Phytoplankton sinking is an important property that can determine community composition, affecting nutrient and light absorption in the photic zone, and influencing biogeochemical cycling via material loss to the deep ocean. To date, the difficulty in exploring the sinking processes is partly due to methodological limitations in measuring phytoplankton sinking rate. However, in the last decade, works have illustrated various methods based on some non-invasive and low perturbing approaches (laser scanner, video-microscopy, fluorescence spectroscopy). In this study, we review the methods for sinking rate estimation and describe the Plankton Tracker, a novel integrated system to investigate in vivo the dynamic sinking behavior of phytoplankton. Plankton Tracker is composed of a long-distance objective and a video-microscopy facility coupled with a specifically developed image analysis system (Plankton Tracker Elements). Diatoms and dinoflagellates were individually-tracked. By processing recorded videos and images, sinking traits (e.g. trajectory length and complexity, sinking velocity, turning angle) were obtained simultaneously with morphological traits (e.g. linear dimensions). We also applied a Biased Correlated Random Walk model to sinking traits. Particularly, we found linear motion in the colony-forming Thalassiosira sp. and sinusoidal reorientation in the dinoflagellate Scrippsiella acuminata. We found complex suspension dynamic of the large Coscinodiscus sp. In this view, the Plankton Tracker approach is likely to provide more insights towards the exploration of dynamic sinking behavior in phytoplankton.
Plankton Tracker: A novel integrated system to investigate the dynamic sinking behavior in phytoplankton
Durante G.;Roselli L.;De Nunzio G.;Marsella G.;Basset A.
2020-01-01
Abstract
Phytoplankton sinking is an important property that can determine community composition, affecting nutrient and light absorption in the photic zone, and influencing biogeochemical cycling via material loss to the deep ocean. To date, the difficulty in exploring the sinking processes is partly due to methodological limitations in measuring phytoplankton sinking rate. However, in the last decade, works have illustrated various methods based on some non-invasive and low perturbing approaches (laser scanner, video-microscopy, fluorescence spectroscopy). In this study, we review the methods for sinking rate estimation and describe the Plankton Tracker, a novel integrated system to investigate in vivo the dynamic sinking behavior of phytoplankton. Plankton Tracker is composed of a long-distance objective and a video-microscopy facility coupled with a specifically developed image analysis system (Plankton Tracker Elements). Diatoms and dinoflagellates were individually-tracked. By processing recorded videos and images, sinking traits (e.g. trajectory length and complexity, sinking velocity, turning angle) were obtained simultaneously with morphological traits (e.g. linear dimensions). We also applied a Biased Correlated Random Walk model to sinking traits. Particularly, we found linear motion in the colony-forming Thalassiosira sp. and sinusoidal reorientation in the dinoflagellate Scrippsiella acuminata. We found complex suspension dynamic of the large Coscinodiscus sp. In this view, the Plankton Tracker approach is likely to provide more insights towards the exploration of dynamic sinking behavior in phytoplankton.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
