Electrical integrity and week-long oscillation in fungal mycelia.

The electrical potential of the mycelia of a cord-forming wood decay fungus, Pholiota brunnescens, was monitored for over 100 days on a plain agar plate during the colonization onto a wood bait. Causality analyses of the electrical potential at different locations of the mycelium revealed a clear and stable causal relationship with the directional flow of the electrical potential from the hyphae at the bait location to other parts of the mycelium. However, this causality disappeared after 60 days of incubation, coinciding with the onset of slow electrical oscillation at the bait location, which occurred over one week per oscillation cycle. We speculated that the hyphae that initially colonized the bait may act as a temporary activity center, which generates electrical signals to other parts of the mycelium, thereby facilitating the colonization of the entire mycelial body to the bait. The week-long electrical oscillation represents the longest oscillation period ever recorded in fungi and warrants further investigation to elucidate its function and stability in response to environmental stimuli.

Synthetic model ecosystem of 12 cryopreservable microbial species allowing for a noninvasive approach.

Simultaneous understanding of both population and ecosystem dynamics is crucial in an era marked by the degradation of ecosystem services. Experimental ecosystems are a powerful tool for understanding these dynamics; however, they often face technical challenges, typically falling into two categories: "complex but with limited replicability microcosms" and "highly replicable but overly simplistic microcosms." Herein, we present a high-throughput synthetic microcosm system comprising 12 functionally and phylogenetically diverse microbial species. These species are axenically culturable, cryopreservable, and can be measured noninvasively via microscopy, aided by machine learning. This system includes prokaryotic and eukaryotic producers and decomposers, and eukaryotic consumers to ensure functional redundancy. Our model system exhibited key features of a complex ecosystem: (i) various positive and negative interspecific interactions, (ii) higher-order interactions beyond two-species dynamics, (iii) probabilistic dynamics leading to divergent outcomes, and (iv) stable nonlinear transitions. We identified several conditions under which at least one species from each of the three functional groups-producers, consumers, and decomposers-and one functionally redundant species, persisted for over six months. These conditions set the stage for detailed investigations in the future. Given its designability and experimental replicability, our model ecosystem offers a promising platform for deeper insights integrating both population and ecosystem dynamics.

Dynamics-based characterization and classification of biodiversity indicators.

Various biodiversity indicators, such as species richness, total abundance, and species diversity indices, have been developed to capture the state of ecological communities over space and time. As biodiversity is a multifaceted concept, it is important to understand the dimension of biodiversity reflected by each indicator for successful conservation and management. Here we utilized the responsiveness of biodiversity indicators' dynamics to environmental changes (i.e., environmental responsiveness) as a signature of the dimension of biodiversity. We present a method for characterizing and classifying biodiversity indicators according to environmental responsiveness and apply the methodology to monitoring data for a marine fish community under intermittent anthropogenic warm water discharge. Our analysis showed that 10 biodiversity indicators can be classified into three super-groups based on the dimension of biodiversity that is reflected. Group I (species richness and community mean of latitudinal center of distribution (cCOD)) showed the greatest robustness to temperature changes; Group II (species diversity and total abundance) showed an abrupt change in the middle of the monitoring period, presumably due to a change in temperature; Group III (species evenness) exhibited the highest sensitivity to environmental changes, including temperature. These results had several ecological implications. First, the responsiveness of species diversity and species evenness to temperature changes might be related to changes in the species abundance distribution. Second, the similar environmental responsiveness of species richness and cCOD implies that fish migration from lower latitudes is a major driver of species compositional changes. The study methodology may be useful in selecting appropriate indicators for efficient biodiversity monitoring.

Temperature sensitivity of the interspecific interaction strength of coastal marine fish communities.

