Human Population Reduction Is Not a Quick Fix for Environmental Problems
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Globalization and Infectious Diseases: a Review of the Linkages
TDR/STR/SEB/ST/04.2 SPECIAL TOPICS NO.3 Globalization and infectious diseases: A review of the linkages Social, Economic and Behavioural (SEB) Research UNICEF/UNDP/World Bank/WHO Special Programme for Research & Training in Tropical Diseases (TDR) The "Special Topics in Social, Economic and Behavioural (SEB) Research" series are peer-reviewed publications commissioned by the TDR Steering Committee for Social, Economic and Behavioural Research. For further information please contact: Dr Johannes Sommerfeld Manager Steering Committee for Social, Economic and Behavioural Research (SEB) UNDP/World Bank/WHO Special Programme for Research and Training in Tropical Diseases (TDR) World Health Organization 20, Avenue Appia CH-1211 Geneva 27 Switzerland E-mail: [email protected] TDR/STR/SEB/ST/04.2 Globalization and infectious diseases: A review of the linkages Lance Saker,1 MSc MRCP Kelley Lee,1 MPA, MA, D.Phil. Barbara Cannito,1 MSc Anna Gilmore,2 MBBS, DTM&H, MSc, MFPHM Diarmid Campbell-Lendrum,1 D.Phil. 1 Centre on Global Change and Health London School of Hygiene & Tropical Medicine Keppel Street, London WC1E 7HT, UK 2 European Centre on Health of Societies in Transition (ECOHOST) London School of Hygiene & Tropical Medicine Keppel Street, London WC1E 7HT, UK TDR/STR/SEB/ST/04.2 Copyright © World Health Organization on behalf of the Special Programme for Research and Training in Tropical Diseases 2004 All rights reserved. The use of content from this health information product for all non-commercial education, training and information purposes is encouraged, including translation, quotation and reproduction, in any medium, but the content must not be changed and full acknowledgement of the source must be clearly stated. -
Litter Pollution in Densely Versus Sparsely Populated Areas: Dog River Watershed
LITTER POLLUTION IN DENSELY VERSUS SPARSELY POPULATED AREAS: DOG RIVER WATERSHED Gabrielle M. Hudson, Department of Earth Sciences, University of South Alabama, Mobile, AL 36688. E-mail: [email protected]. It is commonly known that when humans populate an area that area is usually subject to some environmental degradation. One of the more common aspects of environmental degradation is litter. This type of degradation is no stranger to the Dog River watershed. For years residents have seen the rivers in this watershed covered in trash, specifically after rain events. The vast majority of the trash is a result of litter from roadsides being carried into the river via drainage pipes. This paper is a comparative study of litter in areas of varying population densities in the Dog River watershed. It seeks to distinguish between the amount of litter found in densely populated areas and sparsely populated areas, and to find out if there is a correlation between population density and litter. I utilize GIS to map population density of the Dog River watershed, and analyze and compare the amounts of litter in areas of sparse and dense populations. The results show that there is no correlation between population density and litter. It also shows that there is no difference in the amounts of litter found in densely and sparsely populated areas. Keyword: litter, population density, watershed Introduction Pollution has long been an issue in the Dog River watershed, in particular litter pollution. The extent of the pollution has not gone unnoticed. There are groups of people and organizations who have taken increased interest in the Dog River watershed with intentions of reducing pollution, including Dog River Clearwater Revival and its numerous volunteers. -
Modeling Population Dynamics
