detrended correspondence analysis (DCA) and selecting detrend- ing-by-segments. Jongman et al. (1995) note that, where gradi- rocystous cyanobacteria were positively correlated to ent lengths are less than 2 standard deviation units, the response TP (p < 0.05), SRP (p < 0.1) and nitrate concentrations curves will generally be monotonic, and therefore linear ordination (p < 0.05) while heterocystous cyanobacteria were neg- techniques should be used. Where gradient lengths are greater than atively correlated with TP (both p < 0.05) and nitrate 4 standard deviation units the data tend towards unimodal (Jongman (p < 0.01) concentrations (Table 3). There was no sig- et al. 1995). We decided to employ the linear techniques of principal nificant correlation (p < 0.05) between cyanobacteria, components analysis (PCA) and redundancy analysis (RDA) since the gradient lengths of the species data were found to be lower than either in total, or split into heterocystous and non-hete- 3 standard deviation units. rocystous forms, and ammonia (Table 3). Other than the All phytoplankton data were expressed as percentages of to- proportion of Chlorophyta, diatoms and Cryptophyta, tal biovolume, at both the level of division and species. This was which were inversely correlated with total or available used in preference to absolute biovolumes to ensure that statisti- N and P (all p < 0.05 and higher), no other phytoplank- cal relationships between phytoplankton and nutrients focussed on phytoplankton composition rather than total biomass. All ordina- ton group was significantly (p < 0.05) correlated with tions were ‘species-centred’ so that phytoplankton with the great- growth-season nutrient concentrations (Table 3). est variance and, therefore normally those with greatest abundance, Flagellated algae such as Ceratium hirundinella dominated the ordinations (Jongman et al. 1995). Environmental (O.F. Müller) Bergh. (Dinophyta), Cryptomonas spp. variables were standardised ‘to zero mean and unit variance’ (Jong- (Cryptophya) and Mallomonas spp. (Chrysophyta), man et al. 1995). For ordinations, sites were plotted according to were associated with higher than average (centre of or- the mean phytoplankton biomass calculated from the seven samples taken during the growth season and from the three samples taken on dination) concentrations of TN, TP, SRP and nitrate-N the one sampling occasion from the Polish sites, and expressed as (Fig. 1). a percentage of the total growth season biovolume. Phytoplankton percentage data were arcsin transformed and the environmental variables were transformed using a natural log where analysis showed the data to be skewed. This and other statistical tests, including correlation coefficients, means, standard errors and comparisons of means using Kruskall-Wallis test and ANOVA, were carried out in SPSS version 15 (IBM, 2006).

RESULTS

Phytoplankton and productivity Mean growth season phosphorus concentrations varied greatly among sites, from less than 14 µg l–1 total P (TP) to nearly 1,600 µg l–1, while total N (TN) varied from just over 1 mg l–1 to over 3 mg l–1 (Table 1). Twelve of the lakes can be conventionally considered to be hyper-eutrophic (P > 100 µg l–1), seventeen eutrophic (25 < P < 100 µg l–1) and seven mesotrophic (8 < P < 25 µg l–1) from their TP concentrations (Table 1) (Vol- lenweider and Kerekes 1981). The larger, deeper, less nutrient-rich lakes tended to be the Polish sites, while Fig. 1. Redundancy Analysis (RDA) of the mean proportion of the smaller lakes with higher total phosphorus concen- phytoplankton species composition expressed as proportion of trations occurred in the UK (Table 1). Cyanobacteria, biovolume, λ1 = 0.094, λ2 = 0.051. Key to species in Table 4, Dinophyta and Chlorophyta made up the bulk of the λ – eigenvalue. 