High-resolution maps of Swiss apiaries and their applicability to study spatial distribution of bacterial honey bee brood diseases

Honey bees directly affect and are influenced by their local environment, in terms of food sources, pollinator densities, pathogen and toxin exposure and climate. Currently, there is a lack of studies analyzing these data with Geographic Information Systems (GIS) to investigate spatial relationships with the environment. Particularly for inter-colonial pathogen transmission, it is known that the likelihood of a healthy colony to become infested (e.g., Varroosis) or infected (e.g., American foulbrood—AFB, European foulbrood—EFB) increases with higher colony density. Whether these transmission paths can actually be asserted at apiary level is largely unknown. Here, we unraveled spatial distribution and high-resolution density of apiaries and bacterial honey bee brood diseases in Switzerland based on available GIS data. Switzerland as ‘model country’ offers the unique opportunity to get apiary data since 2010 owing to compulsory registration for every beekeeper. Further, both destructive bee brood diseases (AFB and EFB) are legally notifiable in Switzerland, and EFB has an epizootic character for the last decades. As governmental data sets have to be ameliorated, raw data from the cantonal agricultural or veterinary offices have been included. We found a mean density of 0.56 apiaries per km2, and high resolution spatial analyzes showed strong correlation between density of apiaries and human population density as well as agricultural landscape type. Concerning two bacterial bee brood diseases (AFB, EFB), no significant correlation was detectable with density of apiaries on cantonal level, though a high correlation of EFB cases and apiary density became obvious on higher resolution (district level). Hence, Swiss EFB epizootics seem to have benefited from high apiary densities, promoting the transmission of pathogens by adult bees. The GIS-based method presented here, might also be useful for other bee diseases, anthropogenic or environmental factors affecting bee colonies.

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A new pan-European dataset for gridded daily average wind speed based on in-situ observations

10.5194/ems2021-358 ◽

2021 ◽

Author(s):

Jouke de Baar ◽

Gerard van der Schrier ◽

Irene Garcia-Marti ◽

Else van den Besselaar

Keyword(s):

Spatial Distribution ◽

High Resolution ◽

Cross Validation ◽

Data Sets ◽

Optimal Prediction ◽

Auxiliary Variables ◽

Climate Data ◽

Ensemble Spread ◽

Wind Fields

ObjectiveThe purpose of the European Copernicus Climate Change Service (C3S) is to support society by providing information about the past, present and future climate. For the service related to in-situ observations, one of the objectives is to provide high-resolution (0.1x0.1 and 0.25x0.25 degrees) gridded wind speed fields. The gridded wind fields are based on ECA&D daily average station observations for the period 1970-2020.Research question&#160;We address the following research questions: [1] How efficiently can we provide the gridded wind fields as a statistically reliable ensemble, in order to represent the uncertainty of the gridding? [2] How efficiently can we exploit high-resolution geographical auxiliary variables (e.g. digital elevation model, terrain roughness) to augment the station data from a sparse network, in order to provide gridded wind fields with high-resolution local features?ApproachIn our analysis, we apply greedy forward selection linear regression (FSLR) to include the high-resolution effects of the auxiliary variables on monthly-mean data. These data provide a &#8216;background&#8217; for the daily estimates. We apply cross-validation to avoid FSLR over-fitting and use full-cycle bootstrapping to create FSLR ensemble members. Then, we apply Gaussian process regression (GPR) to regress the daily anomalies. We consider the effect of the spatial distribution of station locations on the GPR gridding uncertainty.The goal of this work is to produce several decades of daily gridded wind fields, hence, computational efficiency is of utmost importance. We alleviate the computational cost of the FSLR and GPR analyses by incorporating greedy algorithms and sparse matrix algebra in the analyses.Novelty&#160;&#160;&#160;The gridded wind fields are calculated as a statistical ensemble of realizations. In the present analysis, the ensemble spread is based on uncertainties arising from the auxiliary variables as well as from the spatial distribution of stations.Cross-validation is used to tune the GPR hyper parameters. Where conventional GPR hyperparameter tuning aims at an optimal prediction of the gridded mean, instead, we tune the GPR hyperparameters for optimal prediction of the gridded ensemble spread.Building on our experience with providing similar gridded climate data sets, this set of gridded wind fields is a novel addition to the E-OBS climate data sets.

