Prymnesium parvum exotoxins affect the grazing and viability of the calanoid copepod Eurytemora affinis

Abstract

The calanoid copepod Eurytemora affinis from the northern Baltic Sea was exposed to cell-free filtrates of the toxic haptophyte Prymnesium parvum as well as to cell mixtures of P. parvum and Rhodomonas salina. To test the effects of P. parvum exudates and allelopathy on selective grazers, copepods were incubated (1) in increasing concentrations of cell-free filtrates of P. parvum in the presence of good food (R. salina), (2) in 1:1 cell mixtures at 2 cell concentrations of P. parvum and R. salina and (3) in R. salina cell suspension, which was used as a control for good-quality food. P. parvum cultures were grown in nutrient-balanced (+NP) or limited (-N or -P) media to obtain different levels of toxicity. Survival, ingestion, faecal pellet production rates and egg production were measured over 3 d, together with measurements of P. parvum toxicity (hemolytic activity) (HA). Most of the copepods incubated in high-filtrate concentrations died or became severely impaired, although (HA) in filtrates was under the detection limit. Further, the ingestion and faecal pellet production rates were suppressed in the highest filtrate concentrations in nutrient-limited treatments. Higher cell density in cell mixtures resulted in significantly lower faecal pellet production, although survival remained high. Our results show that HA is not a good overall indicator of the total harmful effects of P. parvum on grazers. Besides monospecific P. parvum diets, filtrates and cell mixtures have negative effects on grazers, and these effects are stronger under nutrient-depleted conditions; however, the presence of good-quality food lowers harmful effects for copepods. The negative effects caused either by direct intoxication or by food limitation following from strong allelopathic effects of P. parvum on other components of nano-and microplankton suggest that P. parvum blooms have a realistic potential to be deleterious for copepod secondary production, irrespective of the presence of alternative food sources.KEY WORDS: Prymnesium parvum · Exotoxins · Hemolytic activity · Eurytemora affinis · Viability · Feeding · Faecal pellet production · Egg production rateResale or republication not permitted without written consent of the publisher

Transcriptomic response of the toxic prymnesiophyte Prymnesium parvum (N. Carter) to phosphorus and nitrogen starvation

“…Several researchers found enhanced intracellular toxicity in Nstarved P. parvum cells (Johansson and Grané li, 1999;Uronen et al, 2005), but according to others, the toxicity of N-depleted cells does not differ significantly from that of nutrient replete cells (Lindehoff et al, 2009;Sopanen et al, 2008). Our findings concerning the intracellular toxicity support the latter observation (Fig.…”

Approach for Supporting Food Web Assessments with Multi-Decadal Phytoplankton Community Analyses—Case Baltic Sea

“…Cyanobacteria and prymnesiophytes have been shown to be low-quality food for herbivorous zooplankton (de Bernardi and Giussani, 1990;Sopanen et al, 2008), while cryptophytes, which decreased in most of the study area, are considered highquality food (Lehman and Sandgren, 1985). On the other hand, the cyanobacterium N. spumigena is known to be a good thiamine source for zooplankton (Sylvander et al, 2013), and thus optimal food may contain a small share of it.…”

“…Instead, we point out some functional characteristics which should be considered. Those functional characteristics (potential suitability as food for grazers, harmfulness, size, trophy) are common to all phytoplankton communities, and were selected based on existing knowledge on their relevance to the next trophic level (e.g., Koski et al, 1998;Sommer et al, 2000;Berglund et al, 2007;Sopanen et al, 2008). Using these functional characteristics within the interpretation of the taxonomic results is novel compared to some other recent approaches on analyzing longterm phytoplankton monitoring data (e.g., Suikkanen et al, 2013;Godhe et al, 2015;Haraguchi et al, 2015).…”

“…Kuuppo et al, 2006;Sipiä et al, 2006;Setälä et al, 2009Setälä et al, , 2014. In the Baltic Sea, phytoplankton toxins have been found in e.g., copepods (Lehtiniemi et al, 2002;Setälä et al, 2009;Sopanen et al, 2011), bivalves (Sipiä et al, 2001;Setälä et al, 2014), Baltic herring, flounder and roach, as well as eider (Sipiä et al, 2006;Karjalainen et al, 2008) with immediate effects of these compounds including reduced feeding and growth rates in fish larvae (Karjalainen et al, 2007), and even mortality in copepods (Sopanen et al, 2008) and fish (Lindholm and Virtanen, 1992). Allelopathy, i.e., the production of allelochemicals which negatively influence the growth and survival of other phytoplankton species, may have an effect on phytoplankton composition and thus affect grazers by modifying the availability of their preferred food (Reigosa et al, 2006).…”

“…The approach consists of four steps: (1) long-term trend analysis of class-level and total phytoplankton biomass using generalized additive models (GAMs) and calculating average biomass share of each phytoplankton class from the total phytoplankton biomass, (2) comparing the current phytoplankton community composition and its long-term changes with non-metric ordination analysis (NMDS) of genus-level biomass, (3) describing which taxa (the most accurate taxonomic level) are primarily responsible for forming the biomass and for causing the possible changes, and (4) interpretation of the phytoplankton results to assess the potential effects on the next trophic level. Potential suitability as food for grazers, harmfulness, cell size, and trophy are the characteristics of the dominant or increased or decreased taxa which are specifically considered when interpreting the results (step 4), based on existing knowledge on their relevance to the next trophic level (e.g., Koski et al, 1998;Sommer et al, 2000;Berglund et al, 2007;Sopanen et al, 2008). Even though we demonstrate the approach with northern Baltic Sea phytoplankton data, the approach can be used for other sea areas as well since the methods are applicable with any long-term data and the functional characteristics which are specifically considered (quality as food, harmfulness, trophy, cell size) are common to all phytoplankton communities.…”