A trend extraction method based on logistic functions and envelopes

A method of step characteristic trend extraction based on logistic functions and envelopes (LFEs) is proposed in this paper. Compared with the existing trend extraction methods, the LFE method can determine the starting position of the step trend using a logistic function and extract the local trend using upper and lower envelopes. This method enhances the extraction accuracy and reduces the computation time. To verify the effectiveness of the LFE method, a simulated signal with a step trend feature was compared with the five-spot triple smoothing method, wavelet transform method and empirical mode decomposition-based method. All of these methods were applied to a real shock signal. The results demonstrate that the LFE method can reliably and accurately extract the trends with step characteristics based on less prior knowledge. Moreover, the proposed technique is suitable for industrial online applications.

Worldwide clustering and infection cycles as universal features of multiscale stochastic processes in the SARS-CoV-2 pandemic

Predicting the evolution of the current epidemic depends significantly on understanding the nature of the underlying stochastic processes. To unravel the global features of these processes, we analyse the world data of SARS-CoV-2 infection events, scrutinising two eight-month periods associated with the epidemic's outbreak and initial immunisation phase. Based on the correlation-network mapping, K-means clustering, and multifractal time series analysis, our results reveal universal patterns, suggesting potential predominant drivers of the pandemic. More precisely, the Laplacian eigenvectors localisation has revealed robust communities of different countries and regions that then cluster according to similar shapes of infection fluctuations. Apart from quantitative measures, the immunisation phase differs significantly from the epidemic outbreak by the countries and regions constituting each cluster. While the similarity grouping possesses some regional components, the appearance of large clusters spanning different geographic locations is persevering. Furthermore, cyclic trends are characteristic of the identified clusters, dominating large temporal fluctuations of infection evolution, which are prominent in the immunisation phase. Meanwhile, persistent fluctuations around the local trend occur in intervals smaller than 14 days. These results provide a basis for further research into the interplay between biological and social factors as the primary cause of infection cycles and a better understanding of the impact of socio-economical and environmental factors at different phases of the pandemic.

Worldwide clustering and infection cycles as universal features of multiscale stochastic processes in the SARS-CoV-2 pandemic

Predicting the evolution of the current epidemic depends significantly on understanding the nature of the underlying stochastic processes. To unravel the global features of these processes, we analyse the world data of SARS-CoV-2 infection events, scrutinising two eight-month periods associated with the epidemic’s outbreak and initial immunisation phase. Based on the correlation-network mapping, K-means clustering, and multifractal time series analysis, our results reveal universal patterns, suggesting potential predominant drivers of the pandemic. More precisely, the Laplacian eigenvectors localisation has revealed robust communities of different countries and regions that then cluster according to similar shapes of infection fluctuations. Apart from quantitative measures, the immunisation phase differs significantly from the epidemic outbreak by the countries and regions constituting each cluster. While the similarity grouping possesses some regional components, the appearance of large clusters spanning different geographic locations is persevering. Furthermore, cyclic trends are characteristic of the identified clusters, dominating large temporal fluctuations of infection evolution, which are prominent in the immunisation phase. Meanwhile, persistent fluctuations around the local trend occur in intervals smaller than 14 days. These results provide a basis for further research into the interplay between biological and social factors as the primary cause of infection cycles and a better understanding of the impact of socio-economical and environmental factors at different phases of the pandemic.

Phenological response to temperature variability and orography in Central Italy

Even if the sensitivity of vegetation phenology to climate change has been accepted on global and continental scales, the correlation between global warming and phenotypic variability shows a modulated answer depending on altitude, latitude, and the local seasonal thermal trend. To connect global patterns of change with local effects, we investigated the impact of the observed signal of warming found in Central Italy on two different willow species, Salix acutifolia and Salix smithiana, growing in three phenological gardens of the International Phenological Gardens’ network (IPG) located in different orographic positions. The time series of temperatures and phenological data for the period 2005–2018 were analysed first to find trends over time in the three gardens and then to correlate the recent local warming and the change in the two species phenology. The results confirmed the correlation between phenological trends and local trend of temperatures. In particular: budburst showed a trend of advancement of 1.4 days/year on average in all three gardens; flowering showed a divergent pattern between the gardens of either advancement of 1.0 days/year on average or delay of 1.1 days/year on average; while senescence showed a delay reaching even 3.3 days/year, although significant in only two gardens for both species. These trends were found to be correlated mainly with the temperatures of the months preceding the occurrence of the phase, with a shift in terms of days of the year (DOY) of the two species. Our conclusion is that the observed warming in Central Italy played a key role in controlling the phenophases occurrences of the two willow species, and that the orographic forcing leads to the different shift in DOY of phenophases (from 5 to 20 days) due to the local thermal forcing of the three phenological gardens.

A probe into the Multifractal Behaviour of Total Ozone Time Series through Detrended Fluctuation Analysis

The present study reports a multifractal detrended fluctuation analysis of total ozone time series. Considering daily total ozone concentration (TOC) data ranging from 2015 to 2019, we have created a new profile by subtracting the trend. Subsequently we have divided the profile \({X}_{i}\) into non intersecting segments of equal time scale varying from 25 to 30. Fitting a second order polynomial, we have eliminated the local trend from each segment and thereafter we have computed the detrended variance. Finally the multifractal behaviour has been identified and the singularity spectra has helped us in obtaining the generalised Hurst exponent which in this case has come out to be greater than 0.5.

