scholarly journals Stability of Patches of Higher Population Density within the Heterogenous Distribution of the Gray Field Slug Deroceras reticulatum in Arable Fields in the UK

Insects ◽  
2020 ◽  
Vol 12 (1) ◽  
pp. 9
Author(s):  
Emily Forbes ◽  
Matthew Back ◽  
Andrew Brooks ◽  
Natalia B. Petrovskaya ◽  
Sergei V. Petrovskii ◽  
...  
Keyword(s):  
Linear Models ◽  
Hot Spot ◽  
Temporal Stability ◽  
Soil Surface ◽  
Deroceras Reticulatum ◽  
Arable Fields ◽  
Regular Sampling ◽  
Spatio Temporal ◽  
Adverse Environmental Conditions ◽  
The Uk

Exploitation of heterogenous distributions of Deroceras reticulatum, in arable fields by targeting molluscicide applications toward areas with higher slug densities, relies on these patches displaying sufficient spatio-temporal stability. Regular sampling of slug activity/distribution was undertaken using 1 ha rectangular grids of 100 refuge traps established in 22 commercial arable field crops. Activity varied significantly between the three years of the study, and the degree of aggregation (Taylor’s Power Law) was higher in fields with higher mean trap catches. Hot spot analysis detected statistically significant spatial clusters in all fields, and in 162 of the 167 individual assessment visits. The five assessment visits in which no clusters were detected coincided with low slug activity (≤0.07 per trap). Generalized Linear Models showed significant spatial stability of patches in 11 fields, with non-significant fields also characterized by low slug activity (≤1.2 per trap). Mantel’s permutation tests revealed a high degree of correlation between location of individual patches between sampling dates. It was concluded that patches of higher slug density were spatio-temporally stable, but detection using surface refuge traps (which rely on slug activity on the soil surface) was less reliable when adverse environmental conditions resulted in slugs retreating into the upper soil horizons.

scholarly journals Surveillance of genetic diversity and evolution in locally transmitted SARS-CoV-2 in Pakistan during the first wave of the COVID-19 pandemic

2021 ◽  
Author(s):  
Muhammad Shakeel ◽  
Muhammad Irfan ◽  
Zaibunnisa ◽  
Muhammad Rashid ◽  
Sabeeta Kanwal Ansari ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Hot Spot ◽  
Spike Protein ◽  
Independent Events ◽  
Recurrent Mutations ◽  
The Usa ◽  
Spatio Temporal ◽  
B Lineage ◽  
The Uk ◽  
The City

AbstractSurveillance of genetic diversity in the SARS-CoV-2 is extremely important to detect the emergence of more infectious and deadly strains of the virus. In this study, we monitored mutational events in the SARS-CoV-2 genome through whole genome sequencing. The samples (n=48) were collected from the hot spot regions of the metropolitan city Karachi, Pakistan during the four months (May 2020 to August 2020) of first wave of the COVID-19 pandemic. The data analysis highlighted 122 mutations, including 120 single nucleotide variations (SNV), and 2 deletions. Among the 122 mutations, there were 71 singletons, and 51 recurrent mutations. A total of 16 mutations, including 5 nonsynonymous mutations, were detected in spike protein. Notably, the spike protein missense mutation D614G was observed in 31 genomes. The phylogenetic analysis revealed majority of the genomes (36) classified as B lineage, where 2 genomes were from B.6 lineage, 5 genomes from B.1 ancestral lineage and remaining from B.1 sub-lineages. It was noteworthy that three clusters of B.1 sub-lineages were observed, including B.1.36 lineage (10 genomes), B.1.160 lineage (11 genomes), and B.1.255 lineage (5 genomes), which represent independent events of SARS-CoV-2 transmission within the city. The sub-lineage B.1.36 had higher representation from the Asian countries and the UK, B.1.160 correspond to the European countries with highest representation from the UK, Denmark, and lesser representation from India, Saudi Arabia, France and Switzerland, and the third sub-lineage (B.1.255) correspond to the USA. Collectively, our study provides meaningful insight into the evolution of SARS-CoV-2 lineages in spatio-temporal local transmission during the first wave of the pandemic.

scholarly journals Establishment and lineage dynamics of the SARS-CoV-2 epidemic in the UK

Science ◽  
2021 ◽  
pp. eabf2946
Author(s):  
Louis du Plessis ◽  
John T. McCrone ◽  
Alexander E. Zarebski ◽  
Verity Hill ◽  
Christopher Ruis ◽  
...  
Keyword(s):  
Large Scale ◽  
Phylogenetic Analyses ◽  
Transmission Dynamics ◽  
Genetic Lineage ◽  
Size Dependent ◽  
Spatio Temporal ◽  
The Uk ◽  
Lineage Structure ◽  
And Control ◽  
Lineage Diversity

