scholarly journals Persistent after-effects of heavy rain on concentrations of ice nuclei and rainfall suggest a biological cause

2015 ◽  
Vol 15 (5) ◽  
pp. 2313-2326 ◽  
Author(s):  
E. K. Bigg ◽  
S. Soubeyrand ◽  
C. E. Morris
Keyword(s):  
Pseudomonas Syringae ◽  
Leaf Surface ◽  
Daily Rainfall ◽  
Heavy Rain ◽  
Historical Record ◽  
Past Century ◽  
Long Term Effects ◽  
Power Stations ◽  
Ice Nuclei ◽  
Rainfall Frequency

Abstract. Rainfall is one of the most important aspects of climate, but the extent to which atmospheric ice nuclei (IN) influence its formation, quantity, frequency, and location is not clear. Microorganisms and other biological particles are released following rainfall and have been shown to serve as efficient IN, in turn impacting cloud and precipitation formation. Here we investigated potential long-term effects of IN on rainfall frequency and quantity. Differences in IN concentrations and rainfall after and before days of large rainfall accumulation (i.e., key days) were calculated for measurements made over the past century in southeastern and southwestern Australia. Cumulative differences in IN concentrations and daily rainfall quantity and frequency as a function of days from a key day demonstrated statistically significant increasing logarithmic trends (R2 > 0.97). Based on observations that cumulative effects of rainfall persisted for about 20 days, we calculated cumulative differences for the entire sequence of key days at each site to create a historical record of how the differences changed with time. Comparison of pre-1960 and post-1960 sequences most commonly showed smaller rainfall totals in the post-1960 sequences, particularly in regions downwind from coal-fired power stations. This led us to explore the hypothesis that the increased leaf surface populations of IN-active bacteria due to rain led to a sustained but slowly diminishing increase in atmospheric concentrations of IN that could potentially initiate or augment rainfall. This hypothesis is supported by previous research showing that leaf surface populations of the ice-nucleating bacterium Pseudomonas syringae increased by orders of magnitude after heavy rain and that microorganisms become airborne during and after rain in a forest ecosystem. At the sites studied in this work, aerosols that could have initiated rain from sources unrelated to previous rainfall events (such as power stations) would automatically have reduced the influences on rainfall of those whose concentrations were related to previous rain, thereby leading to inhibition of feedback. The analytical methods described here provide means to map and delimit regions where rainfall feedback mediated by microorganisms is suspected to occur or has occurred historically, thereby providing rational means to establish experimental set-ups for verification.

scholarly journals Rainfall feedback via persistent effects on bioaerosols

2014 ◽  
Vol 14 (18) ◽  
pp. 25503-25532
Author(s):  
E. K. Bigg ◽  
S. Soubeyrand ◽  
C. E. Morris
Keyword(s):  
Metropolitan Areas ◽  
Fungal Spores ◽  
Daily Rainfall ◽  
Heavy Rain ◽  
Historical Record ◽  
Feedback Process ◽  
Bacterial Populations ◽  
Power Stations ◽  
Ice Nuclei ◽  
Micro Organisms

Abstract. Consistent temporal differences between ice nucleus concentrations after and before a heavy fall of rain have been found in four areas of Australia. Closely similar differences were found between rainfall quantity or frequency at 106 sites in south-eastern and 61 sites in south-western Australia that had >92 years of daily rainfall records. The differences suggest an impulsive increase in ice nuclei or in rain on the day following heavy rain that decreased exponentially with time and was often still detectable after 20 days. The similarity of ice nucleus concentrations, bacterial populations, bioaerosols and rainfall responses to heavy rain strongly corroborate the involvement of biological ice nuclei in a rainfall feedback process. Cumulative differences of after-before rainfall amount or frequency for each rainfall event were next combined to form a historical record of the feedback process for each site. Comparison of cumulative totals pre-1960 and post-1960 showed differences bearing apparent relations to upwind coal-fired power stations, growth of metropolitan areas and increased areas of cultivation of wheat. These observations suggested that fungal spores or other bioaerosols as well as ice-nucleating bacteria were involved in the feedback. The overall conclusion is that interactions between micro-organisms, bioaerosols and rainfall have impacts over longer time spans and are stronger than have been previously described.

Future Extreme Climates Projection over Huang-Huai-Hai Region of China

2014 ◽  
Vol 955-959 ◽  
pp. 3887-3892 ◽  
Author(s):  
Huang He Gu ◽  
Zhong Bo Yu ◽  
Ji Gan Wang
Keyword(s):  
Climate Changes ◽  
Climate Model ◽  
Regional Climate ◽  
Surface Air Temperature ◽  
Daily Rainfall ◽  
Heavy Rain ◽  
Near Surface ◽  
Temperature And Precipitation ◽  
Huai River ◽  
The Future