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Iberian autumnal precipitation characterization through observed, simulated and reanalysed data

Advances in Geosciences ◽

10.5194/adgeo-16-49-2008 ◽

2008 ◽

Vol 16 ◽

pp. 49-54 ◽

Cited By ~ 8

Author(s):

A. Morata ◽

M. Y. Luna ◽

M. L. Martín ◽

M. G. Sotillo ◽

F. Valero

Keyword(s):

Principal Component Analysis ◽

Spatial Distribution ◽

Comparative Analysis ◽

High Resolution ◽

Dynamical Downscaling ◽

Principal Component ◽

Reanalysis Data ◽

Data Sets ◽

Precipitation Data ◽

Global Reanalysis

Abstract. A 44-year (1958–2001) homogeneous Mediterranean high-resolution atmospheric database was generated through dynamical downscaling within the HIPOCAS Project framework. The present work attempts to provide a validation of the monthly 41-autumnal (1961–2001) HIPOCAS precipitation over the Iberian Peninsula, being also provided an evaluation of its improvement versus current global reanalysis data sets. A statistical comparative analysis between observed, HIPOCAS and global reanalyses precipitation data sets was carried out, highlighting the noticeable agreement existing between the observed and the HIPOCAS precipitation data sets in terms of not only time and spatial distribution, but also in terms of total amount of precipitation. A principal component analysis is carried out showing that the patterns derived from the HIPOCAS data largely capture the main characteristics of the studied field. Moreover, it is worth to note that the HIPOCAS patterns reproduce accurately the observed regional characteristics linked to the main orographic features of the study domain.

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Ultrastructural analysis of the spatial distribution of MRNA

Proceedings, annual meeting, Electron Microscopy Society of America ◽

10.1017/s0424820100123167 ◽

1992 ◽

Vol 50 (1) ◽

pp. 552-553

Author(s):

Gary Bassell ◽

Robert H. Singer

Keyword(s):

Electron Microscopy ◽

Spatial Distribution ◽

In Situ Hybridization ◽

High Resolution ◽

Nucleic Acids ◽

Colloidal Gold ◽

Dna Probe ◽

Nucleotide Analogs ◽

Gold Particles

We have been investigating the spatial distribution of nucleic acids intracellularly using in situ hybridization. The use of non-isotopic nucleotide analogs incorporated into the DNA probe allows the detection of the probe at its site of hybridization within the cell. This approach therefore is compatible with the high resolution available by electron microscopy. Biotinated or digoxigenated probe can be detected by antibodies conjugated to colloidal gold. Because mRNA serves as a template for the probe fragments, the colloidal gold particles are detected as arrays which allow it to be unequivocally distinguished from background.

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Causes and consequences of crossing-over evidenced via a high-resolution recombinational landscape of the honey bee

Genome Biology ◽

10.1186/s13059-014-0566-0 ◽

2015 ◽

Vol 16 (1) ◽

Cited By ~ 36

Author(s):

Haoxuan Liu ◽

Xiaohui Zhang ◽

Ju Huang ◽

Jian-Qun Chen ◽

Dacheng Tian ◽

...

Keyword(s):

High Resolution ◽

Honey Bee ◽

Crossing Over

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Do galactic bars depend on environment?: an information theoretic analysis of Galaxy Zoo 2

Monthly Notices of the Royal Astronomical Society ◽

10.1093/mnras/staa3665 ◽

2020 ◽

Vol 501 (1) ◽

pp. 994-1001

Author(s):

Suman Sarkar ◽

Biswajit Pandey ◽

Snehasish Bhattacharjee

Keyword(s):

