Machine learning techniques to characterize functional traits of plankton from image data.

Plankton imaging systems supported by automated classification and analysis have improved ecologists' ability to observe aquatic ecosystems. Today, we are on the cusp of reliably tracking plankton populations with a suite of lab-based and in situ tools, collecting imaging data at unprecedentedly fine spatial and temporal scales. But these data have potential well beyond examining the abundances of different taxa; the individual images themselves contain a wealth of information on functional traits. Here, we outline traits that could be measured from image data, suggest machine learning and computer vision approaches to extract functional trait information from the images, and discuss promising avenues for novel studies. The approaches we discuss are data agnostic and are broadly applicable to imagery of other aquatic or terrestrial organisms.

Reconciliation of the carbon budget in the ocean's twilight zone.

Photosynthesis in the surface ocean produces approximately 100 gigatonnes of organic carbon per year, of which 5 to 15 per cent is exported to the deep ocean. The rate at which the sinking carbon is converted into carbon dioxide by heterotrophic organisms at depth is important in controlling oceanic carbon storage. It remains uncertain, however, to what extent surface ocean carbon supply meets the demand of water-column biota; the discrepancy between known carbon sources and sinks is as much as two orders of magnitude. Here we present field measurements, respiration rate estimates and a steady-state model that allow us to balance carbon sources and sinks to within observational uncertainties at the Porcupine Abyssal Plain site in the eastern North Atlantic Ocean. We find that prokaryotes are responsible for 70 to 92 per cent of the estimated remineralization in the twilight zone (depths of 50 to 1,000 metres) despite the fact that much of the organic carbon is exported in the form of large, fast-sinking particles accessible to larger zooplankton. We suggest that this occurs because zooplankton fragment and ingest half of the fast-sinking particles, of which more than 30 per cent may be released as suspended and slowly sinking matter, stimulating the deep-ocean microbial loop. The synergy between microbes and zooplankton in the twilight zone is important to our understanding of the processes controlling the oceanic carbon sink.

Microbial gardening in the ocean's twilight zone: detritivorous metazoans benefit from fragmenting, rather than ingesting, sinking detritus: fragmentation of refractory detritus by zooplankton beneath the euphotic zone stimulates the harvestable production of labile and nutritious microbial biomass.

Sinking organic particles transfer ∼10 gigatonnes of carbon into the deep ocean each year, keeping the atmospheric CO2 concentration significantly lower than would otherwise be the case. The exact size of this effect is strongly influenced by biological activity in the ocean's twilight zone (∼50-1,000 m beneath the surface). Recent work suggests that the resident zooplankton fragment, rather than ingest, the majority of encountered organic particles, thereby stimulating bacterial proliferation and the deep-ocean microbial food web. Here we speculate that this apparently counterintuitive behaviour is an example of 'microbial gardening', a strategy that exploits the enzymatic and biosynthetic capabilities of microorganisms to facilitate the 'gardener's' access to a suite of otherwise unavailable compounds that are essential for metazoan life. We demonstrate the potential gains that zooplankton stand to make from microbial gardening using a simple steady state model, and we suggest avenues for future research.

Similarities between the biochemical composition of jellyfish body and mucus.

Recognition of the importance of jellyfish in marine ecosystems is growing. Yet, the biochemical composition of the mucus that jellyfish constantly excrete is poorly characterized. Here we analyzed the macromolecular (proteins, lipids and carbohydrates) and elemental (carbon and nitrogen) composition of the body and mucus of five scyphozoan jellyfish species (Aurelia aurita, Chrysaora fulgida, Chrysaora pacifica, Eupilema inexpectata and Rhizostoma pulmo). We found that the relative contribution of the different macromolecules and elements in the jellyfish body and mucus was similar across all species, with protein being the major component in all samples (81 ± 4% of macromolecules; 3.6 ± 3.1% of dry weight, DW) followed by lipids (13 ± 4% of macromolecules; 0.5 ± 0.4%DW) and carbohydrates (6 ± 3% of macromolecules; 0.3 ± 0.4%DW). The energy content of the jellyfish matter ranged from 0.2 to 3.1 KJ g-1 DW. Carbon and nitrogen content was 3.7 ± 3.0 and 1.0 ± 0.8%DW, respectively. The average ratios of protein:lipid:carbohydrate and carbon:nitrogen for all samples were 14.6:2.3:1 and 3.8:1, respectively. Our study highlights the biochemical similarity between the jellyfish body and mucus and provides convenient and valuable ratios to support the integration of jellyfish into trophic and biogeochemical models.