Mighty small: Observing and modeling individual microbes becomes big science

Progress in microbiology has always been driven by technological advances, ever since Antonie van Leeuwenhoek discovered bacteria by making an improved compound microscope. However, until very recently we have not been able to identify microbes and record their mostly invisible activities, such as nutrient consumption or toxin production on the level of the single cell, not even in the laboratory. This is now changing with the rapid rise of exciting new technologies for single-cell microbiology (1, 2), which enable microbiologists to do what plant and animal ecologists have been doing for a long time: observe who does what, when, where, and next to whom. Single cells taken from the environment can be identified and even their genomes sequenced. Ex situ, their size, elemental, and biochemical composition, as well as other characteristics can be measured with high-throughput and cells sorted accordingly. Even better, individual microbes can be observed in situ with a range of novel microscopic and spectroscopic methods, enabling localization, identification, or functional characterization of cells in a natural sample, combined with detecting uptake of labeled compounds. Alternatively, they can be placed into fabricated microfluidic environments, where they can be positioned, exposed to stimuli, monitored, and their interactions controlled “in microfluido.” By introducing genetically engineered reporter cells into a fabricated landscape or a microcosm taken from nature, their reproductive success or activity can be followed, or their sensing of their local environment recorded.

Long-Term Retrospective Analysis of Mackerel Spawning in the North Sea: A New Time Series and Modeling Approach to CPR Data

We present a unique view of mackerel (Scomber scombrus) in the North Sea based on a new time series of larvae caught by the Continuous Plankton Recorder (CPR) survey from 1948-2005, covering the period both before and after the collapse of the North Sea stock. Hydrographic backtrack modelling suggested that the effect of advection is very limited between spawning and larvae capture in the CPR survey. Using a statistical technique not previously applied to CPR data, we then generated a larval index that accounts for both catchability as well as spatial and temporal autocorrelation. The resulting time series documents the significant decrease of spawning from before 1970 to recent depleted levels. Spatial distributions of the larvae, and thus the spawning area, showed a shift from early to recent decades, suggesting that the central North Sea is no longer as important as the areas further west and south. These results provide a consistent and unique perspective on the dynamics of mackerel in this region and can potentially resolve many of the unresolved questions about this stock

Transdisciplinary Science: A Path to Understanding the Interactions Among Ocean Acidification, Ecosystems, and Society

The global nature of ocean acidification (OA) transcends habitats, ecosystems, regions, and science disciplines. The scientific community recognizes that the biggest challenge in improving understanding of how changing OA conditions affect ecosystems, and associated consequences for human society, requires integration of experimental, observational, and modeling approaches from many disciplines over a wide range of temporal and spatial scales. Such transdisciplinary science is the next step in providing relevant, meaningful results and optimal guidance to policymakers and coastal managers. We discuss the challenges associated with integrating ocean acidification science across funding agencies, institutions, disciplines, topical areas, and regions, and the value of unifying science objectives and activities to deliver insights into local, regional, and global scale impacts. We identify guiding principles and strategies for developing transdisciplinary research in the ocean acidification science community.

Heavy metal accumulation reflecting natural sedimentary processes and anthropogenic activities in two contrasting coastal wetland ecosystems, eastern China

Due to the impacts of natural processes and anthropogenic activities, different coastal wetlands are faced with variable patterns of heavy metal contamination. It is important to quantify the contributions of pollutant sources, in order to adopt appropriate protection measures for local ecosystems. The aim of this research was to compare the heavy metal contamination patterns of two contrasting coastal wetlands in eastern China. In addition, the contributions from various metal sources were identified and quantified, and influencing factors, such as the role of the plant Spartina alterniflora, were evaluated. Materials and methods Sediment samples were taken from two coastal wetlands (plain-type tidal flat at the Rudong (RD) wetland vs embayment-type tidal flat at Luoyuan Bay (LY)) to measure the content of Al, Fe, Co, Cr, Cu, Mn, Mo, Ni, Sr, Zn, Pb, Cd, and As. Inductively coupled plasma atomic emission spectrometry, flame atomic absorption spectrometry, and atomic fluorescence spectrometry methods were used for metal detection. Meanwhile, the enrichment factor and geoaccumulation index were applied to assess the pollution level. Principle component analysis and receptor modeling were used to quantify the sources of heavy metals. Results and discussion Marked differences in metal distribution patterns between the two systems were present. Metal contents in LY were higher than those in RD, except for Sr and Mo. The growth status of S. alterniflora influenced metal accumulations in RD, i.e., heavy metals were more easily adsorbed in the sediment in the following sequence: Cu > Cd > Zn > Cr > Al > Pb ≥ Ni ≥ Co > Fe > Sr ≥ Mn > As > Mo as a result of the presence and size of the vegetation. However, this phenomenon was not observed in LY. A higher potential ecological risk was associated with LY, compared with RD, except for Mo. Based on a receptor model output, sedimentary heavy metal contents at RD were jointly influenced by natural sedimentary processes and anthropogenic activities, whereas they were dominated by anthropogenic activities at LY. Conclusions A combination of geochemical analysis and modeling approaches was used to quantify the different types of natural and anthropogenic contributions to heavy metal contamination, which is useful for pollution assessments. The application of this approach reveals that natural and anthropogenic processes have different influences on the delivery and retention of metals at the two contrasting coastal wetlands. In addition, the presence and size of S. alterniflora can influence the level of metal contamination in sedimentary environments.

