Arable soil nitrogen dynamics reflect organic inputs via the extended composite phenotype.

Achieving food security requires resilient agricultural systems with improved nutrient-use efficiency, optimized water and nutrient storage in soils, and reduced gaseous emissions. Success relies on understanding coupled nitrogen and carbon metabolism in soils, their associated influences on soil structure and the processes controlling nitrogen transformations at scales relevant to microbial activity. Here we show that the influence of organic matter on arable soil nitrogen transformations can be decoded by integrating metagenomic data with soil structural parameters. Our approach provides a mechanistic explanation of why organic matter is effective in reducing nitrous oxide losses while supporting system resilience. The relationship between organic carbon, soil-connected porosity and flow rates at scales relevant to microbes suggests that important increases in nutrient-use efficiency could be achieved at lower organic carbon stocks than currently envisaged.

The effects of long-term fertilizations on soil hydraulic properties vary with scales.

Soil structure is an indicator of soil quality and its alterations following cropping system conversion or fertilization change evolve slowly. How such alterations vary with scale remains elusive. We investigated this based on the Rothamsted long-term wheat experiment (since 1843) in the UK. Triplicate cores 7 cm high and 10 cm in diameter were taken from plots that have been under different fertilizations or returned to natural woodland for more than one century for imaging using X-ray computed tomography with the voxel size being 40 µm. We then broke each core and sampled three aggregates from it to scan with the voxel size being 1.5 µm. For each core and aggregate sample, we calculated its pore size distribution, permeability and tortuosity. The results showed that the fertilization change >170 years ago reshaped the soil structure differently between the core scale and the aggregate scale. Macro-porosity of the pores (>40 µm) in the cores unfertilized or fertilized with inorganic fertilizers was low and the pores were poorly connected in the top 10 cm of soil, compared to those given farmyard manure or in the woodland. In all treatments, the pores in the core images were hydraulically anisotropic with their permeability in the horizontal direction being higher than that in the vertical direction, whereas the aggregates were comparatively isotropic. The fertilization affected image porosity and permeability at core scale more significantly than at aggregate scale, and the aggregates fertilized with farmyard manure and in the woodland were more permeable than the aggregates in other treatments. It was also found that compared to no-fertilization or fertilization with complete fertilizers, fertilizing without phosphorus over the past 20 years increased the porosity and permeability of the aggregates but not of the cores. Fertilization with inorganic fertilizers increased the tortuosity of the macropores in the cores but not of the intra-aggregate pores, compared to no-fertilization. Porosity-permeability relationship for aggregates unfertilized or fertilized with inorganic fertilisers followed a power law with R 2 > 0.8. In contrast, the permeability of the aggregates in farmyard manure and in the woodland trended differently as their porosity increased. The results also revealed that the transport ability of the aggregates and cores responded differently to carbon in that with soil carbon increasing, the permeability of the aggregates increased asymptotically while the permeability of the cores, especially its horizontal component, increased exponentially.

Soil as an extended composite phenotype of the microbial metagenome.

We use a unique set of terrestrial experiments to demonstrate how soil management practises result in emergence of distinct associations between physical structure and biological functions. These associations have a significant effect on the flux, resilience and efficiency of nutrient delivery to plants (including water). Physical structure, determining the air-water balance in soil as well as transport rates, is influenced by nutrient and physical interventions. Contrasting emergent soil structures exert selective pressures upon the microbiome metagenome. These selective pressures are associated with the quality of organic carbon inputs, the prevalence of anaerobic microsites and delivery of nutrients to microorganisms attached to soil surfaces. This variety results in distinctive gene assemblages characterising each state. The nature of the interactions provide evidence that soil behaves as an extended composite phenotype of the resident microbiome, responsive to the input and turnover of plant-derived organic carbon. We provide new evidence supporting the theory that soil-microbe systems are self-organising states with organic carbon acting as a critical determining parameter. This perspective leads us to propose carbon flux, rather than soil organic carbon content as the critical factor in soil systems, and we present evidence to support this view.

