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Reconstructing interactions from observational data is a critical need for investigating natural biological networks, wherein network dimensionality is usually high. However, these pose a challenge to existing methods that can quantify only small interaction networks. Here, we proposed a novel approach to reconstruct high-dimensional interaction Jacobian networks using empirical time series without specific model assumptions. This method, named "multiview distance regularised S-map," generalised the state space reconstruction to accommodate high dimensionality and overcome difficulties in quantifying massive interactions with limited data. When evaluating this method using time series generated from theoretical models involving hundreds of interacting species, estimated strengths of interaction Jacobians were in good agreement with theoretical expectations. Applying this method to a natural bacterial community helped identify important species from the interaction network and revealed mechanisms governing the dynamical stability of a bacterial community. The proposed method overcame the challenge of high dimensionality in large natural dynamical systems.

Zoosporic parasites (i.e. fungi and fungi-like aquatic microorganisms) constitute important drivers of natural populations, causing severe host mortality. Economic impacts of parasitic diseases are notable in the microalgae biotech industry, affecting production of food ingredients, biofuels, pharma- and nutraceuticals. While scientific research on this topic is gaining traction by increasing studies elucidating the functional role of zoosporic parasites in natural ecosystems, we are currently lacking integrated and interdisciplinary efforts for effectively detecting and controlling parasites in the microalgae industry. To fill this gap we propose to establish an innovative, dynamic European network connecting scientists, industries and stakeholders to optimize information exchange, equalize access to resources and to develop a joint research agenda. ParAqua aims at compiling and making available all information on the occurrence of zoosporic parasites and their relationship with hosts, elucidate drivers and evaluate impacts of parasitism in natural and man-made aquatic environments. We aim to implement new tools for monitoring and prevention of infections, and to create protocols and a Decision Support Tool for detecting and controlling parasites in the microalgae biotech production. Applied knowledge on zoosporic parasites can feed back from industry to ecology, and we therefore will explore whether the developed tools can be applied for monitoring lakes and reservoirs. Short-Term Scientific Missions and Training Schools will be organised specifically for early stage scientists and managers – with a specific focus on ITC – with the aim to share and integrate both scientific and applied expertise and increase exchange between basic and applied researchers and stakeholders.

Host-parasite interactions between phytoplankton and fungi (chytrids) are key processes in aquatic ecosystems. However, individual-level heterogeneity in these interactions remains unexplored, although its importance in predicting the spread of diseases has been demonstrated in epidemiology. In this study, we experimentally tested whether individual-level heterogeneity could be a good indicator of phytoplankton-chytrid interactions, using a freshwater green algaStaurastrumsp., the diatomsUlnariasp. andFragilaria crotonensis, and chytrid fungi. The number of attached fungi per host cell showed a non-random clumped parasite distribution onUlnariasp. andF. crotonensis, but a random Poisson distribution onStaurastrumsp. To explore the potential mechanisms of these patterns, we developed a mathematical model describing sequential encounters between chytrid zoospores and host cells. The statistical fits of the model explained the parasite distributions forUlnariasp. andF. crotonensiswell, indicating that the clumped parasite distributions may result from an infection rate, increasing with the number of infections that already occurred on each host cell. Simultaneous analysis of volatile organic compounds (VOCs) from uninfected and infected host populations revealed that, among 13 VOCs detected, 6 components characterized the differences in VOC compositions between species and infection status. In particular, the level of beta-ionone, potentially acting against fungal activities, was significantly reduced in the presence of chytrid infection ofStaurastrumsp. These VOCs are targets for future studies, which potentially act as chemical signals influencing chytrid zoospores’ behaviors. The combination of mathematical and chemical analyses represents a promising approach to better understand the individual-level processes of phytoplankton-chytrid interactions.