Modeling Population Dynamics Gary C. White INTRODUCTION Population modeling is a tool used by wildlife managers. At its simplest, population modeling is a book keeping system to keep track of the four components of population change: births, deaths, immigration, and emigration. In mathematical symbolism, a population model can be expressed as Nt+1 = Nt + Bt - Dt + It - Et . Population size (N) at time t+1 is equal to the population size at time t plus births (B) minus deaths (D) plus immigrants (I) minus emigrants (E). The simplicity of the relationship belies its usefulness. If you were managing a business, you would be interested in knowing how much money was being paid out of the business, relative to how much money was coming in. The net difference represents your “profit”. The same is true for managing a wildlife population. By knowing the net change in the size of the wildlife population from one year to the next, you as a wildlife manager know whether the population is “profitable” (i.e., gaining in size), or headed towards bankruptcy (i.e., becoming smaller). Two examples will demonstrate typical uses of population models in big game management. In November 1995, voters in Colorado passed an amendment to the state’s constitution that outlawed hunting black bears during spring. Wildlife managers were asked if the bear population would increase because of no spring harvest. A population model can be used to answer this question. The second example of the use of a model is to determine which of two management schemes (e.g., no antlerless harvest versus significant antlerless harvest) will result in Modeling Population Dynamics – Draft May 6, 1998 2 the largest buck harvest in a mule deer population. -
Immigration and the Stable Population Model
IMMIGRATION AND THE STABLE POPULATION MODEL Thomas J. Espenshade The Urban Institute, 2100 M Street, N. W., Washington, D.C. 20037, USA Leon F. Bouvier Population Reference Bureau, 1337 Connecticut Avenue, N. W., Washington, D.C. 20036, USA W. Brian Arthur International Institute for Applied Systems Analysis, A-2361 Laxenburg, Austria RR-82-29 August 1982 Reprinted from Demography, volume 19(1) (1982) INTERNATIONAL INSTITUTE FOR APPLIED SYSTEMS ANALYSIS Laxenburg, Austria Research Reports, which record research conducted at IIASA, are independently reviewed before publication. However, the views and opinions they express are not necessarily those of the Institute or the National Member Organizations that support it. Reprinted with permission from Demography 19(1): 125-133, 1982. Copyright© 1982 Population Association of America. All rights reserved. No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage or retrieval system, without permission in writing from the copyright holder. iii FOREWORD For some years, IIASA has had a keen interest in problems of population dynamics and migration policy. In this paper, reprinted from Demography, Thomas Espenshade, Leon Bouvier, and Brian Arthur extend the traditional methods of stable population theory to populations with below-replacement fertility and a constant annual quota of in-migrants. They show that such a situation results in a stationary population and examine how its size and ethnic structure depend on both the fertility level and the migration quota. DEMOGRAPHY© Volume 19, Number 1 Februory 1982 IMMIGRATION AND THE STABLE POPULATION MODEL Thomos J. -
Mathematical Analysis of Population Growth Subject to Environmental Change
SCIENTIA MANU E T MENTE MATHEMATICAL ANALYSIS OF POPULATION GROWTH SUBJECT TO ENVIRONMENTAL CHANGE A thesis submitted for the degree of Doctor of Philosophy By Hamizah Mohd Safuan M.Sc.(Mathematics) Applied and Industrial Mathematics Research Group, School of Physical, Environmental and Mathematical Sciences, The University of New South Wales, Canberra, Australian Defence Force Academy. November 2014 PLEASE TYPE THE UNIVERSITY OF NEW SOUTH WALES Thesis/Dissertation Sheet Surname or Family name: Mohd Safuan First name: Hamizah Other name/s: - Abbreviation for degree as given in the University calendar: Ph.D (Mathematics) School: Faculty: UNSW Canberra School of Physical, Environmental and Mathematical Sciences Tille: Mathematical analysis of population growth subject lo environmental change Abstract 350 words maximum: (PLEASE TYPE) Many ecosystems are pressured when the environment is perturbed, such as when resources are scarce, or even when they are over-abundant. Changes in the environment impact on its ability lo support a population of a given species. However, most current models do not lake the changing environment into consideration. The standard approach in modelling a population in its environment is lo assume that the carrying capacity, which is a proxy for the state of the environment, is unchanging. In effect, the assumption also posits that the population is negligible compared lo the environment and cannot alter the carrying capacity in any way. Thus, modelling the interplay of the population with its environments is important lo describe varying factors that exist in the system. This objective can be achieved by treating the carrying capacity as lime- and space-dependent variables in the governing equations of the model. -
