Functional and compositional responses of stream microphytobenthic communities to multiple stressors increase and release in a mesocosm experiment.

Field observations form the basis of the majority of studies on microphytobenthic algal communities in freshwater ecosystems. Controlled mesocosm experiments data are comparatively uncommon. The few experimental mesocosm studies that have been conducted provide valuable insights into how multiple stressors affect the community structures and photosynthesis-related traits of benthic microalgae. The recovery process after the stressors have subsided, however, has received less attention in mesocosm studies. To close this gap, here we present the results of a riparian mesocosm experiment designed to investigate the effects of reduced flow velocity, increased salinity and increased temperature on microphytobenthic communities. We used a full factorial design with a semi-randomised distribution of treatments consisting of two levels of each stressor (2 × 2 × 2 treatments), with eight replicates making a total of 64 circular mesocosms, allowing a nuanced examination of their individual and combined influences. We aimed to elucidate the responses of microalgae communities seeded from stream water to the applied environmental stressors. Our results showed significant effects of reduced flow velocity and increased temperature on microphytobenthic communities. Recovery after stressor treatment led to a convergence in community composition, with priority effects (hypothesized to reflect competition for substrate between resident and newly arriving immigrant taxa) slowing down community shifts and biomass increase. Our study contributes to the growing body of literature on the ecological dynamics of microphytobenthos and emphasises the importance of rigorous experiments to validate hypotheses. These results encourage further investigation into the nuanced interactions between microphytobenthos and their environment and shed light on the complexity of ecological responses in benthic systems.

Differential associations of five riverine organism groups with multiple stressors.

The decline of river and stream biodiversity results from multiple simultaneous occuring stressors, yet few studies explore responses explore responses across various taxonomic groups at the same locations. In this study, we address this shortcoming by using a coherent data set to study the association of nine commonly occurring stressors (five chemical, one morphological and three hydraulic) with five taxonomic groups (bacteria, fungi, diatoms, macro-invertebrates and fish). According to studies on single taxonomic groups, we hypothesise that gradients of chemical stressors structure community composition of all taxonomic groups, while gradients of hydraulic and morphological stressors are mainly related to larger organisms such as benthic macro-invertebrates and fish. Organisms were sampled over two years at 20 sites in two catchments: a recently restored urban lowland catchment (Boye) and a moderately disturbed rural mountainous catchment (Kinzig). Dissimilarity matrices were computed for each taxonomic group within a catchment. Taxonomic dissimilarities between sites were linked to stressor dissimilarities using multivariable Generalized Linear Mixed Models. Stressor gradients were longer in the Boye, but did in contrast to the Kinzig not cover low stress intensities. Accordingly, responses of the taxonomic groups were stronger in the Kinzig catchment than in the recently restored Boye catchment. The discrepancy between catchments underlines that associations to stressors strongly depend on which part of the stressor gradient is covered in a catchment. All taxonomic groups were related to conductivity. Bacteria, fungi and macro-invertebrates change with dissolved oxygen, and bacteria and fungi with total nitrogen. Morphological and hydraulic stressors had minor correlations with bacteria, fungi and diatoms, while macro-invertebrates were strongly related to fine sediment and discharge, and fish to high flow peaks. The results partly support our hypotheses about the differential associations of the different taxonomic groups with the stressors.

Improving deep learning-based segmentation of diatoms in gigapixel-sized virtual slides by object-based tile positioning and object integrity constraint.

Diatoms represent one of the morphologically and taxonomically most diverse groups of microscopic eukaryotes. Light microscopy-based taxonomic identification and enumeration of frustules, the silica shells of these microalgae, is broadly used in aquatic ecology and biomonitoring. One key step in emerging digital variants of such investigations is segmentation, a task that has been addressed before, but usually in manually captured megapixel-sized images of individual diatom cells with a mostly clean background. In this paper, we applied deep learning-based segmentation methods to gigapixel-sized, high-resolution scans of diatom slides with a realistically cluttered background. This setup requires large slide scans to be subdivided into small images (tiles) to apply a segmentation model to them. This subdivision (tiling), when done using a sliding window approach, often leads to cropping relevant objects at the boundaries of individual tiles. We hypothesized that in the case of diatom analysis, reducing the amount of such cropped objects in the training data can improve segmentation performance by allowing for a better discrimination of relevant, intact frustules or valves from small diatom fragments, which are considered irrelevant when counting diatoms. We tested this hypothesis by comparing a standard sliding window / fixed-stride tiling approach with two new approaches we term object-based tile positioning with and without object integrity constraint. With all three tiling approaches, we trained Mask-R-CNN and U-Net models with different amounts of training data and compared their performance. Object-based tiling with object integrity constraint led to an improvement in pixel-based precision by 12-17 percentage points without substantially impairing recall when compared with standard sliding window tiling. We thus propose that training segmentation models with object-based tiling schemes can improve diatom segmentation from large gigapixel-sized images but could potentially also be relevant for other image domains.

