Cyanobacteria are an ancient group of autotrophic bacteria that are found in both freshwater and marine environments and are an important component of the primary producers (Huisman et al. 2005). Cyanobacteria dominate at high nutrient concentrations and high temperatures, and in inland standing waters throughout the world, there is an increasing incidence of dense cyanobacteria blooms fuelled by eutrophication and climate change (Kardinaal and Visser 2005; Zurawell et al. 2005; Jöhnk et al. 2008; Paerl and Huisman 2008; Kosten et al. 2011). Many cyanobacteria species produce a diverse range of toxic metabolites and bioactive compounds such as hepato-, neuro-, cyto- and endotoxins (Sivonen and Jones 1999; Codd et al. 2005) that are hazardous to both human and livestock health (Kuiper-Goodman et al. 1999; Codd et al. 2005). Cyanobacteria blooms can cause major problems both in terms of ecological structure and functioning of aquatic systems (Ghadouani et al. 2003; Dao et al. 2010) as well as public health, livestock health and recreation (Bell and Codd 1994; Jochimsen et al. 1998; Kuiper-Goodman et al. 1999; Ouellette and Wilhelm 2003; Zimba et al. 2006; Stewart et al. 2008; Martínez Hernandez et al. 2009). Much effort is therefore invested in preventing or controlling cyanobacteria blooms (Chorus and Mur 1999; Codd 2000; Paerl et al. 2001). The most effective management is to avoid cyanobacteria blooms by reducing nutrient loads and restoring water quality (Chorus and Mur 1999; Paerl et al. 2001; Anderson et al. 2002). Hence, most applications with respect to the control of nuisance cyanobacteria blooms take a bottom-up approach. They often involve profound interference with the physical or chemical structure of water bodies, such as artificial mixing or flushing (e.g. Huisman et al. 2004, 2005; Maier et al. 2004) or precipitation and fixation of phosphorus in the sediments with La- or Al-rich clays (Douglas et al. 1999; Robb et al. 2003; van Oosterhout and Lürling 2011). A reduction of nutrient loads is, however, sometimes hard to achieve, especially when sources of nutrient input are diffuse or when nutrient enrichment is partly because of atmospheric deposition. And even when successful, most of these approaches are expensive and work only in relatively small water bodies and in systems for which a heavy investment is counterbalanced by strong added value, such as public swimming waters. Another much advocated strategy to improve the ecological quality of nutrient-enriched water bodies and prevent the occurrence of cyanobacterial blooms is to combine control of external nutrient inputs with food-web manipulation (Moss et al. 1996; Madgwick 1999; Jeppesen et al. 2007; Kasprzak et al. 2007). Several recent studies have focused on potential agents of biological control for the prevention of cyanobacterial blooms, using bacteria, viruses and unicellular grazers (e.g. Sigee et al. 1999; Nishibe et al. 2004; Choi et al. 2005; Tucker and Pollard 2005; Honjo et al. 2006; Zhang et al. 2008; Van Wichelen et al. 2010), exploiting allelopathic interactions (Wu et al. 2011) or manipulating fish stocks (Madgwick 1999; Jeppesen et al. 2007; Kasprzak et al. 2007). An important asset of biological control of cyanobacteria blooms resides in the fact that the controlling agent through its population growth may exert its impact throughout larger water bodies and for longer periods of time. Top–down control may also be more powerful in shallow water bodies where internal eutrophication through resuspension of sediments reduces the strength of bottom-up control (Moss 2010). There are many known cases of successful biomanipulation, including a few cases in which bloom-forming cyanobacteria were kept under control by zooplankton grazing (Peretyatko et al. 2010).
Zooplankton–cyanobacteria interactions have been discussed extensively over the years, yet the literature yields a highly inconsistent picture (see also Zurawell et al. 2005). Several studies indicate that Daphnia may control the development of Microcystis blooms depending on initial conditions and history (e.g. Christoffersen et al. 1993; Matveev et al. 1994; Sarnelle 2007; Dejenie et al. 2009; Peretyatko et al. 2010). Other studies, however, reported that toxic Microcystis could not be controlled by zooplankton grazing, as Microcystis suppressed Daphnia population growth and resulted in a decrease in zooplankton biomass and a shift in zooplankton community structure towards smaller species and individuals (e.g. Ghadouani et al. 2003). In line with these observations, there are several cases where biomanipulation failed when cyanobacteria were present (Gliwicz 1990; Gulati et al. 2008). Large-bodied zooplankton species are claimed to be particularly vulnerable as they can ingest the cyanobacteria and thus get intoxicated (Gliwicz and Siedlar 1980). Microcystis, a commonly occurring cyanobacterium genus, can suppress zooplankton in several ways. First, through the formation of colonies, they may reduce ingestion and interfere with filtering activity in Daphnia (Lampert 1981, 1982). Secondly, cyanobacteria tend to be poor food. They feature low levels of highly unsaturated fatty acids and low sterol contents (Brett and Müller-Navarra 1997; von Elert et al. 2003), and their membrane and mucilage layers are not readily digestible (Kurmayer and Jüttner 1999), which renders them nutritionally unfavourable for zooplankton compared with, for example, green algae. Thirdly, Microcystis strains produce a wide range of secondary metabolites. Examples of cyanotoxins that are deleterious to Daphnia are microcystins (Chen et al. 2005), protease inhibitors (Schwarzenberger et al. 2010), microviridin peptides (Kaebernick et al. 2001), and the polyunsaturated fatty acid gamma-linolenic acid (Reinikainen et al. 2001), among others (Nizan et al. 1986; Jungmann and Benndorf 1994). Other studies, however, did not find any deleterious effect of cyanobacteria on Daphnia (De Bernardi et al. 1981; Matveev et al. 1994).