The effects of temperature on interaction strengths are important for understanding and forecasting how global climate change impacts marine ecosystems; however, tracking and quantifying interactions of marine fish species are practically difficult especially under field conditions, and thus, how temperature influences their interaction strengths under field conditions remains poorly understood. We herein performed quantitative fish environmental DNA (eDNA) metabarcoding on 550 seawater samples that were collected twice a month from 11 coastal sites for 2 years in the Boso Peninsula, Japan, and analyzed eDNA monitoring data using nonlinear time series analytical tools. We detected fish-fish interactions as information flow between eDNA time series, reconstructed interaction networks for the top 50 frequently detected species, and quantified pairwise, fluctuating interaction strengths. Although there was a large variation, water temperature influenced fish-fish interaction strengths. The impact of water temperature on interspecific interaction strengths varied among fish species, suggesting that fish species identity influences the temperature effects on interactions. For example, interaction strengths that Halichoeres tenuispinis and Microcanthus strigatus received strongly increased with water temperature, while those of Engraulis japonicus and Girella punctata decreased with water temperature. An increase in water temperature induced by global climate change may change fish interactions in a complex way, which consequently influences marine community dynamics and stability. Our research demonstrates a practical research framework to study the effects of environmental variables on interaction strengths of marine communities in nature, which would contribute to understanding and predicting natural marine ecosystem dynamics.

The world's oceans are home to tens of thousands of fish species, many of which live in nutrient-rich coastal waters. Different species living in a particular environment interact with each other in many ways. For example, a predatory fish may prey on some species of small fish but avoid feeding on others that help it by removing parasites from its skin. Rising ocean temperatures caused by global climate change could affect how different fish species interact with one another and, as a result, impact their communities. One of the first steps to understanding how fish interact with each other in nature typically requires researchers to count the number of different species present and observe how they behave, which is time-consuming and labor-intensive. An alternative is to use an emerging technique in which researchers extract DNA from water, soil or air ­ known as environmental DNA ­ and analyze it to identify the species present and estimate their numbers. Ushio et al. analyzed hundreds of samples of seawater that had been collected over a two-year period from the Boso Peninsula in Japan. Statistical methods were used to quantify how strongly fish species interact with each other and determine whether the temperature of the water influenced how different species of fish interacted over time. The findings showed that water temperature had a significant but complex effect on how strongly pairs of fish species interacted, with both positive and negative effects depending on the conditions. The impact of water temperature on the strength of the interactions varied between species, for example, Japanese anchovy and largescale blackfish interacted less strongly with other fish species in warmer water, whereas the Stripey and a species of wrasse interacted with other fish species more strongly. The findings provide new insights into how water temperature affects the communities of fish living in coastal areas. Alongside complementing existing knowledge in the field, refining the research framework used in this work will benefit those working in fishery science by providing valuable insights into how natural and commercially important fish species respond to climate change.

Reconstruction of a Soil Microbial Network Induced by Stress Temperature.

The microbial community is viewed as a network of diverse microorganisms connected by various interspecific interactions. While the stress gradient hypothesis (SGH) predicts that positive interactions are favored in more stressful environments, the prediction has been less explored in complex microbial communities due to the challenges of identifying interactions. Here, by applying a nonlinear time series analysis to the amplicon-based diversity time series data of the soil microbiota cultured under less stressful (30°C) or more stressful (37°C) temperature conditions, we show how the microbial network responds to temperature stress. While the genera that persisted only under the less stressful condition showed fewer positive effects, the genera that appeared only under the more stressful condition received more positive effects, in agreement with SGH. However, temperature difference also induced reconstruction of the community network, leading to an increased proportion of negative interactions at the whole-community level. The anti-SGH pattern can be explained by the stronger competition caused by increased metabolic rate and population densities. IMPORTANCE By combining amplicon-based diversity survey with recently developed nonlinear analytical tools, we successfully determined the interaction networks of more than 150 natural soil microbial genera under less or more temperature stress and explored the applicability of the stress gradient hypothesis to soil microbiota, shedding new light on the well-known hypothesis.

Diagnosing underdetermination in stable isotope mixing models.