208 J. Fisher et al. ) 0 6 2 2 0 0 9 1 0 –1 11 11 72 27 38 20 15 61 22 43 24 14 33 29 49 15 66 18 31 26 13 21 20 41 34 65 25 17 22 123 (µg l Chlorophyll- a % 0 3 2 0 0 0 0 0 0 3 1 0 0 0 0 11 11 43 33 14 35 10 13 13 56 59 19 79 30 29 19 21 13 32 84 33 90 41 67 0 0 5 0 0 0 0 0 8 69 23 86 18 62 94 16 14 Dinophyta abs 467 896 136 892 194 135 172 978 686 926 869 503 154 233 874 261 252 1,011 2,155 4,120 2,225 2,900 % 1 2 3 1 2 0 1 0 0 0 0 3 0 0 3 1 0 0 0 1 0 6 7 0 0 0 0 0 1 9 0 3 3 1 3 0 3 1 12 4 4 0 6 0 2 2 0 3 0 0 7 0 0 0 7 0 5 6 0 0 5 3 abs 11 45 30 32 10 50 29 41 21 62 78 31 38 17 43 Chrysophyta 192 3 9 0 1 0 0 0 0 0 0 1 0 4 6 0 0 1 0 0 0 0 0 0 0 0 1 7 1 0 4 0 0 1 0 0 0 3 7 0 % 0 0 8 0 0 0 0 0 0 2 0 1 0 0 9 0 9 6 0 0 1 abs 21 42 10 24 20 10 72 16 Euglenophyta 10 10 15 56 21 26 17 13 13 164 % 5 7 5 3 2 5 7 9 1 1 3 2 3 4 9 2 8 3 3 2 1 5 11 13 36 37 53 62 22 10 75 17 47 14 24 23 23 33 31 Diatoms 9 2 38 15 68 47 64 63 44 63 68 54 18 64 abs 136 124 145 139 120 301 243 158 684 230 862 191 148 104 183 148 158 141 176 185 144 173 concentrations in the thirty-six study lakes. Data is expressed as absolute (abs) study lakes. Data is expressed as absolute in the thirty-six -a concentrations 1,336 2,231 1,300 0 7 5 5 6 0 2 0 3 1 1 4 5 0 0 1 40 40 10 37 21 92 74 47 39 111 146 995 357 123 859 830 159 275 330 131 150 % 4,460 1,014 Heterocystous Cyanobacteria 4 1 6 1 1 6 0 5 1 9 4 8 9 0 2 2 2 8 1 3 2 abs 18 36 73 12 87 30 16 70 49 13 12 14 35 10 81 51 21 15 2 7 7 5 7 3 2 8 2 5 2 % 61 74 37 12 88 39 12 24 75 64 51 13 12 13 71 14 60 51 42 61 83 43 59 68 24 60 24 21 Total Total 6 11 82 12 46 34 71 73 63 48 31 30 211 406 233 654 163 504 106 791 170 648 455 221 abs Cyanobacteria 1,363 1,009 5,127 1,191 2,058 1,227 1,694 2,528 1,850 1,771 2,753 1,252 1,187 1,635 1,280 7 5 7 8 5 7 4 5 9 5 4 6 6 5 3 8 23 12 18 37 74 15 83 65 16 19 23 18 21 13 18 15 16 22 22 60 44 62 19 % 99 68 73 88 99 72 27 88 abs Chlorophyta 111 111 110 116 129 292 485 221 552 449 490 620 160 253 189 407 233 186 167 342 328 579 194 134 187 121 358 138 531 197 6,449 1 0 5 2 1 6 0 0 3 0 3 1 7 4 2 1 2 0 1 0 1 2 2 2 2 1 2 2 1 3 4 1 4 5 9 4 1 % 10 14 ) and percentage (%) of total phytoplankton biovolume. –1 ml 4 6 5 1 6 4 3 8 8 5 8 Cryptophyta abs 26 36 12 30 34 24 95 13 87 17 82 30 37 75 34 44 10 45 24 76 68 43 43 23 15 16 16 –3 140 µm –4 a See Table 1. See Table Bialskie Sosnowickie The mean growth season proportions of phytoplankton in each Division and chlorophyll in each growth season proportions of phytoplankton The mean 2. Table a total biovolume (× 10 Alkmund Park Pool Majcz Wielki Majcz Czarne Sosnowickie

Betton Pool Gołdopiwo Maśluchowskie Blake Mere Krasne Bomere Stręgiel “Gąsior” Budworth Mere Mamry (Północne) Cole Mere Rydzówka Crose Mere Silec Ellesmere Śniardwy Hanmer Mere Białoławki Marbury Big Mere Orzysz Newton Mere Inulec Pick Mere Median Redes Mere Lower quartile (Q1) White Mere Upper quartile (Q3) Mere Rostherne Mere Piaseczno Rogόźno Zagłębocze Włodawskie Zagłębocze Białe Włodawskie Białe Czarne Włodawskie Czarne Dinophyta Characterise Nitrogen Scarcity 209

Table 4. Phytoplankton species and their codes as shown in Figs 1, 2 and 3.

