Methylocystis sp. strain SC2 can adapt to a wide range of methane concentrations. This is due to the presence of two isozymes of particulate methane monooxygenase exhibiting different methane oxidation kinetics. To gain insight into the underlying genetic information, its genome was sequenced and found to comprise a 3.77 Mb chromosome and two large plasmids.
We report important features of the strain SC2 genome. Its sequence is compared with those of seven other methanotroph genomes, comprising members of the Alphaproteobacteria, Gammaproteobacteria, and Verrucomicrobia. While the pan-genome of all eight methanotroph genomes totals 19,358 CDS, only 154 CDS are shared. The number of core genes increased with phylogenetic relatedness: 328 CDS for proteobacterial methanotrophs and 1,853 CDS for the three alphaproteobacterial Methylocystaceae members, Methylocystis sp. strain SC2 and strain Rockwell, and Methylosinus trichosporium OB3b. The comparative study was coupled with physiological experiments to verify that strain SC2 has diverse nitrogen metabolism capabilities. In correspondence to a full complement of 34 genes involved in N2 fixation, strain SC2 was found to grow with atmospheric N2 as the sole nitrogen source, preferably at low oxygen concentrations. Denitrification-mediated accumulation of 0.7 nmol 30N2/hr/mg dry weight of cells under anoxic conditions was detected by tracer analysis. N2 production is related to the activities of plasmid-borne nitric oxide and nitrous oxide reductases.
Presence of a complete denitrification pathway in strain SC2, including the plasmid-encoded nosRZDFYX operon, is unique among known methanotrophs. However, the exact ecophysiological role of this pathway still needs to be elucidated. Detoxification of toxic nitrogen compounds and energy conservation under oxygen-limiting conditions are among the possible roles. Relevant features that may stimulate further research are, for example, absence of CRISPR/Cas systems in strain SC2, high number of iron acquisition systems in strain OB3b, and large number of transposases in strain Rockwell.
The objective of the present study is to evaluate the cost and effectiveness of decontamination strategies in the special decontamination areas in Fukushima in regard to external radiation dose. A geographical information system (GIS) was used to relate the predicted external dose in the affected areas to the number of potential inhabitants and the land use in the areas. A comprehensive review of the costs of various decontamination methods was conducted as part of the analysis. The results indicate that aerial decontamination in the special decontamination areas in Fukushima would be effective for reducing the air dose rate to the target level in a short period of time in some but not all of the areas. In a standard scenario, analysis of cost and effectiveness suggests that decontamination costs for agricultural areas account for approximately 80% of the total decontamination cost, of which approximately 60% is associated with storage. In addition, the costs of decontamination per person per unit area are estimated to vary greatly. Appropriate selection of decontamination methods may significantly decrease decontamination costs, allowing more meaningful decontamination in terms of the limited budget. Our analysis can help in examining the prioritization of decontamination areas from the viewpoints of cost and effectiveness in reducing the external dose. Decontamination strategies should be determined according to air dose rates and future land-use plans.
Purpose: Cochlear implants (CIs) enable children with severe and profound hearing impairments to perceive the sensation of sound sufficiently to permit oral language acquisition. So far, studies have focused mainly on technological improvements and general outcomes of implantation for speech perception and spoken language development. This study quantitatively explored the organization of the semantic networks of children with CIs in comparison to those of age-matched normal hearing (NH) peers.
Method: Twenty seven children with CIs and twenty seven age- and IQ-matched NH children ages 7–10 were tested on a timed animal verbal fluency task (Name as many animals as you can). The responses were analyzed using correlation and network methodologies. The structure of the animal category semantic network for both groups were extracted and compared.
Results: Children with CIs appeared to have a less-developed semantic network structure compared to age-matched NH peers. The average shortest path length (ASPL) and the network diameter measures were larger for the NH group compared to the CIs group. This difference was consistent for the analysis of networks derived from animal names generated by each group [sample-matched correlation networks (SMCN)] and for the networks derived from the common animal names generated by both groups [word-matched correlation networks (WMCN)].
