Influence of instantaneous fertility decline to replacement level on population growth: An alternative model

If age-specific birth rates m, of a stable population drop abruptly tom _x/R ₀, whereR ₀ is the net reproduction rate, then, according to Keyfitz, the size of the ultimate stationary population relative to.that at the beginning of the process is given byI =be ⁰ ₀ R ₀ ? 1)/(rμR ₀, whereb andr are the birth rate and the rate of growth, respectively, of the stable population,e ₀ ⁰ the life expectancy at birth, andμ the average age at childbirth in the resulting stationary population. Noting that the decline inm _x need not necessarily be uniform, investigation has been carried out to examine the effect on Iwhen fertility decline is more rapid at higher ages. In particular, the effect of the reduced age-specific rates such asm _xe^? rx (which also produces a stationary population) has been analyzed, and simplifications of the results carried out separately for three different models of the net maternity function. It has also been shown that when m, drops abruptly to somem _x ^*, where the form ofm _x ^* need not be specified except for the restriction that the resulting population will be stationary, the value of the index can be approximately obtained fromI ^* =be ₀ ⁰ (1 -rμ/2), whereμ is the average age at childbearing of the initial stable population.     

Calculating life tables by estimating Chiang’s a from observed rates

A simple, accurate method of life table construction is advanced based upon a new way to estimate Chiang’s _n a _x (the average number of years lived in the x to x + n age interval by those dying in the interval). The estimate for _n a _x leads immediately to an expression for l _x+n (the survivors to age x + n) in terms of l _x and the known mortality rates for the interval x to x+n and the two adjacent intervals. The complete solution for the basic life table is given. The proposed method and five other easily applied methods are then compared against the standard provided by the U.S. life tables for 1969–1971. The results attest to the excellent performance and high degree of accuracy of the proposed method. Finally, extensions of the method to multiple decrement and associated single decrement life tables are briefly described.     

On long-term mortality trends in the United States, 1850–1968

This study of United States life tables analyzes the process of mortality transition during 1850–1968. Special features of the study are (1) a phase-specific, rather than an age-specific, analysis of mortality and (2) use of measures based on person-years of life (nL _x ) in phase-intervals, rather than survival rates (nPx) or expectation of life at given ages (e _x ^o). The analysis suggests that the historical transition of mortality in the United States can be described as a three-stage process: an initial stage of slow improvement in life expectancy during 1850–1900, a second stage of rapid improvement during 1900–1950, and a third stage of slower improvement since 1950. Quantitative measures of rapidity of mortality decline in the several phases indicate that they are not identical for all phases and in all stages. The analysis also suggests that there have been rapid changes in the components of overall mortality differentials by sex and race in the United States. The paper draws attention to the need for studies of factors in variations of mortality at ages beyond 50 in the United States population subgroups.     

Some extensions of the keyfitz momentum relationship

A stable population, such that the total birthrateB(t) =B _o e ^ro^t, is abruptly altered by modifying the age-specific birth rate,m(x). The survivor function remains unaltered. The modified population ultimately settles down to a stable behavior, such thatB(t) =B ₁ e ^r ₁ ^t . It is shown thatB ₁/B ₀ = (R ₀ ?R ₁)/[(r ₀ ?r ₁)R ₀ Z ₁], whereR ₀,R ₁ are the net reproduction rates before and after the change, and \(\bar Z_1 \) expected age giving birth for the stable population after the change. The age structure and transients resulting from the change are also described. The effect of an abrupt change in the survivor functionl(x) is also investigated for the simple case where the change is caused by alteringl(x) toe ^?λx l(x). It is shown that the above ratio becomes \(B_1 /B_0 = N_1 /N_0 = [1 - \smallint _0^\infty e^{ - kx} g(x)dx]/\bar Z_1 \lambda \) , whereN refers to the numbers in the population,k =r ₀ + λ, andg(x) =m(x)l(x), the value before the change. A measure for the reproductive worth of the population is also established.     

