Reconstructing large interaction networks from empirical time series data.

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.

Long-term warming destabilizes aquatic ecosystems through weakening biodiversity-mediated causal networks.

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.

Using food network unfolding to evaluate food-web complexity in terms of biodiversity: theory and applications.

Food-web complexity often hinders disentangling functionally relevant aspects of food-web structure and its relationships to biodiversity. Here, we present a theoretical framework to evaluate food-web complexity in terms of biodiversity. Food network unfolding is a theoretical method to transform a complex food web into a linear food chain based on ecosystem processes. Based on this method, we can define three biodiversity indices, horizontal diversity (DH ), vertical diversity (DV ) and range diversity (DR ), which are associated with the species diversity within each trophic level, diversity of trophic levels, and diversity in resource use, respectively. These indices are related to Shannon's diversity index (H'), where H' = DH  + DV  - DR . Application of the framework to three riverine macroinvertebrate communities revealed that D indices, calculated from biomass and stable isotope features, captured well the anthropogenic, seasonal, or other within-site changes in food-web structures that could not be captured with H' alone.

Integrating chytrid fungal parasites into plankton ecology: research gaps and needs.

Chytridiomycota, often referred to as chytrids, can be virulent parasites with the potential to inflict mass mortalities on hosts, causing e.g. changes in phytoplankton size distributions and succession, and the delay or suppression of bloom events. Molecular environmental surveys have revealed an unexpectedly large diversity of chytrids across a wide range of aquatic ecosystems worldwide. As a result, scientific interest towards fungal parasites of phytoplankton has been gaining momentum in the past few years. Yet, we still know little about the ecology of chytrids, their life cycles, phylogeny, host specificity and range. Information on the contribution of chytrids to trophic interactions, as well as co-evolutionary feedbacks of fungal parasitism on host populations is also limited. This paper synthesizes ideas stressing the multifaceted biological relevance of phytoplankton chytridiomycosis, resulting from discussions among an international team of chytrid researchers. It presents our view on the most pressing research needs for promoting the integration of chytrid fungi into aquatic ecology.

Infections of Wolbachia may destabilize mosquito population dynamics.

Recent efforts in controlling mosquito-borne diseases focus on biocontrol strategies that incapacitate pathogens inside mosquitoes by altering the mosquito's microbiome. A case in point is the introduction of Wolbachia into natural mosquito populations in order to eliminate Dengue virus. However, whether this strategy can successfully control vector-borne diseases is debated; particularly, how artificial infection affects population dynamics of hosts remains unclear. Here, we show that natural Wolbachia infections are associated with unstable mosquito population dynamics by contrasting Wolbachia-infected versus uninfected cage populations of the Asian tiger mosquito (Aedes albopictus). By analyzing weekly data of adult mosquito abundances, we found that the variability of the infected populations is significantly higher than that of the uninfected. The elevated population variability is explained by increased instability in dynamics, as quantified by system nonlinearity (i.e., state-dependence). In addition, predictability of infected populations is substantially lower. A mathematical model analysis suggests that Wolbachia may alter mosquito population dynamics by modifying larval competition of hosts. These results encourage examination for effects of artificial Wolbachia establishment on mosquito populations, because an enhancement of population variability with reduced predictability could pose challenges in management. Our findings have implications for application of microbiome alterations in biocontrol programs.

Vibronic coupling in the excited-states of carotenoids.

The ultrafast femtochemistry of carotenoids is governed by the interaction between electronic excited states, which has been explained by the relaxation dynamics within a few hundred femtoseconds from the lowest optically allowed excited state S2 to the optically dark state S1. Extending this picture, some additional dark states (3A(g)(-) and 1B(u)(-)) and their interaction with the S2 state have also been suggested to play a major role in the ultrafast deactivation of carotenoids and their properties. Here, we investigate the interaction between such dark and bright electronic excited states of open chain carotenoids, particularly its dependence on the number of conjugated double bonds (N). We focus on the ultrafast wave packet motion on the excited potential surface, which is modified by the interaction between bright and dark electronic states. Such a coupling between electronic states leads to a shift of the vibrational frequency during the excited-state evolution. In this regard, pump-degenerate four-wave mixing (pump-DFWM) is applied to a series of carotenoids with different numbers of conjugated double bonds N = 9, 10, 11 and 13 (neurosporene, spheroidene, lycopene and spirilloxanthin, respectively). Moreover, we demonstrate in a closed-chain carotenoid (lutein) that the coupling strength and therefore the vibrational shift can be tailored by changing the energy degeneracy between the 1B(u)(+) and 1B(u)(-) states via solvent interaction.