Conclusions: The main difference between the semantic networks of children with CIs and NH lies in the network structure. The semantic network of children with CIs is under-developed compared to the semantic network of the age-matched NH children. We discuss the practical and clinical implications of our findings.
cochlear implants; semantic networks; verbal fluency; network science; spreading activation; mental lexicon
Changes in electroencephalography (EEG) amplitude modulations have recently been linked with early-stage Alzheimer’s disease (AD). Existing tools available to perform such analysis (e.g., detrended fluctuation analysis), however, provide limited gains in discriminability power over traditional spectral based EEG analysis. In this paper, we explore the use of an innovative EEG amplitude modulation analysis technique based on spectro-temporal signal processing. More specifically, full-band EEG signals are first decomposed into the five well-known frequency bands and the envelopes are then extracted via a Hilbert transform. Each of the five envelopes are further decomposed into four so-called modulation bands, which were chosen to coincide with the delta, theta, alpha and beta frequency bands. Experiments on a resting-awake EEG dataset collected from 76 participants (27 healthy controls, 27 diagnosed with mild-AD, and 22 with moderate-AD) showed significant differences in amplitude modulations between the three groups. Most notably, i) delta modulation of the beta frequency band disappeared with an increase in disease severity (from mild to moderate AD), ii) delta modulation of the theta band appeared with an increase in severity, and iii) delta modulation of the beta frequency band showed to be a reliable discriminant feature between healthy controls and mild-AD patients. Taken together, it is hoped that the developed tool can be used to assist clinicians not only with early detection of Alzheimer’s disease, but also to monitor its progression.
Complex networks have been extensively used in the last decade to characterize and analyze complex systems, and they have been recently proposed as a novel instrument for the analysis of spectra extracted from biological samples. Yet, the high number of measurements composing spectra, and the consequent high computational cost, make a direct network analysis unfeasible. We here present a comparative analysis of three customary feature selection algorithms, including the binning of spectral data and the use of information theory metrics. Such algorithms are compared by assessing the score obtained in a classification task, where healthy subjects and people suffering from different types of cancers should be discriminated. Results indicate that a feature selection strategy based on Mutual Information outperforms the more classical data binning, while allowing a reduction of the dimensionality of the data set in two orders of magnitude.
For biopharmaceutical companies, investments in research and development are risky, and the results from clinical trials are key inflection points in the process. Few studies have explored how and to what extent the public equity market values clinical trial results.
Our study dataset matched announcements of clinical trial results for investigational compounds from January 2011 to May 2013 with daily stock market returns of large United States-listed pharmaceutical and biotechnology companies. Event study methodology was used to examine the relationship between clinical research events and changes in stock returns.
We identified public announcements for clinical trials of 24 investigational compounds, including 16 (67%) positive and 8 (33%) negative events. The majority of announcements were for Phase 3 clinical trials (N = 13, 54%), and for oncologic (N = 7, 29%) and neurologic (N = 6, 24%) indications. The median cumulative abnormal returns on the day of the announcement were 0.8% (95% confidence interval [CI]: –2.3, 13.4%; P = 0.02) for positive events and –2.0% (95% CI: –9.1, 0.7%; P = 0.04) for negative events, with statistically significant differences from zero. In the day immediately following the announcement, firms with positive events were associated with stock price corrections, with median cumulative abnormal returns falling to 0.4% (95% CI: –3.8, 12.3%; P = 0.33). For firms with negative announcements, the median cumulative abnormal returns were –1.7% (95% CI: –9.5, 1.0%; P = 0.03), and remained significantly negative over the two day event window. The magnitude of abnormal returns did not differ statistically by indication, by trial phase, or between biotechnology and pharmaceutical firms.
The release of clinical trial results is an economically significant event and has meaningful effects on market value for large biopharmaceutical companies. Stock return underperformance due to negative events is greater in magnitude and persists longer than abnormal returns due to positive events, suggesting asymmetric market reactions.
