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Featured Paper: LISST-Holo2 in aquaculture and phytoplankton study

YANG Tianwei, LIN Jun, JIAO Junpeng, WU Yue (2025): Integrated Analysis of Phytoplankton Community Characteristics in Mussel Aquaculture Areas Using Net Sampling with Microscopy and Holographic Particle Imaging. Journal of Tropical Oceanography, in press. https://www.jto.ac.cn/EN/10.11978/2025051

The paper studies the drivers of the diurnal dynamics of phytoplankton communities in suspended mussel raft aquaculture areas in Zhejiang Province, China. Two main techniques were used:

  • A shallow-water plankton net was used to collect phytoplankton from both the full water column and the mussel farming layer (upper 5 meters). Samples were preserved with formaldehyde and analyzed under an inverted microscope for species identification and abundance.
  • A Sequoia LISST-Holo2 captured in-situ particle images in the water column, allowing for real-time, non-invasive observation of phytoplankton, especially large-sized species. LISST-Holo2 data were processed using Holo Detail and Holo Batch software.

The LISST-Holo2 was deployed vertically alongside the plankton nets to capture real-time images of phytoplankton at different depths. The images were then used to identify species, measure particle size, and analyze abundance patterns. Finally, LISST-Holo2 data were compared with traditional net sampling and microscopy to assess consistency and reliability.

75 phytoplankton species from 5 phyla were identified; diatoms and dinoflagellates were dominant. The mussel farming layer had lower species richness and abundance than the full water column but showed higher network complexity, greater community stability, and stronger interspecies interactions. Main environmental drivers were the tides in the full water column and light in the mussel layer.

The LISST-Holo2 was more effective at detecting large phytoplankton species compared to small-sized phytoplankton (< 100 um) but still detected 89% of genera identified by net sampling and subsequent microscopy analysis.

The study demonstrates the LISST-Holo2 as a powerful tool for monitoring large phytoplankton species in aquaculture environments. It offers high temporal and spatial resolution, and high consistency with traditional methods, making it suitable for dynamic ecosystem studies.