The soil microbial community predicts the importance of plant traits in plant-soil feedback.

Reciprocal interaction between plant and soil (plant-soil feedback, PSF) can determine plant community structure. Understanding which traits control interspecific variation of PSF strength is crucial for plant ecology. Studies have highlighted either plant-mediated nutrient cycling (litter-mediated PSF) or plant-microbe interaction (microbial-mediated PSF) as important PSF mechanisms, each attributing PSF variation to different traits. However, this separation neglects the complex indirect interactions between the two mechanisms. We developed a model coupling litter- and microbial-mediated PSFs to identify the relative importance of traits in controlling PSF strength, and its dependency on the composition of root-associated microbes (i.e. pathogens and/or mycorrhizal fungi). Results showed that although plant carbon: nitrogen (C : N) ratio and microbial nutrient acquisition traits were consistently important, the importance of litter decomposability varied. Litter decomposability was not a major PSF determinant when pathogens are present. However, its importance increased with the relative abundance of mycorrhizal fungi as nutrient released from the mycorrhizal-enhanced litter production to the nutrient-depleted soils result in synergistic increase of soil nutrient and mycorrhizal abundance. Data compiled from empirical studies also supported our predictions. We propose that the importance of litter decomposability depends on the composition of root-associated microbes. Our results provide new perspectives in plant invasion and trait-based ecology.

Fe K-Edge X-ray Absorption Fine Structure Determination of γ-Al2 O3 -Supported Iron-Oxide Species.

The structure of FeOx species supported on γ-Al2 O3 was investigated by using Fe K-edge X-ray absorption fine structure (XAFS) and X-ray diffraction (XRD) measurements. The samples were prepared through the impregnation of iron nitrate on Al2 O3 and co-gelation of aluminum and iron sulfates. The dependence of the XRD patterns on Fe loading revealed the formation of α-Fe2 O3 particles at an Fe loading of above 10 wt %, whereas the formation of iron-oxide crystals was not observed at Fe loadings of less than 9.0 wt %. The Fe K-edge XAFS was characterized by a clear pre-edge peak, which indicated that the FeO coordination structure deviates from central symmetry and that the degree of FeOFe bond formation is significantly lower than that in bulk samples at low Fe loading (<9.0 wt %). Fe K-edge extended XAFS oscillations of the samples with low Fe loadings were explained by assuming an isolated iron-oxide monomer on the γ-Al2 O3 surface.

Biodiversity and multifunctionality in a microbial community: a novel theoretical approach to quantify functional redundancy.

Ecosystems have a limited buffering capacity of multiple ecosystem functions against biodiversity loss (i.e. low multifunctional redundancy). We developed a novel theoretical approach to evaluate multifunctional redundancy in a microbial community using the microbial genome database (MBGD) for comparative analysis. In order to fully implement functional information, we defined orthologue richness in a community, each of which is a functionally conservative evolutionary unit in genomes, as an index of community multifunctionality (MF). We constructed a graph of expected orthologue richness in a community (MF) as a function of species richness (SR), fit the power function to SR (i.e. MF = cSR(a)), and interpreted the higher exponent a as the lower multifunctional redundancy. Through a microcosm experiment, we confirmed that MF defined by orthologue richness could predict the actual multiple functions. We simulated random and non-random community assemblages using full genomic data of 478 prokaryotic species in the MBGD, and determined that the exponent in microbial communities ranged from 0.55 to 0.75. This exponent range provided a quantitative estimate that a 6.6-8.9% loss limit in SR occurred in a microbial community for an MF reduction no greater than 5%, suggesting a non-negligible initial loss effect of microbial diversity on MF.

Linking secondary structure of individual size distribution with nonlinear size-trophic level relationship in food webs.

