Analysis of spatial association between two species based on the interspecies mean crowding

Summary and Conclusion The measurement of spatial association between two species is considered on the basis of interspecies mean crowding. Two indices of overlapping, γ andC _p, are derived as geometric and weighted arithmetic means of the same component ratios related to inter-and intraspecies mean crowdings. Both indices behave in a similar way, ranging from 1 when the distributions of two species are completely overlapped to 0 when they are completely exclusive with each other. The former is essentially identical with indices proposed byKuno (1968) andPianka (1973), and the latter is a modified form ofMorisita's (1959)C _σ index. Indices to measure the degree of spatial correlation between species, Ω andR _μ, are then derived for both kinds of overlapping indices, which vary from 1 in complete overlapping, through 0 in independent occurrence, to −1 in complete exclusion. Various kinds of interspecies association are analyzed using these indices and an extended form of the regression graph which provides a convenient way of indicating the spatial interrelation between two species as well as distribution patterns of respective species. The method presented in this paper may also be applicable to compare temporal distribution patterns between species, similarity between communities, etc. For such a wider application which includes continuous as well as discrete distributions, the interpretation of intra-and interspecies mean crowdings is not necessarily appropriate, and hence the concept of mean concentration with the symbols and for intraspecies relation and and for interspecies relation is suggested. This study was supported by Science Research Fund (No. 148041) from the Ministry of Education.     

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.     

An index of spatial distribution

Summary The index , which takes the value of −1 for a perfectly regular distribution, +1 for a highly aggregated distribution and 0 for the distribution implied by the theoretical varianceσ ², is proposed and a significance table provided.     

A distance measure of spatial pattern in a biological population

Summary Suppose thatn individuals locate independently and randomly on a segment of line of finite length (habitat). Let the theoretical and observed ranges of the sites of the individuals on the segment be μ _n-1 andr _n-1, respectively. Then, the degree of dispersion of the individual sites is measured by the ratio, T _n =n _n-1/μ _n-1, as follows: A random spatial pattern forI _r−1 =1 An aggregated spatial pattern for 0≤I _r <1 A uniform spatial pattern for (n+1)/(n−1)≥I _r >1. Another method was derived. Let the probability that an observed range is less thanr _n−1 beI _p , under the hypothesis of a Beta distribution. Then indicates A random spatial pattern forI _p =1/2 An aggregated spatial pattern forI _p <1/2 A uniform spatial pattern forI _p >1/2. The first index can be used for comparing populations having the same number of individuals, whereas the second one can be used for comparing populations with different numbers of individuals.     

Spatial pattern indices based on distances between individuals on a line-segment with finite length

Summary Let us consider a strip-wise habitat of line-segment, like a corridor, to simplify the subject mathematically, and assume that the length of the habitat is γ and there aren individuals. Here, we assume that the spatial pattern of the individuals is random if then distances from the left end of the habitat to each individual follow a uniform distribution on the strip. Under such an assumption, the variance of the distances between any two neighbors is represented by the formulanθ ²(n+1)⁻²(n+2)⁻¹ and the variance betweenn+1 distances betweenn individuals from the left end to the right end to the strip, is represented by the formulanθ ²(n+1)⁻²(n+2)⁻¹. These two kinds of variances can be used for determining (1) the spatial pattern of a population on the strip and (2) the spatial structure within the population, by comparison with the variances calculated from the data. Two examples cited from the literature, a cattle population on a pasture and an aphid population on a sycamore leaf, are presented.     

The Association Between Perceived Spirituality, Religiosity, and Life Satisfaction: The Mediating Role of Self-Rated Health

This study examined the mediating role of self-perceived health between perceived spirituality, religiosity, and life satisfaction among a stratified, random sample of college students, while controlling for gender. Although both models displayed excellent fit criteria, the perceived spirituality and life satisfaction model was fully mediated by self-perceived health χ² (n=459, 4) = 1.64, p=0.80, CFI =0.99, TLI=0.99), and the perceived religiosity and life satisfaction model was partially mediated by self-perceived health χ² (n=459, 10) = 22.29, p=0.01 CFI = 0.99, TLI = 0.99). Both models were equal for men and women. Students who describe themselves as spiritual (or religious) are likely to report greater self-perceived health and greater self-perceived health likely influences life satisfaction for both men and women. Results preliminarily support the contention that life satisfaction is related to differing reported health status, whether physical or mental, and that life satisfaction may be influenced by religiosity and spirituality engagement. Implications for colleges and universities are discussed.     

