scholarly journals Spatial Distribution of Hunting Billbugs (Coleoptera: Curculionidae) in Sod Farms

Insects ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 402
Author(s):  
Midhula Gireesh ◽  
Jhalendra P. Rijal ◽  
Shimat V. Joseph
Keyword(s):  
Spatial Distribution ◽  
Spatial Dependence ◽  
Normal Growth ◽  
Distribution Patterns ◽  
Spatial Distributions ◽  
Pitfall Traps ◽  
Soil Cores ◽  
Distribution Maps ◽  
Aggregation Pattern ◽  
History Of

The hunting billbug, Sphenophorus venatus vestitus Chittenden (Coleoptera: Curculionidae), is an important turfgrass pest, especially in sod farms. S. venatus vestitus larvae feed on the stems and roots of turfgrass. Damaged turfgrass is loosely held together and poses a challenge for machine harvesting. Additionally, the normal growth of turfgrass is affected, especially after winter dormancy. Because S. venatus vestitus larvae are hidden inside the stems or under the soil, larval management is challenging. To improve sampling and management, the spatial distribution patterns of S. venatus vestitus larvae and adults were assessed at four sod farm sites with a history of S. venatus vestitus infestation in central Georgia (USA). The larvae were sampled by soil cores using a hole cutter, whereas adults were collected using pitfall traps for 7 d. The spatial distributions of larvae and adults was analyzed using SADIE and variograms. The SADIE and variogram analyses revealed a significant aggregation pattern for adults, whereas aggregated distributions were detected for larvae with variogram analyses. The average ranges of spatial dependence for larval and adult samples were 3.9 m and 5.4 m, respectively. Interpolated distribution maps were created to visually depict S. venatus vestitus infestation hotspots within the sod farms.

Spatial distribution of physico-chemical parameters for groundwater quality evaluation in a part of Satluj River Basin, India

2019 ◽  
Vol 19 (5) ◽  
pp. 1480-1490 ◽  
Author(s):  
Akshay Kumar Chaudhry ◽  
Kamal Kumar ◽  
Mohammad Afaq Alam
Keyword(s):  
Spatial Distribution ◽  
Groundwater Quality ◽  
Spatial Dependence ◽  
Groundwater Resources ◽  
Quality Parameters ◽  
Northern Region ◽  
Total Hardness ◽  
Data Set ◽  
Distribution Maps ◽  
Physico Chemical

Abstract The rising population, contamination and mismanagement of groundwater worldwide require sustainable management techniques and strategies to prevent misuse of groundwater resources especially in the semi-arid regions of the world. The aim of the present study is to assess the distribution of contaminants in groundwater at a spatial level by using a geostatistical method, namely ordinary kriging. For this, a physico-chemical parameter data set at 14 sampling locations for a period over 25 years was assessed. Three semi-variogram models, namely exponential, Gaussian and spherical, fitted well for the data set and were cross-validated using predictive statistics. Based on nugget/sill ratio, which characterizes the overall spatial dependence of water quality parameters, it was observed that, apart from nitrate, all the other parameters showed moderate to weak spatial dependence (i.e. total hardness), indicating significant influence of urbanization, fertilization and industrialization. Spatial distribution maps of all the parameters were generated. Concentration of most of the parameters reported high values in the northern region, while silicon dioxide and potassium recorded high values in the southern and central regions of the study area respectively. The study highlighted the depleting groundwater resources in various regions of the study area, indicating that the groundwater quality is in a declining state.

spatial distribution patterns of basking sharks on the european shelf: preliminary comparison of satellite-tag geolocation, survey and public sightings data

2005 ◽  
Vol 85 (5) ◽  
pp. 1083-1088 ◽  
Author(s):  
e.j. southall ◽  
d.w. sims ◽  
j.d. metcalfe ◽  
j.i. doyle ◽  
s. fanshawe ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Population Distribution ◽  
Distribution Patterns ◽  
Irish Sea ◽  
Distribution Maps ◽  
North East ◽  
The North ◽  
Current Concerns ◽  
Clyde Sea ◽  
Satellite Tag

current concerns about the population levels of the basking shark (cetorhinus maximus) in the north-east atlantic have prompted a need to understand population distribution, habitat preference and centres of abundance. in this study, spatial distribution maps derived from satellite-tag geolocations, boat surveys and public sightings data were compared. the broad distribution patterns revealed by these different methods are similar, but there are considerable differences in density distributions. surface sightings data show high densities, or ‘hotspots’ in the hebridean sea, clyde sea, irish sea and close inshore around devon and cornwall. tag geolocations, in contrast, identified two areas where individuals spent considerable time outside the distributions indicated by surveys and public sightings: the celtic sea and western approaches of the english channel. the reason for this disparity and its implications for population estimates for the species are discussed.