An ecosystem function is suggested to be more sensitive to biodiversity loss (i.e. low functional redundancy) when focusing on specific-type functions than broad-type functions. Thus far, specific-type functions have been loosely defined as functions performed by a small number of species (facilitative species) or functions involved in utilizing complex substrates. However, quantitative examination of functional specificity remains underexplored. We quantified the functional redundancy of 33 ecosystem functions in a freshwater system from 76 prokaryotic community samples over 3 years. For each function, we used a sparse regression model to estimate the number of facilitative Amplicon Sequence Variants (ASVs) and to define taxon-based functional specificity. We also used Bertz structural complexity to determine substrate-based functional specificity. We found that functional redundancy increased with the taxon-based functional specificity, defined as the proportion of facilitative ASVs (= facilitative ASV richness/facilitative ASV richness + repressive ASV (ASVs reducing functioning) richness). When using substrate-based functional specificity, functional redundancy was influenced by Bertz complexity per se and by substrate acquisition mechanisms. Therefore, taxon-based functional specificity is a better predictive index for evaluating functional redundancy than substrate-based functional specificity. These findings provide a framework to quantitatively predict the consequences of diversity losses on ecosystem functioning.

The effect of Ce doping and pretreatment of Pt/Al2O3 on its catalysis of propane oxidation was investigated after aging the catalysts. The Ce amount and pretreatment conditions were varied, and the propane oxidation activity was measured. The properties of the catalysts were investigated by means of XRD, STEM-EDX, FT-IR, and H2-TPR. The size of the Pt nanoparticles (PtNPs) decreased for water-treated catalysts doped with a small amount of Ce, suggesting that water treatment of Ce-doped catalysts inhibits Pt sintering. The minimum PtNP size was obtained with ca. 3.6 wt% of Ce. The Ce species with less than 3.6 wt% existed in a dispersed state, whereas above this value, CeO2 particulates co-existed. The propane oxidation temperature of the water-treated catalysts was lowered to an extent that depended on the Ce content. This tendency is consistent with the PtNP size in the catalysts. It is considered that highly dispersed Ce species take a primary role in promoting propane oxidation on PtNPs. The reduction temperature of Ce species on water-treated catalysts was lower than that of untreated catalysts, probably owing to a stronger interaction between Pt and Ce, demonstrated by FT-IR measurements. The increased reducibility of Ce species may be the reason for the improved oxidation activity of the catalysts.

The thermal deactivation of Pd/CeO2-ZrO2 (Pd/CZ) three-way catalysts was studied via nanoscale structural characterization and catalytic kinetic analysis to obtain a fundamental modeling concept for predicting the real catalyst lifetime. The catalysts were engine-aged at 600-1100 °C and used for chassis dynamometer driving test cycles. Observations using an electron microscope and chemisorption experiments showed that the Pd particle size significantly changed in the range of 10-550 nm as a function of aging temperatures. The deactivated catalyst structure was modeled using different-sized hemispherical Pd particles that were in intimate contact with the support surface. Therefore, Pd/CZ contained two types of surface Pd sites residing on the surface of a hemisphere (Pds) and circular periphery of the Pd/CZ interface (Pdb), whereas a reference catalyst, Pd/Al2O3, contained only Pds. In all Pd particle sizes investigated herein, Pd/CZ exhibited higher reaction rates than Pd/Al2O3, which nonlinearly increased with increasing slope as the weight-based number of surface-exposed Pd atoms ([Pds] + [Pdb]) increased. This finding contrasted with that of Pd/Al2O3, where the reaction rate linearly increased with [Pds]. When the Pds sites in both catalysts were equivalent in terms of their specific activities, the activity difference between Pd/CZ and Pd/Al2O3 corresponded to the contribution from Pdb, where oxygen storage/release to/from CZ played a key role. This contribution linearly increased with [Pdb] and therefore decreased with Pd sintering. Although both Pds and Pdb sites showed nearly constant turnover frequencies despite the difference in the Pd particle size, the values for Pdb were more than 2 orders of magnitude greater than those for Pds when assuming a single-atom width one-dimensional Pdb row model. These results suggest that the thermal deterioration of the three-phase boundary site, where Pd, CZ, and the gas phase meet, determines the activity under surface-controlled conditions.

