Amplitude Of Seasonal Fluctuations Research Articles

Birth Seasonality in Russia: Regional Features

In the article based on statistical methods the authors evaluateinterregional differences in seasonality of births in Russia and attempt toexplain the differences in the seasonality of the number of births in the regions of Russia. The relevance of these issues is explained by the need to monitor changes in demographic indicators following the implementation of national projects for the period up to the mid-2020s.The authors considered the most fundamental results of some domestic and foreign studies on this subject. Some hypotheses regarding the causes of the seasonality of births were tested using econometric tools (based on official birth statistics in the regions of the Russian Federation for the period 2006–2020).The statistically significant factors that form the amplitude of seasonal fluctuations were the degree of urbanization, income and the climate based on the OLS model. The amplitude of fluctuations in births decreased with an increase in the level of urbanization (growth in the share of the urban population) and the population of the region. An increase in January temperature increased the amplitude of birth fluctuations. The positive impact of income on the amplitude of the fluctuation was explained by the active planning of the timing of childbearing in high-income regions, but further research was needed. Nutritional characteristics were found to be statistically insignificant factors. The number of marriages took a special place in the formation of the seasonality of births. On the whole for the Russian Federation, based on time series models, a cointegration relationship between the number of marriages and the number of births was found. This relationship had begun to weaken over the past five years.

Specifics of long-term dynamics of terrestrial water storage detected using GRACE satellite in Belgorod region

GRACE monthly satellite data for the period from 2002 to 2016 were used to analyze the longterm dynamics of the terrestrial water storage in the Belgorod region of Russia. The correlation of satellite data with climatic water balance with a lag varying on the territory from 2 to 4 months was revealed. There was found a stable tendency to decrease in terrestrial water storage, and predominance of negative values on the territory of the Belgorod region since 2008. The minimum attains the lowest values in comparison with the whole studied period. However, seasonality of the changes is maintained throughout the entire analyzed time series. The frequency of changes in the terrestrial water storage throughout the entire area is not very clear: only the long-term maximum of the terrestrial water storage of the territory in 2006 is well expressed. Another, less pronounced local maximum was observed in 2013. Local long-term minima of the terrestrial water storage of the territory were in 2002, 2009 and 2015. There is a positive trend in the amplitude of seasonal fluctuations in the terrestrial water storage of the territory: the amplitude has been constantly increasing in recent years. The territory of the Belgorod region has negative long-term trend of terrestrial water storage with their rather large spatial variation. The angle of inclination of the trend decreases from north-west to south-east in the region. GRACE satellite data can serve as a fairly reliable detection indicator of the trend of terrestrial water storage in large areas.

RYE PRICE VARIABILITY IN POLAND BETWEEN 2010 AND 2018

In the paper, the range of rye price variability was determined and a decomposition of a time series of prices was carried out, distinguishing seasonal, cyclical and irregular fluctuations. The rye market is a market of a product produced seasonally but with a storage period longer than one season, which influences seasonal changes of prices, on which economic changes overlap. The research material consists of prices of rye in monthly graduation for the years 2010-2018, from the Integrated System of Agricultural Market Information. In the analyzed period, the nominal price of rye more than doubled from 327 PLN/t in January 2010 to 719 PLN/t in December 2018. The coefficient of variability of rye prices ranged from 4.0% to 27.2%. The decomposition of the time series of prices indicates seasonal, cyclical and irregular fluctuations. The amplitude of seasonal fluctuations was 14% on average, the highest prices were in June (105%) and the lowest in August (91%). Cyclical changes averaged 71.2% per year, seasonal changes 17.9% and irregular changes 10.9% of overall rye price variation. The production of rye is steadily falling both in the world and Poland.

The dependence of сircannual dynamics of blood pressure on seasonal fluctuations of meteorological and heliophysical factors. Meta-analysis