The UK’s COVID-19 epidemic during early 2020 was one of world’s largest and unusually well represented by virus genomic sampling. Here we reveal the fine-scale genetic lineage structure of this epidemic through analysis of 50,887 SARS-CoV-2 genomes, including 26,181 from the UK sampled throughout the country’s first wave of infection. Using large-scale phylogenetic analyses, combined with epidemiological and travel data, we quantify the size, spatio-temporal origins and persistence of genetically-distinct UK transmission lineages. Rapid fluctuations in virus importation rates resulted in >1000 lineages; those introduced prior to national lockdown tended to be larger and more dispersed. Lineage importation and regional lineage diversity declined after lockdown, while lineage elimination was size-dependent. We discuss the implications of our genetic perspective on transmission dynamics for COVID-19 epidemiology and control.

scholarly journals Does Entrepreneurship Contribute to Innovation Performance When Considering Spatial Spillover Effects? Evidence From the Automobile Industrial Cluster in China

SAGE Open ◽  
2020 ◽  
Vol 10 (4) ◽  
pp. 215824402098299
Author(s):  
Haishi Li ◽  
Xiangyi Xu ◽  
Shuaishuai Li
Keyword(s):  
Automobile Industry ◽  
Hot Spots ◽  
Hot Spot ◽  
Empirical Support ◽  
Temporal Patterns ◽  
Spillover Effects ◽  
Industrial Clusters ◽  
Innovation Performance ◽  
Spatial Spillover ◽  
Spatio Temporal

Entrepreneurship, as one of the important factors to promote industrial innovation, is closely related to the development of the regional economy. Based on the methods of Kernel density and standard deviation ellipse, this article presents the spatio-temporal patterns of entrepreneurship and innovation performance. The article also examines the spatial spillover mechanism of entrepreneurship on innovation performance by establishing spatial Durbin models. The heterogeneous results of the spatial regression models in six clusters are also discussed. The final results show that the spatio-temporal patterns of entrepreneurship are gradually presenting three major hot spots and two secondary hot spots while the spatio-temporal patterns of innovation performance are presenting four major hot spots and a secondary hot spot; the spatial distribution of both entrepreneurship and innovation performance are changing regularly; the spillover effects of entrepreneurship and innovation performance are both significant; the spatial spillover mechanisms in six automobile industrial clusters are different. The results can provide empirical support for decision-making in the automobile industry in China in the future.

scholarly journals Spatio-Temporal Variation of the Bacterial Communities along a Salinity Gradient within a Thalassohaline Environment (Saline di Tarquinia Salterns, Italy)

Molecules ◽  
2021 ◽  
Vol 26 (5) ◽  
pp. 1338
Author(s):  
Susanna Gorrasi ◽  
Andrea Franzetti ◽  
Roberto Ambrosini ◽  
Francesca Pittino ◽  
Marcella Pasqualetti ◽  
...  
Keyword(s):  
Bacterial Diversity ◽  
Generalized Linear Models ◽  
Bacterial Communities ◽  
Linear Models ◽  
Salinity Gradient ◽  
Sampling Site ◽  
Α Diversity ◽  
Spatio Temporal ◽  
Abundance Variation ◽  
Microbiological Aspects

The “Saline di Tarquinia” salterns have been scarcely investigated regarding their microbiological aspects. This work studied the structure and composition of their bacterial communities along the salinity gradient (from the nearby sea through different ponds). The communities showed increasing simplification of pond bacterial diversity along the gradient (particularly if compared to those of the sea). Among the 38 assigned phyla, the most represented were Proteobacteria, Actinobacteria and Bacteroidetes. Differently to other marine salterns, where at the highest salinities Bacteroidetes dominated, preponderance of Proteobacteria was observed. At the genus level the most abundant taxa were Pontimonas, Marivita, Spiribacter, Bordetella, GpVII and Lentibacter. The α-diversity analysis showed that the communities were highly uneven, and the Canonical Correspondence Analysis indicated that they were structured by various factors (sampling site, sampling year, salinity, and sampling month). Moreover, the taxa abundance variation in relation to these significant parameters were investigated by Generalized Linear Models. This work represents the first investigation of a marine saltern, carried out by a metabarcoding approach, which permitted a broad vision of the bacterial diversity, covering both a wide temporal span (two years with monthly sampling) and the entire salinity gradient (from the nearby sea up to the crystallisation ponds).

scholarly journals Spatiotemporal mapping and detection of mortality cluster due to cardiovascular disease with Bayesian hierarchical framework using integrated nested Laplace approximation: A discussion of suitable statistic applications in Kersa, Oromia, Ethiopia

