Global oceanic production of nitrous oxide

We use transient time distributions calculated from tracer data together with in situ measurements of nitrous oxide (N(2)O) to estimate the concentration of biologically produced N(2)O and N(2)O production rates in the ocean on a global scale. Our approach to estimate the N(2)O production rates integrates the effects of potentially varying production and decomposition mechanisms along the transport path of a water mass. We estimate that the oceanic N(2)O production is dominated by nitrification with a contribution of only approximately 7 per cent by denitrification. This indicates that previously used approaches have overestimated the contribution by denitrification. Shelf areas may account for only a negligible fraction of the global production; however, estuarine sources and coastal upwelling of N(2)O are not taken into account in our study. The largest amount of subsurface N(2)O is produced in the upper 500 m of the water column. The estimated global annual subsurface N(2)O production ranges from 3.1 ± 0.9 to 3.4 ± 0.9 Tg N yr(-1). This is in agreement with estimates of the global N(2)O emissions to the atmosphere and indicates that a N(2)O source in the mixed layer is unlikely. The potential future development of the oceanic N(2)O source in view of the ongoing changes of the ocean environment (deoxygenation, warming, eutrophication and acidification) is discussed.     

Global diversity and oceanic divergence of humpback whales (Megaptera novaeangliae)

Humpback whales (Megaptera novaeangliae) annually undertake the longest migrations between seasonal feeding and breeding grounds of any mammal. Despite this dispersal potential, discontinuous seasonal distributions and migratory patterns suggest that humpbacks form discrete regional populations within each ocean. To better understand the worldwide population history of humpbacks, and the interplay of this species with the oceanic environment through geological time, we assembled mitochondrial DNA control region sequences representing approximately 2700 individuals (465 bp, 219 haplotypes) and eight nuclear intronic sequences representing approximately 70 individuals (3700 bp, 140 alleles) from the North Pacific, North Atlantic and Southern Hemisphere. Bayesian divergence time reconstructions date the origin of humpback mtDNA lineages to the Pleistocene (880 ka, 95% posterior intervals 550–1320 ka) and estimate radiation of current Northern Hemisphere lineages between 50 and 200 ka, indicating colonization of the northern oceans prior to the Last Glacial Maximum. Coalescent analyses reveal restricted gene flow between ocean basins, with long-term migration rates (individual migrants per generation) of less than 3.3 for mtDNA and less than 2 for nuclear genomic DNA. Genetic evidence suggests that humpbacks in the North Pacific, North Atlantic and Southern Hemisphere are on independent evolutionary trajectories, supporting taxonomic revision of M. novaeangliae to three subspecies.     

Estimating nutrients recycling by tropical oceanic macroplankton-micronekton from biomass data

Simultaneous measurements of biomass and excretion of macroplankton-micronektonlead to similar results in tropical Atlantic and Pacific Oceans.Ratios are thus proposed to roughly estimate regenerated productionin oligotrophic tropical waters from biomass data: biomass figures(mg dry wt m^–2) should be multiplied by 0.32 to estimatethe amount of total nitrogen excreted (µg at m^–2day^–1) and by 0.027 to estimate the amount of total phosphorusexcreted (µg at m^–2 day^–1).     

Global analysis of fluorescence fluctuation data

Over the last decade the number of applications of fluorescence correlation spectroscopy (FCS) has grown rapidly. Here we describe the development and application of a software package, FCS Data Processor, to analyse the acquired correlation curves. The algorithms combine strong analytical power with flexibility in use. It is possible to generate initial guesses, link and constrain fit parameters to improve the accuracy and speed of analysis. A global analysis approach, which is most effective in analysing autocorrelation curves determined from fluorescence fluctuations of complex biophysical systems, can also be implemented. The software contains a library of frequently used models that can be easily extended to include user-defined models. The use of the software is illustrated by analysis of different experimental fluorescence fluctuation data sets obtained with Rhodamine Green in aqueous solution and enhanced green fluorescent protein in vitro and in vivo.An erratum to this article can be found at Victor V. Skakun, Mark A. Hink and Anatoli V. Digris contributed equally to this work.     