The relationship between a market index and its constituent stocks is complicated. While an index is a weighted average of its constituent stocks, when the investigated time scale is one day or longer the index has been found to have a stronger effect on the stocks than vice versa. We explore how this interaction changes in short time scales using high frequency data. Using a correlation-based analysis approach, we find that in short time scales stocks have a stronger influence on the index. These findings have implications for high frequency trading and suggest that the price of an index should be published on shorter time scales, as close as possible to those of the actual transaction time scale.
Many biological networks are signed molecular networks which consist of positive and negative links. To reveal the distinct features between links with different signs, we proposed signed link-clustering coefficients that assess the similarity of inter-action profiles between linked molecules. We found that positive links tended to cluster together, while negative links usually behaved like bridges between positive clusters. Positive links with higher adhesiveness tended to share protein domains, be associated with protein-protein interactions and make intra-connections within protein complexes. Negative links that were more bridge-like tended to make interconnections between protein complexes. Utilizing the proposed measures to group positive links, we observed hierarchical modules that could be well characterized by functional annotations or known protein complexes. Our results imply that the proposed sign-specific measures can help reveal the network structural characteristics and the embedded biological contexts of signed links, as well as the functional organization of signed molecular networks.
The evolution of biological signalling systems and apparently altruistic or cooperative traits in diverse organisms has required selection against the subversive tendencies of self-interested biological entities. The bacterial signalling and response system known as quorum sensing or Acylated Homoserine Lactone (AHL) mediated gene expression is thought to have evolved through kin selection. In this in vitro study on the model quorum sensing bioluminescent marine symbiont Vibrio fischeri, competition and long-term sub culturing experiments suggest that selection for AHL synthesis (encoded by the AHL synthase gene luxI) is independent of the quorum sensing regulated phenotype (bioluminescence encoded by luxCDABE). Whilst results support the hypothesis that signal response (AHL binding and transcriptional activation encoded by the luxR gene) is maintained through indirect fitness benefits (kin selection), signal synthesis is maintained in the V. fischeri genome over evolutionary time through direct fitness benefits at the individual level from an unknown function.
Biofilm-related infections can develop everywhere in the human body and are rarely cleared by the host immune system. Moreover, biofilms are often tolerant to antimicrobials, due to a combination of inherent properties of bacteria in their adhering, biofilm mode of growth and poor physical penetration of antimicrobials through biofilms. Current understanding of biofilm recalcitrance toward antimicrobial penetration is based on qualitative descriptions of biofilms. Here we hypothesize that stress relaxation of biofilms will relate with antimicrobial penetration. Stress relaxation analysis of single-species oral biofilms grown in vitro identified a fast, intermediate and slow response to an induced deformation, corresponding with outflow of water and extracellular polymeric substances, and bacterial re-arrangement, respectively. Penetration of chlorhexidine into these biofilms increased with increasing relative importance of the slow and decreasing importance of the fast relaxation element. Involvement of slow relaxation elements suggests that biofilm structures allowing extensive bacterial re-arrangement after deformation are more open, allowing better antimicrobial penetration. Involvement of fast relaxation elements suggests that water dilutes the antimicrobial upon penetration to an ineffective concentration in deeper layers of the biofilm. Next, we collected biofilms formed in intra-oral collection devices bonded to the buccal surfaces of the maxillary first molars of human volunteers. Ex situ chlorhexidine penetration into two weeks old in vivo formed biofilms followed a similar dependence on the importance of the fast and slow relaxation elements as observed for in vitro formed biofilms. This study demonstrates that biofilm properties can be derived that quantitatively explain antimicrobial penetration into a biofilm.
