Zooplankton feeding behaviour and survival to toxic and non-toxic cyanobacteria during the seasonal bloom progression of a eutrophic lake

Harmful cyanobacterial blooms pose increasing threats to aquatic ecosystems and human health; yet, the role of zooplankton grazing in regulating blooms remains understudied. We investigated the seasonal feeding behaviour and fitness consequences of feeding preferences in natural zooplankton communities for toxic (microcystin-producing) versus non-toxic cyanobacteria across temperature gradients in eutrophic Lake Greifen, Switzerland. We conducted monthly experiments from April to October 2023 to test the grazing behaviour of four zooplankton groups (daphnids, calanoid copepods, cyclopoid copepods, and microzooplankton) exposed to mixed diets of green algae and either toxic or non-toxic Microcystis strains at 15 °C and 25 °C. Contrary to expectations of cyanobacteria avoidance, zooplankton exhibited predominantly non-selective grazing throughout the seasonal succession, consuming both toxic and non-toxic cyanobacteria at similar rates, regardless of temperature. Notably, during the peaks of phytoplankton abundance (April and September), mesozooplankton demonstrated a selective preference for cyanobacteria over green algae, particularly non-toxic strains. Temperature effects were subtle but revealed metabolic constraints: elevated temperatures occasionally triggered selective consumption of cyanobacteria in copepods, while fitness costs (survival) from exposure to toxic species were mostly restricted to transitional bloom periods and high-temperature conditions. These findings suggest that toxic cyanobacteria may not always evade grazing pressure through secondary metabolite deterrent effects. Our results suggest that zooplankton communities can adapt and graze on cyanobacteria regardless of toxicity under the tested conditions, even during bloom conditions. These observations highlight the potential for zooplankton to interact with cyanobacterial populations, which may have implications for bloom prediction and management strategies, particularly under climate warming scenarios.