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Relevant bibliographies by topics / Population dynamics

Academic literature on the topic 'Population dynamics'

Author: Grafiati

Published: 4 June 2021

Last updated: 29 July 2024

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Journal articles on the topic "Population dynamics"

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Juliano, Steven A. "POPULATION DYNAMICS." Journal of the American Mosquito Control Association 23, sp2 (July 2007): 265–75. http://dx.doi.org/10.2987/8756-971x(2007)23[265:pd]2.0.co;2.

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Rudnicki, Ryszard, Ovide Arino, and Pierre Auger. "Population dynamics." Comptes Rendus Biologies 327, no. 3 (March 2004): 173. http://dx.doi.org/10.1016/j.crvi.2003.10.008.

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Cooch, E. G., and A. A. Dhondt. "Population dynamics." Animal Biodiversity and Conservation 27, no. 1 (June 1, 2004): 469–70. http://dx.doi.org/10.32800/abc.2004.27.0469.

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Increases or decreases in the size of populations over space and time are, arguably, the motivation for much of pure and applied ecological research. The fundamental model for the dynamics of any population is straightforward: the net change over time in the abundance of some population is the simple difference between the number of additions (individuals entering the population) minus the number of subtractions (individuals leaving the population). Of course, the precise nature of the pattern and process of these additions and subtractions is often complex, and population biology is often replete with fairly dense mathematical representations of both processes. While there is no doubt that analysis of such abstract descriptions of populations has been of considerable value in advancing our, there has often existed a palpable discomfort when the ‘beautiful math’ is faced with the often ‘ugly realities’ of empirical data. In some cases, this attempted merger is abandoned altogether, because of the paucity of ‘good empirical data’ with which the theoretician can modify and evaluate more conceptually–based models. In some cases, the lack of ‘data’ is more accurately represented as a lack of robust estimates of one or more parameters. It is in this arena that methods developed to analyze multiple encounter data from individually marked organisms has seen perhaps the greatest advances. These methods have rapidly evolved to facilitate not only estimation of one or more vital rates, critical to population modeling and analysis, but also to allow for direct estimation of both the dynamics of populations (e.g., Pradel, 1996), and factors influencing those dynamics (e.g., Nichols et al., 2000). The interconnections between the various vital rates, their estimation, and incorporation into models, was the general subject of our plenary presentation by Hal Caswell (Caswell & Fujiwara, 2004). Caswell notes that although interest has traditionally focused on estimation of survival rate (arguably, use of data from marked individuals has been used for estimation of survival more than any other parameter, save perhaps abundance), it is only one of many transitions in the life cycle. Others discussed include transitions between age or size classes, breeding states, and physical locations. The demographic consequences of these transitions can be captured by matrix population models, and such models provide a natural link connecting multi–stage mark–recapture methods and population dynamics. The utility of the matrix approach for both prospective, and retrospective, analysis of variation in the dynamics of populations is well–known; such comparisons of results of prospective and retrospective analysis is fundamental to considerations of conservation management (sensu Caswell, 2000). What is intriguing is the degree to which these methods can be combined, or contrasted, with more direct estimation of one or more measures of the trajectory of a population (e.g., Sandercock & Beissinger, 2002). The five additional papers presented in the population dynamics session clearly reflected these considerations. In particular, the three papers submitted for this volume indicate the various ways in which complex empirical data can be analyzed, and often combined with more classical modeling approaches, to provide more robust insights to the dynamics of the study population. The paper by Francis & Saurola (2004) is an example of rigorous analysis and modeling applied to a large, carefully collected dataset from a long–term study of the biology of the Tawny Owl. Using a combination of live encounters and dead recoveries, the authors were able to separate the relative contributions of various processes (emigration, mortality) on variation in survival rates. These analyses were combined with periodic matrix models to explore comparisons of direct estimation of changes in population size (based on both census and mark–recapture analysis) with model estimates. The utility of combining sources of information into analysis of populations was the explicit subject of the other two papers. Gauthier & Lebreton (2004) draw on a long–term study of an Arctic–breeding Goose population, where both extensive mark–recapture, ring recovery, and census data are available. The primary goal is to use these various sources of information to to evaluate the effect of increased harvests on dynamics of the population. A number of methods are compared; most notably they describe an approach based on the Kalman filter which allows for different sources of information to be used in the same model, that is demographic data (i.e. transition matrix) and census data (i.e. annual survey). They note that one advantage of this approach is that it attempts to minimize both uncertainties associated with the survey and demographic parameters based on the variance of each estimate. The final paper, by Brooks, King and Morgan (Brooks et al., 2004) extends the notion of the combining information in a common model further. They present a Bayesian analysis of joint ring–recovery and census data using a state–space model allowing for the fact that not all members of the population are directly observable. They then impose a Leslie–matrix–based model on the true population counts describing the natural birth–death and age transition processes. Using a Markov Chain Monte Carlo (MCMC) approach (which eliminates the need for some of the standard assumption often invoked in use of a Kalman filter), Brooks and colleagues describe methods to combine information, including potentially relevant covariates that might explain some of the variation, within a larger framework that allows for discrimination (selection) amongst alternative models. We submit that all of the papers presented in this session indicate clearly significant interest in approaches for combining data and modeling approaches. The Bayesian framework appears a natural framework for this effort, since it is able to not only provide a rigorous way to evaluate and integrate multiple sources of information, but provides an explicit mechanism to accommodate various sources of uncertainty about the system. With the advent of numerical approaches to addressing some of the traditionally ‘tricky’ parts of Bayesian inference (e.g., MCMC), and relatively user–friendly software, we suspect that there will be a marked increase in the application of Bayesian inference to the analysis of population dynamics. We believe that the papers presented in this, and other sessions, are harbingers of this trend. Cite