Species name Code Division Amphora spp. Amp spp. Diatom Anabaena subcylindrica Anab sub Cyanophyta Dinophyta ** –0.4 ** 0.47 ** 0.38 * 0.29 *** –0.66 * 0.32 * 0.27 Aphanizomenon flos-aquae Aph flaq Cyanophyta Asterionella formosa Ast form Diatom Ceratium hirundinella Cera hir Dinophyta Chroococcus limneticus Chr lim Cyanophyta Closterium spp. Clos spp. Chlorophyta Coelastrum spp. Coel spp. Chlorophyta Chrysophyta * –0.27 Cosmarium spp. Cos spp. Chlorophyta Cryptomonas spp. Cryp spp. Cryptophyta Cymbella spp. Cym spp. Diatom Fragilaria crotonensis Frag cro. Diatom Fragilaria spp. Frag spp. Diatom Kirchneriella subsolitaria Kir sub Chlorophyta concentrations. Only environmental variables and variables environmental Only concentrations. a Mallomonas spp. Mall spp. Chrysophyta Euglenophyta ** –0.43 ** –0.38 * –0.33 * –0.31 Oscillatoria retzii Osc ret Cyanophyta Oscillatoria tiny Osc tiny Cyanophyta Oscillatoria spp. Osc spp. Cyanophyta Pediastrum boryanum Ped bory Chlorophyta Phormidium spp. Phor spp. Cyanophyta Sphaerocystis spp. Sph spp. Chlorophyta Diatoms ** –0.42 * –0.31 Staurastrum spp. Stau spp. Chlorophyta Synura spp. Syn spp. Chrysophyta Tabellaria spp. Tab spp. Diatom Trachelomonas spp. Trac spp. Euglenophyta -N) alkalinity and chlorophyll- and -N) alkalinity 4 Unidentified centric diatom cent diat Diatom Unknown flagellate un flag ? Non-heterocystous Cyanobacteria ** –0.44 ** –0.47 ** –0.4 ** –0.39 * –0.33 ** 0.47 ** 0.39 ** 0.38 cyanobacteria, heterocystous Cyan-het Cyanophyta cyanobacteria, non-heterocystous Cyan-non Cyanophyta -N), ammonia (NH -N), ammonia 3 PCA separated the lakes into those dominated (1) by Heterocystous Cyanobacteria * 0.3 *** 0.48 * –0.32 Dinophyta, (2) by heterocystous cyanobacteria and (3) a group where Chlorophyta, diatoms and Cryptophyta were co-dominant (Figs 2 and 3). The proportion of Di- nophyta was correlated with axis 1 (λ1 = 0.377), which explains 38% of the species data, while heterocystous cyanobacteria were weekly correlated to axis 1 and 2.

