Phytoplankton traits from long-term oceanographic time-series

Trait values are usually extracted from laboratory studies of single phytoplankton species, which presents challenges for understanding the immense diversity of phytoplankton species and the wide range of dynamic ocean environments. Here we use a Bayesian approach and a trait-based model to extract trait values for 4 functional types and 10 diatom species from field data collected at Station L4 in the Western Channel Observatory, English Channel. We find differences in maximum net growth rate, temperature optimum and sensitivity, half-saturation constants for light and nitrogen, and density-dependent loss terms across the functional types. We find evidence of very high linear loss rates, suggesting that grazing may be even more important than commonly assumed and differences in density-dependent loss rates across functional types, indicating the presence of strong niche differentiation among functional types. Low half-saturation constants for nitrogen at the functional type level may indicate widespread mixotrophy. At the species level, we find a wide range of density-dependent effects, which may be a signal of diversity in grazing susceptibility or biotic interactions. This approach may be a way to obtain more realistic and better-constrained trait values for functional types to be used in ecosystem modeling

A Trait-Based Clustering for Phytoplankton Biomass Modeling and Prediction

When designing models for predicting phytoplankton biomass or characterizing traits, it is useful to aggregate the myriad of species into a few biologically meaningful groups and focus on group-level attributes, the common practice being to combine phytoplankton species by functional types. However, biogeochemists and plankton ecologists debate the most applicable grouping for describing phytoplankton biomass patterns and predicting future community structure. Although trait-based approaches are increasingly being advocated, methods are missing for the generation of trait-basedtaxaasalternativestofunctionaltypes. Hereweintroducesuchamethodanddemonstrate the usefulness of the resulting clustering with field data. We parameterize a Bayesian model of biomass dynamics and analyze long-term phytoplankton data collected at Station L4 in the Western English Channel between April 2003 and December 2009. We examine the tradeoffs encountered regarding trait characterization and biomass prediction when aggregating biomass by (1) functional types, (2) the trait-based clusters generated by our method, and (3) total biomass. The model conveniently extracted trait values under the trait-based clustering, but required well-constrained priors under the functional type categorization. It also more accurately predicted total biomass under the trait-based clustering and the total biomass aggregation with comparable root mean squared prediction errors, which were roughly five-fold lower than under the functional type grouping. Although the total biomass grouping ignores taxonomic differences in phytoplankton traits,it predicts total biomass change as well as the trait-based clustering. Our results corroborate the value of trait-based approaches in investigating the mechanisms under lying phytoplankton biomass dynamics and predicting the community response to environmental changes

Collaborative Deep Learning Models to Handle Class Imbalance in FlowCam Plankton Imagery

Usingautomatedimagingtechnologies,itisnowpossibletogeneratepreviouslyunprecedented volumes of plankton image data which can be used to study the composition of plankton assemblages. However, the current need to manually classify individual images introduces a bottleneck into processing chains.AlthoughMachineLearningtechniqueshavebeenusedtotryandaddressthisissue,pasteffortshave suffered from accuracy limitations, especially in minority classes. Here we use state-of-the-art methods in Deep Learning to investigate suitable architectures for training an automated plankton classification system which achieves high efficacy for both abundant and rare taxa. We collected live plankton from Station L4 in the Western English Channel and imaged 11,371 particles covering 104 taxonomic groups using the automatedplanktonimagingsystemFlowCam.Theimagesetcontainedasevereclassimbalance,withsome taxa represented by > 600 images while other, rarer taxa were represented by just 14. We demonstrate that by allowing multiple Deep Learning models to collaborate in a single classification system, classification accuracyimprovesforminorityclasseswhencomparedwiththebestindividualmodel.Thetopcollaborative model achieved a 6 % improvement in F1 accuracy over the best individual model, while overall accuracy improved by 3.2 %. This resulted in a 97.4 % overall accuracy score and a 96.2 % F1 macro score on a separate holdout test set containing 104 taxonomic groups. Based on a survey of similar studies in the literature, we believe collaborative deep learning models can significantly improve the accuracy of existing automated plankton classification systems