Stable isotope mixing models (SIMMs) provide a powerful methodology for quantifying relative contributions of several sources to a mixture. They are widely used in the fields of ecology, geology, and archaeology. Although SIMMs have been rapidly evolved in the Bayesian framework, the underdetermination of mixing space remains problematic, i.e., the estimated relative contributions are incompletely identifiable. Here we propose a statistical method to quantitatively diagnose underdetermination in Bayesian SIMMs, and demonstrate the applications of our method (named ß-dependent SIMM) using two motivated examples. Using a simulation example, we showed that the proposed method can rigorously quantify the expected underdetermination (i.e., intervals of ß-dependent posterior) of relative contributions. Moreover, the application to the published field data highlighted two problematic aspects of the underdetermination: 1) ordinary SIMMs was difficult to quantify underdetermination of each source, and 2) the marginal posterior median was not necessarily consistent with the joint posterior peak in the case of underdetermination. Our study theoretically and numerically confirmed that ß-dependent SIMMs provide a useful diagnostic tool for the underdetermined mixing problem. In addition to ordinary SIMMs, we recommend reporting the results of ß-dependent SIMMs to obtain a biologically feasible and sound interpretation from stable isotope data.

Novel robust time series analysis for long-term and short-term prediction.

Nonlinear phenomena are universal in ecology. However, their inference and prediction are generally difficult because of autocorrelation and outliers. A traditional least squares method for parameter estimation is capable of improving short-term prediction by estimating autocorrelation, whereas it has weakness to outliers and consequently worse long-term prediction. In contrast, a traditional robust regression approach, such as the least absolute deviations method, alleviates the influence of outliers and has potentially better long-term prediction, whereas it makes accurately estimating autocorrelation difficult and possibly leads to worse short-term prediction. We propose a new robust regression approach that estimates autocorrelation accurately and reduces the influence of outliers. We then compare the new method with the conventional least squares and least absolute deviations methods by using simulated data and real ecological data. Simulations and analysis of real data demonstrate that the new method generally has better long-term and short-term prediction ability for nonlinear estimation problems using spawner-recruitment data. The new method provides nearly unbiased autocorrelation even for highly contaminated simulated data with extreme outliers, whereas other methods fail to estimate autocorrelation accurately.

Estimating fish population abundance by integrating quantitative data on environmental DNA and hydrodynamic modelling.

Molecular analysis of DNA left in the environment, known as environmental DNA (eDNA), has proven to be a powerful and cost-effective approach to infer occurrence of species. Nonetheless, relating measurements of eDNA concentration to population abundance remains difficult because detailed knowledge on the processes that govern spatial and temporal distribution of eDNA should be integrated to reconstruct the underlying distribution and abundance of a target species. In this study, we propose a general framework of abundance estimation for aquatic systems on the basis of spatially replicated measurements of eDNA. The proposed method explicitly accounts for production, transport and degradation of eDNA by utilizing numerical hydrodynamic models that can simulate the distribution of eDNA concentrations within an aquatic area. It turns out that, under certain assumptions, population abundance can be estimated via a Bayesian inference of a generalized linear model. Application to a Japanese jack mackerel (Trachurus japonicus) population in Maizuru Bay revealed that the proposed method gives an estimate of population abundance comparable to that of a quantitative echo sounder method. Furthermore, the method successfully identified a source of exogenous input of eDNA (a fish market), which may render a quantitative application of eDNA difficult to interpret unless its effect is taken into account. These findings indicate the ability of eDNA to reliably reflect population abundance of aquatic macroorganisms; when the "ecology of eDNA" is adequately accounted for, population abundance can be quantified on the basis of measurements of eDNA concentration.

Tracking long-distance migration of marine fishes using compound-specific stable isotope analysis of amino acids.

