Demographic Antecedents of a Revitalization Movement: Population Change, Population Size, and the 1890 Ghost Dance

1981 ◽  
Vol 46 (1) ◽  
pp. 88 ◽  
Author(s):  
Russell Thornton
Keyword(s):  
Population Size ◽  
Population Change ◽  
Ghost Dance ◽  
Revitalization Movement

scholarly journals Shifting trends: Detecting changes in cetacean population dynamics in shifting habitat

PLoS ONE ◽  
2021 ◽  
Vol 16 (5) ◽  
pp. e0251522
Author(s):  
Charlotte Boyd ◽  
André E. Punt
Keyword(s):  
Population Dynamics ◽  
Population Size ◽  
Wildlife Conservation ◽  
Population Change ◽  
Stock Assessment ◽  
Distance Sampling ◽  
Distribution Patterns ◽  
Population Trend ◽  
Mobile Species ◽  
Population Size Estimates

The ability to monitor population dynamics and detect major changes in population trend is essential for wildlife conservation and management. However, this is often challenging for cetaceans as surveys typically cover only a portion of a population’s range and conventional stock assessment methods cannot then distinguish whether apparent changes in abundance reflect real changes in population size or shifts in distribution. We developed and tested methods for estimating population size and trend and detecting changes in population trend in the context of shifting habitat by integrating additional data into distance-sampling analysis. Previous research has shown that incorporating habitat information can improve population size estimates for highly mobile species with dynamic spatial distributions. Here, using simulated datasets representative of a large whale population, we demonstrate that incorporating individual mark-recapture data can increase the accuracy and precision of trend estimation and the power to distinguish whether apparent changes in abundance reflect changes in population trend or distribution shifts. We recommend that similar simulation studies are conducted for specific cetacean populations to assess the potential for detecting changes in population dynamics given available data. This approach is especially important wherever population change may be confounded with long-term change in distribution patterns associated with regime shifts or climate change.

scholarly journals Reversed optimality and predictive ecology: burrowing depth forecasts population change in a bivalve

2008 ◽  
Vol 5 (1) ◽  
pp. 5-8 ◽  
Author(s):  
Jan A van Gils ◽  
Casper Kraan ◽  
Anne Dekinga ◽  
Anita Koolhaas ◽  
Jan Drent ◽  
...  
Keyword(s):  
Population Size ◽  
Population Change ◽  
Population Decline ◽  
Macoma Balthica ◽  
Optimal Foraging Theory ◽  
Marine Bivalve ◽  
Behavioural Ecology ◽  
Per Capita ◽  
To Come ◽  
Optimality Principles

Optimality reasoning from behavioural ecology can be used as a tool to infer how animals perceive their environment. Using optimality principles in a ‘reversed manner’ may enable ecologists to predict changes in population size before such changes actually happen. Here we show that a behavioural anti-predation trait (burrowing depth) of the marine bivalve Macoma balthica can be used as an indicator of the change in population size over the year to come. The per capita population growth rate between years t and t +1 correlated strongly with the proportion of individuals living in the dangerous top 4 cm layer of the sediment in year t : the more individuals in the top layer, the steeper the population decline. This is consistent with the prediction based on optimal foraging theory that animals with poor prospects should accept greater risks of predation. This study is among the first to document fitness forecasting in animals.

Evolution Determined by Trajectory of Expected Populations: Sufficient Conditions, with Application to Crossover

1999 ◽  
Vol 7 (2) ◽  
pp. 151-171 ◽  
Author(s):  
I. Douglas Bruce ◽  
R. Jamie Simpson
Keyword(s):  
Population Size ◽  
Population Change ◽  
Sufficient Conditions ◽  
Finite Size ◽  
Valid Conclusion ◽  
Genetic Operator ◽  
Expected Result ◽  
Expected Outcome ◽  
Size Population