Intraspecific variation in resource use is not explained by population persistence or seasonality.

Populations of generalist grazers often contain genotypes with "powerful" and "efficient" strategies. Powerful genotypes grow rapidly on rich-quality resources, but slowly on poorer-quality ones, while efficient genotypes grow relatively better on poorer resources but cannot exploit richer resources as well. Via a "power-efficiency" trade-off, variation in resource quality could maintain genetic diversity. To evaluate this mechanism, we sampled six populations of the freshwater cladoceran Daphnia pulicaria. In persisting (year-round) populations, Daphnia consume resources that vary in quality, whereas in non-persisting (spring-only) populations, Daphnia primarily encounter rich-quality resources. We hypothesized that non-persisting populations harbor no efficient clones (hence should show lower growth on poor-quality resources). Although individuals from non-persisting populations remained smaller than individuals from persisting populations, no evidence arose for a trade-off between powerful and efficient strategies. In fact, growth rates on the two diets were positively correlated (instead of negatively, as predicted). Furthermore, in the persisting populations, we predicted that clonal selection from spring to summer should shift the distribution of genotypes from powerful (specialists on richer spring resources) to efficient (poorer, summer resources). Genetic composition of populations shifted from spring to summer, but not toward more efficient genotypes. Therefore, in these lakes, maintenance of variation among genotypes must stem from more complicated factors than population persistence patterns or seasonal shifts in resource quality alone.

Quantifying Network Dynamics and Information Flow Across Chinese Social Media During the African Ebola Outbreak.

OBJECTIVE: Social media provides us with a new platform on which to explore how the public responds to disasters and, of particular importance, how they respond to the emergence of infectious diseases such as Ebola. Provided it is appropriately informed, social media offers a potentially powerful means of supporting both early detection and effective containment of communicable diseases, which is essential for improving disaster medicine and public health preparedness. METHODS: The 2014 West African Ebola outbreak is a particularly relevant contemporary case study on account of the large number of annual arrivals from Africa, including Chinese employees engaged in projects in Africa. Weibo (Weibo Corp, Beijing, China) is China's most popular social media platform, with more than 2 billion users and over 300 million daily posts, and offers great opportunity to monitor early detection and promotion of public health awareness. RESULTS: We present a proof-of-concept study of a subset of Weibo posts during the outbreak demonstrating potential and identifying priorities for improving the efficacy and accuracy of information dissemination. We quantify the evolution of the social network topology within Weibo relating to the efficacy of information sharing. CONCLUSIONS: We show how relatively few nodes in the network can have a dominant influence over both the quality and quantity of the information shared. These findings make an important contribution to disaster medicine and public health preparedness from theoretical and methodological perspectives for dealing with epidemics. (Disaster Med Public Health Preparedness. 2018;12:26-37).

Water flow across the interface of contrasting materials: Pressure discontinuity and its implications.

Water flow along or across the interfaces of contrasting materials is ubiquitous in hydrology and how to solve them in macroscopic models derived from volumetric average of the pore-scale processes remains elusive. While the change in the average velocity and pressure at water-sediment interface has been well established for channel flow over porous beds, whether a volumetric average alerts the pressure continuity when water flows across the interface of two porous materials is poorly understood despite its imperative implications in hydrological modelling. The primary purpose of this paper is to provide evidences via pore-scale simulations that volumetrically averaging the pore-scale processes indeed yields a discontinuous pressure when water flows across a material interface. We simulated two columns numerically reconstructed by filling them with stratified media: One is an idealised two-layer system and the other one is a 3D column filled by fine glass beads over coarse glass beads with their pore geometry acquired using x-ray computed tomography. The pore-scale simulation is to mimic the column experiment by driving fluid to flow through the void space under an externally imposed pressure gradient. Once fluid flow reaches steady state, its velocity and pressure in all voxels are sampled and they are then spatially averaged over each section perpendicular to the average flow direction. The results show that the average pressure drops abruptly at the material interface no matter which direction the fluid flows. Compared with the effective permeability estimated from the homogenization methods well established in the literature, the emerged discontinuous pressure at the interface reduces the combined ability of the two strata to conduct water. It is also found that under certain circumstances fluid flow is direction-dependant, moving faster when flowing in the fine-coarse direction than in the coarse-to-fine direction under the same pressure gradient. Although significant efforts are needed to incorporate these findings into practical models, we do elicit the emergence of discontinuous pressure at material interface due to volumetric average as well as its consequent implications in modelling of flow in heterogeneous and stratified media.