Math 636 - Mathematical Modeling Discrete Modeling 1 Discrete Modeling – Population of the United States U
Discrete Modeling { Population of the United States Discrete Modeling { Population of the United States Variation in Growth Rate Variation in Growth Rate Autonomous Models Autonomous Models Outline Math 636 - Mathematical Modeling Discrete Modeling 1 Discrete Modeling { Population of the United States U. S. Population Malthusian Growth Model Programming Malthusian Growth Joseph M. Mahaffy, 2 Variation in Growth Rate [email protected] General Discrete Dynamical Population Model Linear Growth Rate U. S. Population Model Nonautonomous Malthusian Growth Model Department of Mathematics and Statistics Dynamical Systems Group Computational Sciences Research Center 3 Autonomous Models San Diego State University Logistic Growth Model San Diego, CA 92182-7720 Beverton-Holt Model http://jmahaffy.sdsu.edu Analysis of Autonomous Models Fall 2018 Discrete Modeling U. S. Population | Discrete Modeling U. S. Population | Joseph M. Mahaffy, [email protected] (1/34) Joseph M. Mahaffy, [email protected] (2/34) Discrete Modeling { Population of the United States Discrete Modeling { Population of the United States Malthusian Growth Model Malthusian Growth Model Variation in Growth Rate Variation in Growth Rate Programming Malthusian Growth Programming Malthusian Growth Autonomous Models Autonomous Models United States Census Census Data Census Data United States Census 1790 3,929,214 1870 39,818,449 1950 150,697,361 Constitution requires census every 10 years 1800 5,308,483 1880 50,189,209 1960 179,323,175 Census used for budgeting federal payments and representation -
Simulation of Working Population Exposures to Carbon Monoxide Using EXPOLIS-Milan Microenvironment Concentration and Time-Activity Data
Journal of Exposure Analysis and Environmental Epidemiology (2004) 14, 154–163 r 2004 Nature Publishing GroupAll rights reserved 1053-4245/04/$25.00 www.nature.com/jea Simulation of working population exposures to carbon monoxide using EXPOLIS-Milan microenvironment concentration and time-activity data YURI BRUINEN DE BRUIN,a,b,c OTTO HA¨ NNINEN,b PAOLO CARRER,a MARCO MARONI,a STYLIANOS KEPHALOPOULOS,c GRETA SCOTTO DI MARCOc AND MATTI JANTUNENb aDepartment of Occupational Health, University of Milan, Via San Barnaba 8, 20122 Milan, Italy bKTL, Department of Environmental Health, P.O. Box 95, FIN-70701, Kuopio, Finland cEC Joint Research Centre, Institute for Health and Consumer Protection, Via E. Fermi, 21020 (VA), Ispra, Italy Current air pollution levels have been shown to affect human health. Probabilistic modeling can be used to assess exposure distributions in selected target populations. Modeling can and should be used to compare exposures in alternative future scenarios to guide society development. Such models, however, must first be validated using existing data for a past situation. This study applied probabilistic modeling to carbon monoxide (CO) exposures using EXPOLIS-Milan data. In the current work, the model performance was evaluated by comparing modeled exposure distributions to observed ones. Model performance was studied in detail in two dimensions; (i) for different averaging times (1, 8 and 24 h) and (ii) using different detail in defining the microenvironments in the model (two, five and 11 microenvironments). (iii) The number of exposure events leading to 8-h guideline exceedance was estimated. Population time activity was modeled using a fractions-of-time approach assuming that some time is spent in each microenvironment used in the model. -
Harvesting in a Resource Dependent Age Structured Leslie Type