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Safonov, Aleksandr, and Yuliya Dolzhenkova. "Dynamics of income of pensioners: analysis, problems and solutions." Population 26, no. 4 (December 15, 2023): 133–47. http://dx.doi.org/10.19181/population.2023.26.4.12.

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Currently there is an increasing number of older people in Russia, primarily pensioners. It appears that the mentioned trend will proceed for a long period of time. So, the issue of ensuring high living standards for this group of the population is acute. However, the present trends in the work remuneration of persons in pre-retirement age, spread on informal employment, and hence, precarization of labor relations, as well as the challenges in pension and tax legislation result in a complex and contradictory situation in the formation of monetary income of pensioners.The present article is devoted to the analysis and forecasting of the basic trends in the financial situation of persons over the able-bodied age. The average size of the insurance old-age pension in the end of 2022 did not achieve the amount recommended by the ILO Convention 102, and the social pension was even lower. In addition, the later retirement often leads to poverty, as it is impossible for the aged to get pensions, on the one hand, and on the other hand, to get a job due to the existing age discrimination and their reduced physical ability to work.The article analyses the factors that have a direct on the size dynamics of insurance and social old-age pensions. At the same time, insurance pensions have the economic nature of deferred wages, i.e. they are formed directly by pensioners themselves. It also analyzes possible ways of compensation for pensioners’ low incomes through continuing work activity.

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Sampson, D. B., and J. A. Gulland. "Fish Population Dynamics." Journal of Applied Ecology 26, no. 2 (August 1989): 741. http://dx.doi.org/10.2307/2404104.

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Elliott, J. M., and J. A. Gulland. "Fish Population Dynamics." Journal of Animal Ecology 58, no. 2 (June 1989): 728. http://dx.doi.org/10.2307/4862.

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Gilbert, James R., and T. Royama. "Analytical Population Dynamics." Journal of Wildlife Management 58, no. 2 (April 1994): 383. http://dx.doi.org/10.2307/3809406.

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Watkinson, A. R., and T. Royama. "Analytical Population Dynamics." Journal of Ecology 82, no. 2 (June 1994): 431. http://dx.doi.org/10.2307/2261318.

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Sheiner, L. B., and T. M. Ludden. "Population Pharmacokinetics/Dynamics*." Annual Review of Pharmacology and Toxicology 32, no. 1 (April 1992): 185–209. http://dx.doi.org/10.1146/annurev.pa.32.040192.001153.