International audience; Understanding how ecosystems will respond to climate changes requires unravelling the network of functional responses and feedbacks among biodiversity, physicochemical environments, and productivity. These ecosystem components not only change over time but also interact with each other. Therefore, investigation of individual relationships may give limited insights into their interdependencies and limit ability to predict future ecosystem states. We address this problem by analyzing long-term (16-39 years) time series data from 10 aquatic ecosystems and using convergent cross mapping (CCM) to quantify the causal networks linking phytoplankton species richness, biomass, and physicochemical factors. We determined that individual quantities (e.g., total species richness or nutrients) were not significant predictors of ecosystem stability (quantified as long-term fluctuation of phytoplankton biomass); rather, the integrated causal pathway in the ecosystem network, composed of the interactions among species richness, nutrient cycling, and phytoplankton biomass, was the best predictor of stability. Furthermore, systems that experienced stronger warming over time had both weakened causal interactions and larger fluctuations. Thus, rather than thinking in terms of separate factors, a more holistic network view, that causally links species richness and the other ecosystem components, is required to understand and predict climate impacts on the temporal stability of aquatic ecosystems.

When the wastewater volume exceeds the sewer pipe capacity during extreme rainfall events, untreated sewage discharges directly into rivers as combined sewer overflow (CSO). To compare the impacts of CSOs and stormwater on urban waterways, we assessed physicochemical water quality, the 16S rRNA gene-based bacterial community structure, and EcoPlate-based microbial functions during rainfall periods in an urban waterway before and after a stormwater storage pipe was commissioned. A temporal variation analysis showed that CSOs have significant impacts on microbial function and bacterial community structure, while their contributions to physicochemical parameters, bacterial abundance, and chlorophyll a were not confirmed. Heat map analysis showed that the impact of CSO on the waterway bacterial community structure was temporal and the bacterial community composition in CSO is distinct from that in sewers. Hierarchical clustering analysis revealed that the waterway physicochemical water qualities, bacterial community composition, and microbial community function were distinguishable from the upper reach of the river, rather than between CSO and stormwater. Changes in the relative abundance of tetracycline resistance (tet) genes—especially tet(M)—were observed after CSOs but did not coincide with changes in the microbial community composition, suggesting that the parameters affecting the microbial community composition and relative abundance of tet genes differ. After pipe implementation, however, stormwater did not contribute to the abundance of tet genes in the waterway. These results indicate that CSO-induced acute microbial disturbances in the urban waterway were alleviated by the implementation of a stormwater storage pipe and will support the efficiency of storage pipe operation for waterway management in urban areas.

The thermal deactivation of engine-aged Pd/CeO2–ZrO2 three-way catalysts was studied by chassis-dynamometer driving test cycles with cold start and in situ diffuse reflectance spectroscopy (DRS). T...

The redox dynamics of Pd catalysts under lean/rich perturbation conditions was analyzed by in situ time-resolved reflectance spectroscopy. The real-time redox of Pd/Al2O3 was monitored using the reflectance at 650 nm at every second under simulated exhausts (CO–C3H6–NO–O2), which were switched between air-to-fuel ratio of 14.1 (rich) and 15.0 (lean). Compared to the fast oxidation of metallic Pd (Pd0) upon rich-to-lean switching, the reduction of Pd oxide (Pd2+) upon reverse (lean-to-rich) switch started after a long induction period and proceeded slowly. Because the similar result was also observed for a Pd metal foil, the unequal redox rates under the lean/rich perturbation condition is characteristic of Pd. The temperature dependence of the redox rate demonstrated that the activation energy for the reduction of Pd oxide is greater than that of the Pd oxidation. The faster oxidation rate of Pd surface is considered as the primary reason for steep decrease of NO reduction efficiency in a slightly lean A/F region.

