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

Phytoplankton realized Niches Track changing oceanic conditions at a long-term coastal station offSydney Australia

© 2018 Ajani, McGinty, Finkel and Irwin. Phytoplankton dynamics are closely linked to the ocean-climate system with evidence that changing ocean conditions are substantially altering phytoplankton biogeography, abundance and phenology. Using phytoplankton community composition and environmental data spanning 1965 to 2013 from a long-term Pacific Ocean coastal station offshore from Sydney, Australia (Port Hacking 100 m), we used the Maximum Entropy Modelling framework (MaxEnt) to test whether phytoplankton realized niches are fixed or shift in response to changing environmental conditions. The mean niches of phytoplankton closely tracked changes in mean temperature, while the mean salinity and mixed layer depth realized niches were consistently at the extreme range of available conditions. Prior studies had shown a fixed niche for nitrate in some phytoplankton species at a site where nitrate concentration was decreasing and potentially limiting; however, at Port Hacking nitrate and silicate niches increased more rapidly than environmental conditions, apparently in response to periodic occurrences of elevated nutrient concentrations. This study provides further evidence that climate change model projections cannot assume fixed realized niches of biotic communities, whilst highlighting the importance of sustained ocean measurements from the southern hemisphere to enhance our understanding of global ocean trends

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

On the roles of cell size and trophic strategy in North Atlantic diatom and dinoflagellate communities

We have examined the inter- and intra-group seasonal succession of 113 diatom and dinoflagellate taxa, as surveyed by the Continuous Plankton Recorder (CPR) in the North Atlantic, by grouping taxa according to two key functional traits: cell size (mg C cell21) and trophic strategy (photoautotrophy, mixotrophy, or heterotrophy). Mixotrophic dinoflagellates follow photoautotrophic diatoms but precede their obligate heterotrophic counterparts in the succession because of the relative advantages afforded by photosynthesizing when light and nutrients are available in spring. The mean cell size of the sampled diatoms is smallest in the summer, likely because of the higher specific nutrient affinity of smaller relative to larger cells. Contrastingly, we hypothesize that mixotrophy diminishes the size selection based on nutrient limitation and accounts for the lack of a seasonal size shift among surveyed dinoflagellates. Relatively small, heterotrophic dinoflagellates (mg C cell21 , 1023) peak after other, larger dinoflagellates, in part because of the increased abundance of their small prey during nutrientdeplete summer months. The largest surveyed diatoms (mg C cell21 . 1022) bloom later than others, and we hypothesize that this may be because of their relatively slow maximum potential growth rates and high internal nutrient storage, as well as to the slower predation of these larger cells. The new trait database and analysis presented here helps translate the taxonomic information of the CPR survey into metrics that can be directly compared with trait-based models

Large centric diatoms allocate more cellular nitrogen to photosynthesis to counter slower RUBISCO turnover rates

© 2014 Wu, Jeans, Suggett, Finkel and Campbell. Diatoms contribute ~40% of primary production in the modern ocean and encompass the largest cell size range of any phytoplankton group. Diatom cell size influences their nutrient uptake, photosynthetic light capture, carbon export efficiency, and growth responses to increasing pCO2. We therefore examined nitrogen resource allocations to the key protein complexes mediating photosynthesis across six marine centric diatoms, spanning 5 orders of magnitude in cell volume, under past, current and predicted future pCO2 levels, in balanced growth under nitrogen repletion. Membrane bound photosynthetic protein concentrations declined with cell volume in parallel with cellular concentrations of total protein, total nitrogen and chlorophyll. Larger diatom species, however, allocated a greater fraction (by 3.5-fold) of their total cellular nitrogen to the soluble Ribulose-1,5-bisphosphate Carboxylase Oxygenase (RUBISCO) carbon fixation complex than did smaller species. Carbon assimilation per unit of RUBISCO large subunit (C RbcL-1 s-1) decreased with cell volume, from ~8 to ~2 C RbcL-1 s-1 from the smallest to the largest cells. Whilst a higher allocation of cellular nitrogen to RUBISCO in larger cells increases the burden upon their nitrogen metabolism, the higher RUBISCO allocation buffers their lower achieved RUBISCO turnover rate to enable larger diatoms to maintain carbon assimilation rates per total protein comparable to small diatoms. Individual species responded to increased pCO2, but cell size effects outweigh pCO2 responses across the diatom species size range examined. In large diatoms a higher nitrogen cost for RUBISCO exacerbates the higher nitrogen requirements associated with light absorption, so the metabolic cost to maintain photosynthesis is a cell size-dependent trait