2018 ◽  
Vol 13 (2) ◽  
Author(s):  
Melkamu Dedefo ◽  
Henry Mwambi ◽  
Sileshi Fanta ◽  
Nega Assefa
Keyword(s):  
Cause Of Death ◽  
Linear Models ◽  
Temporal Distribution ◽  
Mortality Data ◽  
Contributing Factors ◽  
Bayesian Hierarchical ◽  
Hierarchical Framework ◽  
Temporal Models ◽  
Spatio Temporal ◽  
Non Parametric

Cardiovascular diseases (CVDs) are the leading cause of death globally and the number one cause of death globally. Over 75% of CVD deaths take place in low- and middle-income countries. Hence, comprehensive information about the spatio-temporal distribution of mortality due to cardio vascular disease is of interest. We fitted different spatio-temporal models within Bayesian hierarchical framework allowing different space-time interaction for mortality mapping with integrated nested Laplace approximations to analyze mortality data extracted from the health and demographic surveillance system in Kersa District in Hararege, Oromia Region, Ethiopia. The result indicates that non-parametric time trends models perform better than linear models. Among proposed models, one with non-parametric trend, type II interaction and second order random walk but without unstructured time effect was found to perform best according to our experience and. simulation study. An application based on real data revealed that, mortality due to CVD increased during the study period, while administrative regions in northern and south-eastern part of the study area showed a significantly elevated risk. The study highlighted distinct spatiotemporal clusters of mortality due to CVD within the study area. The study is a preliminary assessment step in prioritizing areas for further and more comprehensive research raising questions to be addressed by detailed investigation. Underlying contributing factors need to be identified and accurately quantified.

scholarly journals Shift in the Spatio-Temporal Natural Fruiting of Boletes in West African Woodlands: the Key Role of the Soil Moisture

2020 ◽  
Author(s):  
Akotchayé Sylvestre Badou ◽  
Roel D. Houdanon ◽  
Kassim I. Tchan ◽  
D.M.T. Apollon Hègbè ◽  
Nourou Soulemane Yorou
Keyword(s):  
Species Richness ◽  
Soil Moisture ◽  
Ectomycorrhizal Fungi ◽  
Linear Models ◽  
Positive Influence ◽  
Permanent Plots ◽  
Data Logger ◽  
Fresh Biomass ◽  
Natural Production ◽  
Spatio Temporal

Abstract Background: The ectomycorrhizal fungi display strong fluctuations during the mycological season. However, how abiotic parameters affect the fruiting sequences of ectomycorrhizal fungi and also the direction and extent of this effect are not yet tapped adequately. The present study seeks to assess the microclimate effect on the natural production of boletes. Nine permanent plots of 2500 m2 (50m x 50m) split into 25 subplots of 100 m2 (10m x 10m) were installed in three different vegetation dominated respectively by Isoberlinia doka, Isoberlinia tomentosa and Uapaca togoensis. Microclimatic parameters were recorded each 30 minutes throughout by mean of a Micro Station Data Logger - H21-002 the mycological seasons. Each plot was surveyed twice a week (from May to October) over three years (2015, 2016 and 2017) to record the presence/absence of fruit bodies and fresh biomass of boletes. To evaluate the effect of time and microclimate variables on natural production, we used mixed effects and generalized linear models using R version 3.5.3. Results: In total, during the three years (2015, 2016 and 2017), we recorded 14 species of boletes. Species richness does not change over time (P > 0.05). In addition, fresh biomass varies within years and vegetation (P < 0.05). The combination of year and month of collection has a significant effect on the number of fruit bodies (P < 0.05). Only the soil moisture has a significant positive influence on the species richness of boletes (P > 0.05). Conclusions: When the soil moisture decreases by four units, the number of fruit bodies of ectomycorrhizal fungi is significantly reduced by one unit. Therefore, above 0.25 m3 / m3 and below 0.05 m3 / m3 there is a decrease in the number of fruit bodies.