Viral infections are a major factor in diatom cell death. However, the effects of viruses on diatom dynamics remain unclear. Based on laboratory studies, it is hypothesized that virus-induced diatom mortality is dependent on the diatom growth rate. The present study aimed to elucidate the relationship between the diatom growth rate and virus-induced mortality using model systems of the marine planktonic diatom, Chaetoceros tenuissimus and its infectious viruses. We also examined the fate of diatom populations in a semi-continuous dilution culture system, in which host growth rates were controlled at 0.69, 2.08, and 3.47 day–1. Diatom populations gradually decreased following the viral inoculation of each culture system, and virus-induced mortality inversely correlated with the diatom growth rate. Furthermore, the viral burst size was slightly higher in lower growth rate cultures. These results suggested that the host physiological status related to the growth rate affected viral infection and proliferation. Diatom populations were not completely lysed or washed out in any of the dilution systems; they showed steady growth in the presence of infectious viruses. This may be partially explained by defective interference particles from viruses and cell debris. The present results indicate that diatoms in dilution environments maintain their populations, even under viral pressure. Moreover, diatom populations with a low growth rate may partially sustain higher growth populations through nutrient recycling following virus-induced cell death. The results of the present study provide insights into diatom dynamics in natural environments in the presence of infectious viruses.

The present study was a cross-sectional comparison of probabilistic structure in the distribution of pitching location among baseball pitchers of various age groups (25 elementary school (ES), 20 junior high school (JH), 15 high school (HS), and 18 college students (CL)). In the results, despite the general age-dependent variations in pitching precision, the difference was reflected not only in error 'size' but also in the 'shape' of error as it was shown by fitting 95% confidence ellipse to the two dimensional distribution of pitch location. While the precision measure as a reflection of trial-by-trial variability of release timing (major axis length of the ellipse) was constant, minor axis length of the ellipse as a reflection of variability in the pitching form of each participant demonstrated significant differences among the groups. In the ES group particularly, the trial-by-trial variability in the trajectory angle of the throwing arm was significantly correlated with the minor axis length; this correlation was far greater than those in older groups. The present study is the first to demonstrate the detailed structure of the variability of pitching location of baseball dependent on age.

How do skilled players change their motion patterns depending on motion effort? Pitchers commonly accelerate wrist and elbow joint rotations via proximal joint motions. Contrastingly, they show individually different pitching motions, such as in wind-up or follow-through. Despite the generality of the uniform and diverse features, effort-dependent effects on these features are unclear. Here, we reveal the effort dependence based on muscle activity data in natural three-dimensional pitching performed by skilled players. We extract motor modules and their effort dependence from the muscle activity data via tensor decomposition. Then, we reveal the unknown relations among motor modules, common features, unique features, and effort dependence. The current study clarifies that common features are obvious in distinguishing between low and high effort and that unique features are evident in differentiating high and highest efforts.

BackgroundInteractions among microorganisms affect the structure and function of microbial communities, potentially affecting ecosystem health and biogeochemical cycles. The functional traits mediating microbial interactions are known for several model organisms, but the prevalence of these traits across microbial diversity is unknown.ResultsWe developed a new genomic approach to systematically explore the occurrence of metabolic functions and specific interaction traits, and applied it to 473 sequenced genomes from marine bacteria. The bacteria could be divided into coherent genome functional clusters (GFCs), some of which are consistent with known bacterial ecotypes (e.g. within pico-Cyanobacteria and Vibrio taxa) while others suggest new ecological units (e.g. Marinobacter, Alteromonas and Pseudoalteromonas). Some traits important for microbial interactions, such as the production of and resistance towards antimicrobial compounds and the production of phytohormones, are widely distributed among the GFCs. Other traits, such as the production of siderophores and secretion systems, as well as the production and export of specific B vitamins, are less common. Linked Trait Clusters (LTCs) include traits that may have evolved together, for example chemotaxis, motility and adhesion are linked with regulatory systems involved in virulence and biofilm formation.ConclusionsOur results highlight specific GFCs, such as those comprising Alpha- and Gammaproteobacteria, as particularly poised to interact both synergistically and antagonistically with co-occurring bacteria and phytoplankton. Similar efficient processing of multidimensional microbial information will be increasingly essential for translating genomes into ecosystem understanding across biomes, and identifying the fundamental rules that govern community dynamics and assembly.