Urban Form,Heart Disease,and Geography: A Case Study in Composite Index Formation and Bayesian Spatial Modeling

Recent studies indicate a relationship between measures of urban form as applied to urban and suburban areas, and obesity, a risk factor for heart disease. Measures of urban form for exurban and rural areas are considerably scarce; such measures could prove useful in measuring relationships between urban form and both mortality and morbidity in such areas. In modeling area-level mortality, geographic relationships between counties warrant consideration because geographically adjacent areas tend to have more in common than areas farther from each other. We modify county-level indices of urban form found in the literature so that they can be applied to exurban and rural counties. We then use these indices in a Bayesian spatial model that accounts for spatial autocorrelation to determine if there is a relationship between such measures and cardiovascular disease mortality for white males age 35 and older for the time period 1999–2001. Issues related to the formation and usefulness of the indices, and issues related to the spatial model, are discussed. Maps of observed and expected relative risk of mortality are presented. Jimmie Givens retired from his service.     

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.     

Studies on the spatial distribution pattern of larvae of the mosquito,Anopheles sinensis, in rice fields

Summary The spatial distribution patterns of the population ofAnopheles sinensis larvae were studied in the rice field area in the suburb of Urawa city in Japan, during the summer seasons in 1973 and 1974. The distribution pattern of the larval population within the field, analysed by the m−m regression method, indicated that the basic component of larval distribution was not a group of individuals but a single individual and such components were distributed contagiously over the field. This basic pattern did not change significantly according to developmental stage, census date or field. Therefore, we could describe the distribution pattern of the population in a rice field by the single linear regression, x=0.021+1.339x(r²−0.912). Also, the relation for the whole population in the field area including the five fields could be shown by the linear regression, x=0.049+1.749x(r²−0.959). The value of α remained to be nearly equal to zero, but the value of β became larger than the value for the single-field relation. Such a change in distribution pattern seemed to reflect the greater heterogeneity in conditions among the fields than within individual field. Using the information on the distribution patterns mentioned above, some considerations were given on the sampling plans for mosquito larvae, including samplesize determination and application of sequential methods to estimate population size as well as to classify population level.     

Income Inequality Indices Interpreted as Measures of Relative Deprivation/Satisfaction

This paper considers different ways of making comparisons between individuals in terms of deprivation and/or satisfaction. This allows the Gini index, the Bonferroni index and the De Vergottini index to be interpreted as social deprivation measures as well as social satisfaction measures. The inequality measures that belong to the ?? family, or linear combinations of them, are obtained when using different weighting schemes to average the deprivation and satisfaction associated with each income level. Particularly, the generalised Gini indices (Yitzhaki, Int Econ Rev 24:617?C628 in 1983), the indices proposed by Aaberge (J Econ Inequal 5(3):305?C322, 2007) or those proposed by Imedio-Olmedo et al. (J Public Econ Theory 13(1):97?C124, 2011) can be used to evaluate social deprivation or social satisfaction in an income distribution.     

Evaluation of statistical precision and design of efficient sampling for the population estimation based on frequency of occurrence

Summary The binomial sampling to estimate population density of an organism based simply upon the frequency of its occurrence among sampled quadrats is a labour-saving technique which is potentially useful for small animals like insects and has actually been applied occasionally to studies of their populations. The present study provides a theoretical basis for this convenient technique, which makes it statistically reliable and tolerable for consistent use in intensive as well as preliminary population censuses. Firs, the magnitude of sampling error in relation to sample size is formulated mathematically for the estimate to be obtained by this indirect method of census, using either of the two popular models relating frequency of occurrence (p) to mean density (m), i.e. the negative binomial model,p=1−(1+m/k) ^−k, and the empirical model,p=1−exp(−am ^b). Then, the equations to calculate sample size and census cost that are necessary to attain a given desired level of precision in the estimation are derived for both models. A notable feature of the relationship of necessary sample size (or census cost) to mean density in the frequency method, in constrast to that in the ordinary census, is that it shows a concave curve which tends to rise sharply not only towards lower but also towards higher levels of density. These theoretical results make it also possible to design sequential estimation procedures based on this convenient census technique, which may enable us with the least necessary cost to get a series of population estimates with the desired precision level. Examples are presented to explain how to apply these programs to acutal censuses in the field.     

