Timo Basen, Katja Maren Fleckenstein, Karsten Rinke, Karl-Otto Rothhaupt and Dominik Martin-Creuzburg
Abstract
The invasive clam Corbicula fluminea was first recorded in Lake Constance (Germany) in 2003; since then its distribution spread in the lake. Clams being filter feeders largely depend on food supply in the water column. Thus, seasonal variation in water temperature and seston composition may determine the individual growth performance of benthic clams. To understand factors affecting growth and survival of C. fluminea in Lake Constance, field experiments were performed throughout the year 2010. Therefore, the temperature, algal composition and quality of seston (lipid, macronutrient composition) in different water depths were documented and growth rates of clams were estimated. Additionally, elemental and biochemical composition of clam tissue was analysed. Accompanying the field studies, standardized laboratory growth experiments were performed at temperatures between 4 and 25 °C. Using principal component analysis and linear models, correlations between seston- or clam tissue-parameters and clam growth rates were statistically investigated. In winter, clams were exposed to low temperatures (< 5 °C) combined with low food supply resulting in high mortality and no shell or tissue growth. Throughout the year, when temperatures exceeded 10 °C, growth of clams was recorded. Analyses showed that the growth of C. fluminea in Lake Constance is mainly determined by water temperature.
Additionally, a strong linear correlation between growth and temperature was confirmed in laboratory tests. Since growth and development of C. fluminea occurs only above a temperature 10 °C, only 7 months are available for reproduction and growth of the clam population in Lake Constance. Corbicula fluminea may benefit from climate change which leads to milder winter temperatures, causing reduced mortality rates, and to an earlier onset of thermal stratification in spring, extending the growing season of C. fluminea. This may support further spread in Lake Constance.
Key words: essential lipids, food quality, invasive species, seasonal succession, temperature
Introduction
The introduction of new species in ecosystems is often highly correlated with a decrease of biodiversity and ecosystem stability, disturbance of food web processes, introduction of new diseases and parasites and displacement of native species (Sala et al. 2000; Chandra and Gerhardt 2008; Ellis et al. 2011; Poulin et al. 2011). Especially in freshwater systems, the introduction of new species is often caused by human activities (Pollux et al. 2003; Briski et al. 2011). A challenge of invasion biology is to identify the mechanisms enabling a successful establishment of non-native species in new habitats. In this context, global warming is discussed as a factor that can favour the successful migration of non-native species (Stachowicz et al. 2002). In addition to increasing temperatures, survival and growth of non-native species and thus the probability of a successful establishment in an invaded habitat may be affected by food availability and food quality. Food quality of phytoplankton for freshwater invertebrates depends on a variety of different factors like morphology or toxicity (Carmichael 1992; Van Donk et al. 2011), but also on the elemental (Elser et al. 2000;
Sterner and Elser 2002) and biochemical composition (Brett and Müller-Navarra 1997;
Martin-Creuzburg and Von Elert 2009). For instance, the biochemical composition of seston can change over the growth period (Tilman et al. 1982; Gächter and Bloesch 1985), due to the succession of species and to seasonal changes in growth conditions, e.g. light and nutrient availability (Harrison et al. 1990; Hessen et al. 2002). Seasonal changes in food quality for filter feeding cladocerans have been investigated in Lake Constance before (Wacker and Von Elert 2001; Hartwich et al. 2012).
Fig. 10 Map of Lake Constance. The circle shows the sampling site of Corbicula fluminea; the arrow indicates the experimental area.
In the last decades, the occurrence of invasive species in freshwater systems has increased considerably (Richardson and Pysek 2008). In central Europe the River Rhine system is a region with ongoing invasions (Tittizer et al. 2000; Bij de Vaate et al. 2002) with potential threads for Lake Constance ecosystem (Hanselmann 2011). In particular, among the molluscs there are many invasive freshwater species that spread worldwide. Quite often they can form massive stocks in rivers and affect biomass and composition of primary producers, which in turn can have significant consequences for the ecosystem (Strayer 2010). Invasive bivalves can significantly affect the structure of native benthic communities, as has been shown for the successful invasion of Dreissena polymorpha in Lake Constance in the 1960s (Mörtl and Rothhaupt 2003). Another non-native bivalve in Lake Constance is the Asian clam Corbicula fluminea, which has been first recorded in the lake in 2003 (Werner and Mörtl 2004; see Fig. 10). Corbicula fluminea originates from East Asia and has been introduced in many freshwater ecosystems in North America and Europe in the past (Mouthon 1981;
McMahon 1982; Den Hartog et al. 1992). A rapid expansion in European inland waters followed (Kinzelbach 1991; Turner et al. 1998). Although C. fluminea has successfully invaded Lake Constance, it has a reduced maximum size and only one reproductive period per year which may explain why the population size increased rather slowly since 2003 (Werner 2008). Nevertheless, when habitat conditions are favourable (i.e. sand, absence of D. polymorpha), it can build up massive stocks and dominate the local benthos community comprising up to 90% of the total benthic biomass (Werner and Rothhaupt 2007).
