Description: Current sampling of genomic sequence data from eukaryotes is relatively poor, biased, and inadequate to address important questions about their biology, evolution, and ecology; this Community Page describes a resource of 700 transcriptomes from marine microbial eukaryotes to help understand their role in the world's oceans.

Description: Background Light microscopic analysis of diatom frustules is widely used both in basic and applied research, notably taxonomy, morphometrics, water quality monitoring and paleoenvironmental 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.

Description: 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. Southern Ocean. 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.

Description: Light microscopy analysis of diatom frustules is widely used in basic and applied research, notably taxonomy, morphometrics, water quality monitoring and paleo-environmental studies. Building on automated imaging solutions developed for medical/histological microscopy, we can now implement substantial parts of an automated diatom imaging workflow. Our methods resemble those drafted by the ADIAC (Automated Diatom Identification And Classification) project, and combine a commercial slide-scanning microscope with our automated diatom image analysis software SHERPA for measuring a broad range of morphometric features from individual frustules mounted on permanent slides. Although a fully automated process enabling routine diatom counting is still far from becoming reality, user intervention is minimized by extensive automation and internal quality control of the results. Furthermore care was taken to allow the user to stay in control of the most critical steps (exact segmentation of valve outlines and selection of objects of interest) using interactive functions for reviewing and revising results. We successfully applied our methods to several projects by finding, selecting and measuring up to several ten thousand diatom valves (presented at the poster session), and present our workflow in the hope that it can facilitate research on diatom morphometry.

Description: Our project aims at bringing automated microscopy and image processing methods into routine diatom analysis from the water column, sediment traps and sediment cores in the Southern Ocean. We combined a Metafer slide scanning system with SHERPA, our image analysis software developed specifically for diatom images, to characterize morphometric variation within and among diatom species. This poster gives an overview of the established methodology (presented in detail by the according talk), and its application to three studies in a paleoceanographic, a life cycle and a taxonomic context, respectively.

Description: Increasing demand for mass screenings and current possibilities of automated image acquisition lead to an accumulation of large amounts of image data in diverse fields of biology, so that the manual measurement and handling of such image data sets is often no longer feasible. The authors’ work in diatom analysis represents one of the areas that are impacted by this trend. The newly developed tool SHERPA offers a versatile image processing workflow focused on the identification and measurement of diatom 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 the ease of use, applicability to a broad range of data and problems, and the minimization of manual intervention by extensive automating and internal quality control of the results. Though it was developed for analyzing images of diatom valves originating from automated slide scanning microscopy, SHERPA can also be useful for other object detection, segmentation and identification problems. Tested with several 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. It identifies relevant valve shapes and extracts features suitable for detailed morphometric analysis and classification. Ranking of results by template matching and quality criteria helps focusing manual inspection upon difficult cases, allowing for minimum user intervention as well as for maximum output, providing a helpful tool for high-throughput analyses of image data. By applying a workflow using digital imaging and automated diatom analysis large amounts of data can be processed, and morphometric trends can be detected easily.

Description: Increasing demand for mass screenings and current possibilities of automated image acquisition lead to an accumulation of large amounts of image data in diverse fields of biology, so that the manual measurement and handling of such image data sets is often no longer feasible. The authors’ work in diatom analysis represents one of the areas that are impacted by this trend. The newly developed tool SHERPA offers a versatile image processing workflow focused on the identification and measurement of diatom 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 the ease of use, applicability to a broad range of data and problems, and the minimization of manual intervention by extensive automating and internal quality control of the results. Though it was developed for analyzing images of diatom valves originating from automated slide scanning microscopy, SHERPA can also be useful for other object detection, segmentation and identification problems. Tested with several 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. It identifies relevant valve shapes and extracts features suitable for detailed morphometric analysis and classification. Ranking of results by template matching and quality criteria helps focusing manual inspection upon difficult cases, allowing for minimum user intervention as well as for maximum output, providing a helpful tool for high-throughput analyses of image data. By applying a workflow using digital imaging and automated diatom analysis large amounts of data can be processed, and morphometric trends can be detected easily.