Predicting the Dispersal Potential of an Invasive Polychaete Pest along a Complex Coastal Biome

Boccardia proboscidea is a recently introduced polychaete in South Africa where it is a notorious pest of commercially reared abalone. Populations were originally restricted to abalone farms but a recent exodus into the wild at some localities has raised conservation concerns due to the species’ invasive status in other parts of the world. Here, we assessed the dispersal potential of B. proboscidea by using a population genetic and oceanographic modeling approach. Since the worm is in its incipient stages of a potential invasion, we used the closely related Polydora hoplura as a proxy due its similar reproductive strategy and its status as a pest of commercially reared oysters in the country. Populations of P. hoplura were sampled from seven different localities and a section of the mtDNA gene, Cyt b and the intron ATPSa was amplified. A high resolution model of the coastal waters around southern Africa was constructed using the Regional Ocean Modeling System. Larvae were represented by passive drifters that were deployed at specific points along the coast and dispersal was quantified after a 12-month integration period. Our results showed discordance between the genetic and modeling data. There was low genetic structure (Φ = 0.04 for both markers) and no geographic patterning of mtDNA and nDNA haplotypes. However, the dispersal model found limited connectivity around Cape Point—a major phylogeographic barrier on the southern African coast. This discordance was attributed to anthropogenic movement of larvae and adult worms due to vectors such as aquaculture and shipping. As such, we hypothesized that cryptic dispersal could be overestimating genetic connectivity. Though wild populations of B. proboscidea could become isolated due to the Cape Point barrier, anthropogenic movement may play the critical role in facilitating the dispersal and spread of this species on the southern African coast.

Predicting the Dispersal Potential of an Invasive Polychaete Pest along a Complex Coastal Biome

Boccardia proboscidea is a recently introduced polychaete in South Africa where it is a notorious pest of commercially reared abalone. Populations were originally restricted to abalone farms but a recent exodus into the wild at some localities has raised conservation concerns due to the species’ invasive status in other parts of the world. Here, we assessed the dispersal potential of B. proboscidea by using a population genetic and oceanographic modeling approach. Since the worm is in its incipient stages of a potential invasion, we used the closely related Polydora hoplura as a proxy due its similar reproductive strategy and its status as a pest of commercially reared oysters in the country. Populations of P. hoplura were sampled from seven different localities and a section of the mtDNA gene, Cyt b and the intron ATPSa was amplified. A high resolution model of the coastal waters around southern Africa was constructed using the Regional Ocean Modeling System. Larvae were represented by passive drifters that were deployed at specific points along the coast and dispersal was quantified after a 12-month integration period. Our results showed discordance between the genetic and modeling data. There was low genetic structure (Φ = 0.04 for both markers) and no geographic patterning of mtDNA and nDNA haplotypes. However, the dispersal model found limited connectivity around Cape Point—a major phylogeographic barrier on the southern African coast. This discordance was attributed to anthropogenic movement of larvae and adult worms due to vectors such as aquaculture and shipping. As such, we hypothesized that cryptic dispersal could be overestimating genetic connectivity. Though wild populations of B. proboscidea could become isolated due to the Cape Point barrier, anthropogenic movement may play the critical role in facilitating the dispersal and spread of this species on the southern African coast.