Informal Networks in Disaster Medicine.

OBJECTIVE: Our study of informal networks aimed to explore information-sharing environments for the management of disaster medicine and public health preparedness. Understanding interagency coordination in preparing for and responding to extreme events such as disease outbreaks is central to reducing risks and coordination costs. METHODS: We evaluated the pattern of information flow for actors involved in disaster medicine through social network analysis. Social network analysis of agencies can serve as a basis for the effective design and reconstruction of disaster medicine response coordination structures. This research used new theoretical approaches in suggesting a framework and a method to study the outcome of complex inter-organizational networks in coordinating disease outbreak response. We present research surveys of 70 health professionals from different skill sets and organizational positions during the swine influenza A (H1N1) PDM09 2009 pandemic. The survey and interviews were designed to collect both qualitative and quantitative data in order to build a comprehensive and in-depth understanding of the dynamics of the inter-organizational networks that evolved during the pandemic. RESULTS: The degree centrality of the informal network showed a positive correlation with performance, in which the ego's performance is related to the number of links he or she establishes informally-outside the standard operating structure during the pandemic. Informal networks facilitate the transmission of both strong (ie, infections, confirmed cases, deaths in hospital or clinic settings) and weak (ie, casual acquaintances) ties. CONCLUSIONS: The results showed that informal networks promoted community-based ad hoc and formal networks, thus making overall disaster medicine and public health preparedness more effective. (Disaster Med Public Health Preparedness. 2017;11:343-354).

Unraveling the mechanistic complexity of Alzheimer's disease through systems biology.

Alzheimer's disease (AD) is a complex, multifactorial disease that has reached global epidemic proportions. The challenge remains to fully identify its underlying molecular mechanisms that will enable development of accurate diagnostic tools and therapeutics. Conventional experimental approaches that target individual or small sets of genes or proteins may overlook important parts of the regulatory network, which limits the opportunity of identifying multitarget interventions. Our perspective is that a more complete insight into potential treatment options for AD will only be made possible through studying the disease as a system. We propose an integrative systems biology approach that we argue has been largely untapped in AD research. We present key publications to demonstrate the value of this approach and discuss the potential to intensify research efforts in AD through transdisciplinary collaboration. We highlight challenges and opportunities for significant breakthroughs that could be made if a systems biology approach is fully exploited.

Networks of preparedness and response during Australian H1N1 outbreak.

OBJECTIVE: New theoretical and practical approaches were used to determine the outcome of complex interorganizational networks during the 2009 H1N1 outbreak in Australia. METHODS: Seventy health professionals from different skill sets and organizational positions who participated in the 2009 swine influenza H1N1 outbreak in Australia were surveyed. Interviews were designed to collect both qualitative and quantitative data to build a comprehensive and in-depth understanding of the dynamics of interorganizational networks that evolve during the coordinated response to the H1N1 outbreak. Three main components of network theory, ie, degree centrality, connectedness, and tie strength, were used to construct a performance model for assessing networks of preparedness and response. RESULTS: We observed that increasing communication frequency and diversifying the tiers of the interorganizational links enhanced the overall network's performance in the case of formal coordination. Network measures such as centrality, connectedness, and tie strength were relevant and resulted in improving the entire network's performance during the outbreak. CONCLUSION: In the context of a disease outbreak in a complex environment and a large geographical area, this investigation has provided a new perspective for understanding how the structure of a collaborative network of personnel affects the performance of the overall network.