Measurement of non-randomness in spatial distributions

Summary The measurement of departure from randomness in spatial distributions has widespread application in ecological work. Several “indices of non-randomness” are compared with regard to their dependence on sample number, sample size and density. Criteria for the best choice of index for specific situations are discussed. A new coefficientC _x is proposed for use with positively contagious distributions and tests of significance are given. WhenC _x and another index (S ²/m−1) are used for positive and negative contagion respectively, values ranging from −1 through 0 (random) to +1 are obtained, regardless of sample number, sample size or density.     

Relationship between surplus energy and body weight in fish populations

Summary This paper theoretically analyses the relationship between surplus energy, which is available for either somatic growth or reproduction, and body weight. From the data of metabolism and growth of the biwamasu,Oncorhynchus rhodurus, obtained by Miura et al., a Bernoulli's differential equation is induced to represent the relationship between body weight and the sum of surplus energy and active metabolic rate. Solving this equation gives the amount of surplus energy,f(W_x), as follows:f(W_x) = (αW _x ^1−γ +β^1−γ)^1/(1−γ)−W_x, in which α, β and γ are constants andW _x is body weight at agex. The function is applied to ten fish populations and consequently it is found to be useful for a wider age range and a wider variety of fishes than the conventional function.     

Counter-Examples about Lower- and Upper-Bounded Population Growth

ABSTRACT

For a unimodal growth function f having its maximum at a critical state x _c , the interval bounding the population size asymptotically is usually presented as being equal to [f ^○2(x _c ), f(x _c )]. This interval however does not represent the maximum range within which the population size can vary, even asymptotically. The actual invariant interval containing the population size is equal to: [min(x*, f ^○2(x _c )), f(x _c )], where x* denotes the non-zero fixed point, assumed to be unique, of the iteration of f.     

Preliminary studies on the respiratory energy loss of a spider,Lycosa pseudoannulata

Summary To elucidate the basic food requirement of spiders, the important polyphagous predators of rice-plant insect pests, an attempt was made to measure the respiratory energy loss of fasting spiders,Lycosa pseudoannulata. Relationship between fresh (y) and dry (x) weights of spiders inhabiting the bottom layer of the rice-plant community was represented by the following allometric equation:y=0.428x ^0.872. The carbon dioxide production by previously fed and unfed females under the dark at 29°C 100% R. H. was measured by a titration technique. The relationship between fresh body weight and CO₂ production by unfed animals could be represented by the equationM=aW ^b, M being the CO₂ output per individual per day andW the fresh body weight. The constantb, which determines the slope of curve, was 0.808. Respiration of the adult female with 100 mg fresh weight was 1.155±0.250 mg CO₂/100 g fresh weight/day or 48.69 mg CO₂/g dry weight/day. This value corresponds to 35.81 cal/g fresh weight/day or 150.94 cal/g dry weight/day. Supposing the calorific content of spiders to be 5820 cal/g dry weight, rate of the respiratory energy loss to total energy of the body was estimated to be 2.60%. This rate did not strongly contradict with the loss of fresh body weight before and after the measurement. The metabolic rate showed remarkable fluctuation with changing food supply. The CO₂ production of starved individuals decreased to 83.63±16.34% as compared with individuals which were fed before the measurement.     

Growth of U.S. population, 1940–1971, in the light of an interactive two-sex model

Since it is logically impossible to hold constant both male and female age-specific fertility rates, the intrinsic growth rates or the net reproduction rates for males and females, based on that assumption, are internally inconsistent. The interactive two-sex model presented in this paper holds constant a set of bivariate age-specific fertility rates by age of men and women and allows the male and female age-specific fertility rates to adjust themselves to achieve stability. The model gives the same intrinsic growth rate for both sexes and generates intrinsic age-specific fertility rates and intrinsic net reproduction rates for males and females which are consistent and can operate simultaneously on a population. The model is applied to the U.S. data for 1940–1971, and the results are compared with those obtained from the one-sex models.     