scholarly journals Análise espacial da mosca-negra em sistema agroflorestal de citros

2015 ◽  
Vol 6 (3) ◽  
pp. 350
Author(s):  
Anderson Gonçalves Silva ◽  
Paulo Roberto Silva Farias ◽  
Arlindo Leal Boiça Junior ◽  
Bruno Gonçaves Lima ◽  
Nara Helena Tavares da Ponte ◽  
...  
Keyword(s):  
Spatial Distribution ◽  
Spatial Dependence ◽  
Spherical Model ◽  
Sampling Point ◽  
Kriging Method ◽  
Citrus Orchard ◽  
Black Fly ◽  
Distribution Maps ◽  
Experimental Area ◽  
Aleurocanthus Woglumi

The aim of this study was to characterize the spatial distribution of citrus black fly (Aleurocanthus woglumi) in citrus orchard in agroforestry plantation in Pará State, Brazil. The experimental area is located in Capitão Poço, Northeastern Pará. Twelve samples were taken monthly where the presence or absence of the pest in the experimental area were evaluated. From each sampling point (plant) we obtained the value of the variable and the coordinates (latitude and longitude). By the parameters of semivariogram models the surveys were interpolated by kriging method which provided us spatial distribution maps of the areas of higher and lower infestation of the black fly. The results showed that the spatial distribution of black fly takes place predominantly in clusters with spatial dependence described by the spherical model, forming clusters from 15.5 to 34 m (range of the model).

Spatial Distribution Patterns of Weed Communities in Corn Fields of Central Spain

Weed Science ◽  
2015 ◽  
Vol 63 (4) ◽  
pp. 936-945 ◽  
Author(s):  
Carolina San Martín ◽  
Dionisio Andújar ◽  
Cesar Fernández-Quintanilla ◽  
José Dorado
Keyword(s):  
Spatial Distribution ◽  
Distribution Patterns ◽  
Scale Dependence ◽  
Individual Species ◽  
Weed Species ◽  
Central Spain ◽  
Purple Nutsedge ◽  
Spatial Distribution Patterns ◽  
Distribution Maps ◽  
Sampling Grid

The overall objective of this study was to identify common patterns in the spatial distribution of the major weed species present in the corn-growing region of central Spain, exploring the scale dependence of these patterns and the possible associations or dissociations between individual species. Weed density was assessed in 16 commercial fields using digital images acquired in a 9-m by 9-m sampling grid. A set of six species was found in all the fields: black nightshade, common cocklebur, fierce thornapple, johnsongrass, purple nutsedge, and velvetleaf. Spatial analysis by distance indices and inverse distance weighting interpolation methods were performed to create weed distribution maps. The results showed aggregated spatial distribution patterns for all individual species regardless their life cycle, annual or perennial. Some associations and dissociations among species were found in the analysis of interactions. Nevertheless, the spatial patterns of co-occurrence of weed species were field-specific and therefore cannot be considered general patterns of weed co-occurrence. In order to explore the scale dependence of these results, an additional study was conducted in an experimental field located in the same area using a 1.0-m by 0.75-m sampling grid. Although this resolution allowed for a better definition of the positions of the weed patches and weed-free gaps, the results obtained revealed similar patterns to those observed with a coarser sampling resolution.

Modeling spatial distribution of the unionid mussels and the core-satellite hypothesis

1998 ◽  
Vol 38 (7) ◽  
pp. 73-79 ◽  
Author(s):  
Hooi-Ling Lee ◽  
Donald DeAngelis ◽  
Hock-Lye Koh
Keyword(s):  
Spatial Distribution ◽  
Life Cycle ◽  
Success Rate ◽  
Distribution Patterns ◽  
Fish Host ◽  
Limited Movement ◽  
Unionid Mussels ◽  
Species Characteristics ◽  
Major Factors ◽  
Fish Hosts