Germination strategy of the East African savanna tree Acacia tortilis

2005 ◽  
Vol 21 (5) ◽  
pp. 509-517 ◽  
Author(s):  
Paul E. Loth ◽  
Willem F. de Boer ◽  
Ignas M. A. Heitkönig ◽  
Herbert H. T. Prins
Keyword(s):  
National Park ◽  
Laboratory Experiments ◽  
Perennial Grass ◽  
Soil Surface ◽  
Bare Soil ◽  
Acacia Tortilis ◽  
East African ◽  
Tree Canopies ◽  
Arable Fields ◽  
Germination Success

Germination of Acacia tortilis seeds strongly depends on micro-site conditions. In Lake Manyara National Park, Tanzania, Acacia tortilis occurs abundantly in recently abandoned arable fields and in elephant-mediated gaps in acacia woodland, but does not regenerate in grass swards or beneath canopies. We examined the germination of Acacia tortilis using field and laboratory experiments. Seeds placed on top of the soil rarely germinated, while seeds covered with elephant dung or buried under the soil surface had a germination success between 23–43%. On bare soil 39% of both the dung-covered and buried seeds germinated, in perennial grass swards 24–43%, and under tree canopies 10–24% respectively. In laboratory experiments, seed water absorption correlated positively with temperature up to 41 °C, while subsequent germination was optimal at lower (21–23 °C) temperatures. Seeds that had absorbed water lost their viability when kept above 35.5 °C. The absence of light did not significantly influence germination success. Acacia tortilis does not actively disperse its seeds, but regeneration outside tree canopies was substantial. The regeneration potential thus strongly depends on the physiognomy of the vegetation.

Spatio-Temporal Hot Spot Analysis of Epidemic Diseases Using Geographic Information System for Improved Healthcare

2019 ◽  
pp. 31-63
Author(s):  
Uma V. ◽  
Jayanthi Ganapathy
Keyword(s):  
Health Care ◽  
Spatial Analysis ◽  
Health Care Services ◽  
Hot Spot ◽  
Care Services ◽  
Treatment And Prevention ◽  
Epidemiology Data ◽  
Care Systems ◽  
Spatio Temporal ◽  
Using Data

Health-care systems aid in the diagnosis, treatment and prevention of diseases. Epidemiology deals with the demographic study on frequency, distribution and determinants of disease in order to provide better health-care. Today information technology has made data pervasive i.e. data is available anywhere and in abundance. GIS in epidemiology enables prompt services to mankind or people at risk. It brings out health-care services that are amicable for prevention and control of disease spread. This could be achieved when epidemiology data is modeled considering temporal and spatial factors and using data driven computation techniques over such models. This chapter discusses 1) the need for integrating GIS and epidemiology, 2) various case studies that indicates the need for spatial analysis being performed on epidemiologic data, 3) few techniques involved in the spatial analysis, 4) functionalities provided by some of the widely used GIS software packages and tools.

scholarly journals Size and Persistence of Nitrous Oxide Hot-Spots in Grazed and Ungrazed Grassland

2015 ◽  
Vol 5 (4) ◽  
pp. 1 ◽  
Author(s):  
Paul R. Hargreaves ◽  
Robert M. Rees ◽  
Graham W. Horgan ◽  
Bruce C. Ball
Keyword(s):  
Nitrous Oxide ◽  
Soil Temperature ◽  
Hot Spots ◽  
Hot Spot ◽  
Nutrient Input ◽  
Young Stock ◽  
Spatial And Temporal Heterogeneity ◽  
The Mean ◽  
To Come ◽  
The Uk

<p class="1Body">Nitrous oxide (N<sub>2</sub>O) emissions from agriculture contributed an estimated 60% of the global total in 2005. In the UK, grassland soils account for 30% of total emissions, 22% of which are estimated to come from urine and dung patches. These patches are possible sources of ‘hot-spots’ (area <em>ca.</em> 1 m<sup>2</sup>) of N<sub>2</sub>O fluxes. Spatial and temporal heterogeneity of N<sub>2</sub>O hot-spot fluxes were investigated in three grassland fields (grazed with dairy cows (DG), grazed with young stock (YG) or cut for silage (SC)) using gas sampling chambers surrounding historic hot-spots to establish their size. Fluxes from old dung and urine patches were measured, as well as freshly applied dung and urine to simulate the creation of hot-spots. Potential chemical and physical drivers were also measured. Large spatial variability of N<sub>2</sub>O fluxes was seen in all three grassland fields. Mean N<sub>2</sub>O fluxes for the historic hot-spots in the grazed fields (DG and YG) were significantly greater than (SC). The mean N<sub>2</sub>O fluxes in DG and YG (117.9 and 243.5 ng N m<sup>-2</sup> s<sup>-1</sup>) were 15 to 30% greater than for SC. Soil temperature (15 - 20 °C) was the most significant driver of N<sub>2</sub>O production with a 1°C rise in soil temperature increasing emissions under DG and YG. N<sub>2</sub>O fluxes were enhanced by the fresh dung but not by urine. However, in the urine treatment, the nutrient input increased the microbial respiration response for the CO<sub>2</sub> flux. Hot-spot N<sub>2</sub>O emissions from old urine and dung patches were persistent several months after application.</p>

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