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McNicoll, Geoffrey, Gayl D. Ness, William D. Drake, and Steven R. Brechin. "Population--Environment Dynamics." Population and Development Review 21, no. 1 (March 1995): 183. http://dx.doi.org/10.2307/2137425.

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Dissertations / Theses on the topic "Population dynamics"

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Koons, David Nelson Grand James Barry. "Transient population dynamics and population momentum in vertebrates." Auburn, Ala, 2005. http://repo.lib.auburn.edu/EtdRoot/2005/SPRING/Forestry_and_Wildlife_Sciences/Dissertation/KOONS_DAVID_55.pdf.

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Ruaro, Lorenzo. "Population dynamics of Ctenosaura bakeri." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020. http://amslaurea.unibo.it/20747/.

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The Ctenosaura bakeri is an iguana species endemic to the island of Utila, a small island off the eastern coast of Honduras. It is currently one of the species of the genus Ctenosaura most threatened with extinction, having its conservation status labelled as "Critically Endangered" by the IUCN Red List. The goals of this paper are to give some insights on the intrinsic trend of the whole population and to analyse the influence of the greater threats to the survival of the species (such as sex dependent hunting and habitat destruction). We will use a transition matrix approach to investigate the intrinsic trend of the population and we will provide arguments for the estimation of the different parameters. For the influence of the threats we will take a deterministic approach using systems of ODEs and DDEs, investigating the stationary points and their stability and giving prediction through simulations for the evolution of the population. We will also introduce a model for the occurence of hybridization with another iguana species of the island. The achieved results are summarized and still open questions stated at the end.

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Agassiz, David J. L. "Population dynamics of invading insects." Thesis, Imperial College London, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.678691.

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Patra, Pintu. "Population dynamics of bacterial persistence." Phd thesis, Universität Potsdam, 2013. http://opus.kobv.de/ubp/volltexte/2014/6925/.