Spatial Distribution ◽

Mutual Information ◽

Local Density ◽

Statistical Significance ◽

Distribution Functions ◽

Cumulative Distribution ◽

Host Galaxy ◽

Data Sets ◽

Data Set ◽

Information Theoretic

ABSTRACT We use an information theoretic framework to analyse data from the Galaxy Zoo 2 project and study if there are any statistically significant correlations between the presence of bars in spiral galaxies and their environment. We measure the mutual information between the barredness of galaxies and their environments in a volume limited sample (Mr ≤ −21) and compare it with the same in data sets where (i) the bar/unbar classifications are randomized and (ii) the spatial distribution of galaxies are shuffled on different length scales. We assess the statistical significance of the differences in the mutual information using a t-test and find that both randomization of morphological classifications and shuffling of spatial distribution do not alter the mutual information in a statistically significant way. The non-zero mutual information between the barredness and environment arises due to the finite and discrete nature of the data set that can be entirely explained by mock Poisson distributions. We also separately compare the cumulative distribution functions of the barred and unbarred galaxies as a function of their local density. Using a Kolmogorov–Smirnov test, we find that the null hypothesis cannot be rejected even at $75{{\ \rm per\ cent}}$ confidence level. Our analysis indicates that environments do not play a significant role in the formation of a bar, which is largely determined by the internal processes of the host galaxy.

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Spatio-temporal distribution patterns of Plutella xylostella (Lepidoptera: Plutellidae) in a fine-scale agricultural landscape based on geostatistical analysis

Scientific Reports ◽

10.1038/s41598-021-92562-9 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Jian-Yu Li ◽

Yan-Ting Chen ◽

Meng-Zhu Shi ◽

Jian-Wei Li ◽

Rui-Bin Xu ◽

...

Keyword(s):

Spatial Distribution ◽

Plutella Xylostella ◽

Agricultural Landscape ◽

Seasonal Pattern ◽

Distribution Patterns ◽

Geostatistical Analysis ◽

Distribution Model ◽

Detailed Knowledge ◽

Fine Scale ◽

Spatio Temporal

AbstractA detailed knowledge on the spatial distribution of pests is crucial for predicting population outbreaks or developing control strategies and sustainable management plans. The diamondback moth, Plutella xylostella, is one of the most destructive pests of cruciferous crops worldwide. Despite the abundant research on the species’s ecology, little is known about the spatio-temporal pattern of P. xylostella in an agricultural landscape. Therefore, in this study, the spatial distribution of P. xylostella was characterized to assess the effect of landscape elements in a fine-scale agricultural landscape by geostatistical analysis. The P. xylostella adults captured by pheromone-baited traps showed a seasonal pattern of population fluctuation from October 2015 to September 2017, with a marked peak in spring, suggesting that mild temperatures, 15–25 °C, are favorable for P. xylostella. Geostatistics (GS) correlograms fitted with spherical and Gaussian models showed an aggregated distribution in 21 of the 47 cases interpolation contour maps. This result highlighted that spatial distribution of P. xylostella was not limited to the Brassica vegetable field, but presence was the highest there. Nevertheless, population aggregations also showed a seasonal variation associated with the growing stage of host plants. GS model analysis showed higher abundances in cruciferous fields than in any other patches of the landscape, indicating a strong host plant dependency. We demonstrate that Brassica vegetables distribution and growth stage, have dominant impacts on the spatial distribution of P. xylostella in a fine-scale landscape. This work clarified the spatio-temporal dynamic and distribution patterns of P. xylostella in an agricultural landscape, and the distribution model developed by geostatistical analysis can provide a scientific basis for precise targeting and localized control of P. xylostella.

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Factors affecting the spatial distribution and co‐occurrence of two sympatric mountain ungulates in southern Mongolia

Journal of Zoology ◽

10.1111/jzo.12889 ◽

2021 ◽

Author(s):

C. Odonjavkhlan ◽

J.S. Alexsander ◽

C. Mishra ◽

G. Samelius ◽

K. Sharma ◽

...

Keyword(s):

Spatial Distribution ◽

Factors Affecting ◽

Mountain Ungulates

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Abrupt Temporal Fluctuations in the Chicken Fecal Microbiota Are Explained by Its Gastrointestinal Origin

Applied and Environmental Microbiology ◽

10.1128/aem.05391-11 ◽

2012 ◽

Vol 78 (8) ◽

pp. 2941-2948 ◽

Cited By ~ 65

Author(s):

M. Sekelja ◽

I. Rud ◽

S. H. Knutsen ◽

V. Denstadli ◽

B. Westereng ◽

...