An important finding in the debate on Microcystis–zooplankton interactions is the observation that there are genetic differences both in the grazer and the prey in their mutual responses (Kurmayer et al. 2001; Wilson et al. 2005). For example, the ability to form colonies in the presence of grazers (e.g. van Gremberghe et al. 2009a), the fatty acid composition (e.g. Martin-Creuzburg et al. 2008), and secondary metabolites differs among Microcystis strains, thus potentially inducing a very diverse response in zooplankton (Jungmann 1992; Czarnecki et al. 2006). Likewise, differences in responses of Daphnia when exposed to cyanobacteria have been reported (Hietala et al. 1995; Hairston et al. 2001; Schwarzenberger et al. 2010). In recent years, evidence has accumulated that Daphnia may develop tolerance against toxic cyanobacteria (Gustafsson and Hansson 2004; Sarnelle and Wilson 2005; Blom et al. 2006; Wilson et al. 2006; Sarnelle et al. 2010) and may genetically adapt to better cope with cyanotoxins (Hairston et al. 1999, 2001; Gustafsson et al. 2005). Sarnelle and Wilson (2005) and Blom et al. (2006) compared Daphnia clones isolated from lakes with low and high prevalence of bloom-forming cyanobacteria and concluded that populations exposed to high cyanobacterial levels over long periods of time can genetically adapt to being more tolerant to toxic cyanobacteria in the diet. Hairston et al. (1999, 2001) similarly showed genetic adaptation of Daphnia in Lake Constance to increased abundances of cyanobacteria over time using a resurrection ecology approach, hatching Daphnia clones from different time periods corresponding to different eutrophication periods of the dormant egg bank. Gustafsson and Hansson (2004) and Gustafsson et al. (2005) demonstrated induced and maternally transferred tolerance in Daphnia when pre-exposed to Microcystis. They observed a higher survival probability, accelerated maturation and early first reproduction as well as a higher number of offspring when comparing animals born from Microcystis-exposed mothers compared to naive Daphnia.Sarnelle et al. (2010) observed that Daphnia populations with prior experience with toxic cyanobacteria may show positive population growth even at high concentrations of cyanobacterial toxins. Acclimation and genetic adaptation likely play a significant role in determining Microcystis–Daphnia interactions.
Microcystis and Daphnia may strongly interact with each other, as Microcystis may intoxicate Daphnia, whereas Daphnia may feed on Microcystis. The high amount of genetic variation in defence mechanisms in Microcystis strains and in resistance to Microcystis toxins in Daphnia then raises the question to what extent populations of both species may coevolve in response to each other, leading to local coadaptation (Thompson 2005). The occurrence of genotype × genotype interactions is a prerequisite for the development of local adaptation in a dynamic, geographic mosaic of coevolution (Thompson 2005). As a first test of this idea, we designed an experiment to quantify to what extent susceptibility to Microcystis in Daphnia is not only dependent on Daphnia genotype and Microcystis strain, but also on genotype × genotype interactions, similar as in, for example, host–parasite interactions (e.g. Carius et al. 2001). Genotype × genotype interactions would explain why in some studies Daphnia seem to be able to control Microcystis, whereas in other systems, Microcystis seem to control Daphnia. Using a meta-analysis approach, Wilson et al. (2006) also concluded that toxicity induced by cyanobacteria on growth rate and survival is strongly dependent on the cyanobacterium and zooplankton strains used, and not as much on the presence or absence of microcystins, as is generally accepted. Here, we experimentally test for genotype × genotype interactions in a systematic way by confronting 10 different genotypes of the water flea Daphnia with 10 different strains of the cyanobacterium Microcystis in a full factorial design. Getting a better grip on genotype × genotype interactions and potential coadaptation between daphnia and toxic cyanobacteria might help to develop successful strategies for top–down control of toxic blooms by zooplankton grazers.