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The life of microorganisms is characterized by two main tasks, rapid growth under conditions permitting growth and survival under stressful conditions. The environments, in which microorganisms dwell, vary in space and time. The microorganisms innovate diverse strategies to readily adapt to the regularly fluctuating environments. Phenotypic heterogeneity is one such strategy, where an isogenic population splits into subpopulations that respond differently under identical environments. Bacterial persistence is a prime example of such phenotypic heterogeneity, whereby a population survives under an antibiotic attack, by keeping a fraction of population in a drug tolerant state, the persister state. Specifically, persister cells grow more slowly than normal cells under growth conditions, but survive longer under stress conditions such as the antibiotic administrations. Bacterial persistence is identified experimentally by examining the population survival upon an antibiotic treatment and the population resuscitation in a growth medium. The underlying population dynamics is explained with a two state model for reversible phenotype switching in a cell within the population. We study this existing model with a new theoretical approach and present analytical expressions for the time scale observed in population growth and resuscitation, that can be easily used to extract underlying model parameters of bacterial persistence. In addition, we recapitulate previously known results on the evolution of such structured population under periodically fluctuating environment using our simple approximation method. Using our analysis, we determine model parameters for Staphylococcus aureus population under several antibiotics and interpret the outcome of cross-drug treatment. Next, we consider the expansion of a population exhibiting phenotype switching in a spatially structured environment consisting of two growth permitting patches separated by an antibiotic patch. The dynamic interplay of growth, death and migration of cells in different patches leads to distinct regimes in population propagation speed as a function of migration rate. We map out the region in parameter space of phenotype switching and migration rate to observe the condition under which persistence is beneficial. Furthermore, we present an extended model that allows mutation from the two phenotypic states to a resistant state. We find that the presence of persister cells may enhance the probability of resistant mutation in a population. Using this model, we explain the experimental results showing the emergence of antibiotic resistance in a Staphylococcus aureus population upon tobramycin treatment. In summary, we identify several roles of bacterial persistence, such as help in spatial expansion, development of multidrug tolerance and emergence of antibiotic resistance. Our study provides a theoretical perspective on the dynamics of bacterial persistence in different environmental conditions. These results can be utilized to design further experiments, and to develop novel strategies to eradicate persistent infections.
Das Leben von Mikroorganismen kann in zwei charakteristische Phasen unterteilt werde, schnelles Wachstum unter Wachstumsbedingungen und Überleben unter schwierigen Bedingungen. Die Bedingungen, in denen sich die Mikroorganismen aufhalten, verändern sich in Raum und Zeit. Um sich schnell an die ständig wechselnden Bedingungen anzupassen entwickeln die Mikroorganismen diverse Strategien. Phänotypische Heterogenität ist eine solche Strategie, bei der sich eine isogene Popolation in Untergruppen aufteilt, die unter identischen Bedingungen verschieden reagieren. Bakterielle Persistenz ist ein Paradebeispiel einer solchen phänotypischen Heterogenität. Hierbei überlebt eine Popolation die Behandlung mit einem Antibiotikum, indem sie einen Teil der Bevölkerung in einem, dem Antibiotikum gegenüber tolerant Zustand lässt, der sogenannte "persister Zustand". Persister-Zellen wachsen unter Wachstumsbedingungen langsamer als normale Zellen, jedoch überleben sie länger in Stress-Bedingungen, wie bei Antibiotikaapplikation. Bakterielle Persistenz wird experimentell erkannt indem man überprüft ob die Population eine Behandlung mit Antibiotika überlebt und sich in einem Wachstumsmedium reaktiviert. Die zugrunde liegende Popolationsdynamik kann mit einem Zwei-Zustands-Modell für reversibles Wechseln des Phänotyps einer Zelle in der Bevölkerung erklärt werden. Wir untersuchen das bestehende Modell mit einem neuen theoretischen Ansatz und präsentieren analytische Ausdrücke für die Zeitskalen die für das Bevölkerungswachstums und die Reaktivierung beobachtet werden. Diese können dann einfach benutzt werden um die Parameter des zugrunde liegenden bakteriellen Persistenz-Modells zu bestimmen. Darüber hinaus rekapitulieren wir bisher bekannten Ergebnisse über die Entwicklung solch strukturierter Bevölkerungen unter periodisch schwankenden Bedingungen mithilfe unseres einfachen Näherungsverfahrens. Mit unserer Analysemethode bestimmen wir Modellparameter für eine Staphylococcus aureus-Popolation unter dem Einfluss mehrerer Antibiotika und interpretieren die Ergebnisse der Behandlung mit zwei Antibiotika in Folge. Als nächstes betrachten wir die Ausbreitung einer Popolation mit Phänotypen-Wechsel in einer räumlich strukturierten Umgebung. Diese besteht aus zwei Bereichen, in denen Wachstum möglich ist und einem Bereich mit Antibiotikum der die beiden trennt. Das dynamische Zusammenspiel von Wachstum, Tod und Migration von Zellen in den verschiedenen Bereichen führt zu unterschiedlichen Regimen der Populationsausbreitungsgeschwindigkeit als Funktion der Migrationsrate. Wir bestimmen die Region im Parameterraum der Phänotyp Schalt-und Migrationsraten, in der die Bedingungen Persistenz begünstigen. Darüber hinaus präsentieren wir ein erweitertes Modell, das Mutation aus den beiden phänotypischen Zuständen zu einem resistenten Zustand erlaubt. Wir stellen fest, dass die Anwesenheit persistenter Zellen die Wahrscheinlichkeit von resistenten Mutationen in einer Population erhöht. Mit diesem Modell, erklären wir die experimentell beobachtete Entstehung von Antibiotika- Resistenz in einer Staphylococcus aureus Popolation infolge einer Tobramycin Behandlung. Wir finden also verschiedene Funktionen bakterieller Persistenz. Sie unterstützt die räumliche Ausbreitung der Bakterien, die Entwicklung von Toleranz gegenüber mehreren Medikamenten und Entwicklung von Resistenz gegenüber Antibiotika. Unsere Beschreibung liefert eine theoretische Betrachtungsweise der Dynamik bakterieller Persistenz bei verschiedenen Bedingungen. Die Resultate könnten als Grundlage neuer Experimente und der Entwicklung neuer Strategien zur Ausmerzung persistenter Infekte dienen.

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Guzmán, Alfredo. "Peru: population, dynamics and health." Universidad Peruana de Ciencias Aplicadas - UPC, 2007. http://hdl.handle.net/10757/272453.