1 Final version Harvesting in a resource dependent age structured Leslie type population model Rui Dilão1, Tiago Domingos1 and Elman M. Shahverdiev1,2 1) Grupo de Dinâmica Não-Linear, Instituto Superior Técnico, Av. Rovisco Pais, 1049- 001 Lisboa, Portugal. 2) Institute of Physics, 33, H. Javid Avenue, 370143 Baku, Azerbaijan. Short Title: Harvesting in a resource dependent model. Corresponding author: Rui Dilão Grupo de Dinâmica Não-Linear, Instituto Superior Técnico Av. Rovisco Pais, 1049-001 Lisbon, Portugal [email protected] Phone (351)218417617; Fax (351)218419123. 2 Abstract We analyse the effect of harvesting in a resource dependent age structured population model, deriving the conditions for the existence of a stable steady state as a function of fertility coefficients, harvesting mortality and carrying capacity of the resources. Under the effect of proportional harvest, we give a sufficient condition for a population to extinguish, and we show that the magnitude of proportional harvest depends on the resources available to the population. We show that the harvesting yield can be periodic, quasi-periodic or chaotic, depending on the dynamics of the harvested population. For populations with large fertility numbers, small harvesting mortality leads to abrupt extinction, but larger harvesting mortality leads to controlled population numbers by avoiding over consumption of resources. Harvesting can be a strategy in order to stabilise periodic or quasi-periodic oscillations in the number of individuals of a population. Key words: harvesting, age structured population models, population extinction. 3 1. Introduction In natural environments and in the laboratory the number of individuals of a population change in time in different ways. -
A Non-Linear Threshold Estimation of Density Effects
sustainability Article Population Dynamics and Agglomeration Factors: A Non-Linear Threshold Estimation of Density Effects Mariateresa Ciommi 1, Gianluca Egidi 2, Rosanna Salvia 3 , Sirio Cividino 4, Kostas Rontos 5 and Luca Salvati 6,7,* 1 Department of Economic and Social Science, Polytechnic University of Marche, Piazza Martelli 8, I-60121 Ancona, Italy; [email protected] 2 Department of Agricultural and Forestry Sciences (DAFNE), Tuscia University, Via San Camillo de Lellis, I-01100 Viterbo, Italy; [email protected] 3 Department of Mathematics, Computer Science and Economics, University of Basilicata, Viale dell’Ateneo Lucano, I-85100 Potenza, Italy; [email protected] 4 Department of Agriculture, University of Udine, Via del Cotonificio 114, I-33100 Udine, Italy; [email protected] 5 Department of Sociology, School of Social Sciences, University of the Aegean, EL-81100 Mytilene, Greece; [email protected] 6 Department of Economics and Law, University of Macerata, Via Armaroli 43, I-62100 Macerata, Italy 7 Global Change Research Institute of the Czech Academy of Sciences, Lipová 9, CZ-37005 Ceskˇ é Budˇejovice, Czech Republic * Correspondence: [email protected] or [email protected] Received: 14 February 2020; Accepted: 11 March 2020; Published: 13 March 2020 Abstract: Although Southern Europe is relatively homogeneous in terms of settlement characteristics and urban dynamics, spatial heterogeneity in its population distribution is still high, and differences across regions outline specific demographic patterns that require in-depth investigation. In such contexts, density-dependent mechanisms of population growth are a key factor regulating socio-demographic dynamics at various spatial levels. Results of a spatio-temporal analysis of the distribution of the resident population in Greece contributes to identifying latent (density-dependent) processes of metropolitan growth over a sufficiently long time interval (1961-2011). -
Global Typology of Urban Energy Use and Potentials for An
Global typology of urban energy use and potentials for SPECIAL FEATURE an urbanization mitigation wedge Felix Creutziga,b,1, Giovanni Baiocchic, Robert Bierkandtd, Peter-Paul Pichlerd, and Karen C. Setoe aMercator Research Institute on Global Commons and Climate Change, 10829 Berlin, Germany; bTechnische Universtität Berlin, 10623 Berlin, Germany; cDepartment of Geographical Sciences, University of Maryland, College Park, MD 20742; dPotsdam Institute for Climate Impact Research, 14473 Potsdam, Germany; and eYale School of Forestry & Environmental Studies, New Haven, CT 06511 Edited by Sangwon Suh, University of California, Santa Barbara, CA, and accepted by the Editorial Board December 4, 2014 (received for review August 17, 2013) The aggregate potential for urban mitigation of global climate (9, 10), and also with GHG