The limiting properties of population distributions with particular application to manpower planning

1983 ◽  
Vol 20 (1) ◽  
pp. 19-30 ◽  
Author(s):  
Mark Woodward
Keyword(s):  
Population Size ◽  
Stable Distribution ◽  
Population Distribution ◽  
Manpower Planning ◽  
Expected Value ◽  
Practical Applications ◽  
Population Distributions ◽  
Number Of Classes

A model for predicting expected-value population distributions is developed, assuming that all movements are Markovian and time-homogeneous. Each individual is classified by the amount of time he has spent in the population and by which of a number of classes, of an unspecified nature, he inhabits. The limiting properties of the population distribution are derived, and, in particular, conditions for convergence to a stable distribution are given.Some discussion of the relevance of the theory to practical applications is given, primarily to manpower planning when recruitment occurs purely to maintain a specified overall population size.

The limiting properties of population distributions with particular application to manpower planning

1983 ◽  
Vol 20 (01) ◽  
pp. 19-30 ◽  
Author(s):  
Mark Woodward
Keyword(s):  
Population Size ◽  
Stable Distribution ◽  
Population Distribution ◽  
Manpower Planning ◽  
Expected Value ◽  
Practical Applications ◽  
Population Distributions ◽  
Number Of Classes

A model for predicting expected-value population distributions is developed, assuming that all movements are Markovian and time-homogeneous. Each individual is classified by the amount of time he has spent in the population and by which of a number of classes, of an unspecified nature, he inhabits. The limiting properties of the population distribution are derived, and, in particular, conditions for convergence to a stable distribution are given. Some discussion of the relevance of the theory to practical applications is given, primarily to manpower planning when recruitment occurs purely to maintain a specified overall population size.

scholarly journals Research on Human Travel Correlation for Urban Transport Planning Based on Multisource Data

Sensors ◽  
2020 ◽  
Vol 21 (1) ◽  
pp. 195
Author(s):  
Hua Chen ◽  
Ming Cai ◽  
Chen Xiong
Keyword(s):  
Travel Demand ◽  
Population Distribution ◽  
Human Mobility ◽  
Urban Transport ◽  
License Plate ◽  
Traffic Patterns ◽  
Trajectory Data ◽  
Transport Planning ◽  
Population Distributions ◽  
Single Dataset

With the rapid development of positioning techniques, a large amount of human travel trajectory data is collected. These datasets have become an effective data resource for obtaining urban traffic patterns. However, many traffic analyses are only based on a single dataset. It is difficult to determine whether a single-dataset-based result can meet the requirement of urban transport planning. In response to this problem, we attempted to obtain traffic patterns and population distributions from the perspective of multisource traffic data using license plate recognition (LPR) data and cellular signaling (CS) data. Based on the two kinds of datasets, identification methods of residents’ travel stay point are proposed. For LPR data, it was identified based on different vehicle speed thresholds at different times. For CS data, a spatiotemporal clustering algorithm based on time allocation was proposed to recognize it. We then used the correlation coefficient r and the significance test p-values to analyze the correlations between the CS and LPR data in terms of the population distribution and traffic patterns. We studied two real-world datasets from five working days of human mobility data and found that they were significantly correlated for the stay and move population distributions. Then, the analysis scale was refined to hour level. We also found that they still maintain a significant correlation. Finally, the origin–destination (OD) matrices between traffic analysis zones (TAZs) were obtained. Except for a few TAZs with poor correlations due to the fewer LPR records, the correlations of the other TAZs remained high. It showed that the population distribution and traffic patterns computed by the two datasets were fairly similar. Our research provides a method to improve the analysis of complex travel patterns and behaviors and provides opportunities for travel demand modeling and urban transport planning. The findings can also help decision-makers understand urban human mobility and can serve as a guide for urban management and transport planning.

scholarly journals Ecological and evolutionary dynamics of interconnectedness and modularity

