Simulated upwelling and marine heatwave events promote similar growth rates but differential domoic acid toxicity in Pseudo-nitzschia australis

模拟上升流和海洋热浪事件促进了南极拟菱形藻(Pseudo-nitzschia australis)相似的生长速率,但对软骨藻酸的毒性作用却有所不同。

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Abstract

Along the west coast of the United States, highly toxic Pseudo-nitzschia blooms have been associated with two contrasting regional phenomena: seasonal upwelling and marine heatwaves. While upwelling delivers cool water rich in pCO(2) and an abundance of macronutrients to the upper water column, marine heatwaves instead lead to warmer surface waters, low pCO(2), and reduced nutrient availability. Understanding Pseudo-nitzschia dynamics under these two conditions is important for bloom forecasting and coastal management, yet the mechanisms driving toxic bloom formation during contrasting upwelling vs. heatwave conditions remain poorly understood. To gain a better understanding of what drives Pseudo-nitzschia australis growth and toxicity during these events, multiple-driver scenario or 'cluster' experiments were conducted using temperature, pCO(2), and nutrient levels reflecting conditions during upwelling (13 °C, 900 ppm pCO(2), replete nutrients) and two intensities of marine heatwaves (19 °C or 20.5 °C, 250 ppm pCO(2), reduced macronutrients). While P. australis grew equally well under both heatwave and upwelling conditions, similar to what has been observed in the natural environment, cells were only toxic in the upwelling treatment. We also conducted single-driver experiments to gain a mechanistic understanding of which drivers most impact P. australis growth and toxicity. These experiments indicated that nitrogen concentration and N:P ratio were likely the drivers that most influenced domoic acid production, while the impacts of temperature or pCO(2) concentration were less pronounced. Together, these experiments may help to provide both mechanistic and holistic perspectives on toxic P. australis blooms in the dynamic and changing coastal ocean, where cells interact simultaneously with multiple altered environmental variables.

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