Short-term Disturbances Research Articles

Behavioral Improvements and its Molecular Mechanism of Ilex kudingcha C.J. Tseng on Animal Model of Alzheimer’s Disease

Alzheimer's disease (AD) is a common chronic neurodegenerative disease with well-defined pathophysiological mechanisms. Ilex kudingcha (IK) C.J. Tseng is commonly known as bitter tea or “Khom” tea in Vietnam. The present study was conducted to investigate the anti-dementia effect of IK using olfactory bulbectomized (OBX) mice. OBX mice were daily treated with IK extract (540 mg/kg) or reference drug, tacrine (2.5 mg/kg) 1 week before and continuously for 3 days after the OBX surgery. The object recognition test, modified Y maze test and fear conditioning test were employed to analyze non-spatial short-term, spatial short-term and long-term memories of the mice respectively. Administration of IK extract and tacrine attenuated these OBX-induced cognitive deficits in mice. The effects of IK and tacrine on spatial short-term memory impairment were reversed by scopolamine, a muscarinic receptor antagonist. The amyloid-beta (Aβ) production in adult transgenic Drosophila brain flies was also investigated by using Western blotting with APP-HA antibody. These results indicated that IK extract improves short-term and long-term memory disturbances in OBX mice and that muscarinic receptor may play a role on these actions. In addition, our result also showed that IK extract reduces the expression of amyloid precursor protein (APP) in brain of AD model using Drosophila melanogaster.

Detecting Ionospheric TEC Disturbances by Three Methods of Detrending through Dense CORS During A Strong Thunderstorm

Satellite navigation and communications system can substantially be disturbed by ionospheric perturbations. Consequently, monitoring ionospheric anomalous has great significance. In this study, we focus on the short-term irregular disturbances through a strong thunderstorm in Wuhan City, Hubei, China by using ground-based GNSS observations from dense Continuously Operating Reference Stations (CORS) with a sampling rate of 1s. The total electron content (TEC) was used to find possible perturbations after biases have been calibrated for the derived TEC. Additionally, the geomagnetic conditions and the state of solar radiation was checked in the study period to recognize the causes for the ionospheric disturbances. The maxima and minima values of TEC deviations were ~2.5 and 0.5 TECU, respectively. Three methods of Detrended Fluctuations Analysis (DFA) were applied to assess the ionospheric disturbances over GNSS CORS stations; “Multi-step numerical difference”(MSND), “6th order polynomials fitting” (PF), and “one-week average difference”(AD). The analyzed results showed that MSND has the lowest performance. Meanwhile, the fitted TEC data with 6th order polynomials technique presented an improvement and a discrepancy related to MSND. To resolve this discrepancy, we proposed AD technique, it accomplished the best performance related to the TEC disturbances and was compared with the other two techniques. The research findings showed that ionospheric disturbed electrons can be generated with various rates and different velocities through lightning influences.

Natural Regeneration After Volcanic Eruptions: Resilience of the Non-legume Nitrogen-Fixing Tree Parasponia rigida