Total Cyanobacteria Total The north-west midland meres tended to be more highly associated with either heterocystous cyanobacteria or Dinophyta, while there was no clear trend within the Polish sites as a whole (data not shown). Chlorophyta * 0.35 ** –0.40 * –0.28 ** –0.4 Phytoplankton and nitrogen scarcity The proportion of Dinophyta and non-heterocystous cyanobactera were inversely correlated to the TN:TP Cryptophyta ** –0.41 ratio and the proportion of heterocystous cyanobacteria was positively correlated to the TN:TP ratio and nitrate

-a concentrations (all p < 0.05, Table 3). The proportion of Dinophyta and non-heterocystous cyanobacteria was positively correlated to lake nutrient status; Dino- phytoplankton groups which were found to be statistically significantly correlated are shown (n = 36). Table 3. SignificantTable correlation coefficients among the proportions of phytoplankton, calculated as percentage of total phytoplankton biovolume and depth (Z), altitude, TN:TP, (NO phosphorus (SRP), nitrate reactive (TP), soluble P total N (TN), total Z max Z mean Altitude TN:TP Ammonium pH TP TN SRP Nitrate Alkalinity Chlorophyll * p < 0.5, ** 0.01, *** 0.001. phyta to both total nitrogen and total phosphorus and 210 J. Fisher et al. non-heterocystous cyanobacteria to total phosphorus nitrate and ammonium and SRP, or neither nutrient, had (all p < 0.05, Table 3). The predominance of Dinophyta dropped below detectable limits, no statistically signifi- was negatively correlated to pH (p < 0.001) and het- cant differences (p < 0.05) were found. Only diatoms erocystous cyanobacteria was positively correlated to and Euglenophyta accounted for a significantly greater pH (p < 0.01) (Table 3) though pH data only exists for proportion of the biomass in lakes where neither nu- the UK sites and there were no significant relationships trient became undetectable when compared with lakes between the proportions of these phytoplankton divi- where both dropped below detectable concentrations sions and alkalinity which included data from Poland (both p < 0.05). In lakes where nitrate and ammoni- and the UK. The majority of the sites associated with um fell below detectable concentrations concurrently high proportions of heterocystous cyanobacteria such Ceratium hirundinella, araphid diatoms such as Tabel- as Anabaena subcylindrica Borge and Aphanizomenon laria spp., Asterionella formosa and centric diatoms, flos-aquae, and Chlorophyta, had TN:TP ratios of > 15. were predominant (Fig. 3b). Lakes where both avail- Indeed, the proportions of heterocystous cyanobacteria able N and P, or where neither nutrient dropped below and Chlorophyta were significantly lower in sites with detectable concentrations, were not clearly associated a mean TN:TP ratio of < 7 than in sites where mean with a characteristic phytoplankton flora (Fig. 3b). TN:TP ratio was > 15 (both p < 0.01). Lakes which had a TN:TP ratio of < 7 were dominated by non-heterocystous cyanobacteria, such as Phormidium spp. and Oscil- DISCUSSION latoria spp., Dinophyta such as Ceratium hirundinella, and diatoms (Fig. 2a, b). Phytoplankton and productivity Dinophyta and non-heterocystous cyanobacteria were most predominant in lakes where available ni- The phytoplankton of the sites consisted predomi- trogen became undetectable in the water column (Fig. nately of Chlorophyta, Dinophyta and cyanobacteria, 3a), though when the proportions of these algae in both in terms of relative proportions and absolute bio- such lakes were compared with those in lakes where volumes (Table 2). The thirty-six lakes can be grouped

Fig. 2. PCA of lakes ordinated in relation to mean growth season composition of phytoplankton, expressed as proportion of biovolume. a – phytoplankton divisions, λ1 = 0.377, λ2 = 0.237; b – phytoplankton species, λ1 = 0.418, λ2 = 0.198, key to species shown in Table 4. Nutrient ratios are TN:TP ratios and symbols are shaded to show mean TN:TP ratios at each site. Dinophyta Characterise Nitrogen Scarcity 211

Fig. 3. PCA of lakes ordinated in relation to mean growth season composition of phytoplankton, expressed as proportion of biovolume. a – phytoplankton divisions; b – phytoplankton species, eigenvalues are the same as in Fig. 2. Symbols shaded to show N:P ratio or to denote where available N or P fell below laboratory detection limits in the growth seasons samples collected (key to symbols in Table 4).

