Abrupt transitions leading to algal blooms are quite well known in aquatic ecosystems and have important implications for the environment. These ecosystem shifts have been largely attributed to nutrient dynamics and food web interactions. Contamination with heavy metals such as copper can modulate such ecological interactions which in turn may impact ecosystem functioning. Motivated by this, we explored the effect of copper enrichment on such regime shifts in planktonic systems. We integrated copper contamination to a minimal phytoplankton–zooplankton model which is known to demonstrate abrupt transitions between ecosystem states. Our results suggest that both the toxic and deficient concentration of copper in water bodies can lead to regime shift to an algal-dominated alternative stable state. Further, interaction with fish density can also lead to collapse of population cycles thus leading to algal domination in the intermediate copper ranges. Environmental stochasticity may result in state transition much prior to the tipping point and there is a significant loss in the bimodality on increasing intensity and redness of noise. Finally, the impending state shifts due to contamination cannot be predicted by the generic early warning indicators unless the transition is close enough. Overall the study provides fresh impetus to explore regime shifts in ecosystems under the influence of anthropogenic changes like chemical contamination.

导致藻类大量繁殖的突变在水生生态系统中是众所周知的，并且对环境具有重要意义。这些生态系统变化在很大程度上归因于营养动态和食物网相互作用。铜等重金属污染可以调节这种生态相互作用，进而可能影响生态系统功能。受此启发，我们探索了铜富集对浮游系统中这种状态转变的影响。我们将铜污染整合到一个最小的浮游植物-浮游动物模型中，该模型可以证明生态系统状态之间的突然转变。我们的研究结果表明，水体中铜的有毒和缺乏浓度都会导致制度转变为以藻类为主的替代稳定状态。更多，与鱼类密度的相互作用也可能导致种群周期崩溃，从而导致藻类在中等铜范围内占主导地位。环境随机性可能会导致在临界点之前的状态转换，并且随着噪声强度和红度的增加，双峰性会出现显着损失。最后，除非转变足够接近，否则通用预警指标无法预测由于污染而即将发生的状态变化。总的来说，这项研究为探索在化学污染等人为变化影响下的生态系统变化提供了新的动力。环境随机性可能会导致在临界点之前的状态转换，并且随着噪声强度和红度的增加，双峰性会出现显着损失。最后，除非转变足够接近，否则通用预警指标无法预测由于污染而即将发生的状态变化。总的来说，这项研究为探索在化学污染等人为变化影响下的生态系统变化提供了新的动力。环境随机性可能会导致在临界点之前的状态转换，并且随着噪声强度和红度的增加，双峰性会出现显着损失。最后，除非转变足够接近，否则通用预警指标无法预测由于污染而即将发生的状态变化。总的来说，这项研究为探索在化学污染等人为变化影响下的生态系统变化提供了新的动力。