Keyword(s):

Barrier Function ◽

16S Rrna Gene Sequencing ◽

Fecal Microbiota ◽

Pathogen Transmission ◽

Rrna Gene ◽

Multivariate Statistical ◽

Content Type ◽

Factors Affecting ◽

Temporal Fluctuations ◽

Gastric Barrier

ABSTRACTOne of the main challenges in understanding the composition of fecal microbiota is that it can consist of microbial mixtures originating from different gastrointestinal (GI) segments. Here, we addressed this challenge for broiler chicken feces using a direct 16S rRNA gene-sequencing approach combined with multivariate statistical analyses. Broiler feces were chosen because of easy sampling and the importance for pathogen transmission to the human food chain. Feces were sampled daily for 16 days from chickens with and without a feed structure-induced stimulation of the gastric barrier function. Overall, we found four dominant microbial phylogroups in the feces. Two of the phylogroups were related to clostridia, one to lactobacilli, and one toEscherichia/Shigella. The relative composition of these phylogroups showed apparent stochastic temporal fluctuations in feces. Analyses of dissected chickens at the end of the experiment, however, showed that the two clostridial phylogroups were correlated to the microbiota in the cecum/colon and the small intestine, while the upper gut (crop and gizzard) microbiota was correlated to the lactobacillus phylogroup. In addition, chickens with a stimulated gizzard also showed less of the proximate GI dominating bacterial group in the feces, supporting the importance of the gastric barrier function. In conclusion, our results suggest that GI origin is a main determinant for the chicken fecal microbiota composition. This knowledge will be important for future understanding of factors affecting shedding of both harmful and beneficial gastrointestinal bacteria through feces.

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High-resolution (mtDNA) melting analysis for simple and efficient characterization of Africanized honey bee Apis mellifera (Hymenoptera:Apidae)

Genetica ◽

10.1007/s10709-021-00139-1 ◽

2021 ◽

Author(s):

Leonardo P. Porrini ◽

Constanza Brasesco ◽

Matias Maggi ◽

Martín J. Eguaras ◽

Silvina Quintana

Keyword(s):

Apis Mellifera ◽

High Resolution ◽

Honey Bee ◽

Africanized Honey Bee ◽

Melting Analysis

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The seven sisters DANCe

Astronomy and Astrophysics ◽

10.1051/0004-6361/201731996 ◽

2018 ◽

Vol 612 ◽

pp. A70 ◽

Cited By ~ 5

Author(s):

J. Olivares ◽

E. Moraux ◽

L. M. Sarro ◽

H. Bouy ◽

A. Berihuete ◽

...

Keyword(s):

Spatial Distribution ◽

Model Comparison ◽

Precise Determination ◽

Model Parameters ◽

Data Sets ◽

Adequate Model ◽

Comparison Results ◽

Bayesian Evidence ◽

Mass Segregation

Context. Membership analyses of the DANCe and Tycho + DANCe data sets provide the largest and least contaminated sample of Pleiades candidate members to date. Aims. We aim at reassessing the different proposals for the number surface density of the Pleiades in the light of the new and most complete list of candidate members, and inferring the parameters of the most adequate model. Methods. We compute the Bayesian evidence and Bayes Factors for variations of the classical radial models. These include elliptical symmetry, and luminosity segregation. As a by-product of the model comparison, we obtain posterior distributions for each set of model parameters. Results. We find that the model comparison results depend on the spatial extent of the region used for the analysis. For a circle of 11.5 parsecs around the cluster centre (the most homogeneous and complete region), we find no compelling reason to abandon King’s model, although the Generalised King model introduced here has slightly better fitting properties. Furthermore, we find strong evidence against radially symmetric models when compared to the elliptic extensions. Finally, we find that including mass segregation in the form of luminosity segregation in the J band is strongly supported in all our models. Conclusions. We have put the question of the projected spatial distribution of the Pleiades cluster on a solid probabilistic framework, and inferred its properties using the most exhaustive and least contaminated list of Pleiades candidate members available to date. Our results suggest however that this sample may still lack about 20% of the expected number of cluster members. Therefore, this study should be revised when the completeness and homogeneity of the data can be extended beyond the 11.5 parsecs limit. Such a study will allow for more precise determination of the Pleiades spatial distribution, its tidal radius, ellipticity, number of objects and total mass.

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