This study projects the future extreme climate changes over Huang-Huai-Hai (3H) region in China using a regional climate model (RegCM4). The RegCM4 performs well in “current” climate (1970-1999) simulations by compared with the available surface station data, focusing on near-surface air temperature and precipitation. Future climate changes are evaluated based on experiments driven by European-Hamburg general climate model (ECHAM5) in A1B future scenario (2070-2099). The results show that the annual temperature increase about 3.4 °C-4.2 °C and the annual precipitation increase about 5-15% in most of 3H region at the end of 21st century. The model predicts a generally less frost days, longer growing season, more hot days, no obvious change in heat wave duration index, larger maximum five-day rainfall, more heavy rain days, and larger daily rainfall intensity. The results indicate a higher risk of floods in the future warmer climate. In addition, the consecutive dry days in Huai River Basin will increase, indicating more serve drought and floods conditions in this region.

scholarly journals First Report of Pseudomonas syringae pv. aptata Causing Bacterial Leaf Spot on Sugar Beet in Serbia

Plant Disease ◽  
2015 ◽  
Vol 99 (2) ◽  
pp. 281-281 ◽  
Author(s):  
V. Stojšin ◽  
J. Balaž ◽  
D. Budakov ◽  
Slaviša Stanković ◽  
I. Nikolić ◽  
...  
Keyword(s):  
Sugar Beet ◽  
Pseudomonas Syringae ◽  
Leaf Spot ◽  
Leaf Surface ◽  
Negative Control ◽  
Gyrb Gene ◽  
Bacterial Suspension ◽  
Bacterial Strains ◽  
Gene Sequences ◽  
Bacterial Leaf Spot

A severe bacterial leaf spot was observed during June and July 2013 on commercial cultivars of sugar beet (Beta vulgaris var. saccharifera) in the Vojvodina Province of Serbia. Serbia is a major sugar beet production area in southeastern Europe, with 62,895 ha and 3 million tons of sugar beet yield in 2013. A foliar leaf spot observed in 25 commercial sugar beet fields surveyed ranged from 0.1 to 40% severity. Symptoms were characterized as circular or irregular, 5- to 20-mm diameter, white to light brown necrotic spots, each with a dark margin. Diseased leaves were rinsed in sterilized, distilled water (SDW) and dried at room temperature, and leaf sections taken from the margin of necrotic tissue were macerated in SDW. Isolations from 48 symptomatic leaves onto nutrient agar with 5% (w/v) sucrose (NAS) produced bacterial colonies that were whitish, circular, dome-shaped, and Levan-positive. Representative isolates (n = 105) were Gram negative; aerobic; positive for catalase, fluorescence on King's medium B, and tobacco hypersensitivity; and negative for oxidase, potato rot, and arginine dehydrolase. These reactions corresponded to LOPAT group Ia, which includes Pseudomonas syringae pathovars (2). Repetitive extragenic palindromic sequence (rep)-PCR was used for genetic fingerprinting the isolates using the REP, ERIC, and BOX primers. Twenty-five different profiles were obtained among the strains. From each profile group, one representative strain was sequenced for the gyrB gene (1). Four heterogenic groups were observed, and representative gyrB gene sequences of each group were deposited in the NCBI GenBank (Accession Nos. KJ950024 to KJ950027). The sequences were compared with those of pathotype strain P. syringae pv. aptata CFBP 1617 deposited in the PAMDB database; one strain was 100% homologous, and the other three were 99% homologous. To fulfill identification of the Serbian sugar beet isolates, gltA and rpoD partial gene sequences were determined (1), and the sequences were deposited as Accession Nos. KM386838 to KM386841 for gltA and KM386830 to KM38683033 for rpoD. The sequences were 100% homologous with those of pathotype strain CFBP 1617. Pathogenicity of each of four representative bacterial strains was tested on 3-week-old plants of the sugar beet cultivars Marinela, Serenada, and Jasmina (KWS, Belgrade, Serbia) and Lara (NS Seme, Novi Sad, Serbia) by atomizing a bacterial suspension of ~106 CFU/ml of the appropriate isolate onto the abaxial leaf surface of three plants per cultivar until water-soaking of the leaf surface was observed. Three plants of each cultivar atomized similarly with P. syringae pv. aptata CFBP 2473 and SDW served as positive and negative control treatments, respectively. Inoculated plants were kept in a clear plastic box at 80 to 100% RH and 17 ± 1°C and examined for symptom development over 3 weeks. For all test isolates and the control strain, inoculated leaves first developed water-soaked lesions 7 days after inoculation (DAI). By 10 to 14 DAI, lesions were necrotic and infection had spread to the petioles. By 21 DAI, wilting was observed on more than 50% of inoculated plants. Negative control plants were symptomless. Bacteria re-isolated onto NAS from inoculated leaves had the same colony morphology, LOPAT results, and gyrB partial gene sequences as described for the test strains. No bacteria were re-isolated from negative control plants. Based on these tests, the pathogen causing leaf spot on sugar beet in Serbia was identified as P. syringae pv. aptata. References: (1) P. Ferrente and M. Scortichini. Plant Pathol. 59:954, 2010. (2) R. A. Lelliott et al. J. Appl. Bacteriol. 29:470, 1966.

scholarly journals Spatial structures and directionalities in Monsoonal precipitation over South Asia