Volcanic eruptions disturb vegetation at a time it is needed for preventing mudflows. A resilient indigenous non-legume nitrogen-fixing tree that is adapted to the ash and spreads rapidly protects areas downstream in a volcanic landscape in Indonesia. Within the volcanic ring of fire both the long-term benefits (including densely populated, fertile agricultural soils) and short-term ecological disturbance of volcanic ash deposition are clear. Mount Kelud in East Java has erupted on a 15–37-years cycle for the past centuries, most recently in 2014, causing damage to settlements, agricultural land, agroforestry, and watershed protection forests, as the ash deposits caused tree mortality, restricted infiltration, and led to ash flows. Rapid “restoration” or recovery of tree-based vegetation with planted Legume trees (such as Calliandra spp.) has been attempted but is not very effective. However, the non-legume nitrogen-fixing Parasponia rigida, symbiotic with rhizobium bacteria, contrasted to its non-symbiotic sibling (Trema orientalis) has been studied in laboratory conditions, but not in its native environment. We mapped and sampled P. rigida in various locations (upper, middle, and lower elevation positions in ridge-slope-valley toposequences) on the Kelud complex starting 1 year after the latest eruption, estimated biomass development, and quantified P. rigida root nodules in relation to N availability in the ash/soil mixtures in these locations. P. rigida was found as a pioneer tree at elevations between 600 and 1,700 m a.s.l. (above sea level) along ridges, in slope, and valley positions. At lower elevations T. orientalis dominated. Within 3 years of the eruption, stem diameters were 3–10 cm. Up to 93% of P. rigida root nodules were found to be effective, based on the hemoglobin color on cross-sections. Rhizobium bacteria were found in root nodule tissue at densities of two to a hundred times higher than in rhizosphere soil. Between a total soil N content from 0.01 to 0.04% the density of effective nodules decreased from 1,200 to 200 m−2. P. rigida stands in the area, especially at ridges close to the crater deserve to be managed proactively as future seed sources, given the high frequency of eruption episodes, while recovery after eruptions on similar volcanoes can likely be facilitated by tactical assisted seed dispersal if effective seed collection and storage methods can be established.

Hybrid four‐level FC inverter using an internal supercapacitor storage system for a microgrid connected application

In this study, a new topology of grid-connected four-level inverter is introduced. The proposed structure, based on intermediate supercapacitors energy storage, is introduced to ensure two operation modes: to provide power to a microgrid from renewable energy sources and to regulate its voltage during short-term power disturbances. The main idea is to replace ordinary capacitors of a four-level flying capacitor (FC) inverter by supercapacitors and operate them under variable voltage conditions. The control strategy applies linear matrix inequalities approach as well as space vector modulation technique to generate the appropriate switching states. The latter part of this study is dedicated to the redundant state selection method for supercapacitors voltages balancing. Through experimental implementation, presented results highlight the efficiency of the proposed hybrid inverter in ensuring microgrid stability.

The benefits of biochar: Enhanced cadmium remediation, inhibited precursor production of nitrous oxide and a short-term disturbance on rhizosphere microbial community.

Biochar has the potential to remediate heavy metals in agricultural soil and mitigate nitrous oxide (N2O) emissions; however, the effects of biochar on heavy metal remediation, the soil microbial community and N2O emissions are not completely understood. In this study, we conducted a pot experiment in which Glycine max L. (soybean) was cultivated in two cadmium (Cd)-contaminated soils (low, 3.14mgkg-1; high, 10.80mgkg-1) to investigate the effects of biochar on the bioremediation of Cd, N2O emissions and the rhizosphere microbial community structure. The bioaccumulation of Cd in the plant shoots and roots increased with all biochar addition rates (0%, 1%, 5% and 10%); unexpectedly, the translocation capacity of Cd to the edible parts of the plant significantly decreased to 0.58mgkg-1, which was close to the edible threshold (0.4mgkg-1). The abundance and activities of functional marker genes of microbial nitrification (amoA) and denitrification (nirK, nirS and nosZ) were quantified with quantitative PCR, and we found that biochar addition reduced the precursor production of rhizoshpere N2O by inhibiting the transcription of the nirK gene. In addition, the nitrogenase activity during anthesis (S) was significantly (P<0.05) increased with 1% (v/v) biochar addition. Noticeably, biochar addition only changed the microbial community structure in the very first stage before eventually stabilize. This study highlighted that biochar has the potential ability to maintain the quality of agricultural crops, remediate Cd-contaminated soils and may help reduce N2O emissions without disturbing the microbial community.