This paper discusses the spatial distribution patterns of the various species of the Unionid mussels as functions of their respective life-cycle characteristics. Computer simulations identify two life-cycle characteristics as major factors governing the abundance of a species, namely the movement range of their fish hosts and the success rate of the parasitic larval glochidia in finding fish hosts. Core mussels species have fish hosts with large movement range to disperse the parasitic larval glochidia to achieve high levels of abundance. Species associated with fish host of limited movement range require high success rate of finding fish host to achieve at least an intermediate level of abundance. Species with low success rate of finding fish hosts coupled with fish hosts having limited movement range exhibit satellite species characteristics, namely rare in numbers and sparse in distributions.

scholarly journals Computing infection distributions and longitudinal evolution patterns in lung CT images

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Dongdong Gu ◽  
Liyun Chen ◽  
Fei Shan ◽  
Liming Xia ◽  
Jun Liu ◽  
...  
Keyword(s):  
Time Course ◽  
Lower Lobe ◽  
Ground Truth ◽  
Distribution Patterns ◽  
Lung Infection ◽  
Ct Images ◽  
Community Acquired Pneumonia ◽  
Disease Course ◽  
Distribution Maps ◽  
Significant Difference

Abstract Background Spatial and temporal lung infection distributions of coronavirus disease 2019 (COVID-19) and their changes could reveal important patterns to better understand the disease and its time course. This paper presents a pipeline to analyze statistically these patterns by automatically segmenting the infection regions and registering them onto a common template. Methods A VB-Net is designed to automatically segment infection regions in CT images. After training and validating the model, we segmented all the CT images in the study. The segmentation results are then warped onto a pre-defined template CT image using deformable registration based on lung fields. Then, the spatial distributions of infection regions and those during the course of the disease are calculated at the voxel level. Visualization and quantitative comparison can be performed between different groups. We compared the distribution maps between COVID-19 and community acquired pneumonia (CAP), between severe and critical COVID-19, and across the time course of the disease. Results For the performance of infection segmentation, comparing the segmentation results with manually annotated ground-truth, the average Dice is 91.6% ± 10.0%, which is close to the inter-rater difference between two radiologists (the Dice is 96.1% ± 3.5%). The distribution map of infection regions shows that high probability regions are in the peripheral subpleural (up to 35.1% in probability). COVID-19 GGO lesions are more widely spread than consolidations, and the latter are located more peripherally. Onset images of severe COVID-19 (inpatients) show similar lesion distributions but with smaller areas of significant difference in the right lower lobe compared to critical COVID-19 (intensive care unit patients). About the disease course, critical COVID-19 patients showed four subsequent patterns (progression, absorption, enlargement, and further absorption) in our collected dataset, with remarkable concurrent HU patterns for GGO and consolidations. Conclusions By segmenting the infection regions with a VB-Net and registering all the CT images and the segmentation results onto a template, spatial distribution patterns of infections can be computed automatically. The algorithm provides an effective tool to visualize and quantify the spatial patterns of lung infection diseases and their changes during the disease course. Our results demonstrate different patterns between COVID-19 and CAP, between severe and critical COVID-19, as well as four subsequent disease course patterns of the severe COVID-19 patients studied, with remarkable concurrent HU patterns for GGO and consolidations.

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

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.

scholarly journals Spatial Dependence Evaluation of Agricultural Technical Efficiency—Based on the Stochastic Frontier and Spatial Econometric Model

2021 ◽  
Vol 13 (5) ◽  
pp. 2708
Author(s):  
Ziqi Yin ◽  
Jianzhai Wu
Keyword(s):  
Spatial Distribution ◽  
Technical Efficiency ◽  
Spatial Dependence ◽  
Stochastic Frontier ◽  
Hebei Province ◽  
Agricultural Technology ◽  
Agricultural Product ◽  
Spatial Econometric ◽  
Frontier Analysis ◽  
The Impact

In recent years, through the implementation of a series of policies, such as the delimitation of major grain producing areas and the construction of advantageous and characteristic agricultural product areas, the spatial distribution of agriculture in China has changed significantly; however, research on the impact of such changes on the efficiency of agricultural technology is still lacking. Taking 11 cities in Hebei Province as the research object, this study examines the spatial dependence of regional agricultural technical efficiency using the stochastic frontier analysis and spatial econometric analysis. The results show that the improvement in agricultural technical efficiency is evident in all cities in Hebei Province from 2008 to 2017, but there is scope for further improvement. Industrial agglomeration has statistical significance in improving the efficiency of agricultural technology. Further, there is an obvious spatial correlation and difference in agricultural technical efficiency. Optimizing the spatial distribution of agricultural production, promoting the innovation, development, and application of agricultural technology, and promoting the expansion of regional elements can contribute to improving agricultural technical efficiency.

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