Lake Constance is a large, monomictic, oligotrophic, prealpine lake situated on the northern edge of the central European Alps. After winter circulation, thermal stratification induces phytoplankton growth (Rinke et al. 2010). Phytoplankton community in spring is dominated by centric diatoms and cryptophytes summer species are dominated by grazing resistant diatoms (Sommer 1985; Gaedke 1992).
Aim of this study was to investigate the relative importance of abiotic (i.e. temperature) and biotic (i.e. food quantity and quality) factors potentially influencing growth and survival of C.
fluminea in Lake Constance. Therefore, field experiments were conducted during winter, spring, summer and autumn in 2010 (one in each season) in which field-collected clams were exposed in different depths in the lake for seven weeks. Clam growth rates were determined and related to prevailing temperatures and to different quantitative and qualitative seston characteristics, i.e. chlorophyll a, species composition, elemental (carbon, nitrogen, phosphorus) and biochemical composition (fatty acids, sterols). Each field experiment was accompanied by a standardized laboratory growth experiment conducted at different temperatures and defined food supply in order to assess conditional changes among field-collected clams during the season.
Materials and methods
Clam sampling
Juvenile C. fluminea were collected in the upper basin of Lake Constance at a sampling site close to the Austrian border (E 9°37′/N 47°30′) as described by Werner and Rothhaupt (2008). The clams were collected at a water depth of 2 - 3 m by scuba-diving 1 - 2 weeks prior to the experiments (see Tab. 5). After separation of living individuals from debris, sand and gravel, they were placed in flow-through systems with filtered (< 30 µm), aerated lake water and pre-combusted sediment at an ambient water temperature of 9 - 12 °C until the start of the respective growth experiments.
Growth experiments
For growth experiments we used juveniles which were not sexually mature to maximize somatic growth rates. Prior to the experiments, each clam was twofold measured (length, width, height) with an electrical calliper (Digi-Met, IP 65), weighed (Mettler UMT2, ± 0.1 µg) and marked individually with nail polish. Field and laboratory experiments were conducted simultaneously during winter, spring, summer and autumn 2010, the former lasted seven weeks and the latter four weeks (see Tab. 5). Slightly varying durations of the field experiments (47 - 51 days) were due to bad weather conditions during the intended days of completion.
Fig. 11 Setup of field experiments. Clams were placed in boxes, installed on a chain, adjustable in depth via deflector rolls and floating buoys.
Field experiment
For field experiments, 400 clams were randomly grouped into subsamples of 20 clams which were required for each treatment and stored in a flow through system with lake water until the experiments started (< 12 h). At the beginning of the experiments, these individuals were placed in plastic boxes (0.01 m²) containing sediment (1.5 l volume, grain size < 2 mm) collected at the clam sampling site. Boxes were attached to a deflector roll construction with floating buoys to enable a flexible adjustment to water level variations during the experiments (Fig. 11). Four chains each with five boxes were exposed in the littoral of Upper Lake Constance (E9°12.163'/N47°41.505'; Fig. 10, see Mörtl and Rothhaupt 2003 for detailed description of the study site); the boxes were exposed at 2, 4, 6, 8 and 10 m below surface.
After 7 weeks of exposure, boxes were recovered and clams were separated from sediment.
Water temperature was recorded hourly with data loggers attached to each box at one of the four chains (HOBO UA-002-64, Onset). Seston samples were taken weekly at five different water depths (2, 4, 6, 8 and 10 m below surface) close to the boxes using a standard water sampler. The water was filtered on site (< 140 µm) and transported into the laboratory for chemical analyses.