Existing individual size distribution (ISD) theories assume that the trophic level (TL) of an organism varies as a linear function of its log-transformed body size. This assumption predicts a power-law distribution of the ISD, i.e., a linear relationship between size and abundance in log space. However, the secondary structure of ISD (nonlinear dome shape structures deviating from a power-law distribution) is often observed. We propose a model that extends the metabolic theory to link the secondary structure of ISD to the nonlinear size-TL relationship. This model is tested with empirical data collected from a subtropical reservoir. The empirical ISD and size-TL relationships were constructed by FlowCAM imaging analysis and stable isotope analyses, respectively. Our results demonstrate that the secondary structure of ISD can be predicted from the nonlinear function of size-TL relationship and vice versa. Moreover, these secondary structures arise due to (1) zooplankton omnivory and (2) the trophic interactions within microbial food webs.

Functional diversity of microbial decomposers facilitates plant coexistence in a plant-microbe-soil feedback model.

Theory and empirical evidence suggest that plant-soil feedback (PSF) determines the structure of a plant community and nutrient cycling in terrestrial ecosystems. The plant community alters the nutrient pool size in soil by affecting litter decomposition processes, which in turn shapes the plant community, forming a PSF system. However, the role of microbial decomposers in PSF function is often overlooked, and it remains unclear whether decomposers reinforce or weaken litter-mediated plant control over nutrient cycling. Here, we present a theoretical model incorporating the functional diversity of both plants and microbial decomposers. Two fundamental microbial processes are included that control nutrient mineralization from plant litter: (i) assimilation of mineralized nutrient into the microbial biomass (microbial immobilization), and (ii) release of the microbial nutrients into the inorganic nutrient pool (net mineralization). With this model, we show that microbial diversity may act as a buffer that weakens plant control over the soil nutrient pool, reversing the sign of PSF from positive to negative and facilitating plant coexistence. This is explained by the decoupling of litter decomposability and nutrient pool size arising from a flexible change in the microbial community composition and decomposition processes in response to variations in plant litter decomposability. Our results suggest that the microbial community plays a central role in PSF function and the plant community structure. Furthermore, the results strongly imply that the plant-centered view of nutrient cycling should be changed to a plant-microbe-soil feedback system, by incorporating the community ecology of microbial decomposers and their functional diversity.

Microbial community composition and function in an urban waterway with combined sewer overflows before and after implementation of a stormwater storage pipe.

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.

Plant volatiles and priority effects interactively determined initial community assembly of arthropods on multiple willow species.

Plant traits, which are often species specific, can serve as environmental filtering for community assembly on plants. At the same time, the species identity of the initially colonizing arthropods would vary between plant individuals, which would subsequently influence colonizing arthropods and community development in the later stages. However, it remains unclear whether interindividual divergence due to priority effects is equally important as plant trait-specific environmental filtering in the initial stages. In this study, we propose that plant volatile organic compounds (PVOCs) may play a crucial role as an environmental filter in the initial stages of community assembly, which can prevent the community assembly process from being purely stochastic. To test this hypothesis, we conducted short term but highly frequent monitoring (19 observations over 9 days) of arthropod community assembly on intact individuals of six willow species in a common garden. PVOC compositions were analyzed before starting the experiment and compared with arthropod compositions occurring on Days 1-2 of the experiment (earliest colonizer community) and those occurring on Days 8-9 of the experiment (subsequent colonizer community). Unintentionally, deer herbivory also occurred at night of Day 2. Distance-based statistics demonstrated that PVOC compositions were plant species specific, but neither the earliest colonizer nor the subsequent colonizer community composition could be explained by plant species identity. Rather, Procrustes analysis showed that both the PVOC composition and that of the earliest colonizer community can be used to explain the subsequent colonizer community. In addition, the linkage between PVOCs and the subsequent colonizer community was stronger on individuals with deer herbivory. These findings indicate that PVOCs have widespread effects on initial community assembly, as well as priority effects brought on by stochastic immigration, and that plant species identity only has weak and indirect effects on the actual composition of the community.

Non-destructive collection and metabarcoding of arthropod environmental DNA remained on a terrestrial plant.

Reliable survey of arthropods is a crucial for their conservation, community ecology, and pest control on terrestrial plants. However, efficient and comprehensive surveys are hindered by challenges in collecting arthropods and identifying especially small species. To address this issue, we developed a non-destructive environmental DNA (eDNA) collection method termed "plant flow collection" to apply eDNA metabarcoding to terrestrial arthropods. This involves spraying distilled or tap water, or using rainfall, which eventually flows over the surface of the plant, and is collected in a container that is set at the plant base. DNA is extracted from collected water and a DNA barcode region of cytochrome c oxidase subunit I (COI) gene is amplified and sequenced using a high-throughput Illumina Miseq platform. We identified more than 64 taxonomic groups of arthropods at the family level, of which 7 were visually observed or artificially introduced species, whereas the other 57 groups of arthropods, including 22 species, were not observed in the visual survey. These results show that the developed method is possible to detect the arthropod eDNA remained on plants although our sample size was small and the sequence size was unevenly distributed among the three water types tested.