into those whose phytoplankton communities were sites with lower nutrient concentrations (Fig. 1b). This dominated by Dinophyta, those by heterocystous cy- suggests that C. hirundinella is adapted to nutrient scar- anobacteria and those where other divisions predomi- city in lakes with high trophic status. nated (Fig. 2a). Unicellular Dinophyta move faster than many other Many studies have related cyanobacteria predomi- freshwater algae (Taylor 1987), Ceratium can migrate nance in lakes to high nutrient concentrations (Trimbee at speeds up to 0.97 mhr–1 (Whittington et al. 2000). Di- and Prepas 1987, Dokulil and Treubner 2000, Reynolds nophyta are able to migrate to the water surface prior to and Petersen 2000, Downing et al. 2001, for example). dawn (Lieberman et al. 1994) and move between areas In this study however, Dinophyta and non-heterocystous of different nutrient concentration both vertically and cyanobacteria tended to dominate in the lakes with the horizontally, which may give this division a competi- highest concentrations of P and N (Table 3; Fig. 1) sug- tive advantage over other phytoplankton (Lieberman gesting that these have low competitive ability for N and et al. 1994), although the mobility of Dinophyta var- P and predominate where there are higher concentra- ies depending on the genus (Blasco 1978). The vertical tions of bioavailable nutrients. Both the proportion of motility of Ceratium is not hindered by thermal strati- Dinophyta and non-heterocystous cyanobacteria were fication of the water column (Frempong 2006), which correlated to the TN:TP ratio which can be indicative of was common during the sampling period in many of the potential N-limitation, and the proportion of non-hete- UK study sites (Fisher, unpublished) and is known to be rocystous cyanobacteria were also negatively correlated a feature of the Polish lakes in the Mazurian Lakeland to nitrate concentrations (Table 3), again suggesting pre- district (Zdanowski 1984). dominance where N is potentially limiting. The contrasting association between heterocystous At the species level, Ceratium hirundinella was the and non-heterocystous cyanobacteria and nutrient con- most abundant species at the highest nutrient concen- centrations (Table 3; Figs 2 and 3) agrees with the ap- trations while Oscillatoria retzii and a form of Oscil- proach of Blomquist et al. (1994) who argue that hetero- latoria with filament width of < 2 µm were abundant in cystous and non-heterocystous cyanobacteria should be 212 J. Fisher et al. treated separately. The lack of significant correlations cyanobacteria in lakes which appear to be potentially between ammonia and any of the phytoplankton divi- N-limited does not necessary mean that fixation was not sions suggests that the high mean growth-season con- taking place by the genera Oscillatoria, Lyngbya and –1 centrations of ammonia (> 50 µg l NH4-N) in some of Phormidium that are sometimes capable of N-fixation the lakes (Table 1) was exceeding demand. Could the (Paerl 1988), but it is unlikely given that phytoplankton correlation between the heterocystous cyanobacteria samples were taken from oxygenated upper water lay- and nitrate concentrations be a result of these algae fix- ers. There is evidence that cyanobacteria may not gain ing and therefore providing N? Horne (1971) showed their competitive dominance in N-limited lakes through that N-fixation contributed approximately 40% of the N-fixation alone, but through their highly competitive nitrogen input to an eutrophic lake, and the presence ability to sequester ammonium. Ferber et al. (2004), for of available nitrogen, especially ammonium, has been example, found that a mixed cyanobacteria population, shown to inhibit N-fixation and the development of including Aphanizomenon flos-aquae, Planktothrix heterocysts (Fogg 1971). It is likely that the cause and agaradhii and Microcystis spp., obtained most of their effect relationship between in-lake nitrogen concentra- N via uptake of ammonia rather than through N-fixing tion and N-fixing cyanobacteria may be too complex to in a N-limited pond in Vermont, USA. be represented by correlations between cyanobacteria The ability of N-fixing cyanobacteria to predomi- biomass and N concentrations in lake water samples, nate may be prevented by light limitation and light has partly as