Intermediate variables and educational differentials in fertility in Korea and the Philippines

This analysis compares the effects of contraceptive use and infant and fetal mortality on the pace offertility in Korea and the Philippines and explores the mediating effects of these intermediate variables on educational differentials in childspacing. For birth intervals initiated in a recent period before a sample survey, second, third and higher-order intervals are examined. Transitions within successive segments of interval exposure (q _xvalues) are examined rather than cumulative transitions (1 - l _xvalues). This methodological choice is substantively important because breastfeeding should primarily affect early segments of exposure and because it allows empirical examination of the timing of the effects of other variables such as contraceptive use. Further, this choice allows multivariate analysis within the structure of the life-table perspective. The results show substantial differences in patterns between Korea and the Philippines, indicate clearly the effect of each intermediate variable, and illustrate how educational differentials in fertility are affected by contraception and infant and fetal mortality.     

A stochastic computer model for simulating population growth

Summary A model is described for investigating the interactions of age-specific birth and death rates, age distribution and density-governing factors determining the growth form of single-species populations. It employs Monte Carlo techniques to simulate the births and deaths of individuals while density-governing factors are represented by simple algebraic equations relating survival and fecundity to population density. In all respects the model’s behavior agrees with the results of more conventional mathematical approaches, including the logistic model andLotka’s Law, which predicts a relationship betwen age-specific rates, rate of increase and age distribution. Situations involving exponential growth, three different age-independent density functions affecting survival, three affecting fecundity and their nine combinations were tested. The one function meeting the assumptions of the logistic model produced a logistic growth curve embodying the correct values orr _m andK. The others generated sigmoid curves to which arbitrary logistic curves could be fitted with varying success. Because of populational time lags, two of the functions affecting fecundity produced overshoots and damped oscillations during the initial approach to the steady state. The general behavior of age-dependent density functions is briefly explored and a complex example is described that produces population fluctuations by an egg cannibalism mechanism similar to that found in the flour beetleTribolium. The model is free of inherent time lags found in other discrete time models yet these may be easily introduced. Because it manipulates separate individuals, the model may be combined readily with the Monte Carlo simulation models of population genetics to study eco-genetic phenomena.     

Ecological and Motivational Determinants of Activation: Studying Compared to Sports and Watching TV

How can we enhance activation? Studying shouldbe a challenging, yet rewarding activity forstudents who intend to graduate. The Flowtheory (Csikszentmihalyi, 1990, 1997) predictsthat differential levels of perceived challengeand skill (flow) are related to optimizedmental states and increased activation.However, the influence of concurrent mentalstates and specific environmental cues for thisstate of optimal experience is unknown. In thisstudy we explore the contextual and subjectivedeterminants of flow in relation to activationin studying, and compare this with sports andwatching TV or listening to the radio. Method: 43 undergraduate students at theUniversity of Maastricht were assessed with theExperience Sampling Method for one week(Delespaul, 1995). At random moments 10 timeseach day subjects evaluated the social context,activities, and mood states. Analyses were donewith multilevel random regression techniques.Results: We replicated the predictedflow-related patterns in activation andemotions. While overall activation wasincreased in high challenging moments(β = 0.51; 95% CI: 0.36, 0.19), thiseffect was less pronounced during study(β = ?0.16; 95% CI: ?0.25, ?0.07). Skillslevels did not affect activation(β = ?0.01; 95% CI: ?0.06, 0.05).Concurrent emotions were independently andadditionally related to activation(Δχ² ₍₄₎ = 117.12,p < 0.0001). Unexpectedly, activation increasedwith demotivation (β = ?0.12; 95% CI:0.16, 0.07). We found highly significant andadditional effects of context for all theactivities (study: χ² = 732.63;p < 0.0001; R² = 0.30; active leisure:χ² = 753.40; p < 0.0001; R² = 0.31;and passive leisure: χ² = 555.86;p < 0.0001; R² = 0.24). Conclusions. TheFlow theory is a valuable model leading topredictions of optimal experience as well asactivation. However, the dynamics of activityengagement are more complex and related toconcurrent emotions and context. In the Dutchstudent culture, escaping boredom or compulsoryduties seems to drive individuals more thanpursuing flow.     