A comparative whole-genome approach identifies bacterial traits for marine microbial interactions.

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 trait-based approach, and applied it to 473 complete genomes (248 genera), representing a substantial fraction of marine microbial communities. We identified genome functional clusters (GFCs) which group bacterial taxa with common ecology and life history. Most GFCs revealed unique combinations of interaction traits, including the production of siderophores (10% of genomes), phytohormones (3-8%) and different B vitamins (57-70%). Specific GFCs, comprising Alpha- and Gammaproteobacteria, displayed more interaction traits than expected by chance, and are thus predicted to preferentially interact synergistically and/or antagonistically with bacteria and phytoplankton. Linked trait clusters (LTCs) identify traits that may have evolved to act together (e.g., secretion systems, nitrogen metabolism regulation and B vitamin transporters), providing testable hypotheses for complex mechanisms of microbial interactions. Our approach translates multidimensional genomic information into an atlas of marine bacteria and their putative functions, relevant for understanding the fundamental rules that govern community assembly and dynamics.

New index of functional specificity to predict the redundancy of ecosystem functions in microbial communities.

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.

Causal networks of phytoplankton diversity and biomass are modulated by environmental context.

Untangling causal links and feedbacks among biodiversity, ecosystem functioning, and environmental factors is challenging due to their complex and context-dependent interactions (e.g., a nutrient-dependent relationship between diversity and biomass). Consequently, studies that only consider separable, unidirectional effects can produce divergent conclusions and equivocal ecological implications. To address this complexity, we use empirical dynamic modeling to assemble causal networks for 19 natural aquatic ecosystems (N24◦~N58◦) and quantified strengths of feedbacks among phytoplankton diversity, phytoplankton biomass, and environmental factors. Through a cross-system comparison, we identify macroecological patterns; in more diverse, oligotrophic ecosystems, biodiversity effects are more important than environmental effects (nutrients and temperature) as drivers of biomass. Furthermore, feedback strengths vary with productivity. In warm, productive systems, strong nitrate-mediated feedbacks usually prevail, whereas there are strong, phosphate-mediated feedbacks in cold, less productive systems. Our findings, based on recovered feedbacks, highlight the importance of a network view in future ecosystem management.

Differing growth responses of major phylogenetic groups of marine bacteria to natural phytoplankton blooms in the western North Pacific Ocean.

Growth and productivity of phytoplankton substantially change organic matter characteristics, which affect bacterial abundance, productivity, and community structure in aquatic ecosystems. We analyzed bacterial community structures and measured activities inside and outside phytoplankton blooms in the western North Pacific Ocean by using bromodeoxyuridine immunocytochemistry and fluorescence in situ hybridization (BIC-FISH). Roseobacter/Rhodobacter, SAR11, Betaproteobacteria, Alteromonas, SAR86, and Bacteroidetes responded differently to changes in organic matter supply. Roseobacter/Rhodobacter bacteria remained widespread, active, and proliferating despite large fluctuations in organic matter and chlorophyll a (Chl-a) concentrations. The relative contribution of Bacteroidetes to total bacterial production was consistently high. Furthermore, we documented the unexpectedly large contribution of Alteromonas to total bacterial production in the bloom. Bacterial abundance, productivity, and growth potential (the proportion of growing cells in a population) were significantly correlated with Chl-a and particulate organic carbon concentrations. Canonical correspondence analysis showed that organic matter supply was critical for determining bacterial community structures. The growth potential of each bacterial group as a function of Chl-a concentration showed a bell-shaped distribution, indicating an optimal organic matter concentration to promote growth. The growth of Alteromonas and Betaproteobacteria was especially strongly correlated with organic matter supply. These data elucidate the distinctive ecological role of major bacterial taxa in organic matter cycling during open ocean phytoplankton blooms.

Growth Rate-dependent Cell Death of Diatoms due to Viral Infection and Their Subsequent Coexistence in a Semi-continuous Culture System.

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.

Effort-dependent effects on uniform and diverse muscle activity features in skilled pitching.

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.