During the field experiments, chlorophyll a (chlA) measurements were conducted twice a week between 0 and 12 m water depth using a multi-channel fluorescence probe (FluoroProbe, bbe Moldaenke). With this probe four different algae classes (Cryptophyte, Chlorophyte, Cyanobacteria, diatoms) could be classified via their specific fluorescence profiles. Probe parameters and calibration procedures are given elsewhere (Rinke et al.
2009). Data samples for time spans between experimental periods were measured weekly, only datapoints from 17.8. - 28.9.2010 were taken from routine sampling from “Überlinger See” (E9°7.743’/ N47°45.453’). A mean of data points for depth step ± 1 m were taken for specific depths.
Laboratory experiments
For laboratory growth experiments the eustigmatophyte Nannochloropsis limnetica (SAG 18.99) was cultivated semi-continuously in Cyano medium (Jüttner et al. 1983) in aerated 5 l vessels at a dilution rate of 0.2 d–1 at 22 °C with illumination at 160 μmol quanta m–2 s–1. Food suspensions were prepared every other day by concentrating the cells via centrifugation (3000 g for 10 min) and resuspension in fresh medium. Carbon concentrations of the food suspensions were estimated from photometric light extinctions (800 nm) and from carbon-extinction equations determined prior to the experiment.
The 30 days lasting laboratory experiments were carried out in climate chambers at temperatures between 4 and 25°C (see Tab. 5) in glass beakers filled with 1 l of filtered lake water (0.45 μm pore-sized membrane filter) and about one centimetre of precombusted
sediment (grain size < 2 mm, 550°C for 5 h) to allow the clams to burrow. Each of the five temperature treatments consisted of ten replicates, i.e. individual clams. Clams were taken from same population used for field experiments and were randomly transferred to each beaker and fed daily with saturating amounts (4 mg C l-1) of the N. limnetica food suspension. Water was exchanged every other day to remove faecal pellets; sediment was exchanged once a week to reduce biofilm formation. Beakers were slightly aerated, to reduce sedimentation of added algae.
Water temperatures in the experimental beakers were documented using data loggers (HOBO). Aliquots of the N. limnetica food suspensions were taken three times during each experiment for chemical analyses.
Determination of clam parameters
Somatic growth rates (gm) of C. fluminea in field and laboratory experiments were determined as the increase in total dry mass of surviving clams from the beginning (M0) to the end of the experiments (Mt) using the equation:
t M gm (lnMt ln 0)
To estimate the initial dry mass of clams at the beginning of each experiment (M0) a fresh-dry-mass regression was established prior to the experiments using the fresh and dry masses (after 48 h of freeze-drying) of 50 individuals. Growth rates of clams were calculated as means ± standard deviations (SD) for each temperature treatment (laboratory experiments;
n = 10) and for each water depth (field experiment; n = 4), respectively.
Shell growth (gL, in mm d-1) of C. fluminea was estimated from differences in shell lengths at the start (L0) and at the end of each experiment (Lt). The determination of growth rates via the increase in shell heights and widths revealed similar results as the determination of growth rates via the increase in shell lengths and, thus, they are not presented here.
t L gL (Lt 0)
Clams used for chemical analyses (carbon, nitrogen, phosphorus, fatty acids, sterols; n = 9) were dissected and the soft body was separated from the shells. The percentage of soft body dry mass (m) on total dry mass including shells (Mt) was estimated as tissue condition index (TCI).
100
Mt
TCI m
Chemical analyses
Aliquots of the N. limnetica food suspensions or of lake water containing seston (< 140 µm) were filtered onto precombusted glass-fibre filters (Whatman GF/F, 25 mm diameter) and analysed for particulate organic carbon (POC) and nitrogen (PON) using an EuroEA3000 elemental analyzer (HEKAtech GmbH). The water volume required for the analyses of lake seston was estimated from concomitantly conducted measurements of the Secchi depths, which is roughly correlated with seston concentrations.
To determine the elemental composition of clams, soft body tissues of freeze-dried clams were separated from shells and weighed. The C and N content of soft body tissues was expressed as molar C:N ratios.