Description: Our software SHERPA enables the automated mass-analysis of diatom shapes by offering a versatile image processing workflow focused on the identification and measurement of object outlines. It handles all steps from image segmentation over object identification to feature extraction with minimal user interaction, extracting of a wide range of outline shape descriptors widely used in diatom studies and elsewhere. Targeting a classical system in polar paleo-oceanography, we analyzed the morphometric variability of Fragilariopsis kerguelensis valves throughout a Southern Ocean sediment core, representing glacial and interglacial periods. Commonly only few features are actually measured for this kind of analysis, whilst e.g. the valve-area is just estimated from the valve’s length and width by applying a correction factor. SHERPA however accurately measures the valve-area, and from these measurements we can identify morphological trends in Fragilariopsis kerguelensis in glacial/interglacial periods more precisely than was previously possible. These analyses also showed that in the last glacial maximum, two clearly distinct morphotypes of F. kerguelensis coexisted. These morphotypes differ in shape-characteristics, thus resulting in different area-correction factors, which are equivalent to the morphometric descriptor “rectangularity” as it is derived by SHERPA from actual measurements. These novel findings in a heavily studied system nicely illustrate the potential gains that can be reached by automated image analyses in diatom morphometrics.

Description: Little is known about life cycle details in open ocean diatoms, such as the preparation for overwintering or timing of sexual reproduction. We applied SHERPA, a diatom image analysis software, to the valves of Fragilariopsis kerguelensis (O’Meara) Hust. captured in a Polar Frontal Zone sediment trap (54°S, 141.45°E, 800m), to investigate these events. The time-series analysis revealed four significant phases: 1) Prolific vegetative reproduction phase: The fraction of smaller valves increased significantly during late spring and early summer, representative of ongoing and potentially rapid seasonal vegetative reproduction. 2) Ceasing vegetative reproduction phase: The bias for a smaller sized population notably reversed from mid-summer through to early autumn, and an increase in the minimum valve size occurred in conjunction with the end of the vegetative productive phase observed from sediment trap fluxes. 3) Sexual reproduction phase: Valves in the initial cell size range (≥ 76µm), from which sexual reproduction can be inferred, occurred principally in autumn. 4) Overwintering vegetative phase: During late autumn and through winter, valve size distributions remained nearly symmetrical with low percentages of smaller valves, and a very low vegetative reproduction rate is hypothesized. The distribution shift towards smaller valves from Phase 1 reflects the spring bloom event. We hypothesize that initially in Phase 2 the very strong distribution shift may be resultant of two concurrent factors: a) a cessation of the productive phase due to a change in environmental factors (e.g. light, nutrient availability), and b) grazing selection pressure was enhanced on the population due to the rapid increase in smaller valves. We speculate, from our observations during Phases 3 and 4, that an overwintering strategy is in place for the species. In this phase only large cells maintain sufficient storage capacity to survive a Southern Ocean winter, and could even sustain a source of ready supplies for inoculating the population in the next spring season. Such a “tactic” relieves the limitation of minimum size restrictions impacting on enhanced generation cycles. The results of this time-series size analysis from sediment trap fluxes, provides the first indication of the life cycle and survival strategy for Fragilariopsis kerguelensis.

Description: Increasing demand for mass screenings and current possibilities of automated image acquisition lead to an accumulation of large amounts of image data in diverse fields of biology, so that the manual measurement and handling of such image data sets is often no longer feasible. The authors’ work in diatom analysis represents one of the areas that are impacted by this trend. The newly developed tool SHERPA offers a versatile image processing workflow focused on the identification and measurement of diatom 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 the ease of use, applicability to a broad range of data and problems, and the minimization of manual intervention by extensive automating and internal quality control of the results. Though it was developed for analyzing images of diatom valves originating from automated slide scanning microscopy, SHERPA can also be useful for other object detection, segmentation and identification problems. Tested with several 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. It identifies relevant valve shapes and extracts features suitable for detailed morphometric analysis and classification. Ranking of results by template matching and quality criteria helps focusing manual inspection upon difficult cases, allowing for minimum user intervention as well as for maximum output, providing a helpful tool for high-throughput analyses of image data. By applying a workflow using digital imaging and automated diatom analysis large amounts of data can be processed, and morphometric trends can be detected easily.