The long-distance migrations by marine fishes are difficult to track by field observation. Here, we propose a new method to track such migrations using stable nitrogen isotopic composition at the base of the food web (δ15 NBase ), which can be estimated by using compound-specific isotope analysis. δ15 NBase exclusively reflects the δ15 N of nitrate in the ocean at a regional scale and is not affected by the trophic position of sampled organisms. In other words, δ15 NBase allows for direct comparison of isotope ratios between proxy organisms of the isoscape and the target migratory animal. We initially constructed a δ15 NBase isoscape in the northern North Pacific by bulk and compound-specific isotope analyses of copepods (n = 360 and 24, respectively), and then we determined retrospective δ15 NBase values of spawning chum salmon (Oncorhynchus keta) from their vertebral centra (10 sections from each of two salmon). We then estimated the migration routes of chum salmon during their skeletal growth by using a state-space model. Our isotope tracking method successfully reproduced a known chum salmon migration route between the Okhotsk and Bering seas, and our findings suggest the presence of a new migration route to the Bering Sea Shelf during a later growth stage.

Estimating range expansion of wildlife in heterogeneous landscapes: A spatially explicit state-space matrix model coupled with an improved numerical integration technique.

Dispersal as well as population growth is a key demographic process that determines population dynamics. However, determining the effects of environmental covariates on dispersal from spatial-temporal abundance proxy data is challenging owing to the complexity of model specification for directional dispersal permeability and the extremely high computational loads for numerical integration. In this paper, we present a case study estimating how environmental covariates affect the dispersal of Japanese sika deer by developing a spatially explicit state-space matrix model coupled with an improved numerical integration technique (Markov chain Monte Carlo with particle filters). In particular, we explored the environmental drivers of inhomogeneous range expansion, characteristic of animals with short dispersal. Our model framework successfully reproduced the complex population dynamics of sika deer, including rapid changes in densely populated areas and distribution fronts within a decade. Furthermore, our results revealed that the inhomogeneous range expansion of sika deer seemed to be primarily caused by the dispersal process (i.e., movement barriers in fragmented forests) rather than population growth. Our state-space matrix model enables the inference of population dynamics for a broad range of organisms, even those with low dispersal ability, in heterogeneous landscapes, and could address many pressing issues in conservation biology and ecosystem management.

Disentangling the drivers of invasion spread in a vector-borne tree disease.

Pine wilt disease (PWD) invaded southern Japan in the early 1900s and has gradually expanded its range to northern Honshu (Japanese mainland). The disease is caused by a pathogenic North American nematode, which is transmitted by native pine sawyer beetles. Recently, the disease has invaded other portions of East Asia and Europe where extensive mortality of host pines is anticipated to resemble historical patterns seen in Japan. There is a critical need to identify the main drivers of PWD invasion spread so as to predict the future spread and evaluate containment strategies in newly invaded world regions. But the coupling of pathogen and vector population dynamics introduces considerable complexity that is important for understanding this and other plant disease invasions. In this study, we analysed historical (1980-2011) records of PWD infection and vector abundance, which were spatially extensive but recorded at coarse categorical levels (none, low and high) across 403 municipalities in northern Honshu. We employed a multistate occupancy model that accounted both for demographic stochasticity and observation errors in categorical data. Analysis revealed that sparse sawyer populations had lower probabilities of transition to high abundance than did more abundant populations even when regional abundance stayed the same, suggesting the existence of positive density dependence, that is an Allee effect, in sawyer dynamics. Climatic conditions (average accumulated degree days) substantially limited invasion spread in northern regions, but this climatic influence on sawyer dynamics was generally weaker than the Allee effect. Our results suggest that tactics (eg sanitation logging of infected pines) which strengthen Allee effects in sawyer dynamics may be effective strategies for slowing the spread of PWD.

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.

[A Case of Renal Cell Carcinoma Growing into the Renal Pelvis with a Fibrin Cap in the Ureter and Bladder].

We present a case of renal cell carcinoma growing into the renal pelvis with a fibrin cap in the ureter and bladder. A 66-year-old man presented to our hospital with anemia and gross hematuria. Computed tomography showed a large left renal tumor and space-occupying lesions in the left renal pelvis and ureter. Cystoscopy showed a 2 cm-restiform mass protruding from the left ureteral orifice. We performed open left nephroureterectomy, and there was a 3 cm white mass with a smooth surface in the bladder. Pathological examination of the resected mass revealed clear cell carcinoma with urinary collecting system invasion and fibrin cap in the ureter and bladder. As a result, it would have been difficult to make the diagnossis of renal cell carcinoma preoperatively if we had performed biopsy of the mass in the bladder or ureter. The patient was diagnosed as having lung metastases 5 months after surgery. Urinary collecting system invasion has been considered an independent prognostic factor in pT3 renal cell carcinoma.