Evolutionary longitudinal network dynamics of global zoonotic research.

At global and local levels, we are observing an increasing range and rate of disease outbreaks that show evidence of jumping from animals to humans, and from food to humans. Zoonotic infections (i.e. Hendra, swine flu, anthrax) affect animal health and can be deadly to humans. The increasing rate of outbreaks of infectious diseases transferring from animals to humans (i.e. zoonotic diseases) necessitates detailed understanding of the education, research and practice of animal health and its connection to human health. These emerging microbial threats underline the need to exploring the evolutionary dynamics of zoonotic research across public health and animal health. This study investigates the collaboration network of different countries engaged in conducting zoonotic research. We explore the dynamics of this network from 1980 to 2012 based on large scientific data developed from Scopus. In our analyses, we compare several properties of the network including density, clustering coefficient, giant component and centrality measures over time. We also map the network over different time intervals using VOSviewer. We analyzed 5182 publication records. We found United States and United Kingdom as the most collaborative countries working with 110 and 74 other countries in 1048 and 599 cases, respectively. Our results show increasing close collaboration among scientists from the United States, several European countries including United Kingdom, Italy, France, Netherland, Switzerland, China and Australia with scientists from other parts of the world.

Resource seeking strategies of zoosporic true fungi in heterogeneous soil habitats at the microscale level.

Zoosporic true fungi have frequently been identified in samples from soil and freshwater ecosystems using baiting and molecular techniques. In fact some species can be components of the dominant groups of microorganisms in particular soil habitats. Yet these microorganisms have not yet been directly observed growing in soil ecosystems. Significant physical characteristics and features of the three-dimensional structures of soils which impact microorganisms at the microscale level are discussed. A thorough knowledge of soil structures is important for studying the distribution of assemblages of these fungi and understanding their ecological roles along spatial and temporal gradients. A number of specific adaptations and resource seeking strategies possibly give these fungi advantages over other groups of microorganisms in soil ecosystems. These include chemotactic zoospores, mechanisms for adhesion to substrates, rhizoids which can penetrate substrates in small spaces, structures which are resistant to environmental extremes, rapid growth rates and simple nutritional requirements. These adaptations are discussed in the context of the characteristics of soils ecosystems. Recent advances in instrumentation have led to the development of new and more precise methods for studying microorganisms in three-dimensional space. New molecular techniques have made identification of microbes possible in environmental samples.

Microbial diversity affects self-organization of the soil-microbe system with consequences for function.

Soils are complex ecosystems and the pore-scale physical structure regulates key processes that support terrestrial life. These include maintaining an appropriate mixture of air and water in soil, nutrient cycling and carbon sequestration. There is evidence that this structure is not random, although the organizing mechanism is not known. Using X-ray microtomography and controlled microcosms, we provide evidence that organization of pore-scale structure arises spontaneously out of the interaction between microbial activity, particle aggregation and resource flows in soil. A simple computational model shows that these interactions give rise to self-organization involving both physical particles and microbes that gives soil unique material properties. The consequence of self-organization for the functioning of soil is determined using lattice Boltzmann simulation of fluid flow through the observed structures, and predicts that the resultant micro-structural changes can significantly increase hydraulic conductivity. Manipulation of the diversity of the microbial community reveals a link between the measured change in micro-porosity and the ratio of fungal to bacterial biomass. We suggest that this behaviour may play an important role in the way that soil responds to management and climatic change, but that this capacity for self-organization has limits.

Toward a synthetic economic systems modeling tool for sustainable exploitation of ecosystems.

Environmental resources that underpin the basic human needs of water, energy, and food are predicted to become in such short supply by 2050 that global security and the well-being of millions will be under threat. These natural commodities have been allowed to reach crisis levels of supply because of a failure of economic systems to sustain them. This is largely because there have been no means of integrating their exploitation into any economic model that effectively addresses ecological systemic failures in a way that provides an integrated ecological-economic tool that can monitor and evaluate market and policy targets. We review the reasons for this and recent attempts to address the problem while identifying outstanding issues. The key elements of a policy-oriented economic model that integrates ecosystem processes are described and form the basis of a proposed new synthesis approach. The approach is illustrated by an indicative case study that develops a simple model for rainfed and irrigated food production in the Murray-Darling basin of southeastern Australia.