Many clinical studies have shown seasonal dynamics of blood pressure (BP), which most authors attribute to seasonal variations in air temperature. However, the fact that in the conditions of modern urban society the influence on the person of air temperature on the street is minimized, as well as the fact that the seasonal dynamics of BP is observed and in a tropical climate contradict this statement. It is known, that the length of the day, the atmospheric pressure, the relative humidity, geomagnetic activity are subject to seasonal dynamics. Studies have shown that fluctuations in these meteorological factors can cause change in blood pressure.Aim.To use meta-analysis of the results of studies, conducted in different climatic zones (from subarctic to tropical) and devoted to seasonal dynamics of BP, to determine which meteorological conditions most often corresponded to the annual maximum of BP and which to the annual minimum of BP.Material and methods. We selected 15 publications about seasonal dynamics of BP and seasonal exacerbations of arterial hypertension in 21 regions of the Northern Hemisphere of the Earth.Results.We confirmed that, in addition to air temperature, other factors are also subject to seasonal dynamics (atmospheric pressure, relative humidity, partial oxygen density in the air). No correlation was found between the amplitude of seasonal fluctuations in air temperature and the amplitude of seasonal fluctuations in BP. In addition, the amplitude of drcannual blood pressure fluctuations was greater in regions with a clear seasonal dynamics of the average monthly atmospheric pressure, compared with regions in which the this parameter does not have a clear seasonal dynamics. Also, in some regions, the seasonal maximum of BP coincided with high geomagnetic activity.Conclusion. According to the results, we concluded that seasonal fluctuations of BP are not a reaction of the cardiovascular system to seasonal dynamics of air temperature only. Most likely, seasonal fluctuations of BP are caused by changes in all meteorological factors that have seasonal dynamics.

Influence of Vegetation Growth on the Enhanced Seasonality of Atmospheric CO2

AbstractThe amplitude of seasonal fluctuations in concentrations of atmospheric CO2 has increased over recent decades. Model‐based studies suggest that this increase could be the result of enhanced vegetation growth during the growing season and ecosystem respiration in the nongrowing season. Here we investigated seasonal changes in vegetation growth derived from satellite‐based observations of the normalized difference vegetation index (NDVI) from 1982 to 2013. We found notable agreement between these observations and interannual variations of seasonality of global atmospheric CO2, suggesting that terrestrial vegetation growth is the dominant driver of the seasonality of the concentration of atmospheric CO2. Specifically, we found that the trend in seasonality of global vegetation growth was not continuous from 1982 to 2013 and that it increased substantially after 2001. In response, the trend of seasonality in the concentration of atmospheric CO2 stalled from 1982 to 2000 but increased from 2001 onward. This 2001 change in the growth seasonality trend was largely a result of decreased NDVI during spring and winter. CMIP5 models were unable to reproduce this observed seasonality. Our results showed the dominant role played by vegetation growth in determining atmospheric CO2 seasonality, highlighting the need to improve representation of vegetation growth in current terrestrial models to adequately indicate seasonal changes in the concentration of atmospheric CO2.

ДЕТЕРМІНАНТИ СПОЖИВЧОЇ ПОВЕДІНКИ: АНАЛІЗ ТРЕНДІВ І ВПЛИВ СЕЗОННОСТІ НА ФОРМУВАННЯ ПОПИТУ

The article is devoted to forecasting demand based on the study of consumer behavior and the factors that determine this behavior. Identifying trends and assessing the impact of seasonality on demand generation is the first challenge in describing typical consumer choice behavior. The consumption effect describes how Habitual buying behaviour is Identifying trends and the seasonality of demand. The solution to the current task was to a retrospective analysis of retail sales. Such issues how the assessment of seasonality, the identification of a general trend, the interdependence of sales of alternative fuels have been researched under this article. The trends noted to decrease in the volume of fuel consumption, differences in the structure of retail turnover, and the total demand for motor fuel should be viewed as behavioral changes in the end-users. While gasoline and gas are mainly sold through the filling stations, the share of diesel fuel sales through filling stations is less than a fifth of the total sales. Structural changes in the retail fuel implication are that the fuel market is being replaced by cheaper substitutes - gas. In this article, we consider that the analysis of seasonality is the initial stage of forecasting the dynamics of demand. Seasonality was estimated for each fuel and for the group of motor fuels as a whole, for retail sales and total fuel consumption. The results of the analysis showed that gasoline and gas sales are moderate seasonality. Diesel fuel is characterized by the greatest amplitude of seasonal fluctuations. The seasonal activity the consuming-industries of diesel fuel explains the dynamics of demand, which is typical for secondary demand goods. Studying seasonality to determine its effect on demand includes: applying a multiplicative seasonality model for analyzing time series of demand and building a model for time series components; calculation of seasonality indices based on the average annual consumption level for prepare data and forecasting dynamics; comparison of peaks of seasonality and the amplitude of non-seasonal demand fluctuations to assess the impact of market factors. The study did not confirm that the seasonality of fuel consumption determines the seasonality of prices; no correlation was found between price fluctuations and the seasonality factor.

