Spatial Distribution of Adult Bemisia tabaci (Homoptera: Aleyrodidae) in Cotton and Development and Validation of Fixed-Precision Sampling Plans for Estimating Population Density

1995 ◽  
Vol 24 (2) ◽  
pp. 261-270 ◽  
Author(s):  
Steven E. Naranjo ◽  
Hollis M. Flint
Keyword(s):  
Spatial Distribution ◽  
Population Density ◽  
Bemisia Tabaci ◽  
Sampling Plans ◽  
Development And Validation

Binomial sampling plans for estimating and classifying population density of adult Bemisia tabaci in cotton

1996 ◽  
Vol 80 (2) ◽  
pp. 343-353 ◽  
Author(s):  
Steve E. Naranjo ◽  
Hollis M. Flint ◽  
Thomas J. Henneberry
Keyword(s):  
Population Density ◽  
Bemisia Tabaci ◽  
Sampling Plans ◽  
Binomial Sampling

Spatial Distribution and Sampling Plans for Mesoplatys ochroptera (Coleoptera: Chrysomelidae) on Sesbania

2002 ◽  
Vol 95 (2) ◽  
pp. 499-506 ◽  
Author(s):  
G. SILESHI ◽  
J. BAUMGÄRTNER ◽  
S. SITHANANTHAM ◽  
C. K. P. O. OGOL
Keyword(s):  
Spatial Distribution ◽  
Sampling Plans ◽  
Mesoplatys Ochroptera

scholarly journals A Quantitative Evaluation of the Multiple Narratives of the Recent Sahelian Regreening*

2016 ◽  
Vol 8 (1) ◽  
pp. 67-83 ◽  
Author(s):  
Mimi Stith ◽  
Alessandra Giannini ◽  
John del Corral ◽  
Susana Adamo ◽  
Alex de Sherbinin
Keyword(s):  
Spatial Distribution ◽  
Population Density ◽  
Environmental Change ◽  
Burkina Faso ◽  
Social Dimensions ◽  
Adaptation To Climate Change ◽  
Southern Central ◽  
Second Category ◽  
The Impact

Abstract A spatial analysis is presented that aims to synthesize the evidence for climate and social dimensions of the “regreening” of the Sahel. Using an independently constructed archival database of donor-funded interventions in Burkina Faso, Mali, Niger, and Senegal in response to the persistence of drought in the 1970s and 1980s, the spatial distribution of these interventions is examined in relation to population density and to trends in precipitation and in greenness. Three categories of environmental change are classified: 1) regions at the northern grassland/shrubland edge of the Sahel where NDVI varies interannually with precipitation, 2) densely populated cropland regions of the Sahel where significant trends in precipitation and NDVI decouple at interannual time scales, and 3) regions at the southern savanna edge of the Sahel where NDVI variation is independent of precipitation. Examination of the spatial distribution of environmental change, number of development projects, and population density brings to the fore the second category, covering the cropland areas where population density and regreening are higher than average. While few, regions in this category coincide with emerging hotspots of regreening in northern Burkina Faso and southern central Niger known from case study literature. In examining the impact of efforts to rejuvenate the Sahelian environment and livelihoods in the aftermath of the droughts of the 1970s and 1980s against the backdrop of a varying and uncertain climate, the transition from desertification to regreening discourses is framed in the context of adaptation to climate change.

scholarly journals Geospatial characterizing of Under-Five Mortality in Alexandria, Egypt

2021 ◽  
Author(s):  
Mahmoud Adel Hassan ◽  
Ahmed Mohamed Ramadan ◽  
Mohamed Mostafa Tahoun ◽  
Abdelrahman Omran ◽  
Shimaa Gad El-karim Ali ◽  
...  
Keyword(s):  
Cardiac Arrest ◽  
Spatial Distribution ◽  
Cardiovascular Diseases ◽  
Population Density ◽  
Spatial Pattern ◽  
Under Five ◽  
Size Population ◽  
Access To Water ◽  
Alexandria City ◽  
Low Incidence

This study aimed to identify geo-spatial pattern of under-five mortality (U5M) in Alexandria and its key determinants. We analyzed the geospatial distribution of 3064 deaths registered at 24 health offices reported from January 2018 to June 2019. The localities of Alexandria city were clustered into high and low incidence areas. Neonates represented 58.7% of U5M, while post-neonates and children were 31.1%, 10.2% respectively. Male deaths were significantly higher (P=0.036). The main leading causes of U5M were prematurity (28.32%), pneumonia (11.01%), cardiac arrest (10.57%), congenital malformation (9.95%), and childhood cardiovascular diseases (9.20%). Spatial distribution of U5M (including the most common three causes) tend to be clustered in western parts of Alexandria (El Hawaria, Bahig, Hamlis and Ketaa Maryiut). Another 9 clusters are at risk of being hotspots. Illiteracy, divorce, and poor locality characteristics (household size, population density, and access to water supply and sanitation), were statistically significant predictors of U5M.