Ecological response of a glacier-fed peatland to late Holocene climate and glacier changes on subantarctic South Georgia

Sedimentary deposits from glacier-fed peatlands provide records of past glacier variability, but the dynamics of these peat-forming ecosystems have rarely been investigated. Through multi-proxy analyses of a 204-cm peat core, we reconstructed the ecological response of a glacier-fed peatland on subantarctic South Georgia to climate and glacier variability over the last 4300 years. A stable peatland with rapid carbon accumulations and dynamic turnovers between brown mosses and monocots persisted between 4300 and 2550 cal yr BP when the up-valley cirque glacier was small under a regional hypsithermal climate. Carbon accumulation rates showed two peak periods driven by climate warming, reaching 140 g C m−2 yr−1 at 4000–3500 cal yr BP and 70 g C m−2 yr−1 at 3200–2700 cal yr BP. Paired δ13C and δ18O data from brown moss cellulose reveal several intervals of glacial meltwater inundation that caused short-term disturbances of the peatland vegetation, indicating that glacial meltwater potentially still affected the peatland ecosystem during this warm period. Moss-dominated vegetation was disrupted and peatland carbon accumulation rates decreased to 15 g C m−2 yr−1 after around 2550 cal yr BP when a cooling-driven glacier advance shifted the erosion and meltwater regime enhancing the glacial sediment influx onto the peatland. Although this enhanced regime of meltwater disturbance has continued since this transition, the brown moss habitat was gradually re-established during the medieval climate warming between 1200 and 600 cal yr BP and then became dominant shortly after that. This re-establishment of brown mosses might have benefited from a period of increased carbon accumulation rates up to 100 g C m−2 yr−1 at 1200–900 cal yr BP that built up the organic matter matrix and stabilized the habitat. We conclude that the ecosystem dynamics of glacier-fed peatlands is strongly shaped by the interplay between regional climate and glacier activity. This study also demonstrates the potential of stable isotope analysis in studying the paleohydrology of non-Sphagnum peatlands.

Influence of cereal harvest on adrenocortical activity in European hares (Lepus europaeus)

Anthropogenic disturbances, such as habitat modifications and machines, are associated with increased levels of faecal glucocorticoid metabolites (fGCMs) in mammals, an indicator of a stress response. One human-caused process provoking incisive habitat alterations is harvesting arable crops. We investigated the effect of cereal harvest on fGCM concentrations in European hares (Lepus europaeus) in arable landscapes in lower Austria during the year 2018 by collecting 591 faecal samples before, during and after cereal harvest. fGCMs were analysed using an enzyme immunoassay, and data were analysed using linear mixed-effects models. We found that neither cereal harvest nor farming practice (organic vs. conventional) caused an overall increase in the hares’ stress level. Lower vegetation density and higher proportions of bare ground were negatively correlated with fGCM concentrations, whereas the proportion of stubble fields was significantly positively correlated with fGCM concentrations in European hares. A change to more open landscapes might decrease time spent avoiding predation, and fallen grains may provide a beneficial additional food source for the hares. This indicates that European hares are well adapted to an opening up of the landscape and short-term disturbances such as cereal harvesting. In conclusion, cereal harvest had no large impact on European hares’ adrenocortical activity in an arable landscape with small average field size and enough available non-farmed areas.

Metabolic potential and community structure of bacteria in an organic tea plantation

Revealing the spatial and temporal distribution of bacteria in organic tea plantations is of great importance to clarify soil- and/or tea plant-associated community. In this study samples were collected from three rhizo-compartments of tea plant during four seasons, which were further subjected to community level physiological profiling and 16S rDNA next generation sequencing. Organic fertilization caused a short-term disturbance on pH, EC, and organic matter content of soil. Three rhizo-compartments harbored distinct bacterial community as revealed by PCA, PCoA and UPGMA analysis. Utilization of six carbon source categories was positively correlated with root surface community while negatively correlated with root interior community. Although there were variations in microbial parameters during four seasons, higher metabolic potential and diversity were observed in soil-associated rhizo-compartments. Bacterial families Gemmataceae, Pedosphaeraceae, and Solibacteraceae were more abundant in soil and root surface, while root interior were dominated by families Acidothermaceae, Burkholderiaceae, Ktedonobacteraceae, and Xanthobacteraceae. It is proposed that Burkholderiaceae and Xanthobacteraceae which dominate in root surface or root interior samples and other poorly studied phylogenetic groups may serve as potential candidates to study their interaction with tea plant.