Persistence is a prime example of phenotypic heterogeneity, where a microbial population splits into two distinct subpopulations with different growth and survival properties as a result of reversible phenotype switching. Specifically, persister cells grow more slowly than normal cells under unstressed growth conditions, but survive longer under stress conditions such as the treatment with bactericidal antibiotics. We analyze the population dynamics of such a population for several typical experimental scenarios, namely a constant environment, shifts between growth and stress conditions, and periodically switching environments. We use an approximation scheme that allows us to map the dynamics to a logistic equation for the subpopulation ratio and derive explicit analytical expressions for observable quantities that can be used to extract underlying dynamic parameters from experimental data. Our results provide a theoretical underpinning for the study of phenotypic switching, in particular for organisms where detailed mechanistic knowledge is scarce.
Sporulation vs. competence provides a prototypic example of collective cell fate determination. The decision is performed by the action of three modules: 1) A stochastic competence switch whose transition probability is regulated by population density, population stress and cell stress. 2) A sporulation timer whose clock rate is regulated by cell stress and population stress. 3) A decision gate that is coupled to the timer via a special repressilator-like loop. We show that the distinct circuit architecture of this gate leads to special dynamics and noise management characteristics: The gate opens a time-window of opportunity for competence transitions during which it generates oscillations that are turned into a chain of transition opportunities – each oscillation opens a short interval with high transition probability. The special architecture of the gate also leads to filtering of external noise and robustness against internal noise and variations in the circuit parameters.
We analyzed one decade of data collected by the Programme for International Student Assessment (PISA), including the mathematics and reading performance of nearly 1.5 million 15 year olds in 75 countries. Across nations, boys scored higher than girls in mathematics, but lower than girls in reading. The sex difference in reading was three times as large as in mathematics. There was considerable variation in the extent of the sex differences between nations. There are countries without a sex difference in mathematics performance, and in some countries girls scored higher than boys. Boys scored lower in reading in all nations in all four PISA assessments (2000, 2003, 2006, 2009). Contrary to several previous studies, we found no evidence that the sex differences were related to nations’ gender equality indicators. Further, paradoxically, sex differences in mathematics were consistently and strongly inversely correlated with sex differences in reading: Countries with a smaller sex difference in mathematics had a larger sex difference in reading and vice versa. We demonstrate that this was not merely a between-nation, but also a within-nation effect. This effect is related to relative changes in these sex differences across the performance continuum: We did not find a sex difference in mathematics among the lowest performing students, but this is where the sex difference in reading was largest. In contrast, the sex difference in mathematics was largest among the higher performing students, and this is where the sex difference in reading was smallest. The implication is that if policy makers decide that changes in these sex differences are desired, different approaches will be needed to achieve this for reading and mathematics. Interventions that focus on high-achieving girls in mathematics and on low achieving boys in reading are likely to yield the strongest educational benefits.
There is a rapidly expanding literature on the application of complex networks in economics that focused mostly on stock markets. In this paper, we discuss an application of complex networks to study international business cycles.
We construct complex networks based on GDP data from two data sets on G7 and OECD economies. Besides the well-known correlation-based networks, we also use a specific tool for presenting causality in economics, the Granger causality. We consider different filtering methods to derive the stationary component of the GDP series for each of the countries in the samples. The networks were found to be sensitive to the detrending method. While the correlation networks provide information on comovement between the national economies, the Granger causality networks can better predict fluctuations in countries’ GDP. By using them, we can obtain directed networks allows us to determine the relative influence of different countries on the global economy network. The US appears as the key player for both the G7 and OECD samples.
The use of complex networks is valuable for understanding the business cycle comovements at an international level.