The Asymmetric Response Concept explains ecological consequences of multiple stressor exposure and release.

Our capacity to predict trajectories of ecosystem degradation and recovery is limited, especially when impairments are caused by multiple stressors. Recovery may be fast or slow and either complete or partial, sometimes result in novel ecosystem states or even fail completely. Here, we introduce the Asymmetric Response Concept (ARC) that provides a basis for exploring and predicting the pace and magnitude of ecological responses to, and release from, multiple stressors. The ARC holds that three key mechanisms govern population, community and ecosystem trajectories. Stress tolerance is the main mechanism determining responses to increasing stressor intensity, whereas dispersal and biotic interactions predominantly govern responses to the release from stressors. The shifting importance of these mechanisms creates asymmetries between the ecological trajectories that follow increasing and decreasing stressor intensities. This recognition helps to understand multiple stressor impacts and to predict which measures will restore communities that are resistant to restoration.

Label-Free Raman Microspectroscopy for Identifying Prokaryotic Virocells.

Raman microspectroscopy has been used to thoroughly assess growth dynamics and heterogeneity of prokaryotic cells, yet little is known about how the chemistry of individual cells changes during infection with virulent viruses, resulting in so-called virocells. Here, we investigate biochemical changes of bacterial and archaeal cells of three different species in laboratory cultures before and after addition of their respective viruses using single-cell Raman microspectroscopy. By applying multivariate statistics, we identified significant differences in the spectra of single cells with/without addition of virulent dsRNA phage (phi6) for Pseudomonas syringae. A general ratio of wavenumbers that contributed the greatest differences in the recorded spectra was defined as an indicator for virocells. Based on reference spectra, this difference is likely attributable to an increase in nucleic acid versus protein ratio of virocells. This method also proved successful for identification of Bacillus subtilis cells infected with the double-stranded DNA (dsDNA) phage phi29, displaying a decrease in respective ratio, but failed for archaeal virocells (Methanosarcina mazei with the dsDNA methanosarcina spherical virus) due to autofluorescence. Multivariate and univariate analyses suggest that Raman spectral data of infected cells can also be used to explore the complex biology behind viral infections of bacteria. Using this method, we confirmed the previously described two-stage infection of P. syringae's phi6 and that infection of B. subtilis with phi29 results in a stress response within single cells. We conclude that Raman microspectroscopy is a promising tool for chemical identification of Gram-positive and Gram-negative virocells undergoing infection with virulent DNA or RNA viruses. IMPORTANCE Viruses are highly diverse biological entities shaping many ecosystems across Earth. However, understanding the infection of individual microbial cells and the related biochemical changes remains limited. Using Raman microspectroscopy in conjunction with univariate and multivariate statistics, we established a marker for identification of infected Gram-positive and Gram-negative bacteria. This nondestructive, label-free analytical method at single-cell resolution paves the way for future studies geared towards analyzing virus-host systems of prokaryotes to further understand the complex chemistry and function of virocells.

The biogeographic differentiation of algal microbiomes in the upper ocean from pole to pole.

Eukaryotic phytoplankton are responsible for at least 20% of annual global carbon fixation. Their diversity and activity are shaped by interactions with prokaryotes as part of complex microbiomes. Although differences in their local species diversity have been estimated, we still have a limited understanding of environmental conditions responsible for compositional differences between local species communities on a large scale from pole to pole. Here, we show, based on pole-to-pole phytoplankton metatranscriptomes and microbial rDNA sequencing, that environmental differences between polar and non-polar upper oceans most strongly impact the large-scale spatial pattern of biodiversity and gene activity in algal microbiomes. The geographic differentiation of co-occurring microbes in algal microbiomes can be well explained by the latitudinal temperature gradient and associated break points in their beta diversity, with an average breakpoint at 14 °C ± 4.3, separating cold and warm upper oceans. As global warming impacts upper ocean temperatures, we project that break points of beta diversity move markedly pole-wards. Hence, abrupt regime shifts in algal microbiomes could be caused by anthropogenic climate change.