Estimation of sediment thickness by solving Poisson's equation with bedrock outcrops as boundary conditions

Sediment thickness and bedrock topography are vital for the terrestrial hydrosphere. In this study, we estimated sediment thickness by using information from digital elevation models, geological maps, and public databases. We discuss two different approaches: First, the horizontal distances to the nearest bedrock outcrop were used as a secondary function in kriging and cokriging. Second, we applied Poisson's equation to estimate the local trend of the sediment thickness where bedrock outcrops were used as boundary conditions. Differences between point observations and the parabolic surface from Poisson's equation were minimized by inverse modelling. Ordinary kriging was applied to the residuals. These two approaches were evaluated with data from the Øvre Eiker, Norway. Estimates derived from Poisson's equation gave the smallest mean absolute error, and larger soil depths were reproduced better if the local trend was included in the estimation procedure. An independent cross-validation was undertaken. The results showed the best accuracy and precision for kriging on the residuals from Poisson's equation. Solutions of Poisson's equation are sensitive to the boundary conditions, which in this case were locations of the bedrock outcrops. Bedrock outcrops are available for direct observations; hence, the quality of the estimates can be improved by updating input from high-resolution mapping.

From global to local scale: where is the best for conservation purpose?

Demographic analysis of plant populations represents an essential conservation tool allowing to identify the population trends both at global and at the local level. In this study, the population dynamics of Helianthemum caput-felis (Cistaceae) was investigated at the local level by monitoring six populations distributed in Sardinia, Balearic Islands and Ibero-Levantine coast (Alicante). Demographic data for each population were analysed by performing Integral Projection Models (IPMs). Our results showed that, although the local trend of the main basic demographic functions was similar, vital rates and demographic dynamics varied among populations indicating high variability. In fact, asymptotic growth rate in Spanish populations widely varied both between years and populations (some populations growth, decline or strongly decline), while Sardinian populations showed greater equilibrium or a slight increase. Also, the typical pattern of a long-lived species was not supported by the results at the local scale. These results indicated that different populations of the same species can present extremely different population dynamics and support the belief that, for conservation needs, local studies are more informative than global ones: the conservation status of H. caput-felis could notably vary at a small spatial scale and, accordingly, the conservation efforts must be planned at the population level and supported by local analysis.

Analyzing the Impacts of Serial Correlation and Shift on the Streamflow Variability within the Climate Regions of Contiguous United States

The spatiotemporal hydrologic variability over different regions of the contiguous United States poses the risk of droughts and floods. Understanding the historic variations in streamflow can help in accessing future hydrologic conditions. The current study investigates the historic changes in the streamflow within the climate regions of the continental United States. The streamflow records of 419 unimpaired streamflow stations were grouped into seven climate regions based on the National Climate Assessment, to evaluate the regional changes in both seasonal streamflow and yearly streamflow percentiles. The non-parametric Mann–Kendall test and Pettitt’s test were utilized to evaluate the streamflow variability as a gradual trend and abrupt shift, respectively. The Walker test was performed to test the global significance of the streamflow variability within each climate region based on local trend and shift significance of each streamflow station. The study also evaluated the presence of serial correlation in the streamflow records and its effects on both trend and shift within the climate regions of the contiguous United States for the first time. Maximum variability in terms of both trend and shift was observed for summer as compared to other seasons. Similarly, a greater number of stations showed streamflow variability for 5th and 50th percentile streamflow as compared to 95th and 100th percentile streamflow. It was also observed that serial correlation affected both trends and steps, while accounting for the lag-1 autocorrelation improved shift results. The results indicated that the streamflow variability has more likely occurred as shift as compared to the gradual trend. The outcomes of the current result detailing historic variability may help to envision future changes in streamflow. The current study may favor the water managers in developing future decisions to resolve the issues related to the streamflow variability in flood and drought-prone regions.

EVALUATION OF THE STATE OF GREEN PLANTS UNDER THE CONDITIONS OF URBANIZATION

The formation of an urban ecological environment is a local trend of the current time. It is necessary to solve the problems of city landscaping since, at the present stage, the deterioration of the state of green spaces and a decrease in the area that they occupy are observed. The article presents data on the state of tree vegetation in the largest park in Vologda (Vologda Region, Russia). According to the dendrometric assessment results in Mira Park, the number of drawback types in each tree species at a specific diameter of the trunk was revealed. It is worth noting that the most common types of drawbacks in linden trees in Mira Park are mechanical damage and frost cleft. The investigation was carried out based on the “Inventory Survey Procedure for Urban Plantations.” Most often, wood drawbacks in this species occur on the trunk diameters in the range from 40 to 52 cm. Based on the bioecological assessment performed in Mira Park, it can be stated that the highest percentage of good tree health status was found in pine – 67.3%, the highest percentage of satisfactory tree health status was found in elm – 35.7% and the highest percentage of poor tree health status was found in oak – 16.1%. According to the results of the investigation, it can be said that most of the tree plants are in good and satisfactory condition. The highest percentage of poor health status was found in tree species such as oak and poplar. There are such common flaws on tree plantations as mechanical damage, a frozen slot, and a curved trunk. The current situation in the biggest park in the city of Vologda is stable. However, to improve the systematic condition, it is necessary to hold some activities that should preserve and diversify the tree and shrub plantations, as well as help to solve existing problems.