Studies on the Housing Density of the Fowl

1968 ◽  
Vol 5 (4) ◽  
pp. 185-189
Author(s):  
MINORU NAKAZAWA ◽  
KENJI FURUTA ◽  
RYOICHI KITANO ◽  
HAJIMU GESHI
Keyword(s):  
Housing Density

Social deprivation, housing density, and gregariousness in rats.

1970 ◽  
Vol 70 (2, Pt.1) ◽  
pp. 221-227 ◽  
Author(s):  
Bibb Latane ◽  
Howard Cappell ◽  
Virginia Joy
Keyword(s):  
Social Deprivation ◽  
Housing Density

Private forests, public benefits: increased housing density and other pressures on private forest contributions

2009 ◽  
Author(s):  
Susan M. Stein ◽  
Ronald E. McRoberts ◽  
Lisa G. Mahal ◽  
Mary A. Carr ◽  
Ralph J. Alig ◽  
...  
Keyword(s):  
Private Forest ◽  
Housing Density ◽  
Private Forests ◽  
Public Benefits

The effects of population and housing density in urban areas on income in the United States

2020 ◽  
Vol 35 (1) ◽  
pp. 27-47
Author(s):  
Daniel Hummel
Keyword(s):  
United States ◽  
Urban Areas ◽  
Metropolitan Areas ◽  
Rapid Development ◽  
The United States ◽  
Housing Density ◽  
Cross Sectional ◽  
Urban Density ◽  
Urbanization Economies ◽  
Benefits And Costs

Cities in the United States have become increasingly less dense either from sprawl from rapid development or vacancy due to decline. The benefits and costs of urban density have been a topic of research since the mid-20th century. The effect of urban density on incomes is one of these areas of research. Based on concepts rooted in urbanization economies and social output, it is assumed in this paper that an increase in urban density increases incomes. Urban density is defined as population and housing density. It was found using a cross-sectional lagged mediated multiple regression that population and housing density have statistically significant indirect effects on income in a sample of more than 300 metropolitan areas in the United States. The significant effects of these variables on employment and the effect of employment on income mediated these effects.

Study on Hazard Analysis Method of Earthquake Secondary Fire Disaster in Urban Area Based on GIS

2012 ◽  
Vol 204-208 ◽  
pp. 3457-3461
Author(s):  
Tian Qi Li ◽  
Fei Geng
Keyword(s):  
Urban Areas ◽  
Hazard Analysis ◽  
Probability Model ◽  
Probability Models ◽  
Housing Density ◽  
Earthquake Excitation ◽  
Fire Disaster ◽  
High Hazard ◽  
The City ◽  
And Diffusion

In order to study the probability of occurrence of secondary fire after the earthquake in urban areas, the probability model of the hazard analysis that the fire occurred and the spread is established and applied. Probability models need to consider the destruction level of buildings under earthquake excitation as well as the probability of the leakage and diffusion of combustible material in the buildings in the corresponding destruction level, combination of weather, season, housing density and other factors to determine the probability of the single building earthquake secondary fire. On this basis , the natural administrative areas in the city as a unit , considering the factors of regional hazard analysis such as population density , property distribution and density within a region , to calculate the hazard indicator and determine the high hazard areas of secondary fire in the city. The Geographic Information System was used as the platform, to division of urban earthquake secondary fire high-hazard areas.

scholarly journals Spatial and temporal drivers of wildfire occurrence in the context of rural development in northern Wisconsin, USA

2012 ◽  
Vol 21 (2) ◽  
pp. 141 ◽  
Author(s):  
Brian R. Miranda ◽  
Brian R. Sturtevant ◽  
Susan I. Stewart ◽  
Roger B. Hammer
Keyword(s):  
Linear Regression ◽  
Land Use Planning ◽  
Temporal Trends ◽  
Point Pattern Analysis ◽  
Annual Number ◽  
Point Pattern ◽  
Linear Regression Models ◽  
Housing Density ◽  
Spatial And Temporal Scales ◽  
Wildfire Occurrence

Most drivers underlying wildfire are dynamic, but at different spatial and temporal scales. We quantified temporal and spatial trends in wildfire patterns over two spatial extents in northern Wisconsin to identify drivers and their change through time. We used spatial point pattern analysis to quantify the spatial pattern of wildfire occurrences, and linear regression to quantify the influence of drought and temporal trends in annual number and mean size of wildfires. Analyses confirmed drought as an important driver of both occurrences and fire size. When both drought and time were incorporated in linear regression models, the number of wildfires showed a declining trend across the full study area, despite housing density increasing in magnitude and spatial extent. Fires caused by campfires and debris-burning did not show any temporal trends. Comparison of spatial models representing biophysical, anthropogenic and combined factors demonstrated human influences on wildfire occurrences, especially human activity, infrastructure and property values. We also identified a non-linear relationship between housing density and wildfire occurrence. Large wildfire occurrence was predicted by similar variables to all occurrences, except the direction of influence changed. Understanding these spatial and temporal drivers of wildfire occurrence has implications for land-use planning, wildfire suppression strategies and ecological goals.

scholarly journals Influence of Porcine Housing Density on Species Diversity and Number of Airborne Microorganisms at Fattening Facilities

2006 ◽  
Vol 75 (4) ◽  
pp. 533-540 ◽  
Author(s):  
Ž. Pavičić ◽  
T. Balenović ◽  
H. Valpotić ◽  
A. Tofant ◽  
M. Popović ◽  
...  
Keyword(s):  
Species Diversity ◽  
Large Scale ◽  
Coliform Bacteria ◽  
Winter Period ◽  
Ambient Conditions ◽  
Airborne Microorganisms ◽  
Housing Density ◽  
Gram Positive Bacteria ◽  
Microclimatic Conditions ◽  
Bacteria And Fungi

Microbiological composition of air, as a factor of ambient conditions in animal facilities can significantly influence performance, health and animal welfare in the swine production. The aim of this investigation was to determine, by monitoring primary microclimatic conditions, the possible association of the number of fattening pigs per unit of housing space with species diversity and number of airborne microorganisms. The research was conducted at a fattening and finishing facility of 450 m2 (equipped with 44 pens designed for 10 animals each) with low-pressure ventilation in three different trials. The first trial was conducted during the autumn-winter period with the capacity of 440 animals (0.7 m2 of pen area per fattening pig), the second trial was conducted during the winter-spring period with 356 animals (0.8 m2 of pen area per fattening pig), and the third trial was conducted during the spring-summer period with 312 animals (1.0 m2 of pen area per fattening pig). The air samples for isolation of fungi and mesophilic, haemolytic, and coliform bacteria were taken and microclimatic conditions were monitored during each trial at the same consecutive weekly periods. According to the data obtained from all trials, the total number of bacteria and fungi did not exceed 104 and 103 CFU per m3, respectively. The most numerous were gram-positive bacteria, followed by gram-negative bacteria and fungi. The total number of airborne microorganisms correlates significantly (at p < 0.05) with porcine housing density. These data may be useful for the assessment of housing density at fattening facilities that will not compromise swine health and welfare regarding the microbiological air quality, and thus may contribute to the implementation of optimal rearing conditions in large-scale animal producing units.

Effect of housing density on alcohol consumption by rats.

1976 ◽  
Vol 37 (11) ◽  
pp. 1556-1563 ◽  
Author(s):  
R Hannon ◽  
K Donlon-Bantz
Keyword(s):  
Alcohol Consumption ◽  
Housing Density
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