For the determination of particulate phosphorus, aliquots of the N. limnetica food suspension or of lake water containing seston (< 140 µm) were collected on acid-rinsed polysulfone filters (HT-200; Pall). Clam soft-tissues were solubilized by mechanical shearing using a mortar and by ultrasound treatment in ultrapure water. Subsequently, clam, seston and algae samples were digested using a solution of 10 % potassium peroxodisulfate and 1.5
% sodium hydroxide for 60 min at 121 °C. Soluble reactive phosphorus was determined using the molybdate-ascorbic acid method (Greenberg et al. 1985).
For lipid analysis of N. limnetica or lake seston, glass-fibre filters loaded with either ~0.5 mg C for fatty acids or ~1.0 mg C for sterols were sonicated and stored at -20 °C in a mixture of dichloromethane/methanol (2:1, v/v). Soft-tissues of freeze-dried clams were separated from their shell, weighed, crushed by mechanical shearing using a mortar, sonicated and subsequently stored at -20 °C in dichloromethane/methanol (2:1, v/v). Total lipids of clam tissue or algae suspensions were extracted three times from each sample using dichloromethane/methanol (2:1, v/v) and the pooled cell-free extracts were dried under a stream of nitrogen and saponified with methanolic KOH (0.2 M, 70 °C, 1 h) for sterols or were transesterified with methanolic HCl (3 M, 60 °C, 15 min) for the analysis of fatty acids.
Subsequently, fatty acid methylesters (FAME) were extracted three times with iso-hexane (2 ml); the neutral lipids were partitioned into iso-hexane:diethylether (9:1, v:v). The lipid-containing fraction was evaporated to dryness under N2 and resuspended in iso-hexane (10 – 20 µl). Lipids were analysed by gas chromatography-flame ionization detection (GC-FID;
Hewlett-Packard 6890, Agilent Technologies) equipped with a DB-225 (J&W Scientific, 30 m, 0.25 mm inner diameter, 0.25 µm film) capillary column for FAME analysis and a HP-5 (Agilent, 30 m, 0.25 mm inner diameter, 0.25 µm film) capillary column for sterol analysis.
Details of GC configurations are given elsewhere (Martin-Creuzburg et al. 2009; 2010). Lipids were quantified by comparison to internal standards (17:0 ME and 23:0 ME; 5a-cholestan) of known concentrations, considering response factors determined previously with lipid standards (Sigma or Steraloids). Lipids were identified by their retention times and their mass spectra, which were recorded with a GC-mass spectrometer (7890A GC system, 5975C inert MSD, Agilent Technologies) equipped with a fused-silica capillary column (DB-225MS, J&W for FAMEs; DB-5MS, Agilent for sterols; GC configurations as described for FID). Sterols
were analysed in their free form. Spectra were recorded between 50 and 600 amu in the electron impact (EI) ionization mode. The limit for quantitation of fatty acids and sterols was 20 ng. The absolute amount of each sterol was related to the POC of the food sources or to the carbon content of clam soft-tissues and expressed as means ± SD.
Statistical analyses
Mortality rates of clams in the field trials were transformed (square root, arcsin, see Underwood 1997) and analysed using analysis of variance (ANOVA, Statistica, Sigmastat 6.0) followed by Tukey’s HSD test (p <0.05). Differences between TCIs at the beginning of the consecutive field experiments were also analysed using ANOVA. An analysis of covariance (ANCOVA, STATISTICA) was used to analyse the effects of water temperature and date of the experiment on clam growth rates in laboratory experiments.
Principal component analyses (PCA) and linear models were carried out using the statistical software package R (R Development Core Team 2006). Analysed parameters used in the four PCAs are presented in Tab. 4. First PCA was calculated on measured seston parameters of Lake Constance (PCA1). For each of the 18 variables, 140 data points (5 * 7 * 4; depth, weeks, experiments) were incorporated into the data set. A second PCA was performed on clam growth rates, length increase, TCI, water temperature and seston parameters (PCA2).
Each of the 21 variables were represented by 20 data points (5 depth * 4 experiments). To estimate possible correlations between clam growth rates and clam tissue parameters, a third PCA was performed (PCA3). Each of the 15 variables were represented by 20 data points (5 depth * 4 experiments). For laboratory experiments, a fourth PCA was performed on clam growth rates and tissue parameters with 16 variables represented by 20 data points (5 temperatures * 4 experiments, PCA4).