Global phylogeography of marine Synechococcus and Prochlorococcus reveals a distinct partitioning of lineages among oceanic biomes

Marine cyanobacteria of the genera Prochlorococcus and Synechococcus are important contributors to global primary production occupying a key position at the base of marine food webs. The genetically diverse nature of each genus is likely an important reason for their successful colonization of vast tracts of the world's oceans, a feature that has led to detailed analysis of the distribution of these genetic lineages at the local and ocean basin scale. Here, we extend these analyses to the global dimension, using new data from cruises in the Pacific, Indian and Arctic Oceans in combination with data from previous studies in the Atlantic Ocean, Arabian Sea, Red Sea and a circumnavigation of the southern hemisphere to form a data set which comprises most of the world's major ocean systems. We show that the distribution patterns of Prochlorococcus and Synechococcus lineages are remarkably similar in different ocean systems with comparable environmental conditions, but producing a strikingly different 'signature' in the four major ocean domains or biomes (the Polar Domain, Coastal Boundary Domain, Trade Winds Domain and Westerly Winds Domain). This clearly reiterates the idea of spatial partitioning of individual cyanobacterial lineages, but at the global scale.     

Global analysis of fluorescence lifetime imaging microscopy data

Global analysis techniques are described for frequency domain fluorescence lifetime imaging microscopy (FLIM) data. These algorithms exploit the prior knowledge that only a limited number of fluorescent molecule species whose lifetimes do not vary spatially are present in the sample. Two approaches to implementing the lifetime invariance constraint are described. In the lifetime invariant fit method, each image in the lifetime image sequence is spatially averaged to obtain an improved signal-to-noise ratio. The lifetime estimations from these averaged data are used to recover the fractional contribution to the steady-state fluorescence on a pixel-by-pixel basis for each species. The second, superior, approach uses a global analysis technique that simultaneously fits the fractional contributions in all pixels and the spatially invariant lifetimes. In frequency domain FLIM the maximum number of lifetimes that can be fit with the global analysis method is twice the number of lifetimes that can be fit with conventional approaches. As a result, it is possible to discern two lifetimes with a single-frequency FLIM setup. The algorithms were tested on simulated data and then applied to separate the cellular distributions of coexpressed green fluorescent proteins in living cells.     

Seawater DMS in a perturbed coastal ecosystem

Intra- and interspecific niche overlap for two mayfly species with similar life cycle timing, Rhithrogena semicolorata and Ecdyonurus sp. gr. venosus, were investigated. The nymphs were classified into 5 classes according to size and spatial overlaps are measured along a substratum roughness gradient. Substratum roughness selection was investigated by defining utilisation curves, optimum and tolerance values of the nymphs in relation to larval growth. Differences between species and size classes within each species were observed. Ecdyonurus sp. gr. venosus dominated on rough substrates, whereas R. semicolorata was most abundant on smooth substrates. An intermediate value of total interspecific substratum roughness overlap (0.49) was found. Higher intraspecific than interspecific overlap values suggested a spatial niche segregation between the two species. The results suggested that the spatial niches measured, were closer to the `fundamental niches' than could be expected if competition was acting on the two studied populations.     

Compartment model for biological conversions of DMS in a microbial mat: Effect of pH on DMS fluxes

Abstract: A model has been developed to describe the biological conversions of five functional groups of microorganisms in a microbial mat. Microbial metabolism and transport of nutrients are the two dominant processes that were considered. The microbial activity was described with Michaelis-Menten kinetics. Transport of nutrients through the mat was described by simple transport processes. The model was validated using documented measurements, and was used to simulate the fluxes of compounds and concentrations in a microbial mat during a light period of 12 hours. Experimental data from Methylopila sulfovorans cultures (isolated from a microbial mat) were incorporated in the model in order to describe DMS oxidation under varying conditions in a mat.     

Global biogeographical data bases on marine fishes: caveat emptor

A review of georeferenced collection‐site records for Caribbean shore‐fishes served by major online distributors of aggregated biodiversity data found large‐scale errors in over a third of the species and genera, in nearly two‐thirds of the families. To avoid compromising the value of their services to the global science community online providers must actively address the question of data quality.     