Integration of temporal environmental variation by the marine plankton community

Theory and observations suggest that low frequency variation in marine plankton populations, or red noise, may arise through cumulative integration of white noise atmospheric forcing by the ocean and its amplification within food webs. Here, we revisit evidence for the integration of stochastic atmospheric variations by comparing the power spectra of time series of atmospheric and oceanographic conditions to the population dynamics of 150 plankton taxa at Station L4 in the Western English Channel. The power spectra of oceanographic conditions (sea surface temperature, surface nitrate) are redder than those of atmospheric forcing (surface wind stress, net heat fluxes) at Station L4. However, plankton populations have power spectral slopes across trophic levels and body sizes that are redder than atmospheric forcing but whiter than oceanographic conditions. While zooplankton have redder spectral slopes than phytoplankton, there is no significant relationship between power spectral slope and body size or generation length. Using a predator−prey model, we show that the whitening of plankton time series relative to oceanographic conditions arises from noisy plankton bloom dynamics in this strongly seasonal system. The model indicates that, for typical predator−prey interactions, where the predator is on average 10 times longer than the prey, grazing leads to a modest reddening of phytoplankton variability by their larger and longer lived zooplankton consumers. Our findings suggest that, beyond extrinsic forcing by the environment, predator–prey interactions play a role in influencing the power spectra of time series of plankton populations

Seasonal phosphorus and carbon dynamics in a temperate shelf sea (Celtic Sea): uptake, partitioning, release, turnover and stoichiometry.

The seasonal cycle of resource availability in shelf seas has a strong selective pressure on phytoplankton diversity and the biogeochemical cycling of key elements, such as carbon (C) and phosphorus (P). Shifts in carbon consumption relative to P availability, via changes in cellular stoichiometry for example, can lead to an apparent ‘excess’ of carbon production. We made measurements of inorganic P (Pi) uptake, in parallel to C-fixation, by plankton communities in the Celtic Sea (NW European Shelf) in spring (April 2015), summer (July 2015) and autumn (November 2014). Short-term (< 8 h) Pi-uptake coupled with dissolved organic phosphorus (DOP) release, in parallel to net (24 h) primary production (NPP), were all measured across an irradiance gradient designed to typify vertically and seasonally varying light conditions. Rates of Pi-uptake were highest during spring and lowest in the low light conditions of autumn, although biomass-normalised Pi-uptake was highest in the summer. The release of DOP was highest in November and declined to low levels in July, indicative of efficient utilization and recycling of the low levels of Pi available. Examination of daily turnover times of the different particulate pools, including estimates of phytoplankton and bacterial carbon, indicated a differing seasonal influence of autotrophs and heterotrophs in P-dynamics, with summer conditions associated with a strong bacterial influence and the early spring period with fast growing phytoplankton. These seasonal changes in autotrophic and heterotrophic influence, coupled with changes in resource availability (Pi, light) resulted in seasonal changes in the stoichiometry of NPP to daily Pi-uptake (C:P ratio); from relatively C-rich uptake in November and late April, to P-rich uptake in early April and July. Overall, these results highlight the seasonally varying influence of both autotrophic and heterotrophic components of shelf sea ecosystems on the relative uptake of C and P

Phosphorus dynamics in the Barents Sea

The Barents Sea is considered a warming hotspot in the Arctic; elevated sea surface temperatures have been accompanied with increased inflow of Atlantic water onto the shelf sea. Such hydrodynamic changes and a concomitant reduction of sea ice coverage enables a prolonged phytoplankton growing season, which will inevitably affect nutrient stoichiometry and the controls on primary production. During the summer of 2018, we investigated the role of phosphorus in mediating primary production in the Barents Sea. Dissolved inorganic phosphorus (DIP), its most bioavailable form, had an average net turnover time of 9.4�4.8 d. The most southern Atlantic influenced station accounted for both the highest rates of primary production (655 mg C m2 d−1) and shortest net DIP turnover (2.8�0.5 d). The fraction of assimilated DIP released as dissolved organic phosphorus (DOP) at this station was < 4% compared to an average of 21% at all other stations. We observed significant differences between phytoplankton communities in Arctic and Atlantic waters within the Barents Sea. Slower DIP turnover and greater release of DOP was associated with Phaeocystis pouchetii dominated communities in Arctic waters. Faster turnover rates and greater phosphorus retention occurred among the Atlantic phytoplankton communities dominated by Emiliania huxleyi. Thesefindings provide baseline measurements of P utilization in the Barents Sea, and suggest increased Atlantic intrusion of this region could be accompanied by more rapid DIP turnover, possibly leading to future P limitation (rather than N limitation) on primary productio

Further records of a new diatom species in the English Channel and North Sea: the importance of image-referenced data