A new approach to demand response in a microgrid based on coordination control between smart meter and distributed superconducting magnetic energy storage unit

Abstract Energy storage and demand response are becoming an increasingly valuable solution for the enhancement of stability and reliability of the electricity grid with high penetration of distributed energy sources such as wind and solar. This paper proposes an intelligent energy management scheme to allow different distributed generation sources and energy storage technologies to actively participate in demand response via the deployed smart meter infrastructure. A Distributed Superconducting Magnetic Energy Storage (D-SMES) device is integrated into the network to deliver instantaneous and large bursts of power to support the grid under short-term disturbances. The proposed demand response-based energy management algorithm receives, via the smart meter infrastructure, the information from the electricity network such as the energy cost, upper load adjustment limit, and the State-of-Charge (SOC) of the storage system then, under very specific conditions, a decision is formulated as a control signal for charging or discharging the storage system, aiming at minimizing the total energy while avoiding any load shedding. The effectiveness of the proposed demand response approach for controlling generation, storage and demand coordination and energy cost reduction is demonstrated on a sample power system simulated in MATLAB/SimPowerSystems toolbox and evaluated under different case study scenarios.

Soil microbial composition varies in response to coffee agroecosystem management

Soil microbes are essential to the continued productivity of sustainably managed agroecosystems. In shade coffee plantations, the relationship between soil microbial composition, soil nutrient availability and coffee productivity have been demonstrated, but the effects of management on the composition of the soil microbial communities remains relatively unexplored. To further understand how management modulates the soil microbiome, the soil fungal and bacterial communities, soil chemistry, and canopy composition were surveyed in a Nicaraguan coffee cooperative, across 19 individual farms. Amplicon sequencing analyses showed that management (organic or conventional), stand age and previous land use affected the soil microbiome, albeit in different ways. Bacterial communities were most strongly associated with soil chemistry, while fungal communities were more strongly associated with the composition of the canopy and historical land use of the coffee plantation. Notably, both fungal and bacterial richness decreased with stand age. In addition to revealing the first in-depth characterization of the soil microbiome in coffee plantations in Nicaragua, these results highlight how fungal and bacterial communities are simultaneously modulated by long-term land use legacies (i.e. an agricultural plot's previous land use) and short-term press disturbance (i.e. farm age).

Examination of high-resolution feed intake data of grower finisher pigs confronted with typical short-term disturbances in stable routine

Modern pig feeding systems allow the collection of highly detailed feeding data for each animal. These data enable the examination of individual feeding behaviours to assess an animal’s wellbeing. As such, four different treatments ‒ undisturbed control, starving (no feed for 24 h, restrictive feeding), feed change (changes in feed composition) and social stress (exchanging of animals between the pens and short-term reduction of accessible water) ‒ were designed to simulate typical short-term disturbances in a practical stable routine. Each treatment was conducted over 2 pens with 12 animals each. Zootechnical performance and feed intake behaviour measures were assessed for each animal. Treatments did not affect zootechnical performance. Results showed that short-term disturbances did not influence feed intake behaviours, such as daily feed intake, amount of intake per feeder visit, number of daily feeder visits and daily feeding action with highest feed intake. Animals developed individual feeding patterns that persisted through artificial short-term disturbances. However, data suggested that an individual animal’s behavioural pattern was strongly influenced by the group (pen) due to group dynamics among animals.