In addition to PCAs, general linear models were calculated to test for significant differences among variables (for PCA2,3,4). To explain the residual variance in the dataset, the residuals of the linear model of the growth rates in dependence on the temperature were correlated in linear models with various seston variables (for PCA2) and two-factor linear models were calculated subsequently. Akaikes information criterion (AIC) was used to evaluate the goodness of fit of the different models (Akaike 1974).
Tab. 4: Variables and abbreviations used in principal component analyses.
variables value PCA
1 2 3 4
ALA α-linolenic acid content seston µg mg C-1
ARA arachidonic acid content seston µg mg C-1
chlA total chlorophyll a concentration seston µg l-1
CN molar carbon to nitrogen ratio seston -
CP molar carbon to phosphorus ratio seston -
clamALA α-linolenic acid content clam tissue µg mg DW-1 clamARA arachidonic acid content clam tissue µg mg DW-1
clamC carbon content clam tissue mg mg TG-1
clamCN molar carbon to nitrogen ratio clam tissue - clamCP molar carbon to phosphorus ratio clam tissue -
clamDHA docosahexaenoic acid content clam tissue µg mg DW-1 clamEPA eicosapentaenoic acid content clam tissue µg mg DW-1 clamFA total fatty acid content clam tissue µg mg DW-1
clamN nitrogen content clam tissue mg mg TG-1
clamP phosphorus content clam tissue mg mg TG-1
clamPUFA PUFA content clam tissue µg mg DW-1
clamST total sterol content clam tissue µg mg DW-1
crypto cryptophyta seston µg l-1
cyan cyanobacteria seston µg l-1
depth depth seston m
diat diatoms seston µg l-1
DHA docosahexaenoic acid content seston µg mg C
EPA eicosapentaenoic acid content seston µg mg C
green green algae seston µg l-1
growth.rate growth rate via dry weight increase clam tissue d-1
lengthincrement length increase clam tissue mm d-1
mean.temp mean water temperature seston °C
POC particulate organic carbon content seston µg l-1 PON particulate organic nitrogen content seston µg l-1 Ppart particulate organic phosphorus content seston µg l-1
PUFA PUFA content seston µg mg C-1
TCI tissue condition index clam tissue -
temp water temperature seston °C
tot.FA total fatty acid content seston µg mg C
tot.ST total sterol content seston µg mg C
Results
Fig. 12 Conture plots of water temperature (a), total chlorophyll a (b) and algal composition (c-f) at the study site in Lake Constance in 2010. The values between sampling dates and between sampled water depths were interpolated linearly. The four experimental periods are accentuated.
Field experiments
During winter 2010 water of Lake Constance was mixed well and temperatures of 4 - 5 °C were measured in the water column at the study site until early April (Fig. 12a). Spring warming increased the temperature in the upper water layers during the second experimental period up to 13 °C at 2 m water depth respectively 10 °C at 10 m depth. The temperature gradient from top to bottom increased further during summer and was highest in July, during the third experimental period, with water temperatures of up to 25 °C in the upper water layers and up to 19 °C in 10 m depth. Temperature decrease started from
a b
c d
e f
August onwards. In late autumn, i.e. during experimental period four, water temperatures were between 8 and 12 °C (mean temperatures during the experiments are presented in Tab. 5).
The total chlA concentrations (Fig. 12b) roughly followed the seasonal temperature changes.
From January to April, chlA was barely detectable (<1 µg l-1). In April, chlA concentrations increased up to 4 µg l-1, with maximum concentrations of 5 - 7 µg l-1 measured in June and July. This chlorophyll maximum shifted to deeper water layers with time (Fig. 12b). A second period of higher chlA concentrations in the upper water layer was recorded between mid August and mid October. Afterwards, the chlA concentrations dropped again to 1 - 2 µg l-1. The abundance of the four different algae groups (Chlorophyceae, Cryptophyceae, cyanobacteria and diatoms) showed a time- and depth-dependent pattern (Fig. 12c - f).
Green algae were abundant from June to October with the highest concentrations occurring in 0 - 6 m water depth (maximum 3.4 µg l-1). Diatoms were abundant already at the end of April and then again in June and July with a maximum of 4.5 µg l-1 in 6 m depth. In late summer, a massive diatom assemblage was present in water layers between 6 and 8 m (Fig.
12f). Diatoms constituted the highest proportion of total chlA during the whole growth
12f). Diatoms constituted the highest proportion of total chlA during the whole growth