[Segmental Testicular Infarction in a Patient with Epididymitis].

Testicular nodules are occasionally palpable in patients with acute epididymitis. In these patients, we need to rule out testicular tumors. Advancement in imaging technology such as doppler ultrasound or magnetic resonance imaging (MRI) has enabled us to distinguish segmental testicular infarction from testicular tumor and refrain from orchiectomy. However, careful diagnosis is necessary and we should not hesitate to perform orchiectomy in case testicular tumor is not ruled out. Since segmental testicular infarction in the presence of epididymitis may occur, we should consider the disease in a case of hard testis in the presence of epididymitis. Herein we report a rare case of segmental testicular infarction after epididymitis, in which testicular tumor was difficult to rule out.

The forecasting of menstruation based on a state-space modeling of basal body temperature time series.

Women's basal body temperature (BBT) shows a periodic pattern that associates with menstrual cycle. Although this fact suggests a possibility that daily BBT time series can be useful for estimating the underlying phase state as well as for predicting the length of current menstrual cycle, little attention has been paid to model BBT time series. In this study, we propose a state-space model that involves the menstrual phase as a latent state variable to explain the daily fluctuation of BBT and the menstruation cycle length. Conditional distributions of the phase are obtained by using sequential Bayesian filtering techniques. A predictive distribution of the next menstruation day can be derived based on this conditional distribution and the model, leading to a novel statistical framework that provides a sequentially updated prediction for upcoming menstruation day. We applied this framework to a real data set of women's BBT and menstruation days and compared prediction accuracy of the proposed method with that of previous methods, showing that the proposed method generally provides a better prediction. Because BBT can be obtained with relatively small cost and effort, the proposed method can be useful for women's health management. Potential extensions of this framework as the basis of modeling and predicting events that are associated with the menstrual cycles are discussed. © 2017 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Dietary compositions and their seasonal shifts in Japanese resident birds, estimated from the analysis of volunteer monitoring data.

Determining the composition of a bird's diet and its seasonal shifts are fundamental for understanding the ecology and ecological functions of a species. Various methods have been used to estimate the dietary compositions of birds, which have their own advantages and disadvantages. In this study, we examined the possibility of using long-term volunteer monitoring data as the source of dietary information for 15 resident bird species in Kanagawa Prefecture, Japan. The data were collected from field observations reported by volunteers of regional naturalist groups. Based on these monitoring data, we calculated the monthly dietary composition of each bird species directly, and we also estimated unidentified items within the reported foraging episodes using Bayesian models that contained additional information regarding foraging locations. Next, to examine the validity of the estimated dietary compositions, we compared them with the dietary information for focal birds based on stomach analysis methods, collected from past literatures. The dietary trends estimated from the monitoring data were largely consistent with the general food habits determined from the previous studies of focal birds. Thus, the estimates based on the volunteer monitoring data successfully detected noticeable seasonal shifts in many of the birds from plant materials to animal diets during spring-summer. Comparisons with stomach analysis data supported the qualitative validity of the monitoring-based dietary information and the effectiveness of the Bayesian models for improving the estimates. This comparison suggests that one advantage of using monitoring data is its ability to detect dietary items such as fleshy fruits, flower nectar, and vertebrates. These results emphasize the potential importance of observation data collecting and mining by citizens, especially free descriptive observation data, for use in bird ecology studies.

Habitat connectivity and resident shared predators determine the impact of invasive bullfrogs on native frogs in farm ponds.