Host-dependent association and its implications on the relative abundance of blue alfalfa aphid and pea aphid (Homoptera: Aphididae) on alfalfa in Oklahoma

Summary Field populations of blue alfalfa aphid and pea aphid on alfalfa were sampled during 1985 and 1986 to determine the association of co-occurrence, interspecific interactions and comparative temporal variations in the spatial dispersion patterns of these species in Oklahoma. Relative abundance of these species is discussed in the light of above analyses.Cole's coefficient revealed a high degree of association between these species in terms of their occurrence on the same alfalfa stems in the field. Regression analyses indicated that the species populations tended to increase in concert on the same stems without evidence of competitive displacement. Spatial dispersion patterns of both species were highly aggregated at low population densities early in the season. Over time, both species tended to disperse and became less aggregated as numbers increased. It was concluded that magnitude of interspecific interactions between the blue alfalfa aphid and the pea aphid were not of a nature that they could be termed as competing species. On the contrary, a concept of an “ecospecies” is proposed for practical applications such as sampling plans and economic threshold determinations.     

What are the Differences between Happiness and Self-Esteem

The present study investigated theoretically and empirically derived similarities and differences between the constructs of enduring happiness and self-esteem. Participants (N = 621), retired employees ages 51–95, completed standardized measures of affect, personality, psychosocial characteristics, physical health, and demographics. The relations between each of the two target variables (happiness and self-esteem) and the full set of remaining variables were assessed through a series of successive statistical analyses: (1) simple Pearson’s correlations, (2) partial correlations, and (3) hierarchical regression analyses. The results revealed that happiness and self-esteem, while highly correlated (r = 0.58), presented unique patterns of relations with the other measured variables. The best predictors of happiness were the following: mood and temperamental traits (i.e., extraversion and neuroticism), social relationships (lack of loneliness and satisfaction with friendships), purpose in life, and global life satisfaction. By contrast, self-esteem was best predicted by dispositions related to agency and motivation (i.e., optimism and lack of hopelessness). Implications for the understanding of happiness and self-esteem are discussed.     

Investigating the Structural Validity of Ryff’s Psychological Well-Being Scales Across Two Samples

Ryff’s (1989b) Psychological Well-Being (PWB) scales measure six related constructs of human functioning. The present paper examined the validity of Ryff’s 6-factor PWB model, using data from a life events study (N = 401) and an organisational climate study (N = 679). Previous validation studies, using Confirmatory Factor Analysis (CFA), have identified alternative PWB models, but limitations include the use of shorter scale versions with items relating to a number of life domains within the same PWB factor, and failure to examine the influence of participants’ socio-demographic characteristics on PWB. In this study, Exploratory Factor Analysis (EFA) mostly found consistency in the PWB items and structure between the two studies whereby a 3-factor model delineated between items relating to Autonomy, Positive Relations and a super-ordinate factor comprising the other PWB factors. Using CFA, Goodness of Fit indices reached acceptable levels for the adjusted PWB model identified by the EFA, whilst differences between adjusted models of PWB previously identified in the literature were hardly evident. Post-hoc analysis by gender demonstrated socio-demographic effects on the structure and items that comprise PWB. Further development of PWB measures is needed to reflect its hierarchical and multi-dimensional nature. In the scales’ current form, the construct validation of the PWB factors will continue to be problematic and will fail to adequately evaluate the nature and impact of PWB.     

Confirmatory Factor Analysis of Scales Measuring Trust,and Control-Self-efficacy of Young Iranian Women

This study is among the first to assess Trust and Control-Self-efficacy scales as measures of cognitive social capital in transitional societies such as Iran. 391 Iranian young women aged between 18 and 35 years (M 27.3, SD 4.8) were recruited at ten sites in the city of Shiraz by cluster convenience sampling to participate in this cross-sectional study. The measures used included “Trust” and “Control-Self-efficacy” scales adapted from the British General Household Survey social capital survey. Confirmatory factor analysis with Structural Equation Modelling was used to assess the model adequacy. In addition, reliability and validity of the model was measured. After assessing all possible models to yield the best fit for the data, the “Trust” scale model represents a change of structure from three subscales to four subscales which provided a best fit with the data (χ² = 2.231, RMSEA = 0.056). While for “Control-Self-efficacy” scale with three subscales, five items were deleted in order to have a fit model (χ² = 2.128, RMSEA = 0.054). As a result, the collective evidence suggested that the instrument includes relevant items for its target population and can be a reliable and valid measure for the population of interest.