Global considerations in hierarchical clustering reveal meaningful patterns in data

Background

A hierarchy, characterized by tree-like relationships, is a natural method of organizing data in various domains. When considering an unsupervised machine learning routine, such as clustering, a bottom-up hierarchical (BU, agglomerative) algorithm is used as a default and is often the only method applied.

Methodology/Principal Findings

We show that hierarchical clustering that involve global considerations, such as top-down (TD, divisive), or glocal (global-local) algorithms are better suited to reveal meaningful patterns in the data. This is demonstrated, by testing the correspondence between the results of several algorithms (TD, glocal and BU) and the correct annotations provided by experts. The correspondence was tested in multiple domains including gene expression experiments, stock trade records and functional protein families. The performance of each of the algorithms is evaluated by statistical criteria that are assigned to clusters (nodes of the hierarchy tree) based on expert-labeled data. Whereas TD algorithms perform better on global patterns, BU algorithms perform well and are advantageous when finer granularity of the data is sought. In addition, a novel TD algorithm that is based on genuine density of the data points is presented and is shown to outperform other divisive and agglomerative methods. Application of the algorithm to more than 500 protein sequences belonging to ion-channels illustrates the potential of the method for inferring overlooked functional annotations. ClustTree, a graphical Matlab toolbox for applying various hierarchical clustering algorithms and testing their quality is made available.

Conclusions

Although currently rarely used, global approaches, in particular, TD or glocal algorithms, should be considered in the exploratory process of clustering. In general, applying unsupervised clustering methods can leverage the quality of manually-created mapping of proteins families. As demonstrated, it can also provide insights in erroneous and missed annotations.     

Extinction debt on oceanic islands

Habitat destruction is the leading cause of species extinctions. However, there is typically a time‐lag between the reduction in habitat area and the eventual disappearance of the remnant populations. These “surviving but ultimately doomed” species represent an extinction debt. Calculating the magnitude of such future extinction events has been hampered by potentially inaccurate assumptions about the slope of species–area relationships, which are habitat‐ and taxon‐specific. We overcome this challenge by applying a method that uses the historical sequence of deforestation in the Azorean Islands, to calculate realistic and ecologically‐adjusted species–area relationships. The results reveal dramatic and hitherto unrecognized levels of extinction debt, as a result of the extensive destruction of the native forest:>95%, in<600 yr. Our estimations suggest that more than half of the extant forest arthropod species, which have evolved in and are dependent on the native forest, might eventually be driven to extinction. Data on species abundances from Graciosa Island, where only a very small patch of secondary native vegetation still exists, as well as the number of species that have not been found in the last 45 yr, despite the extensive sampling effort, offer support to the predictions made. We argue that immediate action to restore and expand native forest habitat is required to avert the loss of numerous endemic species in the near future.     

Global data for ecology and epidemiology: a novel algorithm for temporal Fourier processing MODIS data

Background

Remotely-sensed environmental data from earth-orbiting satellites are increasingly used to model the distribution and abundance of both plant and animal species, especially those of economic or conservation importance. Time series of data from the MODerate-resolution Imaging Spectroradiometer (MODIS) sensors on-board NASA''s Terra and Aqua satellites offer the potential to capture environmental thermal and vegetation seasonality, through temporal Fourier analysis, more accurately than was previously possible using the NOAA Advanced Very High Resolution Radiometer (AVHRR) sensor data. MODIS data are composited over 8- or 16-day time intervals that pose unique problems for temporal Fourier analysis. Applying standard techniques to MODIS data can introduce errors of up to 30% in the estimation of the amplitudes and phases of the Fourier harmonics.

Methodology/Principal Findings

We present a novel spline-based algorithm that overcomes the processing problems of composited MODIS data. The algorithm is tested on artificial data generated using randomly selected values of both amplitudes and phases, and provides an accurate estimate of the input variables under all conditions. The algorithm was then applied to produce layers that capture the seasonality in MODIS data for the period from 2001 to 2005.