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

Bayesian two-part modeling of phytoplankton biomass and occurrence

Phytoplankton biomass data often involve zero outcomes preventing a description by continuous distributions with positive support such as the lognormal distribution commonly used to describe ecological data. Two usual solutions: ignoring the zeroes and adding a small positive number to all outcomes, induce bias and reduce predictive power. To address these shortcomings, we design a Bayesian two-part model with a binary component for presence or absence and a continuous component involving a lognormal model for non-zero biomass. We specify two equations relating species-specific occurrence probabilities and expected log-biomasses when present to potential covariates, with spike-and-slab priors imposed on linear effects to selectively discard the irrelevant predictors. We analyze the biomass data of 74 phytoplankton (57 diatoms and 17 dinoflagellates) recorded weekly at Station L4 (Western English Channel, UK) between April 2003 and December 2009, along with measurements of abiotic covariates. Our results disclose different combinations of environmental predictors for the occurrence and the biomass of individual species. Overall, the occurrence of dinoflagellates is associated with higher temperature and irradiance levels compared to diatoms, with virtually no dependence on nutrient concentrations. Irradiance emerges as the key predictor of biomass when species are present. Optimum temperatures for biomass accumulation and temperature sensitivities vary widely among and within functional types. Compared to one-stage models based on usual zero handling approaches, our two-part model stands out with higher prediction accuracy. The two-part modeling approach provides a valuable framework for decoupling the predictors of species occurrence and abundance from observational data

Anthropogenic climate change impacts on copepod trait biogeography

Copepods are among the most abundant marine metazoans and form a key link between marine primary producers, higher trophic levels, and carbon sequestration pathways. Climate change is projected to change surface ocean temperature by up to 4°C in the North Atlantic with many associated changes including slowing of the overturning circulation, areas of regional freshening, and increased salinity and reductions in nutrients available in the euphotic zone over the next century. These changes will lead to a restructuring of phytoplankton and zooplankton communities with cascading effects throughout the food web. Here we employ observations of copepods, projected changes in ocean climate, and species distribution models to show how climate change may affect the distribution of copepod species in the North Atlantic. On average species move northeast at a rate of 14.1 km decade. Species turnover in copepod communities will range from 5% to 75% with the highest turnover rates concentrated in regions of pronounced temperature increase and decrease. The changes in species range vary according to copepod traits with the largest effects found to occur in the cooling, freshening area in the subpolar North Atlantic south of Greenland and in an area of significant warming along the Scotian shelf. Large diapausing copepods (>2.5 mm) which are higher in lipids and a crucial food source for whales, may have an advantage in the cooling waters due to their life-history strategy that facilitates their survival in the arctic environment. Carnivorous copepods show a basin wide increase in species richness and show significant habitat area increases when their distribution moves poleward while herbivores see significant habitat area losses. The trait-specific effects highlight the complex consequences of climate change for the marine food web

Case Study: LifeWatch Italy Phytoplankton VRE

LifeWatch Italy, the Italian node of LifeWatch ERIC, has promoted and stimulated the debate on the use of semantics in biodiversity data management. Actually, biodiversity and ecosystems data are very heterogeneous and need to be better managed to improve the actual scientific knowledge extracted, as well as to address the urgent societal challenges concerning environmental issues. LifeWatch Italy has realized the Phytoplankton Virtual Research Environment (hereafter Phytoplankton VRE), a collaborative working environment supporting researchers to address basic and applied studies on phytoplankton ecology. The Phytoplankton VRE provides the IT infrastructure to enable researchers to obtain, share and analyse phytoplankton data at a level of resolution from individual cells to whole assemblages. A semantic approach has been used to address data harmonisation, integration and discovery: an interdisciplinary team has developed a thesaurus on phytoplankton functional traits and linked its concepts to other existing conceptual schemas related to the specific domain

Iron Deficiency Increases Growth and Nitrogen-Fixation Rates of Phosphorus-Deficient Marine Cyanobacteria

Marine dinitrogen (N2)-fixing cyanobacteria have large impacts on global biogeochemistry as they fix carbon dioxide (CO2) and fertilize oligotrophic ocean waters with new nitrogen. Iron (Fe) and phosphorus (P) are the two most important limiting nutrients for marine biological N2 fixation, and their availabilities vary between major ocean basins and regions. A long-standing question concerns the ability of two globally dominant N2-fixing cyanobacteria, unicellular Crocosphaera and filamentous Trichodesmium, to maintain relatively high N2-fixation rates in these regimes where both Fe and P are typically scarce. We show that under P-deficient conditions, cultures of these two cyanobacteria are able to grow and fix N2 faster when Fe deficient than when Fe replete. In addition, growth affinities relative to P increase while minimum concentrations of P that support growth decrease at low Fe concentrations. In Crocosphaera, this effect is accompanied by a reduction in cell sizes and elemental quotas. Relatively high growth rates of these two biogeochemically critical cyanobacteria in low-P, low-Fe environments such as those that characterize much of the oligotrophic ocean challenge the common assumption that low Fe levels can have only negative effects on marine primary producers. The closely interdependent influence of Fe and P on N2-fixing cyanobacteria suggests that even subtle shifts in their supply ratio in the past, present and future oceans could have large consequences for global carbon and nitrogen cycles