     

Nectar secretion pattern of the dish-shaped flower,Cayratia japonica (Vitaceae), and nectar utilization patterns by insect visitors

Summary We studied the relationship between the diurnal nectar secretion pattern of flowers ofCayratia japonica and insect visiting patterns to these flowers. Flower morphology ofC. japonica changed greatly for about 12 hours after flower-opening and the maximum duration of nectar secretion was 2 days. The nectar volume peaked at 11∶00 and 15∶00, and declined at night and at 13∶00 regardless of time elapsed after flower-opening. The nectar volume at the two peaks was, on average, 0.25 μl on bagged inflorescences and 0.1μl on unbagged inflorescences (both, sugar concentration=60%). The flower secreted nectar compensatory when the nectar was removed. This means that insects consume more nectar than the difference of nectar volume between bagged and unbagged flowers. Apis cerana is a primary visitor of this flower, and was the only species for which we confirmed pollen on the body, among many species of flower visiting insects to this flower.Apis cerana visited intensively at the two peaks of nectar secretion. Visits of the other insects were rather constant or intensive only when there was no nectar secretion. Thus flowers ofC. japonica with morphologically unprotected nectaries may increase likelihood that their nectar is used by certain pollinators, by controlling the nectar secretion time in day. In this study the pattern of nectar secretion allowedA. cerana maximum harvest of nectar. Contribution to the ecological and bioeconomoical studies of the pollinator community in Kyoto I.     

How three rocky shore snails coexist on a limited food resource

Summary Competition theory poses a major problem when several species coexist on what appears to be one resource. ThreeThais species living on the Pacific Northwest Coast provide an example: at many sites, all three depend primarily on one barnacle species. Growth rates of three species were measured for 3 years and these provide an indirect means to assess how these snails use their common food resource. Major temporal differences were observed:T. lamellosa grew 0–1 mm/mo during the spring and 2–3 mm/mo during the summer, whileT. emarginata andT. canaliculata grew 2–3 mm/mo during the spring and 0–1 mm/mo during the summer. However, all species are opportunists when food is available, and seasonal and interspecific differences disappeared when all three species were kept well fed together in the laboratory. Therefore, temporal differences arise from spatial segregation rather than from intrinsic differences in activity, and must arise because barnacle abundance patterns differe consistently from one area of the shore to another. Species-specific activity patterns lead each species to a food intake that is independent of the food supply on the shore as a whole and is also independent of food intake by the other two species. Where two snail species depend upon a single food species, their use of the food supply appears to make it function as two different resources. This resource use is possible because prey quality is markedly dependent on shore level.     

Horizontal and Vertical Inequality: Some Interconnections and Indicators

This note is concerned with presenting some simple indices of group-wise relative disadvantage in the distribution of income, in terms of the distance between the group’s share in total population and its share in total income. The group-wise indices are then aggregated into society-wide indices of inter-group disparity. Empirical illustrations of the note’s measurement concerns are provided, using data on the global distribution of income. The measures of horizontal inequality are shown to lead to corresponding measures of vertical inequality, in the special case in which the grouping resorted to is ‘individualistic’.     

δ15N examination of the Lindeman-Hutchinson-Peters theory of increasin omnivory with trophic height in aquatic foodwebs

The advent of stable nitrogen isotope analysis in ecological research has at last enabled precise identification of trophic position and omnivory due to the differential enrichment of¹⁵N over¹⁴N with progressive assimilation up the foodweb. I compiled literature data on δ¹⁵N values in freshwater and marine foodwebs to search for qeneral patterns in omnivory, specifically the supposition originally proposed by Lindeman (1942) and most recently advanced by Peters (1977), that omnivory should increase with trophic height or position. Omnivory, measured as average intraspecific variability in δ¹⁵N, was indeed found to increase with trophic height, such that species at the top of foodwebs were comprised of animals relying, on average, on energy originating from a mixture of different trophic categories.     

Inconstancy of Taylor'sb: Simulated sampling with different quadrat sizes and spatial distributions

Summary Taylor's power law,s ² =am ^b , provides a precise summary of the relationship between sample variance (s ² ) and sample mean (m) for many organisms. The coefficientb has been interpreted as an index of aggregation, with a characteristic value for a given species in a particular environment, and has been thought to be independent of the sample unit. Simulation studies were conducted that demonstrate that the value ofb may vary with the size of the sample unit in quadrat sampling, and this relationship, in turn, depends on the underlying spatial distribution of the population. For example, simulated populations with hierarchical aggregation on a large scale produced values ofb that increased with the size of the sample unit. In contrast, for a simulated population with randomly distributed clusters of individuals, the value ofb eventually decreased with increasing quadrat size, as sample counts became more uniform. A single value ofTaylor'sb, determined with a particular sample unit, provides neither a fixed index of aggregation nor a complete picture of a species' spatial distribution. Rather, it describes a consistent relationship between sample variance and sample mean over a range of densities, on a spatial scale related to the size of the sample unit. This relationship may reflect, but not uniquely define, density-dependent population and behavioral processes governing the spatial distribution of the organism. Interpretation ofTaylor'sb for a particular organism should be qualified by reference to the sample unit, and comparisons should not be made between cases in which different sample units were used. Whenever possible, a range of sample units should be used to provide information about the pattern of distribution of a population on various spatial scales.