Systems pathology--taking molecular pathology into a new dimension.

The wealth of morphological, histological, and molecular data from human cancers available to pathologists means that pathology is poised to become a truly quantitative systems science. By measuring morphological parameters such as tumor stage and grade, and by measuring molecular biomarkers such as hormone receptor status, pathologists have sometimes accurately predicted what will happen to a patient's tumor. While 'omic' technologies have seemingly improved prognostication and prediction, some molecular 'signatures' are not useful in clinical practice because of the failure to independently validate these approaches. Many associations between gene 'signatures' and clinical response are correlative rather than mechanistic, and such associations are poor predictors of how cellular biochemical networks will behave in perturbed, diseased cells. Using systems biology, the dynamics of reactions in cells and the behavior between cells can be integrated into models of cancer. The challenge is how to integrate multiple data from the clinic into tractable models using mathematical models and systems biology, and how to make the resultant model sufficiently robust to be of practical use. We discuss the difficulties in using mathematics to model cancer, and review some approaches that may be used to allow systems biology to be successfully applied in the clinic.

Anomalous diffusion of heterogeneous populations characterized by normal diffusion at the individual level.

The characterization of the dispersal of populations of non-identical individuals is relevant to most ecological and epidemiological processes. In practice, the movement is quantified by observing relatively few individuals, and averaging to estimate the rate of dispersal of the population as a whole. Here, we show that this can lead to serious errors in the predicted movement of the population if the individuals disperse at different rates. We develop a stochastic model for the diffusion of heterogeneous populations, inspired by the movement of the parasitic nematode Phasmarhabditis hermaphrodita. Direct observations of this nematode in homogeneous and heterogeneous environments reveal a large variation in individual behaviour within the population as reflected initially in the speed of the movement. Further statistical analysis shows that the movement is characterized by temporal correlations and in a heterogeneously structured environment the correlations that occur are of shorter range compared with those in a homogeneous environment. Therefore, by using the first-order correlated random walk techniques, we derive an effective diffusion coefficient for each individual, and show that there is a significant variation in this parameter among the population that follows a gamma distribution. Based on these findings, we build a new dispersal model in which we maintain the classical assumption that individual movement can be described by normal diffusion, but due to the variability in individual dispersal rates, the diffusion coefficient is not constant at the population level and follows a continuous distribution. The conclusions and methodology presented are relevant to any heterogeneous population of individuals with widely different diffusion rates.

Continuous time random walk model better describes the tailing of atrazine transport in soil.

Contaminant transport in soils is complicated and involves some physical and chemical nonequilibrium processes. In this research, the soil column displacement experiments of Cl(-) and atrazine under different flow velocities were carried out. The data sets of Cl(-) transport in sandy loam fitted to the convection dispersion equation (CDE) and the two-region model (TRM) indicated that the effects of physical nonequilibrium process produced by immobile water on the breakthrough curves (BTCs) of Cl(-) and atrazine transport through the repacking soil columns were negligible. The two-site model (TSM) and the continuous time random walk (CTRW) were also used to fit atrazine transport behavior at the flow rate of 19.86 cm h(-1). The CTRW convincingly captured the full evolution of atrazine BTC in the soil column, especially for the part of long tailing. However, the TSM failed to characterize the tailing of atrazine BTC in the soil column. The calculated fraction of equilibrium sorption sites, F, ranging from 0.78 to 0.80 for all flow rates suggested the contribution of nonequilibrium sorption sites to the asymmetry of atrazine BTCs. Furthermore, the data sets for the flow rates of 6.68 cm h(-1) and 32.81 cm h(-1) were predicted by the TSM and the CTRW. As to the flow rate of 6.68 cm h(-1), the CTRW predicted the entire BTC of atrazine transport better than the TSM did. For the flow rate of 32.81 cm h(-1), the CTRW characterized the late part of the tail better, while the TSM failed to predict the tailings of atrazine BTC.