On the mathematical basis of the variance-mean power relationship

The mathematical basis of a widely-known variance-mean power relationship of ecological populations was examined. It is shown that the log variance (S ²)—log mean, (m) plot is virtually delimited by two lines logS ²=logn+2 logm and logS ²=logm, thus increasing the chance that a linear regression line can be successfully fitted, without a profoundly behavioural background. This makes difficult the task of interpreting a successful fit of the power law regression and its parameterb in a biologically meaningful manner. In comparison with the power law regression, Iwao'sm ^*-m regression is structurally less constrained, i.e. has a wider spatial region in which data points can scatter. This suggests that a comparison between the two methods in terms of how good a fit is achieved for a particular data set is largely meaningless, since the power law regression may inherently produce a better fit due to its constrained spatial entity. Furthermore, it could be argued that a successful fit in Iwao's method, when found, is less taxed with mathematical arterfacts and perhaps more clearly linked to some biological mechanisms underlying spatial dispersion of populations.     

Adult population parameters and life tables of an epilachnine beetle (Coleoptera: Coccinellidae) feeding on bitter cucumber in Sumatra

Summary The population dynamics of an epilachnine beetle, which is closely related toEpilachna sparsa Dieke (henceforth called “sp. C”) and feeds on bitter cucumberMomordica charantia, was studied by mark-recapture of adults and the construction of life tables. The study was repeated three times, i.e., March–May, July–September and October–December in 1982, in Padang, Sumatra, Indonesia. After the establishment of the host plants, adults of “sp. C” soon colonized, and each study period ended in the death of the plants due to defoliation by the larvae and adults. The estimated mean length of residence of adults ranged from 6–11 days, but this was probably much shorter than the actual longevity, because the adults were so active that they flew away, or dropped off the plants, when they were approached or slightly disturbed. Life tables indicated that egg mortality ranged from 17.8–53.9%, and a parasitic waspTetrastichus sp. B made up 41.1–64.2% of egg mortality. Two wasps,Tetrastichus sp. C andPediobius foveolatus killed 1.2–19.4% (7.6–100%)^* of 4th instars and only the latter species attacked the pupae, killing 24.6–59.1% (45.1–72.4%). Parasitism and starvation by overcrowding contributed most to the total mortality from egg to adult emergence, which ranged from 89.4–99.5%. “Sp. C” had a higher diversity and level of parasitism than the Japanese species,E. vigintioctopunctata. The high dispersal power of “sp. C”, coupled with the prolongedl _x−m_x schedules shown under laboratory conditions, was advantageous for exploiting the food plant which was available throughout the year, but was rather patchily distributed in space.     

Social components of metropolitan population densities

The decline of population density from the center of metropolitan areas can be expressed mathematically as: d _r = d _o e ^gr where d _r is the population density of a subarea at distance r from the center, d _o is the hypothetical density at the center, and g is the population-density gradient, empirically always negative. Expanding this exponential model permits examining systematically the relationship between distance from center and various components of population density—housing-unit density, vacant units, household size, and group-quarters population-and the change over time in these components. For the metropolitan areas of Columbus, Dayton, Hartford, Miami, and Syracuse in 1950 and 1960, housing-unit density decreased from the center more sharply than population density. Vacancies, which increased slightly at the center, were proportionately low in the stable middle zones but somewhat higher in the rapidly growing outer zones. While household size decreased around the center between 1950 and 1960, on the periphery it remained constant or increased slightly because of increased family size. During the same decade, the group-quarters population, relative to total population, shifted outward from the center to the periphery to a small extent.     

The Leverage of Demographic Dynamics on Carbon Dioxide Emissions: Does Age Structure Matter?

