Global Distribution of Zooplankton Biomass Estimated by In Situ Imaging and Machine Learning

Abstract

Zooplankton plays a major role in ocean food webs and biogeochemical cycles, and provides major ecosystem services as a main driver of the biological carbon pump and in sustaining fish communities. Zooplankton is also sensitive to its environment and reacts to its changes. To better understand the importance of zooplankton, and to inform prognostic models that try to represent them, spatially-resolved biomass estimates of key plankton taxa are desirable. In this study we predict, for the first time, the global biomass distribution of 19 zooplankton taxa (1-50 mm Equivalent Spherical Diameter) using observations with the Underwater Vision Profiler 5, a quantitative in situ imaging instrument. After classification of 466,872 organisms from more than 3,549 profiles (0-500 m) obtained between 2008 and 2019 throughout the globe, we estimated their individual biovolumes and converted them to biomass using taxa-specific conversion factors. We then associated these biomass estimates with climatologies of environmental variables (temperature, salinity, oxygen, etc.), to build habitat models using boosted regression trees. The results reveal maximal zooplankton biomass values around 60°N and 55°S as well as minimal values around the oceanic gyres. An increased zooplankton biomass is also predicted for the equator. Global integrated biomass (0-500 m) was estimated at 0.403 PgC. It was largely dominated by Copepoda (35.7%, mostly in polar regions), followed by Eumalacostraca (26.6%) Rhizaria (16.4%, mostly in the intertropical convergence zone). The machine learning approach used here is sensitive to the size of the training set and generates reliable predictions for abundant groups such as Copepoda (R2 ≈ 20-66%) but not for rare ones (Ctenophora, Cnidaria, R2 < 5%). Still, this study offers a first protocol to estimate global, spatially resolved zooplankton biomass and community composition from in situ imaging observations of individual organisms. The underlying dataset covers a period of 10 years while approaches that rely on net samples utilized datasets gathered since the 1960s. Increased use of digital imaging approaches should enable us to obtain zooplankton biomass distribution estimates at basin to global scales in shorter time frames in the future.

Three major mesoplanktonic communities resolved by in situ imaging in the upper 500 m of the global ocean

“…Then, other groups were merged because they exhibited similar patterns in preliminary analysis (e.g., Copepoda and Copepoda‐like), for a final list of 28 taxa (Figure 1). Finally, the same operator reviewed a random subsample of images from each final taxonomic group, with error rates at <10% for all groups and <2.5% for most (Drago et al, 2022). Although a normalized biomass size spectrum revealed an underestimation in the 600 μm–1 mm size range, 80% of organisms in our dataset were over 1 mm in ESD, therefore accurately detected by UVP5.…”

“…New in situ cameras now image planktonic organisms in their natural environment and resolve their fine‐scale vertical distribution (Stemmann et al, 2008), while generating large datasets (Kiko et al, 2022), homogenized by reviewing images (Irisson et al, 2022). These tools also allow studying fragile taxonomic groups such as Rhizaria, whose contribution to global planktonic biomass was underestimated (Biard et al, 2016; Dennett et al, 2002; Drago et al, 2022). These approaches lack in taxonomic identification fineness, but compensate with identifications and data quantity consistency.…”

“…Concentration and biovolume estimates from the UVP5 proved coherent with those from net samples for large (>1 mm ESD) Arctic copepods, while smaller organisms were underestimated (Forest et al, 2012). Data from UVP5 was already used to estimate organic carbon vertical particle flux (Guidi et al, 2015) or study zooplankton distribution (Biard et al, 2016; Drago et al, 2022; Forest et al, 2012; Stemmann et al, 2008). Leveraging net data from the Tara Oceans expedition, Soviadan et al (2022) detected a lower particle flux attenuation in Oxygen Minimum Zones (OMZ).…”

Elemental content allometries and silicon uptake rates of planktonic Rhizaria: Insights into their ecology and role in biogeochemical cycles

“…Today, in situ imaging allows quantification and distinction at low taxonomic level of large Rhizaria as well as measurement of their biovolume (Nakamura et al 2017; Biard and Ohman 2020). Following our measurements of elemental composition on individual Rhizaria, it is very likely that previous global C biomass assessments based on in situ imaging (Biard et al 2016; Drago et al 2022) need to be revised. Indeed, all giant Phaeodaria (> 600 μ m) sampled by this method have a C density much lower (ranging from 0.6 ± 0.2 μ g C mm −3 for Aulosphaeridae to 52.9 ± 13.1 μ g C mm −3 for Castanellidae; Table 1) than the conversion factor used previously (80 μ g C mm −3 ).…”

Temperature increase alters fatty acid composition and has negative effects on reproductive output of the benthic copepod Microarthridion littorale (Copepoda: Harpacticoida)

“…Sea surface temperature (SST) rise, one of the consequences of climate change, will continue to intensify under all CO 2 emission scenarios (Kwiatkowski et al 2020). When considering climate change effects on marine ecosystem functioning copepods are a key focus group due to their high abundance (Drago et al 2022), their nutritional value for higher trophic levels (Brett et al, 2009) and their role in biogeochemical cycling (Steinberg and Landry 2017). They represent between 70-90% of the mesozooplankton in pelagic ecosystems (Turner 2004) and are amongst the most abundant taxa of the meiofauna in benthic ecosystems together with nematodes (Giere 1993).…”