Live cell analysis at sea reveals divergent thermal performance between photosynthetic ocean microbial eukaryote populations

Abstract

Experimentation at sea provides insight into which traits of ocean microbes are linked to performance in situ. Here we show distinct patterns in thermal tolerance of microbial phototrophs from adjacent water masses sampled in the southwest Pacific Ocean, determined using a fluorescent marker for reactive oxygen species (ROS). ROS content of pico-eukaryotes was assessed after 1, 5 and 25 h of incubation along a temperature gradient (15.6-32.1°C). Pico-eukaryotes from the East Australian Current (EAC) had relatively constant ROS and showed greatest mortality after 25 h at 7°C below ambient, whereas those from the Tasman Sea had elevated ROS in both warm and cool temperature extremes and greatest mortality at temperatures 6-10°C above ambient, interpreted as the outcome of thermal stress. Tracking of water masses within an oceanographic circulation model showed populations had distinct thermal histories, with EAC pico-eukaryotes experiencing higher average temperatures for at least 1 week prior to sampling. While acclimatization and community assembly could both influence biological responses, this study clearly demonstrates that phenotypic divergence occurs along planktonic drift trajectories.

Structural Characteristics and Driving Factors of the Planktonic Eukaryotic Community in the Danjiangkou Reservoir, China

“…Many changes occur in the reservoir each spring: The reservoir capacity declines, the frequency of water exchange decreases, and as temperatures rise, most of the plankton begin to reproduce rapidly. According to the geographical characteristics of the Danjiangkou Reservoir [11], five sampling sites in the Henan area of the reservoir were selected for sampling in May 2017 and May 2018. Kuxin (K) is located in the center of the Danjiangkou Reservoir.…”

“…Long-term monitoring shows that all the variables in the Danjiangkou Reservoir except TN meet the requirements of class I or II water standards. Exceeding the standard for TN is an important environmental problem in the reservoir area and watershed [8,11,35]. Although the TN content is not included in the national evaluation standards for surface water in China, nitrogen, and phosphorus nutrient sources are the most important cause of lake eutrophication.…”

“…With the advent and improvement of high-throughput sequencing technology [7], eukaryotic diversity can be evaluated. High-throughput sequencing of specific PCR products, such as eukaryotic 18S rDNA genes, on such platforms, can be used to obtain information on eukaryotic community structure, evolutionary relationships, and correlations between eukaryotic plankton and the environment [8][9][10][11]. Molecular biology has been widely used in studying plankton in water [12][13][14][15][16].…”

Small-scale convective turbulence constrains microbial patchiness

“…IBMs are particularly well-suited to explicitly modelling 3D aquatic ecosystems in complex flow regimes, wherein agents must interact individually with their local environment (a turbulent eddy, for instance, or a nutrient patch), and/or with each other, and where complex ecosystem dynamics can emerge naturally from the collective behaviour of individuals in the model. IBMs of this kind have already seen active service in ecological research pertaining to questions as diverse as microbial patchiness 32 and evolutionary dynamics 58 , spatial dynamics of fish 59 , fish larvae 60 and sea turtle hatchlings 61 , thermal responses in phytoplankton populations 62 and the dynamics of ocean plastics [63][64][65] . Here we describe the mathematical framework of our microbial motility model and its implementation using the OceanParcels 66,67 Lagrangian analysis toolkit.…”

Investigating microscale patchiness of motile microbes driven by the interaction of turbulence and gyrotaxis in a 3D simulated convective mixed layer.

“…IBMs are particularly appropriate for explicitly modelling 3D aquatic ecosystems in complex flow regimes, wherein agents must interact individually with their local environment (a turbulent eddy, for instance, or a nutrient patch), and/or with each other, and where complex ecosystem dynamics can emerge naturally from the collective behaviour of individuals in the model. IBMs of this kind have already seen active service in ecological research pertaining to questions as diverse as microbial patchiness [32] and evolutionary dynamics [58], spatial dynamics of fish [59], fish larvae [60] and sea turtle hatchlings [61], thermal responses in phytoplankton populations [62] and the dynamics of ocean plastics [63][64][65]. Here we describe the mathematical framework of our microbial motility model and its implementation using the OceanParcels [66,67] Lagrangian analysis toolkit.…”