This article provides a methodological contribution to the study of the effect of changes in population age structure on carbon dioxide (CO₂) emissions. First, I propose a generalization of the IPAT equation to a multisector economy with an age-structured population and discuss the insights that can be obtained in the context of stable population theory. Second, I suggest a statistical model of household consumption as a function of household size and age structure to quantitatively evaluate the extent of economies of scale in consumption of energy-intensive goods, and to estimate age-specific profiles of consumption of energy-intensive goods and of CO₂ emissions. Third, I offer an illustration of the methodologies using data for the United States. The analysis shows that per-capita CO₂ emissions increase with age until the individual is in his or her 60s, and then emissions tend to decrease. Holding everything else constant, the expected change in U.S. population age distribution during the next four decades is likely to have a small, but noticeable, positive impact on CO₂ emissions.     

On the momentum of population growth

If age-specific birth rates drop immediately to the level of bare replacement the ultimate stationary number of a population will be given by (9): $$\left( {{\textstyle{{b\mathop e\limits^ \bullet {}_0} \over {r\mu }}}} \right)\left( {\frac{{R_0 - 1}}{{R_0 }}} \right)$$ multiplied by the present number, where b is the birth rate, r the rate of increase, \(\mathop e\limits^ \bullet _0 \) the expectation of life, and R ₀ the Net Reproduction Rate, all before the drop in fertility, and μ the mean age of childbearing afterwards. This expression is derived in the first place for females on the stable assumption; extension to both sexes is provided, and comparison with real populations shows the numerical error to be small where fertility has not yet started to drop. The result (9) tells how the lower limit of the ultimate population depends on parameters of the existing population, and for values typical of underdeveloped countries works out to about 1. 6. If a delay of 15 years occurs before the drop of the birth rate to replacement the population will multiply by over 2. 5 before attaining stationarity. The ultimate population actually reached will be higher insofar as death rates continue to improve. If stability cannot be assumed the ultimate stationary population is provided by the more general expression (7), which is still easier to calculate than a detailed projection.     

Survival Convergence and the Preceding Mortality Crossover for Two Population Subgroups

In this paper, we present and develop the argument that if the survival functions for two population subgroups converge in later life, a mortality crossover must precede the occurrence of this convergence. Specifically, two survival curves, S ₁(x) and S ₂(x), associated with two distinct population subgroups, G₁ and G₂, tend to converge before all members die out, as often observed and anticipated. This convergence leads to an increased mortality acceleration for the “advantaged” group, and eventually fosters the occurrence of a mortality crossover. We present a mathematical proof for this relationship and offer several explanations for the mechanisms involved in the process of survival convergence and the preceding mortality crossover. This new presentation demonstrates that mortality crossover is a highly observable demographic event given the trend of survival convergence in later life.     

Spatial pattern of pine wilt disease caused byBursaphelenchus xylophilus (Nematoda: Aphelenchoididae) within aPinus thunbergii stand

Summary To understand the mechanism of spread of pine wilt disease caused by the pinewood nematode,Bursaphelenchus xylophilus, which is vectored by a cerambycid,Monochamus alternatus, the spatial distribution of trees weakened by the nematode was examined within aPinus thunbergii stand from June to October for 4 years. The weakened trees were distributed in a clumped pattern in 1980 and 1981, at an early stage of infestation. In many cases, they showed a double-clumped pattern. The degree of aggregation was higher in June or July than after August. They were uniformly distributed in June or July 1982 and in June 1983 whereas they showed a double-clumped pattern after August. The trees were frequently weakened in June or July when they were near the trees weakened during the previous year. At quadrat sizes of more than 25 m², spatial overlapping was pronounced between trees weakened during June–July of the current year and those weakened in the previous year. The seasonal changes in spatial distribution of weakened trees were explained by the interaction amongM. alternatus, B. xylophilus andPinus trees.     

Dynamics of Mixed Coalitions Under Social Cohesion Constraints

ABSTRACT

Parameters for the birth and death diffusion life table model subject to downward jumps randomly occurring at a constant rate are estimated. The jump magnitudes have a beta distribution with support [0, l_x ], where l_x is the total number of survivors prior to the jump. The estimation method is maximum likelihood. The Cramer–Rao Lower bound and the asymptotic distribution for the MLE are derived. The model is applied to the U.S. men′s population from 1900 to 1999.