Intelligent islanding detection method for photovoltaic power system based on Adaboost algorithm

The universal islanding detection methods (IDMs) for photovoltaic (PV) power systems require manually thresholds setting. That will lead to a certain non-detection zone (NDZ). Moreover, disturbance signals injected by active detection methods may adversely affect power quality. Aiming at the above problems, this study proposes a passive intelligent IDM for parallel multi-PV system based on improved Adaptive Boosting (Adaboost) algorithm. Using Adaboost algorithm to generate classification models for islanding detection can theoretically avoid the NDZ of passive methods. The proposed method takes advantage of the electrical connection between characteristic parameters to adjust the classification model and improves the detection ability by redistributing the weight of each sub-model. Simulation results show that when adopted to a multi-PV system, the proposed method can effectively distinguish islanding operation in the NDZs of conventional passive IDMs. The method can also achieve accurate detection in the case of short-term power quality interferences, line faults and disturbance signal interference injected by active methods.

TEC anomalies assessment for earthquakes precursors in North-Eastern India and adjoining region using GPS data acquired during 2012–2018

A total of 160 earthquakes in North East Indian region and surroundings were analysed for earthquake precursor detection using GPS based Total Electron Content (TEC) estimation in the Ionosphere. TEC is very sensitive to short-term disturbances of a geomagnetic storm, solar flares and seismic activities. In the present study, TEC in the ionosphere was measured using dual-frequency signals from five GPS-based continuously operating reference stations/system (CORS) installed in North Eastern states of India. The abnormality in TEC variations was observed by constructing boundary limits using statistical method, the values crossing the limits being the anomaly. The results for Mw > 5 earthquakes such as Mw 5.5 Kohima Earthquake (July 14, 2012), Mw 6.8 Myanmar earthquake (November 11, 2012) and Mw 5.6 Kokrajhar Earthquake (June 28, 2015) covering North East India suggest TEC anomaly 10 days, 12 days and 13 days prior to the events. Analysis of 160 earthquakes suggests that the rate of success in TEC based anomaly detection for earthquake precursor increases with increase in Magnitude of the earthquakes. Accordingly, mostly Mw < 5 earthquakes could be 46.50% detectable, Mw 5–6 could be 81.56% detectable and Mw > 6 earthquakes could be fully detectable. Rate of success with reference to CORS as computed, is found in the order of Cherrapunjee, Meghalaya > Madankamdev, Assam > Mohanpur, Agartala > Mawtawar, Meghalaya > Khanapara, Assam. Therefore present investigations confirmed TEC anomalies prior to earthquakes with good rate of success, making it imperative to set up an automated system for real-time monitoring of TEC for Earthquake precursor detection and appropriate forewarning in near future.

Disturbance-Encoding-Based Neural Hammerstein–Wiener Model for Industrial Process Predictive Control

The control reliability of model predictive control is largely determined by the accuracy of the process model. The Hammerstein–Wiener (HW) model is an important nonlinear process modeling technique that has obtained great success in some process industries. Disturbances result in model mismatch and steady-state deviation, but little effort has been devoted to the coupling effects and inertial information in measured disturbances. In addition, few studies try to construct a disturbance observer (DO) to alleviate unmeasured disturbances. The present work proposes prompt disturbance rejection. First, a spatial–temporal long short-term memory-based measurable disturbance encoder is devised to analyze time-series information from measured disturbances and their coupling effects. The encoder can further clarify the status of inertial interference components and the disturbance intensity. Second, a DO is designed to estimate and attenuate unmeasured disturbances. Third, to create the new HW network, which is improved by integrating the disturbance encoder and observer differential, neural networks are used as nonlinear parts. Finally, a model predictive controller based on this improved model is constructed for real-time industrial process control. Simulation comparison experiments have demonstrated the superiority of the proposed methods. Real industry application in the country’s largest lead-zinc froth flotation plant in China validated the proposed model’s effectiveness in controlling chemical reagents.