Habitat connectivity is considered to have an important role on the persistence of populations in the face of habitat fragmentation, in particular, for species with conservation concern. However, it can also impose indirect negative effects on native species through the spread of invasive species. Here, we investigated direct and indirect effects of habitat connectivity on populations of invasive bullfrogs and native wrinkled frogs and how these effects are modified by the presence of common carp, a resident shared predator, in a farm pond system in Japan. The distribution pattern analysis using a hierarchical Bayesian modelling indicated that bullfrogs had negative effects on wrinkled frogs, and that these negative effects were enhanced with increasing habitat connectivity owing to the metapopulation structure of bullfrogs. The analysis also suggested that common carp mitigated these impacts, presumably owing to a top-down trophic cascade through preferential predation on bullfrog tadpoles. These presumed interspecific interactions were supported by evidence from laboratory experiments, i.e. predation by carp was more intense on bullfrog tadpoles than on wrinkled frog tadpoles owing to the difference in refuge use. Our results indicate that metacommunity perspectives could provide useful insights for establishing effective management strategies of invasive species living in patchy habitats.

[Additional administration of dutasteride in patients with benign prostatic hyperplasia who did not respond sufficiently to α1-adrenoceptor antagonist : investigation of clinical factors affecting the therapeutic effect of dutasteride].

We performed additional administration of dutasteride in patients who did not respond sufficiently to α1-adrenoceptor antagonist treatment for lower urinary tract symptoms (LUTS) associated with benign prostatic hyperplasia (BPH) (LUTS/BPH). Among 76 registered patients, efficacy was analyzed in 58 patients. International Prostate Symptom Score (IPSS), subscores for voiding and storage symptoms and quality of life (QOL) on the IPSS, and Overactive Bladder Symptom Score (OABSS) were all significantly improved from the third month of administration compared to the time of initiating additional administration of dutasteride. Additional administration of dutasteride also significantly reduced prostate volume, and residual urine with the exception of the sixth month after administration. Age at initiation of administration and voiding symptom subscore on the IPSS were clinical factors affecting the therapeutic effects of dutasteride. The rate of improvement with treatment decreased with increasing age at initiation of dutasteride administration, and increased as voiding symptom subscore on the IPSS increased. Therefore, additional administration of dutasteride appears useful for cases of LUTS/BPH in which a sufficient response is not achieved with α1-adrenoceptor antagonist treatment. Because patients who have severe voiding symptoms or begin dutasteride at an early age may be expected to respond particularly well to dutasteride in terms of clinical efficacy, they were considered to be suitable targets for additional administration.

IsoWeb: a bayesian isotope mixing model for diet analysis of the whole food web.

Quantitative description of food webs provides fundamental information for the understanding of population, community, and ecosystem dynamics. Recently, stable isotope mixing models have been widely used to quantify dietary proportions of different food resources to a focal consumer. Here we propose a novel mixing model (IsoWeb) that estimates diet proportions of all consumers in a food web based on stable isotope information. IsoWeb requires a topological description of a food web, and stable isotope signatures of all consumers and resources in the web. A merit of IsoWeb is that it takes into account variation in trophic enrichment factors among different consumer-resource links. Sensitivity analysis using realistic hypothetical food webs suggests that IsoWeb is applicable to a wide variety of food webs differing in the number of species, connectance, sample size, and data variability. Sensitivity analysis based on real topological webs showed that IsoWeb can allow for a certain level of topological uncertainty in target food webs, including erroneously assuming false links, omission of existent links and species, and trophic aggregation into trophospecies. Moreover, using an illustrative application to a real food web, we demonstrated that IsoWeb can compare the plausibility of different candidate topologies for a focal web. These results suggest that IsoWeb provides a powerful tool to analyze food-web structure from stable isotope data. We provide R and BUGS codes to aid efficient applications of IsoWeb.

[A patient with a primary malignant lymphoma surrounding the female urethra].

A 90-year-old female patient presented with dysuria. She was treated with partial excision of the mass protruding from the urethral meatus. Pathological examination revealed non-Hodgkin's malignant lymphoma of the B-cell type. The patient received a total of 42.4 Gy extrabeam irradiation. Our patient was disease-free for 14 months. We reviewed 25 cases of this rare entity reported previously.