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Milligan, Paul. "Population dynamics of African trypanosomiasis." Thesis, University of Salford, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.306017.

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Forrest, Michael Bruce. "Toxins and blowfly population dynamics." Thesis, University of Leicester, 1996. http://hdl.handle.net/2381/34346.

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This thesis studies the effects of toxins upon larvae of the blowfly Lucilia sericata. A field study of fly populations infesting carcasses showed aggregations in space and time of a number of fly species, although L, sericata was not common. The presence of cadmium or deltamethrin in the larval diet was shown to have deleterious effects upon the larvae. Development was slowed down and the resultant adults were smaller. When the diet contained cadmium, adults had a lower fecundity than those arising from larvae fed upon the control diet. These effects became more pronounced as larval population density was increased. Models were constructed that simulated the population dynamics of L. sericata under two conditions. In each population, the larval diet was limited to 20 g/day whilst in one the diet was contaminated with 50 mg Cd/kg diet. These models allowed the underlying dynamics and their driving forces to be identified. The control model predicted sustained population cycles with a period of 67 days, approximately twice the generation time calculated from cohort life-tables. The cadmium model predicted that these cycles would be dampened and the mass of individual pupae increased relative to those from the control simulation model. These theoretical results, which apparently contradict the predictions made by scope for growth theory, are consistent with results from a long-term population study and were due to the interaction of cadmium with the effects of population density.

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Siriwardena, Pathiranage Lochana Pabakara. "STOCHASTIC MODELS IN POPULATION DYNAMICS." OpenSIUC, 2014. https://opensiuc.lib.siu.edu/dissertations/908.

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This dissertation discusses the construction of some stochastic models for population dynamics with a variety of birth and death rate functions. A general model is constructed considering a fundamental growth rate function of the population while allowing random births and deaths in the population. Four stochastic discrete delay models and two non-delay models using the infinitesimal mean and variance given by birth and death rate functions have been produced and analyzed. In these constructions drift terms are in the form of logistic growth or logistic growth with delay. Logistic growth models are well known to biologists and economists. For each model, the existence and uniqueness of the global solution, non-negativeness of the solution is discussed, and for some models, boundedness of the path is also given. Persistence of the population and the boundary behavior have also been discussed through the hitting times. Here, a new method to analyze the hitting times for a specific class of stochastic delay models is presented. This work is related to and also extends the work of Edward Allen, Linda Allen and Bernt Oksendal in population dynamics.

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Choudhury, Md Abu Hasnat Zamil. "Population Dynamics of RNA viruses." Thesis, Queensland University of Technology, 2013. https://eprints.qut.edu.au/60866/1/Md._Choudhury_Thesis.pdf.

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Between 50 and 100 million people are infected with dengue viruses each year and more than 100,000 of these die. Dr Choudhury has demonstrated that populations of dengue viruses in individual patients are genetically and functionally very diverse and that this diversity changes significantly at the time of major outbreaks of disease. The results of his studies may inform strategies which will make dengue vaccines far more effective.

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Ward, Eric John. "Incorporating model selection and decision analysis into population dynamics modeling /." Thesis, Connect to this title online; UW restricted, 2006. http://hdl.handle.net/1773/5319.

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Books on the topic "Population dynamics"

1

Rieman, Bruce E. Kokanee population dynamics. [Idaho]: Idaho Fish & Game, 1991.

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Royama, T. Analytical Population Dynamics. Dordrecht: Springer Netherlands, 1992. http://dx.doi.org/10.1007/978-94-011-2916-9.

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Newman, K. B., S. T. Buckland, B. J. T. Morgan, R. King, D. L. Borchers, D. J. Cole, P. Besbeas, O. Gimenez, and L. Thomas. Modelling Population Dynamics. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-0977-3.

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Bélanger, Alain, and Patrick Sabourin. Microsimulation and Population Dynamics. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-44663-9.

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Kerr, Donald W. Population dynamics in Canada. [Ottawa]: Statistics Canada, 1994.

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Kerr, Don. Population dynamics in Canada. Ottawa: Statistics Canada, 1994.

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William, Brass, Jolly Carole L, and National Research Council (U.S.). Working Group on Kenya., eds. Population dynamics of Kenya. Washington, D.C: National Academy Press, 1993.