Background In September 2015, an at the time undescribed, autotrophic taxon was discovered in the western English Channel (station L4) and also in the eastern English Channel and Celtic Sea during the Polarstern Cruise PS95 a month later. Subsequent investigations revealed further extensive records (going back to 1992) at stations in the English Channel and the southern North Sea (e.g. Helgoland Roads and Sylt Roads time series stations). Stations in the Northern North Sea have not recorded this distinct taxon. With the available records and crucially, the accompanying image metadata, we are able to chart a clear distribution record with occurrences being restricted to the southern North Sea and English Channel. Methods The biological data shown are from Lugol-fixed Utermöhl counts and investigations of live and Formalin-fixed net hauls (20 μm mesh size). All image material shown is available in the online repository Planktonnet (http://planktonnet.awi.de). Results We report the distribution, based on geo-referenced image records of an easily recognisable, yet taxonomically uncertain, autotrophic organism. Conclusions Distribution patterns of the unidentified autotrophic taxon suggests entry of this taxon into/out of the North Sea via the English Channel. Further investigations providing image-documented information over several years is clearly necessary to clarify its dynamics and ecological characteristics

Competition Drives Clumpy Species Coexistence in Estuarine Phytoplankton

Understanding the mechanisms that maintain biodiversity is a fundamental problem in ecology. Competition is thought to reduce diversity, but hundreds of microbial aquatic primary producers species coexist and compete for a few essential resources (e.g., nutrients and light). Here, we show that resource competition is a plausible mechanism for explaining clumpy distribution on individual species volume (a proxy for the niche) of estuarine phytoplankton communities ranging from North America to South America and Europe, supporting the Emergent Neutrality hypothesis. Furthermore, such a clumpy distribution was also observed throughout the Holocene in diatoms from a sediment core. A Lotka-Volterra competition model predicted position in the niche axis and functional affiliation of dominant species within and among clumps. Results support the coexistence of functionally equivalent species in ecosystems and indicate that resource competition may be a key process to shape the size structure of estuarine phytoplankton, which in turn drives ecosystem functioning

The significance of nitrogen regeneration for new production within a filament of the Mauritanian upwelling system

The Lagrangian progression of a biological community was followed in a filament of the Mauritanian upwelling system, north-west Africa, during offshore advection. The inert dual tracers sulfur hexafluoride and helium-3 labelled a freshly upwelled patch of water that was mapped for 8 days. Changes in biological, physical, and chemical characteristics were measured, including phytoplankton productivity, nitrogen assimilation, and regeneration. Freshly upwelled water contained high nutrient concentrations but was depleted in N compared to Redfield stoichiometry. The highest rate of primary productivity was measured on the continental shelf, associated with high rates of nitrogen assimilation and a phytoplankton community dominated by diatoms and flagellates. Indicators of phytoplankton abundance and activity decreased as the labelled water mass transited the continental shelf slope into deeper water, possibly linked to the mixed layer depth exceeding the light penetration depth. By the end of the study, the primary productivity rate decreased and was associated with lower rates of nitrogen assimilation and lower nutrient concentrations. Nitrogen regeneration and assimilation took place simultaneously. Results highlighted the importance of regenerated NHC 4 in sustaining phytoplankton productivity and indicate that the upwelled NO3 pool contained an increasing fraction of regenerated NO3 as it advected offshore. By calculating this fraction and incorporating it into an f ratio formulation, we estimated that of the 12:38Tg C of annual regional production, 4:73Tg C was exportable

Ecological equivalence of species within phytoplankton functional groups

1.There are tens of thousands of species of phytoplankton found throughout the tree of life. Despite this diversity, phytoplankton are often aggregated into a few functional groups according to metabolic traits or biogeochemical role. We investigate the extent to which phytoplankton species dynamics are neutral within functional groups. 2.Seasonal dynamics in many regions of the ocean are known to affect phytoplankton at the functional group level leading to largely predictable patterns of seasonal succession. It is much more difficult to make general statements about the dynamics of individual species. 3.We use a 7 year time-series at station L4 in the Western English Channel with 57 diatom and 17 dinoflagellate species enumerated weekly to test if the abundance of diatom and dinoflagellate species vary randomly within their functional group envelope or if each species is driven uniquely by external factors. 4.We show that the total biomass of the diatom and dinoflagellate functional groups is well predicted by irradiance and temperature and quantify trait values governing the growth rate of both functional groups. The biomass dynamics of the functional groups are not neutral and each has their own distinct responses to environmental forcing. Compared to dinoflagellates, diatoms have faster growth rates, and grow faster under lower irradiance, cooler temperatures, and higher nutrient conditions. 5.The biomass of most species vary randomly within their functional group biomass envelope, most of the time. As a consequence, modelers will find it difficult to predict the biomass of most individual species. Our analysis supports the approach of using a single set of traits for a functional group and suggests that it should be possible to determine these traits from natural communities