Microbial interactions shape the structure and function of microbial communities with profound consequences for biogeochemical cycles and ecosystem health. Yet, most interaction mechanisms are studied only in model systems and their prevalence is unknown. To systematically explore the functional and interaction potential of sequenced marine bacteria, we developed a new trait-based approach, and applied it to 473 complete genomes (248 genera), representing a significant fraction of marine microbial communities. We identified genome functional clusters (GFCs) which condense bacterial diversity into groups with potentially common ecology and life history. Most GFCs revealed unique combinations of interaction traits, some widely distributed (e.g., antimicrobial activity), others less common (e.g., production of siderophores and phytohormones, biosynthesis and export of specific B vitamins). Specific GFCs, comprising Alpha- and Gammaproteobacteria, are predicted to preferentially interact synergistically and/or antagonistically with bacteria and phytoplankton. Moreover, linked trait clusters (LTCs) identify traits that may have evolved together and point to specific modes of interactions. Our approach translates multidimensional genomic information into an atlas of marine bacteria and their ecosystem functions, relevant for understanding the fundamental rules that govern community assembly and dynamics.

This study explored the mechanical factors that determine accuracy of a baseball pitching. In particular, we focused on the mechanical parameters at ball release, referred to as release parameters. The aim was to understand which parameter has the most deterministic influence on pitch location by measuring the release parameters during actual pitching and developing a simulation that predicts the pitch location from given release parameters. By comparing the fluctuation of the simulated pitch location when varying each release parameter, it was found that the elevation pitching angle and speed significantly influenced the vertical pitch location, and the azimuth pitching angle significantly influenced the horizontal pitch location. Moreover, a regression model was obtained to predict the pitch location, and it became clear that the significant predictors for the vertical pitch location were the elevation pitching angle, the speed, and spin axis, and those for the horizontal pitch location were the azimuth pitching angle, the spin axis, and horizontal release point. Therefore, it was suggested that the parameter most affecting pitch location weas pitching angle. On the other hand, multiple regression analyses revealed that the relation between release parameters varied between pitchers. The result is expected to contribute to an understanding of the mechanisms underlying accurate ball control skill in baseball pitching.

Despite the consensus that warming will affect biodiversity, alter physicochemical environments, and disrupt biological interactions, the relative importance of these key processes and how they interact to determine overall ecosystem function is poorly understood. Here, we analyze long-term (16∼39 years) time series data from ten aquatic ecosystems and use convergent cross mapping (CCM) to quantify the hidden causal network linking species diversity, ecosystem function, and physicochemical factors. We observe that aquatic ecosystems subject to stronger warming exhibit decreased stability (larger fluctuations in phytoplankton biomass). We further show that this effect can be attributed to a weakening of stabilizing causal pathways between biodiversity, nutrient cycling, and phytoplankton biomass. Thus, rather than thinking in terms of separate factors, a more holistic view, that causally links biodiversity and the other ecosystem components, is required to understand and predict climate impacts on the temporal stability of aquatic ecosystems.

Fungal diseases threaten natural and man‐made ecosystems. Chytridiomycota (chytrids) infect a wide host range, including phytoplankton species that form the basis of aquatic food webs and produce roughly half of Earth's oxygen. However, blooms of large or toxic phytoplankton form trophic bottlenecks, as they are inedible to zooplankton. Chytrids infecting inedible phytoplankton provide a trophic link to zooplankton by producing edible zoospores of high nutritional quality. By grazing chytrid zoospores, zooplankton may induce a trophic cascade, as a decreased zoospore density will reduce new infections. Conversely, fewer infections will not produce enough zoospores to sustain long‐term zooplankton growth and reproduction. This intricate balance between zoospore density necessary for zooplankton energetic demands (growth/survival), and the loss in new infections (and thus new zoospores) because of grazing was tested empirically. To this end, we exposed a cyanobacterial host (Planktothrix rubescens) infected by a chytrid (Rizophydium megarrhizum) to a grazer density gradient (the rotifer Keratella cf. cochlearis). Rotifers survived and reproduced on a zoospore diet, but the Keratella population growth was limited by the amount of zoospores provided by chytrid infections, resulting in a situation where zooplankton survived but were restricted in their ability to control disease in the cyanobacterial host. We subsequently developed and parameterized a dynamical food‐chain model using an allometric relationship for clearance rate to assess theoretically the potential of different‐sized zooplankton groups to restrict disease in phytoplankton hosts. Our model suggests that smaller‐sized zooplankton may have a high potential to reduce chytrid infections on inedible phytoplankton. Together, our results point out the complexity of three‐way interactions between hosts, parasites, and grazers and highlight that trophic cascades are not always sustainable and may depend on the grazer's energetic demand.