The spontaneous emergence of pattern formation is ubiquitous in nature, often arising as a collective phenomenon from interactions among a large number of individual constituents or sub-systems. Understanding, and controlling, collective behavior is dependent on determining the low-level dynamical principles from which spatial and temporal patterns emerge; a key question is whether different group-level patterns result from all components of a system responding to the same external factor, individual components changing behavior but in a distributed self-organized way, or whether multiple collective states co-exist for the same individual behaviors. Using schooling fish (golden shiners, in groups of 30 to 300 fish) as a model system, we demonstrate that collective motion can be effectively mapped onto a set of order parameters describing the macroscopic group structure, revealing the existence of at least three dynamically-stable collective states; swarm, milling and polarized groups. Swarms are characterized by slow individual motion and a relatively dense, disordered structure. Increasing swim speed is associated with a transition to one of two locally-ordered states, milling or highly-mobile polarized groups. The stability of the discrete collective behaviors exhibited by a group depends on the number of group members. Transitions between states are influenced by both external (boundary-driven) and internal (changing motion of group members) factors. Whereas transitions between locally-disordered and locally-ordered group states are speed dependent, analysis of local and global properties of groups suggests that, congruent with theory, milling and polarized states co-exist in a bistable regime with transitions largely driven by perturbations. Our study allows us to relate theoretical and empirical understanding of animal group behavior and emphasizes dynamic changes in the structure of such groups.
The patterns exhibited by moving animal groups like flocks of birds and schools of fish are typical of self-organizing systems in which global structural and dynamical properties arise from local interactions between individuals. Despite their apparent complexity, such systems can often be described, and understood, in terms of these emergent properties, rather than the detailed low-level description needed for depicting the individual dynamics. Here we show that schooling fish (in groups of 30 to 300 golden shiners) can be described in terms of the degree of alignment and degree of rotation among group members. We demonstrate that shiner schools exhibit three distinct behaviors: a swarm state with low speeds and little order; a strongly aligned state where the fish move with higher speeds; and a milling state, where each fish moves around the center of the group. Simulations have previously predicted this type of behavior, and we relate our findings to a well-known model of collective motion to help highlight similarities and differences between models and animal groups. Our results give insight into the regulation of group structure among animals, and also inform us generally about how global structures arise naturally from interactions among components of dynamical systems.
Treated biosolids have been applied to 750-ha of a Pinus radiata forest plantation on Rabbit Island near Nelson City in New Zealand since 1996. A long-term research trial was established in 1997 to investigate the effects of the biosolids applications on the receiving environment and tree growth. An analysis of the likely economic impact of biosolids application shows that biosolids application has been beneficial. Stem volume of the high treatment (biosolids applied at 600 kg N ha-1 every three years) was 36% greater than the control treatment (no biosolids applied), and stem volume of the standard treatment (300 kg N ha-1) was 27% greater than the control treatment at age 18 years of age. Biosolids treatments have effectively transformed a low productivity forest site to a medium productivity site. Although this increased productivity has been accompanied by some negative influences on wood quality attributes with reduced wood stiffness, wood density, and larger branches, an economic analysis shows that the increased stem volume and greater average log diameter in the biosolids treatments outweighs these negative effects. The high and standard biosolids treatments are predicted to increase the net stumpage value of logs by 24% and 14% respectively at harvesting, providing a large positive impact on the forest owner’s economic return.
Various movement parameters of grasping movements, like velocity or type of the grasp, have been successfully decoded from neural activity. However, the question of movement event detection from brain activity, that is, decoding the time at which an event occurred (e.g. movement onset), has been addressed less often. Yet, this may be a topic of key importance, as a brain-machine interface (BMI) that controls a grasping prosthesis could be realized by detecting the time of grasp, together with an optional decoding of which type of grasp to apply. We, therefore, studied the detection of time of grasps from human ECoG recordings during a sequence of natural and continuous reach-to-grasp movements. Using signals recorded from the motor cortex, a detector based on regularized linear discriminant analysis was able to retrieve the time-point of grasp with high reliability and only few false detections. Best performance was achieved using a combination of signal components from time and frequency domains. Sensitivity, measured by the amount of correct detections, and specificity, represented by the amount of false detections, depended strongly on the imposed restrictions on temporal precision of detection and on the delay between event detection and the time the event occurred. Including neural data from after the event into the decoding analysis, slightly increased accuracy, however, reasonable performance could also be obtained when grasping events were detected 125 ms in advance. In summary, our results provide a good basis for using detection of grasping movements from ECoG to control a grasping prosthesis.