Epiphytic diatom community structure and richness is determined by macroalgal host and location in the South Shetland Islands (Antarctica).

The marine waters around the South Shetland Islands are paramount in the primary production of this Antarctic ecosystem. With the increasing effects of climate change and the annual retreat of the ice shelf, the importance of macroalgae and their diatom epiphytes in primary production also increases. The relationships and interactions between these organisms have scarcely been studied in Antarctica, and even less in the volcanic ecosystem of Deception Island, which can be seen as a natural proxy of climate change in Antarctica because of its vulcanism, and the open marine system of Livingston Island. In this study we investigated the composition of the diatom communities in the context of their macroalgal hosts and different environmental factors. We used a non-acidic method for diatom digestion, followed by slidescanning and diatom identification by manual annotation through a web-browser-based image annotation platform. Epiphytic diatom species richness was higher on Deception Island as a whole, whereas individual macroalgal specimens harboured richer diatom assemblages on Livingston Island. We hypothesize this a possible result of a higher diversity of ecological niches in the unique volcanic environment of Deception Island. Overall, our study revealed higher species richness and diversity than previous studies of macroalgae-inhabiting diatoms in Antarctica, which could however be the result of the different preparation methodologies used in the different studies, rather than an indication of a higher species richness on Deception Island and Livingston Island than other Antarctic localities.

First Evidence of the Toxin Domoic Acid in Antarctic Diatom Species.

The Southern Ocean is one of the most productive ecosystems in the world. It is an area heavily dependent on marine primary production and serving as a feeding ground for numerous seabirds and marine mammals. Therefore, the phytoplankton composition and presence of toxic species are of crucial importance. Fifteen monoclonal strains of Pseudo-nitzschia subcurvata, a diatom species endemic to the Southern Ocean, were established, which were characterized by morphological and molecular data and then analysed for toxin content. The neurotoxins domoic acid and iso-domoic acid C were present in three of the strains, which is a finding that represents the first evidence of these toxins in strains from Antarctic waters. Toxic phytoplankton in Antarctic waters are still largely unexplored, and their effects on the ecosystem are not well understood. Considering P. subcurvata's prevalence throughout the Southern Ocean, these results highlight the need for further investigations of the harmful properties on the Antarctic phytoplankton community as well as the presence of the toxins in the Antarctic food web, especially in the light of a changing climate.

Deep learning-based diatom taxonomy on virtual slides.

Deep convolutional neural networks are emerging as the state of the art method for supervised classification of images also in the context of taxonomic identification. Different morphologies and imaging technologies applied across organismal groups lead to highly specific image domains, which need customization of deep learning solutions. Here we provide an example using deep convolutional neural networks (CNNs) for taxonomic identification of the morphologically diverse microalgal group of diatoms. Using a combination of high-resolution slide scanning microscopy, web-based collaborative image annotation and diatom-tailored image analysis, we assembled a diatom image database from two Southern Ocean expeditions. We use these data to investigate the effect of CNN architecture, background masking, data set size and possible concept drift upon image classification performance. Surprisingly, VGG16, a relatively old network architecture, showed the best performance and generalizing ability on our images. Different from a previous study, we found that background masking slightly improved performance. In general, training only a classifier on top of convolutional layers pre-trained on extensive, but not domain-specific image data showed surprisingly high performance (F1 scores around 97%) with already relatively few (100-300) examples per class, indicating that domain adaptation to a novel taxonomic group can be feasible with a limited investment of effort.

Adaptive divergence across Southern Ocean gradients in the pelagic diatom Fragilariopsis kerguelensis.

The Southern Ocean is characterized by longitudinal water circulations crossed by strong latitudinal gradients. How this oceanographic background shapes planktonic populations is largely unknown, despite the significance of this region for global biogeochemical cycles. Here, we show, based on genomic, morphometric, ecophysiological and mating compatibility data, an example of ecotypic differentiation and speciation within an endemic pelagic inhabitant, the diatom Fragilariopsis kerguelensis. We discovered three genotypic variants, one present throughout the latitudinal transect sampled, the others restricted to the north and south, respectively. The latter two showed reciprocal monophyly across all three genomes and significant ecophysiological differences consistent with local adaptation, but produced viable offspring in laboratory crosses. The third group was also reproductively isolated from the latter two. We hypothesize that this pattern originated by an adaptive expansion accompanied by ecotypic divergence, followed by sympatric speciation.