The intrinsic growth rate as a predictor of population viability under climate warming

1. Lately, there has been interest in using the intrinsic growth rate (rm) to predict the effects of climate warming on ectotherm population viability. However, because rm is calculated using the Euler-Lotka equation, its reliability in predicting population persistence depends on whether ectotherm populations can achieve a stable age/stage distribution in thermally variable environments. Here, we investigate this issue using a mathematical framework that incorporates mechanistic descriptions of temperature effects on vital rates into a stage-structured population model that realistically captures the temperature-induced variability in developmental delays that characterize ectotherm life cycles. 2. We find that populations experiencing seasonal temperature variation converge to a stage distribution whose intra-annual pattern remains invariant across years. As a result, the mean annual per capita growth rate also remains constant between years. The key insight is the mechanism that allows populations converge to a stationary stage distribution. Temperature effects on the biochemical processes (e.g. enzyme kinetics, hormonal regulation) that underlie life-history traits (reproduction, development and mortality) exhibit well-defined thermodynamical properties (e.g. changes in entropy and enthalpy) that lead to predictable outcomes (e.g. reduction in reaction rates or hormonal action at temperature extremes). As a result, life-history traits exhibit a systematic and predictable response to seasonal temperature variation. This in turn leads to temporally predictable temperature responses of the stage distribution and the per capita growth rate. 3. When climate warming causes an increase in the mean annual temperature and/or the amplitude of seasonal fluctuations, the population model predicts the mean annual per capita growth rate to decline to zero within 100 years when warming is slow relative to the developmental period of the organism (0.03-0.05°C per year) and to become negative, causing population extinction, well before 100 years when warming is fast (e.g. 0.1°C per year). The Euler-Lotka equation predicts a slower decrease in rm when warming is slow and a longer persistence time when warming is fast, with the deviation between the two metrics increasing with increasing developmental period. These results suggest that predictions of ectotherm population viability based on rm may be valid only for species with short developmental delays, and even then, only over short time-scales and under slow warming regimes.

Individuality in modelling: a simplifying assumption too far?

When developing individual-based models (IBMs) of populations of rare or cryptic species, it may not be possible to gain precise measurements of individual traits such as age or body size for example. It may be necessary to assume that an individual is a member of a discrete class, rather than a unique entity in these cases. What will be the effect on the population dynamics predicted by an IBM of using discrete classes to represent individuals, rather than modelling individuals as unique entities? An IBM was developed to answer this question. Individuals were modelled as unique organisms in the full IBM, and the resultant population dynamics compared to a series of simplified models where individuals were treated as members of discrete classes. The number of classes varied from one to 32. The full IBM generated population time series that did not go extinct, but varied around an equilibrium level with a coefficient of variation of less than 15%. When the model was simplified to the point where all individuals were found in a single class, the simulated populations were found to be less variable, the opposite result to that predicted by general IBM theory. However, between these two extreme cases of full individual variability and no individual variability, complex interactions were found between the number of classes, background mortality rate and seasonality, which did not match the results of either extreme. Mean population size in the full IBM decreased as background mortality increased, and when the amplitude of seasonal fluctuations in food availability increased. This was due to the limited reproduction rate in comparison to unlimited mortality rate assumed in the model. As with the coefficient of variation in population size, the extreme cases of the full IBM and single class differed markedly from one another in mean size, with the scenarios in between these extremes showing complex interactions. The models presented in this paper demonstrate that making simplifying assumptions about the distinctiveness of individuals can affect the predicted population dynamics dramatically. If IBMs treat individuals as members of classes, rather than as unique organisms, predictions of population size and variability may be wrong.

Intertidal microalgal production and molluscan herbivory in relation to season and elevation on two rocky shores on the east coast of southern Africa

Microalgal production (ungrazed rock) and standing stock (grazed) were measured over a period of 15 months in the lower, middle and upper balanoid zones of two rocky snores in the Transkei region of southern Africa. The mean monthly production of chlorophyll a, which ranged from 0,3 to 2,0 μg·cm−2. was inversely correlated with tidal elevation. Highest rates of production (3,5–6,0 μg·cm−2) were recorded in winter at all tidal levels. The amplitude of seasonal fluctuations decreased with tidal height. At the middle and upper levels standing stock usually exceeded monthly production, whereas the opposite often occurred in the lower balanoid. No temporal or spatial trends in standing stock were evident. The intertidal distribution of grazing gastropods (excluding littorinids) correlated positively with primary production but showed no relationship with standing stock. No clear seasonal trends in grazer abundance were evident. The fact that standing stock exceeds monthly production suggests that grazing press...