Optical sensor nanoparticles in artificial sediments--a new tool to visualize O2 dynamics around the rhizome and...

Seagrass communities provide important ecosystems services in coastal environments but are threatened by anthropogenic impacts. Especially the ability of seagrasses to aerate their below-ground tissue and immediate rhizosphere to prevent sulfide intrusion from the surrounding sediment is critical for their resilience to environmental disturbance. There is a need for chemical techniques that can map the O2 distribution and dynamics in the seagrass rhizosphere upon environmental changes and thereby identify critical stress thresholds of e.g. water flow, turbidity, and O2 conditions in the water phase. In a novel experimental approach, we incorporated optical O2 sensor nanoparticles into a transparent artificial sediment matrix consisting of pH-buffered deoxygenated sulfidic agar. Seagrass growth and photosynthesis was not inhibited in the experimental setup when the below-ground biomass was immobilized in the artificial sulfidic sediment with nanoparticles and showed root growth rates (∼ 5 mm day(-1)) and photosynthetic quantum yields (∼ 0.7) comparable to healthy seagrasses in their natural habitat. We mapped the real-time below ground O2 distribution and dynamics in the whole seagrass rhizosphere during experimental manipulation of light exposure and O2 content in the overlaying water. Those manipulations showed that oxygen release from the belowground tissue is much higher in light as compared to darkness and that water column hypoxia leads to diminished oxygen levels around the rhizome/roots. Oxygen release was visualized and analyzed on a whole rhizosphere level, which is a substantial improvement to existing methods relying on point measurements with O2 microsensors or partial mapping of the rhizosphere in close contact with a planar O2 optode. The combined use of optical nanoparticle-based sensors with artificial sediments enables imaging of chemical microenvironments in the rhizosphere of aquatic plants at high spatiotemporal resolution with a relatively simple experimental setup and thus represents a significant methodological advancement for studies of environmental impacts on aquatic plant ecophysiology.