Repositories for Taxonomic Data: Where We Are and What is Missing.

Natural history collections are leading successful large-scale projects of specimen digitization (images, metadata, DNA barcodes), thereby transforming taxonomy into a big data science. Yet, little effort has been directed towards safeguarding and subsequently mobilizing the considerable amount of original data generated during the process of naming 15,000-20,000 species every year. From the perspective of alpha-taxonomists, we provide a review of the properties and diversity of taxonomic data, assess their volume and use, and establish criteria for optimizing data repositories. We surveyed 4113 alpha-taxonomic studies in representative journals for 2002, 2010, and 2018, and found an increasing yet comparatively limited use of molecular data in species diagnosis and description. In 2018, of the 2661 papers published in specialized taxonomic journals, molecular data were widely used in mycology (94%), regularly in vertebrates (53%), but rarely in botany (15%) and entomology (10%). Images play an important role in taxonomic research on all taxa, with photographs used in >80% and drawings in 58% of the surveyed papers. The use of omics (high-throughput) approaches or 3D documentation is still rare. Improved archiving strategies for metabarcoding consensus reads, genome and transcriptome assemblies, and chemical and metabolomic data could help to mobilize the wealth of high-throughput data for alpha-taxonomy. Because long-term-ideally perpetual-data storage is of particular importance for taxonomy, energy footprint reduction via less storage-demanding formats is a priority if their information content suffices for the purpose of taxonomic studies. Whereas taxonomic assignments are quasifacts for most biological disciplines, they remain hypotheses pertaining to evolutionary relatedness of individuals for alpha-taxonomy. For this reason, an improved reuse of taxonomic data, including machine-learning-based species identification and delimitation pipelines, requires a cyberspecimen approach-linking data via unique specimen identifiers, and thereby making them findable, accessible, interoperable, and reusable for taxonomic research. This poses both qualitative challenges to adapt the existing infrastructure of data centers to a specimen-centered concept and quantitative challenges to host and connect an estimated $ \le $2 million images produced per year by alpha-taxonomic studies, plus many millions of images from digitization campaigns. Of the 30,000-40,000 taxonomists globally, many are thought to be nonprofessionals, and capturing the data for online storage and reuse therefore requires low-complexity submission workflows and cost-free repository use. Expert taxonomists are the main stakeholders able to identify and formalize the needs of the discipline; their expertise is needed to implement the envisioned virtual collections of cyberspecimens. [Big data; cyberspecimen; new species; omics; repositories; specimen identifier; taxonomy; taxonomic data.].

Quantitative comparison of taxa and taxon concepts in the diatom genus Fragilariopsis: a case study on using slide scanning, multiexpert image annotation, and image analysis in taxonomy1.

Semiautomated methods for microscopic image acquisition, image analysis, and taxonomic identification have repeatedly received attention in diatom analysis. Less well studied is the question whether and how such methods might prove useful for clarifying the delimitation of species that are difficult to separate for human taxonomists. To try to answer this question, three very similar Fragilariopsis species endemic to the Southern Ocean were targeted in this study: F. obliquecostata, F. ritscheri, and F. sublinearis. A set of 501 extended focus depth specimen images were obtained using a standardized, semiautomated microscopic procedure. Twelve diatomists independently identified these specimen images in order to reconcile taxonomic opinions and agree upon a taxonomic gold standard. Using image analyses, we then extracted morphometric features representing taxonomic characters of the target taxa. The discriminating ability of individual morphometric features was tested visually and statistically, and multivariate classification experiments were performed to test the agreement of the quantitatively defined taxa assignments with expert consensus opinion. Beyond an updated differential diagnosis of the studied taxa, our study also shows that automated imaging and image analysis procedures for diatoms are coming close to reaching a broad applicability for routine use.

In situ expression of eukaryotic ice-binding proteins in microbial communities of Arctic and Antarctic sea ice.

Ice-binding proteins (IBPs) have been isolated from various sea-ice organisms. Their characterisation points to a crucial role in protecting the organisms in sub-zero environments. However, their in situ abundance and diversity in natural sea-ice microbial communities is largely unknown. In this study, we analysed the expression and phylogenetic diversity of eukaryotic IBP transcripts from microbial communities of Arctic and Antarctic sea ice. IBP transcripts were found in abundances similar to those of proteins involved in core cellular processes such as photosynthesis. Eighty-nine percent of the IBP transcripts grouped with known IBP sequences from diatoms, haptophytes and crustaceans, but the majority represented novel sequences not previously characterized in cultured organisms. The observed high eukaryotic IBP expression in natural eukaryotic sea ice communities underlines the essential role of IBPs for survival of many microorganisms in communities living under the extreme conditions of polar sea ice.