2018 ◽  
Vol 115 (4) ◽  
pp. 750-755 ◽  
Author(s):  
Jan M. Nordbotten ◽  
Simon A. Levin ◽  
Eörs Szathmáry ◽  
Nils C. Stenseth
Keyword(s):  
Population Dynamics ◽  
Natural Selection ◽  
Evolution Equation ◽  
Evolutionary Dynamics ◽  
Population Distribution ◽  
Theoretical Framework ◽  
Ecological System ◽  
Macro Level ◽  
Population Distributions ◽  
Trait Space

In this contribution, we develop a theoretical framework for linking microprocesses (i.e., population dynamics and evolution through natural selection) with macrophenomena (such as interconnectedness and modularity within an ecological system). This is achieved by developing a measure of interconnectedness for population distributions defined on a trait space (generalizing the notion of modularity on graphs), in combination with an evolution equation for the population distribution. With this contribution, we provide a platform for understanding under what environmental, ecological, and evolutionary conditions ecosystems evolve toward being more or less modular. A major contribution of this work is that we are able to decompose the overall driver of changes at the macro level (such as interconnectedness) into three components: (i) ecologically driven change, (ii) evolutionarily driven change, and (iii) environmentally driven change.

scholarly journals Estimation of population distributions of habitual nutrient intakebased on a short-run weighed food diary

2000 ◽  
Vol 83 (3) ◽  
pp. 287-293 ◽  
Author(s):  
Clifton Gay
Keyword(s):  
Nutrient Intake ◽  
Population Distribution ◽  
Random Component ◽  
Food Diary ◽  
Nutrient Intakes ◽  
Diary Data ◽  
Population Distributions ◽  
Short Run ◽  
Nationally Representative

There have been many attempts to characterize day-to-day variation in nutrient intake. This variation has a fixed component, associated with particular days of the week, and a random component. Both components were studied for a range of nutrients, using 4 d weighed diary data from a large, nationally representative survey of people aged 65 years or over. Since day-to-day variation may distort the characterization of the population distribution of habitual nutrient intakes, especially when diets are studied over only a small number of days, a statistical method was developed to correct for this distortion. Results suggested that population distributions of habitual nutrient intake could be accurately constructed from 4 d weighed diary data and that the method might be successfully applied to studies based on as little as 2 d of observation. The method is particularly valuable for correcting estimates of extreme nutrient intakes for biases induced by uneven representation of days of the week and by within-person variation.

scholarly journals Estimating Hilly Areas Population Using a Dasymetric Mapping Approach: A Case of Sri Lanka’s Highest Mountain Range

2019 ◽  
Vol 8 (4) ◽  
pp. 166 ◽  
Author(s):  
Ananda Karunarathne ◽  
Gunhak Lee
Keyword(s):  
Land Use ◽  
Population Distribution ◽  
Estimation Methods ◽  
Mountain Range ◽  
Dasymetric Mapping ◽  
Ancillary Data ◽  
Hilly Area ◽  
Fine Grain ◽  
Population Distributions ◽  
Gis Environment

Since populations in the developing world have been rapidly increasing, accurately determining the population distribution is becoming more critical for many countries. One of the most widely used population density estimation methods is dasymetric mapping. This can be defined as a precise method for areal interpolation between different spatial units. In most applications of dasymetric mapping, land use and land cover data have been considered as ancillary data for the areal disaggregation process. This research presents an alternative dasymetric approach using area specific ancillary data for hilly area population mapping in a GIS environment. Specifically, we propose a Hilly Area Dasymetric Mapping (HDM) technique by combining topographic variables and land use to better disaggregate hilly area population distribution at fine-grain division of ancillary units. Empirical results for Sri Lanka’s highest mountain range show that the combined dasymetric approach estimates hilly area population most accurately and because of the significant association that is found to exist between topographic variables and population distribution within this setting. This research is expected to have significant implications for national and regional planning by providing useful information about actual population distributions in environmentally hazardous and sparsely populated areas.

scholarly journals Challenges of ecological monitoring: estimating population abundance from sparse trap counts