The study of a population's evolution under the action of a genetic operator, or composition of operators, is more difficult when the population size is finite because the examination of the expected population at each generation does not necessarily yield the overall expected result. In certain circumstances, some interesting properties of a population change during evolution in such a way that a valid conclusion can be drawn by charting the change from expected population to expected population. We establish sufficient conditions that ensure that the evolution of a property of a population can be determined by examination of the expected populations only. An example of the application of this characterization is a proof that a finite size population under repeated crossover in the absence of selection or mutation converges, in the sense of expected outcome, to the population with maximum diversity. The proof extends the results already established by others for infinite populations.

scholarly journals THE HOMOZYGOSITY TEST AFTER A CHANGE IN POPULATION SIZE

Genetics ◽  
1986 ◽  
Vol 112 (4) ◽  
pp. 899-907
Author(s):  
G A Watterson
Keyword(s):  
Computer Simulation ◽  
Population Size ◽  
Population Change ◽  
Simulation Method ◽  
Recent Change ◽  
Numerical Examples ◽  
Computer Simulation Method ◽  
Neutral Mutation ◽  
Significance Levels

ABSTRACT The homozygosity of a population will be influenced by any recent change in the population size. The "homozygosity test" of the neutral mutation hypothesis might also be influenced by a population change. A computer simulation method is described that establishes the significance levels of observed homozygosities after a change in population size. Some numerical examples are given.

scholarly journals Evolution of cancer cell populations under cytotoxic therapy and treatment optimisation: insight from a phenotype-structured model

2019 ◽  
Vol 53 (4) ◽  
pp. 1157-1190 ◽  
Author(s):  
Luís Almeida ◽  
Patrizia Bagnerini ◽  
Giulia Fabrini ◽  
Barry D. Hughes ◽  
Tommaso Lorenzi
Keyword(s):  
Population Size ◽  
Cancer Cell ◽  
Cell Population ◽  
Evolutionary Dynamics ◽  
Population Change ◽  
Biological Data ◽  
Cytotoxic Drug ◽  
High Dose ◽  
Structured Model ◽  
Nonlocal Parabolic Equation

We consider a phenotype-structured model of evolutionary dynamics in a population of cancer cells exposed to the action of a cytotoxic drug. The model consists of a nonlocal parabolic equation governing the evolution of the cell population density function. We develop a novel method for constructing exact solutions to the model equation, which allows for a systematic investigation of the way in which the size and the phenotypic composition of the cell population change in response to variations of the drug dose and other evolutionary parameters. Moreover, we address numerical optimal control for a calibrated version of the model based on biological data from the existing literature, in order to identify the drug delivery schedule that makes it possible to minimise either the population size at the end of the treatment or the average population size during the course of treatment. The results obtained challenge the notion that traditional high-dose therapy represents a “one-fits-all solution” in anticancer therapy by showing that the continuous administration of a relatively low dose of the cytotoxic drug performs more closely to i.e. the optimal dosing regimen to minimise the average size of the cancer cell population during the course of treatment.

Trends of population change at colonies of cliff-nesting seabirds in the Moray Firth

1986 ◽  
Vol 91 ◽  
pp. 73-80
Author(s):  
G. P. Mudge
Keyword(s):  
Population Size ◽  
Population Change ◽  
Abundant Species ◽  
Moray Firth ◽  
Available Information ◽  
Made In

SynopsisAvailable information on the sizes and locations of seabird breeding colonies in the Moray Firth is reviewed. Guillemot is the most abundant species with a population of about 149,000 individuals at thirteen main colonies. The bulk of the populations of each species occur in east Caithness. Comparison of counts made in 1969 with more recent censuses indicate substantial increases in population size in the 1970s for most species. The results of annual counts at detailed study plots in five Caithness colonies between 1980 and 1984 suggest that this trend of increase has ceased for guillemots, razorbills and kittiwakes.