Potential effects of climate change on the distribution range of the main silicate sinker of the Southern Ocean.

Fragilariopsis kerguelensis, a dominant diatom species throughout the Antarctic Circumpolar Current, is coined to be one of the main drivers of the biological silicate pump. Here, we study the distribution of this important species and expected consequences of climate change upon it, using correlative species distribution modeling and publicly available presence-only data. As experience with SDM is scarce for marine phytoplankton, this also serves as a pilot study for this organism group. We used the maximum entropy method to calculate distribution models for the diatom F. kerguelensis based on yearly and monthly environmental data (sea surface temperature, salinity, nitrate and silicate concentrations). Observation data were harvested from GBIF and the Global Diatom Database, and for further analyses also from the Hustedt Diatom Collection (BRM). The models were projected on current yearly and seasonal environmental data to study current distribution and its seasonality. Furthermore, we projected the seasonal model on future environmental data obtained from climate models for the year 2100. Projected on current yearly averaged environmental data, all models showed similar distribution patterns for F. kerguelensis. The monthly model showed seasonality, for example, a shift of the southern distribution boundary toward the north in the winter. Projections on future scenarios resulted in a moderately to negligibly shrinking distribution area and a change in seasonality. We found a substantial bias in the publicly available observation datasets, which could be reduced by additional observation records we obtained from the Hustedt Diatom Collection. Present-day distribution patterns inferred from the models coincided well with background knowledge and previous reports about F. kerguelensis distribution, showing that maximum entropy-based distribution models are suitable to map distribution patterns for oceanic planktonic organisms. Our scenario projections indicate moderate effects of climate change upon the biogeography of F. kerguelensis.

SHERPA: an image segmentation and outline feature extraction tool for diatoms and other objects.

BACKGROUND: Light microscopic analysis of diatom frustules is widely used both in basic and applied research, notably taxonomy, morphometrics, water quality monitoring and paleo-environmental studies. In these applications, usually large numbers of frustules need to be identified and/or measured. Although there is a need for automation in these applications, and image processing and analysis methods supporting these tasks have previously been developed, they did not become widespread in diatom analysis. While methodological reports for a wide variety of methods for image segmentation, diatom identification and feature extraction are available, no single implementation combining a subset of these into a readily applicable workflow accessible to diatomists exists. RESULTS: The newly developed tool SHERPA offers a versatile image processing workflow focused on the identification and measurement of object outlines, handling all steps from image segmentation over object identification to feature extraction, and providing interactive functions for reviewing and revising results. Special attention was given to ease of use, applicability to a broad range of data and problems, and supporting high throughput analyses with minimal manual intervention. CONCLUSIONS: Tested with several diatom datasets from different sources and of various compositions, SHERPA proved its ability to successfully analyze large amounts of diatom micrographs depicting a broad range of species. SHERPA is unique in combining the following features: application of multiple segmentation methods and selection of the one giving the best result for each individual object; identification of shapes of interest based on outline matching against a template library; quality scoring and ranking of resulting outlines supporting quick quality checking; extraction of a wide range of outline shape descriptors widely used in diatom studies and elsewhere; minimizing the need for, but enabling manual quality control and corrections. Although primarily developed for analyzing images of diatom valves originating from automated microscopy, SHERPA can also be useful for other object detection, segmentation and outline-based identification problems.

High-resolution SAR11 ecotype dynamics at the Bermuda Atlantic Time-series Study site by phylogenetic placement of pyrosequences.