Conclusions/Significance

Global temporal Fourier processed images of 1 km MODIS data for Middle Infrared Reflectance, day- and night-time Land Surface Temperature (LST), Normalised Difference Vegetation Index (NDVI), and Enhanced Vegetation Index (EVI) are presented for ecological and epidemiological applications. The finer spatial and temporal resolution, combined with the greater geolocational and spectral accuracy of the MODIS instruments, compared with previous multi-temporal data sets, mean that these data may be used with greater confidence in species'' distribution modelling.     

Re-examination of global emerging patterns of ocean DMS concentration

During the last decade the number of seawater dimethylsulfide (DMS) concentration measurements has increased substantially. The importance this gas, emitted from the ocean to the atmosphere, may have in the cloud microphysics and hence in the Earth albedo and radiation budget, makes it necessary to accurately reproduce the global distribution. Recently, the monthly global DMS climatology has been updated taking advantage of the threefold increased size and better resolved distribution of the observations available in the DMS database. Here, the emerging patterns found with the previous versions of the database and climatology are explored with the updated versions. The statistical relationships between the seasonalities of DMS concentrations and other variables are re-examined. The positive correlation previously found between surface seawater DMS and the daily-averaged climatological solar radiation dose in the upper mixed layer of the open ocean is confirmed with both the updated DMS database and climatology. Re-examination of the latitudinal match-mismatch between the seasonalities of DMS and phytoplankton, represented by the chlorophyll a concentration, reveals that they are highly positively correlated in latitudes higher than 40°, but anti-correlated in the 20°–40° latitudinal bands of both hemispheres. Overall, these global emerging patterns provide key information to further understanding the factors that control the emission of volatile sulfur from the ocean. The large uncertainties associated with the methodologies used in global computations, however, call for caution in using these emerging patterns as predictive tools, and prompt to the design of time series and process-oriented studies aimed at testing the validity of the observed relationships.     

Global rigid body modeling of macromolecular complexes against small-angle scattering data

New methods to automatically build models of macromolecular complexes from high-resolution structures or homology models of their subunits or domains against x-ray or neutron small-angle scattering data are presented. Depending on the complexity of the object, different approaches are employed for the global search of the optimum configuration of subunits fitting the experimental data. An exhaustive grid search is used for hetero- and homodimeric particles and for symmetric oligomers formed by identical subunits. For the assemblies or multidomain proteins containing more then one subunit/domain per asymmetric unit, heuristic algorithms based on simulated annealing are used. Fast computational algorithms based on spherical harmonics representation of scattering amplitudes are employed. The methods allow one to construct interconnected models without steric clashes, to account for the particle symmetry and to incorporate information from other methods, on distances between specific residues or nucleotides. For multidomain proteins, addition of missing linkers between the domains is possible. Simultaneous fitting of multiple scattering patterns from subcomplexes or deletion mutants is incorporated. The efficiency of the methods is illustrated by their application to complexes of different types in several simulated and practical examples. Limitations and possible ambiguity of rigid body modeling are discussed and simplified docking criteria are provided to rank multiple models. The methods described are implemented in publicly available computer programs running on major hardware platforms.     

Global protein interactome exploration through mining genome-scale data in Arabidopsis thaliana

Background

Many essential cellular processes, such as cellular metabolism, transport, cellular metabolism and most regulatory mechanisms, rely on physical interactions between proteins. Genome-wide protein interactome networks of yeast, human and several other animal organisms have already been established, but this kind of network reminds to be established in the field of plant.

Results

We first predicted the protein protein interaction in Arabidopsis thaliana with methods, including ortholog, SSBP, gene fusion, gene neighbor, phylogenetic profile, coexpression, protein domain, and used Naïve Bayesian approach next to integrate the results of these methods and text mining data to build a genome-wide protein interactome network. Furthermore, we adopted the data of GO enrichment analysis, pathway, published literature to validate our network, the confirmation of our network shows the feasibility of using our network to predict protein function and other usage.

Conclusions

Our interactome is a comprehensive genome-wide network in the organism plant Arabidopsis thaliana, and provides a rich resource for researchers in related field to study the protein function, molecular interaction and potential mechanism under different conditions.