Recovery after stroke correlates with non-active (stunned) brain regions, which may persist for years. The current study aimed to evaluate whether increasing the level of dissolved oxygen by Hyperbaric Oxygen Therapy (HBOT) could activate neuroplasticity in patients with chronic neurologic deficiencies due to stroke.
Methods and Findings
A prospective, randomized, controlled trial including 74 patients (15 were excluded). All participants suffered a stroke 6–36 months prior to inclusion and had at least one motor dysfunction. After inclusion, patients were randomly assigned to "treated" or "cross" groups. Brain activity was assessed by SPECT imaging; neurologic functions were evaluated by NIHSS, ADL, and life quality. Patients in the treated group were evaluated twice: at baseline and after 40 HBOT sessions. Patients in the cross group were evaluated three times: at baseline, after a 2-month control period of no treatment, and after subsequent 2-months of 40 HBOT sessions. HBOT protocol: Two months of 40 sessions (5 days/week), 90 minutes each, 100% oxygen at 2 ATA. We found that the neurological functions and life quality of all patients in both groups were significantly improved following the HBOT sessions while no improvement was found during the control period of the patients in the cross group. Results of SPECT imaging were well correlated with clinical improvement. Elevated brain activity was detected mostly in regions of live cells (as confirmed by CT) with low activity (based on SPECT) – regions of noticeable discrepancy between anatomy and physiology.
The results indicate that HBOT can lead to significant neurological improvements in post stroke patients even at chronic late stages. The observed clinical improvements imply that neuroplasticity can still be activated long after damage onset in regions where there is a brain SPECT/CT (anatomy/physiology) mismatch.
Most economic theories are based on the premise that individuals maximize their own self-interest and correctly incorporate the structure of their environment into all decisions, thanks to human intelligence. The influence of this paradigm goes far beyond academia–it underlies current macroeconomic and monetary policies, and is also an integral part of existing financial regulations. However, there is mounting empirical and experimental evidence, including the recent financial crisis, suggesting that humans do not always behave rationally, but often make seemingly random and suboptimal decisions.
Methods and Findings
Here we propose to reconcile these contradictory perspectives by developing a simple binary-choice model that takes evolutionary consequences of decisions into account as well as the role of intelligence, which we define as any ability of an individual to increase its genetic success. If no intelligence is present, our model produces results consistent with prior literature and shows that risks that are independent across individuals in a generation generally lead to risk-neutral behaviors, but that risks that are correlated across a generation can lead to behaviors such as risk aversion, loss aversion, probability matching, and randomization. When intelligence is present the nature of risk also matters, and we show that even when risks are independent, either risk-neutral behavior or probability matching will occur depending upon the cost of intelligence in terms of reproductive success. In the case of correlated risks, we derive an implicit formula that shows how intelligence can emerge via selection, why it may be bounded, and how such bounds typically imply the coexistence of multiple levels and types of intelligence as a reflection of varying environmental conditions.
Rational economic behavior in which individuals maximize their own self interest is only one of many possible types of behavior that arise from natural selection. The key to understanding which types of behavior are more likely to survive is how behavior affects reproductive success in a given population’s environment. From this perspective, intelligence is naturally defined as behavior that increases the probability of reproductive success, and bounds on rationality are determined by physiological and environmental constraints.
We demonstrate that a live epithelial cell monolayer can act as a planar waveguide. Our infrared reflectivity measurements show that highly differentiated simple epithelial cells, which maintain tight intercellular connectivity, support efficient waveguiding of the infrared light in the spectral region of 1.4–2.5 µm and 3.5–4 µm. The wavelength and the magnitude of the waveguide mode resonances disclose quantitative dynamic information on cell height and cell-cell connectivity. To demonstrate this we show two experiments. In the first one we trace in real-time the kinetics of the disruption of cell-cell contacts induced by calcium depletion. In the second one we show that cell treatment with the PI3-kinase inhibitor LY294002 results in a progressive decrease in cell height without affecting intercellular connectivity. Our data suggest that infrared waveguide spectroscopy can be used as a novel bio-sensing approach for studying the morphology of epithelial cell sheets in real-time, label-free manner and with high spatial-temporal resolution.