scholarly journals Culture Process and the Interpretation of Radiocarbon Data

Radiocarbon ◽  
2017 ◽  
Vol 60 (2) ◽  
pp. 453-467 ◽  
Author(s):  
Jacob Freeman ◽  
David A Byers ◽  
Erick Robinson ◽  
Robert L Kelly
Keyword(s):  
Time Series ◽  
Energy Consumption ◽  
Population Size ◽  
Population Change ◽  
Future Research ◽  
Human Populations ◽  
Data Sets ◽  
Economic Complexity ◽  
Using Data ◽  
Outstanding Question

AbstractOver the last decade, archaeologists have turned to large radiocarbon (14C) data sets to infer prehistoric population size and change. An outstanding question concerns just how direct of an estimate 14C dates are for human populations. In this paper we propose that 14C dates are a better estimate of energy consumption, rather than an unmediated, proportional estimate of population size. We use a parametric model to describe the relationship between population size, economic complexity and energy consumption in human societies, and then parametrize the model using data from modern contexts. Our results suggest that energy consumption scales sub-linearly with population size, which means that the analysis of a large 14C time-series has the potential to misestimate rates of population change and absolute population size. Energy consumption is also an exponential function of economic complexity. Thus, the 14C record could change semi-independent of population as complexity grows or declines. Scaling models are an important tool for stimulating future research to tease apart the different effects of population and social complexity on energy consumption, and explain variation in the forms of 14C date time-series in different regions.

scholarly journals Predicting the Population Growth and Structure of China Based on Grey Fractional-Order Models

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Xiaojun Guo ◽  
Rui Zhang ◽  
Naiming Xie ◽  
Jingliang Jin
Keyword(s):  
Population Size ◽  
Fractional Order ◽  
Population Change ◽  
External Disturbance ◽  
Aging Population ◽  
Data Series ◽  
Grey System ◽  
Effective Population ◽  
Population System ◽  
Population Prediction

Scientific prediction and accurate grasp of the future trend of population change are conducive to the formulation of different population policies at different stages, so as to alleviate the adverse effects of the aging population on society and provide scientific theoretical reference for controlling the population size and making policy. Considering that the population system is affected by many complex factors and the structural relationship among these factors is complex, it can be regarded as a typical dynamic grey system. In this paper, the fractional-order GM (1, 1) model and the fractional-order Verhulst model are established, respectively, based on the statistical data of China's population indices from 2015 to 2019 to forecast the population size and the change trend of population structure of China from 2015 to 2050 in the short-term and medium- to long-term. The forecast results show that China’s population will grow in an inverse S shape from 2015 to 2050, when the total population will reach 1.43 billion. Moreover, during this period, the birth rate and natural growth rate of population will decrease year by year, and the proportion of aging population and the dependency ratio of population will increase year by year. Besides, the problem of aging population is going to become increasingly serious. The application of grey system method to population prediction can mine the complex information contained in the population number series. Meanwhile, the fractional-order accumulation can weaken the randomness of the original data series and reduce the influence of external disturbance factors, so it is a simple and effective population prediction method.

scholarly journals Demography and public health

2021 ◽  
pp. 317-334
Author(s):  
Emily Grundy ◽  
Michael Murphy
Keyword(s):  
Public Health ◽  
Population Size ◽  
Population Change ◽  
Health Planning ◽  
Health Profile ◽  
Demographic Trends ◽  
Healthcare Needs ◽  
Demographic Methods ◽  
And Migration ◽  
Size And Structure

The health and healthcare needs of a population cannot be measured or met without knowledge of its size and characteristics. Demography is the scientific study of population and is concerned both with the measurement, or estimation, of population size and structure and with population dynamics—the interplay between fertility, mortality, and migration which determines population change. These are pre-requisites for making the forecasts about future population size and structure which largely determine the health profile of a population and should underpin public health planning. This chapter presents information on demographic methods and data sources, their application to health and population issues, information on demographic trends and their implications, and the major theories about demographic change. The aim is to illustrate and elucidate the complex inter-relationship between population change and human health.

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