Modelling interactions in fungi.

Indeterminate organisms have received comparatively little attention in theoretical ecology and still there is much to be understood about the origins and consequences of community structure. The fungi comprise an entire kingdom of life and epitomize the indeterminate growth form. While interactions play a significant role in shaping the community structure of indeterminate organisms, to date most of our knowledge relating to fungi comes from observing interaction outcomes between two species in two-dimensional arena experiments. Interactions in the natural environment are more complex and further insight will benefit from a closer integration of theory and experiment. This requires a modelling framework capable of linking genotype and environment to community structure and function. Towards this, we present a theoretical model that replicates observed interaction outcomes between fungal colonies. The hypotheses underlying the model propose that interaction outcome is an emergent consequence of simple and highly localized processes governing rates of uptake and remobilization of resources, the metabolic cost of production of antagonistic compounds and non-localized transport of internal resources. The model may be used to study systems of many interacting colonies and so provides a platform upon which the links between individual-scale behaviour and community-scale function in complex environments can be built.

Visualization, modelling and prediction in soil microbiology.

The introduction of new approaches for characterizing microbial communities and imaging soil environments has benefited soil microbiology by providing new ways of detecting and locating microorganisms. Consequently, soil microbiology is poised to progress from simply cataloguing microbial complexity to becoming a systems science. A systems approach will enable the structures of microbial communities to be characterized and will inform how microbial communities affect soil function. Systems approaches require accurate analyses of the spatio-temporal properties of the different microenvironments present in soil. In this Review we advocate the need for the convergence of the experimental and theoretical approaches that are used to characterize and model the development of microbial communities in soils.

Modelling nematode movement using time-fractional dynamics.

We use a correlated random walk model in two dimensions to simulate the movement of the slug parasitic nematode Phasmarhabditis hermaphrodita in homogeneous environments. The model incorporates the observed statistical distributions of turning angle and speed derived from time-lapse studies of individual nematode trails. We identify strong temporal correlations between the turning angles and speed that preclude the case of a simple random walk in which successive steps are independent. These correlated random walks are appropriately modelled using an anomalous diffusion model, more precisely using a fractional sub-diffusion model for which the associated stochastic process is characterised by strong memory effects in the probability density function.

The role of modelling in identifying drug targets for diseases of the cell cycle.

The cell cycle is implicated in diseases that are the leading cause of mortality and morbidity in the developed world. Until recently, the search for drug targets has focused on relatively small parts of the regulatory network under the assumption that key events can be controlled by targeting single pathways. This is valid provided the impact of couplings to the wider scale context of the network can be ignored. The resulting depth of study has revealed many new insights; however, these have been won at the expense of breadth and a proper understanding of the consequences of links between the different parts of the network. Since it is now becoming clear that these early assumptions may not hold and successful treatments are likely to employ drugs that simultaneously target a number of different sites in the regulatory network, it is timely to redress this imbalance. However, the substantial increase in complexity presents new challenges and necessitates parallel theoretical and experimental approaches. We review the current status of theoretical models for the cell cycle in light of these new challenges. Many of the existing approaches are not sufficiently comprehensive to simultaneously incorporate the required extent of couplings. Where more appropriate levels of complexity are incorporated, the models are difficult to link directly to currently available data. Further progress requires a better integration of experiment and theory. New kinds of data are required that are quantitative, have a higher temporal resolution and that allow simultaneous quantitative comparison of the concentration of larger numbers of different proteins. More comprehensive models are required and must accommodate not only substantial uncertainties in the structure and kinetic parameters of the networks, but also high levels of ignorance. The most recent results relating network complexity to robustness of the dynamics provide clues that suggest progress is possible.