Crude oil price prediction based on LSTM network and GM (1,1) model

PurposeAccording to the problem of crude oil price forecasting, the purpose of this paper is to propose a multi-step prediction method based on the empirical mode decomposition, long short-term memory network and GM (1,1) model.Design/methodology/approachFirst, the empirical mode decomposition method is used to decompose the crude oil price series into several components with different frequencies. Then, each subsequence is classified and synthesized based on the specific periodicity and other properties to obtain several components with different significant characteristics. Finally, all components are substituted into a suitable prediction model for fitting. LSTM models with different parameters are constructed for predicting specific components, which approximately and respectively represent short-term market disturbance and long-term influences. Rolling GM (1,1) model is constructed to simulate a series representing the development trend of oil price. Eventually, all results obtained from forecasting models are summarized to evaluate the performance of the model.FindingsThe model is respectively applied to simulate daily, weekly and monthly WTI crude oil price sequences. The results show that the model has high accuracy on the prediction, especially in terms of series representing long-term influences with lower frequency. GM (1,1) model has excellent performance on fitting the trend of crude oil price.Originality/valueThis paper combines GM (1,1) model with LSTM network to forecast WTI crude oil price series. According to the different characteristics of different sequences, suitable forecasting models are constructed to simulate the components.

Dynamic optimization strategies for on-demand ride services platform: Surge pricing, commission rate, and incentives

On-demand ride services reshape urban transportation systems, human mobility, and travelers' mode choice behavior. Compared to the traditional street-hailing taxi, an on-demand ride services platform analyzes ride requests of passengers and coordinates real-time supply and demand with dynamic operational strategies in the ride-sourcing market. To test the impact of dynamic optimization strategies on the ride-sourcing market, this paper proposes a dynamic vacant car-passenger meeting model. In this model, the accumulative arrival rate and departure rate of passengers and vacant cars determine the waiting number of passengers and vacant cars, while the waiting number of passengers and vacant cars in turn influence the meeting rate (which equals to the departure rate of both passengers and vacant cars). The departure rate means the rate at which passengers and vacant cars match up and start a paid trip. Compared with classic equilibrium models, this model can be utilized to characterize the influence of short-term variances and disturbances of current demand and supply (i.e., arrival rates of passengers and vacant cars) on the waiting numbers of passengers and vacant cars. Using the proposed meeting model, we optimize dynamic strategies under two objective functions, i.e., platform revenue maximization, and social welfare maximization, while the driver's profit is guaranteed above a certain level. We also propose an algorithm based on approximate dynamic programming (ADP) to solve the sequential dynamic optimization problem. The results show that our algorithm can effectively improve the objective function of the multi-period problem, compared with the myopic algorithm. A broader range of surge pricing and commission rate and the introduction of incentives are helpful to achieve better optimization results. The dynamic optimization strategies help the on-demand ride services platform efficiently adjust supply and demand resources and achieve specific optimization goals.

Increasing ground-layer plant taxonomic diversity masks declining phylogenetic diversity along a silvicultural disturbance gradient

Most plant diversity in temperate deciduous forests is found in the ground layer, but nearly all studies comparing plant community assembly using taxonomic, trait, and phylogenetic diversity indices are limited to woody plants. To examine the relationship between short-term ground-layer plant community assembly and disturbance severity, we leveraged a silvicultural experiment that applied a combination of harvest and site preparation treatments in a northern hardwood forest in Michigan, USA. We predicted that after two growing seasons, plant communities would be less sensitive to harvest treatments when compared with site preparation treatments that disturb the rhizosphere and modify rooting substrate. We also predicted that an increase in taxonomic diversity would accompany a decline in trait diversity and phylogenetic diversity. Instead, plant species composition responded similarly to harvest treatment and site preparation treatment. However, our measure of disturbance severity was positively correlated with both trait diversity and taxonomic diversity but negatively correlated with phylogenetic diversity, indicating that increasingly diverse traits and taxonomies along this disturbance severity gradient were comprised of more phylogenetically simple plant communities. Informed management decisions should therefore consider the underlying value of each diversity measure, as taxonomic diversity alone may not be the best metric for assessing plant community assembly.

Short-term Effects of Cadmium and Mercury on Soil Nematode Communities in a Pot Experiment.