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Ranade, Prabha Shastri. Population dynamics in India. New Delhi: Ashish Pub. House, 1990.

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Gilles, Pison, and National Research Council (U.S.). Working Group on Senegal., eds. Population dynamics of Senegal. Washington, D.C: National Academy Press, 1995.

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1957-, Tripathy S. N., Bishoyi Deepak 1981-, and Patel Sangram Kishor 1978-, eds. Dynamics of population issues. New Delhi: Sonali Publications, 2007.

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Book chapters on the topic "Population dynamics"

1

Frank, J. Howard, J. Howard Frank, Michael C. Thomas, Allan A. Yousten, F. William Howard, Robin M. Giblin-davis, John B. Heppner, et al. "Population Dynamics." In Encyclopedia of Entomology, 3007. Dordrecht: Springer Netherlands, 2008. http://dx.doi.org/10.1007/978-1-4020-6359-6_3073.

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Kidd, N. A. C., and M. A. Jervis. "Population Dynamics." In Insect Natural Enemies, 293–374. Dordrecht: Springer Netherlands, 1996. http://dx.doi.org/10.1007/978-94-011-0013-7_5.

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Matsuura, Makoto, and Seiki Yamane. "Population Dynamics." In Biology of the Vespine Wasps, 140–84. Berlin, Heidelberg: Springer Berlin Heidelberg, 1990. http://dx.doi.org/10.1007/978-3-642-75230-8_6.

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Bloomfield, Victor. "Population Dynamics." In Computer Simulation and Data Analysis in Molecular Biology and Biophysics, 141–57. New York, NY: Springer New York, 2009. http://dx.doi.org/10.1007/978-1-4419-0083-8_7.

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Raffoul, Youssef N. "Population Dynamics." In Qualitative Theory of Volterra Difference Equations, 229–52. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-97190-2_5.

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Puu, Tönu. "Population Dynamics." In Nonlinear Economic Dynamics, 44–85. Berlin, Heidelberg: Springer Berlin Heidelberg, 1993. http://dx.doi.org/10.1007/978-3-642-97450-2_4.

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Bungartz, Hans-Joachim, Stefan Zimmer, Martin Buchholz, and Dirk Pflüger. "Population Dynamics." In Springer Undergraduate Texts in Mathematics and Technology, 241–53. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-39524-6_10.

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Puu, Tönu. "Population Dynamics." In Nonlinear Economic Dynamics, 25–44. Berlin, Heidelberg: Springer Berlin Heidelberg, 1989. http://dx.doi.org/10.1007/978-3-662-00754-9_3.

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Tomé, Tânia, and Mário J. de Oliveira. "Population Dynamics." In Graduate Texts in Physics, 319–33. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-11770-6_14.

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Adams, Clark E. "Population Dynamics." In Urban Wildlife Management, 165–78. Third edition. | Boca Raton, FL : Taylor & Francis Group, 2016.: CRC Press, 2018. http://dx.doi.org/10.1201/9781315371863-6.

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Conference papers on the topic "Population dynamics"

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Webb, Glenn F. "Structured population dynamics." In Mathematical Modelling of Population Dynamics. Warsaw: Institute of Mathematics Polish Academy of Sciences, 2003. http://dx.doi.org/10.4064/bc63-0-4.

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Arino, Ovide, and Eva Sánchez. "Delays induced in population dynamics." In Mathematical Modelling of Population Dynamics. Warsaw: Institute of Mathematics Polish Academy of Sciences, 2003. http://dx.doi.org/10.4064/bc63-0-1.

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Sowunmi, C. O. A. "Time discrete 2-sex population model." In Mathematical Modelling of Population Dynamics. Warsaw: Institute of Mathematics Polish Academy of Sciences, 2003. http://dx.doi.org/10.4064/bc63-0-13.

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Koide, Kazuharu, Nobuo Noda, Hiroyuki Matsuura, and Masahiro Nakano. "Population Dynamics in Population Decline Society." In Second International Conference on Innovative Computing, Informatio and Control (ICICIC 2007). IEEE, 2007. http://dx.doi.org/10.1109/icicic.2007.456.