Advances in next-generation sequencing technologies are providing longer nucleotide sequence reads that contain more information about phylogenetic relationships. We sought to use this information to understand the evolution and ecology of bacterioplankton at our long-term study site in the Western Sargasso Sea. A bioinformatics pipeline called PhyloAssigner was developed to align pyrosequencing reads to a reference multiple sequence alignment of 16S ribosomal RNA (rRNA) genes and assign them phylogenetic positions in a reference tree using a maximum likelihood algorithm. Here, we used this pipeline to investigate the ecologically important SAR11 clade of Alphaproteobacteria. A combined set of 2.7 million pyrosequencing reads from the 16S rRNA V1-V2 regions, representing 9 years at the Bermuda Atlantic Time-series Study (BATS) site, was quality checked and parsed into a comprehensive bacterial tree, yielding 929 036 Alphaproteobacteria reads. Phylogenetic structure within the SAR11 clade was linked to seasonally recurring spatiotemporal patterns. This analysis resolved four new SAR11 ecotypes in addition to five others that had been described previously at BATS. The data support a conclusion reached previously that the SAR11 clade diversified by subdivision of niche space in the ocean water column, but the new data reveal a more complex pattern in which deep branches of the clade diversified repeatedly across depth strata and seasonal regimes. The new data also revealed the presence of an unrecognized clade of Alphaproteobacteria, here named SMA-1 (Sargasso Mesopelagic Alphaproteobacteria, group 1), in the upper mesopelagic zone. The high-resolution phylogenetic analyses performed herein highlight significant, previously unknown, patterns of evolutionary diversification, within perhaps the most widely distributed heterotrophic marine bacterial clade, and strongly links to ecosystem regimes.

Putative monofunctional type I polyketide synthase units: a dinoflagellate-specific feature?

Marine dinoflagellates (alveolata) are microalgae of which some cause harmful algal blooms and produce a broad variety of most likely polyketide synthesis derived phycotoxins. Recently, novel polyketide synthesase (PKS) transcripts have been described from the Florida red tide dinoflagellate Karenia brevis (gymnodiniales) which are evolutionarily related to Type I PKS but were apparently expressed as monofunctional proteins, a feature typical of Type II PKS. Here, we investigated expression units of PKS I-like sequences in Alexandrium ostenfeldii (gonyaulacales) and Heterocapsa triquetra (peridiniales) at the transcript and protein level. The five full length transcripts we obtained were all characterized by polyadenylation, a 3' UTR and the dinoflagellate specific spliced leader sequence at the 5'end. Each of the five transcripts encoded a single ketoacylsynthase (KS) domain showing high similarity to K. brevis KS sequences. The monofunctional structure was also confirmed using dinoflagellate specific KS antibodies in Western Blots. In a maximum likelihood phylogenetic analysis of KS domains from diverse PKSs, dinoflagellate KSs formed a clade placed well within the protist Type I PKS clade between apicomplexa, haptophytes and chlorophytes. These findings indicate that the atypical PKS I structure, i.e., expression as putative monofunctional units, might be a dinoflagellate specific feature. In addition, the sequenced transcripts harbored a previously unknown, apparently dinoflagellate specific conserved N-terminal domain. We discuss the implications of this novel region with regard to the putative monofunctional organization of Type I PKS in dinoflagellates.

The model marine diatom Thalassiosira pseudonana likely descended from a freshwater ancestor in the genus Cyclotella.

BACKGROUND: Publication of the first diatom genome, that of Thalassiosira pseudonana, established it as a model species for experimental and genomic studies of diatoms. Virtually every ensuing study has treated T. pseudonana as a marine diatom, with genomic and experimental data valued for their insights into the ecology and evolution of diatoms in the world's oceans. RESULTS: The natural distribution of T. pseudonana spans both marine and fresh waters, and phylogenetic analyses of morphological and molecular datasets show that, 1) T. pseudonana marks an early divergence in a major freshwater radiation by diatoms, and 2) as a species, T. pseudonana is likely ancestrally freshwater. Marine strains therefore represent recent recolonizations of higher salinity habitats. In addition, the combination of a relatively nondescript form and a convoluted taxonomic history has introduced some confusion about the identity of T. pseudonana and, by extension, its phylogeny and ecology. We resolve these issues and use phylogenetic criteria to show that T. pseudonana is more appropriately classified by its original name, Cyclotella nana. Cyclotella contains a mix of marine and freshwater species and so more accurately conveys the complexities of the phylogenetic and natural histories of T. pseudonana. CONCLUSIONS: The multitude of physical barriers that likely must be overcome for diatoms to successfully colonize freshwaters suggests that the physiological traits of T. pseudonana, and the genes underlying those traits, might differ from those of strictly marine diatoms. The freshwater ancestry of T. pseudonana might therefore confound generalizations about the physiological and metabolic properties of marine diatoms. The freshwater component of T. pseudonana's history merits careful consideration in the interpretation of experimental data collected for this important model species.