2010 ◽  
Vol 17 (5) ◽  
pp. 371-381 ◽  
Author(s):  
N. Malik ◽  
N. Marwan ◽  
J. Kurths
Keyword(s):  
Indian Subcontinent ◽  
Monsoon Season ◽  
Daily Rainfall ◽  
Heavy Rain ◽  
Data Sets ◽  
Spatial Structures ◽  
Break Phase ◽  
Rainfall Events ◽  
Monsoonal Precipitation ◽  
Rain Events

Abstract. Precipitation during the monsoon season over the Indian subcontinent occurs in form of enormously complex spatiotemporal patterns due to the underlying dynamics of atmospheric circulation and varying topography. Employing methods from nonlinear time series analysis, we study spatial structures of the rainfall field during the summer monsoon and identify principle regions where the dynamics of monsoonal rainfall is more coherent or homogenous. Moreover, we estimate the time delay patterns of rain events. Here we present an analysis of two separate high resolution gridded data sets of daily rainfall covering the Indian subcontinent. Using the method of event synchronization (ES), we estimate regions where heavy rain events during monsoon happen in some lag synchronised form. Further using the delay behaviour of rainfall events, we estimate the directionalities related to the progress of such type of rainfall events. The Active (break) phase of a monsoon is characterised by an increase(decrease) of rainfall over certain regions of the Indian subcontinent. We show that our method is able to identify regions of such coherent rainfall activity.

scholarly journals A Typical Basalt Platform Landslide: Mechanism and Stability Prediction of Xiashan Landslide

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Yongliang Huang ◽  
Zhiwei Sun ◽  
Chunyan Bao ◽  
Man Huang ◽  
Anyuan Li ◽  
...  
Keyword(s):  
Rainfall Intensity ◽  
Influencing Factor ◽  
Heavy Rain ◽  
Element Model ◽  
Maximum Tensile Stress ◽  
Natural State ◽  
Landslide Area ◽  
Rainfall Frequency ◽  
Geological Conditions ◽  
Rainfall Statistics

The Xiashan landslide, which is classified as a typical basalt platform landslide, is the most massive landslide in Zhejiang Province, China. Once sliding occurs, it will pose a severe threat to the life and property of downstream residents and the nearby section of Hangzhou-Taizhou Expressway. On the basis of the geological conditions, present situation, and latest monitoring data of the landslide, this study finds that rainfall is the main influencing factor, and the creep mode is the main prediction mode of its subsequent deformation. The rainfall statistics of the landslide area in the past 30 years show that the rainfall and rainfall frequency in the landslide area display an increasing trend. The probability of heavy rain with rainfall intensity of 100–250 mm/day in the landslide area is very high. On this basis, combined with the numerical analysis method, a finite element model of the slope considering rainfall and groundwater conditions is constructed to analyze the causes and failure mechanism of this landslide comprehensively. Results indicate that the maximum tensile stress at the top of the trailing edge under the natural state is 5.10 MPa, which is very close to the saturated tensile strength of rock mass. Thus, tensile cracks are easily generated and developed, thereby causing the failure mode to be the hydraulic driving type. Also, with the increase in rainfall intensity, the slope plastic strain increases and the slope plastic zone develops and extends until it is completely penetrated. When the rainfall intensity is more than 200 mm/day, the slope safety factor is close to unity, and the slope approaches a failure condition. Therefore, the landslide should be controlled through water treatment and integrated with engineering measures.

scholarly journals Analysis of Aflatoxin Biomarkers in the Hair of Experimental Animals

Toxins ◽  
2021 ◽  
Vol 13 (8) ◽  
pp. 570
Author(s):  
Innocent Mupunga ◽  
Ilse Janse van Rensburg ◽  
Nokuthula Luthuli ◽  
Ovokeroye A. Abafe ◽  
Leshweni J. Shai ◽  
...  
Keyword(s):  
Guinea Pigs ◽  
Hair Analysis ◽  
Historical Record ◽  
Body Fluids ◽  
Urine Samples ◽  
Long Term Effects ◽  
Experimental Animals ◽  
Explorative Study ◽  
Hair Samples

Analysis of body fluids and tissues of aflatoxin exposed individuals for the presence of aflatoxins and aflatoxin metabolites has emerged as a reliable indicator of exposure and metabolism of aflatoxins. However, current aflatoxin biomarkers are not appropriate for investigating the long-term effects of aflatoxin exposure. In this explorative study, we investigated the analysis of hair as a complementary or alternative matrix for the assessment of biomarkers of long-term aflatoxin exposure. Three groups of guinea pigs were orally dosed with 5 ugkg−1bw−1, 50 ugkg−1bw−1, and 100 ugkg−1bw−1 of AFB1. Urine and hair samples were collected on days 0, 1, 2, 3, 7, 30, 60, and 90 and analysed for AFB1 and AFM1 using UHPLC-MS/MS. AFB1 and AFM1 were detected in 75% and 13.6%, respectively, of the day 1 to day 7 urine samples. AFB1 was detected in hair samples collected from day 3 up to day 60. This is the first report to confirm the deposition of AFB1 in the hair of experimental animals. These findings indicate that hair analysis has the potential to provide an accurate long-term historical record of aflatoxin exposure with potentially important implications for the field of aflatoxin biomarkers.

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