emissions from the residential change is insufficiently understood. Our analysis, using a dataset sector (11). The recent IPCC report identifies urban form of 274 cities representing all city sizes and regions worldwide, as a driver of urban emissions but does not provide guidance on demonstrates that economic activity, transport costs, geographic its relative importance vis-à-vis other factors. In comparative factors, and urban form explain 37% of urban direct energy use studies, cities are often sampled from similar geographies (5, 12, and 88% of urban transport energy use. If current trends in urban 13) or population sizes (8). In these studies, causality is difficult expansion continue, urban energy use will increase more than to establish, and self-selection (14) as well as topological prop- threefold, from 240 EJ in 2005 to 730 EJ in 2050. Our model shows erties and specific urban form characteristics (15) partially ex- that urban planning and transport policies can limit the future plain the relationship between urban population density and increase in urban energy use to 540 EJ in 2050 and contribute to transport energy consumption. -
Peak Oil and the Everyday Complexity of Human Progress Narratives
Peak Oil and the Everyday Complexity of Human Progress Narratives John C. Pruit University of Missouri The “big” story of human progress has polarizing tendencies featuring the binary options of progress or decline. I consider human progress narratives in the context of everyday life. Analysis of the “little” stories from two narrative environments focusing on peak oil offers a more complex picture of the meaning and contours of the narrative. I consider the impact of differential blog site commitments to peak oil perspectives and identify five narrative types culled from two narrative dimensions. I argue that the lived experience complicates human progress narratives, which is no longer an either/or proposition This is going to be an environmental disaster of unprecedented proportions and the only thing that people seem to really care about is keeping the Mississippi open to shipping traffic so that BAU [business as usual] can continue. I weep for the wetlands and what their loss will mean. “FMagyar” April 30, 2010 What's the worst the doomers can moan about now? An oil spill (not even a big one by historical standards) and a bit of toxic mess in Canada. Woo, I'm so scared! Come on doomers, you can do better than this! :) “Mr Potato Head” July 9, 2010 Oil and oil-related events such as the 2010 BP spill in the Gulf of Mexico are part of the story of human progress and important to how people story their own lives. Oil powers lifestyles and plays a role in everything from transportation to food production. -
Handout: Ecological Footprints from Around the World
Ecological Footprints From Around the World Handout Map Your Eco-Footprint lesson plan support material Green Star! Newsletter May/June 2006 Handout: Ecological Footprints From Around the World (Adapted from: “How big is your footprint,” Energy for a Sustainable Future — Education Project, www.esfep.org/ ) Ecological Footprints From Around the World: Where Do You Fit In? How Much Land Do You Need to Live? If you had to provide everything you use from your own land — how much land area would you need? This land would have to provide you with all of your food, water, energy and everything else that you use. The amount of land you would need to support your lifestyle is called your Ecological Footprint. The ecological footprint is one way of measuring the impact a person has on the environment. Is the World Big Enough for All of Our BIG Feet? The size of a person’s Ecological Footprint will depend on many factors. Do you grow your own food? Do you walk or drive? Do you use renewable or non-renewable energy sources? Everyone has an ecological footprint because we all need to use the earth’s resources to survive. But we must make sure we don’t take more resources than the earth can provide. Different people in the same country will have different sized ecological footprints. Different countries also have different ecological footprints. For example, a person with the average Canadian lifestyle has an ecological footprint of 8.56 hectares. A person living in Ethiopia, Africa, has an average ecological footprint of 0.67 hectares.