a result of the time-lag between available nu- been shown to be a potential limiting factor in Ros- trient concentration and resultant changes to the phyto- therne Mere, one of the lakes included in this study plankton composition. (Reynolds 1978, Reynolds and Bellinger 1992, Barker 2006). Pinto and Litchman (2010) have shown that Phytoplankton and nitrogen scarcity N-fixing activity is not related to N:P ratios where light Low TN:TP ratios, the occurrence of both nitrate is limiting. The occurrence of undetectable concentra- and ammonia falling below test detection limits and tions of available nutrients, despite high total nutrient the results of nutrient bioassay studies (Carvalho and concentrations in some of the lakes, however, indicates Moss 1995, James et al. 2003, Fisher et al. 2009) sug- that biological uptake of nutrients was high and not lim- gest that nitrogen was potentially limiting in more of ited by light in these sites. In the other sample lakes, the these lakes than phosphorus. It is generally assumed persistence of available concentrations of nutrients may that cyanobacteria will be more predominant in lakes be a result of light limitation. Indeed, light limitation which are N-limited (Schindler 1977, Smith 1983, Lev- may be a feature of these eutrophic moderately deep ine and Schindler 1999) and reduction of N-loading has lakes, either through self-shading as a result of the high been shown to lead to an increase in N-fixing activity phytoplankton biomass or due to mixing of the water (Schindler et al. 2008, Vrede et al. 2009) in certain lake column to depths below the euphotic zone. The vertical types. Some researchers argue that N-fixing cyanobac- migration ability of Dinophyta and bloom forming cy- teria only increase in response to relative N deficiency anobacteria, which predominate, enables them to over- in certain lakes where the physical and chemical en- come light limitation under thermally stable condition. vironment is suitable (Conley et al. 2009, Paerl 2009) Eleven of the UK meres were found to be thermally and that their N-fixing may not be sufficient to main- stratified during the growth-season (Fisher, unpub- tain phytoplankton standing stocks (Scott and McCathy lished data). 2010). In contrast, in the UK and Polish lakes, the pro- Levine and Schindler (1999) found that Dinophyta portion of heterocystous cyanobacteria was positively were particularly successful in lakes with low N:P ratios. correlated to nitrate concentrations and they predomi- In this study Dinophyta reached their greatest propor- nated in lakes which did not have low N:P ratios and tion in lakes where available N alone became exhausted where available nitrogen was detectable on all sampling (Fig. 3a, b) and the proportion of Dinophyta was in- occasions (Figs 2a, 3a; Table 3). The lakes which were versely correlated to TN:TP ratios (Table 3). Some field most likely to be N-limited (mean growth season N:P experiments show that Dinophyta have a high require- ratios of lower than 7 and where available nitrogen was ment for available nitrogen (Sakka et al. 1999, Chap- below detectable limits) were associated with either man and Pfiester 1995). Despite this, Reynolds (1973a, non-heterocystous cyanobacteria or Dinophyta popula- b) found that Ceratium hirundinella dominated, and the tions (Figs 2a, 3a). The presence of non-heterocystous growth of cyanobacteria was restricted, when nitrate Dinophyta Characterise Nitrogen Scarcity 213 became undetectable in the eplimnion during a study to overcome low epilimnion P concentrations by migra- of Crose Mere, and Lieberman et al. (1994) found that tion to the bottom lake sediment can also be limited by blooms of the dinoflagellate Gymnodinium spp. oc- low oxygen concentrations in the hypolimnion (James curred during periods of low N and high P. et al. 1992). Therefore while Dinophyta can migrate to The dinoflagellate species present in these lakes overcome P scarcity, P sequestrations may be hindered may have been able to overcome N-limitation. Heaney by bottom water anoxia, which is known to occur in and Eppley (1981) found that increased N-depletion led most of the UK meres sampled and in moderately deep to the downward migration of Dinophyta over a verti- lakes in the Mazurian Lakeland (Zdanowski et al. 1984, cal distance of 2 metres, and the