Understanding correlations in complex systems is crucial in the face of turbulence, such as the ongoing financial crisis. However, in complex systems, such as financial systems, correlations are not constant but instead vary in time. Here we address the question of quantifying state-dependent correlations in stock markets. Reliable estimates of correlations are absolutely necessary to protect a portfolio. We analyze 72 years of daily closing prices of the 30 stocks forming the Dow Jones Industrial Average (DJIA). We find the striking result that the average correlation among these stocks scales linearly with market stress reflected by normalized DJIA index returns on various time scales. Consequently, the diversification effect which should protect a portfolio melts away in times of market losses, just when it would most urgently be needed. Our empirical analysis is consistent with the interesting possibility that one could anticipate diversification breakdowns, guiding the design of protected portfolios.
A Kuhnian approach to research assessment requires us to consider that the important scientific breakthroughs that drive scientific progress are infrequent and that the progress of science does not depend on normal research. Consequently, indicators of research performance based on the total number of papers do not accurately measure scientific progress. Similarly, those universities with the best reputations in terms of scientific progress differ widely from other universities in terms of the scale of investments made in research and in the higher concentrations of outstanding scientists present, but less so in terms of the total number of papers or citations. This study argues that indicators for the 1% high-citation tail of the citation distribution reveal the contribution of universities to the progress of science and provide quantifiable justification for the large investments in research made by elite research universities. In this tail, which follows a power low, the number of the less frequent and highly cited important breakthroughs can be predicted from the frequencies of papers in the upper part of the tail. This study quantifies the false impression of excellence produced by multinational papers, and by other types of papers that do not contribute to the progress of science. Many of these papers are concentrated in and dominate lists of highly cited papers, especially in lower-ranked universities. The h-index obscures the differences between higher- and lower-ranked universities because the proportion of h-core papers in the 1% high-citation tail is not proportional to the value of the h-index.
Paenibacillus dendritiformis is a Gram-positive, soil-dwelling, spore-forming social microorganism. An intriguing collective faculty of this strain is manifested by its ability to switch between different morphotypes, such as the branching (T) and the chiral (C) morphotypes. Here we report the 6.3-Mb draft genome sequence of the P. dendritiformis C454 chiral morphotype.
Economic impact assessment of invasive species requires integration of information on pest entry, establishment and spread, valuation of assets at risk and market consequences at large spatial scales. Here we develop such a framework and demonstrate its application to the pinewood nematode, Bursaphelenchus xylophilus, which threatens the European forestry industry. The effect of spatial resolution on the assessment result is analysed.
Direct economic impacts resulting from wood loss are computed using partial budgeting at regional scale, while impacts on social welfare are computed by a partial equilibrium analysis of the round wood market at EU scale. Substantial impacts in terms of infested stock are expected in Portugal, Spain, Southern France, and North West Italy but not elsewhere in EU in the near future. The cumulative value of lost forestry stock over a period of 22 years (2008–2030), assuming no regulatory control measures, is estimated at €22 billion. The greatest yearly loss of stock is expected to occur in the period 2014–2019, with a peak of three billion euros in 2016, but stabilizing afterwards at 300–800 million euros/year. The reduction in social welfare follows the loss of stock with considerable delay because the yearly harvest from the forest is only 1.8%. The reduction in social welfare for the downstream round wood market is estimated at €218 million in 2030, whereby consumers incur a welfare loss of €357 million, while producers experience a €139 million increase, due to higher wood prices. The societal impact is expected to extend to well beyond the time horizon of the analysis, and long after the invasion has stopped.
Pinewood nematode has large economic consequences for the conifer forestry industry in the EU. A change in spatial resolution affected the calculated directed losses by 24%, but did not critically affect conclusions.