2011 ◽  
Vol 9 (68) ◽  
pp. 420-435 ◽  
Author(s):  
Natalia Petrovskaya ◽  
Sergei Petrovskii ◽  
Archie K. Murchie
Keyword(s):  
Population Size ◽  
Numerical Integration ◽  
Spatial Data ◽  
Population Distribution ◽  
Species Abundance ◽  
Ecological Monitoring ◽  
Field Studies ◽  
Pest Species ◽  
Population Size Estimates ◽  
Size Estimates

Ecological monitoring aims to provide estimates of pest species abundance—this information being then used for making decisions about means of control. For invertebrate species, population size estimates are often based on trap counts which provide the value of the population density at the traps' location. However, the use of traps in large numbers is problematic as it is costly and may also be disruptive to agricultural procedures. Therefore, the challenge is to obtain a reliable population size estimate from sparse spatial data. The approach we develop in this paper is based on the ideas of numerical integration on a coarse grid. We investigate several methods of numerical integration in order to understand how badly the lack of spatial data can affect the accuracy of results. We first test our approach on simulation data mimicking spatial population distributions of different complexity. We show that, rather counterintuitively, a robust estimate of the population size can be obtained from just a few traps, even when the population distribution has a highly complicated spatial structure. We obtain an estimate of the minimum number of traps required to calculate the population size with good accuracy. We then apply our approach to field data to confirm that the number of trap/sampling locations can be much fewer than has been used in many monitoring programmes. We also show that the accuracy of our approach is greater that that of the statistical method commonly used in field studies. Finally, we discuss the implications of our findings for ecological monitoring practice and show that the use of trap numbers ‘smaller than minimum’ may still be possible but it would result in a paradigm shift: the population size estimates should be treated probabilistically and the arising uncertainty may introduce additional risk in decision-making.

scholarly journals The Polycentric Dynamics of Melbourne and Sydney: suburb attractiveness divides a city at the home ownership level

2021 ◽  
Vol 477 (2245) ◽  
pp. 20200514
Author(s):  
Emanuele Crosato ◽  
Mikhail Prokopenko ◽  
Michael S. Harré
Keyword(s):  
Population Distribution ◽  
Home Ownership ◽  
Critical Threshold ◽  
Political Factors ◽  
Urban Dynamics ◽  
Complex Interactions ◽  
Population Distributions ◽  
Long Run ◽  
Two Cities

Urban dynamics in large metropolitan areas result from complex interactions across social, economic and political factors, including population distribution, flows of wealth and infrastructure requirements. We develop a Census-calibrated model of urban dynamics for the Greater Sydney and Melbourne areas for 2011 and 2016, highlighting the evolution of population distributions and the housing market structure in these two cities in terms of their mortgage and rent distributions. We show that there is a tendency to homophily between renters and mortgage holders: renters tend to cluster nearer commercial centres, whereas mortgagors tend to populate the outskirts of these centres. We also identify a critical threshold at which the long-term evolution of these two cities will bifurcate between a ‘sprawling’ and a ‘polycentric’ configuration, showing that both cities lie on the polycentric side of the critical point in the long-run. Importantly, there is a divergence of these centric tendencies between the renters and mortgage holders. The polycentric patterns characterizing the mortgagors are focused around commercial centres, and we show that the emergent housing patterns follow the major transport routes through the cities.

scholarly journals Can More Accurate Night-Time Remote Sensing Data Simulate a More Detailed Population Distribution?