Population Ecology and Spatial Distribution of Whitefly, Bemisia tabaci, (Homoptera: Aleyrodidae) on Brinjal

2021 ◽  
pp. 54-61
Author(s):  
Z. Mohd Rasdi ◽  
I. Fauziah ◽  
K. Fairuz ◽  
M. S. Mohd Saiful
Keyword(s):  
Spatial Distribution ◽  
Bemisia Tabaci ◽  
Population Ecology

Remarks on the spatial distribution of a reproducing population

1977 ◽  
Vol 14 (03) ◽  
pp. 577-583 ◽  
Author(s):  
J. F. C. Kingman
Keyword(s):  
Spatial Distribution ◽  
Population Density ◽  
Poisson Process ◽  
Limiting Distribution ◽  
Statistical Equilibrium ◽  
Spatially Distributed ◽  
Simple Models

Several authors have noted that simple models for the evolution of a reproducing and spatially distributed population have no limiting distribution, although a Poisson process in statistical equilibrium has sometimes been implicitly assumed. It is shown that, even when a mechanism for restricting population density is postulated, a Poisson process is usually impossible to achieve, essentially because of an assumption of independent displacements. When this assumption is abandoned, a Poisson process is possible, at least for some highly idealised models.

scholarly journals Spatial distribution pattern and sequential sampling plans for Bactrocera oleae (Gmelin) (Dip: Tephritidae) in olive orchards

2016 ◽  
Vol 48 (1) ◽  
pp. 23
Author(s):  
A. Arbab ◽  
F. Mirphakhar
Keyword(s):  
Spatial Distribution ◽  
Sample Size ◽  
Sequential Sampling ◽  
Bactrocera Oleae ◽  
Sampling Plans ◽  
Optimum Sample Size ◽  
Precision Level ◽  
The Individual ◽  
Optimum Sample ◽  
Basic Distribution

The distribution of adult and larvae <em>Bactrocera oleae</em> (Diptera: Tephritidae), a key pest of olive, was studied in olive orchards. The first objective was to analyze the dispersion of this insect on olive and the second was to develop sampling plans based on fixed levels of precision for estimating <em>B. oleae</em> populations. The Taylor’s power law and Iwao’s patchiness regression models were used to analyze the data. Our results document that Iwao’s patchiness provided a better description between variance and mean density. Taylor’s <em>b</em> and Iwao’s <em>β</em> were both significantly more than 1, indicating that adults and larvae had aggregated spatial distribution. This result was further supported by the calculated common <em>k</em> of 2.17 and 4.76 for adult and larvae, respectively. Iwao’s a for larvae was significantly less than 0, indicating that the basic distribution component of <em>B. oleae</em> is the individual insect. Optimal sample sizes for fixed precision levels of 0.10 and 0.25 were estimated with Iwao’s patchiness coefficients. The optimum sample size for adult and larvae fluctuated throughout the seasons and depended upon the fly density and desired level of precision. For adult, this generally ranged from 2 to 11 and 7 to 15 traps to achieve precision levels of 0.25 and 0.10, respectively. With respect to optimum sample size, the developed fixed-precision sequential sampling plans was suitable for estimating flies density at a precision level of D=0.25. Sampling plans, presented here, should be a tool for research on pest management decisions of <em>B. oleae</em>.

scholarly journals Population Distribution in the Wake of a Sphere

Symmetry ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 1498 ◽  
Author(s):  
Taraprasad Bhowmick ◽  
Yong Wang ◽  
Michele Iovieno ◽  
Gholamhossein Bagheri ◽  
Eberhard Bodenschatz
Keyword(s):  
Reynolds Number ◽  
Spatial Distribution ◽  
Population Density ◽  
Density Distribution ◽  
Population Distribution ◽  
Fluid Velocity ◽  
Three Dimensional ◽  
Wake Flow ◽  
Sample Number ◽  
Scalar Fluxes

The physics of heat and mass transfer from an object in its wake has significant importance in natural phenomena as well as across many engineering applications. Here, we report numerical results on the population density of the spatial distribution of fluid velocity, pressure, scalar concentration, and scalar fluxes of a wake flow past a sphere in the steady wake regime (Reynolds number 25 to 285). Our findings show that the spatial population distributions of the fluid and the transported scalar quantities in the wake follow a Cauchy-Lorentz or Lorentzian trend, indicating a variation in its sample number density inversely proportional to the squared of its magnitude. We observe this universal form of population distribution both in the symmetric wake regime and in the more complex three dimensional wake structure of the steady oblique regime with Reynolds number larger than 225. The population density distribution identifies the increase in dimensionless kinetic energy and scalar fluxes with the increase in Reynolds number, whereas the dimensionless scalar population density shows negligible variation with the Reynolds number. Descriptive statistics in the form of population density distribution of the spatial distribution of the fluid velocity and the transported scalar quantities is important for understanding the transport and local reaction processes in specific regions of the wake, which can be used e.g., for understanding the microphysics of cloud droplets and aerosol interactions, or in the technical flows where droplets interact physically or chemically with the environment.

Sign in / Sign up

Export Citation Format

Share Document