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Diekmann, Odo. "A beginner's guide to adaptive dynamics." In Mathematical Modelling of Population Dynamics. Warsaw: Institute of Mathematics Polish Academy of Sciences, 2003. http://dx.doi.org/10.4064/bc63-0-2.

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Lachowicz, Mirosław. "On bilinear kinetic equations. Between micro and macro descriptions of biological populations." In Mathematical Modelling of Population Dynamics. Warsaw: Institute of Mathematics Polish Academy of Sciences, 2003. http://dx.doi.org/10.4064/bc63-0-10.

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Loskutov, Alexander, Sergei Rybalko, and Ekaterina Zhuchkova. "A model of cardiac tissue as an excitable medium with two interacting pacemakers having refractory time." In Mathematical Modelling of Population Dynamics. Warsaw: Institute of Mathematics Polish Academy of Sciences, 2003. http://dx.doi.org/10.4064/bc63-0-11.

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Skakauskas, Vladas. "Large time behavior in a density-dependent population dynamics problem with age structure and child care." In Mathematical Modelling of Population Dynamics. Warsaw: Institute of Mathematics Polish Academy of Sciences, 2003. http://dx.doi.org/10.4064/bc63-0-12.

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Thieme, Horst R., and Hauke Vosseler. "Semilinear perturbations of Hille-Yosida operators." In Mathematical Modelling of Population Dynamics. Warsaw: Institute of Mathematics Polish Academy of Sciences, 2003. http://dx.doi.org/10.4064/bc63-0-3.

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Banasiak, Jacek. "A complete description of dynamics generated by birth-and-death problem: a semigroup approach." In Mathematical Modelling of Population Dynamics. Warsaw: Institute of Mathematics Polish Academy of Sciences, 2003. http://dx.doi.org/10.4064/bc63-0-5.

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Reports on the topic "Population dynamics"

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Peters, Michael, and Conor Walsh. Population Growth and Firm Dynamics. Cambridge, MA: National Bureau of Economic Research, October 2021. http://dx.doi.org/10.3386/w29424.

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Huntley, Mark E. Physical Forcing of Zooplankton Population Dynamics. Fort Belvoir, VA: Defense Technical Information Center, September 1998. http://dx.doi.org/10.21236/ada352487.

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Busing, Richard T., and Thomas A. Spies. Modeling the population dynamics of Pacific yew. Portland, OR: U.S. Department of Agriculture, Forest Service, Pacific Northwest Research Station, 1995. http://dx.doi.org/10.2737/pnw-rn-515.

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Schmieder, R. W. Population dynamics of minimally cognitive individuals. Part 2: Dynamics of time-dependent knowledge. Office of Scientific and Technical Information (OSTI), July 1995. http://dx.doi.org/10.2172/495734.

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Schmieder, R. W. Population dynamics of minimally cognitive individuals. Part I: Introducing knowledge into the dynamics. Office of Scientific and Technical Information (OSTI), July 1995. http://dx.doi.org/10.2172/100115.

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Adams, B. M., H. T. Banks, J. E. Banks, and J. D. Stark. Population Dynamics Models in Plant-Insect Herbivore-Pesticide Interactions. Fort Belvoir, VA: Defense Technical Information Center, August 2003. http://dx.doi.org/10.21236/ada444007.

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Yanev, Nikolay M., Vessela K. Stoimenova, and Dimitar V. Atanasov. Stochastic Modelling and Estimation of COVID-19 Population Dynamics. "Prof. Marin Drinov" Publishing House of Bulgarian Academy of Sciences, May 2020. http://dx.doi.org/10.7546/crabs.2020.04.02.

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Munroe, Peter. Population dynamics of nonmetropolitan cities in five western states. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.3046.

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Goluskin, David. Who Ate Whom: Population Dynamics With Age-Structured Predation. Fort Belvoir, VA: Defense Technical Information Center, October 2010. http://dx.doi.org/10.21236/ada558579.

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Martinez-Moyano, Ignacio, and Charles Macal. COVID-19 Impact on Prison Population and Flow Dynamics. Office of Scientific and Technical Information (OSTI), March 2022. http://dx.doi.org/10.2172/1855167.

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