2019 ◽  
Vol 11 (16) ◽  
pp. 4488 ◽  
Author(s):  
Nannan Gao ◽  
Fen Li ◽  
Hui Zeng ◽  
Daniël van Bilsen ◽  
Martin De Jong
Keyword(s):  
Remote Sensing ◽  
Urban Areas ◽  
Large Scale ◽  
Population Distribution ◽  
Remote Sensing Data ◽  
Urban Land Use ◽  
Residential Areas ◽  
Night Time ◽  
Sensing Data ◽  
Population Distributions

Aging, shrinking cities, urban agglomerations and other new key terms continue to emerge when describing the large-scale population changes in various cities in mainland China. It is important to simulate the distribution of residential populations at a coarse scale to manage cities as a whole, and at a fine scale for policy making in infrastructure development. This paper analyzes the relationship between the DN (Digital number, value assigned to a pixel in a digital image) value of NPP-VIIRS (the Suomi National Polar-orbiting Partnership satellite’s Visible Infrared Imaging Radiometer Suite) and LuoJia1-01 and the residential populations of urban areas at a district, sub-district, community and court level, to compare the influence of resolution of remote sensing data by taking urban land use to map out auxiliary data in which first-class (R1), second-class (R2) and third-class residential areas (R3) are distinguished by house price. The results show that LuoJia1-01 more accurately analyzes population distributions at a court level for second- and third-class residential areas, which account for over 85% of the total population. The accuracy of the LuoJia1-01 simulation data is higher than that of Landscan and GHS (European Commission Global Human Settlement) population. This can be used as an important tool for refining the simulation of residential population distributions. In the future, higher-resolution night-time light data could be used for research on accurate simulation analysis that scales down large-scale populations.

Some Effects of Parameter Uncertainty in Density-Independent and Density-Dependent Leslie Models for Fish Populations

1981 ◽  
Vol 38 (1) ◽  
pp. 91-100 ◽  
Author(s):  
R. V. O'Neill ◽  
R. H. Gardner ◽  
S. W. Christensen ◽  
W. Van Winkle ◽  
J. H. Carney ◽  
...  
Keyword(s):  
Population Size ◽  
Striped Bass ◽  
Total Population ◽  
White Perch ◽  
Model Parameters ◽  
Prediction Errors ◽  
Total Population Size ◽  
Density Dependent ◽  
Truncated Normal ◽  
Number Of Classes

Density-independent and density-dependent Leslie models were investigated by Monte Carlo methods. Random values for parameters of striped bass (Morone saxatilis), white perch (Morone americanus), and tomcod (Microgadus tomcod) populations were selected from truncated normal distributions with standard deviations equal to 10% of the mean. Only total population size after 40 yr was considered. The error propagation properties of the density-independent models are strongly influenced by model assumptions (e.g. calculating egg to 1-yr-old survival to ensure an eigenvalue of 1.0) and by the way model parameters are estimated (e.g. reestimated from data each year). Prediction errors on total population size depend on the number of age-classes in a species, but become insensitive when the number of classes exceed 7. Under the very restrictive assumptions used here, there is little difference in the error propagating properties of alternative density-dependent models.Key words: matrix, population, striped bass, white perch, tomcod

Ten years of the resource-based habitat paradigm: the biotope-habitat issue and implications for conserving butterfly diversity

2014 ◽  
Vol 2 (8) ◽  
pp. 1 ◽  
Author(s):  
Roger L. H. Dennis ◽  
Leonardo Dapporto ◽  
John W. Dover
Keyword(s):  
Population Size ◽  
Basic Problem ◽  
Population Distribution ◽  
Range Size ◽  
Population Status ◽  
Population Changes ◽  
Butterfly Diversity ◽  
The Status ◽  
Species Evolution ◽  
Habitat Parameters

The widely used term ‘habitat’ underlies all aspects of a species’ (and community’s) population size, consequently population changes, distribution and range size and changes; ultimately, habitat parameters determine the status of species, whether thriving or threatened with extinction. Habitat parameters also lie at the root of species’ evolution (speciation) involving cycles of resource specialism/generalism. A basic problem is that habitat has long been treated as synonymous with biotope. But, the two variable terms habitat and biotope describe very different phenomena and we make a case for clarity in the use of the term ‘habitat’, especially when the focus is conserving biodiversity. In this review, in reference to butterflies, we distinguish habitat from biotope as a real, grounded resources-based and conditions-based entity, and explain how usage of the terms greatly affects our perception of population status, and of population, distribution, range and speciation processes, central to conserving biodiversity.

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