avoidance of high ir- James et al. 2003). radiance at the surface, during laboratory experiments, Using Cyanobacteria for monitoring nutrient con- which would enable them to exploit the nutrient-rich centrations in lakes hypolimnion. Their rapid migration to water layers of higher nutrient concentrations and their ability to main- This study has contributed evidence that cyanobac- tain a steeper nutrient concentration gradient round their teria are not reliable indicators of low TN:TP ratios or cells, through their mobility and action of the transverse of nitrogen scarcity in moderately deep, lowland, eu- flagellum (Pollingher 1988), may also enable them to trophic lakes. Nor was the proportion of cyanobacteria out-compete other species when nitrogen is low. The clearly related to trophic status. In fact, the proportion vertical migration of Dinophyta and cyanobacteria has of heterocystous cyanobacteria was inversely corre- been shown to occur at all depths in the water column lated to TP concentrations (Table 3), while only the in Rostherne Mere and Mere Mere (The Mere) (Barker proportion of non-heterocystous cyanobacteria were 2006). During periods of N-limitation, some Dinophyta significantly correlated to TP. This has particular sig- may be able to supplement their nutrient requirements nificance in the context of the European Water Frame- through phagocytosis (Sanders 1991, Hansen and Ca- work Directive, where it has been suggested that the lado 1999, Stoecker 1999). It is unknown whether the proportion of nuisance cyanobacteria, in conjunction particular individuals of Ceratium hirundinella, pre- with chlorophyll concentrations, can be used as a meas- dominant in these lakes, were capable of mixotrophy, ure of nutrient enrichment (Solheim et al. 2008, WFD but it has previously been reported for freshwater Di- UKTAG 2008). The nuisance cyanobacteria include the nophyta, including Ceratium hirundinella (Dodge and heterocystous Anabaena and Aphanizonemon, which, Crawford 1970, Sanders 1991). Several dinophyte gen- in this study, were inversely associated with nutrient era are also known to contain N-fixing symbionts, al- concentrations, including TP (Fig. 1b; Table 3). It may though this has yet been reported for marine rather than be the lack of relationship between cyanobacteria and freshwater species (Gordon et al. 1994) though Wehr trophic state in this study is a result of these lakes com- (2003) reports the Ceratium may also injest cyano- prising predominantly eutrophic to hyper-eutrophic bacteria which may thus provide an addition nitrogen sites, rather than spanning the whole trophic spectrum, source. though such high nutrient concentrations are a common If heterotrophy is important for Dinophyta to over- occurrence across much of lowland Europe. come N-limitation, it might also be expected to allow While the lakes sampled in this study were predom- Dinophyta to avoid P-limitation. Like cyanobacteria, inately eutrophic or hypereutrophic, the concentration Dinophyta are known to have a capacity for luxury of available nutrients in the surface layers became un- uptake and storage of phosphorus for use during pe- detectable in some of the lakes, bringing about potential riods when this nutrient is low (Serruya and Berman nutrient limitation. Given that these lakes are moder- 1975, Healey 1982). Dinophyta were not predominant ately deep, the vertical separation of light and nutrients in lakes with high TN:TP ratios, or where both avail- enabled Dinophyta to predominate, and their occur- able P and N became undetectable however (Figs 2a, b; rence appeared to be more highly related to trophic sta- 3a, b). While Dinophyta are known to migrate down in tus and potential N scarcity than the proportion of het- response to P scarcity (Taylor 1987) Dinophyta tend to erocystous cyanobacteria. It is concluded that motility have lower affinities and lower uptake rates for P than and nutritional flexibility of the Dinophyta may enable other phytoplankton groups, and therefore do not have them to become at least as successful as heterocystous competitive advantage when this nutrient is limiting cyanobacteria in overcoming nitrogen scarcity in such (Berman and Dubinsky 1985). The ability of Dinophyta moderately deep lakes. 214 J. Fisher et al.

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