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Hit or miss? Impact of time series resolution on resolving phytoplankton dynamics at hourly, weekly, and satellite remote sensing frequencies
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2024
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Source: Limnology and Oceanography: Methods, 22(4), 254-267
[PDF-2.40 MB]
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Journal Title:Limnology and Oceanography: Methods
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Description:Characterizing marine phytoplankton community variability is crucial to designing sampling strategies and interpreting time series. Satellite remote sensing, microscopy sampling, and flow through imaging systems have widely different resolutions: from weekly or monthly with microscopy sampling to daily when no cloud cover or glint is present with polar‐orbiting satellites, and hourly for autonomous imaging instruments. To improve our understanding of data robustness against sampling resolution at different taxonomic levels, we analyze 2 yr of data from an Imaging FlowCytobot with hourly resolution and resample it to daily, satellite‐temporal, and weekly microscopy sampling resolution. We show that weekly and satellite‐temporal resolutions are sufficient to resolve general community composition but that the randomness of satellite‐temporal resolution can result in overrepresenting or underrepresenting certain categories. While the yearly phytoplankton biomass bloom is detected in late winter by all four resolutions, category‐specific yearly blooms are generally consistent in timing but often underestimated or missed by the weekly and satellite‐temporal resolutions, introducing a bias in year‐to‐year comparisons. A minimum of biweekly sampling, particularly during known bloom periods, would lower the bias in such categories. Similarly, sampling time should be considered as daily variations are category‐specific. Overall, morning and low tide sampling tended to have higher biomass. We provide tables for categories detected by the IFCB in Narragansett Bay with their major bloom characteristics and recorded daily variability to inform future sampling designs. These results provide tools to interpret past and future time series, including possible detection of specific taxonomic groups with targeted satellite algorithms.
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Source:Limnology and Oceanography: Methods, 22(4), 254-267
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ISSN:1541-5856;1541-5856;
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Rights Information:CC BY
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Compliance:Submitted
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