SummaryAnalysis of soil nematode feeding groups and functional guilds were used as a valuable tool to detect heavy metal pollution. Effects of cadmium (Cd) at 5 mg/kg, mercury (Hg) at 20mg/kg, combined Cd and Hg at 5+20mg/kg on the nematode communities were studied after three months application. Nematodes were collected from soil in rhizosphere of Morning glories (Pharhiris nil) which were applied as heavy metal accumulators and were grown in the experimental pots. Both single and combined heavy metals had marked effects on the nematode abundance, life-history strategies and feeding type composition. Bacteriovores and c-p 2 group were found to be the most abundant trophic group and functional guild, respectively. Acrobeloides and Pratylenchus were the most two abundant genera, decreasing number of them was responsible for the significant difference between control and polluted treatments. Cd-5 and Cd-Hg 5+20 presented lower values of nematode diversity index (H’) and evenness index (J’) than Hg-20. The combination of Cd and Hg showed lower nematode trophic diversity (TD), in comparison with single Cd or Hg. Conversely, heavy metals addition exhibited no pronounced effect on Maturity index (MI), structural index (SI) and enrichment index (EI). Our results demonstrate that genera composition is a better indicator to short-term heavy metal effects than some common indicator indices and emphasize that deeper assemblage analyses are needed for a correct interpretation of short-term disturbance on soil nematodes.

Forced nest site relocations negatively affect reproductive investment in a colonial seabird species

Species breeding in urban environments are highly prone to a wide variety of non-natural, human activities, which range from short-term disturbances to the degradation or loss of suitable habitat. The latter in turn may force individuals to relocate to new sites for foraging or breeding, both of which presumably entails fitness costs due the trade-offs of finding and exploring new habitats. Species showing a high level of spatial foraging specialisation or nest site fidelity are expected to be most vulnerable. In this study, we explored the consequences of nest site loss on the reproductive investment of lesser black-backed gulls (Larus fuscus), a site faithful seabird species breeding in an urban environment. We monitored a population of 1.173 colour-ringed gulls across 13 years, that involved several episodes of spatially restricted loss of breeding habitat. We found that birds which lost their breeding territories reduced their investment into the eggs as reflected in a decrease of the clutch volume. They relocated over larger distances compared to birds that relocated voluntarily. Moreover, the likelihood of skipping the subsequent breeding season increased after a forced relocation. These negative effects of forced relocation likely contribute to the decline in the number of breeding pairs in our urban population as observed during the last ten years, and highlights the importance of maintaining a stable breeding environment in urban areas for the conservation of this and potentially other colonial breeding seabird species.

Effect of sulfate addition on carbon flow and microbial community composition during thermophilic digestion of cellulose

Substrates with high sulfate levels pose problems for biogas production as they allow sulfate reducing bacteria to compete with syntrophic and methanogenic members of the community. In addition, the end product of sulfate reduction, hydrogen sulfide, is toxic and corrosive. Here we show how sulfate addition affects physiological processes in a thermophilic methanogenic system by analyzing the carbon flow and the microbial community with quantitative PCR and amplicon sequencing of the 16s rRNA gene. A sulfate addition of 0.5 to 3 g/L caused a decline in methane production by 73–92%, while higher sulfate concentrations had no additional inhibitory effect. Generally, sulfate addition induced a shift in the composition of the microbial community towards a higher dominance of Firmicutes and decreasing abundances of Bacteroidetes and Euryarchaeota. The abundance of methanogens (e.g., Methanoculleus and Methanosarcina) was reduced, while sulfate reducing bacteria (especially Candidatus Desulforudis and Desulfotomaculum) increased significantly in presence of sulfate. The sulfate addition had a significant impact on the carbon flow within the system, shifting the end product from methane and carbon dioxide to acetate and carbon dioxide. Interestingly, methane production quickly resumed, when sulfate was no longer present in the system. Despite the strong impact of sulfate addition on the carbon flow and the microbial community structure during thermophilic biogas production, short-term process disturbances caused by unexpected introduction of sulfate may be overcome due to the high resilience of the engaged microorganisms.