This chapter provides a synthesis of major existing models and theories of microbial communities, with a focus on their often overlooked roles in the maintenance of biodiversity and the regulation of ecosystem processes. This chapter covers the topics from both terrestrial and aquatic ecosystems where microbes are one of the major players of biogeochemical cycling and also mediated interactions between other organisms such as plants. In terrestrial ecosystems, the competitive relationship between plants is largely modified by soil microbes with diverse functional groups (e.g. microbial decomposer, pathogenic, or mutualistic groups) so that microbe-mediated plant–soil interactions have the potential to revise the classical theory of competitive coexistence. In aquatic ecosystems, a microbial food web including bacteria, fungi, protozoa, and phages structures the whole carbon and nutrient cycle. One challenging aspect of modeling microbial community is how to deal with taxonomic and functional diversity of microbes. Major modeling frameworks with different levels of complexity and the comparison of their performance will be discussed. Finally, a new modeling direction integrating mathematical models with bioinformatics will be also proposed.

EcoPlate quantifies the ability of a microbial community to utilize 31 distinct carbon substrates, by monitoring color development of microplate wells during incubation. Well color patterns represent metabolic profiles. Previous studies typically used color patterns representing average values of three technical replicates on the final day of the incubation and did not consider substrate chemical diversity. However, color fluctuates during incubation and color varies between replicates, undermining statistical power to distinguish differences among samples in microbial functional composition and diversity. Therefore, we developed a protocol to improve statistical power with two approaches. First, we optimized data treatment for color development during incubation and technical replicates. Second, we incorporated chemical structural information for the 31 carbon substrates into the computation. Our framework implemented as the protocol in the R environment is able to compare the statistical power among different calculation methods. When we applied it to data from aquatic microcosm and forest soil systems, we observed substantial improvement in statistical power when we incorporated temporal patterns during incubation instead of using only endpoint data. Using maximum or minimum values of technical replicates also sometimes gave better results than averages. Incorporating chemical structural information based on fuzzy set theory could improve statistical power but only when relative color density information was considered; it was not seen when the pattern was first binarized into the presence or absence of metabolic activity. Finally, we discuss research directions to improve these approaches and offer some practical considerations for applying our methods to other datasets.

Our human-dominant world can be viewed as being built up in two parts, social and ecological systems, each consisting of multi-level organizations that interact in a complex manner. However, there are knowledge gaps among those interactions. In this paper, we focus on studies filling two types of gaps in the socioecological system, some of which are case studies in the East Asia region and others are discussed in a more general context. First, we address the gaps between different levels of organizations in ecological systems, namely, (1) the importance of plant trait plasticity in bridging evolution and ecology, (2) linking primary producer diversity and the dynamics of blue carbon in coastal ecosystems in the Asia–Pacific region, and (3) research direction of climate change biology to fill the gaps across evolution, community, and ecosystem. Also included is (4) the gap between ecological monitoring programs and theories, which also addresses the potential of citizen science. Second, we illustrate the gaps between ecological and social systems through ongoing development of an ecosystem management framework, i.e., ecosystem-based disaster risk reduction. Finally, we summarize the benefits of filling the gaps for ecologists and society.